Spectra of walnut kernel for moisture content measurement

The rapid and accurate detection of moisture content is of great significance to the quality evaluation and oil extraction process of walnut kernel. Near-infrared (NIR) spectroscopy is an ideal method for measuring moisture content in walnut kernel. In this paper, an analysis model for the moisture content in walnut kernel was developed based on NIR diffuse reflectance spectroscopy using chemometric methods. The different spectral pretreatment methods were adopted to pre-process the original spectral data. The whole spectra band was divided into 5 subbands, 10 subbands, 15 subbands and 20 subbands to screen specific wavelengths relevant to the walnut kernel moisture content and different pretreatment spectral data. The PLS, MLR, PCR and SVR were used to establish the relationship model between the spectral data and measurement values of moisture content. In comparison, the optimized modeling conditions were determined as follows: detection wavelength range from 1349 to 1490nm, SNV+1st p...快速精准检测核桃仁水分含量，对其品质评价与油脂提取工艺均具有重要意义。近红外（NIR）光谱技术是测定核桃仁水分含量的理想方法。本文基于近红外漫反射光谱结合化学计量学方法，构建了核桃仁水分含量分析模型。针对原始光谱数据，采用多种不同的光谱预处理方案对其进行处理。将全光谱波段划分为5个子波段、10个子波段、15个子波段及20个子波段，以筛选与核桃仁水分含量相关的特征波长，并适配不同预处理后的光谱数据。分别采用偏最小二乘回归（PLS）、多元线性回归（MLR）、主成分回归（PCR）以及支持向量回归（SVR）构建光谱数据与水分含量实测值之间的关联模型。经对比分析，确定最优建模条件如下：检测波长范围为1349~1490nm，采用标准正态变换（SNV）结合一阶导数（1st）预处理……