Image-based phenotyping of seed architectural traits and prediction of seed weight using machine learning models in soybean.

Among seed attributes, weight is one of the main factors determining the soybean harvest index. Recently, the focus of soybean breeding has shifted to improving seed size and weight for crop optimization in terms of seed and oil yield. With recent technological advancements, there is an increasing application of imaging sensors that provide simple, real-time, non-destructive, and inexpensive image data for rapid image-based prediction of seed traits in plant breeding programs.

NGS-based profiling identifies miRNAs and pathways dysregulated in cisplatin-resistant esophageal cancer cells.

Esophageal cancer (EC) incidence remains to be on a global rise supported by an unchanged recurrence and 5-year survival rate owing to the development of chemoresistance. Resistance to cisplatin, one of the majorly used chemotherapeutic drugs in EC, is a major nuisance. This study sheds light on miRNA dysregulation and its inverse relation with dysregulated mRNAs to guide pathways into the manifestation of cisplatin resistance in EC.

Photosynthetic machinery under salinity stress: Trepidations and adaptive mechanisms.

Chloroplasts and photosynthesis are the physiologically fateful arenas of salinity stress. Morphological and anatomical alterations in the leaf tissue, ultrastructural changes in the chloroplast, compromise in the integrity of the three-layered chloroplast membrane system, and defects in the light and dark reactions during the osmotic, ionic, and oxidative phases of salt stress are conversed in detail to bring the salinity-mediated physiological alterations in the chloroplast on to a single platform. Chloroplasts of salt-tolerant plants have evolved highly regulated salt-responsive pathways.

Development of Prediction Models for Soil Nitrogen Management Based on Electrical Conductivity and Moisture Content.

A study was conducted with the goal of developing an algorithm for use in sensors to monitor available soil N. For this purpose, three different soils were selected. The soils were studied for electrical conductivity (EC) at four different moisture levels and four levels of N.

Germplasm variability-assisted near infrared reflectance spectroscopy chemometrics to develop multi-trait robust prediction models in rice.

Rice is a major staple food across the world in which wide variations in nutrient composition are reported. Rice improvement programs need germplasm accessions with extreme values for any nutritional trait. Near infrared reflectance spectroscopy (NIRS) uses electromagnetic radiations in the NIR region to rapidly measure the biochemical composition of food and agricultural products.