Genetic parameters for milk fatty acid profiles in Gir and Guzerá cows using a Bayesian approach

Genetic parameters for milk fatty acid profiles in Gir and Guzerá cows using a Bayesian approach | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Genetic parameters for milk fatty acid profiles in Gir and Guzerá cows using a Bayesian approach Alvimara Felix dos Reis, Paulo Sávio Lopes, Renata Veroneze, Eula Regina Carrara, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6843607/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Studies with taurine breeds indicate that genetic selection can improve the fatty acid (FA) composition of bovine milk. This study aimed to estimate genetic parameters for FA concentrations and unsaturation indexes in milk fat from Zebu cows and evaluate their potential as selection criteria to enhance milk fat nutritional quality. Milk samples from 299 Gir and 266 Guzerá cows across 22 herds were analyzed by gas chromatography. Fourteen individual FAs, 11 FA groups, four nutritional quality indexes, and five unsaturation indexes were selected. Tri-trait Bayesian models were used to estimate (co)variance components, using 305-day milk yield and fat yield as anchor traits. The models included fixed effects such as contemporary group, age at calving, diet category, age class at sampling, and days in milk. Most individual FAs were present at concentrations < 4 g/100 g of total FA, with palmitic acid being the most abundant, followed by oleic acid, stearic acid, and myristic acid. Heritability estimates ranged from 0.28 to 0.63 for individual FAs, 0.32 to 0.66 for FA groups, and 0.38 to 0.57 for unsaturation indexes in the Gir breed, and from 0.24 to 0.75, 0.26 to 0.65, and 0.50 to 0.68 in the Guzerá breed, respectively. Genetic correlations were generally moderate to high, with long-chain FAs negatively correlated with short- and medium-chain FAs. These findings support the feasibility of selecting Gir and Guzerá cows to genetically improve milk FA profiles and increase the proportion of health-promoting FAs in milk fat. Heritability estimates Lipid metabolism Multivariate analysis Nutritional quality Unsaturation index Zebu breeds Figures Figure 1 Figure 2 INTRODUCTION Ruminant milk fat is the most complex lipid in the human diet. It contains several bioactive fatty acids (FAs) with potential benefits on human health, with some not found in significant amounts in other food sources (Lopes et al. 2015 ; Gómez-Cortés et al. 2018 ). Due to the high saturated fat content in milk, some health professionals have recommended reducing its consumption (Matosinho et al. 2023 ), and the media has published articles against its use in human nutrition, which has damaged the image of milk among consumers worldwide. However, several FAs have beneficial effects on health, including anti-cancer, anti-atherogenic, and immunomodulatory activities (Abdoul-Aziz et al. 2021 ; Coniglio et al. 2023 ). Among these, the most well-known are butyric acid (C4:0); odd- and branched-chain FAs (OBCFAs), rumenic acid ( cis -9, trans -11 conjugated linoleic acid [CLA]) and its precursor vaccenic acid ( trans -11 C18:1), oleic acid ( cis -9 C18:1), and omega-3 FAs (Kratz et al. 2013 ; Gómez-Cortés et al. 2018 ). The nutritional quality of milk fat can be assessed using indexes based on concentrations of specific FAs. The atherogenic (AI) and thrombogenic (TI) indices are among the most commonly used indices. There is a consensus in the literature that lower AI and TI values indicate a lower concentration of undesirable FAs and a higher concentration of bioactive FAs that are beneficial to human health (Hanuš et al. 2018 ; Chen and Liu 2020 ; Duque et al. 2020 ). Several studies have estimated genetic parameters for the bovine milk FA profile (Soyeurt et al. 2007 ; Stoop et al. 2009 ; Narayana et al. 2017 ; Bobbo et al. 2020 ; Klein et al. 2021 ). Their results generally indicate that short-chain FAs (SCFAs) and medium-chain FAs (MCFAs) are under greater genetic control than long-chain FAs (LCFAs). LCFAs originate from the diet, ruminal biohydrogenation, and mobilization from adipose tissue, while SCFAs and MCFAs are mainly synthesized de novo in the mammary gland (Bouwman et al. 2011 ). Higher heritability estimates are expected for saturated FAs (SFAs) than for unsaturated FAs (UFAs) because most SFAs originate from de novo synthesis in the mammary gland (Chilliard et al. 2000 ). Most studies that have estimated genetic parameters for the milk FA profile have involved taurine breeds. Information on relevant traits in Zebu breeds, such as Gir and Guzerá, remains limited, despite their importance for dairy production in countries like Brazil, where most dairy cattle have a Zebu genetic composition (Peixoto et al. 2021 ; Carvalho et al. 2023 ; Matosinho et al. 2023 ). Since Zebu breeds represent a valuable national genetic resource, studying the genetic variability of the milk FA profile, mainly FAs with nutraceutical potential, is crucial for defining selection criteria to improve both milk production and milk fat quality focused on human health. Therefore, this study aimed to estimate the variance components and genetic parameters of the FA profile and unsaturation indexes from milk fat of Zebu cows using a Bayesian approach. MATERIALS AND METHODS Phenotypic and genealogical data This study used records on milk production traits from the databases of the National Programs for the Improvement of Gir and Guzerá Dairy Cattle, coordinated by Embrapa Gado de Leite in close partnership with the Brazilian Association of Gir Dairy Cattle Breeders and the Brazilian Center for the Genetic Improvement of Guzerá. The analyses first used the lactation records of 15,620 Gir cows, measured from 1997 to 2016, and 7,569 Guzerá cows, measured from 1983 to 2022. Monthly production data was accumulated and truncated at 305 days. The FA profile data was obtained from the project “Influence of polymorphisms in the stearoyl-CoA desaturase (SCD) enzyme gene on the nutritional quality of milk fat from Gir and Guzerá cows” (Fapemig: CVZ APQ 02003-15), coordinated by Embrapa Gado de Leite. To study the FA profile, individual and unique milk samples were taken from 337 Gir cows and 284 Guzerá cows from 11 herds of each breed during the period around peak lactation, when the expression of genes involved in lipid metabolism and phenotypic expression is expected to be highest (Bionaz and Loor 2007 ; 2008 ). The Gir herds were distributed in Southeastern Brazil, and the Guzerá herds were distributed in Southeastern and Northeastern Brazil. Milk samples were collected in 2012, 2016 (except for the Gir breed), 2017, and 2018. Each 15 mL milk sample comprised ⅔ of the milk from the A.M. (morning) milking and ⅓ from the P.M. (afternoon) milking, representing individual daily production close to the testing day. The samples were collected in Falcon tubes containing no preservative, and were immediately frozen at − 20ºC until analyzed. All procedures and conditions used in the gas chromatography analysis of the milk FA profile were described in detail by Matosinho et al. ( 2023 ). The concentrations of FAs in milk samples were described in g/100 g of total FA. This study examined 14 individual FAs, 11 FA groups, four nutritional quality indices, and five unsaturation indices (Tables 1 and 2 ). Tables 3 and 4 describe the FAs in each FA group and the formulas used to calculate the indices. The unsaturation indices were calculated for the four main stearoyl-CoA desaturase 1 (SCD1) product/substrate pairs ( cis -9 C14:1/C14:0, cis -9 C16:1/C16:0, cis -9C18:1/C18:0, and cis -9 trans -11 CLA/ trans -11 C18:1), and the total unsaturation index (TUI) was calculated, as described by Schennink et al. ( 2008 ). Table 1 Nomenclature of the individual fatty acids and the fatty acid groups studied Trait Common nomenclature Individual fatty acids C4:0 butyric acid C8:0 caprylic acid C10:0 capric acid C12:0 lauric acid C14:0 myristic acid C16:0 palmitic acid C18:0 stearic acid trans -11 C18:1 trans -vaccenic acid cis -9 C18:1 oleic acid C18:2 ω-6 linoleic acid (omega 6) CLA cis -9, trans -11 rumenic acid C18:3 ω-3 α-linolenic acid (omega 3) C18:3 ω-6 γ-linolenic acid (omega 6) C20:5 ω-3 eicosapentaenoic acid (omega 3) Fatty acid groups SCFA short-chain fatty acids MCFA medium-chain fatty acids LCFA long-chain fatty acids SFA saturated fatty acids UFA unsaturated fatty acids MUFA monounsaturated fatty acids PUFA polyunsaturated fatty acids OLCFA odd- and linear-chain fatty acids OBCFA odd- and branched-chain fatty acids ω-6 cis cis -configured omega-6 fatty acids ω-3 cis cis -configured omega-3 fatty acids Table 2 Nomenclature of milk fat nutritional quality indexes and unsaturation indexes studied Trait Common nomenclature Milk fat nutritional quality indexes ω6/ω3 relationship between omega 6 and omega 3 fatty acids h/H relationship between hypocholesterolemic and hypercholesterolemic fatty acids AI atherogenic index IT thrombogenic index Unsaturation indexes Index C14:1 unsaturation index C14:1 Index C16:1 unsaturation index C16:1 Index C18:1 unsaturation index C18:1 Index CLA unsaturation index CLA TUI total unsaturation index Table 3 Groups of fatty acids calculated from the milk FA profile of Gir and Guzerá cows FA group Fatty acids included SCFA a ∑ (C4:0 + C6:0 + C8:0 + C10:0) MCFA a ∑ (C11:0 + C12:0 + C14:0 + cis -9 C14:1 + C15:0 + C16:0 + cis -9 C16:1) LCFA a ∑ (C17:0 + C18;0 + C17:1 + C18:1 ω-9 trans + C18:1 ω-9 cis + C18:2 ω-6 trans + C18:2 ω-6 cis + C18:3 ω-3 + C22:5 ω-3 + cis -9, trans - 11 CLA) SFA a ∑ (C4:0 + C6:0 + C8:0 + C10:0 + C11:0 + C12:0 + C13:0 + C14:0 + C15:0 + C16:0 + C17:0 + C18:0) UFA a ∑ ( cis -9 C14:1 + cis -9 C16:1 + cis -9 C17:1 + cis-9 C18:1 + C18:2 ω-6 trans + C18:2 ω-6 cis + C18:3 ω-3 + C22:5 ω-3 + cis -9, trans - 11 CLA) MUFA b ∑ ( cis -9 C14:1 + cis -9 C16:1 + trans -11 C18:1 + cis -9 C18:1) PUFA b ∑ (C18:2 ω-6 + C18:3 ω-3 + cis -9, trans -11 CLA) OLCFA ∑ (C5:0 + C7:0 + C9:0 + C11:0 + C15:0 + C17:0 + cis- 9 C17:1 + C21:0 + C23:0) OBCFA ∑ (OLCFA + anteiso C15:0 + iso C14:0 + iso C15:0 + iso C16:0 + iso C17:0 iso + C18:0) ω-6 cis ∑ (C18:2 ω-6 + C18:3 ω-6 + C20:2 ω-6 + C20:3 ω-6 + C20:4 ω-6) ω-3 cis ∑ (C18:3 ω-3 + C20:5 ω-3 + C22:5 ω-3) SCFA: short-chain fatty acids; MCFA: medium-chain fatty acids; LCFA: long-chain fatty acids; SFA: saturated fatty acids; UFA: unsaturated fatty acids; MUFA: monounsaturated fatty acids; PUFA: polyunsaturated fatty acids; OLCFA: odd- and linear-chain fatty acids; OBCFA: odd- and branched-chain fatty acids; ω-6 cis : omega 6 fatty acids with a cis configuration; ω-3 c is : omega 3 fatty acids with a cis configuration. Source: a Narayana et al. ( 2017 ); b Krag et al. (2013). Table 4 Fatty acids and formulas used to calculate the fatty acid profile indexes of the milk fat from Gir and Guzerá cows Trait Fatty acids included Milk fat nutritional quality indexes - Formulas ω-6/ω-3 (∑ ω-6 cis ) / (∑ ω-3 cis ) h/H a ( cis -9 C18:1 + C18:2 ω-6 + C20:4 ω-6 + C18:3 ω-3 + C20:5 ω-3 + C22:5 ω- 3 + C22:5 ω-6) / (C12:0 + C14:0 + C16:0) AI b (C12:0 +(4 x C14:0) + C16) / ( cis -9 C18:1 + ω-6 cis + ω-3 cis ) TI b (C14:0 + C16:0 + C18:0) / ((0.5 x cis -9 C18:1) + (0.5 x ω-6 cis ) + (3 x ω-3 cis ) + (ω-6/ω-3)) Unsaturation index - Formulas Index C14:1 c ( cis -9 C14:1)/( cis -9 C14:1 + C14:0) x 100 Index C16:1 c ( cis -9C16:1) / ( cis -9 C16:1 + C16:0) x 100 Index C18:1 c ( cis -9 C18:1) / ( cis -9 C18:1 + C18:0) x 100 Index CLA c ( cis -9, trans -11 CLA) / ( cis -9, trans -11 CLA + trans -11 C18:1) x 100 TUI c,d 100 x ( cis -9 C14:1 + cis -9 C16:1 + cis -9 C18:1 + cis -9, trans -11 CLA) / (( cis -9 C14:1 + cis- 9 C16:1 + cis -9 C18:1 + cis -9, trans -11 CLA + C14:0 + C16:0 + C18:0 + trans -11 C18:1)) ω6/ω3: ratio between omega-6 and omega-3 fatty acids; h/H: ratio between hypocholesterolemic and hypercholesterolemic fatty acids; AI: atherogenic index; TI: thrombogenic index; C14:1 index: stearoyl Co-A desaturase enzyme activity index (unsaturation index); TUI: total unsaturation index. Source: a Santos-Silva et al. (2002); b Ulbricht and Southgate (1991); c Schennink et al. ( 2008 ); c,d Mele et al. (2007). The pedigree data comprised 34,248 Gir animals (13,365 dams and 2,221 sires) distributed over nine generations, and 21,954 Guzerá animals (10,773 dams and 2,203 sires) distributed over 14 generations. Two databases were established, one for the Gir breed and one for the Guzerá breed. These data were evaluated separately. Besides the animal identification and pedigree data, these databases contained information on cows’ birth date, calving date, date of FA profile sampling, age at calving, age at FA profile sampling, herd, diet, contemporary group (CG), days in milk (DIM), 305-day milk yield (MY305) and fat yield (FY305), FA profile, and indices. The mean DIM for cows with an FA profile was 67.00 ± 34.89 days for the Gir breed and 73.00 ± 38.54 days for the Guzerá breed. For the FA profile analyses, the birth order at sampling and diet were grouped into classes. For age at sampling (AS), three classes were defined for both breeds. For diet, six categories were defined for the Gir breed and four for the Guzerá breed (Tables 5 and 6 ). During categorization, the diets were initially divided into three large groups (tropical pasture, corn silage, and mixed [tropical pasture and corn silage]), and then these groups were subdivided according to the type of concentrate provided: with lipid concentrate (soy, protected fat or whole cottonseed were included in this class) or without lipid concentrate (barley was used). A greater diversity of diets was observed in Gir herds. Table 5 Number of animals (N) of the Gir cows sampled for the fatty acid profile study, according to the age class and diet category Class N Composition of the animals’ age class 1 99 First birth 2 87 Second to fourth birth order 3 113 Animals above the fourth calving order Diet composition 1 57 Corn silage + Non-lipid concentrate 2 62 Corn silage + Lipid concentrate 3 41 Tropical pasture + Non-lipid concentrate 4 71 Tropical pasture + Lipid concentrate 5 34 Mixed + Non-lipid concentrate 6 34 Mixed + Lipid concentrate The average age at first calving from the milk database was taken as the basis for determining the age of the animals that would be included in the first class. Table 6 Number of animals (N) by age class and category of diet fed to the Guzerá cows sampled for the fatty acid profile study Class N Composition of the animals’ age class 1 69 First birth 2 76 Second to fourth birth order 3 121 Animals above the fourth calving order Diet composition 1 59 Corn silage + Non-lipid concentrate 2 116 Tropical pasture + Non-lipid concentrate 3 58 Tropical pasture + Lipid concentrate 4 33 Mixed + Non-lipid concentrate The average age at first calving from the milk database was taken as the basis for determining the age of the animals that would be included in the first class. In the MY305 and FY305 analyses, only data from the first lactation were retained, and CGs were formed by concatenating herd, year, and calving season (dry: April to September; rainy: October to March). In the FA analyses, CGs were formed by concatenating herd, year, and sampling season (dry and rainy). Cows with an FA profile but missing information (unknown dam and/or sire, birth date, and/or calving date) were eliminated from the database. Only CGs with more than three cows, consisting of daughters of at least two different sires, were retained. Values outside ± 3 standard deviations for each trait were considered outliers and excluded from the CG. Finally, for the Gir breed, the phenotypic dataset contained information on MY305 (CG = 2,117) from 15,902 cows, FY305 (CG = 705) from 5,255 cows, and FA profile (CG = 12) from 299 cows. For the Guzerá breed, the phenotypic dataset contained information on MY305 (CG = 655) from 7,159 cows, for FY305 (CG = 206) from 2,460 cows, and the FA profile (CG = 16) from 266 cows. Variance components and genetic parameters For the FA profile, the (co)variance components were estimated via Bayesian inference in tri-trait analyses, using MY305 and FY305 as genetic anchor traits. The systematic effects considered in the models for MY305 and FY305 analyses were CG and age at calving (linear covariate). The systematic effects for the FA profile were AS class, diet category, CG, and DIM (linear covariate). The general model used to estimate the genetic parameters was: $$\:\mathbf{y}=\mathbf{X}\varvec{\beta\:}+\mathbf{Z}\mathbf{a}+\varvec{\epsilon\:}$$ , where y is the vector of phenotypes for each trait (MY305, FY305, or FA), X is the incidence matrix related to systematic effects, β is the vector of systematic effects, Z is the incidence matrix of genetic-additive random effects, a is the vector of genetic-additive random effects, and ε is the vector of residual random effects. The following distributions were assumed: 𝐲| 𝛽 , 𝐚, 𝜀 ~N ( 𝐗𝛽 +𝐙𝐚, 𝐑 0 ⊗ 𝐈); 𝛽 ~N (0, 𝚺 β ⊗𝐈), where 𝚺 β is a diagonal matrix with values of 1 × 10 9 to represent uninformative priors; 𝐚|𝐆 0 ~ N(0, 𝐆 0 ⊗ 𝐀); 𝜀 |~ N(0, 𝐑 0 ⊗ 𝐈), where 𝐆 0 is the (co)variance matrix of the genetic-additive effects, A is the numerator of the relationship matrix; I is an identity matrix; and 𝐑 0 is the residual (co)variance matrix. An a priori inverted Wishart distribution (IW) was assumed for 𝐆 0 and 𝐑 0 . 𝐆 0| 𝑉 𝑔 , 𝑣 𝑔 ~ IW (𝑉 𝑔 , 𝑣 𝑔 ); 𝐑 0 |𝑉 𝑟 , 𝑣 𝑟 ~ IW (𝑉 𝑟 , 𝑣 𝑟 ), where 𝑉 𝑔 and 𝑉 𝑟 are the values of the hyperparameters of the (co)variance components, and 𝑣 𝑔 and 𝑣 𝑟 are a priori degrees of freedom corresponding to the values of the hyperparameters of the (co)variances. The models were implemented in a Bayesian approach using a Markov chain Monte Carlo methodology with Gibbs sampling using the GIBBSF90 + program (Misztal et al. 2014 ). A chain size of 2,000,000 iterations was generated, considering a burn-in of 500,000 iterations and a thinning of 50, for all traits. Then, 30,000 samples were used to obtain the marginal posterior distribution of the variance components and genetic parameters. The convergence criteria of the Gibbs chains were monitored by graphical inspection and the Geweke test (Geweke 1991 ). The posterior estimates of the heritability coefficients (ℎ 2 ) and genetic correlations were calculated using the values obtained in the tri-trait analysis for the FA profile and in the bi-trait analysis for MY305 and FY305. RESULTS Tables 7 – 10 present the descriptive statistics for each trait among the Gir and Guzerá cows. For Gir cows, large coefficients of variation (CVs) were observed for most of the FA profile traits. In contrast, Guzerá cows had slightly lower CVs for FA traits. Regardless of the breed, palmitic acid (C16:0) was the most abundant FA in milk fat, followed by oleic ( cis -9 C18:1), stearic (C18:0), and myristic (C14:0) acids. Concentrations were higher for MCFAs than for LCFAs and SCFAs, and for SFAs than for UFAs. The proportion was higher for monounsaturated FAs (MUFAs) than for polyunsaturated FAs (PUFAs). The other individual FAs and FA groups were found at concentrations < 4 g/100 g total FA. The nutritional quality of milk fat and unsaturation indices were similar for both breeds (Tables 8 and 10 ). Table 7 Means, standard deviations (SD), coefficients of variation (CV), minimum and maximum values for the milk yield (MY305), fat yield (FY305), and individual fatty acids (g/100 g of total fatty acids) from the milk fat of Gir cows Trait N Mean (kg) ± SD CV (%) Minimum Maximum MY305 15,601 2,894 1,736.3 59.99 2,314.9 8,102.9 FY305 5,255 119.14 53.72 45.08 41.96 280.24 Individual fatty acids C4:0 299 3.53 0.6 17.99 1.92 5.23 C8:0 299 1.32 0.3 19.06 0.48 2.12 C10:0 299 2.45 0.6 25.87 0.74 4.36 C12:0 299 2.78 0.7 26.77 0.99 5.04 C14:0 297 9.14 1.6 17.16 5.17 12.81 C16:0 298 28.46 4.0 14.22 20.09 42.79 C18:0 298 9.78 2.1 21.14 4.46 16.63 trans -11 C18:1 296 1.45 0.6 40.29 0.45 3.09 cis -9 C18:1 299 21.32 4.7 22.23 11.47 33.33 cis -9, trans -11 CLA 298 0.77 0.3 38.34 0.28 1.71 C18:3 ω-3 297 0.37 0.1 31.80 0.14 0.67 C18:2 ω-6 298 1.90 0.9 46.91 0.74 4.22 C18:3 ω-6 298 0.02 0.0 42.76 0.01 0.05 C20:5 ω-3 299 0.02 0.0 39.11 0.01 0.06 CLA = conjugated linoleic acid. Table 8 Means, standard deviations (SD), coefficients of variation (CV), minimum and maximum values for the fatty acid groups, nutritional quality indexes, and unsaturation indexes (g/100 g of total fatty acids) from the milk fat of Gir cows Trait N Mean (kg) ± SD CV (%) Minimum Maximum Fatty acid groups SCFA 299 9.41 1.6 17.00 4.39 14.58 MCFA 298 44.46 6.0 13.53 31.31 61.50 LCFA 298 35.29 6.2 17.50 18.60 49.71 SFA 297 61.35 6.5 10.53 46.33 75.24 UFA 298 27.93 5.6 20.08 15.66 42.40 MUFA 298 25.70 5.1 19.78 14.82 38.41 PUFA 296 3.04 1.2 38.49 1.39 6.31 OLCFA 298 2.04 0.4 21.19 1.16 3.74 OBCFA 299 3.14 0.8 23.91 1.74 6.12 ω-6 cis 297 2.11 0.9 43.37 0.95 4.43 ω-3 cis 298 0.45 0.1 27.56 0.20 0.80 Milk fat nutritional quality indexes ω-6/ω-3 298 4.71 1.5 31.57 1.74 7.98 h/H 297 0.66 0.2 34.39 0.25 1.28 AI 299 3.07 1.1 36.39 1.08 6.85 TI 299 3.81 1.2 31.30 1.87 7.78 Unsaturation indexes Index C14:1 298 10.22 2.2 21.14 3.52 16.82 Index C16:1 297 6.38 1.5 23.13 3.46 10.92 Index C18:1 299 68.19 5.7 8.32 54.35 82.62 Index CLA 299 34.72 4.4 12.56 20.28 46.24 TUI 299 33.82 6.3 18.64 19.49 49.60 SCFA: short-chain fatty acids; MCFA: medium-chain fatty acids; LCFA: long-chain fatty acids; SFA: saturated fatty acids; UFA: unsaturated fatty acids; MUFA: monounsaturated fatty acids; PUFA: polyunsaturated fatty acids; OLCFA: odd- and linear-chain fatty acids; OBCFA: odd- and branched-chain fatty acids; ω-6 cis : cis -configured omega-6 fatty acids; ω-3 cis : cis -configured omega-3 fatty acids; ω-6/ω-3: ratio between omega-6 and omega-3 fatty acids; h/H: ratio between hypocholesterolemic