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The net return from milk to the producers is defined as the aggregate market income from dairy products, after deducting all processing and marketing costs. The way to distribute this net return is through the payment system, which is usually based on multiple components, mainly with a reward for fat and protein and, in the case of the New Zealand dairy industry, a penalty for milk volume. Traditionally, the value of genetic improvement is evaluated using selection index theory assuming that there is an unlimited market where all dairy products can be sold in unlimited amounts at a fixed price and therefore economic values for fat and protein are assumed to be independent of demand. The objective of this study was to estimate the value of continuous genetic improvement evaluated using a model encompassing all the dairy producers in the industry where prices of the dairy products were determined by product specific supply-demand curves. Over 10 years of genetic improvement, the present value of the benefit (10% discount rate) was estimated to be $123,000 per farm. The corresponding benefit when the markets were assumed to have fixed commodity prices was $183,000 per farm. The model revealed that systematic genetic gains had a finite duration during which incremental benefits progressively declined and would be exhausted eventually.

The objectives of this study were to estimate genetic parameters for citric acid content (CA) and lactic acid content (LA) in sheep milk and to identify the associated candidate genes in a New Zealand dairy sheep flock. Records from 165 ewes were used. Heritability estimates based on pedigree records for CA and LA were 0.65 and 0.33, respectively. The genetic and phenotypic correlations between CA and LA were strong-moderate and negative. Estimates of genomic heritability for CA and LA were also high (0.85, 0.51) and the genomic correlation between CA and LA was strongly negative (-0.96 ± 0.11). No significant associations were found at the Bonferroni level. However, one intragenic SNP in C1QTNF1 (chromosome 11) was associated with CA, at the chromosomal significance threshold. Another SNP associated with CA was intergenic (chromosome 15). For LA, the most notable SNP was intragenic in CYTH1 (chromosome 11), the other two SNPs were intragenic in MGAT5B and TIMP2 (chromosome 11), and four SNPs were intergenic (chromosomes 1 and 24). The functions of candidate genes indicate that CA and LA could potentially be used as biomarkers for energy balance and clinical mastitis. Further research is recommended to validate the present results.

An increasing number of dairy farmers in New Zealand (NZ) have adopted a once-a-day (OAD) milking production system, and little is known about the impact of this production system on milk protein composition. The objective of this study was to evaluate the effect of OAD milking on the protein composition in milk from individual cows. Milk was sampled in early, mid-, and late lactation from cows kept at Massey University farms Dairy No. 1 (OAD milking) and Dairy No. 4 (TAD milking) in Palmerston North, NZ. The yields of total milk and milk solids, the proximate composition, and the protein composition were determined. Results showed that OAD milking yielded less milk and milk solids than TAD milking. However, no significant differences in protein, fat, and lactose contents were found. While the proportions of total casein (CN), total whey proteins, αs1-CN, β-CN, and β-lactoglobulin were not affected by the milking frequency, milk from a OAD milking system contained higher proportions of αs2-CN and κ-CN and lower proportions of α-lactalbumin. These proteins also changed differently throughout the milking season in a OAD milking system than in a TAD milking system. These changes in the protein composition of the milk observed in a OAD milking system could have implications for its processing properties and product quality.

Abstract Background Vitamin E has a positive effect in the management of osteoarthritis in humans, and in a previous study of dogs. It has been suggested to decrease C‐reactive protein concentrations and liver enzyme activities in humans and animals. Objective To assess the effect of vitamin E supplementation on lameness, pain, pain medication requirement, clinical pathology variables, and quality of life in large‐breed dogs with naturally occurring osteoarthritis. Animals Fifty‐seven client‐owned dogs with naturally occurring osteoarthritis. Methods Dogs received either vitamin E or placebo for 90 days in a randomized, placebo‐controlled, double‐blinded, prospective clinical trial. Clinical lameness scores, pain medication requirements, and owner questionnaires were used to assess response to treatment every 30 days. Blood samples were collected at enrollment and at the end of the study period. Results Vitamin E administration did not improve pain, lameness, or quality of life as assessed by owners and veterinarians. Vitamin E supplementation did not decrease the requirement for rescue pain relief. No changes in clinical pathology variables were observed after 90 days of vitamin E supplementation. Body weight was negatively associated with the lameness scores and requirement for rescue pain relief. Conclusion Vitamin E supplementation did not have any observable positive effects in dogs with naturally occurring osteoarthritis.

