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基于有效积温的中国水稻生长模型的构建
引用本文:苏李君,刘云鹤,王全九.基于有效积温的中国水稻生长模型的构建[J].农业工程学报,2020,36(1):162-174.
作者姓名:苏李君  刘云鹤  王全九
作者单位:西安理工大学省部共建西北旱区生态水利国家重点实验室,西安 710048;西安理工大学省部共建西北旱区生态水利国家重点实验室,西安 710048;中国科学院水利部水土保持研究所黄土高原土壤侵蚀与旱地农业国家重点实验室,杨凌 712100
基金项目:国家自然科学基金面上项目(51679190);国家自然科学基金重点项目(41830754);国家自然科学基金面上项目(51979220)
摘    要:有效积温是指作物生长至某一生育阶段所需要积累的有效温度,是反映气象条件对作物生长影响的主要指标,研究有效积温对作物生长过程的影响对提高农业生产效率具有重要意义。该文以有效积温作为气象因子,收集中国气象数据网中的气象数据和已发表的学术论文中的水稻生长数据,建立了描述水稻生长过程的叶面积指数和干物质积累量的普适Logistic模型,并研究了水稻最大叶面积指数与最大干物质积累量、收获指数(作物经济产量与生物产量的比值)及降水量之间的关系。结果表明:有效积温为1000℃左右时,水稻叶面积指数最大,且此时干物质增长速率最大;水稻最大叶面积指数与最大干物质积累量之间表现为线性关系;最大叶面积指数和收获指数、降水量之间为二次抛物线关系,当降水量为670.5 mm时,最大叶面积指数为7.93,对应的水稻收获指数达到最大值0.50。该研究对于构建其他作物的生长模型具有一定的参考意义。

关 键 词:降水量  生物量  水稻  有效积温  作物生长指标  Logistic模型
收稿时间:2019/4/16 0:00:00
修稿时间:2019/10/10 0:00:00

Rice growth model in China based on growing degree days
Su Lijun,Liu Yunhe and Wang Quanjiu.Rice growth model in China based on growing degree days[J].Transactions of the Chinese Society of Agricultural Engineering,2020,36(1):162-174.
Authors:Su Lijun  Liu Yunhe and Wang Quanjiu
Institution:1. Xi''an University of Technology, State Key Laboratory Base of Eco-hydraulic Engineering in Arid Area, Xi''an 710048, China;,1. Xi''an University of Technology, State Key Laboratory Base of Eco-hydraulic Engineering in Arid Area, Xi''an 710048, China; and 1. Xi''an University of Technology, State Key Laboratory Base of Eco-hydraulic Engineering in Arid Area, Xi''an 710048, China; 2. Institute of Soil and Water Conservation Chinese Academy of Sciences, State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Yangling 712100, China;
Abstract:Temperature determines the maturity of crops by affecting the formation of dry matter, and ultimately affects crop yield. Therefore, studying the relationship between temperature and crop growth is very important to improve agricultural production efficiency. In this study, an universal Logistic model for describing the growth process of rice was established with growing degree days as independent variable, the leaf area index and dry matter accumulation of rice as dependent variable, respectively. A large number of data of rice growth index were collected. At the same time, the relationships between the maximum leaf area index, the maximum dry matter accumulation, harvest index(the ratio of crop economic yield to total biomass) and precipitation throughout the growth period of rice were analyzed. The results showed that with the increase of growing degree days, the change of rice leaf area index revealed obvious characteristics: increase firstly then decrease, and the change trend of leaf area index in different regions was basically similar. When the growing degree days was increased to about 1 000 ℃, the leaf area index reached the maximum and this stage corresponded to the booting stage. When the growing degree days was increased to about 1 000 ℃, the increase rate of dry matter accumulation was the largest. At this time, the leaf area almost stoped growing, and the rice entered the reproductive growth stage. There was an obvious linear relationship between the maximum leaf area index and the maximum dry matter accumulation of rice. With the increase of the maximum leaf area index, the maximum dry matter accumulation increased gradually. There was a quadratic polynomial relationship between the maximum leaf area index and harvest index of rice. When the maximum leaf area index was about 8, the harvest index was the largest. The maximum leaf area index of rice increased first and then decreased with the increase of precipitation in the whole growing period. When the precipitation of the whole growing period was about 670.5 mm, the maximum leaf area index of rice increased to about 7.9. The corresponding harvest index was also almost the maximum value. If the precipitation was more than 670.5 mm, the growth of rice leaves would be inhibited, and the photosynthesis of rice leaves would be weakened, so that the function of leaves could not be brought into full play. At the same time, too much precipitation was not conducive to the growth of rice roots, resulting in yield reduction. In this study, the rice growth regulation and yield prediction model were constructed. The results showed that the growing degree days could be used to analyze the growth process of rice accurately, and it could improve the precision of rice yield prediction and efficiency agricultural production. In this study, we considered the relationsips between the meteorological factors and the crop growth, and established the universal rice growth model by using growing degree days, precipitation and the physiological index of the rice, and estalished the prediction model of the rice yield by using the harvest index. It would be a guidance of constructing growth models of other crops.
Keywords:precipitaition  biomass  rice  growing degree days  crop growth index  Logistic models
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