Browsing by Author "Angadi, U.B"

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    DeepAProt: Deep learning based abiotic stress protein sequence classification and identification tool in cereals
    (Frontiers in Plant Science, 2023) Ahmed, Bulbul; Haque, Md Ashraful; Iquebal, Mir Asif; Jaiswal, Sarika; Angadi, U.B; Kumar, Dinesh; Rai, Anil
    The impact of climate change has been alarming for the crop growth. The extreme weather conditions can stress the crops and reduce the yield of major crops belonging to Poaceae family too, that sustains 50% of the world’s food calorie and 20% of protein intake. Computational approaches, such as artificial intelligence-based techniques have become the forefront of prediction-based data interpretation and plant stress responses. In this study, we proposed a novel activation function, namely, Gaussian Error Linear Unit with Sigmoid (SIELU) which was implemented in the development of a Deep Learning (DL) model along with other hyper parameters for classification of unknown abiotic stress protein sequences from crops of Poaceae family. To develop this models, data pertaining to four different abiotic stress (namely, cold, drought, heat and salinity) responsive proteins of the crops belonging to poaceae family were retrieved from public domain. It was observed that efficiency of the DL models with our proposed novel SIELU activation function outperformed the models as compared to GeLU activation function, SVM and RF with 95.11%, 80.78%, 94.97%, and 81.69% accuracy for cold, drought, heat and salinity, respectively. Also, a web-based tool, named DeepAProt (http://login1.cabgrid. res.in:5500/) was developed using flask API, along with its mobile app. This server/App will provide researchers a convenient tool, which is rapid and economical in identification of proteins for abiotic stress management in crops Poaceae family, in endeavour of higher production for food security and combating hunger, ensuring UN SDG goal 2.0.
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    Unveiling the Wheat Microbiome under Varied Agricultural Field Conditions
    (2022-11) Jaiswal, S; Aneja, B; Jagannadham, J; Pandey, B; Chhokar, RS; Gill, S; Ahlawat, O; Kumar, A; Angadi, U.B; Rai, A; Tiwari, R; Iquebal, M; Kumar, D
    Wheat being the important staple food crop plays a significant role in nutritional security. A wide variety of microbial communities beneficial to plants and contributing to plant health and production are found in the rhizosphere. The wheat microbiome encompasses an extensive variety of microbial species playing a key role in sustaining the physiology of the crop, nutrient uptake, and biotic/abiotic stress resilience. This report presents wheat microbiome analysis under six different farm practices, namely, organic (Org), timely sown (TS), wheat after pulse crop (WAPC), tem perature-controlled phenotyping facility (TCPF), maize-wheat cropping system (MW), and residue burnt field (Bur), using 16S rRNA sequencing methodology. The soil sam ples collected from either side of the wheat row were mixed to get a final sample set for DNA extraction under each condition. After the data preprocessing, microbial com munity analysis was performed, followed by functional analysis and annotation. An abundance of the phylum Proteobacteria was observed, followed by Acidobacteria, Actinobacteria, andGemmatimonadetes in the majority of the samples, while relative abundance was found to vary at the genus level. Analysis against the Carbohydrate Active Enzymes (CAZy) database showed a high number of glycoside hydrolase genes in the TS, TCPF, and WAPC samples, while the Org, MW, and Bur samples predomi nantly had glycosyltransferase genes and carbohydrate esterase genes were in the low est numbers. Also, the Org and TCPF samples showed lower diversity, while rare and abundant species ranged from 12 to 25% and 20 to 32% of the total bacterial species in all the sets, respectively. These variations indicate that the different cropping sequence had a significant impact on soil microbial diversity and community composi tion, which characterizes its economic and environmental value as a sustainable agri cultural approach to maintaining food security and ecosystem health.