Garrido-Fernández Antonio, Cortés-Delgado Amparo, López-López Antonio
Instituto de la Grasa (CSIC), Food Biotechnology Department, Campus Universitario Pablo de Olavide, Edificio 46. Ctra. Utrera, km 1, 41013 Sevilla, Spain.
Foods. 2022 Dec 13;11(24):4024. doi: 10.3390/foods11244024.
This manuscript considers that the composition of Manzanilla and Hojiblanca fats are compositional data (CoDa). Thus, the work applies CoDa analysis (CoDA) to investigate the effect of processing and packaging on the fatty acid profiles of these cultivars. To this aim, the values of the fat components in percentages were successively subjected to exploratory CoDA tools and, later, transformed into (isometric log-ratio) in the Euclidean space, where they were subjected to the standard multivariate techniques. The results from the first approach (bar plots of geometric means, tetrahedral plots, compositional biplots, and balance dendrograms) showed that the effect of processing was limited while most of the variability among the fatty acid (FA) profiles was due to cultivars. The application of the standard multivariate methods (i.e., Canonical variates, Linear Discriminant Analysis (LDA), ANOVA/MANOVA with bootstrapping and = 1000, and nested General Linear Model (GLM)) to the transformed data, following Ward's clustering or descending order of variances criteria, showed similar effects to the exploratory analysis but also showed that Hojiblanca was more sensitive to fat modifications than Manzanilla. On the contrary, associating GLM changes in with fatty acids was not straightforward because of the complex deduction of some . Therefore, according to the CoDA, table olive fatty acid profiles are scarcely affected by Spanish-style processing compared with the differences between cultivars. This work has demonstrated that CoDA could be successfully applied to study the fatty acid profiles of olive fat and olive oils and may represent a model for the statistical analysis of other fats, with the advantage of applying appropriate statistical techniques and preventing misinterpretations.
本手稿认为曼萨尼亚橄榄和霍吉布兰卡橄榄的脂肪成分属于成分数据(CoDa)。因此,该研究应用成分数据分析(CoDA)来探究加工和包装对这些品种脂肪酸谱的影响。为此,脂肪成分的百分比值先经过探索性CoDA工具分析,随后在欧几里得空间中转换为等距对数比(ilr),并在该空间中应用标准多元技术进行分析。第一种方法(几何均值条形图、四面体图、成分双标图和平衡树状图)的结果表明,加工的影响有限,而脂肪酸(FA)谱之间的大部分变异性是由品种造成的。将标准多元方法(即典型变量分析、线性判别分析(LDA)、采用自抽样法且抽样次数为1000的方差分析/多变量方差分析以及嵌套广义线性模型(GLM))应用于根据沃德聚类或方差降序标准转换后的数据,结果显示与探索性分析有相似的效果,但也表明霍吉布兰卡橄榄比曼萨尼亚橄榄对脂肪变化更敏感。相反,由于一些ilr的推导复杂,将GLM中ilr的变化与脂肪酸联系起来并不直接。因此,根据成分数据分析,与品种间的差异相比,西班牙式加工对油橄榄脂肪酸谱的影响很小。这项研究表明,成分数据分析可以成功应用于研究橄榄脂肪和橄榄油的脂肪酸谱,并且可能为其他脂肪的统计分析提供一个模型,其优势在于能够应用适当的统计技术并避免误解。