Deep Learning Applications in Plant Biology: Bridging Genotype and Phenotype

Plant biology now relies on deep learning technology because artificial neural networks use this method to handle complex biological relationships between genotype and phenotype. The use of deep learning models has produced new capabilities for genome interpretation while simultaneously enabling the prediction of gene expression at high speeds and fast plant analysis and disease detection systems. The capability to integrate genotype data with phenotype information enables choices of genotypes alongside combination of omics data points leading to advanced agricultural development. Plant science development potential can be achieved through single-cell research and transfer learning and real-time phenotyping methods although these advances encounter challenges connected to data compatibility and program complexity together with result interpretation difficulties. Modern plant biology research will benefit from AI-driven models because they offer promising capabilities to enhance crop resilience as well as productivity while supporting sustainable agricultural practices.

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Publication Details

Journal
Premier Journal of Plant Biology
Published
2025-02-05
DOI
https://doi.org/10.70389/pjpb.100011
Citations
2
Primary Topic
Genetics, Bioinformatics, and Biomedical Research
Type
article
Field-Weighted Citation Impact
1.61
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article

Deep Learning Applications in Plant Biology: Bridging Genotype and Phenotype

Amita Kajrolkar
2 citations
Premier Journal of Plant Biology
Genetics, Bioinformatics, and Biomedical Research
1.61
article

Deep Learning Applications in Plant Biology: Bridging Genotype and Phenotype

Amita Kajrolkar
article en
2 citations

Abstract

Plant biology now relies on deep learning technology because artificial neural networks use this method to handle complex biological relationships between genotype and phenotype. The use of deep learning models has produced new capabilities for genome interpretation while simultaneously enabling the prediction of gene expression at high speeds and fast plant analysis and disease detection systems. The capability to integrate genotype data with phenotype information enables choices of genotypes alongside combination of omics data points leading to advanced agricultural development. Plant science development potential can be achieved through single-cell research and transfer learning and real-time phenotyping methods although these advances encounter challenges connected to data compatibility and program complexity together with result interpretation difficulties. Modern plant biology research will benefit from AI-driven models because they offer promising capabilities to enhance crop resilience as well as productivity while supporting sustainable agricultural practices.

Premier Journal of Plant Biology
University of Mumbai (IN)
Openalex Percentile: Top 19%
Genetics, Bioinformatics, and Biomedical Research
1.61
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Deep Learning Applications in Plant Biology: Bridging Genotype and Phenotype — Amita Kajrolkar · Premier Journal of Plant Biology (2025) | TGRS Research Map | TGRS