Víctor M. Fernández-Cabanás

Near Infrared Spectroscopy (NIRS) for the determination of the milk fat fatty acid profile of goats

Milk fatty acid (FA) composition is important for the goat dairy industry because of its influence on cheese properties and human health. The aim of the present work was to evaluate the feasibility of NIRS reflectance (oven-dried milk using the DESIR method) and transflectance (liquid milk) analysis to predict milk FA profile and groups of fats in milk samples from individual goats. NIRS analysis of milk samples allowed to estimate FA contents and their ratios and indexes in fat with high precision and accuracy. In general, transflectance analysis gave better or similar results than reflectance mode. Interestingly, NIRS analysis allowed direct prediction of the Atherogenicity and Thrombogenicity indexes, which are useful for the interpretation of the nutritional value of goat milk. Therefore, the calibrations obtained in the present work confirm the viability of NIRS as a fast, reliable and effective analytical method to provide nutritional information of milk samples.

Evaluation of Pretreatment Strategies for Near-Infrared Spectroscopy Calibration Development of Unground and Ground Compound Feedingstuffs

Chemometric procedures are usually applied to near-infrared (NIR) spectra in order to obtain prediction models. These procedures include the application of different combinations of spectral mathematical pretreatments for the improvement of calibrations and the selection of the best model on the basis of validation results. In this work, we used an automatic routine to obtain calibrations for unground and ground compound feedingstuffs (N = 354 samples), including 49 combinations of pretreatments (first and second derivatives, an auto scaling procedure, detrending and two versions of multiplicative scatter correction). Calibrations for crude fiber and crude protein were developed without elimination of outliers and with 2 or 9 maximum passes of elimination of outliers. Validation statistics were highly influenced by the pretreatments used, as a combined result of their ability to improve the detection of outliers and the model adjustment. The standard error of prediction (SEP) values ranged from 0.61 to 1.27 for crude protein (CP) and from 0.74 to 1.33 for crude fiber (CF). In spite of the fact that validation statistics did not show a clear distribution pattern, some combinations of pretreatments provided consistently better results.

Pleiotropic effects of the goat prolactin receptor genotype on milk fatty acid composition.

In the lactating mammary gland, prolactin (PRL) stimulates the synthesis of lactose as well as fatty acid uptake, lipogenesis, and triacylglycerol synthesis. Associations between bovine PRL receptor (PRLR) genotype and fat yield have been reported, which illustrates the role of PRL in conveying lipids toward the udder as well as in stimulating their local synthesis during lactation. Conversely, and to the best of our knowledge, the effects of PRLR genotype on milk fatty acid content have not been studied so far in any mammalian species. In this study, we sequenced most of the coding region of the caprine PRLR gene in several individuals from the Malagueña and Murciano-Granadina breeds. This approach allowed us to identify 2 long and short mRNA isoforms, produced by alternative splicing, and 4 single-nucleotide polymorphisms (SNPs), namely, c.177T>C, c.1131G>A, c.1201G>A and c.1355C>T. Two of these SNPs are nonsynonymous and involve G401R (c.1201G>A) and T452I (c.1355C>T) amino acid substitutions in the cytoplasmic domain of PRLR, which plays a fundamental role in signal transduction. Performance of an association analysis with milk composition traits in a Murciano-Granadina goat population revealed highly suggestive effects on palmitoleic acid content, whereas suggestive effects were detected for other fatty acids, such as palmitic and linoleic. These results are consistent with the pleiotropic effects of PRL on mammary gland lipid metabolism and milk composition.

Direct prediction of bioethanol yield in sugar beet pulp using near infrared spectroscopy.

Sugar beets are a raw material for the production of sugar and ethanol. The decision on which end product to pursue could be facilitated by fast and reliable means of predicting the potential ethanol yield from the beets. A Near Infrared (NIR) Spectroscopy-based approach was tested for the direct prediction of the potential bioethanol production from sugar beets. A modified partial least squares (MPLS) regression model was applied to 125 samples, ranging from 21.9 to 31.0 gL(-1) of bioethanol in sugar beet brei. The samples were analyzed in reflectance mode in a Direct Contact Food Analyser (DCFA) FOSS-NIRSystems 6500 monochromator, with standard error of cross validation (SECV), standard error of prediction (SEP), coefficient of determination (r(2)) and coefficient of variation (CV) of 0.51, 0.49, 0.91 and 1.9 gL(-1), respectively. The NIR technique allowed direct prediction of the ethanol yield from sugar beet brei (i.e. the product obtained after sawing beets with a proper machine) in less than 3 min.

