Small Ruminant Research 144 (2016) 100–103 Contents lists available at ScienceDirect Small Ruminant Research journal homepage: www.elsevier.com/locate/smallrumres Principal components analysis of the lipid profile of fat deposits in Santa Inês sheep Maria N. Ribeiro a,∗ , Roberto G. Costa b , Neila L. Ribeiro b , Michelly D.A. Almeida b , George Rodrigo B. Cruz b , Edvaldo S. Beltrão Filho b a Universidade Federal Rural de Pernambuco (UFRPE), Recife, PE, Brazil b Universidade Federal da Paraíba (UFPB), CEP 58397-000. Areia, PB, Brazil a r t i c l e i n f o Article history: Received 15 February 2016 Accepted 30 May 2016 Available online 11 August 2016 Keywords: Fatty acids Adipocyte Chemical composition Lamb Lipid Multivariate a b s t r a c t The aim of this research was to characterise the lipid profile of internal fat deposits in Santa Inês sheep and determine which variables have the greatest explanatory power on the total variation using prin- cipal components. Forty two male lambs were used, with a slaughter weight of 28.85 ± 2.33 kg and an average age of 7–8 months. Samples were collected from omentum, mesenteric, kidney and pelvic fat deposits. The fatty acids were separated in a gas chromatograph coupled to a flame ionization detector. The chromatograms, with the data on the retention times and the percentages of areas of fatty acids, were stored in Peak simply type software (ARI Instruments–USA). The first four principal components explained 68.03% of the total variation. Of the total 45 variables, 12 variables were the most relevant in the first 4 components, representing a significant reduction in the sample space, as almost 75% of the variables made small contributions to the total variance. The variables C140, C160, C171n7c, C18:0, C183n6, C203n3c, C204n6c, C23:0, monounsaturated fatty acids (MUFA), polyunsaturated fatty acids (PUFA), total unsaturated fatty acids (TUFA), saturated fatty acids (SFA), MUFA/SFA, TUFA/SFA, desirable fatty acids (DFA) and atherogenic index (AI) contributed the most to the total variation in the data. © 2016 Elsevier B.V. All rights reserved. 1. Introduction Adipose fat deposits have been highlighted in assessment stud- ies of meat product quality, as these deposits are increasingly being used in the formulation of products aiming to improve texture and palatability, as well as the appearance of the meat products arriving at the consumer’s table. The public has become increasingly more demanding with the food they consume (Carvalho et al., 2005). Through the study of these fats, it is possible to identify the fatty acid profiles that may be considered beneficial, or not, to health, and the search for quality food and functional properties is very much required in today’s world. Numerous studies have been conducted examining the effects of fat levels in the diets of patients suffer- ing from chronic diseases (Bertolami and Bertolami, 1986; Watts et al., 1996; Metz et al., 1997; Oliver, 1997). More deaths by coro- nary heart disease occur in populations where diets have excessive fat. However, analysis of the phenomenon globally is limited, and a better understanding of the phenomena could be obtained from a ∗ Corresponding author. E-mail addresses: normaribeiro70@gmail.com, ribeiromn1@hotmail.com (M.N. Ribeiro). multivariate approach. With this approach, it is possible to define the profile of fatty acids in fat deposits while considering all the studied variables simultaneously. Multivariate methods are based on correlations between vari- ables, allowing for simultaneous analysis and providing more consistent and useful interpretations (Ferreira et al., 2009), and may contribute to improved interpretations of large sets of vari- ables (Guerra et al., 2002). Among multivariate analysis, principal component analysis has been widely used to identify the vari- ables that best explain total variation (Hair Junior et al., 2009). This technique enables the evaluation of interrelationships between the variables, reducing an original set of variables into a smaller num- ber of independent factors, facilitating interpretation (Cruz and e Regazzi, 2003). A large group of qualitative and quantitative vari- ables from different populations may be analysed using a group of multivariate analysis simultaneously (Dossa et al., 2007). There- fore, the aim of this research was to characterise the lipid profile of internal fat deposits in Santa Inês sheep and determine which vari- ables have the greatest explanatory power over the total variation in the data by using the principal components technique. http://dx.doi.org/10.1016/j.smallrumres.2016.05.020 0921-4488/© 2016 Elsevier B.V. All rights reserved.