An Assessment of the Feasibility and Impacts of Optimized Alternate Wetting and Drying (AWD) Systems in Various Thai Rice Cultivars

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Bittawat Wichaidist
Duangporn Vithoonjit

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By assessing water-use efficiency in the face of increasing environmental uncertainties, this study addressed an essential requirement for climate adaptation in rice production. In two different seasons, we examined the physiological reactions of four Thai rice cultivars (RD61, RD97, RD111, and PTT1) under four different irrigation regimes: continuously flooding (CF), conventional AWD (cAWD), intensive AWD (iAWD), and drought condition (D). The results demonstrated that cAWD maintained grain yields and physiological integrity comparable to CF, with yield potential reaching 1.1 ton in the wet season. Conversely, iAWD and drought treatments induced severe metabolic strain, particularly in the dry season, where high VPDleaf and lower humidity suppressed quantum yield of photosystem II (ΦPSII) which decreased to 0.228–0.477, and electron transport rate (ETR) which decreased to 146–276 μmol m−2 s−1. Furthermore, restricted stomatal conductance (gsw) under iAWD and drought treatments led to elevated leaf temperatures (Tleaf) and increased chlorophyll fluorescence (Fs). These comparisons highlight that while cAWD is a robust strategy, exceeding the -15 cm threshold poses significant risks to productivity. Seasonal dynamics significantly influenced genotypic responses to water management. During the wet season, characterized by higher rainfall and more frequent rainy days, RD61, RD97, and PTT1 demonstrated high adaptability under iAWD, maintaining grain yields comparable to the CF. Conversely, in the dry season under reduced rainfall and fewer rainy days, only RD61 managed with iAWD exhibited physiological resilience, sustaining a grain yield that did not statistically differ from CF. Therefore, the successful adaptation of alternative irrigation technique requires integrating precise hydrological thresholds with cultivar-specific resilience and real-time climate data to ensure food security within the Water-Energy-Food Nexus.

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