李树强,李民赞.冬小麦生育早期长势反演模型通用性研究[J].农业机械学报,2014,45(2):246-250.
Li Shuqiang,Li Minzan.Generality of Winter Wheat Growth Prediction in Early Growth Periods[J].Transactions of the Chinese Society for Agricultural Machinery,2014,45(2):246-250.
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冬小麦生育早期长势反演模型通用性研究   [下载全文]
Generality of Winter Wheat Growth Prediction in Early Growth Periods   [Download Pdf][in English]
投稿时间:2013-08-21  
DOI:10.6041/j.issn.1000-1298.2014.02.041
中文关键词:  冬小麦 生育早期 叶绿素 通用模型 偏最小二乘法
基金项目:“十二五”国家科技支撑计划资助项目(2012BAH29B04)和国家高技术研究发展计划(863计划)资助项目(2013AA102303)
作者单位
李树强 河南科技大学,中国农业大学 
李民赞 中国农业大学 
中文摘要:分析了生育早期(返青期、拔节前期、拔节后期)各阶段的冠层叶片光谱特性与叶绿素含量的关系,基于单波段反射率构建了一元预测模型,同样基于植被指数构建了多元叶绿素含量的反演模型,对两类建模方法构建的叶绿素含量预测模型进行了同生长阶段预测(SPV)和后续生长阶段的交叉预测(CPV),比较了模型的预测效果,得出了构建冬小麦生育早期冠层叶片叶绿素含量的通用预测模型的建模策略。研究结果表明:以返青期冠层叶片单波段反射率构建的一元反演模型,具有一定的模型通用性,能够较为准确的预测拔节前期的叶片叶绿素含量。利用偏最小二乘原理构建多元反演模型具有良好的通用性和较强的鲁棒性,能够较好地反演冬小麦生育早期冠层叶片叶绿素含量。而以MPRI、NDVI、RVI为组合构建的多元模型兼具通用性和简练性,可以作为多元预测模型构建的参考组合。
Li Shuqiang  Li Minzan
Henan University of Science and Technology,China Agricultural University;China Agricultural University
Key Words:Winter wheat Early growth period Chlorophyll General model PLS
Abstract:The winter wheat early growth period consists of reviving stage, early jointing stage and later joint stage, which is the most important period for precision management. It is significance to understand the growth status of winter wheat and provide accurate and scientific data for precision agriculture in the early growth period. The general model used to describe the canopy reflectance and chlorophyll of early growth period was necessary. The linear regression models, which used character wavelength as independent variable, were constructed. The PLS(partial least square) algorithm was applied to construct multiple regression models, which used the vegetation index as the independent variables. All models were used to predict the chlorophyll content in the same period and different periods. The better general model was found according to the predictive effect. According to the curve of correlation between reflectance and chlorophyll content, the curve ranged from 500 nm to 600 nm contained the extreme values. The linear regression independent variable was 550 nm selected from this range. The linear regression model of the reviving stage predicted accurately in the early jointing stage and poorly in the later jointing stage. In contrast, the multiple regression prediction model of the reviving stage had more versatile. It showed the satisfactory predication in early and later jointing stage. In order to improve the accuracy of predication in different stages, MPRI(mobil PRI) was developed to construct the multiple model with NDVI(normalized differential vegetation index) and RVI(ration vegetation index), instead of TCARI. The test results proved that MPRI was simpler than TCARI on the parameter and the structure. The multiple model, made by MPRI,NDVI and RVI was general for the winter wheat growth periods.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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