and hypercholesterolemic fatty acids; AI: atherogenic index; TI: thrombogenic index; Index C14:1: unsaturation index (stearoyl Co-A desaturase-1 enzyme activity index) and TUI: total unsaturation index. Table 9 Means, standard deviations (SD), coefficients of variation (CV), minimum and maximum values for milk yield (PL305), fat yield (PG305), and individual fatty acids (g/100 g total fatty acids) from the milk fat of Guzerá cows Trait N Mean (kg) ± SD CV (%) Minimum Maximum MY305 7,159 2,080 1,080.56 51.96 1,161.68 5,322.7 FY305 2460 84.93 38.51 45.35 29.37 200.46 Individual fatty acids C4:0 266 3.27 0.40 12.35 1.55 4.68 C8:0 266 1.35 0.24 17.67 0.78 2.07 C10:0 266 2.53 0.66 25.97 1.05 4.48 C12:0 266 2.98 0.82 27.34 1.39 5.40 C14:0 266 9.39 1.24 13.21 4.70 12.35 C16:0 266 27.55 3.21 11.66 19.79 34.90 C18:0 266 10.41 2.02 19.44 6.45 17.03 trans -11 C18:1 265 1.83 0.90 49.05 0.43 3.91 cis -9 C18:1 266 20.81 3.24 15.58 13.18 30.59 cis -9, trans -11 CLA 264 0.92 0.40 42.79 0.26 1.82 C18:3 ω-3 265 0.39 0.09 24.21 0.21 0.89 C18:2 ω-6 265 1.10 0.34 30.57 0.41 1.98 C18:3 ω-6 266 0.01 0.01 46.57 0.00 0.03 C20:5 ω-3 264 0.03 0.01 41.03 0.01 0.08 CLA: conjugated linoleic acid. Table 10 Means, standard deviations (SD), coefficients of variation (CV), minimum and maximum values for the fatty acid groups, nutritional quality indexes, and unsaturation indexes (g/100 g of total fatty acids) of milk fat from Guzerá cows Trait N Mean (kg) ± SD CV (%) Minimum Maximum Fatty acid groups SCFA 266 9.24 1.33 14.42 6.13 13.16 MCFA 266 44.41 5.06 11.40 32.55 55.44 LCFA 266 34.88 4.70 13.49 23.38 48.82 SFA 265 61.69 4.66 7.55 50.69 73.51 UFA 265 26.97 3.55 13.17 17.87 37.54 MUFA 266 25.71 3.62 14.09 16.45 35.14 PUFA 265 2.42 0.40 16.62 1.48 3.51 OLCFA 266 2.39 0.31 13.16 1.79 3.52 OBCFA 265 3.94 0.59 15.11 2.93 5.82 ω-6 cis 265 1.29 0.37 28.70 0.52 2.28 ω-3 cis 265 0.49 0.11 22.58 0.31 1.01 Milk fat nutritional quality indexes ω-6/ω-3 266 2.81 1.07 38.23 1.00 5.66 h/H 266 0.63 0.16 26.05 0.34 1.23 AI 264 3.12 0.79 25.48 1.29 5.52 TI 264 3.76 0.78 20.77 2.02 6.33 Unsaturation indexes Index C14:1 265 10.87 2.01 18.52 5.17 18.37 Index C16:1 260 6.68 1.11 16.58 3.78 9.68 Index C18:1 265 66.71 4.44 6.66 53.57 79.77 Index CLA 265 34.49 4.29 12.43 23.11 45.69 TUI 265 33.52 4.28 12.75 21.71 44.88 SCFA: short-chain fatty acids; MCFA: medium-chain fatty acids; LCFA: long-chain fatty acids; SFA:saturated fatty acids; UFA: unsaturated fatty acids; MUFA: monounsaturated fatty acids; PUFA: polyunsaturated fatty acids; OLCFA: odd- and linear-chain fatty acids; OBCFA: odd- and branched-chain fatty acids; ω-6 cis : cis -configured omega-6 fatty acids; ω-3 cis : cis -configured omega-3 fatty acids; ω-6/ω-3: ratio between omega-6 and omega-3 fatty acids; h/H: ratio between hypocholesterolemic and hypercholesterolemic fatty acids; AI: atherogenic index; TI: thrombogenic index; C14:1 index: unsaturation index (stearoyl Co-A desaturase-1 enzyme activity index) and TUI: total unsaturation index. Only the 10 most studied individual FAs associated with human health, FA groups (SCFA, MCFA, LCFA, SFA, UFA, MUFA, PUFA, odd- and linear-chain FA [OLCFA], branched-chain FAs, ω-6 c is , and ω-3 c is ), ω-6/ω-3 ratio, and unsaturation indices were used to estimate variance components and heritability. Genetic correlations were estimated only among individual FAs, MY305, and FY305. The number of chains analyzed was sufficient to stabilize all analyses for both breeds. Tables 11 – 16 present the posterior estimates of the variance components and heritability of the milk FA profile in Gir and Guzerá cows. Regardless of the breed, the credibility intervals (CIs) were wide. The posterior means of the estimates were 0.17 and 0.29 for the MY305 heritability coefficients and 0.06 and 0.21 for the FY305 heritability coefficients in the Gir and Guzerá breeds, respectively. In the Gir data, the posterior means of the heritability estimates ranged from 0.28 to 0.63 for individual Fas, from 0.32 to 0.66 for FA groups, and from 0.38 to 0.57 for the unsaturation indices. In the Guzerá data, the heritability estimates ranged from 0.25 to 0.74 for the individual FAs, from 0.26 to 0.65 for the FA groups, and from 0.50 to 0.68 for the unsaturation indices. Table 11 Posterior means and respective standard deviation (PSD), confidence interval (CI, 95%) of estimates of additive genetic variance ( \(\:{{\sigma\:}}_{a}^{2}\) ), residual variance ( \(\:{{\sigma\:}}_{e}^{2}\) ), and heritability (h²) for milk yield (MY305), fat yield (FY305) and individual fatty acids in milk from Gir cows Trait \(\:{{\sigma\:}}_{a}^{2}\) \(\:{{\sigma\:}}_{e}^{2}\) h² Mean (PSD) [CI] Mean (PSD) [CI] Mean (PSD) [CI] MY305 219,120.00 (21,846.00) [177,700.00; 263,000.00] 1,089,800.00 (21.562) [1,050,000; 1,134,000] 0.17 (0.02) [0.14;0.20] FY305 358.95 (65.12) [234.10;486.70] 5.656 (135.54) [5.384; 5.915] 0.06 (0.01) [0.04;0.08] Individual fatty acids C4:0 0.0566 (0.025) [0.0132; 0.1024] 0.1412 (0.023) [0.0963; 0.1861] 0.28 (0.1) [0.07; 0.49] C8:0 0.0136 (0.005) [0.0069; 0.0206] 0.0287 (0.004) [0.0217; 0.0369] 0.32 (0.1) [0.17; 0.48] C10:0 0.1025 (0.037) [0.0520; 0.1537] 0.1933 (0.032) [0.1433; 0.2545] 0.34 (0.1) [0.18; 0.51] C12:0 0.1404 (0.052) [0.0714; 0.2114] 0.2350 (0.043) [0.1702; 0.3171] 0.37 (0.1) [0.20; 0.54] C14:0 0.5916 (0.233) [0.3213; 1.0650] 0.8008 (0.162) [0.5038; 1.0330] 0.42 (0.1) [0.25; 0.68] C16:0 6.4563 (1.743) [2.3970; 8.4250] 3.6920 (1.268) [2.4380; 6.7810] 0.63 (0.1) [0.27; 0.76] C18:0 0.8888 (0.289) [0.2915; 1.5410] 1.5140 (0.246) [1.0380; 2.1590] 0.37 (0.1) [0.12; 0.57] trans -11 C18:1 0.0309 (0.015) [0.0091; 0.0597] 0.0797 (0.016) [0.0434; 0.1008] 0.28 (0.1) [0.09; 0.57] cis -9 C18:1 4.4835 (1.718) [1.4380; 7.8810] 7.5755 (1.685) [4.4010; 10.3800] 0.37 (0.1) [0.14; 0.62] cis -9, trans -11 CLA 0.0021 (0.001) [0.0007; 0.0040] 0.0020 (0.001) [0.0010; 0.0030] 0.51 (0.2) [0.21; 0.78] CLA: conjugated linoleic acid. Lower upper limits of the 95% probability confidence interval. Table 12 Posterior means and respective standard deviation (PSD), confidence interval (CI, 95%) of estimates of additive genetic variance ( \(\:{{\sigma\:}}_{a}^{2}\) ), residual variance ( \(\:{{\sigma\:}}_{e}^{2}\) ), and heritability (h²) of the fatty acid groups in milk fat from Gir cows Trait \(\:{{\sigma\:}}_{a}^{2}\) \(\:{{\sigma\:}}_{e}^{2}\) h² Mean (PSD) [CI] Mean (PSD) [CI] Mean (PSD) [CI] Fatty acid groups SCFA 0.4869 (0.166) [0.1779; 0.7322] 0.8260 (0.145) [0.5742; 1.0920] 0.37 (0.1) [0.14; 0.53] MCFA 8.5974 (2.507) [2.5510; 11.7000] 10.5600 (1.897) [7.3110; 14.9800] 0.44 (0.1) [0.15; 0.60] LCFA 9.1399 (2.888) [2.2250; 13.7700] 9.3594 (2.881) [6.3670; 15.6400] 0.49 (0.1) [0.15; 0.67] SFA 7.2026 (2.770) [1.7520; 12.2800] 10.0370 (2.213) [6.0320; 14.6100] 0.41 (0.1) [0.12; 0.65] UFA 6.3455 (1.635) [2.5420; 10.0500] 8.0655 (1.590) [4.5710; 10.7400] 0.44 (0.1) [0.22; 0.68] MUFA 4.9392 (1.725) [2.0420; 9.1070] 8.4987 (1.719) [4.7840; 10.8900] 0.37 (0.1) [0.20; 0.68] PUFA 0.0917 (0.032) [0.0337; 0.1570] 0.1247 (0.027) [0.0724; 0.1789] 0.42 (0.1) [0.18; 0.68] OLCFA 0.0321 (0.008) [0.0137; 0.0459] 0.0167 (0.007) [0.0086; 0.0329] 0.66 (0.1) [0.33; 0.84] OBCFA 0.0369 (0.014) [0.0112; 0.0640] 0.0793 (0.013) [0.0519; 0.1060] 0.32 (0.1) [0.10; 0.53] ω-6 cis 0.0536 (0.020) [0.0170; 0.0916] 0.1003 (0.018) [0.0656; 0.1348] 0.35 (0.1) [0.12; 0.56] ω-3 cis 0.0027 (0.001) [0.0012; 0.0041] 0.0025 (0.001) [0.0014; 0.0037] 0.52 (0.1) [0.26; 0.73] SCFA: short-chain fatty acids; MCFA: medium-chain fatty acids; LCFA: long-chain fatty acids; SFA: saturated fatty acids; UFA: unsaturated fatty acids; MUFA: monounsaturated fatty acids; PUFA: polyunsaturated fatty acids; OLCFA: odd- and linear-chain fatty acids; OBCFA: odd- and branched-chain fatty acids; ω-6 cis : cis -configured omega-6 fatty acids; ω-3 cis : cis -configured omega-3 fatty acids. Lower upper limits of the 95% probability confidence interval. Table 13 Posterior means and respective standard deviation (PSD), confidence interval (CI, 95%) of estimates of additive genetic variance ( \(\:{{\sigma\:}}_{a}^{2}\) ), residual variance ( \(\:{{\sigma\:}}_{e}^{2}\) ), and heritability (h²) of the indexes of nutritional quality and unsaturation of milk fat in Gir cows Trait \(\:{{\sigma\:}}_{a}^{2}\) \(\:{{\sigma\:}}_{e}^{2}\) h² Mean (PSD) [CI] Mean (PSD) [CI] Mean (PSD) [CI] Milk fat quality indexes ω-6/ω-3 0.1651 (0.084) [0.0316; 0.3444] 0.5326 (0.081) [0.3712; 0.6869] 0.23 (0.1) [0.05; 0.46] Unsaturation indexes Index C14:1 1.9568 (0.583) [0.6998; 3.2260] 1.7827 (0.468) [0.8938; 2.9550] 0.52 (0.1) [0.21; 0.77] Index C16:1 0.9206 (0.323) [0.3021; 1.3390] 0.6540 (0.224) [0.3533; 1.1010] 0.57 (0.2) [0.24; 0.79] Index C18:1 6.4679 (2.159) [2.2340; 10.4800] 10.2350 (1.849) [6.4130; 13.7300] 0.38 (0.1) [0.15; 0.59] Index CLA 6.6018 (1.965) [2.9920; 10.8000] 9.3318 (1.762) [5.5860; 12.4200] 0.41 (0.1) [0.23; 0.66] TUI 8.2461 (2.976) [3.1230; 14.8500] 12.5230 (2.637) [6.3850; 16.9000] 0.39 (0.1) [0.17; 0.69] ω-6/ω-3: ratio between omega-6 and omega-3 fatty acids; Index C14:1: unsaturation index (stearoyl Co-A desaturase-1 enzyme activity index) and TUI: total unsaturation index. Lower upper limits of the 95% probability confidence interval. Table 14 Posterior means and respective standard deviation (PSD), confidence interval (CI, 95%) of estimates of additive genetic variance ( \(\:{{\sigma\:}}_{a}^{2}\) ), residual variance ( \(\:{{\sigma\:}}_{e}^{2}\) ), and heritability (h²) for milk yield (MY305), fat yield (FY305) and individual fatty acids in milk from Guzerá cows Trait \(\:{{\sigma\:}}_{a}^{2}\) \(\:{{\sigma\:}}_{e}^{2}\) h² Mean (PSD) [CI] Mean (PSD) [CI] Mean (PSD) [CI] MY305 143,090.00 (16,369.00) [112,500.00; 175,700.00] 348,150.00 (12,864.00) [323,600.00; 374,000.00] 0.29 (0.03) [0.23;0.35] FY305 242.51 (42.16) [164.20;326.50] 925.08 (41.04) [846.80;1006.0] 0.21 (0.03) [0.14;0.27] Individual fatty acids C4:0 0.0328 (0.016) [0.0076; 0.0650] 0.0987 (0.015) [0.0689; 0.1291] 0.25 (0.1) [0.06; 0.46] C8:0 0.0183 (0.005) [0.0085; 0.0286] 0.0132 (0.004) [0.0056; 0.0210] 0.58 (0.1) [0.31; 0.84] C10:0 0.1223 (0.030) [0.0633; 0.1792] 0.0584 (0.023) [0.0176; 0.1022] 0.67 (0.1) [0.42; 0.91] C12:0 0.1912 (0.042) [0.1133; 0.2734] 0.0663 (0.031) [0.0166; 0.1250] 0.74 (0.1) [0.50; 0.94] C14:0 0.4710 (0.153) [0.1834; 0.7797] 0.3765 (0.121) [0.1278; 0.6002] 0.55 (0.2) [0.26; 0.84] C16:0 2.2550 (0.881) [0.7426; 4.0310] 3.0498 (0.741) [1.6050; 4.4510] 0.42 (0.1) [0.15; 0.70] C18:0 1.5169 (0.489) [0.6634; 2.4550] 0.9518 (0.375) [0.2422; 1.6610] 0.61 (0.2) [0.30; 0.89] trans -11 C18:1 0.0417 (0.026) [0.0042; 0.0953] 0.0768 (0.023) [0.0274; 0.1126] 0.34 (0.2) [0.05; 0.72] cis -9 C18:1 2.8626 (1.078) [0.9212; 4.9380] 3.0800 (0.868) [1.3610; 4.7060] 0.48 (0.2) [0.19; 0.77] cis -9, trans -11 CLA 0.0124 (0.005) [0.0032; 0.0223] 0.0159 (0.044) [0.0073; 0.0241] 0.43 (0.2) [0.10; 0.73] CLA: conjugated linoleic acid. Lower upper limits of the 95% probability confidence interval. Table 15 Posterior means and respective standard deviation (PSD), confidence interval (CI, 95%) of estimates of additive genetic variance ( \(\:{{\sigma\:}}_{a}^{2}\) ), residual variance ( \(\:{{\sigma\:}}_{e}^{2}\) ), and heritability (h²) of the fatty acid groups in milk fat from Guzerá cows Trait \(\:{{\sigma\:}}_{a}^{2}\) \(\:{{\sigma\:}}_{e}^{2}\) h² Mean (PSD) [IC] Mean (PSD) [IC] Mean (PSD) [IC] Fatty acid groups SCFA 0.3408 (0.150) [0.0911; 0.6352] 0.5818 (0.131) [0.3196; 0.8256] 0.37 (0.1) [0.11; 0.64] MCFA 3.4889 (1.867) [0.3444; 7.0270] 6.7156 (1.579) [3.5810; 9.6580] 0.34 (0.2) [0.05; 0.64] LCFA 4.7567 (2.150) [0.6009; 8.7500] 5.9152 (1.740) [2.3710; 9.1670] 0.44 (0.2) [0.08; 0.76] SFA 3.4938 (1.520) [0.8112; 6.4880] 5.7973 (1.290) [3.2110; 8.3370] 0.37 (0.1) [0.11; 0.65] UFA 4.3440 (1.606) [1.4650; 7.3740] 3.0161 (1.268) [0.7397; 5.2450] 0.58 (0.2) [0.25; 0.91] MUFA 2.9643 (1.536) [0.4850; 5.9930] 3.7884 (1.254) [1.1520; 5.9230] 0.43 (0.2) [0.09; 0.81] PUFA 0.0361 (0.017) [0.0037; 0.0680] 0.0444 (0.014) [0.0179; 0.0710] 0.44 (0.2) [0.07; 0.77] OLCFA 0.0103 (0.005) [0.0018; 0.0200] 0.0235 (0.004) [0.0149; 0.0322] 0.30 (0.1) [0.06; 0.55] OBCFA 0.0249 (0.013) [0.0051; 0.0495] 0.0708 (0.012) [0.0472; 0.0935] 0.26 (0.1) [0.06; 0.49] ω-6 cis 0.0108 (0.005) [0.0019; 0.0211] 0.0196 (0.005) [0.0107; 0.0283] 0.35 (0.2) [0.07; 0.64] ω-3 cis 0.0031 (0.001) [0.0009; 0.0048] 0.0016 (0.001) [0.0005; 0.0034] 0.65 (0.2) [0.25; 0.90] SCFA: short-chain fatty acids; MCFA: medium-chain fatty acids; LCFA: long-chain fatty acids; SFA: saturated fatty acids; UFA: unsaturated fatty acids; MUFA: monounsaturated fatty acids; PUFA: polyunsaturated fatty acids; OLCFA: odd- and linear-chain fatty acids; OBCFA: odd- and branched-chain fatty acids; ω-6 cis : cis -configured omega-6 fatty acids; ω-3 cis : cis -configured omega-3 fatty acids. Lower upper limits of the 95% probability confidence interval. Table 16 Posterior means and respective standard deviation (PSD), confidence interval (CI, 95%) of estimates of additive genetic variance ( \(\:{{\sigma\:}}_{a}^{2}\) ), residual variance ( \(\:{{\sigma\:}}_{e}^{2}\) ), and heritability (h²) of the indexes of nutritional quality and unsaturation of milk fat in Guzerá cows Trait \(\:{{\sigma\:}}_{a}^{2}\) \(\:{{\sigma\:}}_{e}^{2}\) h² Mean (PSD) [CI²] Mean (PSD) [CI] Mean (PSD) [CI] Milk fat quality indexes ω-6/ω-3 0.0329 (0.029) [0.0014; 0.0898] 0.1227 (0.025) [0.0697; 0.1674] 0.21 (0.2) [0.01; 0.53] Unsaturation indexes Index C14:1 2.5935 (0.784) [1.1710; 4.1230] 1.1992 (0.595) [0.1351; 2.2590] 0.68 (0.2) [0.38; 0.96] Index C16:1 0.6899 (0.193) [0.3116; 1.0560] 0.3259 (0.147) [0.0626; 0.6114] 0.67 (0.2) [0.38; 0.95] Index C18:1 9.6737 (3.170) [3.3530; 15.3300] 5.2263 (2.478) [0.9302; 9.9460] 0.64 (0.2) [0.31; 0.95] Index CLA 8.3183 (2.789) [3.1740; 13.8100] 4.5980 (2.142) [0.7437; 8.4990] 0.64 (0.2) [0.32; 0.95] TUI 5.3284 (2.083) [1.5150; 9.3560] 5.1575 (1.685) [1.8050; 8.2540] 0.50 (0.2) [0.19; 0.84] ω-6/ω-3: ratio between omega-6 and omega-3 fatty acids; Index C14:1: unsaturation index (stearoyl Co-A desaturase-1 enzyme activity index) and TUI: total unsaturation index. Lower upper limits of the 95% probability confidence interval. The posterior means of the genetic correlation coefficients are shown in Fig. 1 for the Gir breed and Fig. 2 for the Guzerá breed. Large posterior standard deviations were observed for the genetic correlation estimates. For the genetic correlations, when zero was within the CIs, the estimates did not differ from zero. The correlations ranged from moderate to high regardless of direction. For the Gir breed, while MY305 showed no genetic correlations with individual FAs, FY305 showed a moderate positive genetic correlation with C4:0 and C16:0 FAs and a moderate negative correlation with cis -9, trans -11 CLA. The genetic correlations among the individual FAs ranged from − 0.90 to 0.98. C4:0 showed a negative and moderate correlation with C10:0, C12:0, and C14:0, and a positive correlation with C16:0 and trans -11 C18:1. Cis -9 C18:1 showed a moderate to high and negative correlation with SCFAs and MCFAs (C8:0 to C16:0). Cis -9, trans -11 CLA showed a positive and high genetic correlation with its precursor trans -11 C18:1 and a moderate to high negative correlation with C8:0 to C14:0. For the Guzerá breed, MY305 showed moderate genetic correlations with individual FAs, which were negative for C8:0 to C14:0 and positive for C18:0. FY305 showed a moderate and negative genetic correlation with C10:0, C12:0, and C14:0. Regarding individual FAs, C18:0 showed a moderate positive correlation with C4:0, and a negative correlation with C8:0 to C14:0. Trans -11 C18:1 showed a low to high correlation with C8:0 to C14:0. Cis -9 C18:1 showed a moderate positive correlation with C4:0, and a moderate to high negative correlation with C12:0 to C16:0. Cis -9, trans -11 CLA showed a moderate negative genetic correlation with C4:0 to C14:0, and a positive correlation with cis -9 C18:1. In both breeds, C8:0 to C14:0 showed high and moderate positive genetic correlations with C18:0 and trans -11 C18:1. Otherwise, the pattern of genetic correlations between C16:0 and the other FAs differed between breeds. Regardless of the breed, when the correlations were non-zero, LCFAs generally correlated negatively with SCFAs and MCFAs. DISCUSSION To our knowledge, no studies have examined genetic parameters of milk FA composition in Zebu cattle ( Bos indicus ). Therefore, this study can be considered the first to undertake quantitative genetic analyses of FA profiles in Zebu cattle. Some studies have demonstrated the ability of Zebu cattle to produce milk with a higher fat content, with levels even above those found in some taurine breeds ( Bos taurus ; Sharma et al. 2018 ; Acosta-Balcazar et al. 2022 ), which could also occur with the FA levels in Zebu milk fat (Samková et al. 2012 ). In general, the milk FA profiles of Gir and Guzerá cows were similar to those described for Bos indicus and Bos taurus breeds in studies that expressed the FA profile in g/100 g of fat (Pegolo et al. 2016 ; Acosta-Balcazar et al. 2022 ; Matosinho et al. 2023 ; Silva et al. 2023 ). Regardless of the breed, FAs considered bioactive, such as cis -9, trans -11 CLA (Gir = 0.77 ± 0.30 g/100 g of total FA; Guzerá = 0.92 ± 0.40 g/100 g of total FA), trans -11 C18:1 (Gir = 1.45 ± 0.60 g/100 g of total FA; Guzerá = 1.83 ± 0.90 g/100 g of total FA), and the ω-3 class (Gir = 0.45 ± 0.10 g/100 g of total FA; Guzerá = 0.49 ± 0.11 g/100 g of total FA) showed slightly higher concentrations than those observed in the Brown Swiss breed ( cis -9, trans -11 CLA = 0.65 g/100 g of total FA; trans -11 C18:1 = 1.20 g/100 g of total FA; Pegolo et al. 2016 ) and the synthetic Girolando breed ( cis -9, trans -11 CLA = 0.75; trans -11 C18:1 = 1.34; ω-3 = 0.16; Silva et al. 2023 ). While the concentrations found for these FAs in our study were < 2 g /100 g of total FA, these contents can have a significant biological impact on human health (Kratz et al. 2013 ). The average concentrations of C18:0 and cis -9 C18:1 FA observed in our study were slightly higher than those observed by Silva et al. ( 2023 ) when evaluating the milk FA profile of Girolando cows at 90 ± 15 DIM Many factors could explain the observed differences, including lactation stage, breed, and, most importantly, the diet. The higher concentrations of C18:0 and cis -9 C18:1 in Zebu milk fat may be attributed to milk sampling around the peak of lactation, when the maximum gene expression is expected and, thus, the maximum phenotypic expression. Moreover, during this period, cows may also experience a negative energy balance (Acosta-Balcazar et al. 2022 ), which would increase body fat mobilization, incorporating more C18:0 and cis -9 C18:1 into the milk fat, since they are the main FAs stored in adipose tissue (Narayana et al. 2017 ; Rodríguez-Bermúdez et al. 2023 ). Another possible explanation is related to the diet provided to both the Gir and Guzerá cows, since 50.62% ( n = 286) received a diet based on tropical pasture, of which 42.10% ( n = 129) also received a lipid concentrate. This finding is consistent with studies that showed that cows grazing pasture supplemented with lipid sources produce milk with higher LCFA and UFA concentrations, increasing the biological and nutritional value of the milk (Rennó et al. 2013 ; Corazzin et al. 2019 ; Samková et al. 2021 ; Plata-Pérez et al. 2022 ). Jointly considering the results of scientific reviews by Arnould and Soyeurt ( 2009 ) and Samková et al. ( 2012 ) and a meta-analysis by Hossein-Zadeh ( 2021 ), it can be considered that there is no consensus on the fact that heritability estimates of FAs are higher when expressed in g/100 g of milk than other concentration units. However, while the concentrations were expressed in g/100 g of total FA, the heritabilities estimated in our study were higher than those obtained by Penasa et al. ( 2015 ), Bobbo et al. ( 2020 ), and Klein et al. ( 2021 ), who expressed the FA profile in g/100 g of milk. Comparing the results on milk FA across different studies is difficult due to differences in interspecific diversity, database structure, sample size, experiments design and precision, laboratory analysis methods (gas chromatography or mid-infrared spectroscopy), concentration units (g/100 g of fat, g/100 dL or 100 g of milk, or g/100 g of total FA), and statistical models (Fleming et al. 2018 ; Lopez-Villalobos et al. 2020 ; Hossein-Zadeh 2021 ), which lead to wide variation in the reported heritability estimates. Our study observed a wider CI, potentially reflecting the database structure, as there were a limited number of cows with milk FA profiles for both breeds (Gir = 299, Guzerá = 266). Studies that used more profiles reported narrower CIs (Penasa et al. 2015 ; Cecchinato et al. 2019 ). Regarding the individual milk FAs, the posterior means of the heritability estimates are similar in our study to those obtained by Palombo et al. ( 2018 ) for taurine breeds, except for C12:0, which was higher for the Guzerá breed. When analyzing data from Holstein × Jersey crossbred cows, Lopez-Villalobos et al. ( 2020 ) found heritability estimates similar to those obtained in our study with the Guzerá breed for C16:0; cis -9, trans -11 CLA; PUFA; and LCFA, and the Gir breed for C8:0, C10:0, and C12:0. According to Fleming et al. ( 2018 ), SCFAs and MCFAs synthesized de novo in the mammary gland present higher heritability estimates than LCFAs, as these are mainly derived from the diet, biohydrogenation in the rumen, and mobilization from adipose tissue (Bastin et al. 2011 ). However, in our study, the posterior heritability estimates were similar for these groups in the two breeds. The heritability estimates found for LCFAs indicate the existence of