Year: 2025
Type: article
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.
Source: Premier Journal of Plant Biology
DOI: 10.70389/pjpb.100011
Author: Amita Kajrolkar
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: hybrid
OpenAlex ID: W4408037926