中红外光谱模型用于烤肉中苯并[a]芘的快速检测和评估
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(1. 菏泽市行政审批服务局,山东 菏泽 274000;2. 菏泽市食品药品检验检测研究院,山东 菏泽 274000;3. 四川轻化工大学生物工程学院,四川 宜宾 644000;4. 四川戎测质检技术服务有限公司,四川 宜宾 644000;5. 宜宾中山医院,四川 宜宾 644000)

作者简介:

邵淑娟,女,菏泽市行政审批服务局、菏泽市食品药品检验检测研究院高级工程师,硕士。

通讯作者:

李丽(1982—),女,四川轻化工大学副教授,博士。E-mail:kokonice@139.com

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基金项目:

烹饪科学四川省高等学校重点实验室开放基金项目(编号:PRKX2017Z05)


Rapid detection and evaluation of benzo[a]pyrene in barbecue by mid-infrared spectroscopy model
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(1. Heze Administrative Examination and Approval Service Bureau, Heze, Shandong 274000, China; 2. Heze Institute of Food and Drug Inspection and Testing, Heze, Shandong 274000, China; 3. College of Bioengineering, Sichuan University of Science and Engineering, Yibin, Sichuan 644000, China; 4. Sichuan Rongce Quality Inspection Technology Service Co., Ltd., Yibin, Sichuan 644000, China; 5. Yibin Zhongshan Hospital, Yibin, Sichuan 644000, China)

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    摘要:

    目的:实现烤肉制品中苯并[a]芘含量的快速检测。方法:提出一种基于中红外光谱模型的苯并[a]芘含量检测方法,利用中红外光谱采集了120个烤肉样品的原始光谱,采用标准正态变量转换法、多元散射校正、一阶导数、二阶导数对原始光谱进行预处理,并通过主成分分析评价了光谱的预处理效果,以8∶2的比例将原始光谱数据分为训练集和验证集建立了烤肉制品评价模型。结果:基于中红外光谱数据建立的模型的训练集决定系数、验证集决定系数、训练集均方根误差以及验证集均方根误差分别为0.995 1、0.995 7、0.164 4 μg/kg和0.116 3 μg/kg,训练集样本经过建模后,其残差较小,最大值为0.406,总残差和趋于零。结论:该模型的预测能力强,准确度高,能够较好反映实际的烤肉中苯并[a]芘的含量,可以实现烤肉制品的无损快速检测,在烤肉制品行业中有实际应用价值。

    Abstract:

    Objective: In order to realize the rapid detection of benzo[a]pyrene content in barbecue products, a method of detection based on mid-infrared spectrum model was proposed. Methods: The original spectra of 120 barbecue samples were collected by mid-infrared spectroscopy. The original spectra were pretreated by standard normal variable transformation, multivariate scattering correction, first derivative and second derivative. The pretreatment effect of the spectra was evaluated by principal component analysis. The original spectral data were divided into training set and verification set at a ratio of 8∶2 to establish the evaluation model of barbecue products. Results: The R2c, R2p, RMSEC, and RMSEP of the model based on mid-infrared spectrum data were 0.995 1, 0.995 7 and 0.164 4 μg/kg, and 0.116 3 μg/kg, respectively. The residual error of training set samples was small after modeling. The maximum value was 0.406, and the total residual sum tended to zero. Conclusion: This model has strong prediction ability and high accuracy, and can better reflect the content of benzo[a]pyrene in actual barbecue. Thus, this can help to realize the non-destructive and rapid detection of barbecue products and has practical application value in the industry of barbecue products.

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引用本文

邵淑娟,李 丽,温 磊,等.中红外光谱模型用于烤肉中苯并[a]芘的快速检测和评估[J].食品与机械,2023,39(3):34-37,102.
SHAO Shu-juan, LI Li, WEN Lei, et al. Rapid detection and evaluation of benzo[a]pyrene in barbecue by mid-infrared spectroscopy model[J]. Food & Machinery,2023,39(3):34-37,102.

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  • 收稿日期:2022-08-09
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  • 在线发布日期: 2023-04-25
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