Impact of reproductive traits on productive life in Iranian Holstein dairy cows

Enhancing reproductive performance is a key strategy to mitigate involuntary culling rates, thereby extending productive life (PL) and ultimately improving profitability in dairy cattle herds. A piecewise Weibull proportional hazards model was used to investigate the effect of several important reproductive traits on PL in Holstein dairy cows. Data comprised 200,747 lactation records from 82,505 cows sired by 1952 bulls across 36 dairy herds. PL was defined as the number of days from the first calving to the last milk record or censoring. The statistical model accounted for the time-dependent fixed effects of changes in herd size, year-season, milk production, fat and protein contents, and the time-independent fixed effect of age at first calving. Herd-year and sire effects were also included as random effects. Reproductive traits include calving traits such as calving ease (CE), calf size (CZ), and calf survival (CS), as well as female fertility traits such as number of inseminations per conception (NI), days from calving to first service (CFS), days from first service to conception (FSC), and days open (DO). All reproductive traits had a significant effect on PL (p < 0.001). Each reproductive trait was analysed separately. The relative risk (RR) of being culled increased as the severity of calving difficulties increased in both primiparous and multiparous cows. Cows that calved small or large calves showed a higher risk of being culled compared with those that calved medium size calves. The increased RR of culling was observed only for primiparous cows that gave birth to dead calves. In addition, cows that required more NI, a longer CFS, FSC, and DO had shorter longevity. These insights can deepen our comprehension of the factors affecting PL and provide information for refining management and breeding strategies, which could lead to increased profitability and sustainability in Iranian dairy farming.

Genetic parameters for milk yield and reproductive traits in Honduran Holstein cattle

The aim of this study was to estimate the (co)variance components and genetic parameters for milk yield adjusted to 305d (MY305), calving-to-conception interval (CCI), number of services per conception (NSC) and calving interval (CI) of Honduran Holstein cows, by fitting a bivariate animal model using Maximum Restricted Likelihood procedures. Model included the fixed effects of calving number, the contemporary calving group (farm-season-year of calving and the cow age as covariate). The estimated means and standard deviations for MY, CCI, NSC and CI were, 5098.60 ± 1564.32 kg, 168.27 ± 104.71 days, 2.46 ± 1.69 services, and 448.73 ± 109.16 days, respectively; and their estimated heritabilities were 0.21 ± 0.05, 0.03 ± 0.028, 0.02 ± 0.024 and 0.06 ± 0.04, respectively. The genetic correlations between MY305 and CCI, NSC and CI were positive and antagonist, with values of 0.64 ± 0.52, 0.99 ± 0.56, and 0.32 ± 0.24 respectively. Even though moderate to low heritability was estimated for MY305, systematic selection for milk yield, with a reduction in reproductive efficiency, if considered as the only selection criterion is important to be considered. By including reproductive traits and considering permanent environment effects into the breeding program, might yield a slow, but constant and permanent improvement over time.

Optimization of breeding program design through stochastic simulation with kernel regression

In recent years, breeding programs have increased significantly in size and complexity, with various highly interdependent parameters and many contrasting breeding goals. As a result, resource allocation in these programs has become more complex, and deriving an optimal breeding strategy has become increasingly challenging. To address this, a common practice is to reduce the optimization problem to a set of scenarios that differ only in a few parameters and can therefore be analyzed in detail. The goal of this article is to provide a framework for the numerical optimization of breeding programs that goes beyond the simple comparison of scenarios. For this, we first determine the space of potential breeding programs only limited by basic constraints like the budget and housing capacities. Subsequently, the goal is to identify the optimal breeding program by finding the parametrization that maximizes the target function by combining different breeding goals. To assess the value of the target function for a parametrization, we propose using stochastic simulations and the subsequent use of a kernel regression method to cope with the stochasticity of simulation outcomes. This procedure is performed iteratively to narrow down the most promising areas of the search space and perform more and more simulations in these areas of interest. In a simplified example applied to a dairy cattle program, our proposed framework has shown its ability to identify an optimal breeding strategy that aligns with a target function aiming at genetic gain and genetic diversity conservation limited by budget constraints.

