Genetic background of calcium and phosphorus phases predicted from milk mid-infrared spectra of Holstein cows

Franzoi, Marco; Costa, Angela; Penasa, M.; Marchi, Massimo De

doi:10.1080/1828051x.2021.1912663

Cited by 2 publications

(2 citation statements)

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“…The present study aimed to quantify the extent of genetic variability in detailed milk protein and FAA composition predicted by MIRS in individual cow milk samples. Nowadays, global milk recording programmes rely on infrared tools for determination of fat and protein content of samples intended to herd testing and genetic evaluations (De Marchi et al, 2014; Franzoi et al, 2021). Currently, protein fractions and FAA are not either determined by MIRS on a routine basis or used for within‐country genetic evaluations.…”

Section: Discussionmentioning

confidence: 99%

Breeding for improved protein fractions and free amino acids concentration in bovine milk

Visentin

Berry

Costa

et al. 2022

J Animal Breeding Genetics

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Although most dairy cow breeding objectives include milk protein and fat concentration and yield at the macro-level (Cole & VanRaden, 2018;Miglior et al., 2005), few consider the detailed milk composition. However, detailed milk composition affects the quality of a variety of dairy products that can be manufactured (Bonfatti, Di Martino, et al. 2011;Wedholm et al., 2006). For example, the concentration of casein (CN) in milk has a favourable effect on the quantity of protein transferred from milk into cheese curd. High concentrations of α s1 -casein (α s1 -CN), βcasein (β-CN), κcasein (κ-CN) and βlactoglobulin B (β-LG B) are known to increase cheese yield (Wedholm et al., 2006).Milk rich in FAA tends to present unfavourable cheesemaking characteristics mainly due to protein hydrolysis

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Section: Discussionmentioning

confidence: 99%

Breeding for improved protein fractions and free amino acids concentration in bovine milk

Visentin

Berry

Costa

et al. 2022

J Animal Breeding Genetics

Self Cite

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“…Several studies have pointed out that this technology can be conveniently used to estimate novel phenotypes that are difficult to measure routinely at population scale (Tsenkova et al., 1999). Examples are: milk fatty acid profile (De Marchi et al., 2011; Soyeurt et al., 2006), coagulation properties (Bittante et al., 2012; Bonfatti et al., 2016; Cellesi et al., 2019; Gaspa et al., 2022) and mineral composition (Franzoi et al., 2021; Visentin et al., 2018); diet composition (Klaffenböck et al., 2017) and digestibility (Simoni et al., 2021); dry matter intake and residual feed intake (Lahart et al., 2019; Shetty et al., 2017) energy balance and efficiency (McParland & Berry, 2016); metabolic profile (de Roos et al., 2007; Santschi et al., 2016); methane emissions (Dehareng et al., 2012; Martínez‐Marín et al., 2023; van Gastelen & Dijkstra, 2016). For this reason, in some countries a systematic collection and storage of milk FTIR spectra generated in dairy herd improvement (DHI) programs has started.…”

Section: Introductionmentioning

confidence: 99%

Investigation of phenotypic, genetic and genomic background of Milk spectra in Sarda dairy sheep

Congiu,

Falchi,

Carta

et al. 2023

J Animal Breeding Genetics

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Aim of this study was to analyse the genetic background of milk Fourier transform infrared (FTIR) spectra in dairy sheep. Individual milk FTIR spectra, with 1060 wavenumbers each, were available for 793 adult Sarda breed ewes genotyped at 45,813 SNP. The absorbance values of each wavenumber was analysed using a linear mixed model that included dim class, parity and lambing month as fixed effects and flock‐test date and animal as random effects. The model was applied to estimate variance components and heritability and to perform a genome‐wide association study for each wavenumber. Average h2 of wavenumbers absorbance was 0.13 ± 0.08, with the largest values observed in the regions associated with the characteristic bonds of carbonylic and methylenic groups of milk fat (h2 = 0.57 at 1724–1728 cm−1; and h2 = 0.34 at 2811–2834 cm−1, respectively). The absorbance values of wavenumbers were moderately correlated with the estimated heritabilities. After the Bonferroni correction, a total of nine markers were found to be significantly associated with 32 different wavenumbers. Of particular interest was the SNP s63269.1, mapped on chromosome 2, that was found to be associated with 27 wavenumbers. Genes previously found to be related to traits of interest (e.g. disease resistance, milk yield and quality, cheese firmness) are located close to the significant SNP. As expected, the heritability estimated for the absorbance of each wavenumbers seems to be associated with the related milk components.

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Genetic background of calcium and phosphorus phases predicted from milk mid-infrared spectra of Holstein cows

Abstract: 2021) Genetic background of calcium and phosphorus phases predicted from milk midinfrared spectra of Holstein cows,

Cited by 2 publications

References 20 publications

Breeding for improved protein fractions and free amino acids concentration in bovine milk

Breeding for improved protein fractions and free amino acids concentration in bovine milk

Investigation of phenotypic, genetic and genomic background of Milk spectra in Sarda dairy sheep

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