ABSTRACT: Of late, “A2 milk” has gained prominence in the dairy sector due to its potential implications in human health. Consequently, the frequency of A2 homozygous animals has considerably increased in many countries. To elucidate the potential implications that beta casein (β-CN) A1 and A2 may have on cheese-making traits, it is fundamental to investigate the relationships between the genetic polymorphisms and cheese-making traits at the dairy plant level. Thus, the aim of the present study was to evaluate the relevance of the β-CN A1/A2 polymorphism on detailed protein profile and cheese-making process in bulk milk. Based on the β-CN genotype of individual cows, 5 milk pools diverging for presence of the 2 β-CN variants were obtained: (1) 100% A1; (2) 75% A1 and 25% A2; (3) 50% A1 and 50% A2; (4) 25% A1 and 75% A2; and (5) 100% A2. For each cheese-making day (n = 6), 25 L of milk (divided into 5 pools, 5 L each) were processed, for a total of 30 cheese-making processes. Cheese yield, curd nutrient recovery, whey composition, and cheese composition were assessed. For every cheese-making process, detailed milk protein fractions were determined through reversed-phase HPLC. Data were analyzed by fitting a mixed model, which included the fixed effects of the 5 different pools, the protein and fat content as a covariate, and the random effect of the cheese-making sessions. Results showed that the percentage of κ-CN significantly decreased up to 2% when the proportion of β-CN A2 in the pool was ≥25%. An increase in the relative content of β-CN A2 (≥50% of total milk processed) was also associated with a significantly lower cheese yield both 1 and 48 h after cheese production, whereas no effects were observed after 7 d of ripening. Concordantly, recovery of nutrients reflected a more efficient process when the inclusion of β-CN A2 was ≤75%. Finally, no differences in the final cheese composition obtained by the different β-CN pools were observed.

The objective of the study was to explore the effect of breed on the composition and coagulation properties (rennet coagulation time (min), curd firming rate (min), and curd firmness (mm)) of milk from cows milked once a day or twice a day in the morning and afternoon, using a Formagraph. Thirty cows (11 Holstein-Friesian, 8 Holstein-Friesian × Jersey cross, and 11 Jersey) from a once-a-day milking herd and thirty cows (16 Holstein-Friesian, 10 Holstein-Friesian × Jersey cross, and 4 Jersey) from a twice-a-day milking herd were sampled in late lactation. The milk composition and coagulation properties were analysed for each milk sample. Jersey cows had better milk coagulation properties at each milking frequency-milking time compared to Holstein-Friesian cows. Curd firmness 30 min after the addition of rennet was positively (p < 0.05) correlated with the protein concentration. However, the correlations were inconsistent between milking frequencies and milking times, resulting in poor prediction of the changes in cheese-making potential. This study indicated that milk composition and coagulation properties were affected by breed and milking frequency. The effect of the breed could be due to the variation in the composition of the milk, but firm recommendations were hampered by a low number of samples. Further research with larger cow numbers is justified.

The aim of the present study was to develop a model to predict muscularity and body condition score (BCS) during the lactation of Italian Simmental dairy cows in Emilia Romagna herds. A total of 2656 Italian Simmental primiparous cows from 324 dairy herds were linear classified between 2002 and 2020. Lactation curves for muscularity and BCS were modelled for each cow using random regression model. The model included the fixed effects of age at linear scoring and days in milk modelled with a Legendre polynomial, and the random effects of herd-year of classification, cow and days in milk for each cow modelled with Legendre polynomials. The most parsimonious model included a fixed cubic Legendre polynomial and a random linear polynomial for cow effects. Results indicated that, on an average, BCS nadir was anticipated to that of muscularity, and, in both cases, this moment was around the lactation peak, when animals have the greatest nutrients requirement. After this period, both BCS and muscularity recovered up to post-partum levels. Moreover, after the 9 month of lactation, the absolute growth rate of muscularity and BCS was negative, suggesting that late-gestating cows could potentially enter a phase of body conformation loss. Results reported in the current research indicate that random regression using Legendre polynomials can be successfully employed to predict muscularity and BCS during the lactation of dairy cows.Highlights Modelling dairy cows’ muscularity and BCS allows to use these parameters as indicator traits for functionality in dairy cows. The use of prediction model of muscularity and BCS allows to understand the evolution of these conformation traits during the lactation. The analysis of muscularity and BCS allows to assess health and welfare status of dairy cows, which is essential to maximise production performances.