Fertility and survival of Swedish Red and White × Holstein crossbred cows and purebred Holstein cows

Swedish Red and White × Holstein (S×H) cows were compared with pure Holstein (HOL) cows for fertility and survival traits in 2 commercial dairy farms in central-southern Córdoba province, Argentina, over 6 years (2008-2013). The following traits were evaluated: first service conception rate (FSCR), overall conception rate (CR), number of services per conception (SC), days open (DO), mortality rate, culling rate, survival to subsequent calvings, and length of productive life (LPL). The data set consisted of 506 lactations from 240 S×H crossbred cows and 1,331 lactations from 576 HOL cows. The FSCR and CR were analyzed using logistic regression, DO and LPL were analyzed using a Cox's proportional hazards regression model, and differences of proportions were calculated for mortality rate, culling rate, and survival to subsequent calvings. The S×H cows were superior to HOL cows in overall lactations for all the fertility traits (+10.5% FSCR, +7.7% CR, -0.5 SC, and 35 fewer DO). During the first lactation, S×H cows were superior to HOL cows for all fertility traits (+12.8% FSCR, +8.0% CR, -0.4 SC, and 34 fewer DO). In the second lactation, S×H cows exhibited lower SC (-0.5) and 21 fewer DO than HOL cows. In the third or greater lactations, S×H cows showed higher FSCR (+11.0%) and CR (+12.2%), lower SC (-0.8), and 44 fewer DO than pure HOL cows. In addition, S×H cows had a lower mortality rate (-4.7%) and a lower culling rate (-13.7%) than HOL cows. Due to the higher fertility and lower mortality and culling rates, the S×H cows had higher survival to the second (+9.2%), third (+16.9%), and fourth (+18.7%) calvings than HOL cows. Because of these results, S×H cows had longer LPL (+10.3 mo) than HOL cows. These results indicate that S×H cows had higher fertility and survival than HOL cows on commercial dairy farms in Argentina.

Grazing season length and stocking rate affect milk production and supplementary feed requirements of spring-calving dairy cows on marginal soils

The objective of this study was to investigate the effect of increasing stocking rate (SR) and extending grazing season (GS) length on pasture and animal productivity on a marginal, poorly draining soil type. The study was a multiyear (2017 to 2020, inclusive) whole farm systems evaluation with a 2 × 2 factorial experimental arrangement of treatments. The systems evaluated comprised 2 GS lengths, average (AGS; 205 d) and extended (EGS; 270 d), and the 2 whole farm stocking rates were medium (2.5 cows/ha) and high (2.9 cows/ha). We used this study design to create 4 grazing system intensities (500, 600, 700, and 800 cow grazing days per hectare per year). In 2017, cows were randomly allocated to 1 of the 4 whole farm systems precalving and remained on the same treatments for the duration of the study. We found no significant differences in total average annual pasture production [14,133 ± 538 kg of dry matter (DM) per hectare] or sward chemical composition between GS and SR treatments over the 4-yr period, with the exception of average crude protein content, which was lower for EGS (211 g/kg DM) compared with AGS (218 g/kg DM). Grazed pasture production was significantly increased in EGS treatments (+758 kg of DM/ha) compared with AGS (9,917 kg of DM/ha), whereas conserved silage DM production was greater for AGS (+716 kg of DM/ha) compared with EGS (3,583 kg of DM/ha). Neither GS nor SR had a significant effect on daily or cumulative lactation milk and fat plus protein production per cow (5,039 and ±440 kg, respectively). Increasing SR resulted in increased milk fat plus protein yield per hectare based on increased grazed pasture utilization. These results add further credence to the important additive contributions of both extended grazing and SR intensification to achieve high levels of grazed pasture utilization and milk production per hectare while reducing supplementary feed requirements within spring-calving grazing systems.

