Introduction Recording sap flow in plants is essential to understanding water usage, especially for herbaceous species like tomatoes. While plant physiology research has progressed, there remains a gap in applying sap flow sensor data to these species. In this study, the predictive capabilities of Recurrent …

Consistency issues limit the sharing of horticultural data across multiple systems, resulting in challenges for users to analyze data effectively across various systems utilizing artificial intelligence technology. Introducing data governance principles can help standardize and unify data practices, …

This study focuses on forecasting tomato sap flow in relation to various climate and irrigation variables. The proposed study utilizes different machine learning (ML) techniques, including linear regression (LR), least absolute shrinkage and selection operator (LASSO), elastic net regression (ENR), support …

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