The Detection of Early-Maturing Pears Effective Acidity Based on Hyperspectral Imaging Technology
The hyperspectral imaging technology is used to detect early-maturing pears effective acidity nondestructively, and effective prediction model is established. 145 pears hyperspectral images are obtained in the wavelength range of 400nm-1000nm. Total 145 pears are separated into the calibration set (77 samples) and prediction set (68 samples). Early-maturing pears effective acidity partial least squares (PLS) prediction model is built in different range of spectrum band. By comparison, the range 498 nm-971 nm was selected in using partial least squares (PLS) to build early-maturing pears effective acidity pre-diction model. The experimental results show that, PLS prediction model of earlymaturing pears effective acidity has the best effect in this range of wave-length. The correlation coefficient R between early-maturing pears actual ef-fective acidity and predicted effective acidity is 0.9944 and 0.9233 for calibration set and prediction set respectively, the root mean squared error of prediction samples (RMSEP) is 0.022 and 0.072 for calibration set and prediction set respectively.
early-maturing pear hyperspectral image effective acidity partial least squares (PLS).
Pengbo Miao Long Xue Muhua Liu Jing Li Xiao Wang Chunsheng Luo
Engineering College, Jiangxi Agricultural University, Nanchang, Jiangxi 330045,P.R. China School of Mechanical and Electronical Engineering, East China JiaoTong University,Nanchang, Jiangxi
国际会议
南昌
英文
528-536
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）