Radiance Research AcademyInternational Journal of Current Research and Review2231-21960975-5241143EnglishN2022February1HealthcareDental Practice Adaptations in Response to COVID-19 Pandemic in Delhi-National Capital Region English0105Singh NeelamEnglish Gupta NatashaEnglish Singh ShradhaEnglish Sybil DeborahEnglishIntroduction: Today the world seems to have turned topsy turvy due to unwanted and unseen circumstances owing to the contagious SARS-COV-2 virus. Everybody’s life seems to have altered. Dental professionals were impacted too by this. In this study, our aim was to assess dental practice modifications made by dentists practicing in Delhi and nearby National Capital Regions. Aim: The study aimed to understand the changes that were adapted to routine practice in order to fight the deadly virus and not compromise the dental care that was required by the patients at the time of the pandemic. Methodology: This study was based on Google form objective pattern, validated questionnaire, and disseminated using various online communication means among 200 dentists practicing in Delhi. The survey included MCQ questions enquiring about the mode of the dental practice, patient flow per day, services provided, adherence to evolving infection control measures, effectiveness and usage of teledentistry, and duration of restricted services in response to a lockdown of 2020. Results: Overall, 105 dentists contributed to this survey. In this survey, we found that periodontal and esthetic services like implantology were most affected. The most rendered service was Oral Medicine during the lockdown owing to Covid 19. All the practicing dental professionals tried to implement all the guidelines given by WHO and IDA. Personal protective methods were preferred by 81% of professionals followed by sanitation methods. Various means to prevent infection were resorted to by most of the dentists while others maintained a time gap between the patients along with cross ventilation methods to stop the spread. Moreover, 52.4% of them preferred online patient scheduling and others have favored teleconsultation as most useful for catering patients during this pandemic. Conclusion: This study highlights the scope and usage of newer methods of dental consultation such as teledentistry or teleconsultations in the routine dental practice and especially during the hours of need like at the times of lockdown so that the dental concerns of all classes of people can be addressed too without increasing the risk of spread of the disease. English COVID-19, Dental Health Survey, Dental Services, Questionnaire, Preventive Guidelines, TeledentistryIntroduction Healthcare services have had to adapt to new systems in response to the covid-19 pandemic. A new normal had to be attained in adherence to the recommendations of WHO. Changes were seen in the patient triaging system, infection control measures, rotational staffing of hospitals, workflow patterns and modes of patient care and communication.1 A major factor in the prompt delivery of healthcare services was the speed at which medical practices adapted to the evolving information of the disease. Dental practice has been one of the most severely affected healthcare services during this pandemic. Oro-dental care was considered non-essential and routine dental practice had to be shut with the provision of only emergency services.2 Dental practitioners had to adapt to the emerging situation and bring about extreme changes to the way they catered to patients. Some of the recommended adaptations that required implementation were structural changes in the clinic and waiting area, improved and enhanced ventilation systems, evolving infection control measures, strict patient triaging, reduced number of patient appointments and teledentistry among others.3 The National capital region is one of the highly affected areas in this pandemic. As on 30th April 2021, total number of people affected by SARS- CoV-2 in Delhi was 11,49,333.4 Dentists in Delhi have had to face adverse conditions with restriction of dental services second time.5 This study aimed to assess dental practice adaptations/modifications by dentists practicing in Delhi at the time of first lockdown of the country.  The study evaluated adherence to recommendations of IDA and the changes brought about in individual dental practice during the pandemic to sustain the spread of the disease and provide emergency dental services. Methodology Study design and population A cross-sectional observational study was conducted online between January 1st to 25th 2021 (almost 25 days) among the (specialist and non-specialist) dentists practicing in Delhi-NCR region. Participants were asked to fill a survey form titled “Adaptations in dental practice during Covid 19 pandemic” which was created using an online platform of google forms. The form was circulated among dentists via various social media platforms like email, whatsapp, instagram and could be easily filled on a smartphone, tablet or a PC. It was kept concise and to the point so as to not take much time and not deviate the dentist from the topic. The questionnaire was sent to 200 dentists whose contact details were obtained from a district-wise list of dentists available on various websites. An effort was made to include roughly equal numbers of participants from each of the 8 districts of Delhi and surrounding NCR region (Figure1). Questionnaire A pretested self -administered questionnaire was set. The questionnaire consisted of two sections, the first section consisted of a detailed email that was self-explanatory for the purpose of the study and informed consent. The participants were assured that no personal information was required. The only inclusion criterion was that the dentist should have a private practice in Delhi. There were no incentives offered to dentists to participate in the study.  The second section consisted of 13 multiple choice questions with 5 close-ended and 7 open-ended questions. Each MCQ had a provision for the dentist to describe his/her opinion if the choices were not suitable. The first 5 questions were related to location, years of practice, mode and zone of dental practice and duration of restricted services in response to lockdown of 2020. Next 4 questions were regarding patient flow per day, services provided and adherence to evolving infection control measures. The rest were in relation to changes in the system of practice, effectiveness and use of teledentistry tools and willingness to implement teledentistry in routine practice. Pre-test was done with the collaborators to ensure proper working, submission and validity of the survey. The questions that were incomprehensive were modified and irrelevant sections were removed. All data was collected and stored in excel form and descriptive analysis of the data was carried out. Result 105 dentists responded to the questionnaire. District-wise distribution of participants and their containment zones is presented in Figure 2. Among the different modes of practice, 61.9% (n=65) of participants had a private dental practice, 21% (n=22) had a multispecialty practice, 18.1% (n=19) had a college-based practice while the rest practiced in a hospital-based setup. More than half of the participants, (56%, n= 59) were practicing dentistry for less than 5 years. It was seen that during COVID-19 lockdown in Delhi, the majority (41.9% n= 44) of dental professionals had shut down their services for 1 to 3 months. Moreover, 10.5% (n= 11) did not stop their services at all. (Graph 1). Out of all the total respondents, more than half (59.6% n= 62) of the dentists had examined less than 10 patients per day. Periodontics (58.1%, n=61) and Dental implantology (56.2%, n=59) were the most affected while Oral Medicine was the most offered services to the patients during Covid-19 pandemic (Table 1). Of all the guidelines given by WHO and IDA, 81% (n=85) of dental professionals have preferred personal protective methods. Additionally, 80% have followed various sanitization methods to prevent the spread of COVID-19 in their practice in Delhi. (Table 2). Contributors, resorted to different means to prevent the infection but more than half of them (81% n= 85) tried to maintain a time gap between the patients and 48.6% (n=51) had utilized cross ventilation to stop the spread or cross-infection in their clinical setups (Table 3). It was observed that 41% (n= 43) dentists were willing to use of tele-dentistry in their routine dental practice while, 52.4% (n= 55) of them preferred online patient scheduling and 45.7%(n=48) have favored teleconsultation as most useful for catering to patient during this pandemic (Table 4). Discussion Covid 19 has become a public health concern due to its high transmissibility. After the reporting of the first case in January 2020 in India, all the measures were adapted to control its spread. The transmission was so rapid that a lockdown of the entire nation was announced. This shutdown led to further increase in the bridge between dental healthcare services and population due to its proximity to patients and aerosol formation during the dental treatment.6 Oral health requires regular screening. Oral diseases like caries are very high prone with high carbohydrate intake and unfortunately, the lockdown led to increase in the consumption of convenience food, tasty treats and alcohol which further worsens the pre-existing dental condition.7 The pandemic urged dental professionals to look for and adapt newer means to continue providing dental healthcare services along with minimizing the risk of spread of virus. In this survey, we tried to develop a correlation of the impact of lockdown on dental professionals and on the patients who required dental services. This survey showed that about 10.5% of the total clinics did not stop functioning and continued to provide emergency dental care whereas all other clinics had to shut down services for 1 to 3 months. This survey revealed that 59.6% of dental practitioners felt the volume of patients that were seen per day was reduced to approximately 10. Unfortunately out of these 10 also only a few were given treatment and others were just screened. This showed the extent to which dental health was neglected and this could only worsen the pre-existing oral health condition affecting the overall health of the patient and also impacting the dental practitioners financially.8 This survey showed us that periodontics and implantology were the most affected services. Non-surgical periodontics had been worldwide impacted, probably due to the need of use of ultrasonic/piezoelectric devices generating aerosols.9 The esthetic dental implants is an elective procedure, the pandemic had a major impact on this due to it being postponed either by patients or by professionals to protect the health care providers and save the system from completely falling down. This was followed by endodontics, prosthodontics and restorative dentistry. The progression of dental pathology leads to pain, infection and sepsis. In early stages, if the pathological condition is diagnosed and intervened if needed the disease can either be reversed or arrested.10 The OSHA considered the Aerosol Generating Procedures as very high risk for known or suspected COVID 19 patients.11 The two procedures that are considered very high in aerosol generation are the one involving the high-speed handpiece with its water spray coolant and the ultrasonic scaler used to remove hard deposits on teeth.12 These both procedures are considered as an advancement in the field of dentistry as they are not just faster but reduce pain for the patient.13 Around 80% of the participants strongly agreed with the suggested measure of revised PPE protocols and others along with this resorted to thermal screening, hand sanitisation, decontamination procedures, good ventilation and fumigation of clinics. Whenever a need for AGPS (Aerosol generated procedures) occurred the participants preferred to go ahead with the RTPCR report. A new guideline was issued by MOHFW in May 2020 amidst the pandemic and lockdown announced in the country which divided the city in zones as per the contaminations. They also gave a guideline to modify the dental clinic into three phases. The preparatory phase, implementation and follow-up phase.14 All the dental treatments were divided among urgent procedures and emergency procedures as per age group (Geriatrics, adults, adolescents and children). The urgent treatments could only be undertaken after teleconsultation as prevention is the cornerstone of public health. Dental care paradigm was shifted to a more preventive approach.15 The only means as of now to fight this deadly virus is to follow the prevention protocols and be very careful while carrying out disinfection procedures.16 Tele dentistry was introduced when face-to-face consultation was not feasible. It is a developing practise for caring patients online and without physical contact.17 This method became the most suited means to address lack of access during the times of pandemic.18 The respondents of these studies had adopted teledentistry in various ways. Online patient scheduling and Tele Consultation were most commonly adopted means followed by E prescriptions. Tele dentistry has many advantages. It can be used for consultation, triage and understanding whether the dental concern requires urgent or emergency care. It helps in-patient counselling when the condition can be temporarily resolved at home and the treatment can be postponed. This decreased the burden on emergency departments that are functioning during the pandemic and also avoided overcrowding and helped maintain social distance. This can continue to provide dental education and the importance of oral health care and diet during lockdown.19 The other aspects of it are electronic health records, electronic referral systems, digitizing images, teleconsultations, and telediagnosis.20 Tele dentistry is a means which can bridge the gap between urban and rural areas of the country. 21 It proved to be the cheapest and fastest way of delivering specialised dental services during the lockdown.22 Though this method has proved to be very helpful during the tough times of pandemic there are some shortcomings associated with it. During this survey, 67% participants felt that the socio-economic condition of people really impacted the success of this method implementation in India followed by lack of funding, infrastructure and manpower. Other shortcomings which may be encountered are the patient not being satisfied and apprehensive with the advice as lack of face-to-face consultation may make him feel his main problem has not been addressed. This survey concluded by showing that 43 % of our participants were willing to use teledentistry as a routine practice whereas 30% were not sure. This study had its limitations. It had a limited sample size and was restricted to only Delhi NCR region only. Conclusion In these testing times teledentistry has been able to reach out to patients, resolve concerns associated with dental health, address dental conditions and categorize them into emergency and urgent by just a phone call or social media. It has helped minimise the spread of Covid 19 and also reduced the use of PPE which is needed in life saving procedures. The scope of teledentistry is vast and is yet to become an integral part of the dental health care technique but the pandemic has pushed the professionals to reach out and try this means. It can reshape the dynamics of the dental care system. The current condition worldwide can be an opportunity for tele-dentistry to be adapted on a larger scale and hence impart dental health to every sector of society. Acknowledgement I wholeheartedly thank all the authors for contributing in making this article a success. Declaration of interests: None Conflict of Interest: None Funding Resource: None       Auther’s contribution Concept and design –                   Dr Neelam Singh                                                       Dr Natasha Gupta Data Collection  and maintenance of record – Shradha Singh Critical analysis and editing  -                         Dr Sybil Deborah Total Number of references cited in main body of the manuscript-  21   Englishhttp://ijcrr.com/abstract.php?article_id=4332http://ijcrr.com/article_html.php?did=4332References Yaffee A, Peacock E, Seitz R, Hughes G, Haun P, Ross M et al. Preparedness, Adaptation, and Innovation: Approach to the COVID-19 Pandemic at a Decentralized, Quaternary Care Department of Emergency Medicine. West. J. Emerg. Med.2020;21(6):63-70. Benzian H, Beltrán-Aguilar E, Mathur M, Niederman R. Pandemic Considerations on Essential Oral Health Care. J. Dent. Res.. 2020;100(3):221-225. Meng L, Hua F, Bian Z. Coronavirus Disease 2019 (COVID-19): Emerging and Future Challenges for Dental and Oral Medicine. J. Dent. Res.. 2020;99(5):481-487. #IndiaFightsCorona COVID-19 [Internet]. MyGov.in. 2021 [cited 16 November 2021]. Available from: https://www.mygov.in/covid-19/ Delhi Govt Portal: Home [Internet]. Delhi.gov.in. 2021 [cited 16 November 2021]. Available from: https://www.delhi.gov.in/ Izzetti R, Nisi M, Gabriele M, Graziani F. COVID-19 Transmission in Dental Practice: Brief Review of Preventive Measures in Italy. J. Dent. Res.. 2020;99(9):1030-1038. Campagnaro R, Collet G, Andrade M, Salles J, Calvo Fracasso M, Scheffel D et al. COVID-19 pandemic and pediatric dentistry: Fear, eating habits and parent’s oral health perceptions. Children and Youth Services Review. 2020;118:105469. Coulthard P, Thomson P, Dave M, Coulthard F, Seoudi N, Hill M. The COVID-19 pandemic and dentistry: the clinical, legal and economic consequences - part 2: consequences of withholding dental care. Br. Dent. J.. 2020;229(12):801-805. Nibali L, Ide M, Ng D, Buontempo Z, Clayton Y, Asimakopoulou K. The perceived impact of Covid-19 on periodontal practice in the United Kingdom: A questionnaire study. J. Dent.. 2020;102:103481. Jepsen S, Blanco J, Buchalla W, Carvalho J, Dietrich T, Dörfer C et al. Prevention and control of dental caries and periodontal diseases at individual and population level: consensus report of group 3 of joint EFP/ORCA workshop on the boundaries between caries and periodontal diseases. J. Clin. Periodontol.. 2017;44:S85-S93. [Internet]. Acfd.ca. 2021 [cited 16 November 2021]. Available from: https://acfd.ca/wp-content/uploads/Members/COVID-19/RTPs/Non-Canada/National/US-OSHA-COVID-19%20Control%20and%20Prevention-Dentistry%20Workers%20&%20Employers-20-04-22.pdf Harrel S, Molinari J. Aerosols and splatter in dentistry. J Am Dent Assoc J AM DENT ASSOC. 2004;135(4):429-437. Chen Y, Chang H, Chiang Y, Lin C. Application and development of ultrasonics in dentistry. J. Formos. Med. Assoc. J FORMOS MED ASSOC. 2013;112(11):659-665. Mehta V, Gid A, Thakur R, Jangid M, Bagwe S, Mathur A. Dentist preparedness regarding novel coronavirus disease: An insight. 2021. Nimbulkar. Dental practice guidelines in the precariousness of covid-19: a review. Int J Cur Res Rev | Vol 12 • Issue 19 • October 2020 82 Ghai S. Teledentistry during COVID-19 pandemic. Diabetes & Metabolic Syndrome: Clinical Research & Reviews. 2020;14(5):933-935. Villa A, Sankar V, Shiboski C. Tele(oral)medicine: A new approach during the COVID?19 crisis. Oral Diseases. 2020;27(S3):744-745. Bhanushali P, Katge F, Deshpande S, Chimata V, Shetty S, Pradhan D. COVID-19: Changing Trends and Its Impact on the Future of Dentistry. Int. J. Dent.. 2020;2020:1-6. Khan S, Omar H. Teledentistry in Practice: Literature Review. Telemedicine and e-Health. 2013;19(7):565-567. Reddy K. Using teledentistry for providing specialist access to rural Indians. Indian J. Dent. Res.. 2011;22(2):189. Deshpande S, Patil D, Dhokar A, Bhanushali P, Katge F. Teledentistry: A Boon Amidst COVID-19 Lockdown—A Narrative Review. Int. J. Telemed. Appl.. 2021;2021(8859746).

