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Agronomy Journal Abstract - Modeling

Modeling Spikelet Sterility Induced by Low Temperature in Rice


This article in AJ

  1. Vol. 97 No. 6, p. 1524-1536
    Received: Feb 3, 2005

    * Corresponding author(s): shimn@affrc.go.jp
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  1. Hiroyuki Shimono *a,
  2. Toshihiro Hasegawab,
  3. Masahisa Moriyamac,
  4. Shigeto Fujimurad and
  5. Takayuki Nagatad
  1. a Dep. of Biology and Environment Sciences, National Agric. Res. Center for Tohoku Region, Shimokuriyagawa, Iwate, 020-0198, Japan and the Japan Society for the Promotion of Science, Tokyo, 102-8577, Japan
    b Dep. of Global Resources, National Inst. for Agro-Environmental Sciences, Tsukuba, Ibaraki, 305-8604, Japan
    c Dep. of Biology and Environment Sciences, National Agric. Res. Center for Tohoku Region, Shimokuriyagawa, Iwate, 020-0198, Japan
    d Graduate School of Agriculture, Hokkaido University, Sapporo, 060-8589, Japan


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 (T a) and cool water temperature (T w) are detrimental factors that can cause spikelet sterility, but a large discrepancy between T a and T w 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 T a, T w, and water depth on spikelet sterility, and was based on panicle temperature (T p), 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 T p than on T w or T a We also developed six models using “cooling degree-day” concept. The model based on T p had higher accuracy than models based solely on T w or T a 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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