Universitas Gadjah Mada Develops AI to Optimize Lettuce Production in Indoor Farming
Yogyakarta – Andri Prima Nugroho, STP., M.Sc., Ph.D., IPU, ASEAN Eng., APEC Eng., a researcher from the Faculty of Agricultural Technology at Universitas Gadjah Mada (UGM), has successfully developed an innovative model to predict the photosynthesis rate of lettuce (Lactuca sativa L.) in indoor farming systems. The research, completed in 2025, uses the Random Forest algorithm to provide accurate photosynthesis estimations, aiming to improve the efficiency of modern agricultural production.
The model developed by Andri Prima Nugroho leverages the Random Forest algorithm, a Machine Learning method, to analyze environmental and physiological data of lettuce plants. As a result, the model can deliver precise predictions of photosynthesis rates, which are crucial for optimizing plant growth conditions.
This research is expected to serve as a key foundation for farmers and indoor farming operators in making smarter decisions regarding environmental control, such as light intensity, temperature, and humidity. The goal is to maximize lettuce growth and yield efficiently.
This internally funded study is also the result of collaboration with external partners, both national and international, reflecting Universitas Gadjah Mada’s commitment to developing technology-driven agricultural solutions. The main output of this research is a model or algorithm ready for implementation to support precision agriculture.
With this AI-based photosynthesis prediction model, indoor farming is expected to achieve higher levels of efficiency and productivity, contributing to food security through sustainable technological innovation.