Radiance Research AcademyInternational Journal of Current Research and Review2231-21960975-5241143EnglishN2022February1HealthcareStudies on Characterization and Optimization Parameters of Zinc Oxide Nanoparticles Synthesis     English0611Sirohi SandeepEnglish Chinta Koteswara RaoEnglish Andanamala Vijay RajeshEnglish Talapudi SruthiEnglish DV Surya PrakashEnglishEnglishZinc nitrate, Zinc oxide, Nanoparticle, Optimization, FTIR, UV-VIS Spectra INTRODUCTION Nanobiotechnology essentially combines biotechnology and nanotechnology to produce bio-synthetic, natural, and nanoscale-based goods.1 Nanomaterial have evolved as effective antimicrobial properties for killing microbes. Nanomaterials have a unique potential to kill germs, and researchers are currently focusing their efforts on microbial resistance to metal ions, antibiotics, and the formation of resistance stains.2 The recent development in porous and nanometric materials prepared by non-conventional methods has opened new vistas in the area of zinc oxide nanoparticles.3 Nano-sized innovations have risen over the previous decade due to advancements in sciences and technology. However, metal nanoparticles have occupied utmost consideration in recent years because of their exceptional properties and potential application in catalysis, plasmonics, optoelectronics, biological sensor, and pharmaceutical applications.4 Synthesis and characterization of nano-scale substances have been an important subject for studying in applied sciences. Metal oxide nanoparticles have been extensively utilized in the previous year’s.5 The synthesis of metal oxides has made it possible to utilize the properties of nanoparticles at ground level. Now a day’s zinc oxide nanoparticles have been given utmost importance because of their unique properties like UV filtration, antibacterial, high catalytic, antifungal, and photochemical action, etc. Inorganic materials, for instance, metal and metal oxides have been laid utmost importance over the previous decade because of their unique ability to understand tedious processes. Metal oxides, for instance, ZnO, TiO2, CaO, and MgO are of peculiar interest since they are very stable under unusual tedious process conditions, these metal oxides are also known as comfortable materials for the use of human beings and animals.6 The application of silver and zinc oxide nanoparticles has been seen as an important tool to stop infectious diseases because of their uncommon antimicrobial properties. The intrinsic property of different metal oxide nanoparticles is characterized its shape, size, composition, morphology, crystallinity, and various other properties.7 Zinc oxide nanoparticles are used as an effective antibacterial and antifungal agent when they are incorporated into various materials, such as cosmetics, paints, and textiles. Zinc oxide has been used in personal care products due to its bacteriostatic, fungistatic, and bactericidal properties. Zinc oxide, on the other hand, has unusual properties when reduced to nano-size compared to its bulk equivalent. Zinc oxide nanoparticles have unique features that allow them to interact with bacteria more effectively.8 As a result, less zinc oxide nanoparticles are needed to achieve the same or better fungal static and biostatic behavior. It is an excellent chemical additive for cotton fabrics in the textile sector due to its non-toxicity and skin compatibility.9 MATERIALS AND METHODS Chemicals Zinc nitrate, soluble starch, sodium hydroxide, MES buffer, Tris-HCl, Zinc nitrate hexahydrate. Synthesis of zinc oxide nanoparticles 1% soluble starch was prepared by dissolving 0.5gm in 500 ml of lukewarm distilled water. Zinc nitrate 14.874gm (0.1mol) was added in the above solution followed by constant stirring in magnetic stirrer for 60 minutes for the complete dissolution of zinc nitrate.10 0.2 M (300ml) NaoH was added dropwise under constant stirring. After 2hr of stirring the completed reaction solution was incubated overnight. The supernatant solution was then discarded very carefully and the rest of the solution was centrifuged 10 min for 10,000 rpm.11 The supernatant was discarded again. The nanoparticle obtained were washed twice using distilled water to remove by-products and excessive starch bound with nanoparticles. After that, it was dried overnight at 80°C. Zinc hydroxide was transformed to ZnO NPs during drying. Optimization of process parameter for zinc oxide nanoparticles synthesis a. Effect of metal ion concentration on zinc nanoparticles synthesis The concentration of Zinc nitrate hexahydrate is an important parameter. Different concentrations ranging from (0.1–0.8M) of zinc nitrate hexahydrate used as substrate and effect on the NP synthesis was ascertained.12 b. Effect of contact time on zinc nanoparticles synthesis Zinc nanoparticles synthesis was evaluated at different (30 min to 3 hour) contact time taking absorbance with UV–VIS spectroscopy.13 c. Effect of temperature on zinc nanoparticles synthesis Impact of temperature on zinc nanoparticles synthesis was evaluated at different temperature (25°C-95°C) of incubator, keeping other conditions are same. d. Effect of pH on zinc nanoparticles synthesis The production of zinc nanoparticles was optimized by varying the pH (5-9). The pH was adjusted to 5.5 –10.5 (MES buffer, 4mM for pH 5.5-6.5 and Tris-HCl, 4mM for pH 7.5-10.5) at an interval of pH 1.0. Characterization techniques for synthesized ZnO NPs a.UV-VIS Spectra Analysis of ZnO Nanoparticles Ultraviolet-Visible Spectroscopy technique is used for optical characterization of nanoparticles. Its absorption spectra is ranges from 300 to 700nm scale.14,15 V-530 ( JASCO) model of this spectrometer is used for this research work. (I am modified above the matter) b. Fourier Transform Infrared spectrometer (FTIR) It is identity of various varieties of chemical substances is viable by this technique.16 The spectroscopy merely dependent on the records that particles soak up particular frequencies which might be feature of their shape named as resonant frequencies. RESULTS AND DISCUSSION Chemical Synthesis of Zinc oxide nanoparticles Wet chemical method as described by Taguchi was used for the fabrication of the zinc oxide nanoparticles using sodium hydroxides, zinc nitrate as precursors while starch acted as stabilizing agent in reaction Figure-1A. After synthesis powder form of zinc oxide nanoparticles seems to be white in colour as seen in Figure-1B. The same method was applied by Vigneshwaran et al. in 2006 and they found small crystals of zinc oxide nanoparticles white in colour. Reddy et al., 2006 also used top-down approach for the quick biosynthesis of nanoparticles. Liqianga et al. (2006) found the photoluminescence spectrum of zinc oxide nanocrystals with an excitation wavelength at 325nm with the same method.17 Chakarborti et al. (2010) used sol-gel injection for the synthesis of zinc oxide nanoparticles inside a porous silica matrix they successfully synthesized Zn2SiO4 crystals using similar approach.   ZnO NPs synthesis. (B) Synthesized ZnO nanoparticles in Eppendorf after purification Optimization of ZnO NPs synthesis Optimization of ZnO NPs was done during the present study with respect to particle size distribution. Wet chemical method was used for optimal conditions. Following steps are involved in the optimization of ZnO NPs. Effect of metal ion concentrations on zinc nanoparticles synthesis The impact of different concentrations (0.1M to 0.8M) of zinc nitrate for the formation of ZnO nanoparticles was optically monitored by UV-Vis spectroscopy and FTIR. It is clearly seen from figure-3 that absorption spectrum of ZnO NPs was in the range of 380 - 420 nm at different concentration of zinc nitrate.18 The optimum concentration for the synthesis of ZnO NPs was exhibited at 0.3M concentration resulting in sharpest peak among all concentrations at 390 nm (figure-7), which stored in anhydrous form in eppendorf (figure-2). Increasing concentrations of zinc nitrate were used in optimization of metal ion concentration. It clearly seen from the present study that concentration of zinc nitrate from 0.1M to 0.3M exhibited upward formation of peaks however at concentration 0.3M the peak was highest subsequently concentration of zinc nitrate from 0.4M to 0.8M, there was hump formation in the peaks indicating poor absorption of zinc nitrate.19 Hence, it was concluded on the basis of present results that increasing concentration of metal ions beyond the limit leads to decreasing the formation of ZnO NPs. Similar observations for the optimization of nanoparticles with different metal ion concentrations were also reported by Kumar et al. (2013). For the better control of synthesis, optimization and morphological characteristics Bhattacharjee et al. (2011) also revealed similar results. Jamdagni et al. (2016) revealed that when they increased the concentration of flower extract from 0.25ml to 1ml, the maximum absorption was reported at 1ml of flower extract in 50ml of zinc acetate. If we alter this volume either increase or decrease then simultaneously decrease in the absorption values, their results also corroborated the present findings.           . Effect of contact time on zinc nanoparticles synthesis           The contact or incubation time is one of the influencing factor for the synthesis of nanoparticles. The obtained results of UV- Vis spectra are depicted in figure-4a and 4b. For contact hours, a spectrum up to 3 hours was recorded. The sharpest absorption peak was observed in 393 nm (after 2 hr) which remain stable after 3 hr.20 While in 0.5 and 1 hr no peak were observed. Chan (2008) found the effect of contact time on the synthesis of nanoparticles, their findings were also similar to our findings. They further also revealed that sharpness and enhancement of UV-Vis absorption peaks with an increase in incubation period. However, in the present work it is optimized at 2 hour duration and stable up to several hours as illustrated in figure-4b.   Effect of temperature on zinc nanoparticles synthesis        Temperature is another most important physical factor for the synthesis of ZnO NPs, UV-Vis spectroscopy signify the role of temperature during nanoparticles synthesis.21 The optimization of the suitable temperature for the reduction of nanoparticles in the reaction process was optimized between 250C to 950C however no spectra were observed between 250C to 450C. Spectra between 550C to 650C are visualized similar pattern with low and extremely wide absorption peak, while absorption peak increased considerable on 750C as depicted in figure- 5a. A sharp and stable peak was observed at 850C with the absorption 390 nm figure- 5b. No prominent peak was observed at 950C. No major peak shifted during optimization process in the synthesis of ZnO NPs.22 However it was noticed that high temperature (850C) was most favourable for ZnO NPs synthesis. Rajendran et al. (2010) found different particle size of ZnO, depending on the range of pH and Temperature. Dissipation of zinc ion in nuclei was increased with higher temperature due to enhanced rate of reduction. Shaymurat et al. (2011) also worked on the ZnO NPs with different ranges of temperature and reported similar findings. Effect of pH on zinc nanoparticles synthesis pH has an unavoidable factor for the nanoparticles synthesis. The effect of pH in the synthesis of ZnO NPs was also estimated by using UV-Vis spectroscopy.23 The production of ZnO nanoparticles were mostly determined by the pH of the reaction media. The present results are depicted by figure – 9a and 10b. It was also observed during the present research work, that there was no absorption peak at 4 pH, However at pH 7 and 8 absorption band were also formed broadening band patterns indicates synthesis of large size of nanoparticles while highest absorption and peak formation occurred at pH 9 which suggest the optimum pH for the synthesis of ZnO NPs.24 Jamdagni et al. (2016) discussed about the two major governing factors i.e. pH and temperature in biological synthesis of ZnO nanoparticles. The absorbance values increased when the pH level was raised from 9 to 12. At pH 12 and 13 characteristic absorption peak was recorded while at pH 9 no absorption peak i.e. straight line was reported, However, at pH 12 the sharpness and absorbance both were recorded better that is called as optimized pH. Characterization techniques of ZnO nanoparticles  UV-VIS Spectra Analysis of ZnO Nanoparticles The absorption spectra of chemically synthesized ZnO NPs prepared with the help of soluble starch are depicted in Figure-7a. The spectrum of these nanoparticles were in the range of 390-420 nm with absorption maxima at 392 nm in the figure. Similar results were also presented in the study carried out by Vigneswaran et al. (2006). FTIR analysis of ZnO Nanoparticles FTIR spectroscopy analyzed Zn oxide (control) and synthesized ZnO nanoparticles which were obtained after optimization through FTIR.25 Various peaks were found at 3169,3119, 2939, 2429, 2339, 2074, 1919, 1764, 1634, 1509, 1384, 1154, 1104, 1019, 934 and 834 cm-1 in Zn oxide samples as control. The IR spectrum of Zn oxide showed sharp absorption bands at 3169 and 3119 cm-1 that may be due to O-H bond stretching vibrations N-H stretch. Peaks at 2429 to 1919 correspondence to stretching vibrations of C ≡ C stretch of alkynes. The 1764 to 1509 peaks result from the stretching bands of function group C = O. The peak of 1384 to 1104 results from aromatic amines and the peak 1019 and 934 indicates the C-N stretching (Rastogi and Arunachalam, 2011). The peaks of below 834 and above 614 indicate alkanes and C-H band. Further, the FTIR spectra of ZnO NPs represents peaks at 3444, 3384, 3342, 3288, 3225, 3201, 2973, 2946, 2898, 2745, 2343, 1767, 1638,1590, 1591, 1497, 1383, 1236, 1152, 1077, 1020, 924, 831, 759 and 738 cm-1 due to symmetric stretching vibration of surface bounded zinc oxide molecules. Therefore, on the basis of these results it is concluded that Zn oxide worked as both reducing as well as capping agents in ZnO NPs formation. Morley et al. (2007) also found similar observations with respect to the bands at 1390 and 1155 can be attributed to the C-N stretching vibrations of the aliphatic and aromatic amines. Here FTIR spectrogram of ZnO NPs at 0.8 M concentration of Zinc nitrate was shown in figure 7b. CONCLUSION Metal nanoparticles have been extensively used in the recent past. Inorganic materials like, metal and metal oxides have gained a lot of interest in the recent years due to their properties which help them withstand adverse process conditions. Now a day’s zinc oxide nanoparticles are considered as important material because of their number of unique properties like antibacterial, antifungal, UV filtration property, high catalytic and photochemical activity. Zinc oxide nanoparticles are useful as effective antibacterial and antifungal agents. In the current study, nanoparticles of zinc oxide were synthesized by wet chemical process with the help of precursors zinc nitrate and sodium hydroxide the properties of starch were used as a stabilizing material. The powder form of zinc oxide nanoparticles appeared white in color was purified through centrifugation process and was stored in eppendorf tube at 40C for further work. Synthesis conditions of zinc oxide nanoparticles were optimized using different parameters, are metal ion concentrations (0.1M to 0.8M), contact time variations (0.5hr to 4hr), effect of pH (4 to 9), and effect of temperatures (55 to 850C). The resultant Zno NPs powder was characterized by UV-Vis spectroscopy and FTIR analysis. ACKNOWLEDGEMENT The authors would like to thanks the Department of Biotechnology, Meerut Institute of Engineering and Technology, Meerut, Uttar Pradesh. Financial Support: Meerut Institute of Engineering and Technology, Meerut provide the financial support for this research work. Conflict of interest: None declared Authors’ Contribution: Dr.Sandeep Sirohi and Dr.Vijay Rajesh are conceptualized in this research while Dr. Surya Prakash and Dr. Koteswar rao are supervised the study. Englishhttp://ijcrr.com/abstract.php?article_id=4333http://ijcrr.com/article_html.php?did=4333 Keerthika E, Ishwarya K, Jayashree L, Maripandian S, Nivetha, Irivichetty Sai Chandana. Potential Antibacterial Activity of Green Synthesized Copper Nanoparticles and its Characterization. Int J Cur Res & Rev. 2021; 13(19): 27-32. Suganya S, Ahila SC, MuthuKumar B, Vasantha Kumar M. Evaluation of Impact Strength of Silver Nano-Particles Reinforced Heat-Activated Polymethylmethacrylate (Pmma) Resin at Various Proportions. Int J Cur Res & Rev. 2021, 13(13): 13-17. Mishra PK, Mishra H, Ekielski A, Talegaonkar S, Vaidya B. Zinc oxide nanoparticles: a promising nanomaterial for biomedical applications. Drug Discov. 2017; 12: 1825-1834. Lopez C, Paez JR. Synthesis and characterization of ZnO nanoparticles: Effect of solvent and antifungal capacity of NPs obtained in ethylene glycol. Appl Phys A, 2017; 123(12): 748-752. Tyagi PK, Mishra M, Khan N, Tyagi S, Sirohi S. Toxicological study of silver nanoparticles on gut microbial community probiotic. Env Nano Monit Manag. 2016, 5:36-43. Paul S, Ban KD. Synthesis, Characterization and the Application of ZnO Nanoparticles in Biotechnology. Int J Adv Che  Engg Bio Sci, 2014; 1(1): 1-5. Arora AK, Devi S, Jaswal VS, Singh J, Kinger M, Gupta VD. Synthesis and Characterization of ZnO nanoparticles. Oriental J Chem, 2014;30(4): 1671- 1679. Talam S, Rao KS, Gunnam N. Synthesis, Characterization, and Spectroscopic Properties of ZnO Nanoparticles. Int Sch Res Notice Nano. 2012; 1: 1-6. Xie Y, He Y, Irwin PL, Jin T, Shi X. Antibacterial activity and mechanism of action of zinc oxide nanoparticles against    Campylobacter jejuni. App and Env Mic. 2011; 77: 2325-2331. Xu M, Fujita D, Kajiwara S, Minowa T, Li X, Takemura T, Iwai H, Hanagata N. Contribution of physicochemical characteristics of nano-oxides to cytotoxicity. Biomaterials. 2010; 31: 8022-8031. Rai M, Yadav A, Gade A. Silver nanoparticles as a new generation of antimicrobials, Biot Adv. 2009; 27: 76-83. Wang H, Xie C, Zeng D. Controlled growth of ZnO by adding H2O. J of Cry Gro. 2005; 277(1–4): 372-377. Vigneshwaran N, Nachane RP, Balasubramanya RH, Varadarajan PV. A novel one-pot green synthesis of stable silver nanoparticles using soluble starch. J Carb Res. 2006; 341(12): 12-18. Reddy VR. Gold nanoparticles: synthesis and applications. Synlett. 2006; 11:1791-1792. Liqianga J, Yichuna Q, Baiqia W, Shudana L, Baojianga J, Libina Y, Weia F, Honggang F, Jiazhong S. Review of photoluminescence performance of nano-sized semiconductor materials and its relationships with photocatalytic activity. Sol Ene Mat Sol Cells. 2006; 90:1773-1787. Chakarborti S, Chatterjee T, Joshi P, Poddar A, Bhattacharyya B, Singh SP, Gupta V, Chakarborti P. Structure and Activity of Lysozyme on Binding to ZnO Nanoparticles. J Langmuir. 2010; 26 (5): 3506–3513. Kumar SS, Venkateswarlu P, Rao VR, Rao GN. Synthesis, characterization and optical properties of zinc oxide nanoparticles. Int Nano Letters. 2013; 3(30): 1- 5. Bhattacharjee CR, Purkayastha DD, Nath A. Homogeneous Chemical Precipitation Route to ZnO Nanosphericals. Assam Uni J Sci & Tech. 2011; 7(2):122-127. Jamdagni P, Khatri P, Rana JS. Green synthesis of zinc oxide nanoparticles using flower extract of Nyctanthes arbour-tristis and their antifungal activity. J Kin Sau Uni Sci. 2016; 30(2): 168-175. Chan H, Tsai MH. Synthesis and Characterization of ZnO Nanoparticles Having Prism Shape by A Novel Gas Condensation Process. Rev of Adv Mat Sci. 2008; 18:734-743. Rajendran R, Balakumar C, Ahammed HAM, Jayakumar S, Vaideki K, Rajesh EM. Use of zinc oxide nanoparticles for production of antimicrobial textiles. Int J of Engg Sci & Tech. 2010; 2(1): 202-208. Shaymurat T, J Gu, C Xu, Z Yang, Q Zhao, Y Liu, Y Liu. Phytotoxic and genotoxic effects of ZnO nanoparticles on garlic (Allium sativum L.): A morphological sudy. J Nano tox, 2011; 6(3): 241-248.  Keerthana S, Kumar A. Potential risks and benefits of zinc oxide nanoparticles: a systematic review. J cri rev in tox. 2020; 50:47-71. Rastogi I, Arunachalam J. Sunlight-based irradiation strategy for rapid green synthesis of highly stable silver nanoparticles using aqueous garlic (Allium sativum) extract and their antibacterial potential. J Mat Chem & Phy. 2011; 129: 558- 563. Morley KS, Webb PB, Tokareva NV, Krasnov AP, Popov VK, Zhang J, Roberts CJ, Howdle SM. Synthesis and characterization of advanced UHMWPE/ sliver nanocomposites for biomedical applications. Eur Poly J. 2007; 43: 307- 314.

Radiance Research AcademyInternational Journal of Current Research and Review2231-21960975-5241143EnglishN2022February1HealthcareActive & Intelligent Packaging Technologies: An Aspect of Food Safety Management     English1218Saikat MazumderEnglish Shalini ChandaEnglish Amiya BhaumikEnglishEnglishActive packaging, Advanced packaging, Food safety, Food waste, Intelligent packaging, SensorIntroduction In the early times, humans used glass and wood containers for food packaging. Packaging as a term evolved from early mankind’s basic need to store and transfer their food from place to place. Although there is no record of when the very first packaging materials were used, researchers believed that leaves, animal skins, nuts, etc. were being used to store and transport goods during the nomadic era.1 Packaging keeps the product safe from the external environment and also performs four basic purposes such as protection, communication, convenience, and containment(fig-1).2, Packaging ensures the item against the outside environment communicates with the customer via written texts or graphics, making the handling better and effective with different types of containers.4 The expectations of consumers are continually changing. When new and revolutionary products emerge, so do the packaging techniques that accompany them. There have been several different ways to package goods in human history, each of which was an advancement in its own time. The emphasis on the customer has remained consistent in the evolution of product packaging.5 Smart packaging is still in its early stages of growth, but it has enormous potential.6 The advancement of smart packaging has progressed very rapidly. Just a couple of years back, smart packaging used to mean a label on a package with a tracking number, or even better, a barcode readable by a laser scanner. The Quick Response (QR) Code has become extremely common in recent years.7 This is an advancement in packaging that reflects the packaging industry's ability to adapt to customers' constantly changing expectations and concerns.5,7 The popularity of Active Packaging, over the years, has signaled a significant change in packaging systems shifting from passive to active. Previously, primary packaging materials were thought to be "passive," meaning they only served as an inert shield to ensure the item against oxygen and dampness. Active packaging was first implemented several years ago as powerful packaging technology, capable of performing all packaging functions.2 Smart packaging is one that includes both intelligent packaging as well as active packaging. Intelligent Packaging communicates with the consumer based on the information recorded.8 Literature Review In recent times, consumers seek food that is both safe and convenient, as well as the food package should be made of recyclable or reused materials. Traditional packaging is becoming less capable of meeting all these demands, as a result of which consumers are switching to more functional packaging technology. Smart packaging is such a transformation of packaging technologies which is a combination of both active and intelligent packaging. As the consumer need is continuously changing so is the packaging technology to feed the world’s growing population a safe and healthy food that will be more natural and less processed for its preservation and handling. Active packaging increases food protection as well as its shelf lifeby adding antimicrobial emitters or oxygen scavengers directly in food packaging film or as sachets in food packets. In the case of intelligent packaging, it functions by interacting with the food product and providing information like ripeness or indicating the freshness of the food.9 These new emerging technologies can also help upgrade the traceability of any food product through its packaging. Numerous studies are continuing forward in today’s world, but they are yet waiting for it to be combined into innovative solutions. The packaging technologies should be so implemented that its customer can continuously monitor the food quality until they are consumed as well as food degradation should be reduced when preserved. 10 The world of smart packaging is significantly growing and advancing in research. This period is characterized by a significant increase in the number of projects and a probable approach to overcome food preservation problems with the new technologies and improved frameworks.11 Problem statement The food service sector accounts for food wastage around 30% of all food produced worldwide.12 This waste is produced from the food sector which includes below standard packaging or improper packaging that will not stand during transportation and distribution, specifically the perishable foods making it more vulnerable to lose. According to FAO, an absence of optimized packaging is one of the main factors responsible for food loss or waste, especially in developing countries.13 New solutions to food packaging technology can be a promising way to fight against food wastage and to feed the increasing population. Methodology for advanced Packaging Technologies to Reduce Food Waste Active Packaging Active Packaging is a concept that is characterized as a mode of packaging in which the package, the product, and the environment interact to extend shelf life, improve protection, and enhance sensory properties while preserving the quality of the product.14 This includes the packaging of foods with materials that provide improved functionality, such as antimicrobial, antioxidant, or bio-catalytic functions. This can be accomplished by incorporating active compounds into the packaging materials or by the application surface alteration with the required functionality.15, 16, 17 This packaging utilizes technology that is intended to discharge or assimilate compounds from the food or the headspace of food packaging, which extends the shelf life of products by slowing down the degrading reactions of lipid oxidation, microbial development, moisture loss and benefit more effectively than conventional food packaging(fig-2).18 There are different types of Active Packaging available, but generally, they are categorized into three types i.e. scavengers, emitters, and adoptors. Scavengers Package scavengers have been in use for around many years in the shape of separate packets or sachets but presently this technology is integrated inside the packaging material. This integrated approach decreases the overall costs and makes it easily approachable for both the manufacturer and the consumer.18 Oxygen scavengers Oxygen scavengers or oxygen absorbers are included in packaging so it reduces the oxygen level within the package. They are utilized to keep up product quality and to extend shelf life.20 There are numerous types of oxygen absorbers available for a wide range of applications.21, 22 The most commonly found substrate is iron followed by ascorbic acid and then other substances. These are incorporated into polymers as light-sensitive dyes.18 The shelf-life and nutritional value decrease with the increase in oxygen amount in the food packet as the oxygen react with vulnerable foods in the package, accelerating the degradation of numerous food products, rancidity in foods with high oil content, and also promoting microbial growth.23 The oxygen absorber scavenges this excess oxygen to slow down the oxidative reactions and also inhibits the microbial growth in the food package.18 Beer-cap seal contains oxygen-absorbing liners on the underside of Carlsberg FreshCap - ZerO2. This removes the headspace oxygen and extends the shelf life of beer by 15%.18, 24 Ethylene Scavenger An ethylene scavenger can be a small sachet containing a suitable scavenging agent or an ethylene scavenger incorporated directly into the packaging material and the material should be greatly permeable to ethylene gases for its functioning.25 This can be further sub-divided into scavengers and absorbers, scavengers absorb water by chemical reaction whereas, absorbers absorb the ethylene from the surrounding atmosphere.26 They increase the shelf life by slowing the aging or ripening process and senescence.18 Fruit Brite by Hazel Technologies released 1-MCP (1-methyl cyclopropane)27 to diffuse ethylene blockers which extends the shelf life and the quality of the product 18, 27. Moisture scavengers Moisture scavengers regulate moisture in the headspace of any packaging and absorb the excess liquid weeping from a food product, thus increasing the shelf life of the product. High-capacity hydro-gels would be more effective in this case.18MoistCatch film by Kyodo Printing is a moisture scavenging film that is flexible and can be molded to any form.18, 28 Emitters Emitters reduce the effect of microbial growth and activity, oxidative reactions, and even uncontrolled ripening in fruits. CO2, antimicrobial, antioxidants, etc. acts as emitters that enhance the shelf life of products.18, 29 Antioxidant Oxidation in fats and oils produces off-flavor as well as reduces the shelf life and causes spoilage in food. This can be avoided by incorporating antioxidants in food with higher fat content. They neutralize the action of harmful free radicals. Common antioxidants found in foods are Vitamin C, Vitamin E, citric acid, etc. 29, 30 Antimicrobial Emitters Antimicrobial emitters would include antimicrobial macromolecules having film-forming properties, sachet, using of bioactive agents in the packaging or on the surface of the packaging material. These are used to avoid microbial contamination in food products.31 Some antimicrobial emitters are ethanol, organic acids, essential oils, and polysaccharides.29, 32             Basil, bay leaves, and cinnamon essential oils are effective against Clostridium sporogenes and E. coli, while cinnamaldehyde