Free-Range Feeding Alters Fatty Acid Composition at the sn-2 Position of Triglycerides and Subcutaneous Fat Physicochemical Properties in Heavy Pigs.

The nutritional value of fat consumption depends on both the fatty acid composition and the positional distribution of fatty acids within the triglyceride molecule. This research studies the effect of feeding with three different diets (4% lard-enriched; 11.5% high-oleic sunflower-enriched; and extensive feeding mainly with acorns) on the composition of fatty acids in the sn-2 position (and sn-1,3) of triglycerides and the textural properties of subcutaneous fat in heavy Iberian pigs (n = 210 castrated males). A moderate dietary enrichment with oleic acid in mixed diets did not alter the regulation of the sn-2 position of triglyceride (69.9% and 13.9% of palmitic and oleic acids, respectively), but the extremely high intake of oleic acid in pigs fed mainly on acorns changed the proportions of palmitic and oleic acids at the sn-2 position in the subcutaneous fat of pigs (55.0% and 27.2%, respectively). Hardness, adhesiveness, cohesiveness, gumminess, and chewiness showed the least values in EXT pigs, and the greatest values in LARD-fed barrows. SUN cohesiveness and gumminess did not differ from those fed LARD. In addition, Iberian pigs raised in free-range conditions had a more favorable nutritional lipid profile for human health compared to pigs fed conventional diets.

Automatic ¹H-NMR Screening of Fatty Acid Composition in Edible Oils.

In this work, we introduce an NMR-based screening method for the fatty acid composition analysis of edible oils. We describe the evaluation and optimization needed for the automated analysis of vegetable oils by low-field NMR to obtain the fatty acid composition (FAC). To achieve this, two scripts, which automatically analyze and interpret the spectral data, were developed. The objective of this work was to drive forward the automated analysis of the FAC by NMR. Due to the fact that this protocol can be carried out at low field and that the complete process from sample preparation to printing the report only takes about 3 min, this approach is promising to become a fundamental technique for high-throughput screening. To demonstrate the applicability of this method, the fatty acid composition of extra virgin olive oils from various Spanish olive varieties (arbequina, cornicabra, hojiblanca, manzanilla, and picual) was determined by ¹H-NMR spectroscopy according to this protocol.

Metabolomics of meat exudate: Its potential to evaluate beef meat conservation and aging.

In this study we analyzed the exudate of beef to evaluate its potential as non invasive sampling for nuclear magnetic resonance (NMR) based metabolomic analysis of meat samples. Exudate, as the natural juice from raw meat, is an easy to obtain matrix that it is usually collected in small amounts in commercial meat packages. Although meat exudate could provide complete and homogeneous metabolic information about the whole meat piece, this sample has been poorly studied. Exudates from 48 beef samples of different breeds, cattle and storage times have been studied by (1)H NMR spectroscopy. The liquid exudate spectra were compared with those obtained by High Resolution Magic Angle Spinning (HRMAS) of the original meat pieces. The close correlation found between both spectra (>95% of coincident peaks in both registers; Spearman correlation coefficient = 0.945) lead us to propose the exudate as an excellent alternative analytical matrix with a view to apply meat metabolomics. 60 metabolites could be identified through the analysis of mono and bidimensional exudate spectra, 23 of them for the first time in NMR meat studies. The application of chemometric tools to analyze exudate dataset has revealed significant metabolite variations associated with meat aging. Hence, NMR based metabolomics have made it possible both to classify meat samples according to their storage time through Principal Component Analysis (PCA), and to predict that storage time through Partial Least Squares (PLS) regression.