首页> 外文期刊>Journal of near infrared spectroscopy >Visible and near infrared spectroscopy of beef longissimus dorsi muscle as a means of discriminating between pasture and corn silage feeding regimes
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Visible and near infrared spectroscopy of beef longissimus dorsi muscle as a means of discriminating between pasture and corn silage feeding regimes

机译:牛肉背最长肌的可见和近红外光谱作为区分牧草和玉米青贮饲料的一种方法

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摘要

Near infrared (NIR) reflectance spectroscopy was used as a tool to classify beef muscle samples according to their feeding regime. Seventy-eight beef longissimus dorsi muscle samples both intact and minced were scanned in a NIRS 6500 instrument (NIRSystems, MD, USA) in reflectance. A dummy regression technique was developed to differentiate beef muscle samples, which originated from beef feed exclusively on pasture or/and mainly on corn silage feeding regimes. Ninety percent of the pasture-fed beef muscle samples were correctly classified using principal component regression (PCR) and 86% of beef fed on corn silage were correctly classified. Both muscle chemical composition and physical characteristics explained the classification results. The results in the present study showed the potential of muscle optical properties for classification and traceability of meat muscles in the food chain.
机译:近红外(NIR)反射光谱法被用作根据牛肉进食方式对牛肉样品进行分类的工具。在NIRS 6500仪器(NIRSystems,MD,美国)中以反射率扫描了完整的和切碎的78个牛肉背最长肌样品。开发了一种虚拟回归技术来区分牛肉肌肉样品,这些样品仅来自牧场或/和主要基于玉米青贮饲料的牛肉饲料。使用主成分回归(PCR)对90%的牧场饲喂的牛肉肌肉样本进行了正确分类,对饲喂玉米青贮饲料的牛肉的86%进行了正确分类。肌肉化学成分和物理特性均解释了分类结果。本研究的结果表明,肌肉光学特性可用于食物链中肉类肌肉的分类和追溯。

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