essential oil inhibits L. monocytogenes. Lipid oxidation is slowed by green tea extract. E. coli, Staphylococcus aureus, and Pseudomonas spp. are all inhibited by orange essential oil.18 CO2 Emitters Carbon dioxide emitters are most commonly used in combination with modified atmosphere packaging gases like nitrogen or with oxygen absorbers.18, 29 Intelligent Packaging Intelligent packaging is a system that utilizes communication to encourage decision-making for extending shelf life and overall food quality and protection.33 Intelligent packaging can carry out functions like sensing, detecting, tracing, warning about possible problems etc. Different Types of Intelligent Packaging are data carriers, Indicators and sensors.34, 35 Data carriers Data carriers assist in the effective flow of information across the supply chain. The objective of data carriers is to ensure traceability, automation, fraud prevention, not to control product quality.36 They store and transmit information about storage, delivery, and other parameters to ensure this. As a result, they're often seen on tertiary packaging. Barcode labels and RFID (Radio Frequency Identification) tags are the most commonly used data carriers.37 Barcodes and QR Codes Barcodes are cheap, simple to use, and commonly used to deal with supply chain management, stock logging, and checkout.36 In general, barcode scan be divided into two types: one-dimensional and two-dimensional. They have different storage capacities depending on the type. A series of parallel spaces and bars make up a one-dimensional barcode. Data is coded as a result of the various arrangements of bars and gaps. The coded information can be translated using a barcode scanner and an associated device.32 The combination of dots and spaces arranged in an array or matrix makes the two-dimensional barcodes occupy more memory power (such as packaging date, batch number, packaging weight, nutritional details, or preparation instructions). This is very convenient for both retailers and customers. An example of 2D barcodes is QR (quick response) Codes.37 Radio Frequency Identification (RFID) RFID (Radio Frequency Identification) is a technology that uses radio waves to process data. RFID tags are advanced data carriers that can store up to 1 MB of data and capture real-time data without involving any touch or line-of-sight. These devices gather, store, and send real-time data to a user's information system RFID tags are more costly than barcodes and require a more efficient electronic information network.37 On the other hand, the details on these tags can be loaded electronically and updated at any time.38 RFID also has additional benefits for the entire food supply chain which include traceability, inventory control, and quality and safety promotion.39 An RFID device is made up of three parts: a tag, which is made up of a microchip linked to a tiny antenna, a reader, which sends the radio signal and collect responses from the tag, and middleware, that connects the RFID hardware to enterprise applications(fig -3).39, 40 Indicators The existence or absence of a substance, the magnitude of a reaction between various substances, or the concentration of a specific substance is all determined by indicators. Changes are direct, which means different color intensities are used to visualize this detail.40 Depending on the indicator they are placed inside or outside of the package.32 Time Temperature Indicators (TTIs) Temperature Indicators (TTIs) Temperature plays an important step in determining the shelf life of any food product. Deviations in the temperature profile can stimulate the development or survival of microorganisms, resulting in product spoilage. Besides, improper freezing may denature meat or other products' proteins. Time-temperature measures may be used to determine if the cold chain or optimal temperature is adequately maintained in the food supply chain or not.37, 42 are known as user-friendly and easily accessible devices due to their easy functionality.43 The Fresh-Check from Lifeline technologies is an example of a TTI predictor. It works by causing a color shift in the indication range as a result of a polymerization reaction. A clear center indicates a fresh TTI. If the active center's color matches the outer ring, the product should be consumed as soon as possible. The dark core of indicates non-fresh products.44 Some Commercially Available TTI are MonitorMark™,Timestrip®, Fresh-Check®,  Checkpoint®. The 3M MonitorMark® (3M Co., St Paul, Minnesota)48 is a diffusion-based indicator label that is based on the color change of an oxidizable chemical system regulated by temperature-dependent permeation through a filter. A blue-dyed fatty acid ester diffusing around a wick activates the action. At a temperature-dependent rate, a viscoelastic material migrates into a diffusely light-reflective porous matrix. The tag configuration, which differs by polymer concentration and glass transition temperature, controls the response rate and temperature dependence and can be set to the desired range.46, 47 Timestrips® (Timestrip UKLimited, UK) are smart labels that keep track of how long a product has been open or in use. Food protection also necessitates temperature control at home. Timestrip® is a consumer-activated, single-use smart-label for tracking elapsed time on perishable items. It was created to allow customers to monitor the amount of time that had passed after activation.49, 50 Fresh-Check®TTI (Temptime Corp., Morris Plains, NJ, USA)(Fig: 4) is a solid-state polymerization reaction that produces a strong colored polymer. The TTI's answer is a color shift that can be measured as a decrease in reflectance.47 Freshness indicators Freshness indicators track the consistency of food items as they are being stored and transported. Unfavorable conditions or a lack of durability may cause a loss of freshness. As a result, they send data on microbiological development, the presence of microbiological metabolites, and product chemical changes.47,51 Glucose, organic acids, ethanol, volatile nitrogen compounds, biogenic amines, carbon dioxide, ATP degradation products, and sulphuric compounds are examples of quality indicating metabolites.37,53 Freshness indicators must be mounted within the packaging to enable interaction with the compounds. Different methods may be used to detect this information depending on the reliable indicator (Table-1).54 Sensor Sensors show the state of the food's quality concerning the indoor environment. Although the actual indicator shows the quality status, a sensor senses and responds to changes in the environment within the packaging.58 Gas sensor The gas sensor detects carbon dioxide in the package as a sign of microbial growth, which shortens the food's shelf life.53 Non-dispersive infrared (NDIR) or chemical sensors are the most common types of CO2 sensors. NDIR sensors are spectroscopic sensors that use gas absorption at a specific wavelength to test CO2 content.57 Although this sensor reacts to the formation of a spoilage metabolite, it does not explicitly track a quality attribute. CO2 is a useful indicator of food quality and can be used as an indicator compound; however, it is not a quality attribute because CO2 does not cause bad taste or spoilage; quality loss is caused by microorganisms. It is a colorimetric indicator label that monitors the freshness of a dessert (fig- 5).58 Biosensor Biosensors detect pathogenic bacteria on food that cause food safety issues. These are specifically monitoring the quality attribute of food. The Food Sentinel System™ (SIRA Technologies, California, USA) is an example of such a biosensor, which consists of a barcode that contains a membrane with antibodies that can bind to particular pathogens.47 The barcode changes color as the pathogenic bacteria develop during storage, resulting in a barcode that can no longer be scanned.58 Discussion: Smart packaging strives to protect products from a variety of risks while also allowing for more active and intelligent packaging applications to be commercially viable. It's critical to keep the ultimate cost of intelligent packaging systems to a small percentage of the overall package cost, as well as to overcome the inherent challenges of transitioning laboratory trials to industrial-scale manufacturing. Multiple functionalities can be combined into a single packaging, and single-use throwaway products can be replaced with long-lasting reusable devices. Conclusions Though the idea of intelligent packaging has not grown rapidly it is the technology of the future. Smart packaging aims to provide safety to the product from all kinds of hazards. To ensure that more active and intelligent packaging applications become commercially feasible and “into everyday packaging commodities” around the world, it is important to ensure that the final cost of intelligent packaging systems is a small fraction of the overall packaging cost and resolve the inherent difficulties in converting laboratory trials to industrial-scale production.  Incorporating multiple functions to be integrated into a single package and replacing single-use disposable products with long-lasting reusable devices. Significant technical advances are still needed to realize these growth goals. Only then it will provide a safe ground for monitoring the food item and controlling the distribution correctly. Acknowledgement: Authors acknowledge the immense help received from the scholars whose articles are cited and included in references of this manuscript. The authors are also grateful to authors/editors/publishers of all those articles, journals and books from where the literature for this article has been reviewed and discussed Source of Funding: Authors have no source of funding Conflict of Interest: Authors have no conflict of interest Authors’ Contribution: Saikat Mazumder, Shalini Chanda, Dr. Amiya Bhaumik have equally contributed in the study. Englishhttp://ijcrr.com/abstract.php?article_id=4334http://ijcrr.com/article_html.php?did=4334  The history of packaging, https://crawfordpackaging.com/automation-and-innovations/history-of-packaging, 23rd August 2021. Yam KL,Takhistov PT, Miltz J. Intelligent packaging: Concepts and applications. J. Food Sci.2005; 70: 1–10. 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Radiance Research AcademyInternational Journal of Current Research and Review2231-21960975-5241143EnglishN2022February1HealthcareDegree of Confidence in the Choice of Organic Products and its Determining Factors: Case of the Moroccan Consumer English1923Saad HEnglish Bennani BEnglishIn recent years, organic products have been at the heart of the news. Many people take a particular interest in the consumption of organic products, unlike those of conventional agriculture. This trend is determined by the degree of confidence that these people can place in an organic products. The estimation of this degree is of practical utility. In this present work, our objective consists in a contribution to developing the levels of confidence in respondents to certain determinants as well as the factors, which direct this confidence. We, therefore, conducted a prospective survey through a questionnaire of 148 respondents, 54.7% of whom are female. A Cronbach’s alpha index (= 0.777) gave very accepted reliability (0.777) for this questionnaire. The results show that 57.3% of respondents gave confidence to organic products. This percentage remains much lower than that of France (95% ° and that of Tunisia (62.5%). The study shows to preserve the environment and consumer health, it is therefore important to develop this mode of production. It shows, moreover, that 58% of our respondents buy their “organic” products occasionally, a result similar to that reported in 2017 in France and that, for Morocco, these products are rarely purchased from supermarkets. The results show that, for those who include “organic” ingredients in their food, the budget allocated to the purchase of this product is between 100 and 200 MAD. English Organic product, Food, Confidence, Determining factors, People surveyed, Morocco INTRODUCTION Across the world people are increasingly engaged in responsible consumption with the purchase of sustainable and environmentally friendly products.1 This trend shows that these products are gradually occupying a prominent place in the consumption habits of organic products. Qualifying an organic product must ensure that its production has been carried out under healthy conditions, without the use of chemicals or pharmaceuticals. The consumption of a food product cannot, therefore, be considered trivial insofar as it corresponds to the incorporation by the consumer of a foreign body Sirieix, (1999).2 unlike many countries around the world, in Morocco there are no studies that have looked at this consumer trend. In France for example, according to the French Ministry of Agriculture and Food (2019), more than 9 in 10 French people (92%) report having consumed organic products in 2018.3 In addition, in France, a study shows that more than 30% of French people believe that it is normal to pay more for organic products.4 Furthermore, according to Slim Kabbaj (2019), President of the Club des entrepreneurs Bio (CEBio), in Morocco, the first organic productions date back to 1986 and in 1919 the area devoted to organic farming in Morocco reached 11,000 hectares, i.e. an increase of almost 50% compared to the last ten years. Usually, this type of agriculture involves fruits, market garden plants and aromatic, medicinal and condiment herbs. This new activity constitutes an emerging economic sector, so the identification of organic consumption values ??is an issue of concern to marketing researchers.5 However, many studies have concerned organic products in America and Europe, but in Morocco, little research has started on this subject despite the efforts undertaken. It is with this in mind that we proposed to contribute to this research by conducting a prospective study on confidence in the consumption of organic products and the link with certain socio-demographic factors. METHODOLOGY We have adopted a method of descriptive and analytical analysis based on a survey of a sample of 148 respondents. The means chosen for data collection is the questionnaire. Data analysis is performed by SPSS 12 software. • Study area and population The data is collected following invitations by email. Guests are expected to complete a questionnaire covering certain socio-demographic criteria. • Data collection tool The questionnaire is made up of 6 items, the choice of which is inspired by a bibliographical summary on work already carried out around the world. The questionnaire is composed of two parts: a part reserved for questions on the socio-demographic and professional profile and a second part intended for the questionnaire itself which is made up of 6 items. Items 1: Do you think that the choice of organic products is important? If so, do you justify it? Item 2: Have you ever bought or consumed an organic product, if so which one? Item 3: where did you buy the organic products? Item 4: What is your allocated budget for the purchase of organic products on average? Item 5: Attendance at places to buy organic products Item 6: What are your motivations of purchase organic products? The data after collection and filtration are subjected to descriptive and analytical analyzes by the SPSS 12 software (trial version). RESULTS 1. Description of people surveyed The survey covers 148 respondents, 54.7% (n=81) of whom are female. In addition, 47.3% (n=67) are under 30 years old, 48% are between 30 and 50 years old and 4.7% are over 50 years old. Regarding the educational level of respondents, 57.3% have a level between 3 and 5 years after the baccalaureate and 26.7% have a baccalaureate-level over 5 years. The majority of respondents are students or civil servants. 2. Study of the distribution of respondents' responses Table (1) below shows the results of the distribution of responses to the various items of the questionnaire proposed for the state of confidence. Remembering that the reliability showed a very important Cronbach index (index = 0.777). 1. Do you think that the choice of organic products is important? If so, do you justify it? The breakdown of respondents according to their answers to this question shows that 57.3% (n = 86) said “yes” against 42.7% (n = 62) who answered “No”. The respondents who answered “yes” justified this for many reasons. Indeed, 41.86% (n = 36) declared that in principle, the choice of organic products helps to guide the deployment of policies in favor of responsible production on the part of organizations. But in fact, since we are in a capitalist system, it is very difficult to produce this policy, while 44.19% (n = 38) justified their answer by the fact that the use of organic products is in close relationship with the environment, society, this responsibility is to be passed on to subsequent generations, so we must be careful what we consume and how we consume it. We should not therefore exaggerate but make our consumption optimal. On the other hand, it is favorable to sustainable development to preserve resources, not to encroach on the resources of future generations to ensure the sustainability of the quality of life for future generations because the environmental situation and of the climate is deteriorating day after day. 13.96% responded that this practice is for the preservation of health. 2. Have you ever bought or consumed an organic product, if so which one? The figure below shows the results of the responses to the question "Have you ever bought or consumed an organic product, if so which". Indeed, 46% of respondents said they bought or consumed the food or cosmetic products. However, 22% bought food products only, and 17% cosmetic products. 3. Where did you buy the organic products? The results concerning this question show that 35% of respondents choose to buy organic products from associations and cooperatives while 26% buy them in specialized stores. 21% say they buy these products from farmers and / or associations. Likewise, 18% of respondents said they are comfortable with supermarkets. Studies carried out in France show that 65% of purchases are made in medium-sized stores. 4. What is your allocated budget before buying organic products on average? The results of the budgets reserved for the purchase of organic products. As a result, 37% of respondents declared spending between 100 and 200 MAD and 24% between 300 and 400 MAD. However, 24% answered spending between 300 and 400 MAD. 5. Regarding the question concerning the frequentation of places of purchase of organic products: The results show 58% said that occasionally while 20% declared that they frequented places of sale once a month and the same frequency for those who responded several times a week. 6. What are your motivations in relation to the purchase of organic products? The breakdown of responses to this question shows that 58% say that the motivation to consume organic products is health, 24% it is for well-being and 18% answer that it is product quality. 3. Global analysis The degree of confidence is obtained by summing the response levels according to the corresponding scale. The average score is 87.23 ± 3.09, this score fluctuates between 5 points as a minimum value and a maximum score of 16 points. The distribution meets the standards of a Gaussian law (skewness coefficient = 0.11 and a kurtosis of 0.99). In fact, given the absence of a standard, we referred to the median value which corresponds to 85.01; 50% of respondents had a score below the median value therefore considered to have a degree of confidence varies from a low to moderate degree and the remaining 50% where the score is greater than the median value are respondents with a degree of confidence. Trust acceptable to best. To look for certain factors related to this behavior, we used a multiple regression analysis whose dependent variable is the score and the explanatory variables are mentioned in the table below. Analysis of variance shows a very highly significant effect (Fisher = 5.754. P Englishhttp://ijcrr.com/abstract.php?article_id=4335http://ijcrr.com/article_html.php?did=4335   Schifferstein HN, Ophuis, PAO.. Health-related determinants of organic food consumption in the Netherlands. F.qua. Prefer;1998; 9 (3):119-133. Sirieix La L. Consommation alimentaire: problématiques, approches et voies de recherche. Recherche et Applications en Marketing (French Edition); 1999;14 (3): 41-58. De Montzey S., De Jubecourt D.. Les signes officiels de qualité en France et dans l'Union Européenne. Techniporc; 2001;24(2) : 19-24.‏ Rivière-Wekstein G. Bio fausses promesses et vrai marketing. Le Publieur ;2012; pp130-136. Lin P C, Huang YH. The influence factors on choice behavior regarding green products based on the theory of consumption values. J. Clear. Pro;2012;22 (1): 11-18. Vega-Zamora M, Torres-Ruiz FJ, Murgado-Armenteros EM, Parras-Rosa, M. Organic as a heuristic cue: What Spanish consumers mean by organic foods. Psychology & Marketing; 2014; 31(5): 349-359. Kesse-Guyot E, Peneau S, Mejean C, de Edelenyi FS, Galan P, Hercberg S et al. Profiles of organic food consumers in a large sample of French adults: results from the Nutrinet-Sante cohort study. PloS one; 2013;8(10): e76998. Kaouther G, Rym K, Basma B A. Le marché des produits bio en Tunisie: Mythe ou Réalité pour les Enseignes de la Grande Distribution. Revue Marocaine de Recherche en Management et Marketing; 2014 ; 9(10): 189-207. Sylvander B. Les tendances de la consommation de produits biologiques en Europe : conséquences sur les perspectives d’évolution du secteur, contribution au colloque. Organic agriculture faces its development, the future issues;1999 ;pp 320. Zanoli RS, Naspetti S. Consumer motivations in the purchase of organic food, Brit. Fo.J; 2002;104 (8): 643-65

Radiance Research AcademyInternational Journal of Current Research and Review2231-21960975-5241143EnglishN2022February1HealthcareFormulation of Ice Cream from Sweet Pearl F1 as Affected by Three Levels of Corn Starch and Its Corresponding Nutritional Analysis English2430Christina T. AlfilerEnglish Cristina B. NatividadEnglish Celia Flor R. FerrerEnglishIce cream is a popular treat that is known to everyone. The goal of this study was to produce ice cream from the sweet pearl F1 variety, which was affected by three different levels of maize starch. It was founded by a group of academics from the College of Education, namely from the BTLEd department, to empower young people to spread technology and livelihood education in rural regions. Because we are an agricultural country, farmers are at the forefront of our economy. As a consequence, we must pay careful attention to how livelihood education is spread among our corn families. The aim of this study was to develop three ice cream formulations and use sensory assessment to assess their nutritional quality and appeal. The flavor and color criteria for sensory evaluation in ice cream did not differ substantially among the three treatments tested, according to the study’s results. ANOVA revealed that the treatments were substantially different in terms of ice cream texture and palatability. According to the nutritional research, only T3 surpassed the USDA’s fat limit of no more than 10%. The three different quantities of starch did not make a significant difference in taste or color among the treatments tested, but they did make a significant difference in texture and palatability. To ensure great palatability and texture, the researchers recommend utilizing one teaspoon (T3) commercial corn starch, as well as a fat level of no more than 10%. More study on the melting ability of the ice cream after it hardens in the ice cream maker is also recommended. EnglishSweet Pearl F1, Nutritional analysis, Ice cream, Palatability, Texture, FlavorIntroduction             Bachelor in Technology and Livelihood Education (BTLEd) prepares young adults to spearhead the diffusion of technology and livelihood education in the countryside. Being an agricultural country, farmers are the forefront of our economy. Hence, livelihood education among our corn household needs due attention.             According to the annual report 2018 of the Department of Agriculture, the national production of corn attained 7,771,918.6 MT. Almost 21% of this volume was contributed by Cagayan Valley. However, in an interview from a local farmer in Gattaran, some farmers abandon their standing cornfield without harvesting the corn ear due to the very low buying price of corn grains that can no longer compensate the effort of harvesting. Moreover, the activities of the corn household in the field are seasonal. Hence, there is more slack time as compared to productive time. It is for this reason to divert some of household time to engage them into corn processing such as but not limited to ice cream. Although ice cream is already known to the consuming public, there is a need to revisit the sources of raw materials to make it more competitive in term of price and nutritional quality. Ice cream has a high nutritional value consisting of small air cells dispersed in a partially frozen, continuous aqueous phase. The desired quality is achieved by both proper processing and formulation of the different ingredients, Goff & Hartel (2013).1 Corn syrup is an indispensable element in ice cream making. Technically speaking, corn syrup is commonly referred to as ‘glucose syrup’ or ‘corn starch hydrolysate syrup. Corn syrup are classified by their dextrose equivalence (DE), which indicates its degree of hydrolysis from starch to dextrose. The higher the DE, the sweeter the corn syrup will be until complete conversion with a DE of 100 is achieved.  However, ice cream manufacturers usually used liquid or dry corn syrup products with a 28 -42 DE, Goff & Hartel (2013).1 This technology would increase the utilization of corn specifically the sweet pearl white corn (F1) variety grown in the region. It likewise opens the opportunity for product diversification resulting to additional income for the farmers and the household. The technology shall develop optimum corn (white corn /f1) ice cream preparation process that can be adopted by micro, small, and medium enterprises (MSMEs), LGUs and even existing ice cream makers in the region. This technology will also produce safe, nutritious, acceptable and all-natural ice cream products that will be available to individuals who are fond of sweets or desserts. Objectives of the Study Generally, this study aimed to formulate and test corn ice cream.  In particular, it aimed to: Formulate ice cream product Determine the nutritional content of the processed ice cream Determine the acceptability of the product thru sensory evaluation Statement of the Null Hypothesis    There is no significant difference on the effect of starch content of the different treatments in terms of taste, texture, color and palatability. Related Literature Corn, technically known as Zea mays Lynn, is one of the Cagayan Valley's secondary crops. Corn production is critical since corn farming is many farmers' primary source of income. Cornice cream offers a lot of benefits. The absence of a well-established and efficient corn ice cream process in the area, on the other hand, restricts the range of goods that producers may provide to local and international customers. Sweet Pearl F1 is a rare hybrid waxy-sweet white maize with milky white kernels and high amylose content. It is a 60-65 day early maturing variety. Because of its great drought tolerance, it is ideal for planting in the dry season. Ice cream is defined as a frozen product produced from a combination of dairy components that has at least 10% milkfat (Marshall and others 2003)2 before the addition of bulk ingredients such as flavorings and sweeteners, according to the United States Federal Regulations (21CFR135.110). Furthermore, (AM  Abd El-Rahman et al.,1997)3viscosity of the ice cream mixes is affected by the source of milk fat and the addition of emulsifiers.Textural characteristics of ice (Syed QA, etal.)4   are the main variables influencing the product's commercial success. Furthermore, ice creams are characterized for particle size distribution of fat globules, melting resistance and amount of proteins in the aqueous phase (Granger C. 2004).5 Moreover,(M.M.R.Koxholt etal. 2001)6 the meltdown is dependent on the fat agglomerate sizes in the unfrozen serum phase.  According to Buyck JR et.al (2011)7, ice cream production costs may be decreased by increasing the temperature of the storage freezer as a way of lowering energy costs. They also discovered that stabilizers and emulsifiers enhance ice cream texture by increasing viscosity and restricting free water molecule mobility. Nonetheless, their abundance may result in reduced melting and whipping capabilities. Sugar gives ice cream a sweet flavor and enhances thickness and bulkiness, but too much of it may cause it to become mushy if the solid percentage exceeds 42 percent. According to Arbuckle (2000)8, ice cream must include less than 10% milkfat and 20% total milk solids to meet US regulatory requirements. It can't have more than 0.5 percent stabilizers and can't have less than 1.6 pounds of total food solids per gallon. Fat is 12 percent, milk solids non-fat (MSNF) is 11 percent, sugar is 15 percent, stabilizers and emulsifiers are 0.3 percent, and TS is 38.3 percent in an excellent average ice cream. Stabilizers enhance water binding capacity, thus they have no impact on taste or product value. In addition, stabilizers in ice cream smooth the texture, increase viscosity, and offer resistance to melting. Furthermore, flavor perception is determined by the nature and quantity of the flavor compound and its availability to the sensory system as a function of time(Li Z. 1997)9.        METHODS AND PROCEDURES Materials    The materials used in this study were corn grits (hard dough stage) of sweet pearl (F1), whole milk, heavy cream, vanilla extract; sweetener table salt; and commercial corn starch.   