Development of Smart-Farming Calendar for Mungbean (Vigna Radiata L.) Production Using Dssat Model
Herlyn S. Apolonio1, Rafael J. Padre2, Orlando F. Balderama2,
Lanie A. Alejo2
herlynapolonio06@gmail.com
Isabela State University, Echague Campus, Echague, Isabela, Philippines
DOI: https://doi.org/10.54476/ioer-imrj/296016
ABSTRACT
This study was conducted to develop a smart-farming calendar for mungbean (Vigna radiata L.) production in the City of Ilagan, Isabela using the Decision Support System for Agro-Technology Transfer (DSSAT). The study utilized agroclimatic, soil, crop, and management data gathered from field surveys, farmer interviews, soil sampling, and secondary sources. Daily weather data including rainfall, maximum and minimum temperature, and solar radiation were obtained and used as primary climatic inputs for the DSSAT model. The DSSAT model was calibrated using observed yield data from 18 farmer respondents during the 2021 cropping season and validated using an independent dataset from 11 farmers during the 2022 cropping season. Model performance during calibration showed strong agreement between simulated and observed yield values, indicating good predictive capability under local conditions. Simulation results revealed that planting date significantly influenced mungbean yield. Simulated yield gradually increased from early January and reached its highest value of approximately 1,738 kg/ha during mid-April, particularly on April 17. Based on the simulation results, a smart-farming calendar was developed to guide farmers in scheduling key crop production activities including land preparation, planting, fertilizer application, crop growth stages, and harvesting.
Keywords: DSSAT Model, Mungbean Cropping Calendar, DSSAT calibration & validation
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