宁夏赤霞珠葡萄水分含量的高光谱无损检测研究
发布时间：2018-10-10 17:49
【摘要】：利用可见近红外高光谱成像技术对宁夏赤霞珠葡萄含水量的无损检测进行了初步探讨。通过高光谱成像系统(400~1000 nm)采集了136幅赤霞珠葡萄图像,对原始光谱、平均平滑、高斯滤波、中值滤波、卷积平滑、归一化、多元散射校正、标准正态化、基线校准、去趋势化等预处理的偏最小二乘回归(PLSR)模型进行对比分析;采用主成分分析(PCA)、偏最小二乘回归(PLSR)、连续投影算法(SPA)、竞争性自适应重加权(CARS)方法选择特征波长,建立4种特征波长下的PLSR的葡萄含水量预测模型,优选CARS提取特征波长的方法。在此基础上,对比分析了全波段与特征波长下的MLR、PCR、PLSR的葡萄含水量预测模型。结果表明:采用多元散射校正(MSC)光谱建立的PLSR模型优于原始光谱和其他预处理光谱的PLSR模型;CARS提取特征波长建立的PLSR模型优于多元线性回归(MLR)、主成分回归(PCR)模型,预测集的相关系数(R)和预测均方根误差(RMSEP)分别为0.806、0.144。因此,利用可见近红外高光谱成像技术提取特征波长进行宁夏赤霞珠葡萄含水量的检测是可行的。
[Abstract]:The nondestructive detection of water content of Cabernet Sauvignon grape in Ningxia was studied by using near infrared hyperspectral imaging technique. 136 Cabernet Sauvignon images were collected by a hyperspectral imaging system (400 nm). The original spectra, average smoothing, Gao Si filtering, median filtering, convolution smoothing, normalization, multivariate scattering correction, normalization, baseline calibration, The partial least squares regression (PLSR) model with detrend and other preprocessing is compared and analyzed, and the (SPA), competitive adaptive reweighted (CARS) method is used to select the characteristic wavelengths by using the (PCA), partial least squares regression (PLSR), continuous projection algorithm, the principal component analysis, and the (PLSR), continuous projection algorithm. The prediction model of grape water content under four characteristic wavelengths of PLSR was established, and the method of extracting characteristic wavelength of CARS was selected. On this basis, the water content prediction model of MLR,PCR,PLSR at full wavelength and characteristic wavelength was compared and analyzed. The results show that the PLSR model based on multivariate scattering correction (MSC) spectrum is superior to the PLSR model of the original spectrum and other pretreatment spectra, and the PLSR model based on CARS extraction characteristic wavelength is superior to the multivariate linear regression (MLR), principal component regression (PCR) model. The correlation coefficient (R) and the root mean square error (RMSEP) of the prediction set are 0.806 and 0.144, respectively. Therefore, it is feasible to detect water content of Cabernet Sauvignon grape in Ningxia by extracting characteristic wavelength by using near infrared hyperspectral imaging technology.
【作者单位】： 宁夏大学农学院;宁夏大学土木与水利工程学院;
【基金】：2014年度国家级大学生创新创业训练计划项目(141074917)
【分类号】：TS255.7;O657.3
[Abstract]:The nondestructive detection of water content of Cabernet Sauvignon grape in Ningxia was studied by using near infrared hyperspectral imaging technique. 136 Cabernet Sauvignon images were collected by a hyperspectral imaging system (400 nm). The original spectra, average smoothing, Gao Si filtering, median filtering, convolution smoothing, normalization, multivariate scattering correction, normalization, baseline calibration, The partial least squares regression (PLSR) model with detrend and other preprocessing is compared and analyzed, and the (SPA), competitive adaptive reweighted (CARS) method is used to select the characteristic wavelengths by using the (PCA), partial least squares regression (PLSR), continuous projection algorithm, the principal component analysis, and the (PLSR), continuous projection algorithm. The prediction model of grape water content under four characteristic wavelengths of PLSR was established, and the method of extracting characteristic wavelength of CARS was selected. On this basis, the water content prediction model of MLR,PCR,PLSR at full wavelength and characteristic wavelength was compared and analyzed. The results show that the PLSR model based on multivariate scattering correction (MSC) spectrum is superior to the PLSR model of the original spectrum and other pretreatment spectra, and the PLSR model based on CARS extraction characteristic wavelength is superior to the multivariate linear regression (MLR), principal component regression (PCR) model. The correlation coefficient (R) and the root mean square error (RMSEP) of the prediction set are 0.806 and 0.144, respectively. Therefore, it is feasible to detect water content of Cabernet Sauvignon grape in Ningxia by extracting characteristic wavelength by using near infrared hyperspectral imaging technology.
【作者单位】： 宁夏大学农学院;宁夏大学土木与水利工程学院;
【基金】：2014年度国家级大学生创新创业训练计划项目(141074917)
【分类号】：TS255.7;O657.3
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