摘要
蛋白质含量是小麦重要的品质指标,快速、大面积获取其变化动态信息,对于品种种植区划研究和食品品质加工非常重要。通过设置不同年份、不同区域的小麦种植试验,综合分析TM遥感影像的植被指数和小麦长势信息之间的关系,结合小麦灌浆期间气候环境条件对籽粒品质形成的影响特点,建立基于NDVI和籽粒氮素积累生理生态过程的籽粒蛋白质含量预测模型。利用不同的试验数据对模型的可靠性进行了检验,模型的预测值与测量值较为一致,均方根差(RMSE)小于0.47%-0.59%。模型预测性能较好,且具有一定的解释性和机理性,可以适用于不同年度、不同区域间对小麦籽粒蛋白质含量的监测预报。基于空间遥感信息和籽粒氮素积累的生理生态过程,建立了较为简化的小麦籽粒蛋白质含量的预测模型,模型的研究不仅为实时预测不同生态条件下小麦籽粒蛋白质含量的动态变化奠定了基础,而且是对国内外现有小麦品质模型的发展和完善。
Wheat is one of the most important crops,and its grain protein content varies from 9% to 18%.Grain protein content is one of the important quality index of winter wheat product.The winter wheat can be divided into weak-gluten (≤1.5%),medium-gluten(>11.5% and<15%)and strong-gluten types(≤15%)according to Chinese of Stantard grain protein content(GB/T 17892-1999 and GB/T17893-1999).Therefore,it is valuble to monitor grain protein content from remotely sensed image for winter wheat quality division and food processing at large scale.Almost all the previous re- searches of monitoring grains protein have made use of content empirical statistical model between grain protein content and the canopy or image spectral information.These empirical statistical models were limited frequently by spatial and temporal condition of the experiments.If the grain protein content of winter wheat is monitored by using the empirical statistical model,serious predicting error often occurs due to the variations of the external experiment conditions,such as tempera- ture,sunlight,soil condition,fertilization and irrigation.The crop growth model possesses the traits of better continuity and mechanism,which can simulate winter wheat growth status dynamically for all growth stages,and can interpret the difference resulted from temporal or environmental changes.However,it is difficult to predict grains protein content of winter wheat at large region by the crop growth model,because the spatial distribution of the crop growth model's parame- ters,such as LAI,above-ground biomass,canopy the temperature and soil moisture cannot be collected without remote sensing technique.Some researches result indicated that from quantitative remote sensing data we can retrieve the spatial distribution information for the growth model parameters.Therefore,it is necessary to monitor grain protein content of win- ter wheat dynamically by assimilating remote sensing data and crop growth model.The field experiments were carried out in Jiangsu and Henan province during 2003 to 2005.The dynamic relations between vegetation index of remote sensing and growth condition of winter wheat were analyzed,and the nitrogen transfer model from plant to grain was built based on the experiment data in Jiangsu province in 2005.As a result,the predicting model for grain protein content of winter wheat was developed based on the normalized difference vegetation index(NDVI)of TM image of the landsat satellite and grain nitrogen accumulation.According to the predicting model,the plant nitrogen accumulation,leaf area index(LAI) and dry above-ground biomass were firstly regressed from NDVI at anthesis,then,the grain nitrogen accumulation was predicted by using the plant nitrogen transfer model from plant to grain.The model was validated using the data sets of dif- ferent ecological regions in Henan province in 2003 and in Jiangsu province in 2004.The root mean square error(RMSE) of the predicted grain protein content varied from 0.47% to 0.59%,and the RMSE of the nitrogen accumulation varied from 4.75 kg·hm^(-2)to 8.76 kg·hm^(-2).Therefore,the model was accurate and applicable for predicting grain protein content of winter wheat under various conditions,which made it possible to predict grain protein content at large region from remotely sensed images.However,the formation of protein content in winter wheat grain is very complex,which is not only influenced by genotype,but also by environmental conditions,such as air temperature,solar radiation,soil con- ditions,fertilization and irrigation.Besides,remote sensing image is influenced by the function sensor,the atmospheric conditions,and imaging angle.Therefore,the model presented in this paper still need to be tested by remote sensing exper- imental data under different environments.
出处
《遥感学报》
EI
CSCD
北大核心
2008年第3期506-514,共9页
NATIONAL REMOTE SENSING BULLETIN
基金
国家863计划项目(编号:2006AA12Z138)
国家自然基金项目(编号:40571118)
北京市农林科学院青年基金(编号:08BH01)
关键词
冬小麦
TM影像
氮素积累
籽粒蛋白质含量
预测模型
winter wheat
TM image
nitrogen accumulation
grain protein content
predicting model