The objective of this study was to evaluate the effect of breed on the overall composition and fatty acid composition of milk from cows milked once a day (OAD) and twice a day (TAD) in different stages of lactation. Milk samples were taken from 39 Holstein-Friesian (F), 27 Jersey (J), and 34 Holstein-Friesian × Jersey (F × J) crossbred cows from a OAD milking herd and 104 F and 83 F × J cows from a TAD milking herd in early (49 ± 15 days in milk), mid (129 ± 12 days in milk), and late (229 ± 13 days in milk) lactation. Calibration equations to predict the concentrations of individual fatty acids were developed using mid-infrared (MIR) spectroscopy. There was a significant interaction between breed within the milking frequency and stage of lactation for the production traits and composition traits. Holstein-Friesian cows milked OAD produced milk with lower concentrations of C18:0 in early and mid lactations compared to F × J and J cows. Holstein-Friesian cows milked TAD produced lower concentrations of C18:0 in early lactation and lower concentrations of C16:0 and C18:0 in late lactation compared to F × J. Lower concentrations of these fatty acids would reduce the hardness of the butter when the milk is processed. In the OAD milking herd, F cows were superior for daily milk yield compared to J cows, but Jersey cows produced significantly (p < 0.05) higher percentages of fat and a higher concentration of C18:0 fatty acid. The relative concentrations of C18:0 and C18 cis-9 in F and J cows milked OAD imply there is no breed effect on the activity of delta-9-desaturase, whereas stages of lactation likely have an effect. These results can be used to assist with selecting breeds and cows that are suitable for either OAD or TAD milking, allowing closer alignment with milk processing needs.

The present study aimed to investigate the association between stayability (STAY) traits, muscularity, and body condition score (BCS) in the Italian Simmental dual-purpose cows. Data were collected from 2,656 cows linearly scored in their first lactation from 2002 to 2020 and reared in 324 herds. The binary trait STAY, which is the ability of a cow to stay in the herd, was obtained for each cow-lactation available up to parity 5 (from STAY1-2 to STAY4-5). Analysis of STAY was carried out using logistic regression, considering the fixed effect of energy corrected milk, conception rate, somatic cell score, and muscularity or BCS predicted at different time points. The herd of linear classification and residual error were the random effects. Primiparous cows with a medium BCS and muscularity in early lactation presented a more favorable STAY across life compared to thinner ones (P < 0.05). In fact, cows with an intermediate BCS/muscularity were more likely to stay in the herd after the third lactation (STAY3-4), compared to those presenting a lower BCS/muscularity (P < 0.01). However, cows whose muscularity was high were generally less likely to start the third lactation compared to the others. A potential explanation for this could be the willing to market cows with good conformation for meat purpose. Simmental is in fact a dual-purpose breed known for the good carcass yield and meat quality. This study demonstrates how muscularity and BCS available early in life can be associated with the ability of Simmental cows to stay in the herd.

In this case study, we compared the gross composition and fatty acid (FA) composition of milk from cows milked once a day (OAD) and twice a day (TAD) at different stages of lactation in real farm conditions with no control on feed. Seventy-two cows from a OAD milking herd and 181 cows from a TAD milking herd were sampled in early, mid and late lactation. Calibration equations were developed to enable the prediction of proportions of individual FAs using mid-infrared (MIR) spectroscopy. Cows milked OAD produced 25% lower daily milk yield (MY) compared to cows milked TAD. Percentages of fat and protein were 21% and 9% higher in cows milked OAD compared to cows milked TAD, respectively. The proportion of saturated fatty acids (SFA) (molecules with unbranched hydrocarbon chains and all single bonds) was significantly lower, while the proportions of de novo synthesised FAs from C8:0 to C14:0 were significantly higher, in cows milked OAD compared to cows milked TAD. OAD milking improved the energy balance of cows, which led to higher proportions of de novo synthesised FAs and lower proportions of long-chain fatty acids (16:0 and above). The proportion of SFA was significantly higher in mid lactation (ML) compared to early lactation (EL) and late lactation (LL) in cows milked OAD and TAD. In EL, the proportions of C4:0 to C12:0 FAs in cows milked OAD were significantly higher compared to the cows milked TAD due to the improved energy status of cows milked OAD. Understanding the proportions of individual FAs in cows milked OAD and TAD will enable further studies on milk fat characteristics and on butter hardness and coagulation properties of milk.

