摘要
应用傅里叶变换近红外光谱技术建立中式传统爆炒猪肉片水分含量预测模型,达到快速无损检测的目的。通过直接干燥法测定100组爆炒猪肉片样品的水分含量,并扫描得到其近红外光谱图。采用偏最小二乘法并通过二阶微分结合卷积平滑算法对光谱进行预处理,通过拐点法、马氏距离法、杠杆值、学生残差法与内部交互验证均方根法进一步剔除异常样本,优化光谱模型。结果表明:所构建的中式爆炒肉片水分含量近红外光谱预测模型的校正均方差值为0.089 1,相关系数为0.972 1;且将预测值与真实值进行比较发现,预测结果正确率大于98.7%(P<0.05),表明本研究建立的用于检测中式爆炒肉片水分含量的近红外光谱预测模型效果良好,能够快速检测并准确预测中式爆炒肉片的水分含量,具有一定的应用价值。
In the study, a nondestructive and rapid method for detecting the water content of Chinese stir-fired pork was established by near infrared reflectance spectroscopy. The moisture contents of 100 groups of stir-fired pork samples were determined by direct drying method and near infrared spectra of the samples were acquired. The original spectra were pretreated by second derivative and Savitzky-Golay smoothing in order to perform a partial least squares regression. Then inflection point, Mahalanobis distance, root mean square error of cross-validation and studentized residual were used to eliminate the outliers in order to establish a calibration model. The results showed that the proposed predictive model had a high correlation coefficient （r = 0.972 1） with a root mean squared error of calibration of 0.089 1. Furthermore, the prediction accuracy was greater than 98.7% （P 〈 0.05） when compared with the true value indicating the model established in this study has a good predictive performance. The results showed that the model allows accurate prediction of water content and has the potential for use in Chinese stir-fired pork processing and food industry.
作者
赵钜阳
石长波
方伟佳
ZHAO Juyang;SHI Changbo;FANG Weijia(College of Tourism and Cuisine,Harbin University of Commerce,Harbin 150076,China)
出处
《肉类研究》
北大核心
2018年第7期42-48,共7页
Meat Research
基金
哈尔滨商业大学校级科研项目(17XN063)
关键词
近红外光谱
中式爆炒猪肉
水分含量
无损检测
near infrared reflectance spectroscopy
Chinese stir-fired pork
moisture content
nondestructive detection