Experimental Procedures Preliminaries in corn ice cream making. The raw materials were purchased from the local public market. However, the corn was taken from Alcala due to the desired variety. Other materials and ingredients were sorted according to the desired quantity. Different pre-treatment activities such as grinding, crushing and pressing were employed to facilitate the extraction of the aroma of corn and obtain the maximum starch. Suspended particles from corn liquid were removed through filtration using cheesecloth. This prevents the inclusion of unnecessary particles that will destroy the desired texture in the treatments. Formulation of Corn Ice Cream. The following ingredients except corn starch were used at a constant amount in the product formulation, namely; desired level of corn kernels (sweet pearl-F1), whole milk, heavy cream, vanilla extract, sweetener, and table salt. Three formulations were made and were subjected to sensory evaluation with common parameters. Consumer Acceptability Test or Sensory Analysis. The physical parameters include taste, texture, palatability, and color. The fifteen panels of evaluators were clustered into three to cover the three treatments. Each cluster evaluated the three treatment formulations and conducted three evaluations per treatment. A 10-point hedonic scale was used to determine the level of each of attribute namely taste, texture, palatability and color.The rubrics for the sensory evaluation are shown below; Laboratory Testing. Treatments that are properly packed were submitted to FAST laboratory in Quezon City for Nutritional Analysis. Packaging and Labeling. The developed products were packed in cups and labeled following the FDA label requirements in the containers. Statistical Tool The rubrics served as the source of raw data. The mean obtained in the score sheet were used to process the data and were analyzed using the One way ANOVA (Analysis of Variance). F-computed and F-tabular values were used to compare the level of significance among treatments at 1% and 5% level of significance. RESULTS Table 1 shows the result of sensory evaluation on the taste parameter of ice cream. The obtained mean of 3.27 falls within the level of satisfaction while 3.67 is nearly very satisfactory. In other words, the effect of starch in the formulation gave more than satisfactory result to consumer. However, using the ANOVA as revealed in Table 1a, showed that treatments were not significantly different from each other. The variable amount of starch from ¼ tsp to 1 tsp did not give any substantial difference in terms of taste among the treatments tested. Table 2 shows the result of sensory evaluation on the texture parameter of the ice cream. The obtained mean of 3.27 and 3.20is nearly described it as satisfactory while that of 3.47 is nearly very satisfactory. In other words, the effect of the three levels of starch in the formulation gave satisfactory results to the consumer. Furthermore, ANOVA  reveals as shown in Table 2a that the treatments gave highly significant differences among each other. The one teaspoon level of starch gave a substantial difference in term of texture as compared to the other treatments. Considering the findings of Syed et al., textural attributes of ice cream are the key factors determining the market success of the product. We can safely say therefore that T1& T2 did not give a comparable result to T3. Hence, one teaspoon is highly favorable compared to the other treatments. Table 3 shows the result of sensory evaluation on the color parameter of ice cream. The mean obtained of 3.27, 3.20, & 3.47 were described it as more than satisfactory. In other words, the effect of starch in the formulation gave more than satisfactory results to the consumer. However, using the ANOVA as revealed in Table 3a, the treatments were not significantly different from each other. The three amounts of starch did not give any substantial difference in terms of color among the treatments tested. Nonetheless, color combination used was quite pleasing and in harmony with the corn flavor as manifested in the rubrics. Table 4 shows the result of sensory evaluation on the palatabilityparameter of ice cream. The mean obtained of 3.13 and 3.07 is described as satisfactory while that of 3.87 is nearly very satisfactory. Looking at the rubrics, the effect of starch in the formulation gave more than a refreshing blend of ingredients but with only a partial corn flavor as observed by the consumer. Moreover, using the ANOVA as shown in Table 4a, it showed that the results gave a highly significant difference among the treatments tested. The varied amount of starch (as stabilizer) gave highly substantial difference in terms of palatability among the treatments tested. Hence, the overall palatability of T3 among the other treatments was highly commendable. The findings runs parallel to the statement of Syed et al. that stabilizers improve the viscosity of the ice cream as it enters the palate of the taster or evaluator. Table 5 shows that Treatment three (T3) had fat content of 8.56% which is way below T2 & T1. The findingsis inconsonant with the recommended level of the US Federal Regulations of fats of not more than 10% as mentioned by Marshall et al. (2003). The rest of the parameters exceeded the recommended values. The minimum sugar content of the treatments was recorded in T3 at 18.8%. However, this value is little bit higher than 15%   as recommended by Arbuckle (2000). Nonetheless, this nutritional content could be managed during packaging so as to meet the recommended body daily allowance by the consumer. DISCUSSION OF FINDINGS The result of sensory evaluation on the taste parameter of ice cream. The obtained mean of 3.27 falls within the level of satisfactory while 3.67 is nearly very satisfactory. In other words, the effect of starch in the formulation gave more than satisfactory result to consumer. However, using the ANOVA as revealed in Table 1a, showed that treatments were not significantly different from each other. The variable amount of starch from ¼ tsp to 1 tsp did not give any substantial difference in terms of taste among the treatments tested. The result of sensory evaluation on the texture parameter of the ice cream. The obtained mean of 3.27 and 3.20 is nearly described it as satisfactory while that of 3.47 is nearly very satisfactory. In other words, the effect of the three levels of starch in the formulation gave satisfactory results to consumer. Furthermore, ANOVA reveals as shown in Table 2a that the treatments gave highly significant differences among each other. The one teaspoon level of starch gave a substantial difference in terms of texture as compared to the other treatments. Considering the findings of Syed et al., textural attributes of ice cream are the key factors determining the market success of the product. We can safely say therefore that T1& T2 did not give a comparable result to T3. Hence, one teaspoon is highly favorable compared to the other treatments. The result of sensory evaluation on the color parameter of ice cream. The mean obtained of 3.27, 3.20, & 3.47 described it as more than satisfactory. In other words, the effect of starch in the formulation gave more than satisfactory result to consumer. However, using the ANOVA as revealed in Table 3a, the treatments were not significantly different from each other. The three amount of starch did not give any substantial difference in terms of color among the treatments tested. Nonetheless, color combination used was quite pleasing and in harmony with the corn flavor as manifested in the rubrics. The result of sensory evaluation on the palatability parameter of ice cream. The mean obtained of 3.13 and 3.07 is described as satisfactory while that of 3.87 is nearly very satisfactory. Looking at the rubrics, the effect of starch in the formulation gave more than a refreshing blend of ingredients but with only a partial corn flavor as observed by the consumer. Moreover, using the ANOVA as shown in Table 4a, showed that the results gave a highly significant difference among the treatments tested. The varied amount of starch (as stabilizer) gave highly substantial difference in terms of palatability among the treatments tested. Hence, the overall palatability of T3 among the other treatments was highly commendable. The findings run parallel to the stabilizers that improve the viscosity of the ice cream as it enters the palate of the taster or evaluator3. Treatment three (T3) had fat content of 8.56% which is way below T2 & T1. The findings is inconsonant with the recommended level of the US Federal Regulations of fats of not more than 10% 2. The rest of the parameters exceeded the recommended values. The minimum sugar content of the treatments was recorded in T3 at 18.8%. However, this value is little bit higher than 15% 4. Nonetheless, this nutritional content could be managed during packaging so as to meet the recommended body daily allowance by the consumer. CONCLUSIONS The study, therefore, closes that the; Three levels of starch did not give any substantial difference in terms of taste and color among the treatments tested; The three levels of starch gave highly significant difference in terms of texture and palatability among the treatments tested; and Treatment three (T3) surpassed the USDA recommendation of not more than 10% fat. RECOMMENDATION Based on the above findings of the study, the researchers recommend: The use of one teaspoon (T3) commercial corn starch to ensure good results on palatability and texture; and The use of treatment 3 (T3) due to its ideal level of nutritional analysis for fats in terms of recommended value. Further study on the melting ability as it hardens in the ice cream maker. More flavors or variants may be tested for nutritional value ECONOMIC/ FINANCIAL IMPLICATIONS Many culinary inventions are currently available on the market. Culinary scientists are overly preoccupied with finding food trends that both elderly and young people would like and become the finest in town (food trends). There are many various types of desserts available on the market, but the nutritional content of these meals is particularly important to consumers. People like ice cream as one of their favorite meals. While there are several commercial ice creams on the market, this research focuses on the palatability and nutritional value of its sources while not compromising the quality of its type. With the economic assistance of this kind of business, many food grabbers would utilize such business, which in turn would prove to be economically or financially beneficial to the company owners. When there is more company like this, there will be economic stability or financial independence. Similarly, smart consumers would be able to purchase goods with great nutritional value as well as those that are reasonably priced. As asserted by Karaman et al.(2014)10 Frozen dessert producers have numerous options for changing the content, ingredients, shape, quality, and packaging of their goods. With such a diverse range of ingredients and techniques at one's disposal, the possibility for creating a plethora of delectable frozen desserts is almost limitless. Acknowledgment: We acknowledge the immense help received from the researchers whose articles are cited and included in the references of this paper. Special thanks is also accorded to the laboratory facility for the analysis and to the group of expert who composts the panel for the sensory evaluation. The authors acknowledge the patience of those people who improved the composition of the study. SOURCE OF FUNDING: The researcher appreciates the assistance of the university research department for the financial support in conducting the study. CONFLICT OF INTEREST: The authors declare no conflicts of interest in preparing this article.          AUTHORS’ CONTRIBUTION: Dr. Alfiler designed and conducted the study,  and prepared the manuscript with important intellectual input from Dr. Natividad and Dr. Rodriguez. Cagayan State University provided funding for the study, statistical support in analyzing the data with input from Dr. Alfiler. We would like to thank Dr. Alma Manera for her editorial support during the publication of the study. Englishhttp://ijcrr.com/abstract.php?article_id=4336http://ijcrr.com/article_html.php?did=4336 Goff  D.H. & Hartel R.W.(2013). Ice cream 7thedition, Springer, Boston, MA publisher New York 2013 Marshall RT, Goff H.D. 2003. Formulating and manufacturing ice cream and other frozen desserts. Food Technol. 57(5): 32-45. El-Rahman AA, Madkor SA, Ibrahim FS, et al.(1997) Physical characteristics of frozen desserts made with cream, anhydrous milk fat, or milk fat fractions. J Dairy Sci, 80(9):1926–1935 Qamar Abbas Syed,  Saba Anwar, Rizwan Shukat, Tahir. 2018. Effects of different ingredients on the texture of ice cream. https://medcraveonline.com/JNHFE/effects-of-different-ingredients-on-texture-of-ice-cream.html Received: October 02, 2018, | Published: November 20, 2018 Granger C, Leger A, Barey P, et al. (2005) Influence of formulation on the structural networks in ice cream. Int Dairy J. 15(3):255–262 Koxholt MMR, Eisenmann B, Hinrichs J. Effect of the fat globule sizes on the meltdown of ice cream. J Dairy Sci. 2001;84(1):31–37. Buyck JR, Baer RJ, Choi J.(2011).  Effect of storage temperature on quality of light and full-fat ice cream. J Dairy Sci. 94(5):2213–2219. Arbuckle, W.S. 2000. Development of ice cream industry. Springer Science + Business Media New York. Li Z, Marshall R, Heymann H, et al. Effect of milk Fat content on flavor perception of vanilla Ice cream J Dairy Sci. 1997;80(12):3133–3141 Karaman S, Toker OS, Yüksel F, et al.(2014).  Physicochemical, bioactive, and sensory properties of persimmon-based ice cream: Technique for order preference by similarity to ideal solution to determine optimum concentration. J Dairy Sci. 2014;97(1): 97–110.

Radiance Research AcademyInternational Journal of Current Research and Review2231-21960975-5241143EnglishN2022February1HealthcareProblematic Patterns of HPLC in Common Practice: Decision Making and Further Investigations English3135Hota SarbashisEnglish Das Tushar KantiEnglishIntroduction: HPLC (High Performance Liquid Chromatography) is the commonest method endorsed for screening of Thalassemia and other hemoglobinopathies in our country. Universal screening of antenatal mothers in the early first trimester has been employed under the Thalassemia control programme launched as a part of National Health Mission. Estimated prevalence of thalassemia in India is as high as 10000-15000 per year and varies from state to state, and even district to district owing to the multi-ethnic population of India and the scattered tribal belts. Case Reports: Here, our discussion has highlighted four scenarios which are reasonably common in Indian subcontinent, but problematic none-the-less due to various reasons. The differential diagnoses, decision making and strategies for further choice of investigations has been elaborated in details. Conclusion: As a tool of screening, the outcome based on haemoglobin HPLC greatly relies on the successful interpretation of the patterns of the graphs and thorough understanding of the gray zones and pit falls inherent to the procedure employed. EnglishIntroduction: HPLC (High Performance Liquid Chromatography) is the commonest method endorsed for screening of Thalassemia and other hemoglobinopathies in our country. It has the added advantage of quantification of the variant hemoglobin in the same sitting, which was not achieved by previous electrophoresis based methods.1 Universal screening of antenatal mothers in the early first trimester has been employed under the Thalassemia control programme launched as a part of National Health Mission.2 Estimated prevalence of thalassemia major in India is as high as 10000-15000 per year and varies from state to state2, and even district to district owing to the multi-ethnic population of India and the scattered tribal belts. As a tool of screening, the outcome based on haemoglobin HPLC greatly relies on the successful interpretation of the patterns of the graphs and thorough understanding of the gray zones and pit falls inherent to the procedure employed. Here, our discussion will highlight those scenarios which are reasonably common in Indian subcontinent, but problematic none-the-less due to various reasons. The differential diagnoses, decision making and strategies for further choice of investigations will be elaborated in details.  Case series: 1)  Age-  18  yr, Hb- 10.3 gm%, RBC count-  3.83 million/mm3, HCT-31.50%, MCV- 82.20 fl, MCH-26.90  pg,  RDW-18.50  % Impression: The person was asked to repeat HPLC after Iron-folate supplementation for 3 months, as the iron profile revealed a low Ferritin level and the result of Vit B12 & Folate assay were below the reference range. Subsequent HPLC confirmed a Beta-Thalassemia carrier state. 2) Age-  36  yr, Hb- 4.20 gm%, RBC count- 2.13  million/mm3,HCT-15.70%, MCV- 73.70 fl, MCH-19.70  pg, RDW-42.40  % Impression: compound heterozygote of Hb E and Beta-thalassemia. 3) Age- 8 yr, Hb- 9.2 gm%, RBC count- 3.87 million/mm3,HCT-28.9%, MCV- 74.7 fl, MCH-23.8pg, RDW-21.8   Impression: Compound heterozygote of Beta-Thalassemia and Sickle Hemoglobin (Hb S). A genetic study was advised for confirmation as well as to rule out a coexistent alpha thalassemia trait. 4) Age-   19 yr, Hb- 11.9 gm%, RBC count-  4.22 million/mm3,HCT-34.90%, MCV- 82.7fl, MCH-28.1pg, RDW-13.60  %    Impression: Patient was referred for genetic study to rule out an alpha-thalassemia trait. Discussion: The commonly used software is the Beta Thalassemia short programme designed by Bio-Rad, which mainly focuses on screening of beta-thalassemia syndromes; and thus the first 63 seconds are not integrated in the graph.3 So the abnormal hemoglobin important in alpha thalassemia detection (like HbH and Hb Bart) cannot be visualised in it. The pre-analytical quality control is also of paramount importance and the EDTA blood samples freshly collected should be run as early as possible; as storage-related deterioration can manifest as multiple aberrant peaks(commonly at P3), which are very difficult to interpret. Another important matter is the measurement of total calibrated area, which ideally should remain between 1 million to 3 million for a properly validated result. It is to be remembered that what we actually detect in HPLC- is the altered pattern of Hb A and HbF percentage in case of adults, which indirectly points toward the diagnosis of thalassemia syndrome. The HPLC-based diagnosis is mostly impractical in infants, where the shift from fetal to adult hemoglobin has not been completed yet4. Moreover, the hemoglobin shift is often delayed in cases of children with hemoglobinopathies, and that creates further confusion. Children with clinically diagnosed beta-thalassemia major often receive multiple transfusions for obvious reasons, prior to a definitive diagnosis is made. The HPLC pattern generated from such patients sustained on repeated transfusions create awesome problem regarding interpretation4, and often the molecular diagnosis is the only resort available. Borderline value of HbA2 in a suspected beta-thalassemia trait:  A common problem is encountered most often when the HbA2 percentage falls between 3.5% and 4% just like in case 1. It is important to remember there are entities like Silent and almost Silent beta-thalassemia carrier, where the HbA2 percentage remains normal or not much elevated.5It is impossible to diagnose a carrier state in such scenarios without any genetic study. Co-inheritance of delta thalassemia or alpha thalassemia decreases the level of Hb A2 that was likely to be increased due to a carrier state5. Perhaps the most important confounding factor in Indian perspective, especially for antenatal screening, is Iron deficiency and megaloblastic anaemia. It is a dictum to scrutinize the hemoglobin, RBC count and red cell indices in details and assess the iron profile, vit B12 & folate levels of the patient, in such cases. Repeat HPLC is to be done after iron-folate supplementation, only then the carrier state may become manifest. The presence of Hb A2 variants, often which elutes in the S window, may underestimate the actual value of A2, and, thus a true thalassemia carrier can be missed5. In our case, the red cell indices with the borderline HbA2 value raised suspicion for a beta-thalassemia carrier state. An iron-profile and vitamin B12 and folate assay were sought. The person was asked to repeat HPLC after Iron-folate supplementation for 3 months, as the iron profile revealed a low Ferritin level and the result of Vit B12 & Folate assay were below the reference range. Subsequent HPLC confirmed a Beta-Thalassemia carrier state. E-beta thalassemia or Hb E disease: The common problem in HPLC Bio-Rad II is the co-elution of different hemoglobins in the same window. It is particularly important for the A2 window, where Hb Lepore and Hb E also appear. Hb E is very common in the Indian subcontinent, especially in the Eastern India surrounding Bengal2. No other common test can separate Hb A2 and Hb E, except Capillary Electrophoresis; although it has the disadvantage of separating Post-translationally modified variants of the same haemoglobin, and thus makes the interpretation troublesome.1 It is also important to study the graph in these cases, otherwise, the Lepore hump can be missed. It is taken as a thumb rule that whenever the HbA2 percentage crosses the value of 10%, some other Hemoglobin like Lepore or E are likely present.1 The problem lies in the fact that actually, no clear cut line of separation is existent, between the diagnosis of E-beta thalassemia and E-disease based on HbA2 percentage only. There is a region of overlap between 65% and 85% of HbA2 percentage, which is shared by both. The common strategy here is to look for the Hb F percentage, usually, it is less than 5% in Hb E disease but more than 15% in cases of A-beta thalassemia. But still there remains a foggy area. In this scenario, the clinical data is of particular significance. Patients with E-beta thalassemia often have past history of multiple blood transfusions, but those with Hb E disease do not have such. The parental study, often, when feasible, ameliorate the problem, but when one of them is dead, the only resort left is genetic study. In our case, the patient was symptomatic and had previous history of transfusions. The peripheral blood findings also favoured the diagnosis of E-beta thalassemia. The parents were alive in this case, and further HPLC-based study revealed the father being a beta-thalassemia carrier and the mother a Hb E trait. Sickle cell disease versus Sickle Beta Thalassemia: Diagnosis of sickle cell disease is done when Hb S is greater than 50% and there is no adult hemoglobin (Hb A), as compared to Sickle cell trait when both Hb A and Hb S are present and the former is the predominant one. In Indian context, due to the presence of the Arab-Indian haplotype, Hb F comprises a significant proportion in cases of Sickle cell disease (maybe up to 40%).5 The diagnosis of compound heterozygosity of sickle hemoglobin and β+ thalassemia is usually straightforward.5 Both Hb A and Hb S are present, and the percentage of Hb S is greater than Hb A. However, the problem arises regarding the distinction of Sickle-β0 thalassemia and Sickle cell anemia. In both cases, no adult hemoglobin is there and the HPLC results are almost similar. The HbA2 percentage can aid in diagnosis. Usually, in sickle- β0 thalassemia the HbA2 is found to be elevated (3.5-5.5%), whereas it remains at 2-4% in Sickle cell disease.5 The peripheral blood picture is of utmost importance in this case, microcytosis favors the diagnosis of Sickle-β0 thalassemia over Sickle cell disease. Also, the parental study, when feasible, can alleviate the problem. However, if the case is Sickle cell anemia with microcytosis(with co-existent alpha-thalassemia), the differentiation is extremely difficult as the HbA2 percentages are almost similar and often need genetic diagnostic aids.5 A case of Sickle- β0 thalassemia has every chance to be misdiagnosed as sickle cell disease when coexistent alpha thalassemia is there.5 In our study, the HPLC pattern pointed towards the diagnosis of Sickle cell disease over Sickle-Beta thalassemia, as the HbA2 level was lower. However, the red cell indices created a strong suspicion for a coexistent beta-thalassemia. So a parental study was sought, luckily both were available. The mother was diagnosed as a case of sickle cell trait and the father, a beta-thalassemia carrier. The normal HbA2 level, in this case, was likely due to the co-existence of an alpha thalassemia trait; so, for confirmation, a genetic study was advised. Can the case be that of an alpha thalassemia trait? It is very difficult to tell. Patients with Hb H disease (deletion of three alpha genes) present either in childhood with anemia, splenomegaly or the diagnosis is made incidentally in adult life. However, in both cases, the Hb H peak is found in HPLC and the diagnosis is straightforward. But, it should be borne in mind that the Hb H peak is not integrated in the beta-thalassemia short program and therefore likely to be missed if separately not searched for. The Hb%, peripheral smear findings and most importantly diminished A2 percentage in otherwise unremarkable HPLC should arouse prompt suspicion, to search for a suitable cause. Demonstration of Characteristic Golf ball inclusions by supra-vital stain can aid in diagnosis.1 It is also important to remember, that iron deficiency can completely mask the disease.5 α+ heterozygote(αα/α-) and α+ homozygote(α-/α-) cannot be detected by HPLC and most often Red cell indices are also normal.4 α0 trait (αα/--) is also very difficult to diagnose by HPLC but the altered red cell indices in the otherwise normal individuals should arise suspicion. Molecular genetic study is the only resort for diagnosis here.4 As HPLC-based screening cannot efficiently diagnose the carrier state of alpha thalassemia, the occurrence of HbH disease and Hydropsfetalis cannot be prevented by HPLC-based screening protocol. In our case, the red cell indices pointed towards a carrier state of thalassemia syndrome. Coupled with the diminished Hb A2 percentage, it gave rise to a strong suspicion as the iron-folate profile was almost normal, and the patient was referred for a genetic study to rule out an alpha-thalassemia trait. Mutational Spectrum and molecular diagnosis: Panigrahi I et al. have studied the mutational spectrum of thalassemia syndromes in India6, whereas Sinha et al. focussed on the regional and state-level diversity of the spectrum.71) IVS 1-5 G→C, 2) IVS 1-1 G→T, 3) mutation of codon 41/42, 4) mutation of codon 819, 5) 619 bp deletion are the common mutations found in case of beta-thalassemia. On the other hand, 1)-α4.2, 2)-α3.7, 3)-αSA, 4)Hb Koya Dora are the common aberrations found in alpha thalassemia. Mondal S K et al. have generated a valuable database on the prevalence of thalassemia in Eastern India, after studying more than a lakh cases over 10 years.8 The common method for molecular detection is usually based on PCR;- ARMS PCR for Beta-thalassemia and Gap PCR for alpha thalassemia. The issue of sickle cell disease has been addressed by the study of Serjeant G R et al.9  Sen R et al. have drawn our attention to the prevalence of alpha thalassemia cases in the tribal belts of India.10 Conclusion: It should remain clear what to expect from HPLC-based thalassemia screening and what to not. Although it is an efficient tool for screening beta-thalassemia traits, it cannot totally rule out the presence of a thalassemia carrier state, owing to the extreme heterogeneity of causative mutations and their more complicated genotype-phenotype correlation. Moreover, the alpha thalassemia traits are easy to miss. Ancillary studies including parental and sibling screening, other electrophoresis-based methods or genetic studies for mutation analysis are to be advocated in appropriate settings. The genetic studies may also reveal inconclusive results; as in most of the molecular biology labs, a handful of tools are employed to rule out only the most common genetic aberrations present, based on the local prevalence patterns. Acknowledgment: Authors acknowledge the immense help received from the scholars whose articles are cited and included in references of this manuscript. The authors are also grateful to the authors/editors/publishers of all those articles, journals, and books from which the literature for this article has been reviewed and discussed. Authors’ Contribution: Dr Sarbashis Hota- Conceptualization of the topic, Collection of Data, Review of Literature, manuscript writing. Dr TusharKanti Das- Overall guidance and supervision, Design of the framework of manuscript, contributing author in the discussion, necessary correction and guidance for final submission. Englishhttp://ijcrr.com/abstract.php?article_id=4337http://ijcrr.com/article_html.php?did=4337 Bain B J, Bates I, Laffan M A. Dacie & Lewis Practical Haematology, twelfth edition. Elsevier, 2017 Prevention and control of Hemoglobinopathies in India- Thalassemias, Sickle cell Disease and another variant Hemoglobins-National Health Mission guidelines on hemoglobinopathies in India- Ministry of Health and Family Welfare, Govt of India, 2016. Manual of Bio-Rad II HPLC machine, Bio-Rad India Private Limited, 2006. Hemoglobinopathies: Current Practices for Screening, Confirmation and Follow up. Association of Public Health Laboratories. CDC. December 2015.  Bain B J, Haemoglobinopathy diagnosis, Third edition. Wiley Blackwell, 2020. Panigrahi I, Marwaha R K. Mutational spectrum of thalassemias in India. Indian J Hum Genet. 2007 Jan-Apr; 13(1): 36-37. Sinha S, Black M L, Agarwal S, Colah R, Das R, Ryan K et al. Profiling beta-thalassemia mutations in India at state and regional levels: implications for genetic education, screening and counseling programs. Hugo J. 2009 Dec; 3(1-4): 51-62. Mondal S K, Mondal S. Prevalence of thalassemia and hemoglobinopathy in Eastern India: A 10-year high-performance liquid chromatography study of 119,336 cases. Asian J Transfusion Sci. Jan-Jun; 10(1): 105-110. Serjeant G R, Ghosh K, Patel J. Sickle cell disease in India: A perspective. Indian J Med Res. 2016 Jan; 143(1): 21-24 Sen R, Chakrabarti S, Sengupta B, De M, Haldar A, Poddar S et al. Alpha –thalassemia among tribal populations of Eastern India. Hemoglobin. 2005; 29(4):277-80.