Abstract Background Economically important milk production traits including milk volume, milk fat and protein yield vary considerably across dairy goats in New Zealand. A significant portion of the variation is attributable to genetic variation. Discovery of genetic markers linked to milk production traits can be utilised to drive selection of high-performance animals. A previously reported genome wide association study across dairy goats in New Zealand identified a quantitative trait locus (QTL) located on chromosome 19. The most significantly associated single nucleotide polymorphism (SNP) marker for this locus is located at position 26,610,610 (SNP marker rs268292132). This locus is associated with multiple milk production traits including fat, protein and volume. The predicted effect of selection for the beneficial haplotype would result in an average production increase of 2.2 kg fat, 1.9 kg protein and 73.6 kg milk yield. An outstanding question was whether selection for the beneficial allele would co-select for any negative pleiotropic effects. An adverse relationship between milk production and udder health traits has been reported at this locus. Therefore, a genome wide association study was undertaken looking for loci associated with udder traits. Results The QTL and production associated marker rs268292132 was identified in this study to also be associated with several goat udder traits including udder depth (UD), fore udder attachment (FUA) and rear udder attachment (RUA). Our study replicates the negative relationship between production and udder traits with the high production allele at position 19:26,610,610 (SNP marker rs268292132) associated with an adverse change in UD, FUA and RUA. Conclusions Our study has confirmed the negative relationship between udder traits and production traits in the NZ goat population. We have found that the frequency of the high production allele is relatively high in the NZ goat population, indicating that its effect on udder conformation is not significantly detrimental on animal health. It will however be important to monitor udder conformation as the chromosome 19 locus is progressively implemented for marker assisted selection. It will also be of interest to determine if the gene underlying the production QTL has a direct effect on mammary gland morphology or whether the changes observed are a consequence of the increased milk volume.

Lameness on dairy goat farms is a welfare concern and could negatively affect milk production. This study’s objective was to evaluate the effects of clinical lameness on the daily milk production of dairy goats. Between July 2019 and June 2020, 11,847 test-day records were collected from 3145 goats on three farms in New Zealand. Locomotion scoring of goats used a five-point scoring system (0 to 4). The dataset was split into two groups by lactation type, where goats were classified as being in seasonal lactation (≤305 days in milk) or extended lactation (>305 days in milk). A linear mixed model was used to analyze datasets using milk characteristics as the dependent variables. Severely lame goats (score 4) in seasonal and extended lactation produced 7.05% and 8.67% less milk than goats not lame, respectively. When the prevalence of severe lameness is between 5 and 20% of the herd, the estimated average daily milk income lost was between NZD 19.5 and 104 per day. This study established the negative impact of lameness on milk production and annual income in dairy goats on three farms.

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.

Abstract Background Identifying associations between genetic markers and traits of economic importance will provide practical benefits for the dairy goat industry, enabling genomic prediction of the breeding value of individuals, and facilitating discovery of the underlying genes and mutations. Genome-wide association studies were implemented to detect genetic regions that are significantly associated with effects on lactation yields of milk (MY), fat (FY), protein (PY) and somatic cell score (SCS) in New Zealand dairy goats. Methods A total of 4,840 goats were genotyped with the Caprine 50 K SNP chip (Illumina Inc., San Diego, CA). After quality filtering, 3,732 animals and 41,989 SNPs were analysed assuming an additive linear model. Four GWAS models were performed, a single-SNP additive linear model and three multi-SNP BayesC models. For the single-SNP GWAS, SNPs were fitted individually as fixed covariates, while the BayesC models fit all SNPs simultaneously as random effects. A cluster of significant SNPs were used to define a haplotype block whose alleles were fitted as covariates in a Bayesian model. The corresponding diplotypes of the haplotype block were then fit as class variables in another Bayesian model. Results Across all four traits, a total of 43 genome-wide significant SNPs were detected from the SNP GWAS. At a genome-wide significance level, the single-SNP analysis identified a cluster of variants on chromosome 19 associated with MY, FY, PY, and another cluster on chromosome 29 associated with SCS. Significant SNPs mapped in introns of candidate genes (45%), in intergenic regions (36%), were 0–5 kb upstream or downstream of the closest gene (14%) or were synonymous substitutions (5%). The most significant genomic window was located on chromosome 19 explaining up to 9.6% of the phenotypic variation for MY, 8.1% for FY, 9.1% for PY and 1% for SCS. Conclusions The quantitative trait loci for yield traits on chromosome 19 confirms reported findings in other dairy goat populations. There is benefit to be gained from using these results for genomic selection to improve milk production in New Zealand dairy goats.

Lactation curves were modelled for dairy sheep in a New Zealand flock, providing information on the lactation yields of milk, fat, protein, and lactose, corrected for 130 days of milking. From 169 ewes, a total of 622 test-day records were obtained during the milk production season of 2021–2022 (from October to January). The flock produced an average of 86.1 kg of milk, 5.1 kg of fat, 4.5 kg of protein, and 4.1 kg of lactose, and moderate to large coefficients of variation were observed (27–31%) for these traits. The lactation persistency of milk, fat, protein, and lactose yields ranged from 52.3 to 72.7%. Analyses of variance for total yield and persistency were performed with an animal model that included the fixed effects of age (parity number), litter size, coat colour, and milking frequency (days in twice-a-day milking) and random residuals. Age and milking frequency were the only factors that significantly affected the yields of milk, fat, protein, and lactose. Age significantly affected the lactation persistency of milk and lactose yields, whereas litter size affected the persistency of protein, and milking frequency affected the persistency of fat. This study on this single flock provides valuable experience for a larger-scale animal breeding programme in New Zealand.

Background. Eighty percent of beef produced in Mexico is consumed domestically. However, in recent years per capita domestic consumption has gradually decreased. Identifying consumer preferences and their perspectives on beef quality could provide information for the design of programs focused on the improvement of beef production chain and encourage meat consumption. Objective. In this study the definition of quality is provided and discussed and the published evidence on the main attributes considered by the Mexican consumer at the time of beef purchase are revised, providing a critical perspective on beef quality appreciation and to identify some implications and limitations. Methodology. Was performed a bibliographic search of available literature including the Mexican consumer perspective on beef quality attributes published in peer reviewed papers from international and national indexed journals. Main findings. Evidences on the main criterions that Mexican consumer considers as indicators for beef quality during de beef purchase are presented, and some implications and perspectives for the future adoption of more complex systems to guarantee beef quality and add value to the entire production chain are discussed. Implications. This study provide some directions on the establishment of proposals to adequately define the Mexican beef consumer preferences focused on quality and consistency of product, favorable for the whole beef industry. Conclusions: The price of beef was identified as the main criterion considered for Mexican consumer for purchasing of beef, and secondarily, his perspective include intrinsic attributes generically describing the beef quality. More studies are necessary for the identification of factors affecting the beef consistency and to adequately define the most important attributes that satisfy the Mexican consumer perspective on beef quality.

The present study aimed to assess the phenotypic variation of milk yield (MY) and quality traits in Italian Jersey (IJ) breed. Sources of variation were investigated through a linear mixed model, including the fixed effects of days in milk (DIM), parity, calving season, milking frequency, recording type, the interaction between DIM and parity, and the random effects of herd-test-day (HTD), cow and the residual. Results highlighted the high contents of milk fat (5.18%), protein (4.08%) and casein (3.16%) of IJ cows. Somatic cell score, averaging 3.35 units, should be lowered through specific managerial actions. Phenotypic variances of MY and milk quality traits were mainly due to cow effect, whereas phenotypic variance of milk urea nitrogen (MUN) content was mainly due to HTD effect, meaning that managerial conditions, especially feeding, are very important to explain the variation of MUN. In conclusion, the present study allowed to characterise milk of IJ cows at population level and to identify environmental factors associated with variation of MY and quality traits, which will be useful to adjust phenotypic records in genetic evaluation of Jersey breed.Highlights Factors affecting milk quality traits of Italian Jersey cows have been investigated. Phenotypic variance of milk composition and SCS was mainly due to cow effect, and that of MUN was mainly driven by herd-test-day effect. Significant environmental factors identified in the present study will be used to adjust phenotypic records in genetic analysis.

