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Pereira, D.

Publications and source records attributed to Pereira, D..

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Processing cookies formulated with goat cream enriched with conjugated linoleic acid

Goat fat is one of the most important sources of conjugated linoleic acid (CLA), a fatty acid which has health benefits. However, CLA consumption is limited to meats and milk products as CLA is generated in ruminants. This study aimed to replace vegetable fat by goat cream enriched with CLA. Four cookie recipes were developed with only the fat source being different: CVF - vegetable fat; CB - butter; CGC - goat cream without CLA; CGCLA - goat cream with CLA. Cookies were evaluated according to physical (color and texture) and physical-chemical parameters (lipids, proteins, total sugars, fiber, ash, moisture and Aw), Consumer Testing (n = 123) and lipid profile. The CGCLA presented higher values in the color parameters, and the higher and the lower scores in relation to hardness were 5.54 (CB) and 2.21 (CVF), respectively. Lipids and total sugars varied inversely, and the highest percentages of lipids were in the CVF and CG samples, which obtained lower total sugar content. There was no difference in the acceptance and preference of the four formulations, and the formulations with the goat creams (CG and CGCLA) were as accepted as CFV. The lipid profile of the cookies presented CFV with the highest percentage of trans fatty acids (TFA) with 16.76 %. CGCLA presented 70 % more CLA in relation to CB and CGC, thus certifying that CLA was present in relevant quantities in the CGCLA, even after cooking. The CGCLA is a biscuit with higher levels of CLA, and in this study it was possible to verify that the goat milk cream enriched with CLA can be used in producing cookies which adds functional and nutritional properties to them and offers other alternatives to produce food from goat's milk cream.

biochemistry

Precision phenotyping reveals novel loci for quantitative resistance to septoria tritici blotch in European winter wheat

O_LIAccurate, high-throughput phenotyping for quantitative traits is the limiting factor for progress in plant breeding. We developed automated image analysis to measure quantitative resistance to septoria tritici blotch (STB), a globally important wheat disease, enabling identification of small chromosome intervals containing plausible candidate genes for STB resistance.\nC_LIO_LI335 winter wheat cultivars were included in a replicated field experiment that experienced natural epidemic development by a highly diverse but fungicide-resistant pathogen population. More than 5.4 million automatically generated phenotypes were associated with 13,648 SNP markers to perform a GWAS.\nC_LIO_LIWe identified 26 chromosome intervals explaining 1.9-10.6% of the variance associated with four resistance traits. Seventeen of the intervals were less than 5 Mbp in size and encoded only 173 genes, including many genes associated with disease resistance. Five intervals contained four or fewer genes, providing high priority targets for functional validation. Ten chromosome intervals were not previously associated with STB resistance.\nC_LIO_LIOur experiment illustrates how high-throughput automated phenotyping can accelerate breeding for quantitative disease resistance. The SNP markers associated with these chromosome intervals can be used to recombine different forms of quantitative STB resistance that are likely to be more durable than pyramids of major resistance genes.\nC_LI

plant biology