Genetic and nongenetic variation of heifer fertility in Italian Holstein cattle

Excellent fertility performance is important to maximize farmers' profit and to reduce the number of culled animals. Although female fertility of adult cows has been included in Italian Holstein breeding objectives since 2009, little has been done to quantify genetic variation of heifer fertility characteristics so far. The aim of the present study was to estimate genetic parameters of 4 fertility traits in nulliparous Italian Holstein heifers and to develop an aggregate selection index to improve heifer fertility. Data were retrieved from the national fertility database and included information on insemination, calving, and pregnancy diagnosis dates. The investigated phenotypes (mean ± standard deviation) were age at first insemination (AFI, mo; 17.25 ± 2.89), nonreturn rate at 56 d from the first insemination (NRR56, binary; 0.78 ± 0.41), conception rate at first insemination (CR, binary; 0.61 ± 0.49), and interval from first to last insemination (IFL, d; 26.09 ± 51.85). Genetic parameters were estimated using a 4-trait animal model that included the following fixed effects: herd-year of birth and month of birth for AFI, and herd-year-season of birth and month-year of insemination for IFL, NRR56, and CR; the animal additive genetic effect (fitted to the pedigree-based relationship matrix) was considered as a random term. An aggregate index was developed from the estimated additive genetic (co)variance matrix by considering CR as the breeding goal and AFI, NRR56, and IFL as selection criteria. Heritability estimates from average covariance matrices ranged from 0.012 (CR) to 0.015 (IFL), with the exception of AFI (0.071). Conception rate at first insemination was strongly correlated with both IFL (-0.730) and NRR56 (0.668), and weakly to AFI (-0.065), and the relative emphasis placed on each selection criteria in the aggregate index was 10%, 47%, and 43% for AFI, IFL, and NRR56, respectively. The results of the present study suggest that heifer fertility should be considered as an additional trait in the breeding objectives of Italian Holstein.

Potential response from selection schemes based on progeny testing and genomic selection for the Chilean dairy cattle under pastoral systems: a deterministic simulation

Recently, a selection index called Valor Económico Lechero (VEL) was developed for Chilean dairy cattle under pasture. However, a specific selection scheme has not yet been implemented. This study aimed to estimate genetic progress from selection on the VEL selection index based on selection schemes using progeny testing (PT) and genomic selection (GS). Under a PT-scheme, estimated genetic progress was 41.50, 3.44, and 2.33 kg/year for milk, fat, and protein yield, respectively. The realised genetic gain takes eight-year after the PT-scheme implementation, which may be a disincentive for implementing a PT-scheme, suggesting that importing frozen semen of proven bulls could be a preferred alternative. In this case, an option may be to conduct the genetic evaluation of those bulls using their progeny in Chile for the traits included in VEL selection index. In the case of implementing a specific selection scheme, compared to PT, a more profitable alternative might be the implementation of a GS-scheme, that would result in a faster genetic gain in the aggregate breeding value or merit for all the traits included in the selection objective (0.323-0.371 vs. 0.194 σg/year).

Implementation of compact calving at the farm level: A qualitative analysis of farmers operating pasture-based dairy systems in Ireland

Pasture-based dairy systems aim to maximize the proportion of grazed pasture in the cow's diet by having a compact calving season that coincides with the onset of the grass growing season. In Ireland, where pasture-based systems are dominant, a key performance indicator that reflects the degree of compact calving is referred to as 6-wk calving rate (6-wk CR). Although the industry target is 90%, the national average 6-wk CR in Ireland is currently 67%. The aim of this study was to use qualitative research to understand in depth farmers' experiences in implementing a high 6-wk CR. Ten case-study dairy farmers were interviewed using the biographical narrative interpretive method. We identified 5 broad and often interrelated themes evoked by farmers regarding 6-wk CR: the "good" farmer; support networks; free time and family time; simplicity of a structured system; and profitability and monetary gain. The findings of this study identify complexities and challenges at farm level when it comes to increasing 6-wk CR, such as increased workload and challenges associated with large numbers of male calves born during a condensed calving season. Benefits experienced by farmers as a result of increasing 6-wk CR included increased days in milk and consequently improved cash flow as well as increased grass utilization. Our findings are of interest to researchers and extension agents involved in programs concerned with reproductive management in pasture-based dairy systems.

