Volumetric Deep Learning-Based Precision Phenotyping of Gene-Edited Tomato for Vertical Farming.

ABSTRACT: Global climate change and urbanization have posed challenges to sustainable food production and resource management in agriculture. Vertical farming, in particular, allows for high-density cultivation on limited land but requires precise control of crop height to suit vertical farming systems. Tomato, a globally significant vegetable crop, urgently requires mutant varieties that suppress indeterminate growth for effective cultivation in vertical farming systems. In this study, we utilized the CRISPR-Cas9 system to develop a new tomato cultivar optimized for vertical farming by editing the Gibberellin 20-oxidase (SlGA20ox) genes, which are well known for their roles in the "Green Revolution". Additionally, we proposed a volumetric model to effectively identify mutants through

SUBMITTER: Jeon YJ 

PROVIDER: S-EPMC12710025 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature