基于高光谱成像技术的脐橙叶片的叶绿素含量及其分布测量

Abstract

The chlorophyll content and distribution in the Gannan navel orange leaves were non-destructively measured by competitive adaptive reweighted algorithm( CARS) and successive projections algorithm( SPA) combined with hyperspectral imaging technology. 32 and 6 characteristic wavelengths were extracted by CARS and SPA,and then partial least squares( PLS) was used for modeling quantitative analysis. The results show that SPA-PLS and CARS-PLS model can obtain better results than PLS model through the analysis of prediction of 37 samples. The prediction set correlation coefficients were 0. 90 and 0. 91,the root mean square error is 1. 53 and 1. 60 respectively.The chlorophyll content of each pixel was calculated with SPA-PLS model,then the chlorophyll distribution map of navel orange leaves was visualized using imaging processing technology. Overall results sufficiently demonstrate that the variable selection method combined with hyperspectral imaging technology can be used to measure the chlorophyll content and distribution in navel orange leaves.