Birth conditions affect the longevity of Holstein offspring

Studies of dairy cow longevity usually focus on the animal life after first calving, with few studies considering early life conditions and their effects on longevity. The objective was to evaluate the effect of birth conditions routinely collected by Dairy Herd Improvement agencies on offspring longevity measured as length of life and length of productive life. Lactanet provided 712,890 records on offspring born in 5,425 Quebec dairy herds between January 1999 and November 2015 for length of life, and 506,066 records on offspring born in 5,089 Quebec dairy herds between January 1999 and December 2013 for length of productive life. Offspring birth conditions used in this study were calving ease (unassisted, pull, surgery, or malpresentation), calf size (small, medium, or large), and twinning (yes or no). Observations were considered censored if the culling reason was "exported," "sold for dairy production," or "rented out" as well as if the animals were not yet culled at the time of data extraction. If offspring were not yet culled when the data were extracted, the last test-day date was considered the censoring date. Conditional inference survival trees were used in this study to analyze the effect of offspring birth conditions on offspring longevity. The hazard ratio of culling between the groups of offspring identified by the survival trees was estimated using a Cox proportional hazard model with herd-year-season as a frailty term. Five offspring groups were identified with different length of life based on their birth condition. Offspring with the highest length of life [median = 3.61 year; median absolute deviation (MAD) = 1.86] were those classified as large or medium birth size and were also the result of an unassisted calving. Small offspring as a result of a twin birth had the lowest length of life (median = 2.20 year; MAD = 1.69) and were 1.52 times more likely to be culled early in life. Six groups were identified with different length of productive life. Offspring that resulted from an unassisted or surgery calving and classified as large or medium when they were born were in the group with the highest length of productive life (median = 2.03 year; MAD = 1.63). Offspring resulting from a malpresentation or pull in a twin birth were in the group with the lowest length of productive life (median = 1.15 year; MAD = 1.11) and were 1.70 times more likely to be culled early in life. In conclusion, birth conditions of calving ease, calf size, and twinning greatly affected offspring longevity, and such information could be used for early selection of replacement candidates.

The effect of Holstein-Friesian, Jersey × Holstein-Friesian, and Norwegian Red × (Jersey × Holstein-Friesian) cows on dry matter intake and production efficiencies in pasture-based systems

The objective of this study was to investigate the effect of cow genotype and parity on dry matter intake (DMI) and production efficiencies in pasture-based systems. Three dairy cow genotypes were evaluated over 3 yr; 40 Holstein-Friesian (HF), 40 Jersey × HF (JEX), and 40 Norwegian Red × JEX (3WAY) each year, with each genotype grazed in equal numbers on 1 of 4 grazing treatments in a 2 × 2 factorial arrangement of treatments [diploid or tetraploid perennial ryegrass (Lolium perenne L.) with or without white clover (Trifolium repens L.)]. A total of 208 individual cows were used during the experiment. The effect of parity (lactation 1, 2, and 3+) was also evaluated. Individual DMI was estimated 8 times during the study, 3 times in 2015 and in 2017, and twice in 2016, using the n-alkane technique. Days in milk at each DMI measurement period were 64, 110, and 189, corresponding to spring, summer, and autumn. Measures of milk production efficiency calculated were total DMI/100 kg of body weight (BW), milk solids (kg fat + protein; MSo)/100 kg of BW, solids-corrected milk (SCM)/100 kg of BW, and unité fourragère lait (net energy requirements for lactation equivalent of 1 kg of standard air-dry barley; UFL) available for standard (4.0% fat and 3.1% protein content) milk production after accounting for maintenance. During the DMI measurement periods HF had a greater milk yield (23.2 kg/cow per d) compared with JEX and 3WAY (22.0 and 21.9 kg/cow per d, respectively) but there was no difference in MSo yield. Holstein-Friesian and JEX, and JEX and 3WAY had similar DMI, but HF had greater total DMI than 3WAY (DMI was 17.2, 17.0, and 16.7 kg/cow per d for HF, JEX, and 3WAY, respectively). Jersey × Holstein-Friesian cows were the most efficient for total DMI/100 kg of BW, SCM/100 kg of BW, and MSo/100 kg of BW (3.63, 4.96, and 0.39 kg/kg of BW) compared with HF (3.36, 4.51, and 0.35 kg/kg of BW) and 3WAY (3.45, 4.63, and 0.37 kg/kg of BW), respectively. Unité fourragère lait available for standard milk production after accounting for maintenance was not different among genotypes. As expected, DMI differed significantly among parities with greater parity cows having higher DMI and subsequently higher milk and MSo yield. Although all 3 genotypes achieved high levels of DMI and production efficiency, JEX achieved the highest production efficiency. Some of the efficiency gains (SCM/100 kg of BW, MSo/100 kg of BW, and total DMI/100 kg of BW) achieved with JEX decreased when the third breed (Norwegian Red) was introduced.