New Zealand farm working dogs are supreme athletes that are crucial to agriculture in the region. The effects that low or high dietary carbohydrate (CHO) content might have on their interstitial glucose (IG) and activity during work are unknown. The goals of the study were to determine if the concentration of IG and delta-g (a measurement of activity) will be lower in dogs fed an ultra-low CHO high fat diet in comparison to dogs fed a high CHO low fat diet, and to determine if low concentrations of IG are followed by reduced physical activity. We hypothesized that feeding working farm dogs an ultra-low CHO diet would reduce their IG concentrations which in turn would reduce physical activity during work. We prospectively recruited 22 farm dogs from four farms. At each farm, dogs were randomized to one of two diets and had a month of dietary acclimation to their allocated diet. The macronutrient proportions as a percentage of metabolizable energy (%ME) for the high CHO low fat diet (Diet 1) were 23% protein, 25% fat, and 52% CHO, and for the ultra-low CHO high fat diet (Diet 2) 37% protein, 63% fat, and 1% CHO. Following the acclimation period, we continuously monitored IG concentrations with flash glucose monitoring devices, and delta-g using triaxial accelerometers for 96 h. Dogs fed Diet 2 had a lower area under the curve (±SE) for IG (AUC Diet 2 = 497 ± 4 mmol/L/96h, AUC Diet 1 = 590 ± 3 mmol/L/96h; P = 0.002) but a higher area under the curve (±SE) for delta-g (AUC Diet 2 = 104,122 ± 6,045 delta-g/96h, AUC Diet 1 = 80,904 ± 4,950 delta-g/96h; P< 0.001). Interstitial glucose concentrations increased as the activity level increased (P < 0.001) and were lower for Diet 2 within each activity level (P < 0.001). The overall incidence of low IG readings (< 3.5 mmol/L) was 119/3810 (3.12%), of which 110 (92.4%) readings occurred in the Diet 2 group (P = 0.001). In the Diet 2 group, 99/110 (90%) of the low IG events occurred during the resting period (19:00-06:00). We conclude that feeding Diet 2 (ultra-low CHO high fat diet) to working farm dogs was associated with increased delta-g despite decreased IG concentrations. Interstitial glucose concentrations were positively associated with dogs' activity levels independent of diet. Lastly, events of low IG occurred at a low incidence and were predominantly seen between 19:00-06:00 in dogs fed the ultra-low CHO high fat diet.

The early detection of health problems in dairy cattle is crucial to reduce economic losses. Mid-infrared (MIR) spectrometry has been used for identifying the composition of cow milk in routine tests. As such, it is a potential tool to detect diseases at an early stage. Partial least squares discriminant analysis (PLS-DA) has been widely applied to identify illness such as lameness by using MIR spectrometry data. However, this method suffers some limitations. In this study, a series of machine learning techniques—random forest, support vector machine, neural network (NN), convolutional neural network and ensemble models—were used to test the feasibility of identifying cow sickness from 1909 milk sample MIR spectra from Holstein-Friesian, Jersey and crossbreed cows under grazing conditions. PLS-DA was also performed to compare the results. The sick cow records had a time window of 21 days before and 7 days after the milk sample was analysed. NN showed a sensitivity of 61.74%, specificity of 97% and positive predicted value (PPV) of nearly 60%. Although the sensitivity of the PLS-DA was slightly higher than NN (65.6%), the specificity and PPV were lower (79.59% and 15.25%, respectively). This indicates that by using NN, it is possible to identify a health problem with a reasonable level of accuracy.

The aim of this study was to investigate the sources of variation of milk fatty acids (FA) routinely predicted by mid-infrared spectroscopy in Holstein-Friesian (HF), Brown Swiss (BS), Simmental (SI) and Alpine Grey (AG) cattle breeds. A linear mixed model was used to analyse the data which included 153,801 individual milk samples from 14,301 cows. Fixed effects included in the model were breed, month of sampling, year of sampling, stage of lactation, parity and first order interactions between them, and random effects were herd nested within breed, cow nested within breed and the residual error. Milk of AG cows exhibited the lowest content of saturated FA and the greatest content of unsaturated FA, whereas milk of BS had an opposite pattern. Holstein-Friesian and SI were intermediate between AG and BS breeds for all the FA except for total C18:1, which was the greatest in HF. Saturated FA, C14:0 and C16:0 increased from calving until 120 days in milk, whereas unsaturated FA and C18:1 decreased. First parity cows produced milk with lower concentration of de novo FA than multiparous animals. The greatest content of unsaturated FA and C18:1 was observed in summer, whereas saturated FA, C14:0, C16:0 and C18:0 decreased in summer and increased in winter. The differences in milk FA profile among breeds are useful for genetic selection and for feeding strategies.

