Lopez Annalaura, Vasconi Mauro, Moretti Vittorio Maria, Bellagamba Federica
Department of Health, Animal Science and Food Safety-Università degli Studi di Milano, Via Trentacoste 2, 20134 Milano, Italy.
Animals (Basel). 2019 Jul 17;9(7):452. doi: 10.3390/ani9070452.
According to the knowledge that the composition in fatty acids of milk is related to the production system, we determined the fatty acid composition of goat milk yielded in three different Italian farms. Two low-input system farms; one organic (LI-O) and one conventional (LI-C), and one high-input system conventional farm (HI-C) were involved in the study. Significant differences were detected among the different groups considering the fatty acid pattern of milk. Fatty acids (FA) strictly related to the rearing system, such as odd and branched chain fatty acids (OBCFA), linoleic acid (LA, 18:2 n6), alpha-linolenic acid (ALA, 18:3 n3), elaidic acid (EA, 18:1 n9), total n6 and total n3 FA, were identified as the most significant factors in the characterization of samples coming from low- or high-input systems. OBCFA amounts were found to be higher ( < 0.05) in the LI-O milk (4.7%), followed by the LI-C milk (4.5%) and then by the HI-C milk (3.4%). The same trend was observed for Σn3 FAs, mainly represented by ALA (0.72%-0.81% in LI-O systems and 0.41% in HI-system), and the opposite for Σn6 FAs, principally represented by LA (2.0%-2.6% in LI-systems and 3.1% in HI-system). A significant ( < 0.01) discrimination among samples clusters coming from the different systems was allowed by the principal component analysis (PCA).
根据牛奶脂肪酸组成与生产系统相关的知识，我们测定了意大利三个不同农场产出的山羊奶的脂肪酸组成。研究涉及两个低投入系统农场，一个有机农场（LI - O）和一个传统农场（LI - C），以及一个高投入系统传统农场（HI - C）。考虑到牛奶的脂肪酸模式，在不同组之间检测到显著差异。与饲养系统密切相关的脂肪酸（FA），如奇数和支链脂肪酸（OBCFA）、亚油酸（LA，18:2 n6）、α - 亚麻酸（ALA，18:3 n3）、反式油酸（EA，18:1 n9）、总n6和总n3脂肪酸，被确定为区分来自低投入或高投入系统样本的最重要因素。发现LI - O牛奶中的OBCFA含量较高（<0.05），为4.7%，其次是LI - C牛奶（4.5%），然后是HI - C牛奶（3.4%）。对于主要由ALA代表的总n3脂肪酸（LI - O系统中为0.72% - 0.81%，HI - 系统中为0.41%）观察到相同趋势，而对于主要由LA代表的总n6脂肪酸则相反（LI - 系统中为2.0% - 2.6%，HI - 系统中为3.1%）。主成分分析（PCA）允许对来自不同系统的样本聚类进行显著（<0.01）区分。