Radiance Research AcademyInternational Journal of Current Research and Review2231-21960975-5241143EnglishN2022February1HealthcareRaspberry Pi (Python AI) for Plant Disease Detection English3642Shagufta AftabEnglish Chaman LalEnglish Suresh Kumar BeejalEnglish Ambreen FatimaEnglishThe diagnosis of diseases at an early stage is the main goal of this paper. We concentrate on image processing techniques in this research. This entails a range of processes ranging from taking a picture of the leaves to using Raspberry PI to diagnose the condition. The Raspberry PI is used to connect the camera to the display device, from which the data is sent to the cloud. Various procedures, such as acquisition, pre-processing, segmentation, and clustering, are used to examine the acquired images. As a result, the demand for labour in big farm areas is reduced. Also, the cost and effort are reduced, whereas productivity is increased. Various procedures, such as acquisition, pre-processing, segmentation, and clustering, are used to examine the acquired images. As a result, the demand for labour on huge farmlands is reduced. Costs and efforts are also minimized, while production is raised. English Raspberry PI, segmentation, Image-processing, Artificial intelligence, Clustering, Disease detectionIntroduction This current paper provides motivation and a brief overview of our study. In terms of monitoring the crops of large farms with minimum staff, presently, technology adoption in farming has shown quantitative outcomes in agricultural productivity. The agriculture sector has been changed by the Internet of Things (IoT), Cloud Computing, Artificial Intelligence, and Computer Vision, which have all helped to boost productivity over time with minimal investment. The failure to diagnose agricultural diseases in their early stages is a key worry that has a negative impact on crop output. In most cases, crop disease identification is done manually. In general, crop disease detection is done by hand, and it is impossible to identify crop illnesses without the help of experts who have acquired knowledge about the signs and causes of the diseases. The importance of accurate and timely illness detection, as well as early prevention, has never been greater in this changing world. Plant diseases can be detected in a variety of methods. Some diseases have no visible symptoms, or the damage becomes apparent too late to intervene, necessitating a thorough investigation. However, because most diseases exhibit themselves in the visible spectrum, a skilled professional's naked eye examination is the primary method for detecting plant diseases in practice. A plant pathologist must have good observation skills to recognize distinctive symptoms to diagnose plant diseases accurately7. In this regard, an automated system that can identify plant illnesses based on the look and visual symptoms of the plant might be extremely useful to both amateur gardeners and skilled professionals as a disease diagnosis verification system. An automated system that could identify plant illnesses based on the appearance and visual symptoms of the plant might be extremely useful to both amateur gardeners and skilled professionals as a disease diagnosis verification system. The suggested approach uses machine learning to detect and classify various plant leaf diseases3, 10. There are four primary steps in the plan. The segmentation process begins with the creation of a colour transformation structure for the input RGB image, followed by the masking and removal of the green pixels using a certain threshold value, and finally the segmentation process. For the effective segments, texture statistics are generated, and the retrieved features are then fed to the classifier. BACKGROUND There has been a slew of earlier studies on plant categorization using picture data and technologies like Probabilistic Neural Networks (PNN) and Support Vector Machines (SVM). Using image processing techniques15, plant diseases can be detected. A digital camera is used to capture photographs of the plant, which is connected to the Raspberry Pi board4. To obtain the features for further analysis, various image processing techniques are applied to the acquired image13. A series of processes are included in this image processing procedure mentioned below. IMAGE ACQUISITION: The camera module captures the RGB photos from the plant. Because the camera has a resolution of 21 megapixels, the RGB photographs are quite clear. TRANSFORMING A RGB IMAGE TO HSV FORMAT: The RGB pictures are transformed to Hue Saturation Value, a colour space that is an excellent tool for colour perception. RGB is used as an ideal representation for colour creation. Like the observer's perseverance, the hue is nothing more than a colour characteristic that expresses pure colour. Saturation, also known as relative purity, is the representation of the quantity of white light added to the hue of the image. The amplitude of light is referred to as its value. The Hue component is included in the analysis, but the Saturation and Value components are excluded because they do not contribute any further information.  PIXEL MASKING IN GREEN: Masking is the process of altering a pixel's background value to zero or any other value in a picture. This step detects the pixels that are mostly green in colour. 4. REMOVING GREEM PIXEL MASKS: The green pixels are then set to zero based on the provided threshold value computed for the pixels. RGB component mapping assigns a value of zero to the pixel's red, green, and blue components. Because the healthy portions of the leaf are represented by green-colored pixels, they do not aid in disease identification. 5. COMPONENT SEGMENTATION: The contaminated area of the leaf is excised and split into several equal-sized segments. 6. COLLECTING THE IMPORTANT SECTIONS FROM THE PROCESS IMAGE: There is no relevant information in any of the portions. For analysis, only segments with a significant amount of data are chosen. 7. COLOR CO-OCCURENCE METHOD: The texture features are produced from the statistical distribution of observed intensities at specified points in the image. 8. EVALUATE THE TEXTURE STATISTICS: For the color content of the image, the contrast, local homogeneity, energy, and correlation are computed. The contrast function returns the difference in intensity between a pixel and its neighbors. RELATED WORK Plant diseases have a significant impact on the growth of their individual species, hence early detection is essential. Machine Learning (ML) models have been used to detect and classify plant illnesses1,6,9. but with recent advances in a subset of ML, Deep Learning (DL) 2, this area of research appears to have a lot of promise in terms of improved accuracy. To detect and classify the symptoms of plant illnesses, several developed/modified DL architectures 14, as well as many visualization techniques, are used. In addition, these architectures/techniques are evaluated using a variety of performance measures. The DL models used to illustrate numerous plant diseases are thoroughly explained in this article 5, 8. Furthermore, several research gaps have been uncovered, allowing for increased transparency in detecting plant illnesses even before symptoms show. Laboratory-based tests are used in direct detection approaches. Indirect methods, on the other hand, rely on sophisticated methodologies with a focus on imaging tool integration. Indirect approaches rely on the on-site integration of sensors and smart devices to give a faster and more accurate method of illness identification. Early detection of apparent plant illnesses is critical, as it allows farmers to take the necessary actions to save the damaged plant. If early detection is possible, the percentage of damaged fruits can be reduced dramatically while still maintaining excellent production standards. a. DIRECT METHODS When a pathogen infects a plant, the DNA of the plant is altered, and the pathogen produces and introduces a specific type of protein molecule to the plant. Direct methods use molecular and serological techniques to look for pathogen DNA or pathogen-produced protein molecules in the plant's biological structure. Polymerase chain reaction (PCR) and enzyme-linked immunosorbent assay (ELIA) are two often-used procedures (ELISA). The genetic material (DNA) of the bacteria causing the disease is extracted utilizing PCR-based disease detection. After the DNA has been purified and amplified, it is run through gel electrophoresis. After the DNA has been purified and amplified, gel electrophoresis is carried out. The presence of a specific brand in the gel electrophoresis verifies the existence of the plant disease organism 13. Although these procedures are reliable and accurate in detecting plant diseases [fig: 1], they have several disadvantages. These methods rely largely on expensive laboratory equipment and lengthy experiments, both of which can be time-consuming and labor-intensive. To ensure trustworthy and precise results, sample preparation takes a significant amount of time and work. Because of the usage of consumable reagents that are individually formulated for each pathogen, these procedures are also quite expensive 12. As a preliminary screening tool for processing huge numbers of plant samples, better and faster disease detection technologies are required. b. INDIRECT METHODS It was studied whether new automated non-destructive technologies could be used to detect plant disease symptoms early and with high sensitivity to specific diseases. These technologies should be able to detect illnesses and stressors in real-time in the field. The imaging technique is a popular method. Researchers applied deep learning architectures [fig: 2] to image recognition and classification as they evolved over time 11. These structures have been used in a variety of agricultural applications as well. The performance of an author-modified CNN and Random Forest (RF) classifier was tested through CA at 97.3 percent in the classification of leaves among 32 species. c. CONVOLUTIONAL NEURAL NETWORK Using deep learning approaches, convolutional neural network models were constructed to detect and diagnose plant diseases using simple leaf photos of healthy and ill plants. The models were trained using an open collection of 87,848 photos, which included 25 different plants in 58 different classes of [plant, illness] pairs, including healthy plants. Several model architectures were trained, with the top performing one achieving a success rate of 99.53 percent in detecting the corresponding [plant, illness] pair (or healthy plant). The model's high success rate makes it a valuable advising or early warning tool, as well as a technique that might be expanded to support an integrated plant disease diagnosis system that can operate in real-world situations. system requirement a. OPEN CV Open CV is a cross-platform library for developing real-time computer vision apps. It primarily focuses on image processing, video recording, and analysis, including capabilities such as face and object detection. It is critical in real-time operation, which is critical in today's systems. It may be used to process photos and videos to recognize items, faces, and even human handwriting. b. TENSOR FLOW The feature extraction network must accurately extract the properties of the disease image to achieve a high disease recognition rate. Tensor flow is used to do this. The convolutional neural network, as a deep learning model, is capable of hierarchical learning and excels at feature extraction. The Tensor flow Object Detection API is used in our project. Tensor flow’s object detection API provides a framework for building a deep learning network that can tackle object detection challenges. In their framework, which they call Model Zoo, there are already pertained models. This comprises models that have been pre-trained using the COCO, KITTI, and Open Images datasets. If we're solely interested in categories, these models can be employed for inference this collection of information. They're also useful for training on a new dataset and initializing your models. For a clear image, we employ a 5-megapixel camera that concentrates on plants. It connects to the Raspberry PI 4 board via USB. METHODOLOGY a. DATA COLLECTION The disease's exact location is then retrieved from the image and saved as an XML file.  b. MODEL IMPLEMENTATION The information is fed into the API, which employs the Mobile-NET SSD (Single Shot MultiBox Detector) feature extractor for real-time detection and the FASTER RCNN for single image detection. The API will iterate over the image until we're happy with the outcome. c. MODEL TESTING The model is then tested using testing photos when the training is done. RESULT AND ANALYSIS If the user hasn't already logged in, this is the first window that will open [fig: 3]. This has two primary buttons login and signup, which allow users to log in or register to enjoy the system's features. This is the main graphical user interface [fig: 4], through which the user can choose from a variety of settings. By clicking on the open picture button, the user can choose a leaf image [fig: 5], as illustrated in figure. This window will appear if you touch/click the “Run Detection” button. To begin detecting the image you just opened above, press "No" [figure: 6]. When the detection is finished, you will be asked if you wish to view the image that was detected or not. To see what the system detects, press "Yes" in [figure: 7]. In [figure: 8], shows, the system detects the plant and the type of disease it has. Small, light to dark green, round to irregularly shaped water-soaked dots are the earliest signs of late blight in the field [fig: 9]. Although the symptoms are similar, the treatment method differs. The steps below should be followed: Always purchase new seed potatoes that are certified, and disease-free. Keep developing tubers covered with soil. Protectant fungicides, like chlorothalonil and fixed copper, can help protect foliage if applied prior to infection. Small, yellow-green lesions on young leaves that are frequently distorted and twisted, or black, water-soaked, greasy-appearing lesions on older foliage [fig: 10], are the first signs. The steps below should be followed: Select resistant varieties Seed and transplants that are disease-free should be purchased. Soak seeds in a 10% chlorine bleach solution for 2 minutes to treat them (1 part bleach; 9 parts water). Before planting, thoroughly rinse and dry the seeds. Plants should be mulched deeply with a thick organic substance such as newspaper coated in straw or grass clippings. Avoid overhead watering. At the conclusion of the season, remove and destroy any sick plant parts as well as all trash. To inhibit the spread of infection, spray with fixed copper (organic fungicide) every 10-14 days. If infections are severe, move peppers to a different site and cover the soil with black plastic mulch or black landscape cloth before planting. These are some of the plant disease detection results. DATAFLOW DIAGRAM [Figure: 11] shows a data flow diagram that explains the system's operation. When the system starts, it sends a command to capture an image, then image processing begins, and the illness name is shown. USE CASE DIAGRAM The flow of work is depicted in the diagram [fig: 12]. To access the system's features, the user must be logged in. The system gives the user two choices: 1. To use a photograph to do detection. He or she can take pictures using a pi4 camera. 2. Alternatively, you can employ real-time detection. The sickness will be detected in real-time because of this. FEATURES OF THE SYSTEM The suggested system uses image processing to detect plant illness. The system is user-friendly; we can quickly obtain data from collected images. The recognized image is saved in the system's database for future usage. The accuracy of the system can be improved by data entry and picture processing of big data sets. With further modifications, this system will benefit society in the future. The system has a 99.99 percent accuracy level. CONCLUSION We developed a classification approach for picture-based plant identification and content-based image retrieval challenges in this research. To detect plant diseases, the Tensor flow Object Detection API is employed. Two alternative models, Faster RCNN for improved accuracy and SSD Mobile net for disease detection in real-time, were trained on diverse plant illnesses and their healthy states. By putting our models to the test, we can assess how well they can detect different plant illnesses given a picture. The model's accuracy is also mentioned, which is sufficient for detecting practically every plant disease. Different detections are shown to evaluate the model's accuracy. Tomatoes, potatoes, and bell peppers may all be tested for illnesses with this approach. ACKNOWLEDGEMENT: Nil Source of Funding: Nil Conflict of Interest: Nil Author’s contribution: Shagufta Aftab: data collection. Chaman lal: writing of first and final drafts. Suresh Kumar B: Manuscript Editing. Ambreen Fatima: data collection. Englishhttp://ijcrr.com/abstract.php?article_id=4338http://ijcrr.com/article_html.php?did=43381.    Shruthi U, Nagaveni V, Raghavendra BK. A review on machine learning classification techniques for plant disease detection. In2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS) 2019 Mar 15 (pp. 281-284). 2.    Nagaraju M, Chawla P. Systematic review of deep learning techniques in plant disease detection. Int Journal of Syst Assur Eng Manag, 2020 Jun;11(3):547-60. 3.    Deepika P, Kaliraj S. A Survey on Pest and Disease Monitoring of Crops. In2021 3rd International Conference on Signal Processing and Communication (ICPSC) 2021 May 13 (pp. 156-160). 4.    Sankaran S, Mishra A, Ehsani R, Davis C. A review of advanced techniques for detecting plant diseases. Computers and electronics in agriculture. 2010 Jun 1;72(1):1-3. 5.    Tiwari D, Ashish M, Gangwar N, Sharma A, Patel S, Bhardwaj S. Potato leaf diseases detection using deep learning. In2020 4th International Conference on Intelligent Computing and Control Systems (ICICCS) 2020 May 13 (pp. 461-466). 6.    Ahmed K, Shahidi TR, Alam SM, Momen S. Rice leaf disease detection using machine learning techniques. In2019 International Conference on Sustainable Technologies for Industry 4.0 (STI) 2019 Dec 24 (pp. 1-5). 7.    Durmu? H, Güne? EO, K?rc? M. Disease detection on the leaves of the tomato plants by using deep learning. In2017 6th International Conference on Agro-Geoinformatics 2017 Aug 7 (pp. 1-5). 8.    Durmu? H, Güne? EO, K?rc? M. Disease detection on the leaves of the tomato plants by using deep learning. In2017 6th International Conference on Agro-Geoinformatics 2017 Aug 7 (pp. 1-5). 9.    Harish S, Gayathri KS. Smart Home-based Prediction of Symptoms of Alzheimer’s Disease using Machine Learning and Contextual Approach. In2019 International Conference on Computational Intelligence in Data Science (ICCIDS) 2019 Feb 21 (pp. 1-6). 10.  Soni H, Arora P, Rajeswari D. Malicious Application Detection in Android using Machine Learning. In2020 International Conference on Communication and Signal Processing (ICCSP) 2020 Jul 28 (pp. 0846-0848). 11.  Valdoria JC, Caballeo AR, Fernandez BI, Condino JM. iDahon: An android based terrestrial plant disease detection mobile application through digital image processing using deep learning neural network algorithm. In2019 4th International Conference on Information Technology (InCIT) 2019 Oct 24 (pp. 94-98). 12. Ramesh S, Hebbar R, Niveditha M, Pooja R, Shashank N, Vinod PV. Plant disease detection using machine learning. In2018 International conference on design innovations for 3Cs compute communicate control (ICDI3C) 2018 Apr 25 (pp. 41-45). 13.  Kusumo BS, Heryana A, Mahendra O, Pardede HF. Machine learning-based for automatic detection of corn-plant diseases using image processing. In2018 International Conference on Computer, Control, Informatics, and its Applications (IC3INA) 2018 Nov 1 (pp. 93-97). 14. Modem Amarendhar R, M. James S, P.V.G.D Prasad R. Analysis of COVID-19 Complications Using Deep Learning-Based Neuro-Fuzzy Classification Approach. Int J Cur Res Rev. 13(20), October, 2021, 85-89, 15. Nanditha B R, Geetha Kiran A. A Review on Imaging Modalities and Techniques for Oral Malignancy Detection Int J of Cur Res Rev. 13(20), October, 71-78.

