基于近红外光谱技术的树莓果粉品质评价

Quality evaluation of raspberry fruit powder based on near infrared spectrum technology

应用近红外光谱技术可实现浆果果粉中品质指标的快速准确检测。研究收集120份树莓果粉样本,采用近红外光谱收集光谱信息,物理化学分析方法测定果粉粒度、花青素含量与维生素C含量,应用多元线性回归算法,建立果粉花青素含量、维生素C含量和粒度的定量分析数学模型。树莓果粉花青素含量、维生素C含量与粒度定量分析数学模型的预测相关系数分别为0.968、0.964、0.985,符合浆果果粉品质在线检测要求。研究结果可为保证浆果制品营养成分和提高浆果加工品质提供先进的检测方法。

Near infrared spectrum technology was applied to detect rapidly and accurately key quality index of the berry fruit powder. Total 120 samples of the raspberry fruit powder were collected in this paper and the spectral information was collected using near infrared spectrum. The physical and chemical analysis method was employed to measure the powder particle, anthocyanin content and vitamin C content. The algorithm of multiple linear regressions was applied to establish the mathematic model of the quantitative analysis of anthocyanin content, vitamin C content and particle. The predictive correlations of the mathematic models of the quantitative analysis were 0.968, 0.964 and 0.985, respectively. The research results can provide a valuable detection method for ensuring the nutritional components of berry products and improving the processing quality of the berry.