摘要
本实验探讨利用近红外光谱分析技术(NIRS)测定鱼丸弹性的可能性,并建立数学模型。以质构仪采用一次压缩法测定鱼丸的弹性,取最大力作为建模数据。以定标集和验证集的相关系数及其预测标准误差作为模型好坏的判定依据。结果表明,采用偏最小二乘法(PLS)建立的数学模型,具有较高的相关系数和较低的预测误差。其中定标集的相关系数(Rc)为0.9709,定标集预测标准误差(SEC)为0.0203;验证集的相关系数(Rv)为0.9697,验证集预测标准误差(SEP)为0.0206。该研究说明利用近红外技术对鱼丸弹性进行预测是可行的。
The present work aimed to evaluate the ability of near infrared spectroscopy （NIRS） in predicting the springiness of fish-balls. For the purpose of this study once-compression method was used by texture analyzer and the maximum value was recorded to describe the springiness. The calibration model was set up. Correlation of calibration （Rc） and validation （Rv）, standard error of calibration （SEC） and error of prediction （SEP） were used to evaluate the quality of the model. The calibration models between original value and NIR spectra were developed using partial least squares （PLS） regression. In addition, a high correlation between original value and predicted value as well as low standard error was found. Rc and Rv are 0.9709 and 0.9697 respectively And SEC and SEP are 0.0203 and 0.0206, respectively. It is confirmed that NIR is feasible to predict the springiness of fish-balls.
出处
《食品科学》
EI
CAS
CSCD
北大核心
2008年第8期530-533,共4页
Food Science
基金
上海市重点学科建设项目(T1102)
关键词
近红外光谱
鱼丸
弹性
NIRS （near-infraved spectroscopy）
fish-ball
springiness
