Accurate prediction of rice harvest dates for Pathumthani 1 and RD - MAEJO 2 rice cultivars using growing degree-day (GDD) obtained from IoT digital weather station

Abstract

Rice cultivation plays a pivotal role in Thailand’s economy, with physical factors significantly affecting rice growth and production quality. Prediction of harvest dates for Pathumthani 1 and RD - Mae Jo 2 rice varieties using IoT digital weather station data collection equipment to record temperature data, which was utilized to calculate growing degree-day (GDD). Additionally, we conducted physical property assessments to determine the quantity and quality of rice grains. Our findings revealed that the Pathum Thani 1 rice variety required an accumulated temperature of 1,865.50 GDD to reach maximum ripeness (55.18% developed whole kernels), corresponding to 110 days after sowing. For the RD - Mae Jo 2 rice variety, 1,862.00 GDD was needed for maximum growth (62.36% developed whole kernels), resulting in harvest after 110 days post-sowing. The GDD data accumulated from the sowing date until the harvest date allowed us to develop precise harvest date prediction models with a harvesting efficiency coefficient of 0.013. These insights can be applied to enhance database systems for predicting and recommending optimal rice harvest times for Pathum Thani 1 and RD - Mae Jo 2 rice varieties, benefitting local farmers.