TPTC: topic-wise problems' trend clusters for smart agricultural insights extraction and forecasting of farmer's information demand.

To meet the challenges of increasing food production demand globally, extracting insights regarding the persistent agriculture-related problems on a nationwide scale is the need of the hour. Policymakers now have limited possibilities for acquiring a comprehensive knowledge of the difficulties that farmers face on a national level. In this direction, the presented work proposes a new artificial intelligence-based pipeline to gain insights at country level regarding the farmers' demand for assistance in India.

Identification of the novel HLA-B*49:01:01:22 allele in an Indian renal transplant donor by next generation sequencing.

HLA-B*49:01:01:22 differs from HLA-B*49:01:01:01 by a single nucleotide C->G change in intron 5 at gDNA 2451.

Effective weight optimization strategy for precise deep learning forecasting models using EvoLearn approach.

Time series analysis and prediction have attained significant attention from the research community in the past few decades. However, the prediction accuracy of the models highly depends on the models' learning process. In order to optimize resource usage, a better learning methodology, in terms of accuracy and learning time, is needed.

Antioxidant activities, dietary nutrients, and yield potential of bitter gourd ( L.) lines in diverse growing environments.

The biotic and abiotic stresses cause a significant decline in the yield and fruit quality traits, including antioxidants and minerals, of bitter gourd when grown in open fields. Protected cultivation technology has emerged to minimize such stresses. We investigated the effect of diverse environments (hi-tech greenhouse, naturally ventilated polyhouse, insect-proof net-house, and open field) and breeding lines on earliness, yield potential, antioxidant activities, and dietary nutrients.

Multivariate Data Analysis Assisted Mining of Nutri-rich Genotypes from North Eastern Himalayan Germplasm Collection of Perilla (Perilla frutescens L.).

Understanding the nutritional diversity in Perilla (Perilla frutescens L.) is essential for selecting and developing superior varieties with enhanced nutritional profiles in the North Eastern Himalayan (NEH) region of India. In this study, we assessed the nutritional composition of 45 diverse perilla germplasm collected from five NEH states using standard protocols and advanced analytical techniques.