Indian Agricultural Statistics Research Institute

About: Indian Agricultural Statistics Research Institute is a facility organization based out in New Delhi, India. It is known for research contribution in the topics: Population & Small area estimation. The organization has 454 authors who have published 870 publications receiving 7987 citations.

Genetic and principal component analysis for agro-morphological traits, bioactive compounds, antioxidant activity variation in breeding lines of early Indian cauliflower and their suitability for breeding

Abstract: This study was conducted to evaluate 16 early Indian cauliflower genotypes for agro-morphological traits, bioactive compounds and antioxidant activity. Analysis of variance, cluster analyse...

Ergonomic Evaluation of Foot Operated Rotary Power Generation

Abstract: Large number of farm machines and hand tools used on Indian farms require rotational power for operation. In India, human energy is extensively used as main source of power to operate farm equipment for low power requirement (<75 W) in different modes including rotational mode. An ergonomic evaluation of foot operated rotational power generation in different modes namely; pedal, stepper and bicycle at five mechanical output conditions was carried out. During experiments, physiological and postural parameters were evaluated. Up to 55.9W of mechanical power output in bicycle mode of operation was found to be the best. At 74.6W of mechanical power output, stepper mode of operation was better than other modes. At no load and 18.6W of mechanical output, the overall discomfort score was the lowest in bicycle mode. At 37.3, 55.9 and 74.6W mechanical outputs, overall discomfort score was lowest in stepper mode. The human efficiency was the highest in bicycle mode of operation at 18.6, 37.3 and 55.9W of mechanical output conditions but at 74.6W mechanical output condition, highest human efficiency was obtained in stepper mode.

Fuzzy regression methodology for crop yield forecasting using remotely sensed data

Abstract: Multiple linear regression methodology is widely employed for crop yield forecasting using remotely sensed data. Here it is assumed that response variable remains same over replications for fixed values of predictor variables. In reality, response variable lies in an interval and so can not be described by a single number. In this paper, a new promising approach of “Fuzzy regression” is discussed which is capable of handling such a situation. The methodology is illustrated with help of secondary data culled from literature. It is shown that latter approach is not only superior to former but is also capable of handling highly correlated variables.

Liver-Specific microRNA Identification in Farmed Carp, Labeo bata (Hamilton, 1822), Fed with Starch Diet Using High-Throughput Sequencing

Abstract: The liver is an important central organ, which controls carbohydrate metabolism through maintaining glucose homeostasis by a tightly regulated system of genes or enzymes. The microRNAs are small non-coding RNAs playing an important role in the regulation of genes associated with developmental biology, physiology, metabolism, etc. Thus, in this study, we have intended to detect liver-specific microRNAs in farmed carp, Labeo bata, upon being fed a diet with different levels of carbohydrates. Here, we have conducted the experiment for 45 days using fingerlings of farmed carp fed with 20% (control), 40%, and 60% gelatinized starch levels. The liver tissues were collected from each treatment and processed for RNA isolation, small RNA library preparation, and high-throughput sequencing using Illumina NexSeq500. Through sequencing, 15,779,417 reads in 20% CHO, 13,959,039 in 40% CHO, and 13,661,950 in 60% CHO reads were generated for control and treated fishes using three small RNA libraries. We have investigated 445 novel and 231 conserved microRNAs in 20%, 40%, and 60% carbohydrate (CHO), respectively, through computational analysis. The differential expression analysis of miRNAs was carried out between different treatments compared with control and this study depicted 117 known and 114 novel miRNA genes involved in carbohydrate metabolic pathways. Further, target prediction and gene ontology analysis revealed that miRNAs were involved in several pathways such as signaling pathway, G protein pathway, complement receptor–mediated pathway, dopamine receptor signaling pathway, epidermal growth factor pathway, and notch signaling pathway. The predicted miRNA sites in targeted genes were associated with cellular activities, developmental biology, DNA binding, Golgi apparatus, extracellular region, catalytic activity, MAPK cascade, etc. Overall, we have generated a vital resource of liver-specific miRNAs involved in metabolic gene regulation. These studies further will help develop miRNA inhibitors to study their role during carbohydrate metabolism in farmed carp.