Radiance Research AcademyInternational Journal of Current Research and Review2231-21960975-5241143EnglishN2022February1HealthcareIndian Healthcare Sector and the Sustainable Development English4347Tavseef Ahmad MirEnglish Manvendra SinghEnglishSustainable development is one of the fundamental aims of health. Health itself is both a result and a contribution to development. Health is a crucial component in the right, people-centred, egalitarian, and inclusive approach to development. It is a vital part of human life due to material, psychological, social, cultural, educational, professional, political, and personal aspects of security. All these aspects are connected and interdependent. Investments in whatever form, in any part, necessarily improve other constituent quality standards. Many advances have been made in this sector under the era of Millennium Development Goals (MDGs). India has met with some progress in reduction of infant mortality rate, from 125 per 1,000 live births in 1990- 91 to 50 per 1,000 live births in 2015-16, and the maternal death rate reduced from 212 per 100000 live births in 2007-09 to 167 in 2013. Nevertheless, the scope exists to address the gaps in policy implementation at the ground level. New goals and targets have been set for us by Sustainable Development Goals (SDG). In addition, the COVID-19 outbreak has made it crucial for policymakers to reconsider our country’s health policies and services.2 This study is a genuine analysis of the health-related sustainability goals and current health care structures and procedures in India and proposes solutions for making healthcare truly universal and consistent with sustainable development objectives. EnglishSustainable development, Healthcare, Policy, National Health Policy, COVID-19 outbreak, Policy implementationIntroduction Sustainable Development means development aimed at meeting present needs without compromising the potential of forthcoming generations to satiate their own necessities. Sustainable development maintains economic advancement and progression while protecting the environment by assimilation of environmental and developmental policies. There is an appreciation of our natural resource scarcities.1 Truly rational, welfare-oriented, and effective governance requires a nation to consider policies that protect the environment and health of the citizens on which its whole march of progress depends. The developmental approach, not taking human health into account, is counterproductive. The nexus between health and development provides a powerful basis for having a sustainable healthcare system. Components of a sustainable system are quality infrastructure and a healthy personnel environment, accounted as public goods as they are non-competitive and non-exclusionary.  It is the primary duty of the public sector to run and regulate these goods and services. More recently, countries have adopted market-based mechanisms to provide healthcare facilities to the public.  The overall motto of sustainable development is consistent economic and environmental stability, which is only possible through the proper analysis and acceptance of concerns related to economic, environmental, and social aspects of the decision-making process. Principles of Sustainable Development have participative decision-making at its core. It is this deeply ingrained concept of integrativeness that differentiates sustainability from other developmental policies.  It provides a working structure where society and the environment get mutually benefitted without damaging the environment. Thus, it is a developmental pathway and a conception that steers towards upgrading standards of living without injuring the earth’s ecological balance. Sustainable development decisions based upon judicious management of resources results in ever-lasting development for the society. These include decisions related to the allocation and management of resources available on this planet. Economic sustainability ensures a production and consumption system that satisfies present needs through sustainable use of resources. While social sustainability signifies equity, upliftment, availability, participation, and stability of institutions. This concept emphasises that human matter as development is all about them as it signifies a social organization system that reduces poverty and lifts the living standards. The sustainable development goals relate to the tenets regarding fulfilment of developmental aspirations along with maintaining the consistent capacity of natural systems to replenish the resources. Though the idea of sustainable development is in vogue since times, its relevance deepens with every passing day as only the number of humans keeps on increasing, while other resources get diminished day after day. Concerned about this phenomenon, international level arrangements and programmes have been formulated regarding the adoption of sustainability principles. Sustainable Development Goals The adoption of Millennium Development Goals (MDGs) signified a major paradigm shift in global political will for the elimination of poverty and the wellbeing of the people. Since the MDGs were conceived, new changes emerged like the rate of environmental degradation increased, inequality has deepened, and the unemployment rate has grown. People across the world are asking for more participative governments and better governance. These striking challenges have necessitated the formulation of global goals. The Seventeen Sustainable Development Goals collectively called Sustainable Development Goals try to achieve the following targets.3 Eradication of poverty as well as hunger levels, universalisation of accessible basic services like drinking water, hygiene, inclusive education, as well as dignified work. Encouragement of new ideas and buoyant infrastructural systems that can produce and consume sustainably. Reduction of inequality on basis of economic potentials and social belonging in the world. Protection of ecological integrity by taking measures for combatting various environmental disasters. Promotion of collaborative practices between various stakeholders for ensuring peaceful production and consumption of goods and services. Agenda 2030 has five main themes which include people, planet, prosperity, peace, and partnerships covering the seventeen sustainable development goals. They are aimed at fulfilling the vision of sustained development. It has received a lot of focus in academics, particularly in the areas of management, planning and development interventions. Many organizations working with the government or otherwise have adopted it as a feasible developmental model.4 It is because most of the advocates of this model seem to accept that the challenges faced by the people such as drastic climatic changes, ozone layer deterioration, water shortage, and poverty can be remedied by adopting the tenets of this paradigm. Economy, society, and environment form the elements of this development process of an ecosystem so this process cannot be carried out in watertight chambers. All decisions need to be aimed at promoting the overall positive and balanced growth of the system. Though sustainable development is considered a serious issue by everyone, international, national, regional organizations, civil society, and government organizations are considered to express concern through the modes of stewardship, partnerships, participation and proprietorship. Health has been recognized as one of the primary concerns for international progress for the last twenty years, during which many initiatives were undertaken to reduce morbidity and mortality either for the whole of the population or through focused programmes on targeted subgroups (like “the poor, women and children"). The Millennium Development Goals (MDGs)formulated in 2000, comprised of health-oriented goals to be achieved by 2015 were reduction in infant (under five years) death rate (Goal 4), reduction in maternal death rate and availability of reproductive health services (goal 5), and preventing the spread of HIV, tuberculosis, and malaria (goal 6). They are important for the diversion of global resources towards developing and underdeveloped nations. The Sustainable Development Goals (SDGs) era gave healthcare a prominent space. The health goal (SDG 3) is wider in its ambit which states that governments must Ensure healthy lives and promote well-being for all ages.6 The statement emphasizes that to achieve the health goal, ‘we must achieve universal health coverage (UHC) and access to quality health care, and no one must be left deprived.  Universal Health Coverage is at the centre of the SDG 3 health goal. This goal acts as a contributor to as well as a beneficiary of sustainable development, with linkages to all the other Sustainable Development Goals. Achieving SDG 3 targets will depend on progress in other SDGs like reduction in poverty; education levels; nutrition standards; gender justice; clean drinking water and better sanitation facilities, sustainable use of energy resources and safer cities.7 Healthcare in India Sustainable Development Goals (SDGs) formulated by United Nations are to be followed by each member nation. India being its member is committed to meeting the targets of this framework. India’s ranking is down two places from last year to 117th about progress for meeting Sustainable Development Goals (SDGs). Over the next coming years, as these new targets are applied globally, countries have mobilized resources and efforts to end all poverty in all its forms, reduce inequality and tackle climate hazards. The Sustainable Development Goals build upon the successful results of the Millennium Development Goals and intend to further progress towards the removal of all forms of deprivation. The goals are special as they direct all countries to act to ensure prosperity and protect the planet. India has formulated its National Health Policy 2017 and meeting these goals is one of its objectives. The National Health Protection Scheme (Ayushman Bharat) was launched to cover the health expenditures of secondary and tertiary care of people living below the poverty lines. Opening of Jana Aushadhi Kendra which is a chain of pharmacy stores to provide medicines at doorsteps. These measures testify to the Indian government’s commitments towards the targets set up by sustainable development goals.7 Discussion NITI AAYOG, the main think tank for developmental planning, developed the Index for Sustainable Development Goals (SDGs), which scrutinises the progress of states and Union Territories (UT) for various parameters which include healthcare, education levels, gender justice, economic growth, institutions, measures to combat climate change, and the environment protection. It was first launched in December 2018 and became a key instrument for tracking the developmental path towards the Sustainable Development Goals in India. This contributed to the development of competition between states and their ranking according to global goals. The index was developed in partnership with the United Nations. It monitors all states and Union Territories on 115 metrics that are in tandem with the National Index System of the Ministry of Statistics and Program Implementation. This tool is important regarding dialogue, formulation, and implementation of targeted based initiatives. This helps to oversee important gaps in monitoring and to highlights the necessity of having indigenous statistical programmes in India.11 It helps identify weaknesses in the implementation of SDGs and the need for developing indigenous statistical systems. Kerala ranked first in the NITI Aayog India SDG Index 2020-21, while Haryana, Mizoram and Uttarakhand are the top achievers in improving their rankings since 2019. The global COVID19 pandemic has presented the Indian health care system with many challenges which this country is fighting with remarkable synergies between industry, civil society, and governments at different levels5. India has met with some progress in the reduction of infant mortality rate, from 125 per 1,000 live births in 1990- 91 to 50per 1,000 live births in 2015-16, and the maternal death rate reduced from 212 per 100000 live births in 2007-09 to 167 in 2013. India progressed in reducing the spread of HIV and AIDS in India various vulnerable categories, with prevalence declining from 0.45 percent in 2002 to 0.27 percent of the adult population in 2011. However, a quarter of the world’s tuberculosis cases are reported in India, where almost 2.1 million people get infected from this disease and approximately 423,000 die each year. Considering the different diversities of the country, its size, and the differential phases of development among regions, it is requisite to draw up local specific targets and programmes. Strong political commitment is fundamental to increased investment in health-related major policy reforms. Universal Insurance Program in Thailand, Health Transformation Program in Turkey and Obama Care in the United States signify strong political commitment towards the wellbeing of the citizens. Around 1.2 percent of the Gross Domestic Product (GDP) is spent upon public health in India, which is one of the lowest public health expenditures globally. Making “health” a citizen’s right can motivate policymakers to propose increased investment in healthcare, accelerate industry reform, and improve health outcomes. Several countries have recognized the right to health as a right governed by “civil society” movements and have recognized health as an electoral tool. India missed this opportunity when it proposed, Right to Health, in the National Health Policy-2017 but was taken out on the premises of health systems being not ready. However, evidence shows that considering health “A Fundamental Right” is necessary for the health system’s readiness. Health is currently a “state subject,” meaning that the state legislature is responsible for enforcing it. To ensure policy uniformity, effective coordination and response, and the ability to transfer health benefits uniformly across the country, there is a need to put health on the Concurrent List where both central and state governments would be responsible for the execution of various programmes. To improve centre-state cooperation and guide multiple actions, the role of the political executive on health-related issues is of high importance. At present, the National Health Mission Steering Group (NHMSG) is the apex policy-related guiding institution, the Central Council of Health and Family Welfare (CCHFW) takes care of logistics and advises the Department of Health on formulations of various policies. The scope of the NHMSG needs to be extended to the entire health sector by placing it under the chairmanship of the Prime Minister, with the union minister for Health and Family Welfare as co-chairman. Likewise, in sync with the vision of National Health Policy 2017, the role of the CCHFW needs to be widened about guiding health Sector Plans (HSPs)’. Healthcare is one of the rapidly growing industries in India, and despite being a prominent exporter of the health workforce to developed nations, the country itself faces a scarcity of doctors and nurses. Therefore, sharing best practices, providing participative roles, engaging with crucial stakeholders within and outside the health sector, building strategic partnerships with the private sector and voluntary organisations should be the focus of the Ministry of Health and Family Welfare. Measures need to be taken for strengthening the legal framework, health standards, and encouraging the best performers by rewarding them and how the developing of the human capital, information systems, and research. Vision needs to be redefined and goals standardized to help countries align with the overall goal of universal health coverage. Create a workable framework of implementation based on National Health Policy 2017 with a focus on activities, targets, goals, schedules, and accountabilities. This framework need not be rigid, it should provide adequate flexibility to states to modify the work plan according to the needs of the region and feedback tracking should be a built-in mechanism for programme modifications. Strategies and programs within the framework should converge into an integrated Universal Health Coverage with adequate resource allocation and monitoring. It will facilitate the introduction and promotion of the Universal Health Care program through a multi-tiered approach. “State Health Investment Plans” should be intermingled with State Health Plans to strengthen physical infrastructure, human resource capabilities, and other subsystems. These plans must reflect the reality of the health system of that region, with a focus upon building capacities, including middle-level service dispensers, employing private sector partners and ensuring the accessibility of essential drugs, vaccines, and other health supplies. An integrated health information system is essential, where every transaction can be recorded through a unique identification number linked with the Aadhar database to ensure smart service delivery. There is a need of strengthening primary healthcare centres for robust delivery of healthcare services. The NHP-2017 provision of establishing “Health and Wellness Centres” to provide a complete package of necessary services by a primary centre team led by a middle-level provider is a feasible working model in the Indian setup. These care providers need effective liaisons with upper-level care providers to ensure continuity of patient care. Recipients should have the right to choose the providers from whom they can avail the service and pay the initial fees. Innovative models based upon performance management framework can be introduced after the full implementation of the policy and increase in demand. The government needs to prioritize prevention and health promotion by allocation of more resources to address Non-Communicable Diseases, traffic accidents, and enhancing immunities. For instant effective management of health threats, building upon the learning from the “Integrated Disease Surveillance Programme,” which should be serviced by a well-coordinated chain of service providers, enablers, laboratories, hospitals, and surveillance units managed by the competent personnel. They should be in touch with a nationwide real-time networked information system operated by one main centre.10 To ensure access to basic health services by all, the government needs to develop a robust system with a pool of public funds that can ensure the provision of essential packages of health services to the citizens which would result in reducing burdens upon their pockets. The Government of India should ensure universal access to the specific package of essential services all over the country, with the state governments modifying services as per requirements within the state.8 Private health insurance should function as add on service to cover conditions not specified in governmental programmes. Evidence suggests that the “Purchaser Provider Split,” separates the roles of buyers and suppliers, resulting in benefits such as increased efficiency and reduced costs. Separation of the functioning of buyer and service provider leads to improvement in efficiency and cost reduction by agreeing upon better prices and regulation of quality. Under the Governmental structure of India, the purchasing agency must be at the state level with the support of the national standards body. As it is equally important to reduce health inefficiencies and improve public financial management.9 India’s mixed public-private health system has witnessed a steady decline in public services, because of the unregulated growth of formal and informal private service providers. To manage provider networks, government and national health agencies must have a vibrant information communication framework to monitor service provider working and aberration management. It will result in effective action to address ethical issues, including quality treatment, diagnostic teams, medical records, and payments. Conclusion World over experiences has shown that well-coordinated health sector reforms can contribute to "inclusive development" by enhancing the health and wellbeing of the citizens, eradicating inequities, and avoiding circumstances adversely affecting public health. Innovative policies and enhanced health financing can help achieve universal health coverage and make a country healthier. Progress on Universal Health Coverage cannot be made instantly. A basic principle for realising it is “progressive universalization,” starting with what is readily available and slowly adding health services and enhancing financial protection to the broader spectrum of the population as the healthcare system develops. In a larger perspective, the assimilation of the Sustainable Development Goals agenda into National HealthPolicy2017 and NITI Aayog Health Vision-2032has provided a historic opportunity for healthcare advancement. Healthcare in the country has become the highest priority, particularly after the outbreak of COVID-19 and not investing in this opportunity can have devastating consequences for the future. Primary and secondary levels of healthcare need upgrades in form of infrastructure and capable human resources. There is the utmost need of investing in healthcare and its allied industries. To touch the goalposts, set up by SDGs, it is necessary to make it more participative for other stakeholders as well. It is time to learn the lessons from the past, build on past achievements and tread upon a goal-oriented journey Source of funding: NA Conflict of Interest: None Authors’ Contribution: The first author collected data and framed the overall paper. Co-Author analysed the whole paper and framed the discussion part. Englishhttp://ijcrr.com/abstract.php?article_id=4339http://ijcrr.com/article_html.php?did=43391. Bartle J, Leuenberger D. The Idea of Sustainable Development in Public Administration. Public Works Management & Policy. 2006;10(3):191-194. 2. Ilesanmi F, Ilesanmi O, Afolabi A. The effects of the COVID-19 pandemic on food losses in the agricultural value chains in Africa: The Nigerian case study. Public Health in Practice. 2021; 2:100087. 3. Mensah J. Sustainable development: Meaning, history, principles, pillars, and implications for human action: Literature review. Cogent Social Sciences. 2019;5(1):1653531. 4. Meuleman L. Public Administration and Governance for the SDGs: Navigating between Change and Stability. Sustainability. 2021;13(11):5914. 5. Mishra A. COVID-19 in India: Impact on the Sustainable Development of Health Sector. SSRN Electronic Journal. 2020; 6. Onyango G, Ondiek J. Digitalization and Integration of Sustainable Development Goals (SGDs) in Public Organizations in Kenya. Public Organization Review. 2021;21(3):511-526. 7. Rashidian A. Effective health information systems for delivering the Sustainable Development Goals and the universal health coverage agenda. Eastern Mediterranean Health Journal (EMHJ). 2019;25(12):849-851 8. Reddy K, Mathur M, Negi S, Krishna B. Redefining public health leadership in the sustainable development goal era. Health Policy and Planning. 2017;32(5):757-759 9. Seke K, Petrovic N, Jeremic V, Vukmirovic J, Kilibarda B, Martic M. Sustainable development and public health: rating European countries. BMC Public Health. 2013;13(1). 10. Singh Z. Sustainable development goals: Challenges and opportunities. Indian J. Public Health. 2016;60(4):247. 11. Strong K, Noor A, Aponte J, Banerjee A, Cibulskis R, Diaz T et al. Monitoring the status of selected health-related sustainable development goals: methods and projections to 2030. Global Health Action. 2020;13(1):1846903.

