RESUMEN
In the present era of climate change, underutilized crops such as rice beans and adzuki beans are gaining prominence to ensure food security due to their inherent potential to withstand extreme conditions and high nutritional value. These legumes are bestowed with higher nutritional attributes such as protein, fiber, vitamins, and minerals than other major legumes of the Vigna family. With the typical nutrient evaluation methods being expensive and time-consuming, non-invasive techniques such as near infrared reflectance spectroscopy (NIRS) combined with chemometrics have emerged as a better alternative. The present study aims to develop a combined NIRS prediction model for rice bean and adzuki bean flour samples to estimate total starch, protein, fat, sugars, phytate, dietary fiber, anthocyanin, minerals, and RGB value. We chose 20 morphometrically diverse accessions in each crop, of which fifteen were selected as the training set and five for validation of the NIRS prediction model. Each trait required a unique combination of derivatives, gaps, smoothening, and scatter correction techniques. The best-fit models were selected based on high RSQ and RPD values. High RSQ values of >0.9 were achieved for most of the studied parameters, indicating high-accuracy models except for minerals, fat, and phenol, which obtained RSQ <0.6 for the validation set. The generated models would facilitate the rapid nutritional exploitation of underutilized pulses such as adzuki and rice beans, showcasing their considerable potential to be functional foods for health promotion.
RESUMEN
BackgroundCOVID-19 emerged as a global pandemic in 2020, rapidly spreading to most parts of the world. The proportion of infected individuals in a population can be reliably estimated via sero-surveillance, making it a valuable tool for planning control measures. We conducted a serosurvey study to investigate SARS-CoV-2 seroprevalence in the urban population of Hyderabad at the end of the first wave of infections. MethodsThe cross-sectional survey conducted in January 2021 included males and females aged 10 years and above, selected by multi-stage random sampling. 9363 samples were collected from 30 wards distributed over 6 zones of Hyderabad and tested for antibodies against SARS-CoV-2 nucleocapsid antigen. ResultsOverall seropositivity was 54.2%, ranging from 50-60% in most wards. Highest exposure appeared to be among 30-39y and 50-59y olds, with women showing greater seropositivity. Seropositivity increased with family size, with only marginal differences among people with varying levels of education. Seroprevalence was significantly lower among smokers. Only 11% of the survey subjects reported any COVID-19 symptoms, while 17% had appeared for Covid testing. ConclusionOver half the citys population was infected within a year of onset of the pandemic. However, [~]46% people were still susceptible, contributing to subsequent waves of infection. Highlights National level serosurveys under-estimate localised prevalence in dense urban areas SARS-CoV-2 seroprevalence in Hyderabad city was 54.2% after the first wave A large proportion of the population remains at risk over a year into the pandemic