Journal Articles

Permanent URI for this collectionhttps://mro.massey.ac.nz/handle/10179/7915

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Author: search.filters.author.Lopez-Villalobos NSubject: search.filters.subject.genetic evaluation

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    Estimates of Genetic Parameters for Milk, the Occurrence of and Susceptibility to Clinical Lameness and Claw Disorders in Dairy Goats
    (MDPI (Basel, Switzerland), 2023-04-17) Jaques N; Turner S-A; Vallée E; Heuer C; Lopez-Villalobos N; Davis ME; Bagnicka E
    The New Zealand goat industry accesses niche markets for high-value products, mainly formula for infants and young children. This study aimed to estimate the genetic parameters of occurrence and susceptibility of clinical lameness and selected claw disorders and establish their genetic associations with milk production traits. Information on pedigree, lameness, claw disorders, and milk production was collected on three farms between June 2019 and July 2020. The dataset contained 1637 does from 174 sires and 1231 dams. Estimates of genetic and residual (co)variances, heritabilities, and genetic and phenotypic correlations were obtained with uni- and bi-variate animal models. The models included the fixed effects of farm and parity, deviation from the median kidding date as a covariate, and the random effects of animal and residual error. The heritability (h2) estimates for lameness occurrence and susceptibility were 0.07 and 0.13, respectively. The h2 estimates for claw disorder susceptibilities ranged from 0.02 to 0.23. The genotypic correlations ranged from weak to very strong between lameness and milk production traits (-0.94 to 0.84) and weak to moderate (0.23 to 0.84) between claw disorder and milk production traits.
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    Estimated Breeding Values of Beef Sires Can Predict Performance of Beef-Cross-Dairy Progeny
    (Frontiers Media S.A., 2021-09-30) Martín N; Coleman L; Lopez-Villalobos N; Schreurs N; Morris S; Blair H; McDade J; Back P; Hickson R
    On average, half of the animal’s estimated breeding value (EBV) is passed on to their progeny. However, it is not known how the performance of beef-cross-dairy cattle relates to the EBV of their beef sire. Such information is required to determine the genetic potential of beef sires selected based on existing EBV to be used on dairy cows in New Zealand. This study evaluated the relationship between the EBV of 30 Angus and 34 Hereford sires and the performance of their progeny for birth, growth, and carcass traits, via progeny testing of 975 beef-cross-dairy offspring born to dairy cows and grown on hill country pasture. Overall, BREEDPLAN EBV did predict progeny performance of the beef-cross-dairy cattle from this study. Gestation length and birthweight increased with increasing sire EBV (mean 0.37–0.62days and 0.52–0.64kg, respectively, p<0.05). Age at weaning decreased with increasing sire EBV for liveweight at 200days (0.17–0.21days per extra kilo of sire EBV, p<0.05) but sire EBV for liveweight at 200days had no effect on the liveweight of the progeny at 200days for either breed (p>0.05). Liveweight increased with sire EBV for liveweight at 400, 600, and 800days, by a similar amount for both breeds (between 0.23 and 0.42kg increase in progeny liveweight per extra kilo of sire EBV, p<0.05). The relationships were more inconsistent for carcass traits. For Hereford, carcass weight and eye muscle area increased with increasing sire EBV (0.27kg and 0.70cm2, respectively, p<0.05). For Angus, marble score increased by 0.10 with 1% extra in sire EBV for intramuscular fat (p<0.05). Rib fat depth tended to increase with sire EBV for both breeds (p<0.1). EBV derived from beef-breed data work in dairy-beef systems but maybe slightly less than the expected 0.5units of performance per unit of EBV. New Zealand farmers should consider BREEDPLAN EBV when selecting sires to mate dairy cows or when buying beef-cross-dairy calves for beef production, to ensure the resulting calves are born safely and on time and then grow well to produce carcasses of suitable meat and fat composition.
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    Advantage of including Genomic Information to Predict Breeding Values for Lactation Yields of Milk, Fat, and Protein or Somatic Cell Score in a New Zealand Dairy Goat Herd
    (MDPI (Basel, Switzerland), 2021-01) Scholtens M; Lopez-Villalobos N; Lehnert K; Snell R; Garrick D; Blair HT
    Selection on genomic breeding values (GBVs) is now readily available for ranking candidates in improvement schemes. Our objective was to quantify benefits in terms of accuracy of prediction from including genomic information in the single-trait estimation of breeding values (BVs) for a New Zealand mixed breed dairy goat herd. The dataset comprised phenotypic and pedigree records of 839 does. The phenotypes comprised estimates of 305-day lactation yields of milk, fat, and protein and average somatic cell score from the 2016 production season. Only 388 of the goats were genotyped with a Caprine 50K SNP chip and 41,981 of the single nucleotide polymorphisms (SNPs) passed quality control. Pedigree-based best linear unbiased prediction (PBLUP) was used to obtain across-breed breeding values (EBVs), whereas a single-step BayesC model (ssBC) was used to estimate across-breed GBVs. The average prediction accuracies ranged from 0.20 to 0.22 for EBVs and 0.34 to 0.43 for GBVs. Accuracies of GBVs were up to 103% greater than EBVs. Breed effects were more reliably estimated in the ssBC model compared with the PBLUP model. The greatest benefit of genomic prediction was for individuals with no pedigree or phenotypic records. Including genomic information improved the prediction accuracy of BVs compared with the current pedigree-based BLUP method currently implemented in the New Zealand dairy goat population.