基于可见-近红外光谱的滩羊肉多品质指标无损检测

针对近红外光谱技术在生鲜肉品质检测中预测模型适用范围窄、检测指标单一、模型稳定性差、难以有效应用于生产检测等问题,本研究采集不同月龄宁夏滩羊宰后3个时期4个部位肉的可见-近红外光谱信息,测定色泽、pH值、蒸煮损失、剪切力以及蛋白质、粗脂肪和水分含量,利用2个波段(370~1 050 nm、900~1 700 nm)的光谱数据分别构建各个指标的偏最小二乘回归(PLSR)预测模型以实现滩羊肉多品质指标同步无损检测。结果表明,两波段中各品质指标的PLSR预测模型相关系数(R)均大于0.80,第二波段中水分含量PLSR模型预测集R可达0.941;两波段中各品质指标预测模型的性能较好,其中370~1 050 nm波段的光谱数据对样品色泽参数预测效果更好。综上所述,可见-近红外光谱技术可实现滩羊肉7个品质指标的快速无损检测。本研究结果为滩羊肉品质控制和滩羊屠宰加工企业优质特色产品的生产提供了技术支撑。

Non-Destructive Detection for Multi-Quality Indexes of Tan Mutton by Visible-Nnear Infrared Spectroscopy

Near-infrared spectroscopy has been used for the detection of fresh meat quality, but the prediction model, single detection index, model stability shall be improved for the effective rapid detection. To achieve simultaneous non-destructive testing of multiple quality indicators of Tan mutton, the visible-near infrared spectroscopy information of different parts of meat at three postmortem stages were collected. A partial least square regression (PLSR) prediction model was established with the two bands of 370~1 050 nm and 900~1 700 nm for quality indexes, including color, pH value, cooking loss, shear force, protein, crude fat and water content. The correlation coefficient of PLSR prediction model for each quality index in the two bands was higher than 0.80, and the correlation coefficient of the PLSR model prediction set for the moisture content in the second band can reach 0.941. The quality index prediction model was good with those two bands, and the spectral range of 370~1 050 nm showed a better prediction of the mutton color. Rapid non-destructive testing could be achieved using visible-near infrared spectroscopy technology, which could assist the quality control of Tan mutton and the production of high-quality products using Tan sheep.