利用卫星遥感进行冬小麦籽粒淀粉含量监测研究

 通过对不同年份、不同区域的遥感影像的植被指数和小麦GPS定点长势数据的综合分析，基于遥感影像信息获取的瞬时性和准确性，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，建立了基于不同生育期（拔节期、抽穗期以及灌浆期）遥感影像归一化植被指数（NDVI）和气候环境因子（气温、日照、氮素营养、土壤水分）的籽粒淀粉含量监测模型，并对模型的可靠性进行了检验。结果表明，模型的监测值与实测值较为一致，利用拔节期、抽穗期、灌浆期遥感影像NDVI和气候环境数据预测籽粒淀粉含量的RMSE值分别为4.57%，4.2%和3.84%。模型监测性能好，且具有解释性，可以用于不同年度、不同区域和不同小麦生长阶段对籽粒淀粉含量的预测。

Study on Monitoring Starch Content in Winter Wheat Grain Using Land-Sat TM Image

The relationships were analyzed between grain starch content and environmental factors including average temperature（T）, solar radiation（S）, nitrogen nutrition（N）, and soil water（W）during grain filling period, then the environmental factor-driven equations were established with TF, SF, NF and WF. By using to modify the impacts of environmental factors on grain starch accumulation, an monitoring model was developed as GSC=（GSCPJ, or GSCPH, or GSCPF） ×TF×ST×min（NF, WF）, where GSCPJ, GSCPH and GSCPF is the perfect starch content of grain which were calculated to with NDVI in jointing, heading and filling stage, respectively. The model was validated using the data sets of NDVI in jointing, heading and filling stage, with the root mean square error （RMSE） of 4.57%, 4.2% and 3.84% for grain starch content in winter wheat, respectively. The results indicated that the model was accurate and applicable for monitoring starch content in winter wheat under different conditions. Yet, more experiment data in different eco-environments are required for wide testing of the present model.