Inspection of Lettuce Water Stress Based on Multi-sensor Information Fusion Technology
Characteristics of reflection spectrum, multispectral images and temperature of lettuce canopy were gained to judge the lettuces water stress condition which could lead to a precise, rapid & stable test of lettuce moisture and enlarged the models universality. By the extraction of lettuces multi-sensor characteristics in 4 different levels, quantitative analysis model of spectrum including 4 characteristic wavelengths, characteristic model of multi-spectral image and CWSI were established. These multi-sensor characteristics were fused by using the BP artificial neural network. Based on the fused multi-sensor characteristics, the lettuce moisture evaluation model was established. The results showed that the correlation coefficient of multi-spectral images model, spectral characteristics model and information fusion model were in turn increased, the correlation coefficients were respectively 0.8042, 0.8547 and 0.9337. It was feasible to diagnose lettuce water content by using multi-sensor information fusion of reflectance spectroscopy, multi-spectral images and can-opy temperature. The correct rate and robustness of the discriminating model from multi-sensor information fusion were better than those of the model from the single-sensor information.
Lettuce Water stress Information fusion
Hongyan Gao Hanping Mao Xiaodong Zhang
Key Laboratory of Modern Agricultural Equipment and Technology,Ministry of Education & Jiangsu Province, Jiangsu University, Zhenjiang 212013, China
国际会议
南昌
英文
53-60
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）