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首页> 外文期刊>Journal of Animal Science >Field testing of a system for online classification of beef carcasses for longissimus tenderness using visible and near-infrared reflectance spectroscopy.
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Field testing of a system for online classification of beef carcasses for longissimus tenderness using visible and near-infrared reflectance spectroscopy.

机译：使用可见光和近红外反射光谱法对牛肉尸体进行长等嫩度在线分类系统的现场测试。

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The present experiments were conducted to field test a system optimized for online prediction of beef LM tenderness based on visible and near-infrared (VISNIR) spectroscopy and to develop and validate a model for prediction of tenderness that would be unbiased by normal variation in bloom time before application of VISNIR. For both Exp. 1 and 2, slice shear force (SSF) was measured on fresh (never frozen) steaks at 14 d postmortem. Carcasses with VISNIR-predicted SSF <=15 kg were classified as VISNIR predicted tender and carcasses with VISNIR-predicted SSF>15 kg were classified as VISNIR not predicted tender. In Exp. 1, spectroscopy was conducted online, during carcass grading, at 3 large-scale commercial fed-beef processing facilities. Each carcass (n=1,155) was evaluated immediately after ribbing and again when the carcass was graded. For model development and validation, carcasses were blocked by plant and observed SSF.One-half of the carcasses (n=579) were assigned to a calibration data set, which was used to develop regression equations, and one-half of the carcasses (n=576) were assigned to a prediction data set, which was used to validate the regression equations. Carcasses predicted tender by VISNIR spectroscopy had smaller (P<10-19) mean LM SSF values at 14 d postmortem in the calibration (13.9 vs. 16.5 kg) and prediction (13.8 vs. 16.4 kg) data sets than did carcasses not predicted tender by VISNIR spectroscopy. Relative to carcasses not predicted tender by VISNIR, a decreased percentage of carcasses predicted tender by VISNIR had LM SSF>25 kg in the calibration (2.0 vs. 7.8%) and prediction (0.8 vs. 8.0%) data sets. In Exp. 2, carcasses (n=4,204) were evaluated with VISNIR online at 6 commercial fed-beef processing facilities on 38 production days. The carcasses predicted tender by VISNIR spectroscopy had decreased mean LM SSF values at 14 d postmortem (16.3 vs. 19.9 kg; P<10-87), longer sarcomere lengths (1.77 vs. 1.72 micro m; P<10-10), and a greater percentage of desmin degraded (42 vs. 34%; P<10-5) by 14 d postmortem. Relative to carcasses not predicted tender by VISNIR, a decreased percentage of carcasses predicted tender by VISNIR had LM SSF>25 kg (4.9 vs. 21.3%). The present experiments resulted in development and independent validation of a robust method to noninvasively predict LM tenderness of grain-fed beef carcasses. This technology could facilitate tenderness-based beef merchandising systems.
机译：进行本实验以现场测试基于可见和近红外（VISNIR）光谱优化用于在线预测牛肉LM嫩度的系统，并开发和验证用于预测嫩度的模型，该嫩度将不受开花时间正常变化的影响。在申请VISNIR之前。对于两个Exp。参照图1和图2，在死后14天在新鲜的（从未冷冻的）牛排上测量切片剪切力（SSF）。 VISNIR预测的SSF <= 15公斤的屠体被分类为VISNIR预测的嫩肉，而VISNIR预测的SSF> 15公斤的屠体被分类为VISNIR不可预测的嫩肉。在实验中如图1所示，光谱是在3个大型商业化饲喂牛肉加工设施的car体分级过程中在线进行的。肋骨切除后立即对每个car体（n = 1,155）进行评估，并在对was体进行分级时再次进行评估。为了进行模型开发和验证，将尸体用植物封堵并观察SSF。将一半的尸体（n = 579）分配给校准数据集，用于建立回归方程式，将一半的尸体（将n = 576）分配给预测数据集，该数据集用于验证回归方程。通过VISNIR光谱法预测的tender体在标定后14 d死后14 d的平均LM SSF值较小（ P <10 -19 ）（13.9 vs. 16.5 kg）和预测值（与未通过VISNIR光谱法预测嫩的tender体相比，数据集分别为13.8和16.4 kg）。相对于VISNIR预测不到的tender体，在校准（2.0对7.8％）和预测（0.8对8.0％）数据集中，VISNIR预测的tender体的LM SSF> 25 kg有所降低。在实验中如图2所示，在38个生产日内，通过VISNIR在6个商业饲喂牛肉加工设施上在线评估了屠体（n = 4,204）。通过VISNIR光谱预测的tender体在死后14 d降低了平均LM SSF值（16.3 vs. 19.9 kg; P <10 -87 ），肌节长度更长（1.77）比1.72微米; P <10 -10 ），desmin降解的比例更高（42比34％; P < 10 -5 ）到死后14天。相对于VISNIR预测不到的tender体，VISNIR预测的tender体的LM SSF> 25 kg的百分比降低了（4.9比21.3％）。本实验导致开发并独立验证了一种可靠的方法来无创地预测谷物饲喂牛car体的LM压痛。该技术可以促进基于嫩度的牛肉销售系统。

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