Murciano-Granadina Goat: A Spanish Local Breed Ready for the Challenges of the Twenty-First Century

Delgado, Juan Vicente; Landi, Vincenzo; Barba, C.; Fernández, J. F.; Gómez, Mayra; Camacho, M. E.; Martínez, Mercedes; Navas, Francisco Javier; León, José M.

doi:10.1007/978-3-319-71294-9_15

Cited by 27 publications

(50 citation statements)

References 13 publications

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“…The productive management of Murciano-Granadina, as a polyestric breed is characterized by two annual kidding periods, with lactations lasting longer than 210-240 days [1]. Milk yield and components were estimated until 210 days of lactation and expressed in Kg [12].…”

Section: Milk Yield Standardization and Composition Analysismentioning

confidence: 99%

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Integrating Casein Complex SNPs Additive, Dominance and Epistatic Effects on Genetic Parameters and Breeding Values Estimation for Murciano-Granadina Goat Milk Yield and Components

Inostroza

Landi

González

et al. 2020

Genes

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Assessing dominance and additive effects of casein complex single-nucleotide polymorphisms (SNPs) (αS1, αS2, β, and κ casein), and their epistatic relationships may maximize our knowledge on the genetic regulation of profitable traits. Contextually, new genomic selection perspectives may translate this higher efficiency into higher accuracies for milk yield and components’ genetic parameters and breeding values. A total of 2594 lactation records were collected from 159 Murciano-Granadina goats (2005–2018), genotyped for 48 casein loci-located SNPs. Bonferroni-corrected nonparametric tests, categorical principal component analysis (CATPCA), and nonlinear canonical correlations were performed to quantify additive, dominance, and interSNP epistatic effects and evaluate the outcomes of their inclusion in quantitative and qualitative milk production traits’ genetic models (yield, protein, fat, solids, and lactose contents and somatic cells count). Milk yield, lactose, and somatic cell count heritabilities increased considerably when the model including genetic effects was considered (0.46, 0.30, 0.43, respectively). Components standard prediction errors decreased, and accuracies and reliabilities increased when genetic effects were considered. Conclusively, including genetic effects and relationships among these heritable biomarkers may improve model efficiency, genetic parameters, and breeding values for milk yield and composition, optimizing selection practices profitability for components whose technological application may be especially relevant for the cheese-making dairy sector.

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Section: Milk Yield Standardization and Composition Analysismentioning

confidence: 99%

“…The Murciano-Granadina goat is one of the main dairy goat breeds in Spain. This special relevance has been achieved through its census, geographical distribution, and its milk quality and production, which on the whole, is well-suited for the dairy industry [1].…”

Section: Introductionmentioning

confidence: 99%

Integrating Casein Complex SNPs Additive, Dominance and Epistatic Effects on Genetic Parameters and Breeding Values Estimation for Murciano-Granadina Goat Milk Yield and Components

Inostroza

Landi

González

et al. 2020

Genes

Self Cite

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“…A more detailed description of breed as handling, feeding practices, level drying off goats, body conformation, milk production and quality, seminal doses, etc. is given in Delgado et al (2017), Ministry of Agriculture, Fisheries and Food of Spain and MURCIGRAN, where the last institutions have updated web pages daily providing official data.…”

Section: Datamentioning

confidence: 99%

“…The Murciano-Granadina (MG) is the most important dairy goat breed of Spain, both in census and in production (Delgado et al 2017). In addition to being very widespread throughout the Spanish territory, currently, herds of the MG are found in several countries in Europe, Africa and the Americas, representing an international repercussion.…”

Section: Introductionmentioning

confidence: 99%

“…The MG is a permanent polyestric breed with high prolificacy (two or more kids/parturition in multiparous females) having an average of 6 lactations, with mean productions of up to 584 L of milk per lactation, dairy yields of between 3 and 4 L in 24 h, also highlighting its high fat content (5.3%) and protein (3.6%) (Delgado et al 2017), and its production is destined almost entirely to the cheese industry.…”

Section: Introductionmentioning

confidence: 99%

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Use of Spline function for the characterisation on peak yield, peak day and persistency in lactation curves in Murciano-Granadina goats

Alejo

León-Jurado

Pieramati

et al. 2019

Italian Journal of Animal Science

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The objective of this study was to characterise the peak yield (PY), peak day (PD) and the persistency (P) of the lactation curve of Murciano-Granadina goats by Spline considering the variation factors (region, type of kidding, lactation number and season) and their levels. A total of 1,349,347 test-day records from 180,872 lactations, of 85,404 goats were used. The analysed data with Spline model was considered for adequate fit in lactation curves for others traits in these goats. All factors affected the scale and/or shape of the lactation curve. In the region factor, significant differences (SD, p < .05) were observed in terms of the total milk yield (TY), final persistency (FP) and total persistency (TP) variables in favour of Almeria versus Cordoba and Granada; the PD variables, PY and initial persistency (IP) did not show SD (NSD, p > .05) between regions. The type of kidding presented SD among its levels (evident between double versus single and triple) with the exception of the PY. The lactation number for the variables of PD, PY and TY from second to fifth lactation showed NSD among themselves; but it did in the case of the first. The P of first lactation was longer, with a decrease in subsequent lactations. In the season factor, PD, TY and P presented SD; where the PD was divided into two groups: late group (winter-spring) and early group (fall-winter). The P, PY and PD can be considered as an additional selection criterion and thus modify the lactation curve. HIGHLIGHTSThe biomodeling of individualized lactation curves is an important information resource for farmers and their breeding program. A conglomerate of microeffects such us climate, photoperiod, agroecological aspects, affect parameters of the lactation curve and their productions. It is preferable to achieve lactations with more emphasis on persistency in order to provide animal welfare and obtain adequate economic benefits. ARTICLE HISTORY

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Bayesian evaluation of the effect of non-genetic factors on the phenomics for quality-related milk nutrients and yield in Murciano-Granadina goats

Inostroza

González

Jurado³

et al. 2022

Trop Anim Health Prod

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Murciano-Granadina Goat: A Spanish Local Breed Ready for the Challenges of the Twenty-First Century

Cited by 27 publications

References 13 publications

Integrating Casein Complex SNPs Additive, Dominance and Epistatic Effects on Genetic Parameters and Breeding Values Estimation for Murciano-Granadina Goat Milk Yield and Components

Integrating Casein Complex SNPs Additive, Dominance and Epistatic Effects on Genetic Parameters and Breeding Values Estimation for Murciano-Granadina Goat Milk Yield and Components

Use of Spline function for the characterisation on peak yield, peak day and persistency in lactation curves in Murciano-Granadina goats

Bayesian evaluation of the effect of non-genetic factors on the phenomics for quality-related milk nutrients and yield in Murciano-Granadina goats

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