Infrared Spectrometry as a High-Throughput Phenotyping Technology to Predict Complex Traits in Livestock Systems

High-throughput phenotyping technologies are growing in importance in livestock systems due to their ability to generate real-time, non-invasive, and accurate animal-level information. Collecting such individual-level information can generate novel traits and potentially improve animal selection and management decisions in livestock operations. One of the most relevant tools used in the dairy and beef industry to predict complex traits is infrared spectrometry, which is based on the analysis of the interaction between electromagnetic radiation and matter. The infrared electromagnetic radiation spans an enormous range of wavelengths and frequencies known as the electromagnetic spectrum. The spectrum is divided into different regions, with near- and mid-infrared regions being the main spectral regions used in livestock applications. The advantage of using infrared spectrometry includes speed, non-destructive measurement, and great potential for on-line analysis. This paper aims to review the use of mid- and near-infrared spectrometry techniques as tools to predict complex dairy and beef phenotypes, such as milk composition, feed efficiency, methane emission, fertility, energy balance, health status, and meat quality traits. Although several research studies have used these technologies to predict a wide range of phenotypes, most of them are based on Partial Least Squares (PLS) and did not considered other machine learning (ML) techniques to improve prediction quality. Therefore, we will discuss the role of analytical methods employed on spectral data to improve the predictive ability for complex traits in livestock operations. Furthermore, we will discuss different approaches to reduce data dimensionality and the impact of validation strategies on predictive quality.

An assessment of the production, reproduction, and functional traits of Holstein-Friesian, Jersey × Holstein-Friesian, and Norwegian Red × (Jersey × Holstein-Friesian) cows in pasture-based systems

Pasture-based production systems typically require highly fertile, healthy, and robust genetics, with greater emphasis on milk solids (MSo; kg of fat + protein) production as opposed to milk yield. This study assessed milk production, production efficiency, reproductive performance, body weight (BW), body condition score, and functional traits in 3 different dairy cow genotypes: Holstein-Friesian (HF), Jersey × Holstein-Friesian (JEX), and Norwegian Red × (Jersey × Holstein-Friesian) (3-way). The 3 genotypes were rotationally grazed on 4 different grazing treatments after calving in spring and were stocked at a rate of 2.75 cows/ha. Holstein-Friesian cows produced higher daily and total milk yields compared with JEX and 3-way cows (5,718 vs. 5,476 and 5,365 kg/cow, respectively). However, JEX and 3-way cows had higher milk fat and protein contents (4.86 and 4.75%, respectively, for JEX and 3.87 and 3.88%, respectively, for 3-way) compared with HF (4.52 and 3.72%), resulting in similar MSo yield for JEX and HF (469 and 460 kg/cow) and slightly lower MSo yield for 3-way (453 kg/cow) compared with JEX. As parity increased, milk and MSo yield per cow increased. Reproductive performance was not significantly different between the 3 genotypes, which had similar 24-d submission rates, 6-wk pregnancy rates, and overall pregnancy rates over the 4-yr period. No difference in calving difficulty, incidence of mastitis, or incidence of lameness was observed among the 3 genotypes. Body weight was significantly different among all 3 genotypes, with HF being the heaviest followed by 3-way and JEX (530, 499, and 478 kg, respectively), and 3-way cows had a higher body condition score throughout lactation compared with HF and JEX cows. The differences in BW coupled with similar MSo production resulted in JEX cows having the highest production efficiency (4.58 kg of MSo/kg of metabolic BW), 3-way cows being intermediate (4.30 kg of MSo/kg of metabolic BW), and HF cows having the lowest (4.16 kg of MSo/kg of metabolic BW). In conclusion, HF herds with poor reproductive performance and low milk fat and protein contents are likely to benefit considerably from crossbreeding with Jersey, and all herds are likely to benefit in terms of production efficiency. However, where herd performance, particularly in relation to reproductive performance, is comparable with HF in the current study, crossbreeding with Jersey or Norwegian Red is unlikely to lead to significant improvements in overall herd performance.

Towards a better understanding of breeding objectives and production performance of dairy cattle in sub-Saharan Africa: a systematic review and meta-analysis

Abstract

The aim of this study was to examine breeding objectives and the impact of production systems and breed types on dairy cattle performance in sub-Saharan Africa (SSA). A total of 64 research studies published between 1980 and 2018 were used for qualitative analysis (qualitative synthesis) of farmers', scientists' and institutional dairy trait preferences. Meta-analysis was conducted to examine the production and reproduction performance of dairy cattle in smallholder and large-scale dairy production systems. Most data used were from smallholder farmers (60%), with the remainder from large-scale farms. Linear mixed-effect models were used to estimate marginal means of production and reproduction traits for different breed types in both production systems. Overall, the results showed that there was a higher emphasis on breeding for improved fertility, increased milk yield and disease resistance. Milk content (fat and protein percentages), temperament, body conformation and total milk cell count (a mastitis indicator) were rarely mentioned in published literature, mainly because of milk pricing policies being volume based. Frequency and multivariate analyses (cluster data analysis) for desirable animal traits suggested that multiple breeding objectives are needed, based on the perceived goals of different farmers and institutions towards genetic improvement for production, reproduction, disease resistance and functional and animal welfare traits. Regardless of the breed type, commercial large-scale farms had a higher milk yield (2857.0 ± 233.3) compared with smallholder dairy farms (2419.8 ± 617.39). Estimated marginal means for lactation milk yield of the three breed types Holstein-Friesian, non-Holstein-Friesian dairy breeds (Jersey, Guernsey, Red Dane, Brown Swiss and Ayrshire) and cross-breds (Bos taurus x Bos indicus) were 3148.5 ± 433.00, 2995.6 ± 456.36 and 1771.1 ± 328.52, respectively. Significantly shorter age at first calving and shorter calving intervals were observed in large-scale farms in comparison to smallholder farms (p < 0.05). No significant differences were noted for age at first calving, calving interval, days open and number of services per conception between the breed types. In conclusion, the present study suggests that (i) improvement of dairy cattle has focused on reproduction, production and disease resistance traits, reflecting the breeding objectives of farmers, scientists and institutions involved in dairy production; (ii) genetics plays a large role in increased dairy productivity in SSA and (iii) future dairy research should emphasise on the interactions between improved feeding, disease control and genetics at a production level to inform profitable combinations of dairy traits.

Reproductive efficiency and survival of Holstein-Friesian cows of divergent Economic Breeding Index, evaluated under seasonal calving pasture-based management

The objective of the current study was to examine phenotypic fertility performance and survival, and to gain insight into underlying factors that may contribute to greater fertility performance in 2 divergent genetic groups (GG) of Holstein-Friesian, selected using the Irish Economic Breeding Index (EBI). The GG were evaluated across 3 spring calving pasture-based feeding treatments (FT) over 4 yr. The 2 divergent GG were (1) high EBI; representative of the top 5% nationally (elite), and (2) EBI representative of the national average (NA). In each year, 90 elite and 45 NA cows were randomly allocated to 1 of 3 FT: control, lower grass allowance, and high concentrate. No interaction between GG and FT was observed for any of the measures of fertility investigated. The elite cows achieved significantly greater pregnancy rate to first service (+14.9 percentage points), and significantly greater pregnancy rates after 21, 42, and 84 d of breeding (+17.3, +15.2, and +9.6 percentage points, respectively) compared with NA. The number of services per cow was fewer for elite (1.57) compared with NA (1.80). The interval from mating start date to pregnancy was significantly shorter for elite cows compared with NA. The elite cows maintained greater mean body condition score than NA throughout the study (2.91 vs. 2.72), and had greater body condition score at calving, artificial insemination, and drying off compared with NA. The elite cows had greater mean circulating concentrations of insulin-like growth factor-1 compared with NA. No significant effect was observed of GG on commencement of luteal activity, or progesterone profile variables. Greater survival to the start of fifth lactation was observed for elite cows. The elite cows were 43% less likely to be culled than NA by the beginning of the fifth lactation. The results highlight the success of the Economic Breeding Index to deliver reproductive performance and longevity consistent with industry targets across a range of seasonal pasture-based FT. The results also clearly demonstrate the potential of appropriate genetic selection to reverse negative fertility trends incurred during previous decades of selection for milk production alone.