Nutritive Evaluation of Olive Tree Leaves by Near-Infrared Spectroscopy: Effect of Soil Contamination and Correction with Spectral Pretreatments

Olive leaves obtained as a byproduct in the Mediterranean region could play an important role in the nutrition of extensive ruminant systems. However, the reported variation in their nutritive value, among other reasons due to discrepancies in mineral content, is considered an important obstacle for their common use. Near-infrared spectroscopy (NIRS) could fulfill the requirements of these productive systems, providing analytical information in a rapid and economic way. In this work, the effect of soil contamination on NIR spectra has been studied, as well as its correction with some of the most commonly used spectral pretreatments (derivatives, multiplicative scatter correction, auto scaling, detrending, and a combination of the last two transforms). Effects were evaluated by visual inspection of the transformed spectra and comparison of the calibration statistics obtained to estimate acid insoluble ash and total ash contents and in vitro pepsin cellulase digestibility of organic and dry matter. The incidence of spectral curvature effects caused by soil contamination that can be conveniently corrected with pretreatments such as derivatives was confirmed.

Genetic variation at the goat hormone-sensitive lipase ( LIPE) gene and its association with milk yield and composition.

Hormone-sensitive lipase (LIPE) plays a fundamental role in the regulation of energy balance by releasing free fatty acids from adipose triacylglycerol stores. These fatty acids can be subsequently transferred to other body compartments to be oxidized or employed in other biochemical reactions. This enzymic function is particularly important in lactating animals because the synthesis of milk components involves the mobilization of lipid depots to satisfy the large energy demands of the mammary gland. In the current study, we partially sequenced the goat LIPE gene in several individuals. In doing so, we identified two synonymous polymorphisms at exons 2 (c.327C>A>T, triallelic polymorphism) and 3 (c.558C>T). Moreover, we found a mis-sense polymorphism at exon 6 (c.1162G>T) that involves an alanine to serine substitution at position 388. Analysis with Polyphen and Panther softwares revealed that this amino acid replacement is expected to be neutral. Performance of an association analysis with a variety of milk traits revealed that goat LIPE genotype has highly suggestive effects on milk yield (P=0.0032) as well as on C18:3 n-6g (P=0.0051), trans-10 cis-12 CLA (P=0.007) and C12:0 (P=0.0084) milk contents. These associations are concordant with the preference of LIPE to selectively mobilize medium-chain and unsaturated fatty acids.

Factors Affecting Rabbit Meat Consumption Among Spanish University Students

This study investigates the rabbit meat consumption patterns among students. Results of the 342 students surveyed at the University of Seville, Spain showed that more men than women consumed rabbit meat. More students consumed wild rabbit meat than farmed rabbit meat. The practice of hunting by students or their relatives, and the raising of rabbits for self-consumption, positively influenced the proportion of students that currently consumed rabbit meat. Most of the students that had eaten rabbit meat before but are currently non-eaters do so because of the meats organoleptic characteristics or from lack of consumption habit.

Polymorphism of the caprine malic enzyme 1 (ME1) gene and its association with milk quality traits in Murciano-Granadina goats

Malic enzyme 1 plays a fundamental role in lipid metabolism because it yields a significant amount of the NADPH necessary for fatty acid biosynthesis. In ruminants, however, its contribution to this biochemical process seems to be less relevant than in other livestock species. In this study, we have partially sequenced the goat ME1 gene with the aim of identifying polymorphic sites. Structural analysis of the goat ME1 amino acid partial sequence evidenced the existence of two dinucleotide-binding motifs, located at positions 158 to 163 (GLGDLG) and 301 to 306 (GAGEAA), and three amino acid residues (E245, D246 and D269) involved in the binding of Mn2+ and strongly conserved among mammalian species. Moreover, multiple sequence alignment allowed us to identify four single nucleotide polymorphisms at exons 5 (c.483C > T), 6 (c.667G > A), 9 (c.927C > T) and 11 (c.1200G > A). The effects of ME1 genotype on milk production and composition traits were investigated in a Murciano-Granadina goat population. None of the associations found reached statistical significance after applying Benjamini-Hochberg correction. At most, associations with uncorrected P-values below 0.01 were observed for C16:0, C18:1n-9t and total conjugated linoleic acids. These negative results reinforce the notion that ME1 plays an ancillary role in ruminant lipogenesis.