As forage may affect the environmental sustainability of a given dairy chain, this study evaluated the discriminant capacity of fatty acids (FAs) and NMR metabolomic profiles of milk from three dairy chains, where forage components of cows diets were: maize silage (MS), grass-legume and maize silage (GMS), grass and lucerne hay (HAY). Canonical discriminant analysis (CDA) based on FAs and NMR metabolites highlighted a reliable discriminative performance for HAY samples that were correctly recognised, especially on the basis of C18:3n-3 and C17:0. The GMS samples were positively correlated with choline, C14:0 and C17:1 cis-9, while the MS ones were represented mainly by C16:1 cis-9. An overlap between MS and GMS samples was observed, even if a low-level fused CDA modelling improved their correct assignment. The footprint of maize silage on the milk metabolomic profile seemed not to be affected if partially replaced by a mix of legume and grass silages.

由于草料可能会影响给定乳品链的环境可持续性，本研究评估了脂肪酸 (FA) 的判别能力和来自三个乳品链的牛奶的 NMR 代谢组学特征，其中奶牛日粮的草料成分是：玉米青贮饲料 (MS)、豆科植物和玉米青贮饲料 (GMS)、草和苜蓿干草 (HAY)。基于 FA 和 NMR 代谢物的典型判别分析 (CDA) 突出了对正确识别的 HAY 样品的可靠判别性能，尤其是基于 C18:3n-3 和 C17:0。GMS样品与胆碱、C14:0和C17:1 cis-9呈正相关，而MS样品主要以C16:1 cis-9为代表。观察到 MS 和 GMS 样本之间存在重叠，即使低水平融合 CDA 建模改进了它们的正确分配。