近红外漫反射检测梨可溶性固形物SSC和硬度的研究

Study on Predicting Sugar Content and Hardness of Pear by Near Infrared Diffuse Reflectance Technique

采用近红外漫反射光谱检测梨可溶性固形物(SSC)和硬度。采集梨的近红外漫反射光谱,光谱经梨的吸光度原始光谱、一阶微分和二阶微分预处理,分别采用多元线性回归、主成分回归和偏最小二乘法,建立了梨可溶性固形物(SSC)和硬度的定量预测数学模型。结果表明采用一阶微分结合偏最小二乘法的预测效果最好,可溶性固形物(SSC)和硬度定量数学校正模型的相关系数分别为0.9285和0.8478,均方根误差分别为0.4364°Birx和1.227。近红外漫反射光谱作为一种无损的检测方法用于评价梨可溶性固形物(SSC)和硬度是可行的。

The objectives of the study were to predict soluble solid content and firmness of pear fruit by using the near-infrared diffuse reflectance（NIR） spectra.The first derivative D1log（1/R） and the second derivative D1log（1/R） were used to preprocess the primitive spectrum of pear fruit respectively.Multi-linear regression（MLR）,principal component regression（PCR） and partial least square（PLS） regression were used to build prediction models which were used to quantitatively analyze soluble solid content and firmness of pear fruit respectively.The PLS model with D1log（1/R） data treatment was prior to the other two ways based on the comparative analysis.The results show that the correlation coefficients of soluble solid content and firmness are 0.9306 and 0.8478 respectively,and root mean standard error of soluble solid content and firmness are 0.42064°Birx and 1.277 respectively.The research indicates that NIR spectroscopy could provide an accurate,reliable and nondestructive method for assessing the quality index soluble solid content and firmness of pear fruit.