Radiance Research AcademyInternational Journal of Current Research and Review2231-21960975-5241143EnglishN2022February1HealthcareUtility of Direct Detection of MEC a Gene in Clinical Specimen for Detection of Methicillin-Resistant Staphylococcus aureus English4852Sevitha BhatEnglish Gopalkrishna Bhat KEnglish Shalini Shenoy MEnglish Archana Bhat KEnglish Pooja RaoEnglishIntroduction: MRSA: Major cause of health care associated infections (HA-MRSA). The alarming rise in the rates of HA-MRSA reported from this region necessitates the need for a DNA based assay. Real-time PCR: rapid platform or detection of MRSA. The study plans to compare culture to real-time PCR for the detection of MRSA directly in the clinical specimen Objectives: The present study aimed to isolate and identify MRSA from clinical specimen, to detect mec A gene in the clinical specimen and to compare direct detection of mec Agene with culture for Staphylococcus aureus Methods: Cross-sectional hospital based study was undertaken noninvasive samples (blood, deep tissue, aspirated pus, sterile body fluids) received for culture. The results of PCR and culture were compared in terms of sensitivity, specificity, PPV, NPV. Results: 110 non-duplicate clinical samples were included. MRSA rate: 29%. The rates of isolation were 74.6%: skin and soft tissue infections, 11% from blood stream infections, 10.4% from osteomyelitis cases, 4% respiratory secretions. Antibiotic resistance rates of MRSA ciprofloxacin(75%), clindamycin (51.1%), trimethoprim sulfamethoxazole (59.1%) and erythromycin (62.5%). 100% of the isolates were sensitive to Vancomycin. PCR for MRSA detection: Sensitivity: 97%, Specificity: 98% Discussion: This study demonstrates the utility of a rapid platform: real-time PCR for the detection of MRSA from clinical samples directly on the same day. The results of Gram stain were used as criteria for selection of samples. EnglishMRSA, Real time PCR, Direct detection, Antibiotic resistance, Invasive samples, Molecular methodsIntroduction MRSA has emerged as a common healthcare-associated pathogen and is implicated in infections ranging from superficial skin infections to sepsis.  HA-MRSA have limited therapeutic options and can be transmitted among patients. The detection of MRSA by conventional methods like culture requires 2 or more days. The real-time PCR platform offers the advantage as a rapid test for detecting MRSA in clinical samples within 2 hours. Thus real-time PCR would enable early detection of MRSA. This approach would supplement the infection control practice by rapidly identifying MRSA strains in clinical specimens directly. The proposed study was done to compare culture with real-time PCR, using primers specific for S. aureus and MRSA (femA, mecA). Present knowledge/Background Staphylococcus aureus is implicated in skin, soft tissue infections and invasive infections like cellulitis, pneumonia, endocarditis, bacteremia, septic shock.1 Methicillin-resistant S. aureus (MRSA) strains have emerged as a global threat to Infection control. MRSA infections are associated with higher morbidity, mortality and higher costs. Health care-associated infections (HA -MRSA) are a cause of concern because they are often resistant to multiple classes of antibiotics.2,3 The mechanism of resistance to Methicillin in staphylococcus aureusis by insertion of staphylococcal cassette chromosome carrying mec A gene which encodes for PBP 2 a.4 The overall HA-MRSA prevalence reported in previous studies were 41.9 % in 2008 (Pakistan), 53% in 2011(Thailand).5,6 The INSAR study reported 42% MRSA rates in 2008.7 HA-MRSA rates have increased from 23.9% in 2013 to 30.2% in 2016 in a tertiary care centre in Mangaluru.8 Clindamycin, tetracycline(doxycycline and minocycline), trimethoprim and sulfamethoxazole, rifampicin, linezolid and Vancomycin are the antibiotics of choice to deal with MRSA. The conventional methods employed for MRSA detection are Oxacillin agar screen, Cefoxitin disc diffusion method and Oxacillin broth dilution method. These conventional methods yield false negative and positive results.9, 10 The alarming rise in the rates of HA- MRSA reported from this region necessitates the need for a DNA-based assay, which would provide a solution the detection of MRSA. Rapid detection of MRSA infections would help in better implementation of Infection control practices.11,12 The investigation compares culture with real-time PCR for direct detection of MRSA in the clinical specimen. Preliminary work A study was conducted in this setup on HA-MRSA. The prevalence of HA-MRSA in our center was reported as 30.2%. Among these, 54.6% of the HA-MRSA were isolated from skin and soft tissue infections, 8.6% from bloodstream infections and 5.2% from osteomyelitis cases. The antibiotic resistance rates of HA- MRSA were clindamycin (51.1%), trimethoprim-sulfamethoxazole (59.1%) ciprofloxacin (75%), and 95.5% of the isolates were sensitive to Vancomycin .13 The rate of HA-MRSA is high in this region. Thus there is a need for further studies on rapid detection of MRSA in hospitals. Aim To study the usefulness of direct mec A gene detection in clinical samples in the identification of Methicillin-resistant Staphylococcus aureus (MRSA) Objectives To isolate and identify MRSA from clinical specimen To detect mec A gene in the clinical specimen To compare the results of PCR with culture for the detection of MRSA Methodology STUDY SETTING: Department of Microbiology, KMC Hospital, Ambedkar Circle, Mangalore STUDY DESIGN:   Cross-sectional study. Sample collection Inclusion criteria: Invasive samples (blood, deep tissue, aspirated pus, bronchoalveolar lavage, sterile body fluids) received for culture with Gram stain suggestive of presence of Staphylococcus Exclusion Criteria: Samples: swabs, sputum, urine, STUDY DURATION:  1 year (prospectively). SAMPLE SIZE: 110 based on the following calculations: Formula used is N = ( Zα2 pq )/E2 .Z is at  95% confidence, p is the relative precision;  p=37, q is the confidence interval; q=63, E = 20% of the relative precision (p),80% power15 DATA COLLECTION: The clinical details were collected using a proforma from the case sheets of the patients. DATA ANALYSIS: Chi-square is done for categorical variables and only those with p-value < 0.05 is statistically significant, following which analyzed data is presented in the form of tables, pie charts and bar diagrams. Results of PCR were compared with culture in terms of positive predictive value, negative predictive value, sensitivity and specificity SAMPLE COLLECTION: Gram stain was performed and the samples were plated onto culture plates and incubated at 370C overnight. Blood culture was done by BacT/Alert 3 D automated system and growth from early subculture was taken. The bacterial growth was identified by standard tests. ANTIBIOTIC SUSCEPTIBILITY TESTING: Antibiotic sensitivity testing was done by the Modified Kirby-Bauer disk diffusion method and Automated Vitek 2 system. The results were analyzed and interpreted in accordance with Clinical Laboratory Standards Institute (CLSI) recommendations.16 S.aureus ATCC 25923 is used for quality control. Cefoxitin (30μg) disk diffusion method for used for MRSA detection. PCR DNA Extraction: modification of a QIAamp blood and tissue kit (QIAGEN), following the instructions in the kit insert. Real-time PCR: using Microbial q PCR Assay (Qiagen) The primer sequence of MecA1 (5´GTA GAA ATG ACT GAA CGT CCG ATAA) and MecA2 (5´CCA ATT CCA CAT TGT TTC GGTCTA A), yielding a 310-bp amplicon, FemB1 (5´TTA CAG AGTTAA CTG TTA CC) and FemB2 (5´ATA CAA ATC CAG CAC GCT CT),  The 20µl real-time PCR reaction with 1X Light CyclerFastsart DNA Master SYBR Green I (containing a modified Taq polymerase with heat-labile blocking groups), 2% DMSO (Sigma), 5 mmol/L MgCl2 and 0.25 µmol/L of each primer. The real-time PCR conditions are an initial step of 95°C for 10 minutes, an amplification program for 40 cycles of 15 seconds at 95°C(denaturation ), and 2 minutes at 60°C with fluorescence acquisition at the end of each extension. (green channel ) 17,18 Results 110 clinical non-duplicate samples were included. The site of infection of MRSA and the antibiotic resistance rates of Staphylococcus aureus are shown in Figures 1 and 2. The comparison of Culture with PCR is shown in Table 1. 32 out of 110 were culture positive for MRSA and 62 out of 110 were culture positive for MSSA.16 samples had no growth, could be due to antibiotic effect. 74.6%: skin and soft tissue infections,11% from bloodstream infections, 10.4% from osteomyelitis cases, 4% from respiratory secretions Antibiotic resistance rates of the 94 isolates of Staphylococcus aureus: ciprofloxacin (88%), clindamycin (45%), trimethoprim-sulfamethoxazole (59.1%) and erythromycin (65%), Vancomycin (0%) and MRSA rate: 29% Discussion Staphylococcus aureus is implicated in variety of human infections. The problem is emergence of antibiotic resistance in Staphylococcus aureus. The bug is associated with Healthcare-associated infections and with the increasing rates of MRSA, empiric use of Vancomycin has increased in the past few years. Rapid test to detect MRSA would be a crucial step in restricting the use of glycopeptides as empiric therapy.19 The infections associated with Staphylococcus aureus include skin and soft tissue infections and bacteremia (62%, 42%). In our study the isolation rates of Staphylococcus aureus were, 75%: skin and soft tissue infections, 11% from bloodstream infections, 10.4% from osteomyelitis cases, 4% respiratory secretions. The findings are similar to the previous studies with skin and soft tissue as common sites of infections caused by this pathogen.20 Antibiotic resistance rates of Staphylococcus aureus reported in other studies revealed high rates of resistance to Penicillin (88%), beta-lactam (53%), macrolides (52%) and fluoroquinolones (79%). Resistance to Clindamycin was 17% and no resistance was reported to Linezolid and Vancomycin. MRSA rate was 29%, it is similar to the studies published earlier. The rate of MRSA isolated from invasive infections was 41% in the previous studies. The prevalence of MDR Staphylococcus aureus was 54%. MRSA rates in this study on blood and invasive samples was high.21  With this rate of MRSA creeping up, especially in the health care settings, the potential utility of its rapid detection is essential. In this study conducted, rapid detection of MRSA directly on the clinical specimen had a sensitivity of 97% and specificity of 98% respectively compared to culture. The potential advantage of this approach would be early detection of MRSA (within hours) compared to culture (2-3 days). This test would minimize the use of Vancomycin as empiric therapy in health care settings. Thus the test could be a magic bullet in the era of Antimicrobial Stewardship.22,23 Real-time PCR for the direct detection of MRSA in clinical samples have a sensitivity of 82-100% and specificity ranging from 94-100%. The findings of our study are in par with the above findings. 24 2 samples with no growth in culture were positive for MRSA by PCR. It could either be a false-positive result in PCR or due to prior antibiotic therapy administered. 1 sample was negative by PCR and culture positive for MRSA. This fact could be attributed to PCR inhibitors in the sample. The limitations in our study were the limited number of samples tested. Utility of this test in respiratory samples is limited as it requires clinical correlation. The findings of the study have gathered information regarding rate of MRSA in clinical specimens using the technique proposed to adapt. Early detection of MRSA will help to identify appropriate antibiotic for early treatment which will reduce morbidity and mortality.  This approach would aid in the implementation of appropriate infection control measures to curtail the spread of MRSA in our setup. Conclusion: Real-time PCR is a rapid sensitive assay for the detection of antibiotic resistance genes. Rapid detection of MRSA directly in the clinical specimen is a tool for better patient care and efficient implementation of infection control practices. The appropriate antibiotic can be started at the earliest. Acknowledgement The authors are grateful to Manipal Center for Infectious Diseases (MAC ID) PSPH, Manipal Academy of Higher Education, Manipal and Manipal Academy of Higher education for the grant and support Source of funding: MACID seed grant 2017-18 MAC ID/SGA/2017/1 Conflict of Interest: None Authors’ Contribution: Dr Sevitha Bhat: idea, execution and writing of the work  Dr Gopalkrishna Bhat K: idea, execution of the study Dr Shalini Shenoy Mulki: execution and writing Dr Archana Bhat K: writing of the study  Dr Pooja Rao: execution of the work Englishhttp://ijcrr.com/abstract.php?article_id=4340http://ijcrr.com/article_html.php?did=4340 Stefani S, Goglio A. Methicillin-resistant Staphylococcus aureus: related infections and antibiotic resistance. Int J Infect Dis. 2010;14(4):19-22. Fomda B A, Thokar M A, Bashir G, Khan A, Kour A, Zahoor D et al. Revalence and genotypic relatedness of methicillin-resistant Staphylococcus aureus in a tertiary care hospital. J Postgrad Med 2014; 60:386-9. Sharma NK, Garg R, Baliga S, Bhat KG. Nosocomial infections and drug susceptibility patterns in methicillin-sensitive and methicillin-resistant Staphylococcus aureus. J Clin Diagn Res 2013; 7:2178-80. Navratna V, Nadig S, Sood V, Prasad K, Arakere G, Gopal B. Molecular basis for the role of Staphylococcus aureus penicillin-binding protein-4 in antimicrobial resistance. J Bacteriol 2010;192(1): 134-144. Chen CJ, Huang YC. New epidemiology of Staphylococcus aureus infection in Asia. Clin Microbiol Infect 2014;20:605-23. Mendes RE, Mendoza M, Bangh Singh KK, Castanheira M, Bell JM, Turnidge JD et al. Regional surveillance program results for 12 Asia pacific regions (2011). Antimicrob Agents Chemother 2013 : 57: 5721-26. Gopalakrishnan R, Sureshkumar D. Changing trends in antimicrobial susceptibility and hospital-acquired infections over an 8-year period in a tertiary care hospital in relation to the introduction of an infection control program. J Assoc Physicians India. 2010;58(Suppl):25–31. Pai V, Rao VI, Rao SP. Prevalence and Antimicrobial Susceptibility Pattern of Methicillin-resistant Staphylococcus Aureus [MRSA] Isolate at a Tertiary Care Hospital in Mangalore, South India. J Lab Physicians. 2010;2(2):82-84. Mohanasoundaram KM, Lalitha MK. Comparison of phenotypic versus genotypic methods in the detection of methicillin-resistance in Staphylococcus aureus. Indian J Med Res 2008;127(1): 78-84. Pillai MM, Latha R, Sarkar G. Detection of methicillin resistance in Staphylococcus aureus by polymerase chain reaction and conventional methods: a comparative study. J Lab Physicians 2012; 4(2): 83-88. Fang H, Hedin G. Rapid screening and identification of methicillin-resistant Staphylococcus aureus from clinical samples by selective-broth and real-time PCR assay. J Clin Microbiol 2003; 41: 2894–2899. Hagen RM, Seegmuller I, Navai J, Kappstein I, Lehn N, Miethke T. Development of a real-time PCR assay for rapid identification of methicillin-resistant Staphylococcus aureus from clinical samples. Int J Med Microbiol 2005; 295: 77–86. Kumari J, Shenoy S,  Baliga S, Chakrapani M, Bhat GK. Healthcare-Associated Methicillin-Resistant Staphylococcus aureus Clinical characteristics and antibiotic resistance profile with emphasis on macrolide –lincosamide-streptogramin B resistance. Sulthan Qaboos University Med J. 2016;16:175-81. Kumari J, Shenoy S, Mahabala C, Vidyalakshmi K, Bhat GK. Susceptibility pattern of healthcare-associated methicillin-resistant staphylococcus aureus to Vancomycin and Daptomycin. Int J Infect Dis 2016; 45 (suppl 1): 101-2 Huletsky A, Giroux R, Rossbach V. New real-time PCR assay for rapid detection of methicillin-resistant Staphylococcus aureus directly from specimens containing a mixture of staphylococci. J Clin Microbiol2004; 42: 1875–84 Clinical and Laboratory Standards Institute M100-S25: Performance standards for antimicrobial susceptibility testing – Twenty–fifth informational supplement Richard IJ, Janae DL, Stephen VA, Debra M. Rapid Extraction from and Direct Identification in Clinical Samples of Methicillin-Resistant Staphylococci Using the PCR. J Clin Microbiol. 2000; 38:9:  3407–12. Suzanne MP, Anna CP, Donna MH, Adrienne GF, Richard BT, Jr., Karen L et al. Direct Detection of Staphylococcus aureus from Adult and Neonate Nasal Swab Specimens Using Real-Time Polymerase Chain Reaction. J  Mol  Diagn. 2004; 6:3:.191-95. Holfelder M, Eigner U, Turnwald AM, Witte W, Weizenegger M, Fahr A. Direct detection of methicillin-resistant Staphylococcus aureus in clinical specimens by a nucleic acid-based hybridization assay. Clin Microbiol Infect. 2006;12(12):1163-7. Tong SY, Davis JS, Eichenberger E, Holland TL, Fowler VG Jr. Staphylococcus aureus infections: epidemiology, pathophysiology, clinical manifestations, and management. Clin Microbiol Rev. 2015;28(3):603-661. Jonas D, Speck M, Daschner FD, Grundmann H. Rapid PCR-based identification of methicillin-resistant Staphylococcus aureus from screening swabs. J Clin Microbiol. 2002;40(5):1821-1823. Mizusawa M, Carroll, K.C. Novel strategies for rapid identification and susceptibility testing of MRSA. Expert. Rev. Anti-Infect. Ther. 2020;13:1–19 Ellem, J.A., Olma, T., O’Sullivan, M.V. Rapid detection of methicillin-resistant Staphylococcus aureus and methicillin-susceptible S. aureus directly from positive blood cultures by use of the BD Max StaphSR assay. J. Clin. Microbiol. 2015; 53 :3900–04. Wolk, D.M, Struelens M.J, Pancholi P, Davis T, Della-Latta P, Fuller D et al. Rapid detection of Staphylococcus aureus and methicillin-resistant S. aureus (MRSA) in wound specimens and blood cultures: Multicenter preclinical evaluation of the Cepheid Xpert MRSA/SA skin and soft tissue and blood culture assays. J. Clin. Microbiol. 2009; 47:823–826.

Radiance Research AcademyInternational Journal of Current Research and Review2231-21960975-5241143EnglishN2022February1HealthcareDetection of COVID-19 from Chest X-ray Images using Concatenated Deep Learning Neural Networks English5359Tharun Pranav S VEnglish Anand JeyasinghEnglishIntroduction: The severity of COVID-19 disease can be viewed from the massive death rate recorded worldwide so far. The majority of increase in death rate is due to late identification of disease. Aim: To detect COVID-19 from Chest X-ray images using concatenated Deep Learning Neural Networks Xception with ResNet152V2 and Xception with EfficientNet-B7. Materials and Methods: This work on Deep Learning (DL) system proposes the concatenation of two DL networks to identify COVID-19 using X-ray images. They are Xception with ResNet152V2 and Xception with EfficientNet-B7. Initially, the input X-ray images are performed with pre-processing. The pre-processed images are given to Xception with ResNet152V2 or Xception with EfficientNet-B7. Various features are extracted from these two networks. The output features from Xception and ResNet152V2 or EfficientNet-B7 are concatenated. The concatenated features are then given to the classifier for the classification of COVID-19. Results: The implementation has been performed on Google Colab using the neural networks with Keras library with a usage of upto 12.69 GB RAM. The average accuracy for COVID-19 is 62% and 60% using concatenated Xception with EfficientNet-B7 and concatenated Xception with ResNet152V2 respectively. Conclusion: The proposed concatenated nets provide better results for 15-epoch with a batch size of 5. With an increase in epoch and batch size the accuracy of the proposed method will be increased upto 99.7%. English COVID-19, Deep Learning, EfficientNet-B7, ResNet152V2, Xception, X-ray images INTRODUCTION COVID-191,2,3 roots to critical respiratory distress. Computer tomography (CT) scan, Lung ultrasound (LUS) and chest X-ray (CXR) are the commonly used imaging approaches to identify COVID-19 infections. 4 CT scan or  X-ray helps to diagnose the severity information of COVID-19. Due to the involvement of the respiratory system, chest CT is firmly used to identify or find COVID-19 cases, but the cost of CT scan is high compared to X-ray.5,6 Currently, automation of severe infected regions in chest X-ray are in need of development. X-ray images helps to identify COVID-19 patients. 7 However manual delineation of X-ray images are challenging to experts. Hence a consistent automated algorithm to classify COVID-19 X-ray images are required to support the experts. Further8, visual analysis of X-ray images may lead to misinterpretation between COVID-19 and pneumonia on a huge number of patients. Major drawback in the analysis of medical images is that, most of the X-ray images used for diagnostic purposes are not openly accessible due to privacy concerns, which means that the results from neural network training on any particular one dataset cannot be replicated or applied in other hospitals. Deep9,10 learning approaches in medical images plays a vital role in reliable analysis. Deep learning based medical image analysis, classifies the images with highly similar features.11,12 Recently several deep learning based approaches are used for the diagnosis of COVID-19. 13 Pretrained deep learning models, classifies the test images with 0.93 validation accuracy based on DenseNet 201. The deep learning models14,15,16 using LUS images were studied. 15 The classification based on ResNet18, ResNet50, Squeeze Net and DenseNet161 were performed for classification on Chexpert dataset. Recently systems were developed based on deep learning techniques using different medical imaging modalities such as CT and X-ray. Research on deep learning approach with high sample efficiency based on self-supervision and transfer learning has been done for the Database of hundreds of X-ray scans of COVID-19 positive cases. 17 Furthermore, in a library of 1,521 pneumonia patients including COVID-19 X-ray images, predictions were made on COVID-19, pneumonia and normal classes. Due to the lack of availability COVID-19 patients X-ray images, detailed studies reporting solutions for automatic detection of COVID-19 from X-ray images are not available. 18 Radiologists faces a challenging issue in X-ray images to identify COVID-19 and other infections. This implies that challenges for radiologists in specifically identifying COVID-19 infections using X-ray images is a need in current scenario. In this work, the X-ray images of COVID-19 patients were distinguished and performance comparison of two concatenated nets were analyzed to identify its effectiveness. The following are the major contribution of this work. Propose a concatenated network of Xception with ResNet152V2 to identify COVID-19. Propose a concatenated network of Xception with EfficientNet-B7 to identify COVID-19. Analyse the performance between above two concatenated networks. This paper is organized as follows. Section 1 discusses on introduction to the work followed by the work done in this area. Section 2 explains the proposed concatenated neural network. Section 3 elucidate the results and discussions of the proposed work. Finally, section 4 concludes the paper. PROPOSED METHOD Raw datasets The images used for the experiment were taken from the kaggle data sets. An infectious disease, coronavirus disease 2019 (COVID-19) causes severe acute respiratory syndrome. The outbreak was officially recognized as a pandemic by the World Health Organization (WHO) on 11 March 2020. Currently Reverse transcription-polymerase chain reaction (RT-PCR) is used for diagnosis of the COVID-19. X-ray machines are hugely available to diagnose COVID-19 at early stages. Dataset is organized in two folders as train and test in Kaggle. Both train and test contain 3 subfolders including COVID19, PNEUMONIA and NORMAL X-rays. Block diagram The overall process of the proposed concatenated network for COVID-19 detection is shown in Figure 1. Initially, the input images are performed with pre-processing operation. The output from the pre-processing is given to Xception with ResNet152V2 or EfficientNet-B7 for extracting the features. The extracted features are concatenated and then the concatenated feature is given to the classifier to diagnose COVID-19. The following process are carried out for the classification of COVID-19 X-ray images. Experimental data analysis and pre-processing: Initially the datasets are characterized, and grouped into classes. Concatenation: Xception with ResNet152V2 features are extracted from the pre-processing X-ray images. The features are concatenated to obtain the training parameters and weights from the network and applied to the training of the target data set. Target dataset training: The pre-trained concatenated model is applied to the target data set to improve the classification accuracy. Classification: Experiments are performed on tuned model, and then applied to the test set to obtain the classification outputs. The above process is repeated for Xception with EfficientNet-B7. Data analysis and pre-processing To enhance the classification performance, the experimental data need to be pre-processed. The pre-processing of dataset includes image scaling and split the images for train and test. i. Image scaling X-ray images in raw format are converted to png format, and if the image is already in png format, the same format is used. The original  X-ray images in dataset is performed to an image scaling before given to the training. Each image in dataset is adjusted to the resolution of 255 × 255 pixels. ii.Grouping: The full test dataset has 11302 images, where 31 images are COVID-19, 4420 images are pneumonia and 6851 images are normal cases. Around 6% of the total images are used for testing purposes and remaining images are used for training purposes. To improve the data identification, this work uses the expansion techniques of 360-degree rotation, zoom, horizontal flip and vertical flip. Concatenation of neural network To identify COVID-19 from chest X-ray, the features of lungs need to be extracted. The classification accuracy in X-ray mainly depends in the feature extraction. Generally deep feature extraction will be followed in regular learning strategies. 19,20 In this work, the features extracted from Xception with ResNet152V2are Concatenated to extract the general features and applied to the target dataset for better classification. 19,21 Also, the Xception with EfficientNet-B7  features are concatenated for classification as shown in Figure 2. Xception generates a 10 x 10 x 2048 feature map on its last feature extractor layer from the input image, and ResNet152V2 or EfficientNet-B7 also produces the same size of feature map on its final layer as shown in figure 2. As both networks generate the same size of feature maps, the features were concatenated by using both of the inception-based layers and residual-based layers of EfficientNet-B7. Hence, the quality of the generated semantic features would be enhanced. A concatenated neural network is designed by concatenating the extracted features of Xception with ResNet152V2 and Xception with EfficientNet-B7 and then connecting the concatenated features to a convolutional layer that is connected to the classifier. The kernel size of the convolutional layer is then added after the concatenated features was 1 x 1 with 1024 filters and no activation function. This layer has been used to extract the valuable semantic feature from the features of a spatial point among all channels, where each channel is a feature map. This convolutional layer helps the network learn better from the concatenated features extracted from Xception with ResNet152V2 and Xception with EfficientNet-B7. RESULTS In this work, two open-source datasets were chosen. The first COVID-19 dataset, were taken from GitHub (https://github.com/ieee8023/covid-chestxray-dataset)and second dataset has been taken from (https://www.kaggle.com/c/rsna-pneumonia-detection -challenge). In this dataset, only X-ray images are considered Parameters and functions The following table 1, gives the parameters and functions used to train the network. From table 1, it has been observed that, the network was trained using Categorical cross-entropy loss function and Nadam optimizer. For the concatenated network Xception with ResNet152V2 and Xception with EfficientNet-B7, the batch size chosen is 5. Each concatenated network has been trained for 15 epochs. As there are 8-training phases, the models were trained for 15 epoches. In addition, data augumentation methods are used in this work to improve the efficiency of training and to reduce the over fitting. These concatenated Networks were implemented using Keras library on a Tesla T4 GPU with 12.69 GB that were provided by Google Collaboratory Notebooks Pro. The software used for this work is Python 3.8. This work has been validated using 11,302 images. Out-of 11,302 X-ray images, 31 images are COVID-19, 4420 images are pneumonia and 6851 images are normal cases. Training and analysis All the X-ray images in database were trained and tested. The parameters training and validation accuracy are measured initially for concatenated Xception with ResNet152V2 and Xception with EfficientNet-B7. Training accuracy is the accuracy measured when applying the model on the training data, while validation accuracy is the accuracy for the validating data. Training accuracy and validation accuracy for each epoch for all the sets are measured and is shown in Figure 3 and Figure 4 for concatenated Xception with ResNet152V2 and Xception with EfficientNet-B7 respectively. Table 2 reports the true positive, false positive and false negative for COVID-19, pneumonia and normal class using concatenated Xception with ResNet152V2 and Xception with EfficientNet-B7. True positive is the number of correct images classified by the network, False positive is the number of wrong classified images by the network, False Negative is the number of images detected as another class by the network and True negative is the number of images not belonging to a class and network classified as not belonging to a class.  From the table 2, it has been observed that, EfficientNet-B7 provides better true positive compared to concatenated Xception with ResNet152V2 except third fold for COVID-19. For pneumonia, concatenated Xception with ResNet152V2 provides better performance compared to concatenated Xception with EfficientNet-B7. Out of two networks, for COVID-19 detection concatenated Xception with EfficientNet-B7 can be used and for pneumonia, concatenated Xception with ResNet152V2 can be preferred. Evaluation Metrics The metric considered for evaluation are accuracy, sensitivity and specificity. Accuracy for all the classes is the ratio between number of correctly classified images and number of all images [ref]. Sensitivity and specificity for all classes is given in equation 2 and 3 respectively. Sensitivity = [True Positive / (True Positive+ False Negative)] * 100 ------2 Specificity = [ True Negative / (False Positive + True Negative)] * 100 -----3 Table 3 gives the COVID-19, pneumonia accuracy, specificity and sensitivity. From the table 2, it has been observed that accuracy for concatenated Xception with EfficientNet-B7 in detecting COVID-19 is high on average compared to concatenated Xception with ResNet152V2. Eventhough the datasets are unbalanced with few COVID-19 cases, the proposed concatenated Xception with EfficientNet-B7 detects better compared to concatenated Xception with ResNet152V2. DISCUSSION An effort has been made in this paper, to identify COVID-19 using proposed concatenated Xception with EfficientNet-B7 and Xception with ResNet152V2. Different images like pneumonia, COVID-19 and normal X-ray images have been used in the database to identify COVID-19. Various parameters like true positive, false positive, false negative, accuracy, sensitivity and specificity for COVID-19, pneumonia and normal class X-ray images using concatenated Xception with ResNet152V2 and Xception with EfficientNet-B7 has been computed and compared. From the comparison, it has been observed that concatenated Xception with EfficientNet-B7 shows better performance than Xception with ResNet152V2.  