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利用光学系统对不同商业肉块类型的多种品质属性进行快速无损预测

Rapid Nondestructive Prediction of Multiple Quality Attributes for Different Commercial Meat Cut Types Using Optical System.

作者信息

An Jiangying, Li Yanlei, Zhang Chunzhi, Zhang Dequan

机构信息

Mechanical and Electrical Engineering College, Beijing Polytechnic College, Beijing 100042, China.

Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Key Laboratory of Agro-Products Quality and Safety Control in Storage and Transport Process, Ministry of Agriculture and Rural Affairs, Beijing 100193, China.

出版信息

Food Sci Anim Resour. 2022 Jul;42(4):655-671. doi: 10.5851/kosfa.2022.e28. Epub 2022 Jul 1.

Abstract

There are differences of spectral characteristics between different types of meat cut, which means the model established using only one type of meat cut for meat quality prediction is not suitable for other meat cut types. A novel portable visible and near-infrared (Vis/NIR) optical system was used to simultaneously predict multiple quality indicators for different commercial meat cut types (silverside, back strap, oyster, fillet, thick flank, and tenderloin) from Small-tailed Han sheep. The correlation coefficients of the calibration set ( ) and prediction set ( ) of the optimal prediction models were 0.82 and 0.81 for pH, 0.88 and 0.84 for L*, 0.83 and 0.78 for a*, 0.83 and 0.82 for b*, 0.94 and 0.86 for cooking loss, 0.90 and 0.88 for shear force, 0.84 and 0.83 for protein, 0.93 and 0.83 for fat, 0.92 and 0.87 for moisture contents, respectively. This study demonstrates that Vis/NIR spectroscopy is a promising tool to achieve the predictions of multiple quality parameters for different commercial meat cut types.

摘要

不同类型的肉块之间存在光谱特征差异,这意味着仅使用一种类型的肉块建立的肉质预测模型不适用于其他类型的肉块。一种新型便携式可见近红外(Vis/NIR)光学系统被用于同时预测来自小尾寒羊的不同商业肉块类型(牛腩、背腰肉、牡蛎肉、里脊、厚腹肉和里脊肉)的多个质量指标。最佳预测模型的校正集( )和预测集( )的相关系数分别为:pH值的相关系数为0.82和0.81,L值的相关系数为0.88和0.84,a值的相关系数为0.83和0.78,b*值的相关系数为0.83和0.82,蒸煮损失的相关系数为0.94和0.86,剪切力的相关系数为0.90和0.88,蛋白质的相关系数为0.84和0.83,脂肪的相关系数为0.93和0.83,水分含量的相关系数为0.92和0.87。本研究表明,可见近红外光谱是实现不同商业肉块类型多个质量参数预测的一种有前途的工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6551/9289799/c30f4c90f488/kosfa-42-4-655-g1.jpg

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