Image-based leaf SPAD value and chlorophyll measurement using a mobile phone: enabling accessible and sustainable crop management

Abstract This study evaluates a practical, low-cost solution for image-based leaf SPAD (Soil and Plant Analysis Development) value and chlorophyll content monitoring using a mobile phone. We compare laboratory assay and SPAD-502+ measurements with image-based estimates from a mobile phone app (PhotoFolia). Performance is tested for four commercial rice varieties grown in Thailand. Results show that the image-based method can predict SPAD values within ± 1.2 units Mean Absolute Error (MAE) and chlorophyll concentrations within 7.2% Mean Absolute Percentage Error (MAPE) of laboratory results. Achieving a SPAD value error close to the industry standard of ±1 unit and a relative error of less than 10% in chlorophyll concentration estimation (compared to a laboratory method) demonstrates that an image-based approach using standard mobile phones can serve as an accessible, low-cost tool for on-farm chlorophyll monitoring, without the need for specialised equipment.