genetic variability underlying the process of incorporating these FAs into the milk (Bastin et al. 2011 ). SFAs were expected to show greater heritability than UFAs (Penasa et al. 2015 ; Lopez-Villalobos et al. 2020 ). Biologically, this difference can be explained by the fact that most FAs synthesized de novo in the mammary gland are SFAs (Chilliard et al. 2000 ). In our study, contrary to what was found by Penasa et al. ( 2015 ) and Lopez-Villalobos et al. ( 2020 ), UFAs showed similar heritability estimates to SFAs. One possible explanation for these unexpected results could be that the individual milk samples were taken at a fixed moment during lactation (around the peak), while the other studies collected several samples during the entire or partial period of lactation (Bilal et al. 2014 ; Hein et al. 2018 ). The period around the peak of lactation was chosen for sampling the milk FA profile because it is assumed that the phenotypic expression of these traits would be greatest during this period (Bionaz and Loor 2007 ; 2008 ). OBCFAs in milk fat primarily originate from the cell wall of rumen bacteria (Ponnampalam et al. 2002 ; Carta et al. 2022 ; Ponnampalam et al. 2024 ). Therefore, they are expected to be under less genetic control, leading to lower heritability (Dias et al. 2019 ). Evaluating taurine breeds, Palombo et al. ( 2018 ) found heritability estimates similar to those obtained in our study for OLCFAs and OBCFAs in the Guzerá breed and lower than those found in the Gir breed for OLCFAs and the ω-6 cis group. Our study also examined the unsaturation indices of the four main SCD1 product/substrate FA pairs (C14:0/ cis -9 C14:1, C16:0/ cis -9 C16:1, C18:0/ cis -9 C18:1, and trans -11 C18:1/ cis -9, trans -11 CLA) and the TUI encompassing all these pairs. Since these pairs were studied to assess SCD1 activity in the mammary gland, the C14:1 index was expected to show greater heritability than the other unsaturation indices because, unlike the FAs included in those indexes, C14:0 is almost entirely synthesized de novo in the mammary gland and, thus, all cis -9 C14:1 is produced by SCD1 (Stoop et al. 2008 ; Bilal et al. 2012 ; Pegolo et al. 2016 ). However, in our study, the heritability estimates obtained for the unsaturation indices were similar, regardless of the breed. In both breeds, the heritabilities for the TUI were similar to those obtained by Schennink et al. ( 2008 ) and Bilal et al. ( 2012 ). The moderate to high heritabilities for the unsaturation indices suggest that they can be altered through genetic selection ( h ²: low, 0.3). Most of the individual FAs, FA groups, or indices evaluated in our study generally showed moderate to high heritability estimates, indicating that direct genetic selection can effectively alter the milk FA composition to obtain milk with a better nutritional profile for human health. The genetic correlation between milk fat FAs refers to the degree to which the same gene pool influences the presence and proportions of the different FAs. Figures 1 and 2 show that the correlations behaved differently in the two breeds, which can be explained by differences in their evolutionary histories and artificial selection intensities. The correlations between MY305 and C8:0, C10:0, C12:0, and C14:0 content (in g/100 g of total FA) were negative for the Guzerá breed (Fig. 2 ). Bastin et al. ( 2011 ) and Bobbo et al. ( 2020 ) observed a similar pattern in taurine breeds, although they expressed FA concentrations in g/dL and g/100 g of milk and took measurements throughout the lactation period. These results reinforce the antagonistic action of proteins involved in synthesizing certain FAs in fat milk, especially SCFAs, which are substrates for the others. In the Gir breed, although weak, FY305 correlated positively with C16:0 (Fig. 1 ). Therefore, these traits share the positive effects of the same gene pool, and selection for increasing MY305 would improve the C16:0 milk fat concentration. As C16:0 is associated with adverse effects on cardiovascular risk indicators, increasing its concentration in milk fat would be undesirable (Hanuš et al. 2018 ). The complexity involving genetic correlations among milk traits represents a challenge for setting breeding goals in dairy cattle (Bilal et al., 2014 ). Soyeurt et al. ( 2007 ) stated that since genetic correlations reflect the physiological processes involved in synthesizing FAs in milk fat, they can be interpreted from a biological perspective. Due to the different origins of FAs in milk fat, the genetic correlations generally showed different directions when preformed FAs (originating from diet, ruminal biohydrogenation, and mobilization of body reserves) were correlated to those synthesized de novo in the mammary gland (Figs. 1 and 2 ). An example is the C8:0, which showed a positive correlation with the other de novo synthesized FAs (C10:0, C12:0 and C14:0) in both breeds, and a negative correlation with cis -9 C18:1 and cis -9, trans -11 CLA in the Gir breed, and with trans -11 C18:1 and cis -9, trans -11 CLA in the Guzerá breed, both of which come partly from the bloodstream. These results suggest that selection can be based on only one FA representative of the de novo synthesized or preformed FA group. Therefore, selection for a lower concentration of a single FA could increase the concentration of certain FAs in milk fat, improving the nutritional composition of the milk fat. In both breeds (Figs. 1 and 2 ), C4:0 was negatively correlated with SCFAs and MCFAs (C10:0, C12:0, and C14:0 [except for the Guzerá breed]), and positively correlated with LCFAs (C18:0 and cis -9 C18:1 [for the Guzerá breed] and trans -11 C18:1 [for the Gir breed]). This pattern can be explained by not all C4:0 being synthesized d e novo in the mammary gland, with some incorporated from the bloodstream. Therefore, when there is a higher concentration of FAs, it can suppress the expression of key proteins involved in de novo synthesis, such as acetyl-CoA carboxylase alpha (ACACα) and fatty acid synthase (FASN), which are central to this metabolic process. Consequently, the concentrations of C4:0 in milk fat will be higher because this FA has not been used as a substrate in de novo FA synthesis (Bionaz and Loor 2008 ; Stoop et al. 2008 ; Qui et al. 2014 ; Dan et al. 2018 ). According to Mu et al. ( 2021 ), ruminant milk fat synthesis is complex and dynamic, as it involves many key enzymes, proteins, and regulatory factors. The final product of the de novo synthesis cycle is C16:0. However, during the finishing process, intermediate SCFAs and MCFAs are formed and included in the milk fat (Knutsen et al. 2018 ), potentially explaining the high genetic correlations observed between C8:0 and C14:0 in the Gir ( r = 0.72) and Guzerá ( r = 0.93) breeds. Therefore, most proteins influencing C8:0 production also influence C14:0 production because they are part of the same metabolic pathway (Buitenhuis et al. 2014 ; Knutsen et al. 2018 ). The genetic correlation between cis -9, trans -11 CLA and trans -11 C18:1 was strong and positive in the Gir breed (0.90; Fig. 1 ). Prado et al. ( 2019 ) reported that most (86.8% ± 2.8%) of the cis -9, trans -11 CLA in milk is produced predominantly from its precursor trans -11 C18:1 in the mammary gland through desaturation mediated by SCD1, explaining our results. In the Guzerá breed, cis -9, trans -11 CLA showed a moderate and positive genetic correlation with cis -9 C18:1 (0.68; Fig. 2 ), similar to that described by Bilal et al. ( 2014 ) in Canadian Holstein cows (0.62). This correlation reflects, in part, the common origin of these two FAs, which are synthetized in the mammary gland by converting cis -9 C18:0 into C18:1, and trans -11 C18:1 into cis -9, trans -11 CLA by the action of SCD1 (Prado et al. 2019 ). The moderate to high heritability estimates observed in our study indicate that the milk FA profile of Gir and Guzerá cows can be improved through selective breeding, with potential beneficial effects on human health. The genetic correlations between the FAs were moderate to high, depending on whether or not they had a common origin, were de novo synthesized, or preformed. Since the genetic correlations of MY305 and FY305 with individual FAs in the Gir breed were mainly not different from zero, direct selection for MY305 or FY305 does not affect the FA profile of milk fat in these populations, except for rumenic, butyric, and palmitic acids. In the Guzerá breed, the estimated genetic correlations indicate that an increase in milk or fat production can negatively affect the composition of SCFAs and MCFAs. Declarations Acknowledgments The authors are grateful to the technician Hernani Guilherme Barbosa Filho, who analyzed the milk fatty acid composition at the Laboratory of Chromatography of Embrapa Dairy Cattle. We also acknowledge CBMG2 and ABCGIL for data cession. We are thankful for the financial support provided by FAPEMIG, CAPES and CNPq. Author contributions The experimental design was developed by Maria Gabriela Campolina Diniz Peixoto, Marco Sundfeld da Gama, Maria Raquel Santos Carvalho, and Fernando César Ferraz Lopes. Sample collection and data generation were carried out by Maria Gabriela Campolina Diniz Peixoto, Paulo Sávio Lopes, Maria Raquel Santos Carvalho, Marco Sundfeld da Gama, Frank Angelo Tomita Bruneli, Fernando César Ferraz Lopes, and Aníbal Eugênio Vercesi Filho. Data analysis was performed by Alvimara Felix dos Reis, Paulo Sávio Lopes, Renata Veroneze, Eula Regina Carrara, Maria Gabriela Campolina Diniz Peixoto, Pablo Augusto de Souza Fonseca, and Maria Raquel Santos Carvalho. All authors participated in the discussion of the results. The first draft of the manuscript was written by Alvimara Felix dos Reis and revised by Paulo Sávio Lopes and Maria Gabriela Campolina Diniz Peixoto. After that, all authors commented on the last version of the manuscript. All authors read and approved the final version of the manuscript. Funding This study was financed by Fundação de Amparo à Pesquisa do Estado de Minas Gerais (Fapemig) – project CVZ APQ 02003-15 and received a PhD grant from a Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), e ao Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), pela consessão da bolsa de estudos. O presente trabalho foi realizado com apoio da Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES) – Código de Financiamento 001. Data avallabillity The datasets generated and/or analyzed during the current study are not publicly available as they are part of ongoing research and part of them belongs to the breeders, but they can be obtained from the corresponding author upon reasonable request. Conflict of interest The authors claim that there are no conflicts of interest. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6843607","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":471633322,"identity":"9493c440-4fee-46cd-9df6-b9069e2d6044","order_by":0,"name":"Alvimara Felix dos Reis","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8UlEQVRIiWNgGAWjYDACdgaGAxAWYwPDByDFxk5ICzOSFsYZIC3MRGhBsHnQRbAB/mYew0M3au7Jm7c3N3+2+bVNno+ZgfHDxxzcWiQO8xgczjlWbDjnzME26dy+24ZtzAzMkjO34bHmMFvC4Ry2BMYZEoltzLk9txmBWtiYefFokQdr+ZdgP0P+YfNny57b9gS1GBxmPnA4ty0hcYYEY4M0w4/biQS1GIK19CUkz+BJbJPsbbid3MbM2IzXL3LHG5s/53xLsJ3Bfvzxhx9/btvOb28++OEjPu+jAMY2MNlArHoQ+EOK4lEwCkbBKBgpAACFaVFV3bRfmAAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0003-4972-2373","institution":"Universidade Federal de Viçosa: Universidade Federal de Vicosa","correspondingAuthor":true,"prefix":"","firstName":"Alvimara","middleName":"Felix dos","lastName":"Reis","suffix":""},{"id":471633323,"identity":"f4f8316d-83cb-4640-acbf-6457a457f9aa","order_by":1,"name":"Paulo Sávio Lopes","email":"","orcid":"","institution":"Universidade Federal de Vicosa","correspondingAuthor":false,"prefix":"","firstName":"Paulo","middleName":"Sávio","lastName":"Lopes","suffix":""},{"id":471633324,"identity":"b35087d2-3196-4108-9706-6341c8b24ad1","order_by":2,"name":"Renata Veroneze","email":"","orcid":"","institution":"Universidade Federal de Viçosa: Universidade Federal de Vicosa","correspondingAuthor":false,"prefix":"","firstName":"Renata","middleName":"","lastName":"Veroneze","suffix":""},{"id":471633325,"identity":"a67babe6-5cb7-4d6b-ab10-d94529a37326","order_by":3,"name":"Eula Regina Carrara","email":"","orcid":"","institution":"University of Georgia","correspondingAuthor":false,"prefix":"","firstName":"Eula","middleName":"Regina","lastName":"Carrara","suffix":""},{"id":471633326,"identity":"5e2d54a5-729b-4686-bfbb-b26f0fab29b2","order_by":4,"name":"Frank Angelo Tomita Bruneli","email":"","orcid":"","institution":"Embrapa Gado de Leite","correspondingAuthor":false,"prefix":"","firstName":"Frank","middleName":"Angelo Tomita","lastName":"Bruneli","suffix":""},{"id":471633327,"identity":"a6787326-68e8-4c34-974b-5bf262476eec","order_by":5,"name":"Aníbal Eugênio Vercesi Filho","email":"","orcid":"","institution":"Agencia Paulista de Tecnologia dos Agronegocios","correspondingAuthor":false,"prefix":"","firstName":"Aníbal","middleName":"Eugênio Vercesi","lastName":"Filho","suffix":""},{"id":471633328,"identity":"f97fdf49-b5d9-45a5-80f8-32cefe9d0d50","order_by":6,"name":"Fernando César Ferraz Lopes","email":"","orcid":"","institution":"Embrapa Gado de Leite","correspondingAuthor":false,"prefix":"","firstName":"Fernando","middleName":"César Ferraz","lastName":"Lopes","suffix":""},{"id":471633329,"identity":"0e176132-f1ca-435e-b9fd-2c9ab6e7da9c","order_by":7,"name":"Maria Raquel Santos Carvalho","email":"","orcid":"","institution":"Universidade Federal de Minas Gerais","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"Raquel Santos","lastName":"Carvalho","suffix":""},{"id":471633330,"identity":"934f61c2-0e92-4729-aaf7-678bbc1e65a0","order_by":8,"name":"Pablo Augusto de Souza Fonseca","email":"","orcid":"","institution":"Instituto de Ganadería de Montaña: Instituto de Ganaderia de Montana","correspondingAuthor":false,"prefix":"","firstName":"Pablo","middleName":"Augusto de Souza","lastName":"Fonseca","suffix":""},{"id":471633331,"identity":"5d8c662d-ff19-4321-b4cc-4ec4a393b955","order_by":9,"name":"Marco Antônio Sundfeld da Gama","email":"","orcid":"","institution":"Embrapa Gado de Leite","correspondingAuthor":false,"prefix":"","firstName":"Marco","middleName":"Antônio Sundfeld da","lastName":"Gama","suffix":""},{"id":471633332,"identity":"ada5c9c4-dbfa-4cf7-932a-0a24b75c93ae","order_by":10,"name":"Maria Gabriela Campolina Diniz Peixoto","email":"","orcid":"","institution":"Embrapa Gado de Leite","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"Gabriela Campolina Diniz","lastName":"Peixoto","suffix":""}],"badges":[],"createdAt":"2025-06-07 15:17:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6843607/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6843607/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84886197,"identity":"bdc44404-0d74-4986-978d-7a89d66c0d96","added_by":"auto","created_at":"2025-06-18 11:42:30","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":31129,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003ePosterior\u003c/em\u003e means of the estimates of the genetic correlation coefficients among milk yield (MY305), fat yield (FY305), and individual fatty acids of Gir cows’ milk\u003c/p\u003e\n\u003cp\u003eSource: The author.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6843607/v1/1d8c11572c8a4c355eeb9792.png"},{"id":84884952,"identity":"5f37f892-6e93-460e-aad1-648073aeefd4","added_by":"auto","created_at":"2025-06-18 11:34:30","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":35775,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003ePosterior\u003c/em\u003e means of the estimates of the genetic correlation coefficients between milk yield (MY305), fat yield (FY305), and individual fatty acids of Guzerá cows’ milk\u003c/p\u003e\n\u003cp\u003eSource: The author.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6843607/v1/5667a2be066ab1687db7f8ea.png"},{"id":86321411,"identity":"16fb130a-d69b-47f9-b076-12c3ceeb74e6","added_by":"auto","created_at":"2025-07-09 09:52:18","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1860929,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6843607/v1/261a27db-df6f-4720-8acb-85b727ca9e1d.pdf"}],"financialInterests":"","formattedTitle":"Genetic parameters for milk fatty acid profiles in Gir and Guzerá cows using a Bayesian approach","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eRuminant milk fat is the most complex lipid in the human diet. It contains several bioactive fatty acids (FAs) with potential benefits on human health, with some not found in significant amounts in other food sources (Lopes et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; G\u0026oacute;mez-Cort\u0026eacute;s et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Due to the high saturated fat content in milk, some health professionals have recommended reducing its consumption (Matosinho et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and the media has published articles against its use in human nutrition, which has damaged the image of milk among consumers worldwide. However, several FAs have beneficial effects on health, including anti-cancer, anti-atherogenic, and immunomodulatory activities (Abdoul-Aziz et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Coniglio et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Among these, the most well-known are butyric acid (C4:0); odd- and branched-chain FAs (OBCFAs), rumenic acid (\u003cem\u003ecis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e-11 conjugated linoleic acid [CLA]) and its precursor vaccenic acid (\u003cem\u003etrans\u003c/em\u003e-11 C18:1), oleic acid (\u003cem\u003ecis\u003c/em\u003e-9 C18:1), and omega-3 FAs (Kratz et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; G\u0026oacute;mez-Cort\u0026eacute;s et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe nutritional quality of milk fat can be assessed using indexes based on concentrations of specific FAs. The atherogenic (AI) and thrombogenic (TI) indices are among the most commonly used indices. There is a consensus in the literature that lower AI and TI values indicate a lower concentration of undesirable FAs and a higher concentration of bioactive FAs that are beneficial to human health (Hanuš et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Chen and Liu \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Duque et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSeveral studies have estimated genetic parameters for the bovine milk FA profile (Soyeurt et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Stoop et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Narayana et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Bobbo et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Klein et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Their results generally indicate that short-chain FAs (SCFAs) and medium-chain FAs (MCFAs) are under greater genetic control than long-chain FAs (LCFAs). LCFAs originate from the diet, ruminal biohydrogenation, and mobilization from adipose tissue, while SCFAs and MCFAs are mainly synthesized \u003cem\u003ede novo\u003c/em\u003e in the mammary gland (Bouwman et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHigher heritability estimates are expected for saturated FAs (SFAs) than for unsaturated FAs (UFAs) because most SFAs originate from \u003cem\u003ede novo\u003c/em\u003e synthesis in the mammary gland (Chilliard et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Most studies that have estimated genetic parameters for the milk FA profile have involved taurine breeds. Information on relevant traits in Zebu breeds, such as Gir and Guzer\u0026aacute;, remains limited, despite their importance for dairy production in countries like Brazil, where most dairy cattle have a Zebu genetic composition (Peixoto et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Carvalho et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Matosinho et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Since Zebu breeds represent a valuable national genetic resource, studying the genetic variability of the milk FA profile, mainly FAs with nutraceutical potential, is crucial for defining selection criteria to improve both milk production and milk fat quality focused on human health. Therefore, this study aimed to estimate the variance components and genetic parameters of the FA profile and unsaturation indexes from milk fat of Zebu cows using a Bayesian approach.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePhenotypic and genealogical data\u003c/h2\u003e \u003cp\u003eThis study used records on milk production traits from the databases of the National Programs for the Improvement of Gir and Guzer\u0026aacute; Dairy Cattle, coordinated by Embrapa Gado de Leite in close partnership with the Brazilian Association of Gir Dairy Cattle Breeders and the Brazilian Center for the Genetic Improvement of Guzer\u0026aacute;. The analyses first used the lactation records of 15,620 Gir cows, measured from 1997 to 2016, and 7,569 Guzer\u0026aacute; cows, measured from 1983 to 2022. Monthly production data was accumulated and truncated at 305 days. The FA profile data was obtained from the project \u0026ldquo;Influence of polymorphisms in the stearoyl-CoA desaturase (SCD) enzyme gene on the nutritional quality of milk fat from Gir and Guzer\u0026aacute; cows\u0026rdquo; (Fapemig: CVZ APQ 02003-15), coordinated by Embrapa Gado de Leite.