Also, the use of different images in the dataset is very effective in identifying COVID-19 using concatenated neural networks. CONCLUSION In this work, concatenated neural network Xception with ResNet152V2 and Xception with EfficientNet-B7 for classifying the chest X-ray images into COVID-19, pneumonia and normal were performed. Two open-source datasets were used as mentioned in the above discussions. The training sets are separated into 8-successive phases, with 633 images in each phase. Out of 633 images, each class are with approximately 149 COVID-19, 234 pneumonia and 250 normal images. For 15 epoch and 5-batch size, the average accuracy and sensitivity for COVID-19 is 62% and 62% respectively using concatenated Xception with EfficientNet-B7 which is 2% higher than concatenated Xception with ResNet152V2. Open-source code for Xception, ResNet152V2 and EfficientNet-B7 has been taken from Github and concatenation has been performed between the nets and evaluation were performed. In future, more COVID-19 X-ray images will be added in database to make it balanced and more epoch will be added to improve the accuracy. Acknowledgement: The Principal and Informatic Practices Teacher of Yuvabharathi Public School, Yuva Enclave Kanuvai, Coimbatore, Tamil Nadu 641108for their support in developing the project. Glada Wesley, Mathematics Teacher of Yuvabharathi Public School, Yuva Enclave Kanuvai, Coimbatore, Tamil Nadu 641108 for her support in mathematics on deep learning. Source of Funding: NIL Conflict of Interest: NIL Authors’ Contribution: Mr. S V Tharun Pranav1: Proposed a concatenated networks of Xception with ResNet152V2 and Xception with EfficientNet-B7 to identify COVID-19.Analyse the performance between the above two concatenated networks and writing the article. Mr. Anand Jeyasingh2: Interpretation of results and writing the article. Englishhttp://ijcrr.com/abstract.php?article_id=4341http://ijcrr.com/article_html.php?did=4341 Islam MM, Islam MZ, Asraf A, Ding W. Diagnosis of COVID-19 from X-rays using combined CNN-RNN Architecture with transfer learning. medRxiv. 2020. Muhammad LJ, Islam MM, Usman SS, Ayon SI.  Predictive data mining models for novel coronavirus (COVID-19) infected patients’ recovery. SN Computer Science. 2020; 1. Islam MM, Karray F, Alhajj R, Zeng J. A review on deep learning techniques for the diagnosis of novel coronavirus (COVID-19). IEEE Access. 2021; 30551–30572. Ning W, Lei S, Yang J, Cao Y, Jiang P, Yang Q, et al. Open resource of clinical data from patients with pneumonia for the prediction of COVID-19 outcomes via deep learning. Nature Biomedical Engineering. 2020; 4. 1197–1207. Harish KB. COVID-19 Pandemic Effect on Social Life of Human. Int J Cur Res Rev. 2021; 12(7). Devarajappa S, Khalida KA, Nagaraja S. Impact of Covid-19 Pandemic on Accredited Social Health Activists (ASHA) in Karnataka: A Empirical Analysis. Int. J. of Current Research and Review. 2021; 13(18). Candemir S, Antani S. A review on lung boundary detection in chest X-rays. Int. J. of Computer Assisted Radiology and Surgery. 2019; 14. 563–576. Osman AH, Aljahdali HM, Altarrazi SM, Ahmed A. SOM-LWL method for identification of COVID-19 on chest X-rays. PLoS One. 2021; 16(2). Pathak A, Athavale H, Pathak T, Athavale SA. Artificial Intelligence in Medicine and Understanding its Potential for Newer Applications. Int J Cur Res Rev. 2021; 13(16). Harish KB. Perspectives of Using Artificial Intelligence in Preventing and Regulating COVID-19:A Letter to the Editor. Int J Cur Res Rev. 2021; 13(15). Maghdid HS, Asaad AT, Ghafoor KZ, Sadiq AS, Khan MK. Diagnosing COVID-19 Pneumonia from X-Ray and CT Images using Deep Learning and Transfer Learning Algorithms. Multimodal Image Exploitation and Learning. 2021;11734. Mangal A, Kalia S, Rajgopal H,  Rangarajan K,  Namboodiri V, Banerjee S, Arora C.  CovidAID: COVID-19 Detection Using Chest X-Ray. arXiv:2004.09803, 2020. Patel S. Classification of COVID-19 from chest X-ray images using a deep convolutional neural network, Turkish Journal of Computer and Mathematics Education. 2021; 12(9). 2643– 2651. Poggiali E, Dacrema A, Bastoni D, Tinelli V, Demichele E, Mateo Ramos  PM, Marciano T, Silva M, Vercelli A,  Magnacavallo A. Can Lung US Help Critical Care Clinicians in the Early Diagnosis of Novel Coronavirus (COVID-19) Pneumonia?. Radiology. 2020; 295(3). Fiala MJ. Ultrasound in COVID-19: a timeline of ultrasound findings in relation to CT. Clinical Radiology. 2020; 75(7). 553–554. Peng QY, Wang XT, Zhang LN. Findings of lung ultrasonography of novel coronavirus pneumonia during the 2019-2020 epidemic. Intensive Care Medicine. 2020; 46(5). 849–850. Rahimzadeh M, Attar A. A modified deep convolutional neural network for detecting COVID-19 and pneumonia from chest X-ray images based on the concatenation of Xception and ResNet50V2. Informatics in Medicine Unlocked. 2020; 19. Bressem KK, Adams LC, Erxleben C, Hamm B,  Niehues SM, Vahldie JL. Comparing different deep learning architectures for classification of chest radiographs. Nature Scientific reports. 2020. Chollet F.  Xception: Deep Learning with Depthwise Separable Convolutions.arXiv:1610.02357. 2017. Elshennawy NM,  Ibrahim DM. 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Radiance Research AcademyInternational Journal of Current Research and Review2231-21960975-5241143EnglishN2022February1HealthcareIn Vitro Culture Techniques from Cotyledon Explants of Celastrus Paiculatus (Wild) a Medicinal Important Plant English6062Mandaloju VenkateshwarluEnglishEnglishIn Vitro Techniques, Cotyledon culture, Celastruspaniculatus, Cell metabolism, Cell membrane synthesis, Growth and differentiation INTRODUCTION This phenomenon is called oxidative stress and is known as one of the major causes of plant damage as a result of environmental stresses15 one that produces the transcription factor in 10 times higher amounts than normal plants and another that does not produce. it at all. It turned out that the plants with the elevated production of the HsFA1 showed increased resistant to heat stress and the plants without any transcription factor sustained severe damage.16,7In general, coconut water reduces the amount of 2, 4-D, required to for initiation and growth of callus and it is well known that 2, 4-D, levels had a pronounced effect on callus initiation in sugarcane explants.8Recent developments in molecular biology and genetic transformation however, have made it possible to identify, isolate and transfer desirable genes in to sugarcane.17In dryland agriculture, the altered plants showed increased production.12 Most of the recent research was made on Tobacco, AlfalfaandArabidopsis thaliana.3,9 MATERIAL AND METHODS: The explants (Cytoledons) were harvested and washed with distilled water. The explants were surface sterilized in a laminar airflow hood by sequentially washing them with 5% Sodium hydrochloride containing 2-3 drops of tween 20 for 7-10 min. The explants were rinsed thrice with sterile distilled water after each sterilant for 3-5 min. the explants were harvested and dipped in water until used. Each of these MS Media contained entire sucrose as the other components these inoculated cotyledonary explants were monitored regularly for induction of micro shoots. The explants which increased at least a single micro shoot was scored as responding explants. Among the three concentrations used, 15% of coconut milk along with 0.5 mg/l BAP has proved to be ideal for multiple shoot induction MS medium fortified with 1.0 mg/l BAP and 2.0 mg/l L-Glutamic acid favored the induction of multiple shoots which ranged from 8-10 from cotyledon segments. Tissue culture techniques have been widely used as an alternative for large-scale micropropagation and can effectively reduce the time period between selection and commercial release of new sugarcane varieties.11 Explants preparation for callus initiation was done as per the protocol followed by 13,10 The cotyledon explants inoculated on MS medium containing BAP and 2, 4-D initiated callus. The addition of NAA and BAP to the MS medium resulted in a small bud formation from callus derived from cotyledon. MS medium supplemented with 10%, 15% and 20% of coconut milk in addition to cytokinin (BAP) triggered the induction of multiple shoots. RESULTS: The present observations of the explants were collected from field-grown plants thought out the year to determine the ideal season for culture established. The shoots obtained were rooted, when placed on media containing 2.0 mg/l NAA + 5 mg/L BAP, resulting in the formation of plantlets with roots containing drained soil, and were covered with polythene bags 20 days in a growth chamber, in order to harden the potted plants. Well-developed plantlets were transferred to earthen pots (Table 1, Figure A-Callus). Celastruspaniculatuscotyledon explants were inoculated on MS basal medium fortified with various Cytokinins i.e, BAP and Kinetin. Coconut water also had a role in triggering the formation of multiple shoots(Figure –B). Among all the explants used, segments were the best for multiple shoot induction (Figure-C) followed by the cotyledon. Well-developed multiple shoots obtained, were carefully isolated into individual segments along with a node each, and were placed on rooting medium. DISCUSSION: Culturing the micro shoots for an extended period by repeatedly sub-culturing them over the same media which induced them to increase the frequency of elongation to 50%. However this attempt also could not elongate the micro shoots longer then 2-4 shoots. We also attempted to elongate the microshoots over the media with reduced agar content. The effectiveness of MS medium in inducing regeneration in the Cotyledon explants. Table -1 In Vitro Culture Techniques From Cotyledon Explants Of CelastrusPaiculatus. CONCLUSION The Cotyledon explants became active within 4-6 weeks after inoculation and new shoots become distinct by the fourth week with leaves and internodes. The explants were collected from field-grown plants thought out the year. Addition of 3.0 mg/l BAP or 5.0 mg/l Kinetin the MS  medium induced shoot regeneration from the cultures and the proximal end of auxiliary region of cotyledon explants. Within a period of two weeks in culture. With an increase in the level of BAP (2.0 – 4.0 mg/l) the percentage of and cotyledon explants producing shoots also increased. We were successful in cotyledon cultures, resected in better yield of fairly good when above maintained condition. MS medium supplemented with BAP and IAA initiated the formation of callus from leaf culture. Addition of kinetin along with L-Glutamic acid and 15% coconut milk induced multiple shoots from callus cotyledon explants. Acknowledgment: I am grateful to the Head and Staff Department of Botany E2 POT Final year students UC, KU for providing the Laboratory facilities. Source of funding: SERO Hyd, TS India. Conflict of Interest: In Vitro Development of regeneration of whole plant through tissue culture. Authors&#39; Contribution: Initiated form a single explant taken from any living part of an explant and within very short time and space a larger number of plantlets can be produced from callus tissues. Englishhttp://ijcrr.com/abstract.php?article_id=4342http://ijcrr.com/article_html.php?did=4342 Benarjee R, Gouswami P, Lavania S, Mukherjee A and Lavania UC. Vetiver grass is a potential Candidate for phytoremediation of iron ore mine spoil dumps. Ecological Engineering (2019) Vol.132: PP120-136. Cocking E.C. Selection and somatic hybridization in Frontiers of plant tissue culture (ed) T.A. Thrope, Academic press. (1978) PP. 151-158. Datta S.K. Recent developments in transgenics for abiotic stress tolerance in rice JIRCAS working Report. (2002) Vol. 23: PP 43-46. Gago J, Martinez-Nunez L, Landin M, Flexas J and Gallego PP Modelling the effects of light and sucrose on in vitro propagated plants. A multiple system analysis using artificial intelligence technology (2014) PLOS ONE Vol. 09: PP 1-11. GantherectR.J.Thenutritionofplanttissuecultures.Ann.Rev.Plant.Physiol.(1995)Vol.6: PP 433-484. Gauchan DP Effect of different sugars on shoot regeneration of maize ( Zia mays L ) Katmandu University Journal of Science and Engineering Tech (KUSET) (2012) Vol. 8: PP119-124. Gyves E, Royani JI and Rugini E Efficient method of micropropagation and in vitro rooting of teak (Tectonagrandis L) focusing on large scale industrial plantations. Animal of Forest Sci. (2007) Vol. 64:PP 73-78. Kell DB. Large Scale sequestration of atmospheric Carbon via plant roots in natural and agricultural ecosystems why and how phil Trans. R. Soc.B. (2012) Vol. 367: PP 1589-1597. Lavania UC and Lavania S. Sequestration of atmospheric carbon into subsoil horizons through deep-rooted grasses-vetiver grass model. Curr.sci (2009) Vol. 97: PP 618-619. Lavania S Descriptors for vetivervetiversim 21: 5-10. Hughes EH, Shanks JV Metabalic engineering of plants for alkaloid production. Metabolic Engineering V. (2002) Vol. 4 PP 41- 48. Lorenzo J.C, Ojeda E, Espinosa A and Borrotoc A. Field performance of temporary immersion Bioreacter- Derived sugarcane plants. In vitro callus Dev. Bio plant. (2001) Vol. 37: PP 803- 806. Moffat A.S. Finding new ways to protect rough-stricken plants. Science (2002)         117: 1226-1229. Santhosha D.A, Roy H, Farrouk A and Greiner R. A rapid and highly efficient method for transformation of sugarcane callus. Molecular Biotechnology(2004) Vol. 28: PP 113-119. Smith and Smet ID Roof system architecture insights from Arabidopsis and cereal crops. Phil. Trans. R. Soc. B (2012) Vol. 367, PP 1441-1452. Street H.E. Growth in organized and unorganized systems. Knowledge gained by culture of organs and tissue explants. In: Plant physiology treatise (e). F.C. Steward, Academic Press, New York. (1969) Vol. 5: PP 213-224. Sunkar R, Bartels D and Kirch H.H. Overexpression of a stress sucible dehydrogenase gene from Arabidopsis thaliangin transgenic plants improve stress tolerance. The plant Journal (2003) Vol. 35(4): PP 452. Wantner R. Stress bewaltingungbeitomaten, FA2 (Feuilletou) 15 Juli Nr (2002) Vol. 136: PP 48. Yamada T, Sakiya I and Kobhimizn K. Cytokinin induced shoot formation phytochemistry: (1972) Vol. 11: PP 1019-1021.

Radiance Research AcademyInternational Journal of Current Research and Review2231-21960975-5241143EnglishN2022February1HealthcareOvarian Pregnancy in Kindu City, D.R. Congo - A Case Report English6366Mbungu Mulaila APEnglish Mbungu Mwimba R.English Mbanzulu Pita NZEnglish Ambambula Yalala O.English Okamba Alangi T.English Kahindo P. MuyayaloEnglishIntroduction: Ovarian pregnancy (OP) is an uncommon form of ectopic pregnancy that is often misdiagnosed. However, the rupture of the expanding OP can lead to internal bleeding and threaten women life. The purpose of this case report is to discuss the challenge to diagnosing and managing OP, specifically in low-income countries, accurately. Case Report: We report the case of an ectopic pregnancy suspected as being an abdominal pregnancy with a dead fetus in utero on ultrasound and which turned out to be ovarian, discovered intraoperatively in a 22-year-old third parous without known morbid history. Discussion: Due to its rarity, OP remains an isolated and exceptional phenomenon in a woman’s life. OP is difficult to diagnose and sometimes lately diagnosed, especially in countries with limited resources as the Democratic Republic of Congo (DRC). Indeed, the lack of adequate imaging and histopathologic equipment, and qualified practitioners in most medical centers do not facilitate the early diagnosis and treatment of OP in those settings. Conclusion: This first reported case of OP in the D.R. Congo confirms the difficulty in making the diagnosis. In case of diagnosis doubts, medical care practitioners should consider directing patients to specialized health care cente EnglishEctopic pregnancy, Ovarian pregnancy, Case report, Mapon Clinic, Kindu City, D.R. CongoINTRODUCTION The most commonly occurring gynecologic emergency leading to maternal death in the first trimester of pregnancy,1 ectopic pregnancy (EP), is a complication of pregnancy in which an embryo attaches itself anywhere outside of the uterus.2The large majority of  EP (95 %) are located at the fallopian tubes; the remain 5 % are located in the abdomen, ovary, and cervix.1 Ovarian pregnancy (OP) is an uncommon form of ectopic pregnancy with an incidence of 0.5-3% of all ectopic gestations3, which occurs when a fertilized ovum implants on the surface of the ovary.4OP are often misdiagnosed as corpus luteum hemorrhage, and around 75% terminate in first trimester5. Indeed, the rupture of the expanding OP is expected at the early stage of pregnancy1, which can lead to internal bleeding and hypovolemic shock.4 Despite the availability of sophisticated diagnostic technology, the diagnosis of OP remains a challenge. Patients most often undergo surgery for suspected tubal ectopic pregnancy or hemorrhagic corpus luteum.6 Here we report the case of an ectopic pregnancy suspected as being an abdominal presenting as missed abortion on ultrasound, which turned out to be an OP during surgery, diagnosed at the Lumbulumbu Hospital Center (LLHC) / Mapon Clinic of Kindu in Maniema in the Democratic Republic of the Congo (DRC). CASE REPORT A 22-year-old gravida 3, para 3 was admitted at the LLHC / Mapon Clinic for lower abdominal pain, vaginal bleeding, and absence of active fetal movements (AFM). She did not have any history of pelvic inflammatory disease or insertion of an intrauterine device (IUD). She saw her last period on December 2th 2019, and 6 weeks later, she did the first ultrasound that confirmed the pregnancy without mentioning its location. The occurrence of vaginal bleeding (or spotting) at around 15 weeks of amenorrhea motivated her consultation in another medical center of the Kindu City. She received treatment for a threatened miscarriage that stopped the bleeding. The recurrency of vaginal bleeding at around 19 weeks of amenorrhea and the absence of AFM let the patients to consult in another medical center of Kindu City different from the previous one, where ultrasound realized by unqualified practitioners reported an aseptic necrobiosis of a uterine fibroid without mentioning pregnancy. Then, the patient was referred for better management by specialists at the LLHC / Mapon Clinic. At the time of her presentation at LLHC / Mapon Clinic, the gestational age was estimated at 28 weeks of amenorrhea. She complained of vaginal bleeding(spotting), intermittent lower abdominal pain, and the absence of AFM. She was in good general condition on examination, with moderately colored eyelid conjunctiva and good vital signs. The breasts were symmetrical, flabby, secreting breast milk. On abdominal examination, we observed a hypogastric arch eccentric to the left, going up to a finger gap below the umbilicus. Two distinct, poorly over conscribed, non-sensitive masses of more or less firm consistency, with irregular surfaces, were palpated in the right para-uterine side. One small and mobile mass to the two planes of the abdominal wall, and the other more significant still. In the left para-uterine side, we notice a tenderness on the deep palpation. The vulva was eutrophic and clean. The speculum examination revealed a healthy cervix pauciparous without ex-utero hemorrhage. On digital vaginal examination, the cervix was posterior, soft, long, closed. The uterus was enlarged about the size of an orange; the pelvis was considered clinically good. In addition, she did not present edema of the lower limbs. Given the patient&#39;s history and the clinical examination, we suspected an aborted pregnancy; and uterine myomatosis was excluded. Laboratory Investigations revealed Blood-Rhesus Group: B +; Hemoglobin (Hb): 12.4g / dl; Hematocrit (Ht): 38%; Red blood cells (RBCs) count: 4,460,000 / mm3; White Blood Cell (WBCs) Count: 5300 / mm3 (Neutrophils 44%, Lymphocytes 52%, Eosinophils 2%, Basophils 1%, and monocytes 1%); Platelets: 288000 / mm3; HIV serology negative. Abdominopelvic ultrasound showed a left para-uterine abdominal pregnancy with a dead fetus in utero whose gestational age was 20 weeks ultrasound (femoral length: 33mm). The empty uterus having measured 98x46x67 mm, the left ovary not visualized, the right ovary with normal echo anatomy measuring 32x25x17 mm. Based on all the above examinations (clinical, laboratory, and ultrasound), we decided to perform an exploratory laparotomy for arrested abdominal pregnancy. The surgery was performed under general anesthesia. After median sub-umbilical coeliotomy, we made the following observations: a peritoneal fluid tinted with old blood estimated at 150ml after aspiration. An old sizeable septate blood clot in the omentum weighed 170g. A pelvic mass of firm consistency, irregular surface, poorly mobilized, at the expense of the left ovary and firmly adhering to the ipsilateral tube, filling the Douglas sac and pushing back the uterus to the right (Figure 1). The mass had no contact with the intestinal loops or omentum (Figure 1). There was a clear cleavage line between the mass and the posterolateral part of the uterus that served as a surgical approach to removing the pelvic mass. The right tube and ovary were normal in appearance and volume. We performed the right total adnexectomy, removing the mass that was fixed by the left utero-ovarian and lumbo-ovarian ligaments (Figure 1). The mass contained a female fetus with overlapping skull bones (Figure 2), first-degree macerated, weighing 457g (Figure 2). We then performed hemostasis, cleaned the peritoneal cavity with 3 liters of warm 0.9% Nacl, and placed a sentinel drain in the Douglas pouch. Finally, we closed the abdominal wall plan by plan and ended with a clean and dry bandage. There weren&#39;t any incidents during the surgery, and the postoperative follow-up was simple. The patient was discharged from the hospital on postoperative day five. DISCUSSION OP is a rare entity among ectopic pregnancies. Its diagnosis and management are not always easy. Its frequency is estimated at 2-3% of GEUs, representing an incidence of approximately 1/2500 to 1/5000 births.7 Sergeant et al. 8 found an incidence of 1 per 1400 births. It should be noted that the lowest Incidence was reported in Tunis with 1/21439 births.9 In the D.R. Congo, no incidence is available as this is the first reported case of OP. In their series, Reithmeller et al.10 reported two cases of OP in older infertile women without an IUD. Similar to the findings of Beugre N. et al.11 in Ivory coast, our patient was younger and fertile. This difference might be related to the fact that the sample is unrepresentative, making it impossible to draw any possible conclusions to be extrapolated. Clinically, abdominal pain, delayed menstruation, and bleeding are often presented.12,13 The pain corresponds to the rupture of the ovarian capsule by the OG and the formation of the hemoperitoneum.8,14 Patients are most often seen in an emergency setting, with significant hemoperitoneum or even in a state of hypovolemic shock.14 However, in our case, the patient was hemodynamically stable with no worsening of other symptoms. This would be justified by the possible existence of a polymorphism of the clinical pictures, resulting in a possible delay in the management when the symptoms are not acute. According to Spiegelberg15, OP is characterized by its usual occurrence in the right side since 1) the average size of the right ovary (16mmx19mm) is much smaller than that of the left ovary (35mmx18mm); 2) part of the parenchyma of the right ovary often turns into a cystic cavity; 3) the wall of this cavity and the ovary have the same histological structure, in this cavity, we usually find fetal remains and placental remains.15,16 Many authors report that OP is diagnosed before 12 gestational weeks8, and some may progress until the 2nd trimester12 or even more. Danish et al. reported a case of a 32 gestational weeks OP that was diagnosed as an abdominal pregnancy before surgery, but during laparotomy, the diagnosis of GO was made.17 Because of the qualified medical practitioners and adequate equipment, our patient&#39;s diagnosis and management were delays (around 33 weeks of amenorrhea).  Indeed, the patient visited several medical centers in the city without getting an accurate diagnosis.  This case highlights the importance for medical care providers of recognizing their limits (in terms of skills and equipment) and better orient patients by transferring them to specialized structures when they are available in the environment. CONCLUSION Ovarian pregnancy is rare and can be associated with high morbidity and mortality rates. Sometimes the clinical presentation is confusing with threatened abortion or simply premature delivery. Despite the progress of medical treatment, its management remains surgical by laparoscopic route when the diagnosis is made early. The lack of adequate equipment and qualified personnel in many health care’s structures in countries with limited resources causes late consultations of pregnant women, often in severe conditions and sometimes fatal states. This first reported case of OP in the D.R. Congo confirms that the diagnosis of OP is still a dilemma. Therefore, when faced with diagnostic difficulties and doubts, the medical care practitioner should consider directing patients to specialized health care centers to improve their prognosis. ACKNOWLEDGEMENTS Authors acknowledge the immense help received from the scholars whose articles are cited and included in the references of this manuscript. The authors are also grateful to the authors /editors/publishers of all those articles, journals and books from where the literature for this article has been reviewed and discussed. Ethical approval Ethical committee of the Faculty of Medicine in the University of Kindu approved this case study. Informed consent was taken from the patient. Source of Funding: None Conflict of interest: None AUTHORS’CONTRIBUTION: Mbungu Mulaila AP.: diagnostic, therapeutic management and follow-up of the patient, writing - original draft and literature review. Ambambula Yalala O. and Okamba Al a ngi T.: diagnostic and therapeutic management of the patient. Mbungu Mwimba R., Mbanzulu Pita NZ, and Kahindo P. Muyayalo: supervision, validation, writing - original draft, writing - review editing. All authors also declare that they have read and approved the final version of the manuscript. Figure 1: Left adnexal mass found during abdominal surgery. By surgical incision into the abdominal cavity (laparotomy), we came directly across a large clot made from old blood. This clot was covered with omentum and did not adhere to any intra-abdominal organs (fig 1a). The pelvic exploration revealed a large ovarian mass intimately adhered to the left fallopian tube and well-buried towards Douglas&#39; cul-de-sac (fig 1b). After careful manual and instrumental adhesiolysis, we had exteriorized the mass and proceeded to the left total adnexectomy (fig 1c). Figure 2: Female fetus with overlapping skull bones discovered after incision of the ovarian mass. The incision of the ovarian mass (fig 2a) let us observe the entire ovarian pregnancy made of a shell in which we saw a part of the fetal head (fig. 2b). The shell dissection allowed the externalization of a female fetus attached to the placenta by its umbilical cord (fig 2 C). Englishhttp://ijcrr.com/abstract.php?article_id=4343http://ijcrr.com/article_html.php?did=43431.         Kadau JV. Sonographic Detection of Ovarian Ectopic Pregnanc : A Case Study. J Diagn Med Sonogr. 2016;32(5):299-303. 2.         Sotelo C. Ovarian Ectopic Pregnancy: A Clinical Analysis. 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