Intake, efficiency, and feeding behavior characteristics of Holstein-Friesian cows of divergent Economic Breeding Index evaluated under contrasting pasture-based feeding treatments

The objective of the current study was to explore differences in dry matter intake, intake capacity, production efficiency, energy balance, and grazing behavior, of 2 divergent genetic groups (GG) of lactating Holstein-Friesian, selected using the Irish Economic Breeding Index (EBI). The GG were evaluated across 3 spring calving pasture-based feeding treatments (FT) over 3 yr. The 2 divergent GG were (1) high EBI, representative of the top 5% nationally (elite), and (2) EBI representative of the national average (NA). In each year 90 elite and 45 NA cows were randomly allocated to 1 of 3 FT: control, lower grass allowance, and high concentrate. Although FT did affect animal performance, there were few notable incidences of GG × FT interaction. The elite cows expressed lower daily milk yield (-1 kg) compared with NA. Elite cows did, however, express higher daily concentrations of milk fat (+3.7 g/kg) and protein (+2.1 g/kg) compared with NA. Daily yield of milk solids and net energy of lactation (NE_L) was similar for both GG. Body weight (BW) was greater for NA (+13 kg) compared with elite, whereas mean body condition score was greater (+0.14) for elite compared with NA. Intake did not differ significantly between GG. Intake capacity, expressed as total dry matter intake/100 kg of BW, was greater with elite compared with NA. Production efficiency expressed as yield of milk solids per 100 kg of BW was greater with elite compared with NA, although milk solids/total dry matter intake did not differ between GG. Expressed as NE_L as a proportion of net energy intake minus net energy of maintenance (NE_L/NE_I - NE_M) and NE_I/milk solids kg, indicated a slight reduction in the utilization of ingested energy for milk production with elite compared with NA. This is, however, suggested as favorable as it manifested as a more positive energy balance with elite compared with NA and so is likely to enhance robustness, increase longevity, and increase overall lifetime efficiency. Noteworthy was a consistent numerical trend toward more intense grazing activity with elite compared with NA cows, exhibited in the numerically greater grazing time (+19 min) and total number of bites per day (+2,591).

Symposium review: Breeding a better cow-Will she be adaptable?

Adaption is a process that makes an individual or population more suited to their environment. Long-term adaptation is predicated on ample usable genetic variation. Evolutionary forces influencing the extent and dynamics of genetic variation in a population include random drift, mutation, recombination, selection, and migration; the relative importance of each differs by population (i.e., drift is likely to be more influential in smaller populations) and number of generations exposed to selection (i.e., mutation is expected to contribute substantially to genetic variability following many generations of selection). The infinitesimal model, which underpins most genetic and genomic evaluations, assumes that each quantitative trait is controlled by an infinitely large number of unlinked and non-epistatic loci, each with an infinitely small effect. Under the infinitesimal model, selection is not expected to noticeably alter the allele frequencies, despite a potential substantial change in the population mean; the exception is in the first few generations of selection when genetic variance is expected to decline, after which it stabilizes. Despite the common use of the heritability statistic in quantitative genetics as a descriptor of adaption or response to selection, it is arguably the coefficient of genetic variation that is more informative to gauge adaptation potential and should, therefore, always be cited in such studies; for example, the heritability of fertility traits in dairy cows is generally low, yet the coefficient of genetic variation for most traits is comparable to many other performance traits, thus supporting the observed rapid genetic gain in fertility performance in dairy populations. Empirical evidence from long-term selection studies, across a range of animal and plant species, fails to support the premise that selection will deplete genetic variability. Even after 100 yr (synonymous with 100 generations) of selection in corn for high protein or oil content, there appears to be no obvious plateauing in the response to selection. Although populations in several selection experiments did reach a selection limit after multiple generations of directional selection, this does not equate to an exhaustion of genetic variance; such a declaration is supported by the observed rapid responses to reverse selection once implemented in long-term selection studies. New technologies such as genome-wide enabled selection and genome editing, as well as having the potential to accelerate genetic gain, could also increase the genetic variation, or at least reduce the erosion of genetic variance over time. In conclusion, there is no evidence, either theoretical or empirical, to indicate that dairy cow breeding programs will be unable to adapt to evolving challenges and opportunities, at least not because of an absence of ample genetic variability.

