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本文以生物学为基础，发展了一个包含非线性积温模式并考虑了日长影响的冬小麦生长发育阶段（DVS）模式，该模式不同于一般以往的冬小麦分段发育模型，它是一个统一的发育模式，利用中国小麦生态实验资料研究表明：黄淮海地区秋播冬小麦发育速度模式可以拟合为V=2．34×10－3＋1．21×10－3×e0．30（DL-DL0）＋1．62×10－7×（T－Tmin）（1．93）（Tmax－T）（1．14），其中T为日平均温度，DL为日长，DL0为临界日长，Tmin、Tmax为小麦生育的最高、最低温度；V的逐日累加即为该日的DVS值。利用中国小麦生态资料确定的DVS值分别为：出苗0．03，三叶0．07，拨节0．70，抽穗0．88，开花0．89，成熟1．0。平均拟合误差3．6天。利用该模型可对大田冬小麦生长进行监测研究。
Based on biology, this paper develops a winter wheat growth and development stage (DVS) model that includes a non-linear accumulated temperature pattern and takes into account the effects of daily growth. This pattern is different from the general previous winter wheat segmented development model, which is a unified development The results showed that the winter wheat sowing rate in Huang-Huai-Hai region could be fitted as V = 2.34 × 10-3 + 1.21 × 10-3 × e0.30 (DL-DL0) +1. (T-Tmin) (1.93) (Tmax-T) (1.14), where T is the daily average temperature, DL is the day length, DL0 is the critical day length, Tmin and Tmax are the wheat Maximum fertility, minimum temperature; V daily accumulation is the DVS value of the day. The DVS values determined by ecological information of Chinese wheat were 0.03 for emergence, 0.07 for clover, 0.70 for dial, 0.88 for heading, 0.89 for flowering and 1.0 for maturity. The average fitting error of 3.6 days. The model can be used to monitor the growth of winter wheat in the field.