Gagaoua Mohammed, Monteils Valérie, Couvreur Sébastien, Picard Brigitte
UMR Herbivores, VetAgro Sup, Université Clermont Auvergne, INRA, F-63122 Saint-Genès-Champanelle, France.
URSE, Ecole Supérieure d'Agriculture (ESA), Université Bretagne Loire, 55 Rue Rabelais, BP 30748, 49007 Angers, CEDEX, France.
Foods. 2019 Jul 22;8(7):274. doi: 10.3390/foods8070274.
This trial aimed to integrate metadata that spread over farm-to-fork continuum of 110 Protected Designation of Origin (PDO)Maine-Anjou cows and combine two statistical approaches that are chemometrics and supervised learning; to identify the potential predictors of beef tenderness analyzed using the instrumental Warner-Bratzler Shear force (WBSF). Accordingly, 60 variables including WBSF and belonging to 4 levels of the continuum that are farm-slaughterhouse-muscle-meat were analyzed by Partial Least Squares (PLS) and three decision tree methods (C&RT: classification and regression tree; QUEST: quick, unbiased, efficient regression tree and CHAID: Chi-squared Automatic Interaction Detection) to select the driving factors of beef tenderness and propose predictive decision tools. The former method retained 24 variables from 59 to explain 75% of WBSF. Among the 24 variables, six were from farm level, four from slaughterhouse level, 11 were from muscle level which are mostly protein biomarkers, and three were from meat level. The decision trees applied on the variables retained by the PLS model, allowed identifying three WBSF classes (Tender (WBSF ≤ 40 N/cm), Medium (40 N/cm < WBSF < 45 N/cm), and Tough (WBSF ≥ 45 N/cm)) using CHAID as the best decision tree method. The resultant model yielded an overall predictive accuracy of 69.4% by five splitting variables (total collagen, µ-calpain, fiber area, age of weaning and ultimate pH). Therefore, two decision model rules allow achieving tender meat on PDO Maine-Anjou cows: (i) IF (total collagen < 3.6 μg OH-proline/mg) AND (µ-calpain ≥ 169 arbitrary units (AU)) AND (ultimate pH < 5.55) THEN meat was very tender (mean WBSF values = 36.2 N/cm, = 12); or (ii) IF (total collagen < 3.6 μg OH-proline/mg) AND (µ-calpain < 169 AU) AND (age of weaning < 7.75 months) AND (fiber area < 3100 µm) THEN meat was tender (mean WBSF values = 39.4 N/cm, = 30).
本试验旨在整合110头受保护原产地认证（PDO）的曼恩-安茹牛从农场到餐桌整个连续过程中的元数据，并结合化学计量学和监督学习这两种统计方法；以识别使用沃纳-布拉茨勒剪切力（WBSF）仪器分析的牛肉嫩度的潜在预测指标。因此，通过偏最小二乘法（PLS）和三种决策树方法（C&RT：分类与回归树；QUEST：快速、无偏、高效回归树；CHAID：卡方自动交互检测）分析了包括WBSF在内的60个变量，这些变量属于农场-屠宰场-肌肉-肉这4个连续水平，以选择牛肉嫩度的驱动因素并提出预测决策工具。前一种方法从59个变量中保留了24个变量，以解释75%的WBSF。在这24个变量中，6个来自农场水平，4个来自屠宰场水平，11个来自肌肉水平（大多为蛋白质生物标志物），3个来自肉品水平。将决策树应用于PLS模型保留的变量上，以CHAID作为最佳决策树方法，可识别出三个WBSF类别（嫩度等级（WBSF≤40 N/cm）、中等（40 N/cm＜WBSF＜45 N/cm）和坚韧（WBSF≥45 N/cm））。最终模型通过五个分割变量（总胶原蛋白、μ-钙蛋白酶、纤维面积、断奶年龄和最终pH值）得出的总体预测准确率为69.4%。因此，两条决策模型规则可使PDO曼恩-安茹牛产出嫩肉：（i）如果（总胶原蛋白＜3.6μg羟脯氨酸/毫克）且（μ-钙蛋白酶≥169任意单位（AU））且（最终pH值＜5.55），那么肉非常嫩（平均WBSF值=36.2 N/cm，样本量=12）；或者（ii）如果（总胶原蛋白＜3.6μg羟脯氨酸/毫克）且（μ-钙蛋白酶＜169 AU）且（断奶年龄＜7.75个月）且（纤维面积＜3100µm），那么肉是嫩的（平均WBSF值=39.4 N/cm，样本量=30）。