\u003c/p\u003e \u003cp\u003eTo study the FA profile, individual and unique milk samples were taken from 337 Gir cows and 284 Guzer\u0026aacute; cows from 11 herds of each breed during the period around peak lactation, when the expression of genes involved in lipid metabolism and phenotypic expression is expected to be highest (Bionaz and Loor \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The Gir herds were distributed in Southeastern Brazil, and the Guzer\u0026aacute; herds were distributed in Southeastern and Northeastern Brazil. Milk samples were collected in 2012, 2016 (except for the Gir breed), 2017, and 2018. Each 15 mL milk sample comprised ⅔ of the milk from the A.M. (morning) milking and ⅓ from the P.M. (afternoon) milking, representing individual daily production close to the testing day. The samples were collected in Falcon tubes containing no preservative, and were immediately frozen at \u0026minus;\u0026thinsp;20\u0026ordm;C until analyzed.\u003c/p\u003e \u003cp\u003eAll procedures and conditions used in the gas chromatography analysis of the milk FA profile were described in detail by Matosinho et al. (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The concentrations of FAs in milk samples were described in g/100 g of total FA.\u003c/p\u003e \u003cp\u003eThis study examined 14 individual FAs, 11 FA groups, four nutritional quality indices, and five unsaturation indices (Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Tables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e describe the FAs in each FA group and the formulas used to calculate the indices. The unsaturation indices were calculated for the four main stearoyl-CoA desaturase 1 (SCD1) product/substrate pairs (\u003cem\u003ecis\u003c/em\u003e-9 C14:1/C14:0, \u003cem\u003ecis\u003c/em\u003e-9 C16:1/C16:0, \u003cem\u003ecis\u003c/em\u003e-9C18:1/C18:0, and \u003cem\u003ecis\u003c/em\u003e-9 \u003cem\u003etrans\u003c/em\u003e-11 CLA/\u003cem\u003etrans\u003c/em\u003e-11 C18:1), and the total unsaturation index (TUI) was calculated, as described by Schennink et al. (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNomenclature of the individual fatty acids and the fatty acid groups studied\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrait\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCommon nomenclature\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndividual fatty acids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC4:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ebutyric acid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC8:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecaprylic acid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC10:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecapric acid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC12:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elauric acid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC14:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emyristic acid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC16:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epalmitic acid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC18:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003estearic acid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003etrans\u003c/em\u003e-11 C18:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003etrans\u003c/em\u003e-vaccenic acid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ecis\u003c/em\u003e-9 C18:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eoleic acid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC18:2 ω-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elinoleic acid (omega 6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCLA \u003cem\u003ecis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e-11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003erumenic acid\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC18:3 ω-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eα-linolenic acid (omega 3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC18:3 ω-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eγ-linolenic acid (omega 6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC20:5 ω-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eeicosapentaenoic acid (omega 3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFatty acid groups\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eshort-chain fatty acids\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emedium-chain fatty acids\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003elong-chain fatty acids\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003esaturated fatty acids\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eunsaturated fatty acids\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMUFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003emonounsaturated fatty acids\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePUFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epolyunsaturated fatty acids\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOLCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eodd- and linear-chain fatty acids\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOBCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eodd- and branched-chain fatty acids\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eω-6 \u003cem\u003ecis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ecis\u003c/em\u003e-configured omega-6 fatty acids\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eω-3 \u003cem\u003ecis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ecis\u003c/em\u003e-configured omega-3 fatty acids\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNomenclature of milk fat nutritional quality indexes and unsaturation indexes studied\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrait\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCommon nomenclature\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMilk fat nutritional quality indexes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eω6/ω3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003erelationship between omega 6 and omega 3 fatty acids\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eh/H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003erelationship between hypocholesterolemic and hypercholesterolemic fatty acids\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eatherogenic index\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ethrombogenic index\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnsaturation indexes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex C14:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eunsaturation index C14:1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex C16:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eunsaturation index C16:1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex C18:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eunsaturation index C18:1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex CLA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eunsaturation index CLA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003etotal unsaturation index\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGroups of fatty acids calculated from the milk FA profile of Gir and Guzer\u0026aacute; cows\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eFA group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFatty acids included\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSCFA\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026sum; (C4:0\u0026thinsp;+\u0026thinsp;C6:0\u0026thinsp;+\u0026thinsp;C8:0\u0026thinsp;+\u0026thinsp;C10:0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMCFA\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026sum; (C11:0\u0026thinsp;+\u0026thinsp;C12:0\u0026thinsp;+\u0026thinsp;C14:0\u0026thinsp;+\u0026thinsp;\u003cem\u003ecis\u003c/em\u003e-9 C14:1\u0026thinsp;+\u0026thinsp;C15:0\u0026thinsp;+\u0026thinsp;C16:0\u0026thinsp;+\u0026thinsp;\u003cem\u003ecis\u003c/em\u003e-9 C16:1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLCFA\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026sum; (C17:0\u0026thinsp;+\u0026thinsp;C18;0\u0026thinsp;+\u0026thinsp;C17:1\u0026thinsp;+\u0026thinsp;C18:1 ω-9 \u003cem\u003etrans\u003c/em\u003e\u0026thinsp;+\u0026thinsp;C18:1 ω-9 \u003cem\u003ecis\u003c/em\u003e\u0026thinsp;+\u0026thinsp;C18:2 ω-6\u003c/p\u003e \u003cp\u003e\u003cem\u003etrans\u003c/em\u003e\u0026thinsp;+\u0026thinsp;C18:2 ω-6 \u003cem\u003ecis\u003c/em\u003e\u0026thinsp;+\u0026thinsp;C18:3 ω-3\u0026thinsp;+\u0026thinsp;C22:5 ω-3\u0026thinsp;+\u0026thinsp;\u003cem\u003ecis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e- 11 CLA)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSFA\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026sum; (C4:0\u0026thinsp;+\u0026thinsp;C6:0\u0026thinsp;+\u0026thinsp;C8:0\u0026thinsp;+\u0026thinsp;C10:0\u0026thinsp;+\u0026thinsp;C11:0\u0026thinsp;+\u0026thinsp;C12:0\u0026thinsp;+\u0026thinsp;C13:0\u0026thinsp;+\u0026thinsp;C14:0\u0026thinsp;+\u0026thinsp;C15:0\u003c/p\u003e \u003cp\u003e+ C16:0\u0026thinsp;+\u0026thinsp;C17:0\u0026thinsp;+\u0026thinsp;C18:0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUFA\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u0026sum; (\u003cem\u003ecis\u003c/em\u003e-9 C14:1\u0026thinsp;+\u0026thinsp;\u003cem\u003ecis\u003c/em\u003e-9 C16:1\u0026thinsp;+\u0026thinsp;\u003cem\u003ecis\u003c/em\u003e-9 C17:1\u0026thinsp;+\u0026thinsp;\u003cem\u003ecis-9\u003c/em\u003e C18:1\u0026thinsp;+\u0026thinsp;C18:2 ω-6\u003c/p\u003e \u003cp\u003e\u003cem\u003etrans\u003c/em\u003e\u0026thinsp;+\u0026thinsp;C18:2 ω-6 \u003cem\u003ecis\u003c/em\u003e\u0026thinsp;+\u0026thinsp;C18:3 ω-3\u0026thinsp;+\u0026thinsp;C22:5 ω-3\u0026thinsp;+\u0026thinsp;\u003cem\u003ecis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e- 11 CLA)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMUFA\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u0026sum; (\u003cem\u003ecis\u003c/em\u003e-9 C14:1\u0026thinsp;+\u0026thinsp;\u003cem\u003ecis\u003c/em\u003e-9 C16:1\u0026thinsp;+\u0026thinsp;\u003cem\u003etrans\u003c/em\u003e-11 C18:1\u0026thinsp;+\u0026thinsp;\u003cem\u003ecis\u003c/em\u003e-9 C18:1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePUFA\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u0026sum; (C18:2 ω-6\u0026thinsp;+\u0026thinsp;C18:3 ω-3\u0026thinsp;+\u0026thinsp;\u003cem\u003ecis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e-11 CLA)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOLCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u0026sum; (C5:0\u0026thinsp;+\u0026thinsp;C7:0\u0026thinsp;+\u0026thinsp;C9:0\u0026thinsp;+\u0026thinsp;C11:0\u0026thinsp;+\u0026thinsp;C15:0\u0026thinsp;+\u0026thinsp;C17:0\u0026thinsp;+\u0026thinsp;\u003cem\u003ecis-\u003c/em\u003e9 C17:1\u0026thinsp;+\u0026thinsp;C21:0 +\u003c/p\u003e \u003cp\u003eC23:0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOBCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u0026sum; (OLCFA\u0026thinsp;+\u0026thinsp;\u003cem\u003eanteiso\u003c/em\u003e C15:0\u0026thinsp;+\u0026thinsp;\u003cem\u003eiso\u003c/em\u003e C14:0\u0026thinsp;+\u0026thinsp;\u003cem\u003eiso\u003c/em\u003e C15:0\u0026thinsp;+\u0026thinsp;\u003cem\u003eiso\u003c/em\u003e C16:0\u0026thinsp;+\u0026thinsp;\u003cem\u003eiso\u003c/em\u003e C17:0 \u003cem\u003eiso\u003c/em\u003e\u0026thinsp;+\u0026thinsp;C18:0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eω-6 \u003cem\u003ecis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u0026sum; (C18:2 ω-6\u0026thinsp;+\u0026thinsp;C18:3 ω-6\u0026thinsp;+\u0026thinsp;C20:2 ω-6\u0026thinsp;+\u0026thinsp;C20:3 ω-6\u0026thinsp;+\u0026thinsp;C20:4 ω-6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eω-3 \u003cem\u003ecis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u0026sum; (C18:3 ω-3\u0026thinsp;+\u0026thinsp;C20:5 ω-3\u0026thinsp;+\u0026thinsp;C22:5 ω-3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eSCFA: short-chain fatty acids; MCFA: medium-chain fatty acids; LCFA: long-chain fatty acids; SFA: saturated fatty acids; UFA: unsaturated fatty acids; MUFA: monounsaturated fatty acids; PUFA: polyunsaturated fatty acids; OLCFA: odd- and linear-chain fatty acids; OBCFA: odd- and branched-chain fatty acids; ω-6 \u003cem\u003ecis\u003c/em\u003e: omega 6 fatty acids with a \u003cem\u003ecis\u003c/em\u003e configuration; ω-3 c\u003cem\u003eis\u003c/em\u003e: omega 3 fatty acids with a \u003cem\u003ecis\u003c/em\u003e configuration.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eSource: \u003csup\u003ea\u003c/sup\u003eNarayana et al. (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2017\u003c/span\u003e); \u003csup\u003eb\u003c/sup\u003eKrag et al. (2013).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eFatty acids and formulas used to calculate the fatty acid profile indexes of the milk fat from Gir and Guzer\u0026aacute; cows\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eTrait\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFatty acids included\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eMilk fat nutritional quality indexes - Formulas\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eω-6/ω-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e(\u0026sum; ω-6 \u003cem\u003ecis\u003c/em\u003e) / (\u0026sum; ω-3 \u003cem\u003ecis\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eh/H\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e(\u003cem\u003ecis\u003c/em\u003e-9 C18:1\u0026thinsp;+\u0026thinsp;C18:2 ω-6\u0026thinsp;+\u0026thinsp;C20:4 ω-6\u0026thinsp;+\u0026thinsp;C18:3 ω-3\u0026thinsp;+\u0026thinsp;C20:5 ω-3\u0026thinsp;+\u0026thinsp;C22:5 ω-\u003c/p\u003e \u003cp\u003e3\u0026thinsp;+\u0026thinsp;C22:5 ω-6) / (C12:0\u0026thinsp;+\u0026thinsp;C14:0\u0026thinsp;+\u0026thinsp;C16:0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAI\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e(C12:0 +(4 x C14:0)\u0026thinsp;+\u0026thinsp;C16) / (\u003cem\u003ecis\u003c/em\u003e-9 C18:1\u0026thinsp;+\u0026thinsp;ω-6 \u003cem\u003ecis\u003c/em\u003e\u0026thinsp;+\u0026thinsp;ω-3 \u003cem\u003ecis\u003c/em\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTI\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e(C14:0\u0026thinsp;+\u0026thinsp;C16:0\u0026thinsp;+\u0026thinsp;C18:0) / ((0.5 x \u003cem\u003ecis\u003c/em\u003e-9 C18:1) + (0.5 x ω-6 \u003cem\u003ecis\u003c/em\u003e) + (3 x ω-3 \u003cem\u003ecis\u003c/em\u003e)\u003c/p\u003e \u003cp\u003e+ (ω-6/ω-3))\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eUnsaturation index - Formulas\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eIndex C14:1\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e(\u003cem\u003ecis\u003c/em\u003e-9 C14:1)/(\u003cem\u003ecis\u003c/em\u003e-9 C14:1\u0026thinsp;+\u0026thinsp;C14:0) x 100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex C16:1\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e(\u003cem\u003ecis\u003c/em\u003e-9C16:1) / (\u003cem\u003ecis\u003c/em\u003e-9 C16:1\u0026thinsp;+\u0026thinsp;C16:0) x 100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c4\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex C18:1\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e(\u003cem\u003ecis\u003c/em\u003e-9 C18:1) / (\u003cem\u003ecis\u003c/em\u003e-9 C18:1\u0026thinsp;+\u0026thinsp;C18:0) x 100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c4\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex CLA\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e(\u003cem\u003ecis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e-11 CLA) / (\u003cem\u003ecis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e-11 CLA\u0026thinsp;+\u0026thinsp;\u003cem\u003etrans\u003c/em\u003e-11 C18:1) x 100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c4\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUI\u003csup\u003ec,d\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e100 x (\u003cem\u003ecis\u003c/em\u003e-9 C14:1\u0026thinsp;+\u0026thinsp;\u003cem\u003ecis\u003c/em\u003e-9 C16:1\u0026thinsp;+\u0026thinsp;\u003cem\u003ecis\u003c/em\u003e-9 C18:1\u0026thinsp;+\u0026thinsp;\u003cem\u003ecis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e-11 CLA) / ((\u003cem\u003ecis\u003c/em\u003e-9 C14:1\u0026thinsp;+\u0026thinsp;\u003cem\u003ecis-\u003c/em\u003e9 C16:1\u0026thinsp;+\u0026thinsp;\u003cem\u003ecis\u003c/em\u003e-9 C18:1\u0026thinsp;+\u0026thinsp;\u003cem\u003ecis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e-11 CLA\u0026thinsp;+\u0026thinsp;C14:0\u0026thinsp;+\u0026thinsp;C16:0\u0026thinsp;+\u0026thinsp;C18:0\u0026thinsp;+\u0026thinsp;\u003cem\u003etrans\u003c/em\u003e-11 C18:1))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c4\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eω6/ω3: ratio between omega-6 and omega-3 fatty acids; h/H: ratio between hypocholesterolemic and hypercholesterolemic fatty acids; AI: atherogenic index; TI: thrombogenic index; C14:1 index: stearoyl Co-A desaturase enzyme activity index (unsaturation index); TUI: total unsaturation index.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eSource: \u003csup\u003ea\u003c/sup\u003eSantos-Silva et al. (2002); \u003csup\u003eb\u003c/sup\u003eUlbricht and Southgate (1991); \u003csup\u003ec\u003c/sup\u003eSchennink et al. (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2008\u003c/span\u003e); \u003csup\u003ec,d\u003c/sup\u003eMele et al. (2007).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe pedigree data comprised 34,248 Gir animals (13,365 dams and 2,221 sires) distributed over nine generations, and 21,954 Guzer\u0026aacute; animals (10,773 dams and 2,203 sires) distributed over 14 generations. Two databases were established, one for the Gir breed and one for the Guzer\u0026aacute; breed. These data were evaluated separately.\u003c/p\u003e \u003cp\u003eBesides the animal identification and pedigree data, these databases contained information on cows\u0026rsquo; birth date, calving date, date of FA profile sampling, age at calving, age at FA profile sampling, herd, diet, contemporary group (CG), days in milk (DIM), 305-day milk yield (MY305) and fat yield (FY305), FA profile, and indices. The mean DIM for cows with an FA profile was 67.00\u0026thinsp;\u0026plusmn;\u0026thinsp;34.89 days for the Gir breed and 73.00\u0026thinsp;\u0026plusmn;\u0026thinsp;38.54 days for the Guzer\u0026aacute; breed.\u003c/p\u003e \u003cp\u003eFor the FA profile analyses, the birth order at sampling and diet were grouped into classes. For age at sampling (AS), three classes were defined for both breeds. For diet, six categories were defined for the Gir breed and four for the Guzer\u0026aacute; breed (Tables\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and \u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). During categorization, the diets were initially divided into three large groups (tropical pasture, corn silage, and mixed [tropical pasture and corn silage]), and then these groups were subdivided according to the type of concentrate provided: with lipid concentrate (soy, protected fat or whole cottonseed were included in this class) or without lipid concentrate (barley was used). A greater diversity of diets was observed in Gir herds.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNumber of animals (N) of the Gir cows sampled for the fatty acid profile study, according to the age class and diet category\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClass\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eComposition of the animals\u0026rsquo; age class\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFirst birth\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSecond to fourth birth order\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAnimals above the fourth calving order\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDiet composition\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCorn silage\u0026thinsp;+\u0026thinsp;Non-lipid concentrate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCorn silage\u0026thinsp;+\u0026thinsp;Lipid concentrate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTropical pasture\u0026thinsp;+\u0026thinsp;Non-lipid concentrate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTropical pasture\u0026thinsp;+\u0026thinsp;Lipid concentrate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMixed\u0026thinsp;+\u0026thinsp;Non-lipid concentrate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMixed\u0026thinsp;+\u0026thinsp;Lipid concentrate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eThe average age at first calving from the milk database was taken as the basis for determining the age of the animals that would be included in the first class.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eNumber of animals (N) by age class and category of diet fed to the Guzer\u0026aacute; cows sampled for the fatty acid profile study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClass\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eComposition of the animals\u0026rsquo; age class\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFirst birth\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSecond to fourth birth order\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAnimals above the fourth calving order\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDiet composition\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCorn silage\u0026thinsp;+\u0026thinsp;Non-lipid concentrate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTropical pasture\u0026thinsp;+\u0026thinsp;Non-lipid concentrate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTropical pasture\u0026thinsp;+\u0026thinsp;Lipid concentrate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMixed\u0026thinsp;+\u0026thinsp;Non-lipid concentrate\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eThe average age at first calving from the milk database was taken as the basis for determining the age of the animals that would be included in the first class.