Abstract

Accurate prediction of spikelet sterility in rice (Oryza sativa L.) is a prerequisite for accurately predicting grain yield in cool climates, since severe yield losses frequently occur when spikelet sterility is induced by cool temperatures during reproductive growth. Both cool air temperature (Ta) and cool water temperature (Tw) are detrimental factors that can cause spikelet sterility, but a large discrepancy between Ta and Tw is often observed in paddy fields. The depth of water can also affect spikelet sterility. We proposed a model that accounted for the effects of Ta, Tw, and water depth on spikelet sterility, and was based on panicle temperature (Tp), then tested the model using 23 independent sets of field data from northern Japan. We also quantified the role of daily amplitude (the difference between maximum and minimum temperatures) and differences in plant sensitivity to temperature in determining spikelet sterility. A cool‐irrigation experiment revealed that spikelet sterility depended more strongly on Tp than on Tw or Ta. We also developed six models using “cooling degree‐day” concept. The model based on Tp had higher accuracy than models based solely on Tw or Ta. In addition, average temperature was a better predictor than minimum temperature. Accounting for the difference in temperature sensitivity also improved the model's accuracy. A model that considers these factors would thus improve prediction accuracy for spikelet sterility due to cool weather.

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