QUANTITATIVE TRAIT LOCI ANALYSIS FOR ASSESSING RAGI'S BLAST RESISTANCE USING MACHINE LEARNING TECHNIQUE

• Main Authors: Baig, Mirza Shahed, Khobragade, Bhavana Purushottam, Ujan, Javed Ahmed, Anees, Mohammed Imran, Shukla, Piyush Kumar, Hemlathadhevi, A, Kumar Agarwal, Ravindra, D. R., Thirupurasundari, Nanda, Namrata, Acharjya, Pinaki Pratim, Mitra, Jayati Chatterjee, Ponnusamy, Sivakumar
• Format: Patent
• Language: English
• Published: 25.11.2021
• Subjects: AGRICULTURE; ANIMAL HUSBANDRY; BEER; BIOCHEMISTRY; CHEMISTRY; COMPOSITIONS OR TEST PAPERS THEREFOR; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL ORENZYMOLOGICAL PROCESSES; ENZYMOLOGY; FISHING; FORESTRY; HUMAN NECESSITIES; HUNTING; INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS; MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEICACIDS OR MICROORGANISMS; METALLURGY; MICROBIOLOGY; MUTATION OR GENETIC ENGINEERING; NEW PLANTS OR PROCESSES FOR OBTAINING THEM; PHYSICS; PLANT REPRODUCTION BY TISSUE CULTURE TECHNIQUES; PROCESSES OF PREPARING SUCH COMPOSITIONS; SPIRITS; TRAPPING; VINEGAR; WINE

Quantitative Trait Loci Analysis for Assessing Ragi's Blast Resistance Using Machine Learning Technique ) Ragi and Wheat utilisation has differentiated in latest days, from simplified utilisation as a primary ingredient to advertising, handling, and livestock nourish utilises. Ragi manufacturers must reduce manufacturing expenses since inflation variations among Ragi and perhaps other agricultural products like wheat and corn impacts yet if paddy is employed for other significance implementations. Increased production via the advancement of high-yielding crops is amongst the most appropriate efficiency metrics. Even many traits of concern in organic agriculture have probabilistic heritage, which complicates the seed germination because genomic efficiency even moderately illustrates users' chromosomal beliefs. The genetic diversity of an empirical trait is thought to be regulated by the collaborative impacts of quantitative trait loci, epistasis, the ecosystem, and QTL-environment activity. Ragi blast is a commercially significant and ephemeral Ragi disorder. The use of host resistance chromosomes to reproduce immune variants has been shown to be the most efficacious and cost-effective strategy of controlling Ragi blast, necessitating the emergence of future friction gene mutations or quantitative trait loci. Quantitative trait loci are phenotypic areas correlated with quantitative trait phenotype fluctuation. Molecular indicators for QTL detection varied across analyses, and yet simple sequence repeats or single nucleotide polymorphisms were the most commonly preferred. Methodologies with many plugins and registry folders were formed to pinpoint PCR- and SNP-based indicators onto the identical relation, co-locate QTL, and probe genome-wide genetic markings to distinctively define SSR and SNP indicators from multiple perspective onto the newly previewed chromosome-scale pseudomolecules. Innovative feature selection methodologies, such as Maximum Relevance Minimum Redundancy (mRMR) and Incremental Feature Selection (IFS), are often used to optimise the evaluation of the influenced gene mutations by the genome indicator to reproduce SKN for blast resistance through marker-assisted hybridisation and genetic evaluation. Our method incorporates ridge regression, recursive feature elimination, and bootstrap resampling to estimate generalization efficiency and marker influence.