拉曼光谱检测脆肉草鱼肌肉脆度
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O 657.37;TS 254.4

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广东省重点领域研发计划项目(2021B0202030001,2019B020215001);广州市重点研发计划项目(202103000067,201803020033,202002030154);花都区渔业产业园项目(21302156);国家自然科学基金 (31872606);广东省教育厅乡村振兴重点领域专项 (2020ZDZX1060);广东省自然科学基金(2018A0303130034,2020A1515010834);广东省教育厅创新强校特色创新项目(2018KTSCX096);广东省省级科技计划项目(2017A020225042);广东省现代农业产业技术体系创新团队建设专项(2019KJ141,2020KJ138)


Muscle crispness of crispy grass carp (Ctenopharyngodon idella) based on Raman spectroscopy
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    摘要:

    脆度是脆肉草鱼品质重要检测指标之一,过度脆化的脆肉草鱼会出现溶血、缺氧和一些器官的病变。为研发出一种检测脆肉草鱼脆度的方法,实验提出一种基于拉曼光谱技术检测脆肉草鱼脆度的方法。首先,通过对不同脆化时间的脆肉草鱼拉曼光谱进行PCA分析,结果显示,拉曼光谱能够应用于不同脆化时间脆肉草鱼脆度鉴别。肌肉总蛋白质结构中的α-螺旋随着脆化时间增加而减少,β-折叠随着脆化时间增加而增加,无规则卷曲在脆化初期变化较大,脆化后期变化不明显。其次,采用SG、SNV、MSC和Normalize这4种方法预处理拉曼光谱数据,发现Normalize的预处理效果最好,预测集RMSEP为2.33,R2P为0.73。再次,采用PLSR、SVR和BPNN方法建立脆肉草鱼脆度与拉曼光谱信息关系模型,预测集RMSEP分别为2.33、2.26和1.96,R2P分别为0.73、0.78和0.83,其中BPNN预测模型效果最好。研究表明,采用拉曼光谱技术和Normalize-BPNN建立的预测模型可以检测脆肉草鱼脆度。本研究将为脆肉草鱼脆度检测提供新的思路。

    Abstract:

    Crispness is one of the most important indexes for Ctenopharyngodon idella. Over-crispy C. idella will show hemolysis, hypoxia and pathological changes of some organs. Therefore, it is urgent to develop method to detect the crispness of C. idella. In this paper, a method based on Raman spectroscopy was proposed to detect the crispness of C. idella. Firstly, the Raman spectra of C. idella with different crisping time were analyzed by PCA method. The results showed that Raman spectroscopy could be used to identify the crispness of crispy C. idella with different crisping time. Additionally, with the extension of the crisping time, the α-helix of the total protein in the muscle of crispy C. idella was decreased, while the β-fold of the total protein in the muscle of crispy C. idella was increased. In terms of irregular curl of the total protein in the muscle of C. idella, obvious changes were observed at the early stage, but not at the late stage of crisping. Secondly, four preprocessing methods, including SG, SNV, MSC and Normalize, were used to preprocess the Raman spectrum data. It was found that Normalize method had the optimal preprocessing effect, with RMSEP of 2.33 and R2P of 0.73. Thirdly, PLSR, SVR and BPNN were used to establish the relationship model between crispness and Raman spectrum information from the muscle of C. idella. The RMSEP of the prediction set was 2.33, 2.26 and 1.96 , respectively, and the R2P of the prediction set was 0.73, 0.78 and 0.83, respectively. Apparently, the BPNN model was the optimal one. Taken together, our results showed that the Normalized-BPNN prediction model based on Raman spectroscopy could effectively detect the crispness of C. idella. This study paves a new way for C. idella muscle crispness detection methods in the future.

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杨灵,王青秀,杨航,师泽晨,苏立恒,吴霆,林蠡,邹娟.拉曼光谱检测脆肉草鱼肌肉脆度[J].水产学报,2022,46(7):1235~1245

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  • 收稿日期:2021-05-23
  • 最后修改日期:2021-07-12
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  • 在线发布日期: 2022-07-02
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