基于无人机遥感可见光参数的水稻氮素营养诊断
2021-06-17袁璐袁自然屠人凤叶寅陈晓芳杨欣
袁璐 袁自然 屠人凤 叶寅 陈晓芳 杨欣



摘 要:氮素是决定水稻产量的重要因素之一,传统水稻氮素的诊断耗时费力且对作物的损害较大,确定无人机遥感水稻氮素营养诊断的最佳可见光参数,对水稻氮素的快速诊断具有良好的实用价值。该研究在安徽省怀远县试验基地,设置5个施氮水平,先后2次进行无人机采样,计算出10个可见光参数,并分析可见光参数与水稻含氮量之间的关系,结合相关系数与变异系数的大小筛选出诊断水稻氮素的最佳可见光参数。结果表明,参数B、G/(R+G+B)、G/B、RGBV1与作物含氮量的相关性较强,其中参数G/(R+G+B)可作为无人机为遥感水稻氮素诊断的最佳可见光参数。通过回归分析得到y(含氮量)与x(绿光化标准值)之间的回归方程y=0.0017x2-0.0074x+0.7201,R2=0.9825。
关键词:无人机遥感;可见光参数;水稻;氮素营养
中图分类号 S511文献标识码 A文章编号 1007-7731(2021)10-0035-04
Rice Nitrogen Nutrition Diagnosis Based on UAV Remote Sensing Visible Light Parameters
YUAN Lu1, 3 et al.
(1Institute of Soil and Fertilizer, Anhui Academy of Agricultural Sciences, Hefei 230031, China; 3College of Resources and Environment, Anhui Agricultural University, Hefei 230031, China)
Abstract: Nitrogen is one of the important factors that determine rice yield. Traditional rice nitrogen diagnosis is time-consuming and laborious and has great damage to crops. To determine the best parameters for the diagnosis of rice nitrogen nutrition by UAV remote sensing visible light parameters. The rapid diagnosis of nitrogen in rice has good practical value. In this study, a field experiment area was set up in the experimental base of Huaiyuan county, Anhui Province, and 5 nitrogen levels were set up. UAV sampling was conducted twice, and 10 visible light parameters were calculated, and the relationship between visible light parameters and nitrogen content of rice was analyzed. Combining the correlation coefficient and the coefficient of variation to screen out the best visible light parameters for diagnosing rice nitrogen. The results show that the parameters B, G/(R+G+B), G/B, RGBV1 have a strong correlation with crop nitrogen content, and the parameter G/(R+G+B) can be used as UAV visible light remote sensing The best visible light parameters for rice nitrogen diagnosis. Through regression analysis, the regression equation between y (nitrogen content) and x (standard value of green light) is y = 0.0017x2-0.0074x + 0.7201, R2=0.9825.
Key words: UAV remote sensing; Visible light parameters; Rice; Nitrogen nutrition
中國水稻种植面积约占全国耕地面积的27.1%,在我国粮食生产中占有举足轻重的地方。水稻产量受诸多因素的影响,如品种特性、土壤环境、施肥技术等[1],而良好精准的施肥策略则是提高水稻产量和品质最有效的措施。氮肥的合理施用直接影响着水稻的生长,氮素营养缺乏或者过剩都不利于水稻生长[2]。如何快速准确地获取水稻氮素状况,及时调整施肥技术,实现氮肥的合理施用是水稻生产中需要解决的重要课题。
传统的水稻氮素诊断耗时费力,对水稻的损伤较大,具有一定的滞后性,并不能快速地获取水稻的氮素营养状况[4]。……
