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Chloro: Optimizing Random Forest Regression Model for Accurate Forecasting of Days to Harvest in Hydroponic Lettuce Cultivation Poster

Chloro: Optimizing Random Forest Regression Model for Accurate Forecasting of Days to Harvest in Hydroponic Lettuce Cultivation

This study developed a system that forecasts the days to harvest hydroponically grown lettuce by optimizing the Random Forest Regressor model, which analyzes patterns in nutrient conditions, namely pH level, Total Dissolved Solids (TDS), air temperature, and relative humidity.

Group Members

star iconAlessandra Gayle S. Cilotstar iconKristianne M. Gabasstar iconJessica D. Ibarbiastar iconMica Ellah Tambalong

Mentor

star iconDr. Angelo C. Arguson

Topics

star iconAgriculture

AVP

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