ICAR-IASRI Newsletter, January- March, 2015

Abstract

A quantitative assessment of harvest and post-harvest losses for 45 major agricultural crops / commodities in 120 districts of the country was made using stratified multistage random sampling design. A comparison of losses between 2013-14 vis-à-vis 2005- 2007 was made for various food grains, oilseeds, fruits and vegetables. Development of resistance to chemical antibiotics in cattle is unsolved till date. Anti Microbial Peptides (AMPs) are considered as alternative to chemical antibiotics. Different machine learning techniques such as Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs) have been applied to predict AMPs in cattle. SVMs with different kernels have exhibited high accuracy of prediction and thus were implemented on a web server for classification/prediction of novel AMPs of cattle. The developed server is made available in public domain for ready use by the application scientists. Phenomics is another emerging area where the institute scientists in collaboration with ICAR-IARI and IIT-Delhi have developed a phenome data management system with several analysis modules meant for estimation of physical and biochemical traits of rice under moisture deficit and low temperature stress tolerance. A non-destructive approach involving regression methodology has been developed for estimation of leaf area and chlorophyll content of rice seedlings under pot culture conditions through image analysis. An online software “Leaf Area Estimator” has been developed and deployed on the production server for ready use by the experimental biologists.