食品科学 ›› 2023, Vol. 44 ›› Issue (8): 301-306.doi: 10.7506/spkx1002-6630-20220422-286

• 安全检测 • 上一篇    下一篇

拉曼光谱快速测定冷冻猪肉酸价和过氧化值

白京, 臧明伍, 乔晓玲, 赵建生, 邹昊, 吴嘉佳, 徐晨晨, 史宇璇, 王守伟, 赵燕   

  1. (1.中国肉类食品综合研究中心,肉类加工技术北京市重点实验室,北京食品科学研究院,北京 100068;2.河南省肉品技术创新中心有限公司,河南 漯河 462000)
  • 出版日期:2023-04-25 发布日期:2023-05-06
  • 基金资助:
    “十四五”国家重点研发计划重点专项(2021YFD2100802)

Rapid Determination of Acid and Peroxide Values in Frozen Pork by Using Raman Spectroscopy

BAI Jing, ZANG Mingwu, QIAO Xiaoling, ZHAO Jiansheng, ZOU Hao, WU Jiajia, XU Chenchen, SHI Yuxuan, WANG Shouwei, ZHAO Yan   

  1. (1. China Meat Research Center, Beijing Key Laboratory of Meat Processing Technology, Beijing Academy of Food Sciences, Beijing 100068, China; 2. Henan Meat Technology Innovation Center Co. Ltd., Luohe 462000, China)
  • Online:2023-04-25 Published:2023-05-06

摘要: 为快速测定冷冻猪肉酸价和过氧化值,利用拉曼光谱技术结合化学计量学方法对冷冻猪肉的脂质氧化程度进行快速检测研究。选择贮藏期为0~360 d的冷冻猪肉为研究对象,利用最小二乘法建立酸价、过氧化值和贮藏时间的回归关系,利用便携式拉曼光谱仪采集其表面光谱数据,并应用Savitzky-Golay 5点平滑方法、标准正态变量校正(standard normal variate correction,SNV)和自适应迭代重加权惩罚最小二乘法(adaptive iterative re-weighted penalized least squares,airPLS)方法对原始光谱进行预处理,利用偏最小二乘回归(partial least square regression,PLSR)进行建模分析。结果显示,在该贮藏期内过氧化值与贮藏时间的相关性更为显著(P=0.000 3<0.05),用SNV和airPLS进行预处理的模型预测效果最优,针对最佳预处理光谱采用竞争性自适应加权算法(competitive adaptive reweighted sampling,CARS)进行拉曼特征变量筛选,并建立CARS-PLSR模型,模型预测效果得到提高。其中,预测酸价和过氧化值的CARS-PLSR模型校正决定系数(R2c)分别为0.88和0.84,交叉验证均方根误差分别为0.31和2.33,验证集决定系数(R2p)分别为0.76和0.75,预测均方根误差分别为0.17和1.87,范围误差比分别为2.59和1.90。结果表明,冷冻猪肉过氧化值与贮藏时间具有显著相关性,采用拉曼光谱技术可以快速测定冷冻猪肉的酸价和过氧化值。

关键词: 拉曼光谱;冷冻猪肉;贮藏时间;酸价;过氧化值

Abstract: The rapid detection of lipid oxidation in frozen pork was carried out by using Raman spectroscopy combined with chemometric methods. Frozen pork stored for 0–360 days was selected in this study, and the regression relationship between acid value or peroxide value and storage time was established by the least squares method. Raman spectra were collected with a portable Raman spectrometer and were preprocessed by Savitzky-Golay with five-point smoothing (SG-5), standard normal variate correction (SNV) or adaptive iteratively re-weighted penalized least squares (airPLS). The partial least square regression (PLSR) was used for modeling and analysis. Then competitive adaptive reweighted sampling (CARS) was used to select the Raman characteristic variables for the best preprocessed spectra to establish a CARS-PLSR model. It was found that the correlation between peroxide value and storage time was more significant during the storage period (P = 0.000 3 < 0.05). The prediction models with spectral preprocessing by using SNV and airPLS performed best. The CARS-PLSR model showed improved prediction performance. The CARS-PLSR models for prediction of acid and peroxide values had the following performance parameters: coefficient of determination for calibration (R2c), 0.88 and 0.84; root mean square error of cross-validation (RMSECV), 0.31 and 2.33; coefficient of determination for prediction (R2p), 0.76 and 0.75; root mean square error of prediction (RMSEP), 0.17 and 1.87, and ratio of performance to deviation (RPD), 2.59 and 1.90, respectively. In conclusion, our results show that the peroxide value of frozen pork is significantly correlated with storage time. The degree of lipid oxidation in frozen pork can be rapidly determined by using Raman spectroscopy.

Key words: Raman spectroscopy; frozen pork; storage time; acid value; peroxide value

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