Validation assessment of nitrogen and irrigation effects on early maturing rice varieties Cakrabuana and Inpari 13 through ORYZA (v3) modeling
2025
Baharuddin, Achmad Kautsar | Padjung, Rusnadi | Kaimuddin, Kaimuddin | Musa, Yunus | Bahrun, Abd Haris | Yassi, Amir | Casimero, Madonna | Llorca, Lizzida | Bugayong, Iris | Jardinero, Benedict | Sembiring, Hasil | Nur, Amin | Wasonga, Daniel O. | Seleiman, Mahmoud F. | Anshori, Muhammad Fuad
Climate-related challenges in rice production in Indonesia underscore the necessity for early-maturing rice varieties. Developing these varieties can enhance productivity by shortening cropping cycles, although the process is often time-consuming, costly, and requires testing across multiple locations. Thus, modeling approaches offer efficient means of simulating the performance of various early maturing rice varieties across many conditions. This study addresses the limited application of the ORYZA (v3) model in tropical settings by calibrating and validating it using field data from two early-maturing rice cultivars: Cakrabuana and Inpari 13. The research used nested split-plots with three replications, two irrigation treatments, continuous flooding (CF) and alternate wetting and drying (AWD), alongside three nitrogen dosage levels: 0 kg ha−1, 90 kg ha−1, and 180 kg ha−1 were implemented. Model calibration was based on observations of phenology and biomass, focusing on parameters such as developmental rates and biomass partitioning. Validation was conducted using independent field data, calibrated Cakrabuana and Inpari 13 crop parameters, and relevant climate and soil information. Cakrabuana met the metric standards, with RMSEn values of 0.11 to 0.17, NSE from 0.68 to 0.93, and MAPE between 0.08 and 0.13%. While, Inpari 13 met the standards for the weight of storage organs. Model tests revealed strong validity for Cakrabuana, while Inpari 13’s lower validity resulted from environmental sensitivity. These findings support the ORYZA (v3) calibrated model as a reliable support planting forecasts for Cakrabuana variety, while further calibration of Inpari 13 is needed.
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