The objectives of this study were two-fold. Firstly, to estimate the likely correlated responses in milk urea nitrogen (MUN) concentration, lactation yields of milk (MY), fat (FY) and crude protein (CPY) and mature cow liveweight (LWT) under three selection scenarios which varied in relative emphasis for MUN; 0% relative emphasis (MUN0%: equivalent to current New Zealand breeding worth index), and sign of the economic value; 20% relative emphasis positive selection (MUN+20%), and 20% relative emphasis negative selection (MUN−20%). Secondly, to estimate for these three scenarios the likely change in urinary nitrogen (UN) excretion under pasture based grazing conditions. The predicted genetic responses per cow per year for the current index were 16.4 kg MY, 2.0 kg FY, 1.4 kg CPY, −0.4 kg LWT and −0.05 mg/dL MUN. Positive selection on MUN in the index resulted in annual responses of 23.7 kg MY, 2.0 kg FY, 1.4 kg CPY, 0.6 kg LWT and 0.10 mg/dL MUN, while negative selection on MUN in the index resulted in annual responses of 5.4 kg MY, 1.6 kg FY, 1.0 kg CPY, −1.1 kg LWT and −0.17 mg/dL MUN. The MUN−20% reduced both MUN and cow productivity, whereas the MUN+20% increased MUN, milk production and LWT per cow. Per cow dry matter intake (DMI) was increased in all three scenarios as milk production increased compared to base year, therefore stocking rate (SR) was adjusted to control pasture cover. Paradoxically, ten years of selection with SR adjusted to maintain annual feed demand under the MUN+20% actually reduced per ha UN excretion by 3.54 kg, along with increases of 63 kg MY, 26 kg FY and 16 kg CPY compared to the base year. Ten years of selection on the MUN0% index generated a greater reductions of 10.45 kg UN and 30 kg MY, and increases of 32 kg FY and 21 kg CPY per ha, whereas the MUN−20% index reduced 14.06 kg UN and 136 kg MY with increases of 32 kg FY and 18 kg CPY compared to base year. All three scenarios increased partitioning of nitrogen excreted as feces. The selection index that excluded MUN was economically beneficial in the current economic circumstances over selection indices including MUN regardless of whether selection was either for or against MUN. There was no substantial benefit from an environmental point of view from including MUN in the Breeding Worth index, because N leaching is more a function of SR rather than of individual cow UN excretion. This study demonstrates that attention needs to be paid to the whole system consequences of selection for environmental outcomes in pastoral grazing circumstances.

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.

This study focuses on calibrating and validating models for hyperspectral canopy reflectance data that are useful to predict the nutritive value of ryegrass-white clover mixed herbage available to the grazing cow. Hyperspectral measurements and herbage cuts were collected from 286 sampling plots from a dairy farm from July 2017 to May 2018. Hyperspectral data were pre-treated by applying a Savitzky-Golay filter followed by a Gap-segment derivative algorithm. Herbage samples were analyzed for determination of herbage nutritive value traits, digestible organic matter in dry matter (DOMD), metabolizable energy (ME), crude protein (CP), neutral detergent fiber (NDF) and acid detergent fiber (ADF). Partial least squares regression was performed to calibrate the spectra against the five nutritive value traits. Results indicate that accuracy was moderately high for the CP model (R2 = 0.78) and moderate for the DOMD, ME, NDF and ADF models (0.54 < R2 < 0.67). The possibility of being able to use proximal sensing for the estimation of herbage nutritive value in the field could potentially contribute to more efficient grazing management with potential economic benefits for the farm business.

New Zealand deer farming centres on the production of meat and velvet antler. Velvet antler removal is a painful procedure and currently, New Zealand Animal Welfare regulations dictate surgical removal of velvet antlers under lignocaine anaesthesia. To improve our knowledge on the efficacy and duration of other local anaesthetics to mitigate pain after antler removal, it is important to accurately assess and quantify pain arising from antler removal. Therefore, the current study was designed to validate mechanical nociceptive threshold (MNT) testing using a Wagner hand-held algometer, and to apply this methodology to assess the efficacy and duration of action of articaine for antler removal in deer. Baseline force (N) required to elicit the nociceptive response was recorded in 40 yearling male red deer on three alternate days. Ten of the 40 animals were selected for antler removal after administration of 4% articaine hydrochloride as a ring block. The duration of analgesic efficacy of articaine was assessed by algometry across 5 time points. There was a significant difference in MNTs among the three days (day 3 versus day 1 (p < 0.0001), day 2 versus day 1 (p < 0.0001), and day 1 versus day 2 (p < 0.01)). Positive correlations were observed between weight, antler length and thresholds. The MNT values remained above 20N for 6 h after removal of velvet antlers under the articaine ring block. This study provides valuable information about the use of MNT in red deer. These findings lay a foundation for future studies in the topics of peri-operative and postoperative pain management in deer antler removal, and a possible alternative use for articaine.