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the MY305 and FY305 analyses, only data from the first lactation were retained, and CGs were formed by concatenating herd, year, and calving season (dry: April to September; rainy: October to March). In the FA analyses, CGs were formed by concatenating herd, year, and sampling season (dry and rainy).\u003c/p\u003e \u003cp\u003eCows with an FA profile but missing information (unknown dam and/or sire, birth date, and/or calving date) were eliminated from the database. Only CGs with more than three cows, consisting of daughters of at least two different sires, were retained. Values outside \u0026plusmn;\u0026thinsp;3 standard deviations for each trait were considered outliers and excluded from the CG. Finally, for the Gir breed, the phenotypic dataset contained information on MY305 (CG\u0026thinsp;=\u0026thinsp;2,117) from 15,902 cows, FY305 (CG\u0026thinsp;=\u0026thinsp;705) from 5,255 cows, and FA profile (CG\u0026thinsp;=\u0026thinsp;12) from 299 cows. For the Guzer\u0026aacute; breed, the phenotypic dataset contained information on MY305 (CG\u0026thinsp;=\u0026thinsp;655) from 7,159 cows, for FY305 (CG\u0026thinsp;=\u0026thinsp;206) from 2,460 cows, and the FA profile (CG\u0026thinsp;=\u0026thinsp;16) from 266 cows.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eVariance components and genetic parameters\u003c/h3\u003e\n\u003cp\u003eFor the FA profile, the (co)variance components were estimated via Bayesian inference in tri-trait analyses, using MY305 and FY305 as genetic anchor traits. The systematic effects considered in the models for MY305 and FY305 analyses were CG and age at calving (linear covariate). The systematic effects for the FA profile were AS class, diet category, CG, and DIM (linear covariate). The general model used to estimate the genetic parameters was:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:\\mathbf{y}=\\mathbf{X}\\varvec{\\beta\\:}+\\mathbf{Z}\\mathbf{a}+\\varvec{\\epsilon\\:}$$\u003c/div\u003e\u003c/div\u003e,\u003c/p\u003e \u003cp\u003ewhere \u003cb\u003ey\u003c/b\u003e is the vector of phenotypes for each trait (MY305, FY305, or FA), \u003cb\u003eX\u003c/b\u003e is the incidence matrix related to systematic effects, \u003cb\u003eβ\u003c/b\u003e is the vector of systematic effects, \u003cb\u003eZ\u003c/b\u003e is the incidence matrix of genetic-additive random effects, \u003cb\u003ea\u003c/b\u003e is the vector of genetic-additive random effects, and \u003cb\u003eε\u003c/b\u003e is the vector of residual random effects. The following distributions were assumed: \u0026#119858;| \u003cb\u003e\u0026#120573;\u003c/b\u003e, \u0026#119834;, \u003cb\u003e\u0026#120576;\u003c/b\u003e~N (\u003cb\u003e\u0026#119831;\u0026#120573;\u003c/b\u003e +\u0026#119833;\u0026#119834;, \u0026#119825;\u003csub\u003e0\u003c/sub\u003e \u0026otimes; \u0026#119816;); \u003cb\u003e\u0026#120573;\u003c/b\u003e~N (0, \u0026#120506;\u003csub\u003eβ\u003c/sub\u003e \u0026otimes;\u0026#119816;), where \u0026#120506;\u003csub\u003eβ\u003c/sub\u003e is a diagonal matrix with values of 1 \u0026times; 10\u003csup\u003e9\u003c/sup\u003e to represent uninformative priors; \u0026#119834;|\u0026#119814;\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;~\u0026thinsp;N(0, \u0026#119814;\u003csub\u003e0\u003c/sub\u003e \u0026otimes; \u0026#119808;); \u003cb\u003e\u0026#120576;\u003c/b\u003e|~ N(0, \u0026#119825;\u003csub\u003e0\u003c/sub\u003e \u0026otimes; \u0026#119816;), where \u0026#119814;\u003csub\u003e0\u003c/sub\u003e is the (co)variance matrix of the genetic-additive effects, \u003cb\u003eA\u003c/b\u003e is the numerator of the relationship matrix; \u003cb\u003eI\u003c/b\u003e is an identity matrix; and \u0026#119825;\u003csub\u003e0\u003c/sub\u003e is the residual (co)variance matrix. An \u003cem\u003ea priori\u003c/em\u003e inverted Wishart distribution (IW) was assumed for \u0026#119814;\u003csub\u003e0\u003c/sub\u003e and \u0026#119825;\u003csub\u003e0\u003c/sub\u003e. \u0026#119814;\u003csub\u003e0|\u003c/sub\u003e\u0026#119881;\u003csub\u003e\u0026#119892;\u003c/sub\u003e, \u0026#119907;\u003csub\u003e\u0026#119892;\u003c/sub\u003e~ IW (\u0026#119881;\u003csub\u003e\u0026#119892;\u003c/sub\u003e, \u0026#119907;\u003csub\u003e\u0026#119892;\u003c/sub\u003e); \u0026#119825;\u003csub\u003e0\u003c/sub\u003e|\u0026#119881;\u003csub\u003e\u0026#119903;\u003c/sub\u003e, \u0026#119907;\u003csub\u003e\u0026#119903;\u003c/sub\u003e~ IW (\u0026#119881;\u003csub\u003e\u0026#119903;\u003c/sub\u003e, \u0026#119907;\u003csub\u003e\u0026#119903;\u003c/sub\u003e), where \u0026#119881;\u003csub\u003e\u0026#119892;\u003c/sub\u003e and \u0026#119881;\u003csub\u003e\u0026#119903;\u003c/sub\u003e are the values of the hyperparameters of the (co)variance components, and \u0026#119907;\u003csub\u003e\u0026#119892;\u003c/sub\u003e and \u0026#119907;\u003csub\u003e\u0026#119903;\u003c/sub\u003e are \u003cem\u003ea priori\u003c/em\u003e degrees of freedom corresponding to the values of the hyperparameters of the (co)variances.\u003c/p\u003e \u003cp\u003eThe models were implemented in a Bayesian approach using a Markov chain Monte Carlo methodology with Gibbs sampling using the GIBBSF90\u0026thinsp;+\u0026thinsp;program (Misztal et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). A chain size of 2,000,000 iterations was generated, considering a burn-in of 500,000 iterations and a thinning of 50, for all traits. Then, 30,000 samples were used to obtain the marginal \u003cem\u003eposterior\u003c/em\u003e distribution of the variance components and genetic parameters. The convergence criteria of the Gibbs chains were monitored by graphical inspection and the Geweke test (Geweke \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1991\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe \u003cem\u003eposterior\u003c/em\u003e estimates of the heritability coefficients (ℎ\u003csup\u003e2\u003c/sup\u003e) and genetic correlations were calculated using the values obtained in the tri-trait analysis for the FA profile and in the bi-trait analysis for MY305 and FY305.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eTables\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e present the descriptive statistics for each trait among the Gir and Guzer\u0026aacute; cows. For Gir cows, large coefficients of variation (CVs) were observed for most of the FA profile traits. In contrast, Guzer\u0026aacute; cows had slightly lower CVs for FA traits. Regardless of the breed, palmitic acid (C16:0) was the most abundant FA in milk fat, followed by oleic (\u003cem\u003ecis\u003c/em\u003e-9 C18:1), stearic (C18:0), and myristic (C14:0) acids. Concentrations were higher for MCFAs than for LCFAs and SCFAs, and for SFAs than for UFAs. The proportion was higher for monounsaturated FAs (MUFAs) than for polyunsaturated FAs (PUFAs). The other individual FAs and FA groups were found at concentrations\u0026thinsp;\u0026lt;\u0026thinsp;4 g/100 g total FA. The nutritional quality of milk fat and unsaturation indices were similar for both breeds (Tables\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e and \u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMeans, standard deviations (SD), coefficients of variation (CV), minimum and maximum values for the milk yield (MY305), fat yield (FY305), and individual fatty acids (g/100 g of total fatty acids) from the milk fat of Gir cows\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrait\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean (kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026plusmn; SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCV (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMinimum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMY305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15,601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,894\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,736.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,314.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e8,102.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFY305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e119.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e41.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e280.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eIndividual fatty acids\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC4:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e5.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC8:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e2.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC10:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e4.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC12:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e5.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC14:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e12.81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC16:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e42.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC18:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003e16.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003etrans\u003c/em\u003e-11 C18:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e296\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ecis\u003c/em\u003e-9 C18:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e33.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ecis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e-11 CLA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC18:3 ω-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC18:2 ω-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC18:3 ω-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC20:5 ω-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c8\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eCLA\u0026thinsp;=\u0026thinsp;conjugated linoleic acid.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMeans, standard deviations (SD), coefficients of variation (CV), minimum and maximum values for the fatty acid groups, nutritional quality indexes, and unsaturation indexes (g/100 g of total fatty acids) from the milk fat of Gir cows\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTrait\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eMean (kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e\u0026plusmn; SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCV (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eMinimum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eFatty acid groups\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e9.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e17.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e14.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e44.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e13.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e31.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e61.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e35.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e17.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e18.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e49.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e61.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e46.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e75.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eUFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e27.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e15.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e42.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMUFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e25.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e19.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e14.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e38.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePUFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e296\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e3.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eOLCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e2.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e21.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eOBCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e3.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e6.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eω-6 \u003cem\u003ecis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e2.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e43.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eω-3 \u003cem\u003ecis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e27.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003eMilk fat nutritional quality indexes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eω-6/ω-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e4.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e31.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eh/H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e34.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e36.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e31.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eUnsaturation indexes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex C14:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e21.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e16.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex C16:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e23.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e10.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex C18:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e5.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e8.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e54.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e82.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex CLA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e12.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e20.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e46.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003e18.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e19.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e49.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c10\" namest=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eSCFA: short-chain fatty acids; MCFA: medium-chain fatty acids; LCFA: long-chain fatty acids; SFA: saturated fatty acids; UFA: unsaturated fatty acids; MUFA: monounsaturated fatty acids; PUFA: polyunsaturated fatty acids; OLCFA: odd- and linear-chain fatty acids; OBCFA: odd- and branched-chain fatty acids; ω-6 \u003cem\u003ecis\u003c/em\u003e: \u003cem\u003ecis\u003c/em\u003e-configured omega-6 fatty acids; ω-3 \u003cem\u003ecis\u003c/em\u003e: \u003cem\u003ecis\u003c/em\u003e-configured omega-3 fatty acids; ω-6/ω-3: ratio between omega-6 and omega-3 fatty acids; h/H: ratio between hypocholesterolemic and hypercholesterolemic fatty acids; AI: atherogenic index; TI: thrombogenic index; Index C14:1: unsaturation index (stearoyl Co-A desaturase-1 enzyme activity index) and TUI: total unsaturation index.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMeans, standard deviations (SD), coefficients of variation (CV), minimum and maximum values for milk yield (PL305), fat yield (PG305), and individual fatty acids (g/100 g total fatty acids) from the milk fat of Guzer\u0026aacute; cows\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrait\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean (kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026plusmn; SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCV (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMinimum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMY305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,080.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e51.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,161.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5,322.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFY305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2460\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e200.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eIndividual fatty acids\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC4:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC8:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC10:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC12:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC14:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC16:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e34.90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC18:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e17.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003etrans\u003c/em\u003e-11 C18:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ecis\u003c/em\u003e-9 C18:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e30.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ecis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e-11 CLA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e42.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC18:3 ω-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC18:2 ω-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC18:3 ω-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC20:5 ω-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eCLA: conjugated linoleic acid.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMeans, standard deviations (SD), coefficients of variation (CV), minimum and maximum values for the fatty acid groups, nutritional quality indexes, and unsaturation indexes (g/100 g of total fatty acids) of milk fat from Guzer\u0026aacute; cows\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrait\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean (kg)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026plusmn; SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCV (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMinimum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eFatty acid groups\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e55.44\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e48.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e73.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e37.54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMUFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePUFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOLCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOBCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eω-6 \u003cem\u003ecis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eω-3 \u003cem\u003ecis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eMilk fat nutritional quality indexes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eω-6/ω-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eh/H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eUnsaturation indexes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex C14:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex C16:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e9.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex C18:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e53.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e79.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex CLA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e45.69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e265\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e44.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eSCFA: short-chain fatty acids; MCFA: medium-chain fatty acids; LCFA: long-chain fatty acids; SFA:saturated fatty acids; UFA: unsaturated fatty acids; MUFA: monounsaturated fatty acids; PUFA: polyunsaturated fatty acids; OLCFA: odd- and linear-chain fatty acids; OBCFA: odd- and branched-chain fatty acids; ω-6 \u003cem\u003ecis\u003c/em\u003e: \u003cem\u003ecis\u003c/em\u003e-configured omega-6 fatty acids; ω-3 \u003cem\u003ecis\u003c/em\u003e: \u003cem\u003ecis\u003c/em\u003e-configured omega-3 fatty acids; ω-6/ω-3: ratio between omega-6 and omega-3 fatty acids; h/H: ratio between hypocholesterolemic and hypercholesterolemic fatty acids; AI: atherogenic index; TI: thrombogenic index; C14:1 index: unsaturation index (stearoyl Co-A desaturase-1 enzyme activity index) and TUI: total unsaturation index.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOnly the 10 most studied individual FAs associated with human health, FA groups (SCFA, MCFA, LCFA, SFA, UFA, MUFA, PUFA, odd- and linear-chain FA [OLCFA], branched-chain FAs, ω-6 c\u003cem\u003eis\u003c/em\u003e, and ω-3 c\u003cem\u003eis\u003c/em\u003e), ω-6/ω-3 ratio, and unsaturation indices were used to estimate variance components and heritability. Genetic correlations were estimated only among individual FAs, MY305, and FY305.