摘要
鱼丸凝胶成型温度关系鱼丸品质与货架期。本文采用近红外光谱技术建立鱼丸成型温度快速检测方法。在5个温度(40,50,70,80,90℃)下成型的鱼丸被用于建模,SIMCA与PLS分别用于定性判别和定量预测模型的建立。SIMCA判别结果显示,5个温度下成型的鱼丸能够被较好地区分,判别准确率达到92%。通过比较不同光谱预处理对优化模型的作用,得到R=0.97077,RMSEC为4.49,RMSEP为4.58的PLS定量模型。模型的预测值与实际值之间有较好的线性关系。近红外光谱技术可为实现鱼丸成型温度的定性判别与定量预测提供一种方法。
The gel molding temperature of fish-ball seriously related to the quality and shelf-fife of fish-bail. Near- infrared reflectance spectroscopy （MRS） was used as a rapid and nondestructive method to determine the gel molding temperature of fish-balls. 150 fish-balls produced at 5 different temperatures （40 % ,50 % ,70℃ ,80℃ ,90 ℃） were prepared for establishing the predicting models. Soft independent modeling of class analogy（SIMCA） and partial least-squares （PLS） were used to develop a calibration which was tested with a validation set. SIMCA provided satisfactory classification results about these different fish-balls. The classification accuracy for the prediction samples achieve to 92%. The optimal PLS model is acquired by the fitting spectral pretreatment methods. The multiply correlation coefficient （R）, root mean square error of calibration（RMSEC） and root mean square error of validation（RMSEV） are respectively 0.97077, 4.49 and 4.58 in the model. A promising linear relationship was observed between NIR-predicted temperatures and the actual gel molding temperatures. The result demonstrate that NIR can effectively achieve the molding temperature of fish-balls＇ qualitative discrimination and quantitative prediction, this could provides theoretic basis for the real-time and on-line quality monitoring of fish-balls.
出处
《中国食品学报》
EI
CAS
CSCD
北大核心
2013年第2期188-192,共5页
Journal of Chinese Institute Of Food Science and Technology
基金
国家自然科学基金项目(30800916,31071514)
十二五国家支撑计划项目(2012BAD29B06)
关键词
近红外光谱
鱼丸
SIMCA
PLS
near infrared reflectance spectroscopy（NIRS）
fish-ball
SIMCA
PLS
