Open AccessEstimation of SPAD value in tomato leaves by multispectral images
Author(s) -
Yongjun Ding,
Jingjing Zhang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1634/1/012128
Subject(s) - mathematics , multispectral image , normalized difference vegetation index , artificial intelligence , pixel , grayscale , color constancy , remote sensing , preprocessor , pattern recognition (psychology) , image (mathematics) , computer science , leaf area index , geography , agronomy , biology
To improve the prediction accuracy of tomato chlorophyll content based on multispectral images, three preprocessing methods that can weaken illumination influence, i.e., self-adaptive gamma correction, multiscale Retinex and reflectance reconstruction, are compared and analyzed, and corresponding estimation models for the tomato Soil-Plant Analysis Development (SPAD) value are established. The correction coefficients are set according to the deviations between the grayscale values of the pixels in the highlighted and shaded areas and the average grayscale values in the area of uniform illumination to realize the self-adaptive gamma correction. The SPAD estimation model is constructed by the corrected image, with input parameters of nir, RVI b,g , RVIg,nir, RVIr,nir, NDVI r,g , and NDVI b,r , and the Rc 2 and Rv 2 of the model are 0.87 and 0.8, respectively. The original image is convolved with three different Gaussian functions to obtain a multiscale Retinex corrected image, and the SPAD estimation model is constructed. The input parameters are b, RVI r,g , RVIr,nir, RVI g,b , RVIg,nir, RVIb,nir, and NDVI r,g , and the Rc 2 and Rv 2 of the model are 0.91 and 0.84, respectively. The accuracy of the above two models depends on the selection of the corrected gamma value and the convolution kernel, and improper selections could seriously affect the accuracy of the model. For the SPAD value estimation model based on the reflectance reconstruction, its input parameters are nir, RVIg,nir, RVI r,g , NDVI g,b , NDVIr,nir, and NDVI b,r , and the Rc 2 and Rv 2 of the model are 0.90 and 0.88, respectively. The preprocessing procedure is simple, and the universality is high, making it suitable for the application of the digital field management of the crop.