\u003c/p\u003e \u003cp\u003eThe number of chains analyzed was sufficient to stabilize all analyses for both breeds. Tables\u0026nbsp;\u003cspan refid=\"Tab11\" class=\"InternalRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab16\" class=\"InternalRef\"\u003e16\u003c/span\u003e present the \u003cem\u003eposterior\u003c/em\u003e estimates of the variance components and heritability of the milk FA profile in Gir and Guzer\u0026aacute; cows. Regardless of the breed, the credibility intervals (CIs) were wide. The \u003cem\u003eposterior\u003c/em\u003e means of the estimates were 0.17 and 0.29 for the MY305 heritability coefficients and 0.06 and 0.21 for the FY305 heritability coefficients in the Gir and Guzer\u0026aacute; breeds, respectively. In the Gir data, the \u003cem\u003eposterior\u003c/em\u003e means of the heritability estimates ranged from 0.28 to 0.63 for individual Fas, from 0.32 to 0.66 for FA groups, and from 0.38 to 0.57 for the unsaturation indices. In the Guzer\u0026aacute; data, the heritability estimates ranged from 0.25 to 0.74 for the individual FAs, from 0.26 to 0.65 for the FA groups, and from 0.50 to 0.68 for the unsaturation indices.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab11\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 11\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003ePosterior\u003c/em\u003e means and respective standard deviation (PSD), confidence interval (CI, 95%) of estimates of additive genetic variance (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\sigma\\:}}_{a}^{2}\\)\u003c/span\u003e\u003c/span\u003e), residual variance (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\sigma\\:}}_{e}^{2}\\)\u003c/span\u003e\u003c/span\u003e), and heritability (h\u0026sup2;) for milk yield (MY305), fat yield (FY305) and individual fatty acids in milk from Gir cows\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTrait\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\sigma\\:}}_{a}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\sigma\\:}}_{e}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eh\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (PSD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (PSD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean (PSD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[CI]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMY305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e219,120.00 (21,846.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[177,700.00;\u003c/p\u003e \u003cp\u003e263,000.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,089,800.00 (21.562)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[1,050,000;\u003c/p\u003e \u003cp\u003e1,134,000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.17 (0.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.14;0.20]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFY305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e358.95 (65.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[234.10;486.70]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.656 (135.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[5.384; 5.915]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.06 (0.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.04;0.08]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eIndividual fatty acids\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC4:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0566 (0.025)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.0132; 0.1024]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1412 (0.023)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.0963; 0.1861]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.28 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.07; 0.49]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC8:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0136 (0.005)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.0069; 0.0206]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0287 (0.004)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.0217; 0.0369]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.32 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.17; 0.48]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC10:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1025 (0.037)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.0520; 0.1537]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1933 (0.032)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.1433; 0.2545]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.34 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.18; 0.51]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC12:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1404 (0.052)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.0714; 0.2114]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2350 (0.043)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.1702; 0.3171]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.37 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.20; 0.54]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC14:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5916 (0.233)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.3213; 1.0650]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8008 (0.162)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.5038; 1.0330]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.42 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.25; 0.68]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC16:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.4563 (1.743)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[2.3970; 8.4250]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.6920 (1.268)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[2.4380; 6.7810]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.63 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.27; 0.76]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC18:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.8888 (0.289)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.2915; 1.5410]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.5140 (0.246)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[1.0380; 2.1590]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.37 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.12; 0.57]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003etrans\u003c/em\u003e-11 C18:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0309 (0.015)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.0091; 0.0597]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0797 (0.016)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.0434; 0.1008]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.28 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.09; 0.57]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ecis\u003c/em\u003e-9 C18:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.4835 (1.718)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[1.4380; 7.8810]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.5755 (1.685)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[4.4010; 10.3800]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.37 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.14; 0.62]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ecis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e-11 CLA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0021 (0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.0007; 0.0040]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0020 (0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.0010; 0.0030]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.51 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.21; 0.78]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eCLA: conjugated linoleic acid.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eLower upper limits of the 95% probability confidence interval.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab12\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 12\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003ePosterior\u003c/em\u003e means and respective standard deviation (PSD), confidence interval (CI, 95%) of estimates of additive genetic variance (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\sigma\\:}}_{a}^{2}\\)\u003c/span\u003e\u003c/span\u003e), residual variance (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\sigma\\:}}_{e}^{2}\\)\u003c/span\u003e\u003c/span\u003e), and heritability (h\u0026sup2;) of the fatty acid groups in milk fat from Gir cows\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTrait\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\sigma\\:}}_{a}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\sigma\\:}}_{e}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eh\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (PSD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (PSD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean (PSD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[CI]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eFatty acid groups\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.4869 (0.166)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.1779; 0.7322]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.8260 (0.145)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.5742; 1.0920]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.37 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.14; 0.53]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.5974 (2.507)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[2.5510; 11.7000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.5600 (1.897)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[7.3110; 14.9800]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.44 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.15; 0.60]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.1399 (2.888)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[2.2250; 13.7700]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.3594 (2.881)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[6.3670; 15.6400]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.49 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.15; 0.67]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.2026 (2.770)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[1.7520; 12.2800]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.0370 (2.213)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[6.0320; 14.6100]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.41 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.12; 0.65]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.3455 (1.635)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[2.5420; 10.0500]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.0655 (1.590)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[4.5710; 10.7400]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.44 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.22; 0.68]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMUFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.9392 (1.725)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[2.0420; 9.1070]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.4987 (1.719)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[4.7840; 10.8900]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.37 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.20; 0.68]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePUFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0917 (0.032)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.0337; 0.1570]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1247 (0.027)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.0724; 0.1789]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.42 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.18; 0.68]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOLCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0321 (0.008)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.0137; 0.0459]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0167 (0.007)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.0086; 0.0329]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.66 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.33; 0.84]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOBCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0369 (0.014)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.0112; 0.0640]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0793 (0.013)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.0519; 0.1060]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.32 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.10; 0.53]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eω-6 \u003cem\u003ecis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0536 (0.020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.0170; 0.0916]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1003 (0.018)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.0656; 0.1348]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.35 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.12; 0.56]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eω-3 \u003cem\u003ecis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0027 (0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.0012; 0.0041]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0025 (0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.0014; 0.0037]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.52 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.26; 0.73]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eSCFA: short-chain fatty acids; MCFA: medium-chain fatty acids; LCFA: long-chain fatty acids; SFA: saturated fatty acids; UFA: unsaturated fatty acids; MUFA: monounsaturated fatty acids; PUFA: polyunsaturated fatty acids; OLCFA: odd- and linear-chain fatty acids; OBCFA: odd- and branched-chain fatty acids; ω-6 \u003cem\u003ecis\u003c/em\u003e: \u003cem\u003ecis\u003c/em\u003e-configured omega-6 fatty acids; ω-3 \u003cem\u003ecis\u003c/em\u003e: \u003cem\u003ecis\u003c/em\u003e-configured omega-3 fatty acids.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eLower upper limits of the 95% probability confidence interval.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab13\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 13\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003ePosterior\u003c/em\u003e means and respective standard deviation (PSD), confidence interval (CI, 95%) of estimates of additive genetic variance (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\sigma\\:}}_{a}^{2}\\)\u003c/span\u003e\u003c/span\u003e), residual variance (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\sigma\\:}}_{e}^{2}\\)\u003c/span\u003e\u003c/span\u003e), and heritability (h\u0026sup2;) of the indexes of nutritional quality and unsaturation of milk fat in Gir cows\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTrait\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\sigma\\:}}_{a}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\sigma\\:}}_{e}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eh\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (PSD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (PSD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean (PSD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[CI]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eMilk fat quality indexes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eω-6/ω-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1651 (0.084)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.0316; 0.3444]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5326 (0.081)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.3712; 0.6869]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.23 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.05; 0.46]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eUnsaturation indexes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex C14:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.9568 (0.583)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.6998; 3.2260]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.7827 (0.468)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.8938; 2.9550]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.52 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.21; 0.77]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex C16:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.9206 (0.323)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.3021; 1.3390]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.6540 (0.224)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.3533; 1.1010]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.57 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.24; 0.79]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex C18:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.4679 (2.159)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[2.2340; 10.4800]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.2350 (1.849)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[6.4130; 13.7300]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.38 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.15; 0.59]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex CLA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.6018 (1.965)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[2.9920; 10.8000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.3318 (1.762)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[5.5860; 12.4200]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.41 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.23; 0.66]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.2461 (2.976)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[3.1230; 14.8500]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.5230 (2.637)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[6.3850; 16.9000]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.39 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.17; 0.69]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eω-6/ω-3: ratio between omega-6 and omega-3 fatty acids; Index C14:1: unsaturation index (stearoyl Co-A desaturase-1 enzyme activity index) and TUI: total unsaturation index.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eLower upper limits of the 95% probability confidence interval.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab14\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 14\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003ePosterior\u003c/em\u003e means and respective standard deviation (PSD), confidence interval (CI, 95%) of estimates of additive genetic variance (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\sigma\\:}}_{a}^{2}\\)\u003c/span\u003e\u003c/span\u003e), residual variance (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\sigma\\:}}_{e}^{2}\\)\u003c/span\u003e\u003c/span\u003e), and heritability (h\u0026sup2;) for milk yield (MY305), fat yield (FY305) and individual fatty acids in milk from Guzer\u0026aacute; cows\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTrait\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\sigma\\:}}_{a}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\sigma\\:}}_{e}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eh\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (PSD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (PSD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean (PSD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[CI]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMY305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e143,090.00 (16,369.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[112,500.00;\u003c/p\u003e \u003cp\u003e175,700.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e348,150.00 (12,864.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[323,600.00;\u003c/p\u003e \u003cp\u003e374,000.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.29 (0.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.23;0.35]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFY305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e242.51 (42.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[164.20;326.50]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e925.08 (41.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[846.80;1006.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.21 (0.