Publications by authors named "Luis F de la Fuente"

Hormonal treatments used in the artificial insemination (AI) of sheep can cause several physiological problems that can affect negatively fertility and animal health; however, AI protocols based on the detection of natural estrus offer a more sustainable option and can achieve high fertility. In this study, an AI protocol at natural estrus in organic sheep was performed. In the first phase (AI protocol development), 125 ewes were exocervically inseminated, and their fertility was assessed based on the following factors: number of AI, physiological state, body condition, estrus detection-AI interval, and vaginal fluids in cervix.

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Background: Single-step genomic best linear unbiased prediction (ssGBLUP) allows the inclusion of information from genotyped and ungenotyped individuals in a single analysis. This avoids the need to genotype all candidates with the potential benefit of reducing overall costs. The aim of this study was to assess the effect of genotyping strategies, the proportion of genotyped candidates and the genotyping criterion to rank candidates to be genotyped, when using ssGBLUP evaluation.

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The effects of some environmental variation factors and the genetic parameters for total milk traits (fat content, protein content, casein content, serum protein content, lactation mean of individual laboratory cheese yield (LILCY), lactation mean of somatic cell count (LSCC), and milk yield) were estimated from the records of 1,111 Churra ewes. Genetic parameters were estimated by multivariate REML. Heritability for fat content was low (0.

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