Justification for setting the individual animal genotype call rate threshold at eighty-five percent

Data quality of SNP arrays impacts the accuracy and precision of downstream data analyses. One such quality control measure often imposed is a threshold on individual animal call rate. Different call rate thresholds have been applied across studies; little is known, however, about the impact of these thresholds on the quality of the genotype data. The objective of the present study was to investigate the effect of different call rate thresholds on the integrity of the genotypes but also to quantify the contribution of different factors to the variability in animal call rate. Data included 142,342 samples genotyped on a custom Illumina genotype panel from 141,591 dairy and beef cattle; the number of Illumina SNP on the panel was 14,371. The mean animal call rate across all samples was 99.09%; 487 animals had both a low call rate (<99%) and a subsequent high call rate (≥99%) after resampling and regenotyping. Several factors were associated ( < 0.001) with individual call rate including animal sex, the sampling herd, the date of genotyping, the genotyping plate, and the plate well. The genotype and allele concordance between the genotypes of the 487 low- and high-call rate individuals improved at a diminishing rate as mean animal call rate increased. Mean genotype and allele concordance rates of 0.987 and 0.997, respectively, existed when animal call rate was between 85 and 90%, increasing to 0.998 and 0.999, respectively, when animal call rate was between 95 and <99%. The mean within-animal allele concordance rate of rare variants (i.e., minor allele frequency < 0.05) between low and high genotype call rate animals increased when animal call rate improved; an allele concordance rate of 1.00 was achieved when animal call rate was between 85 and <99%. The accuracy of imputation of the nonobserved genotypes in the low-call rate animals improved as animal call rate increased; the mean genotype concordance rate of the imputed nonobserved SNP was 0.41 when animal call rate was <40% but increased to 0.95 when animal call rate was between 95 and <99%. Parentage validation, determined by the count of opposing homozygotes in a parent-progeny pair, was unreliable when animal call rate was <85%. Therefore, to ensure the provision of high-quality genotypes while also considering the cost and inconvenience of resampling and regenotyping, we suggest a minimum animal call rate threshold of 85%.

Genetic parameters for lactose and its correlation with other milk production traits and fitness traits in pasture-based production systems

Lactose is a major component of milk (typically around 5% of composition) that is not usually directly considered in national genetic improvement programs of dairy cattle. Daily test-day lactose yields and percentage data from pasture-based seasonal calving herds in Australia were analyzed to assess if lactose content can be used for predicting fitness traits and if an additional benefit is achieved by including lactose yield in selecting for milk yield traits. Data on lactose percentage collected from 2007 to 2014, from about 600 herds, were used to estimated genetic parameters for lactose percentage and lactose yield and correlations with other milk yield traits, somatic cell count (SCC), calving interval (CIV), and survival. Daily test-day data were analyzed using bivariate random regression models. In addition, multi-trait models were also performed mainly to assess the value of lactose to predict fitness traits. The heritability of lactose percentage (0.25 to 0.37) was higher than lactose yield (0.11 to 0.20) in the first parity. Genetically, the correlation of lactose percentage with protein percentage varied from 0.3 at the beginning of lactation to -0.24 at the end of the lactation in the first parity. Similar patterns in genetic correlations were also observed in the second and third parity. At all levels (i.e., genetic, permanent environmental, and residual), the correlation between milk yield and lactose yield was close to 1. The genetic and permanent environmental correlations between lactose percentage and SCC were stronger in the second and third parity and toward the end of the lactation (-0.35 to -0.50) when SCC levels are at their maximum. The genetic correlation between lactose percentage in the first 120 d and CIV (-0.23) was similar to correlation of CIV with protein percentage (-0.28), another component trait with the potential to predict fertility. Furthermore, the correlations of estimated breeding values of lactose percentage and estimated breeding values of traits such as survival, fertility, SCC, and angularity suggest that the value of lactose percentage as a predictor of fitness traits is weak. The results also suggest that including lactose yield as a trait into the breeding objective is of limited value due to the high positive genetic correlation between lactose yield and protein yield, the trait highly emphasized in Australia. However, recording lactose percentage as part of the routine milk recording system will enable the Australian dairy industry to respond quickly to any future changes and market signals.