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.14;0.27]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eIndividual fatty acids\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC4:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0328 (0.016)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.0076; 0.0650]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0987 (0.015)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.0689; 0.1291]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.25 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.06; 0.46]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC8:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0183 (0.005)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.0085; 0.0286]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0132 (0.004)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.0056; 0.0210]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.58 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.31; 0.84]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC10:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1223 (0.030)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.0633; 0.1792]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0584 (0.023)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.0176; 0.1022]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.67 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.42; 0.91]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC12:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1912 (0.042)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.1133; 0.2734]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0663 (0.031)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.0166; 0.1250]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.74 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.50; 0.94]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC14:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.4710 (0.153)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.1834; 0.7797]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3765 (0.121)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.1278; 0.6002]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.55 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.26; 0.84]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC16:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.2550 (0.881)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.7426; 4.0310]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.0498 (0.741)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[1.6050; 4.4510]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.42 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.15; 0.70]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC18:0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.5169 (0.489)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.6634; 2.4550]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.9518 (0.375)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.2422; 1.6610]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.61 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.30; 0.89]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003etrans\u003c/em\u003e-11 C18:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0417 (0.026)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.0042; 0.0953]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0768 (0.023)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.0274; 0.1126]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.34 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.05; 0.72]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ecis\u003c/em\u003e-9 C18:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.8626 (1.078)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.9212; 4.9380]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.0800 (0.868)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[1.3610; 4.7060]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.48 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.19; 0.77]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ecis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e-11 CLA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0124 (0.005)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.0032; 0.0223]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0159 (0.044)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.0073; 0.0241]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.43 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.10; 0.73]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eCLA: conjugated linoleic acid.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eLower upper limits of the 95% probability confidence interval.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab15\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 15\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003ePosterior\u003c/em\u003e means and respective standard deviation (PSD), confidence interval (CI, 95%) of estimates of additive genetic variance (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\sigma\\:}}_{a}^{2}\\)\u003c/span\u003e\u003c/span\u003e), residual variance (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\sigma\\:}}_{e}^{2}\\)\u003c/span\u003e\u003c/span\u003e), and heritability (h\u0026sup2;) of the fatty acid groups in milk fat from Guzer\u0026aacute; cows\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTrait\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\sigma\\:}}_{a}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\sigma\\:}}_{e}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eh\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (PSD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[IC]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (PSD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[IC]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean (PSD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[IC]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eFatty acid groups\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.3408 (0.150)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.0911; 0.6352]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5818 (0.131)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.3196; 0.8256]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.37 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.11; 0.64]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.4889 (1.867)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.3444; 7.0270]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.7156 (1.579)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[3.5810; 9.6580]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.34 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.05; 0.64]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.7567 (2.150)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.6009; 8.7500]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.9152 (1.740)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[2.3710; 9.1670]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.44 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.08; 0.76]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.4938 (1.520)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.8112; 6.4880]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.7973 (1.290)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[3.2110; 8.3370]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.37 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.11; 0.65]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.3440 (1.606)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[1.4650; 7.3740]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.0161 (1.268)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.7397; 5.2450]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.58 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.25; 0.91]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMUFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.9643 (1.536)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.4850; 5.9930]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.7884 (1.254)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[1.1520; 5.9230]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.43 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.09; 0.81]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePUFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0361 (0.017)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.0037; 0.0680]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0444 (0.014)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.0179; 0.0710]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.44 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.07; 0.77]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOLCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0103 (0.005)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.0018; 0.0200]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0235 (0.004)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.0149; 0.0322]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.30 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.06; 0.55]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOBCFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0249 (0.013)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.0051; 0.0495]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0708 (0.012)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.0472; 0.0935]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.26 (0.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.06; 0.49]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eω-6 \u003cem\u003ecis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0108 (0.005)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.0019; 0.0211]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0196 (0.005)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.0107; 0.0283]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.35 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.07; 0.64]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eω-3 \u003cem\u003ecis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0031 (0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.0009; 0.0048]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0016 (0.001)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.0005; 0.0034]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.65 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.25; 0.90]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eSCFA: short-chain fatty acids; MCFA: medium-chain fatty acids; LCFA: long-chain fatty acids; SFA: saturated fatty acids; UFA: unsaturated fatty acids; MUFA: monounsaturated fatty acids; PUFA: polyunsaturated fatty acids; OLCFA: odd- and linear-chain fatty acids; OBCFA: odd- and branched-chain fatty acids; ω-6 \u003cem\u003ecis\u003c/em\u003e: \u003cem\u003ecis\u003c/em\u003e-configured omega-6 fatty acids; ω-3 \u003cem\u003ecis\u003c/em\u003e: \u003cem\u003ecis\u003c/em\u003e-configured omega-3 fatty acids.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eLower upper limits of the 95% probability confidence interval.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab16\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 16\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003ePosterior\u003c/em\u003e means and respective standard deviation (PSD), confidence interval (CI, 95%) of estimates of additive genetic variance (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\sigma\\:}}_{a}^{2}\\)\u003c/span\u003e\u003c/span\u003e), residual variance (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\sigma\\:}}_{e}^{2}\\)\u003c/span\u003e\u003c/span\u003e), and heritability (h\u0026sup2;) of the indexes of nutritional quality and unsaturation of milk fat in Guzer\u0026aacute; cows\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTrait\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\sigma\\:}}_{a}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{{\\sigma\\:}}_{e}^{2}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eh\u0026sup2;\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (PSD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[CI\u0026sup2;]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (PSD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean (PSD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[CI]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eMilk fat quality indexes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eω-6/ω-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0329 (0.029)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.0014; 0.0898]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.1227 (0.025)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.0697; 0.1674]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.21 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.01; 0.53]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eUnsaturation indexes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex C14:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.5935 (0.784)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[1.1710; 4.1230]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.1992 (0.595)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.1351; 2.2590]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.68 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.38; 0.96]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex C16:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6899 (0.193)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[0.3116; 1.0560]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3259 (0.147)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.0626; 0.6114]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.67 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.38; 0.95]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex C18:1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.6737 (3.170)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[3.3530; 15.3300]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.2263 (2.478)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.9302; 9.9460]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.64 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.31; 0.95]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndex CLA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.3183 (2.789)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[3.1740; 13.8100]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.5980 (2.142)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[0.7437; 8.4990]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.64 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.32; 0.95]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTUI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.3284 (2.083)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e[1.5150; 9.3560]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.1575 (1.685)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[1.8050; 8.2540]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.50 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e[0.19; 0.84]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eω-6/ω-3: ratio between omega-6 and omega-3 fatty acids; Index C14:1: unsaturation index (stearoyl Co-A desaturase-1 enzyme activity index) and TUI: total unsaturation index.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eLower upper limits of the 95% probability confidence interval.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe \u003cem\u003eposterior\u003c/em\u003e means of the genetic correlation coefficients are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e for the Gir breed and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e for the Guzer\u0026aacute; breed. Large \u003cem\u003eposterior\u003c/em\u003e standard deviations were observed for the genetic correlation estimates. For the genetic correlations, when zero was within the CIs, the estimates did not differ from zero. The correlations ranged from moderate to high regardless of direction.\u003c/p\u003e \u003cp\u003eFor the Gir breed, while MY305 showed no genetic correlations with individual FAs, FY305 showed a moderate positive genetic correlation with C4:0 and C16:0 FAs and a moderate negative correlation with \u003cem\u003ecis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e-11 CLA. The genetic correlations among the individual FAs ranged from \u0026minus;\u0026thinsp;0.90 to 0.98. C4:0 showed a negative and moderate correlation with C10:0, C12:0, and C14:0, and a positive correlation with C16:0 and \u003cem\u003etrans\u003c/em\u003e-11 C18:1. \u003cem\u003eCis\u003c/em\u003e-9 C18:1 showed a moderate to high and negative correlation with SCFAs and MCFAs (C8:0 to C16:0). \u003cem\u003eCis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e-11 CLA showed a positive and high genetic correlation with its precursor \u003cem\u003etrans\u003c/em\u003e-11 C18:1 and a moderate to high negative correlation with C8:0 to C14:0.\u003c/p\u003e \u003cp\u003eFor the Guzer\u0026aacute; breed, MY305 showed moderate genetic correlations with individual FAs, which were negative for C8:0 to C14:0 and positive for C18:0. FY305 showed a moderate and negative genetic correlation with C10:0, C12:0, and C14:0. Regarding individual FAs, C18:0 showed a moderate positive correlation with C4:0, and a negative correlation with C8:0 to C14:0. \u003cem\u003eTrans\u003c/em\u003e-11 C18:1 showed a low to high correlation with C8:0 to C14:0. \u003cem\u003eCis\u003c/em\u003e-9 C18:1 showed a moderate positive correlation with C4:0, and a moderate to high negative correlation with C12:0 to C16:0. \u003cem\u003eCis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e-11 CLA showed a moderate negative genetic correlation with C4:0 to C14:0, and a positive correlation with \u003cem\u003ecis\u003c/em\u003e-9 C18:1.\u003c/p\u003e \u003cp\u003eIn both breeds, C8:0 to C14:0 showed high and moderate positive genetic correlations with C18:0 and \u003cem\u003etrans\u003c/em\u003e-11 C18:1. Otherwise, the pattern of genetic correlations between C16:0 and the other FAs differed between breeds. Regardless of the breed, when the correlations were non-zero, LCFAs generally correlated negatively with SCFAs and MCFAs.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eTo our knowledge, no studies have examined genetic parameters of milk FA composition in Zebu cattle (\u003cem\u003eBos indicus\u003c/em\u003e). Therefore, this study can be considered the first to undertake quantitative genetic analyses of FA profiles in Zebu cattle. Some studies have demonstrated the ability of Zebu cattle to produce milk with a higher fat content, with levels even above those found in some taurine breeds (\u003cem\u003eBos taurus\u003c/em\u003e; Sharma et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Acosta-Balcazar et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), which could also occur with the FA levels in Zebu milk fat (Samkov\u0026aacute; et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). In general, the milk FA profiles of Gir and Guzer\u0026aacute; cows were similar to those described for \u003cem\u003eBos indicus\u003c/em\u003e and \u003cem\u003eBos taurus\u003c/em\u003e breeds in studies that expressed the FA profile in g/100 g of fat (Pegolo et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Acosta-Balcazar et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Matosinho et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Silva et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRegardless of the breed, FAs considered bioactive, such as \u003cem\u003ecis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e-11 CLA (Gir\u0026thinsp;=\u0026thinsp;0.77\u0026thinsp;\u0026plusmn;\u0026thinsp;0.30 g/100 g of total FA; Guzer\u0026aacute; = 0.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.40 g/100 g of total FA), \u003cem\u003etrans\u003c/em\u003e-11 C18:1 (Gir\u0026thinsp;=\u0026thinsp;1.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.60 g/100 g of total FA; Guzer\u0026aacute; = 1.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.90 g/100 g of total FA), and the ω-3 class (Gir\u0026thinsp;=\u0026thinsp;0.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10 g/100 g of total FA; Guzer\u0026aacute; = 0.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11 g/100 g of total FA) showed slightly higher concentrations than those observed in the Brown Swiss breed (\u003cem\u003ecis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e-11 CLA\u0026thinsp;=\u0026thinsp;0.65 g/100 g of total FA; \u003cem\u003etrans\u003c/em\u003e-11 C18:1\u0026thinsp;=\u0026thinsp;1.20 g/100 g of total FA; Pegolo et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) and the synthetic Girolando breed (\u003cem\u003ecis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e-11 CLA\u0026thinsp;=\u0026thinsp;0.75; \u003cem\u003etrans\u003c/em\u003e-11 C18:1\u0026thinsp;=\u0026thinsp;1.34; ω-3\u0026thinsp;=\u0026thinsp;0.16; Silva et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). While the concentrations found for these FAs in our study were \u0026lt;\u0026thinsp;2 g /100 g of total FA, these contents can have a significant biological impact on human health (Kratz et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe average concentrations of C18:0 and \u003cem\u003ecis\u003c/em\u003e-9 C18:1 FA observed in our study were slightly higher than those observed by Silva et al. (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) when evaluating the milk FA profile of Girolando cows at 90\u0026thinsp;\u0026plusmn;\u0026thinsp;15 DIM Many factors could explain the observed differences, including lactation stage, breed, and, most importantly, the diet. The higher concentrations of C18:0 and \u003cem\u003ecis\u003c/em\u003e-9 C18:1 in Zebu milk fat may be attributed to milk sampling around the peak of lactation, when the maximum gene expression is expected and, thus, the maximum phenotypic expression. Moreover, during this period, cows may also experience a negative energy balance (Acosta-Balcazar et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), which would increase body fat mobilization, incorporating more C18:0 and \u003cem\u003ecis\u003c/em\u003e-9 C18:1 into the milk fat, since they are the main FAs stored in adipose tissue (Narayana et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Rodr\u0026iacute;guez-Berm\u0026uacute;dez et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Another possible explanation is related to the diet provided to both the Gir and Guzer\u0026aacute; cows, since 50.62% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;286) received a diet based on tropical pasture, of which 42.10% (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;129) also received a lipid concentrate. This finding is consistent with studies that showed that cows grazing pasture supplemented with lipid sources produce milk with higher LCFA and UFA concentrations, increasing the biological and nutritional value of the milk (Renn\u0026oacute; et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Corazzin et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Samkov\u0026aacute; et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Plata-P\u0026eacute;rez et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eJointly considering the results of scientific reviews by Arnould and Soyeurt (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) and Samkov\u0026aacute; et al. (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) and a meta-analysis by Hossein-Zadeh (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), it can be considered that there is no consensus on the fact that heritability estimates of FAs are higher when expressed in g/100 g of milk than other concentration units. However, while the concentrations were expressed in g/100 g of total FA, the heritabilities estimated in our study were higher than those obtained by Penasa et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), Bobbo et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), and Klein et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), who expressed the FA profile in g/100 g of milk.