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.

Phylogenetic Relationship Among Brackishwater Vibrio Species.

Abstract: Vibriosis is regarded as an important disease of penaeid shrimps affecting larvae in hatcheries. Among the Vibrio species, Vibrio parahaemolyticus, Vibrio vulnificus, Vibrio furnissii, Vibrio campbellii, Vibrio harveyi, Vibrio alginolyticus, and Vibrio anguillarum are often associated with diseases in finfish and shellfish of brackishwater ecosystem. Accurate species differentiating methods for the organisms present in an ecosystem are required for precise classification of the species and to take steps for their management. Conventional methods like 16s rRNA phylogeny and multilocus sequence typing (MLST) have often failed to correctly identify Vibrio species. This has necessitated a comprehensive investigation on methodologies available to distinguish Vibrio species associated with brackishwater aquaculture system. To achieve this, 35 whole genomes belonging to 7 Vibrio species were subjected to phylogenetic analysis based on 16s rRNA gene, MLST genes, single-copy orthologous genes, and single-nucleotide polymorphisms. In addition, genome-based similarity indices like average nucleotide identity (ANI) and in silico DNA-DNA hybridization (DDH) were computed as confirmatory tests to verify the phylogenetic relations. There were some misclassifications occurred regarding phylogenetic relations based on 16s rRNA genes and MLST genes, while phylogeny with single-copy orthologous genes produced accurate species-level clustering. Study reveals that the species identification based on whole genome-based estimates or genome-wide variants are more precise than the ones done with single or subset of genes.

Deep long short-term memory based model for agricultural price forecasting

Abstract: Agricultural price forecasting is one of the research hotspots in time series forecasting due to its unique characteristics. In this paper, we developed a deep long short-term memory (DLSTM) based model for the accurate forecasting of a nonstationary and nonlinear agricultural prices series. DLSTM model is a type of deep neural network which is advantageous in capturing the nonlinear and volatile patterns by utilizing both the recurrent architecture and deep learning methodologies together. The study further compares the price forecasting ability of the developed DLSTM model with conventional time-delay neural network (TDNN) and ARIMA models using international monthly price series of maize and palm oil. The empirical results demonstrate the superiority of the developed DLSTM model over other models in terms of various forecasting evaluation criteria like root mean square error, mean absolute percentage error and mean absolute deviation. The DLSTM model also showed dominance over other models in predicting the directional change of those monthly price series. Moreover, the accuracy of the forecasts obtained by all the models is also evaluated using the Diebold–Mariano test and the Friedman test whose results validate that the DLSTM based model has a clear advantage over the other two models.

Degradation of Kresoxim-Methyl in Water: Impact of Varying pH, Temperature, Light and Atmospheric CO2 Level

Abstract: In the present investigation, persistence of kresoxim-methyl (a broad spectrum strobilurin fungicide) was studied in water. Results revealed that kresoxim-methyl readily form acid metabolite. Therefore, residues of kresoxim-methyl were quantified on the basis of parent molecule alone and sum total of kresoxim-methyl and its acid metabolite. In water, influence of various abiotic factors like pH, temperature, light and atmospheric carbon dioxide level on dissipation of kresoxim-methyl was studied. The half life value for kresoxim-methyl and total residue varied from 1 to 26.1 and 6.1 to 94.0 days under different conditions. Statistical analysis revealed the significant effect of abiotic factors on the dissipation of kresoxim-methyl from water.

Understanding the biological role of PqqB in Pseudomonas stutzeri using molecular dynamics simulation approach.

Abstract: Phosphate solubilization is an important and widely studied plant growth promoting trait exhibited by many bacteria. Pyrroloquinoline quinone (PQQ), a redox cofactor of methanol and glucose dehydro...