基于小麦冠层近地多光谱图像的叶绿素(SPAD值)估测方法

Estimation Method of Chlorophyll Content Based on Near Ground Multispectral Images of Wheat Canopy

选择山东省泰安市山东农业大学实验田为研究区,利用ADC便携式多光谱相机和SPAD-502叶绿素计采集该区泰农18和山农15两个品种小麦越冬期、返青期、起身期冠层近地多光谱图像和SPAD值,构建不同生育期小麦的归一化植被指数(NDVI)与SPAD值的线性、对数、乘幂、指数、二次函数5种模型,进而优选小麦叶绿素含量最佳估测模型。结果显示:泰农18和山农15两个小麦品种不同时期的SPAD值与NDVI值均具有极显著相关关系(P<0.01),相关系数在0.797~0.915之间;泰农18小麦冠层SPAD值估测最佳模型为y=68.585x0.5841,山农15小麦冠层SPAD值估测最佳模型为y=124.4x^2+23.212x+44.973。该研究探索了基于近地多光谱数据的小麦叶绿素含量估测方法,为小麦叶绿素含量估测及营养诊断提供了一种快速有效的技术方法。

The experimental field of Shandong Agricultural University was choosed as the study area,which is located in Taian,Shandong Province. The near ground multispectral images and SPAD values of Tainong 18 and Shannong 15 wheat canopy at overwintering stage,returning green stage and setting stage were collected by ADC portable multispectral camera and SPAD- 502 chlorophyll meter. Then the NDVI and SPAD values in different wheat growth periods were used to build 5 models. These models included linear function,logarithmic function,power function,exponentiation function and quadratic function. The best estimation model for chlorophyll content of wheat was selected out. The results indicated that the SPAD and NDVI values of Tainong 18 and Shannong 15 in different growth periods both had very significant correlation. The correlation coefficient was between 0. 797 and 0. 915. The best estimation model of SPAD values of Tainong 18 wheat canopy was y = 68. 585x0. 5841,and that of Shannong 15 wheat canopy was y = 124. 4x2＋ 23. 212 x ＋ 44. 973.The wheat chlorophyll estimation method based on near ground multispectral data was probed in this study,which would provide a quick and effective technique for wheat chlorophyll estimation and nutrient diagnosis.