短波近红外光谱快速无损检测生鲜鸡肉胆固醇含量

摘要

A portable near infrared spectrometer was applied to collect spectral information in the short-wave infrared region of 236 samples of fresh chicken to establish a quantitative model for predicting the cholesterol content of fresh chicken breast through partial least squares regression combined with chemometrics. The results showed that the optimal spectral pretreatment method was the combination of normalization and baseline correction. Model calibration was achieved by elimination of abnormal values performed twice. Parameters of the optimal prediction model developed were determined as follows:Rc (correlation coefifcient for calibration set)=0.801 1, sEC (standard error of calibration)=6.699 8, Rp (correlation coefifcient for prediction set)=0.803 4, sEP (standard error of prediction)=7.529 6, MF (number of main factors)=4, and sEP/sEC=1.12, which indicated the prediction model had better reliability, robustness and performance than other models.%采用短波近红外光谱对生鲜鸡肉中的胆固醇含量进行检测，使用便携式近红外光谱仪在近红外光谱短波区域采集236份生鲜鸡肉的光谱信息，采用化学计量学法建立鸡肉胆固醇的偏最小二乘法定量预测模型。结果表明：最佳光谱预处理方法为标准化和基线校正，并通过剔除两次异常值对模型进行校正，所建定标模型的校正集相关系数Rc=0.8011，校正标准差（sEC）=6.6998，验证集相关系数Rp=0.8034，预测标准差（sEP）=7.5296，主因子数MF=4，sEP/sEC=1.12，说明模型可靠性、稳健性和预测效果较好。