Research Jujube Pest Stress Index Leaf Pigment Hyperspectral Model Based on Wireless Sensor Networks in the Southern Region of Xinjiang

Abstract:

Measured southern jujube pest stress index leaf pigment, create jujube jujube leaf rust sensitive bands characteristic parameter table, analyze the spectral characteristics of the relevant characteristics and vegetation index jujube high correlation parameters. Determination of diseased leaves and growing spectrum of different pigment content. Analysis jujube leaf rust pigment content and spectral reflectance correlation study comparing jujube leaf rust pigment content and differential spectral correlation. Hyperspectral characteristic parameters to achieve the southern jujube jujube leaf rust pigments PC1/PC2 and PC1+PC2 content estimation. Using a combination of linear and polynomial fitting method to construct the canopy hyperspectral disease dates Brix content estimation model and test. The probabilistic neural network PNN and SVM classifier SVC applied to hyperspectral estimation model, comparative analysis of model accuracy. The results of the quantitative estimation of disease hyperspectral information dates pigment content in leaves of jujube growing use of high spectral monitoring and impact assessment of disease have high practical value. classification accuracy of 98%, obtained very satisfactory recognition results.

• Periodical: Advanced Materials Research (Volumes 955-959)
• Pages: 763-770
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.955-959.763
• Online since: June 2014
• Authors: Peng Zhou*, Xiao Tai Niu, Song Guo, Ming Deng Shi
• Keywords: Estimation Model, Jujube Pests, Pigment Content, Sensor Network, Stress Index

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