\u003c/p\u003e \u003cp\u003eComparing the results on milk FA across different studies is difficult due to differences in interspecific diversity, database structure, sample size, experiments design and precision, laboratory analysis methods (gas chromatography or mid-infrared spectroscopy), concentration units (g/100 g of fat, g/100 dL or 100 g of milk, or g/100 g of total FA), and statistical models (Fleming et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Lopez-Villalobos et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Hossein-Zadeh \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), which lead to wide variation in the reported heritability estimates.\u003c/p\u003e \u003cp\u003eOur study observed a wider CI, potentially reflecting the database structure, as there were a limited number of cows with milk FA profiles for both breeds (Gir\u0026thinsp;=\u0026thinsp;299, Guzer\u0026aacute; = 266). Studies that used more profiles reported narrower CIs (Penasa et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Cecchinato et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRegarding the individual milk FAs, the \u003cem\u003eposterior\u003c/em\u003e means of the heritability estimates are similar in our study to those obtained by Palombo et al. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) for taurine breeds, except for C12:0, which was higher for the Guzer\u0026aacute; breed. When analyzing data from Holstein \u0026times; Jersey crossbred cows, Lopez-Villalobos et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) found heritability estimates similar to those obtained in our study with the Guzer\u0026aacute; breed for C16:0; \u003cem\u003ecis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e-11 CLA; PUFA; and LCFA, and the Gir breed for C8:0, C10:0, and C12:0.\u003c/p\u003e \u003cp\u003eAccording to Fleming et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), SCFAs and MCFAs synthesized \u003cem\u003ede novo\u003c/em\u003e in the mammary gland present higher heritability estimates than LCFAs, as these are mainly derived from the diet, biohydrogenation in the rumen, and mobilization from adipose tissue (Bastin et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). However, in our study, the \u003cem\u003eposterior\u003c/em\u003e heritability estimates were similar for these groups in the two breeds. The heritability estimates found for LCFAs indicate the existence of genetic variability underlying the process of incorporating these FAs into the milk (Bastin et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSFAs were expected to show greater heritability than UFAs (Penasa et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Lopez-Villalobos et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Biologically, this difference can be explained by the fact that most FAs synthesized \u003cem\u003ede novo\u003c/em\u003e in the mammary gland are SFAs (Chilliard et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). In our study, contrary to what was found by Penasa et al. (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and Lopez-Villalobos et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), UFAs showed similar heritability estimates to SFAs. One possible explanation for these unexpected results could be that the individual milk samples were taken at a fixed moment during lactation (around the peak), while the other studies collected several samples during the entire or partial period of lactation (Bilal et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Hein et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The period around the peak of lactation was chosen for sampling the milk FA profile because it is assumed that the phenotypic expression of these traits would be greatest during this period (Bionaz and Loor \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOBCFAs in milk fat primarily originate from the cell wall of rumen bacteria (Ponnampalam et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Carta et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Ponnampalam et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Therefore, they are expected to be under less genetic control, leading to lower heritability (Dias et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Evaluating taurine breeds, Palombo et al. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) found heritability estimates similar to those obtained in our study for OLCFAs and OBCFAs in the Guzer\u0026aacute; breed and lower than those found in the Gir breed for OLCFAs and the ω-6 \u003cem\u003ecis\u003c/em\u003e group.\u003c/p\u003e \u003cp\u003eOur study also examined the unsaturation indices of the four main SCD1 product/substrate FA pairs (C14:0/\u003cem\u003ecis\u003c/em\u003e-9 C14:1, C16:0/\u003cem\u003ecis\u003c/em\u003e-9 C16:1, C18:0/\u003cem\u003ecis\u003c/em\u003e-9 C18:1, and \u003cem\u003etrans\u003c/em\u003e-11 C18:1/\u003cem\u003ecis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e-11 CLA) and the TUI encompassing all these pairs. Since these pairs were studied to assess SCD1 activity in the mammary gland, the C14:1 index was expected to show greater heritability than the other unsaturation indices because, unlike the FAs included in those indexes, C14:0 is almost entirely synthesized \u003cem\u003ede novo\u003c/em\u003e in the mammary gland and, thus, all \u003cem\u003ecis\u003c/em\u003e-9 C14:1 is produced by SCD1 (Stoop et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Bilal et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Pegolo et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). However, in our study, the heritability estimates obtained for the unsaturation indices were similar, regardless of the breed. In both breeds, the heritabilities for the TUI were similar to those obtained by Schennink et al. (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) and Bilal et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The moderate to high heritabilities for the unsaturation indices suggest that they can be altered through genetic selection (\u003cem\u003eh\u003c/em\u003e\u0026sup2;: low, \u0026lt;\u0026thinsp;0.1; moderate, 0.1\u0026ndash;0.3; high, \u0026gt;\u0026thinsp;0.3).\u003c/p\u003e \u003cp\u003eMost of the individual FAs, FA groups, or indices evaluated in our study generally showed moderate to high heritability estimates, indicating that direct genetic selection can effectively alter the milk FA composition to obtain milk with a better nutritional profile for human health. The genetic correlation between milk fat FAs refers to the degree to which the same gene pool influences the presence and proportions of the different FAs. Figures\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e show that the correlations behaved differently in the two breeds, which can be explained by differences in their evolutionary histories and artificial selection intensities.\u003c/p\u003e \u003cp\u003eThe correlations between MY305 and C8:0, C10:0, C12:0, and C14:0 content (in g/100 g of total FA) were negative for the Guzer\u0026aacute; breed (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Bastin et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) and Bobbo et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) observed a similar pattern in taurine breeds, although they expressed FA concentrations in g/dL and g/100 g of milk and took measurements throughout the lactation period. These results reinforce the antagonistic action of proteins involved in synthesizing certain FAs in fat milk, especially SCFAs, which are substrates for the others.\u003c/p\u003e \u003cp\u003eIn the Gir breed, although weak, FY305 correlated positively with C16:0 (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Therefore, these traits share the positive effects of the same gene pool, and selection for increasing MY305 would improve the C16:0 milk fat concentration. As C16:0 is associated with adverse effects on cardiovascular risk indicators, increasing its concentration in milk fat would be undesirable (Hanuš et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The complexity involving genetic correlations among milk traits represents a challenge for setting breeding goals in dairy cattle (Bilal et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eSoyeurt et al. (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) stated that since genetic correlations reflect the physiological processes involved in synthesizing FAs in milk fat, they can be interpreted from a biological perspective. Due to the different origins of FAs in milk fat, the genetic correlations generally showed different directions when preformed FAs (originating from diet, ruminal biohydrogenation, and mobilization of body reserves) were correlated to those synthesized \u003cem\u003ede novo\u003c/em\u003e in the mammary gland (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). An example is the C8:0, which showed a positive correlation with the other \u003cem\u003ede novo\u003c/em\u003e synthesized FAs (C10:0, C12:0 and C14:0) in both breeds, and a negative correlation with \u003cem\u003ecis\u003c/em\u003e-9 C18:1 and \u003cem\u003ecis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e-11 CLA in the Gir breed, and with \u003cem\u003etrans\u003c/em\u003e-11 C18:1 and \u003cem\u003ecis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e-11 CLA in the Guzer\u0026aacute; breed, both of which come partly from the bloodstream. These results suggest that selection can be based on only one FA representative of the \u003cem\u003ede novo\u003c/em\u003e synthesized or preformed FA group. Therefore, selection for a lower concentration of a single FA could increase the concentration of certain FAs in milk fat, improving the nutritional composition of the milk fat.\u003c/p\u003e \u003cp\u003eIn both breeds (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), C4:0 was negatively correlated with SCFAs and MCFAs (C10:0, C12:0, and C14:0 [except for the Guzer\u0026aacute; breed]), and positively correlated with LCFAs (C18:0 and \u003cem\u003ecis\u003c/em\u003e-9 C18:1 [for the Guzer\u0026aacute; breed] and \u003cem\u003etrans\u003c/em\u003e-11 C18:1 [for the Gir breed]). This pattern can be explained by not all C4:0 being synthesized d\u003cem\u003ee novo\u003c/em\u003e in the mammary gland, with some incorporated from the bloodstream. Therefore, when there is a higher concentration of FAs, it can suppress the expression of key proteins involved in \u003cem\u003ede novo\u003c/em\u003e synthesis, such as acetyl-CoA carboxylase alpha (ACACα) and fatty acid synthase (FASN), which are central to this metabolic process. Consequently, the concentrations of C4:0 in milk fat will be higher because this FA has not been used as a substrate in \u003cem\u003ede novo\u003c/em\u003e FA synthesis (Bionaz and Loor \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Stoop et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Qui et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Dan et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAccording to Mu et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), ruminant milk fat synthesis is complex and dynamic, as it involves many key enzymes, proteins, and regulatory factors. The final product of the \u003cem\u003ede novo\u003c/em\u003e synthesis cycle is C16:0. However, during the finishing process, intermediate SCFAs and MCFAs are formed and included in the milk fat (Knutsen et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), potentially explaining the high genetic correlations observed between C8:0 and C14:0 in the Gir (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.72) and Guzer\u0026aacute; (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.93) breeds. Therefore, most proteins influencing C8:0 production also influence C14:0 production because they are part of the same metabolic pathway (Buitenhuis et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Knutsen et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe genetic correlation between \u003cem\u003ecis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e-11 CLA and \u003cem\u003etrans\u003c/em\u003e-11 C18:1 was strong and positive in the Gir breed (0.90; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Prado et al. (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) reported that most (86.8% \u0026plusmn; 2.8%) of the \u003cem\u003ecis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e-11 CLA in milk is produced predominantly from its precursor \u003cem\u003etrans\u003c/em\u003e-11 C18:1 in the mammary gland through desaturation mediated by SCD1, explaining our results. In the Guzer\u0026aacute; breed, \u003cem\u003ecis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e-11 CLA showed a moderate and positive genetic correlation with \u003cem\u003ecis\u003c/em\u003e-9 C18:1 (0.68; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), similar to that described by Bilal et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) in Canadian Holstein cows (0.62). This correlation reflects, in part, the common origin of these two FAs, which are synthetized in the mammary gland by converting \u003cem\u003ecis\u003c/em\u003e-9 C18:0 into C18:1, and \u003cem\u003etrans\u003c/em\u003e-11 C18:1 into \u003cem\u003ecis\u003c/em\u003e-9, \u003cem\u003etrans\u003c/em\u003e-11 CLA by the action of SCD1 (Prado et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe moderate to high heritability estimates observed in our study indicate that the milk FA profile of Gir and Guzer\u0026aacute; cows can be improved through selective breeding, with potential beneficial effects on human health. The genetic correlations between the FAs were moderate to high, depending on whether or not they had a common origin, were \u003cem\u003ede novo\u003c/em\u003e synthesized, or preformed. Since the genetic correlations of MY305 and FY305 with individual FAs in the Gir breed were mainly not different from zero, direct selection for MY305 or FY305 does not affect the FA profile of milk fat in these populations, except for rumenic, butyric, and palmitic acids. In the Guzer\u0026aacute; breed, the estimated genetic correlations indicate that an increase in milk or fat production can negatively affect the composition of SCFAs and MCFAs.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp;\u003c/strong\u003eThe authors are grateful to the technician Hernani Guilherme Barbosa Filho, who analyzed the milk fatty acid composition at the Laboratory of Chromatography of Embrapa Dairy Cattle. \u0026nbsp;We also acknowledge CBMG2 and ABCGIL for data cession. We are thankful for the financial support provided by FAPEMIG, CAPES and CNPq.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u0026nbsp;\u003c/strong\u003eThe experimental design was developed by Maria Gabriela Campolina Diniz Peixoto,\u0026nbsp;Marco Sundfeld da Gama, Maria Raquel Santos Carvalho, and Fernando C\u0026eacute;sar Ferraz Lopes. Sample collection and data generation were carried out by Maria Gabriela Campolina Diniz Peixoto, Paulo S\u0026aacute;vio Lopes, Maria Raquel Santos Carvalho, Marco Sundfeld da Gama, Frank Angelo Tomita Bruneli,\u0026nbsp;Fernando C\u0026eacute;sar Ferraz Lopes, and An\u0026iacute;bal Eug\u0026ecirc;nio Vercesi Filho. Data analysis was performed by Alvimara Felix dos Reis, Paulo S\u0026aacute;vio Lopes, Renata Veroneze, Eula Regina Carrara, Maria Gabriela Campolina Diniz Peixoto,\u0026nbsp;Pablo Augusto de Souza Fonseca, and\u0026nbsp;Maria Raquel Santos Carvalho. All authors participated in the discussion of the results. The first draft of the manuscript was written by Alvimara Felix dos Reis and revised by Paulo S\u0026aacute;vio Lopes and Maria Gabriela Campolina Diniz Peixoto. After\u0026nbsp;that, all authors commented on the last version of the manuscript. All authors read and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e This study was financed by Funda\u0026ccedil;\u0026atilde;o de Amparo \u0026agrave; Pesquisa do Estado de Minas Gerais (Fapemig) \u0026ndash; project CVZ APQ 02003-15 and received a PhD grant from a Coordena\u0026ccedil;\u0026atilde;o de Aperfei\u0026ccedil;oamento de Pessoal de N\u0026iacute;vel Superior (CAPES), e ao Conselho Nacional de Desenvolvimento Cient\u0026iacute;fico e Tecnol\u0026oacute;gico (CNPq), pela consess\u0026atilde;o da bolsa de estudos. O presente trabalho foi realizado com apoio da Coordena\u0026ccedil;\u0026atilde;o de Aperfei\u0026ccedil;oamento de Pessoal de N\u0026iacute;vel Superior \u0026ndash; Brasil (CAPES) \u0026ndash; C\u0026oacute;digo de Financiamento 001.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData avallabillity\u0026nbsp;\u003c/strong\u003eThe datasets generated and/or analyzed during the current study are not publicly available as they are part of ongoing research and part of them belongs to the breeders, but they can be obtained from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u0026nbsp;\u003c/strong\u003e The authors claim that there are no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatement of animal rights\u0026nbsp;\u003c/strong\u003eThis project was approved by the Ethics Committee of Embrapa Dairy Cattle (protocol number CEUA No. 11/2015).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbdoul-Aziz SKA, Zhang YE, Wang J (2021). 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J Dairy Sci (91):385-394. https://doi.org/10.3168/jds.2007-0181. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Heritability estimates, Lipid metabolism, Multivariate analysis, Nutritional quality, Unsaturation index, Zebu breeds","lastPublishedDoi":"10.21203/rs.3.rs-6843607/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6843607/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eStudies with taurine breeds indicate that genetic selection can improve the fatty acid (FA) composition of bovine milk. This study aimed to estimate genetic parameters for FA concentrations and unsaturation indexes in milk fat from Zebu cows and evaluate their potential as selection criteria to enhance milk fat nutritional quality. Milk samples from 299 Gir and 266 Guzer\u0026aacute; cows across 22 herds were analyzed by gas chromatography. Fourteen individual FAs, 11 FA groups, four nutritional quality indexes, and five unsaturation indexes were selected. Tri-trait Bayesian models were used to estimate (co)variance components, using 305-day milk yield and fat yield as anchor traits. The models included fixed effects such as contemporary group, age at calving, diet category, age class at sampling, and days in milk. Most individual FAs were present at concentrations\u0026thinsp;\u0026lt;\u0026thinsp;4 g/100 g of total FA, with palmitic acid being the most abundant, followed by oleic acid, stearic acid, and myristic acid. Heritability estimates ranged from 0.28 to 0.63 for individual FAs, 0.32 to 0.66 for FA groups, and 0.38 to 0.57 for unsaturation indexes in the Gir breed, and from 0.24 to 0.75, 0.26 to 0.65, and 0.50 to 0.68 in the Guzer\u0026aacute; breed, respectively. Genetic correlations were generally moderate to high, with long-chain FAs negatively correlated with short- and medium-chain FAs. These findings support the feasibility of selecting Gir and Guzer\u0026aacute; cows to genetically improve milk FA profiles and increase the proportion of health-promoting FAs in milk fat.\u003c/p\u003e","manuscriptTitle":"Genetic parameters for milk fatty acid profiles in Gir and Guzerá cows using a Bayesian approach","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-18 11:34:26","doi":"10.21203/rs.3.rs-6843607/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fd678b43-d298-4ba6-9f03-7535693c9d1b","owner":[],"postedDate":"June 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-09T09:44:09+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-18 11:34:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6843607","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6843607","identity":"rs-6843607","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}