无人机搭载数码相机航拍进行小麦、玉米氮素营养诊断研究

Diagnosis of nitrogen nutrition of winter wheat and summer corn using images from digital camera equipped on unmanned aerial vehicle

  • 摘要: 精准施肥是减少农业面源污染的重要技术之一,而土壤养分测试与作物营养诊断是其实施的技术保障,特别是在农业规模化经营方式下,急需发展快速、经济、无损的作物氮素营养诊断技术。本文在应用数字图像进行冬小麦、夏玉米氮素营养诊断研究的基础上,将数码相机搭载到无人机上,利用无人机航拍技术采集作物冠层数字图像,研究不同航拍高度下冠层图像相关色彩参数反演冬小麦和夏玉米氮素营养状态的差异,以确定适宜的航拍高度与敏感的色彩参数,建立利用无人机航拍数字图像诊断冬小麦和夏玉米氮素营养状态模型。研究结果表明:在冬小麦拔节期适宜的航拍高度是16 m,敏感的色彩参数是可见光大气阻抗植被指数(VARI),诊断模型为:冬小麦茎基部硝酸盐浓度=2.103 4e18.874VARI;夏玉米大喇叭口期适宜的航拍高度是50 m,敏感色彩参数是蓝光标准化值B/(R+G+B),诊断模型为:夏玉米第1完全展开叶叶脉硝酸盐浓度=1.526×1032×B/(R+G+B)50.445。依据建立的航拍方法与诊断模型,分别对冬小麦、夏玉米进行了氮素状态监测的验证,结果表明诊断结果与冬小麦、夏玉米实测数据的决定系数分别为0.80和0.85,且均在P < 0.01水平显著相关。最后将研究结果进行应用,生成了冬小麦、夏玉米氮肥追肥作业图。利用无人机搭载数码相机对冬小麦、夏玉米进行氮素营养诊断简单、可行,但仍有一些技术细节需要完善,以提高该技术的实用性。

     

    Abstract: The large number of population and scarce land resources require crop yield per unit area to be increased greatly to ensure the food supplies and food security in China. To meet this requirement, chemical fertilizer application is an important and simple measure. Consequently, the agricultural non-point pollution caused by chemical fertilizer is becoming more and more serious. Precision fertilization is one of the important technologies to control agricultural non-point source pollution, while soil nutrient testing and crop nutrition diagnosis are indispensable works of precision fertilization. With the increasing of agriculture scale management, it is urgent to develop fast, economic and nondestructive techniques of the nitrogen nutrition diagnosis of crops. In this study, in the light of related researches of diagnosis of nitrogen nutrition in winter wheat and summer corn using digital photographs, cost-effective unmanned aerial vehicle (UAV) system was introduced and digital camera mounted on its platform was used to obtain the canopy photographs of crops. To determine the appropriate aerial heights and sensitive color parameters of aerial photographs for the diagnosis of nitrogen nutrition of winter wheat and summer corn, the relationships between a variety of color parameters retrieved from the aerial photographs obtained at different heights and the status of nitrogen nutrition of winter wheat and summer corn measured in situ in 2015 were analyzed. It was indicated that VARI (visible atmospherically resistant index based on digital photography) and B/(R+G+B) were the most sensitive color parameters for the diagnosis of nitrogen nutrition in winter wheat and summer corn, respectively. For the winter wheat, 16 m was the suitable aerial height at jointing stage, and the diagnosis model was:stem sap nitrate concentration= 2.103 4e18.874VARI. 50 m was the best aerial height for summer corn at big trumpet stage, and the diagnosis model was:vein nitrate concentration=1.526×1032×B/(R+G+B)50.445. The established diagnose models were verified at the same field in 2016. The results showed that the determination coefficients of relationship between predicted and observed nitrate nitrogen concentrations of stem sap of winter wheat and vein of summer corn were 0.80 and 0.85, respectively, with significant levels of P < 0.01. In 2017, the method was applied to the diagnosis of nitrogen nutrition of winter wheat and summer corn in Nanpi County, Hebei Province, and the prescription maps of top-dressing nitrogen fertilizer for winter wheat and summer corn were made. The nitrogen fertilization rates of winter wheat and summer corn given by the prescription maps were fitting well with the growth status of crops. As shown in this study, diagnosis of nitrogen nutrition of winter wheat and summer corn using photographs from digital camera equipped on UAV was a cost-effective way to achieve precision management of fertilization. Beyond the achievements of this study, there were still problems should be solved to enhance the practicability and applicability of this method.

     

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