The objective of this study was to determine the effect of seasonal variation on milk composition and establish an algorithm to predict density based on milk composition to enable the calculation of season-based density conversion calculations. A total of 1035 raw whole milk samples were collected from morning and evening milking of 60 spring-calving individual cows of different genetic groups, namely Jersey, Elite HF (Holstein–Friesian) and National Average HF, once every two weeks for a period of 9 months (March–November, 2018). The average mean and standard deviation for milk compositional traits were 4.72 ± 1.30% fat, 3.85 ± 0.61% protein and 4.69 ± 0.30% lactose and density was estimated at 1.0308 ± 0.002 g/cm3. The density of the milk samples was evaluated using three methods: a portable density meter, DMA 35; a standard desktop version, DMA 4500M; and an Association of Official Agricultural Chemists (AOAC) method using 100-mL glass pycnometers. Statistical analysis using a linear mixed model showed a significant difference in density of milk samples (p < 0.05) across seasonal and compositional variations adjusted for the effects of days in milk, parity, the feeding treatment, the genetic group and the measurement technique. The mean density values and standard error of mean estimated for milk samples in each season, i.e., spring, summer and autumn were 1.0304 ± 0.00008 g/cm3, 1.0314 ± 0.00005 g/cm3 and 1.0309 ± 0.00007 g/cm3, respectively.

The aim of this study was to identify risk factors for culling, sales and deaths in intensively managed dairy goat herds in New Zealand. A data set provided by the New Zealand Dairy Goat Cooperative (n = 13,197 does) was analyzed using a Cox proportional hazard model. The outcome of interest was length of productive life (LPL), defined as the number of days from the date of second kidding to the date of removal from the herd or the date on which follow-up was terminated, whichever occurred first. Milk solids yield in the first lactation (MSL1) as a predictor of LPL was parameterized in the model as a penalized spline term. To account for MSL1 violating the proportional hazards assumption of the Cox model, LPL was divided into two intervals: T1 (less than or equal to 730 days from the date of second kidding) and T2 (greater than 730 days from the date of second kidding). MSL1 was then included in the model as a time-dependent covariate. A frailty term was included in the model to account for unmeasured, herd-level effects on LPL. During T1, the daily hazard of removal for does that produced 80 kg milk solids in the first lactation was 0.84 (95% CI 0.58–1.23) times the daily hazard of removal for does that produced 30 kg milk solids in the first lactation. During T2, the daily hazard of removal for does that produced 80 kg milk solids in the first lactation was 1.44 (95% CI 0.79–2.65) times the daily hazard of removal for does that produced 30 kg milk solids in the first lactation. We conclude that involuntary losses may be avoided if high MSL1 yielding does are preferentially managed from 2 years beyond the date of second kidding.

Biofilm formation is of growing concern in human and animal health. However, it is still unclear how biofilms are related to mastitis infections in dairy cattle. In this study, a comparison between two tests for biofilm formation and the association between biofilm and the presence of genes associated with biofilm formation were investigated for 92 Staphylococcus aureus isolates from clinical mastitis cases. Congo red agar (CRA) and microtitre test assay (MTA) in vitro phenotypic tests were used to evaluate biofilm formation. The presence of icaA, icaD, and bap genes associated with biofilm formation was confirmed using the polymerase chain reaction. Results show that most of the S. aureus isolates, though not possessing one of the biofilm-forming genes, were able to produce biofilms. MTA was more frequently positive in identifying biofilm-forming isolates than CRA.

Minimizing the decrease in intracellular pH during high-intensity exercise training promotes greater improvements in mitochondrial respiration. This raises the intriguing hypothesis that pH may affect the exercise-induced transcription of genes that regulate mitochondrial biogenesis. Eight males performed 10x2-min cycle intervals at 80% VO2speak intensity on two occasions separated by ~2 weeks. Participants ingested either ammonium chloride (ACID) or calcium carbonate (PLA) the day before and on the day of the exercise trial in a randomized, counterbalanced order, using a crossover design. Biopsies were taken from the vastus lateralis muscle before and after exercise. The mRNA level of peroxisome proliferator-activated receptor co-activator 1α (PGC-1α), citrate synthase, cytochome c and FOXO1 was elevated at rest following ACID (P0.05); the difference in PGC-1α mRNA content 2 h post-exercise between ACID and PLA was not significant (P = 0.08). Thus, metabolic acidosis abolished the early post-exercise increase of PGC-1α mRNA and the mRNA of downstream mitochondrial and glucose-regulating proteins. These findings indicate that metabolic acidosis may affect mitochondrial biogenesis, with divergent responses in resting and post-exercise skeletal muscle.

Diabetes mellitus is a common endocrinopathy of cats that is characterized by persistent fasting hyperglycemia. However, stress induces substantial hyperglycemia in cats that poses a challenge to the veterinarian who may wrongly interpret the high serum concentration of blood glucose as evidence of diabetes mellitus. Fructosamine is a glycated serum protein that serves as an index of glycemic control in cats and is useful because it is not affected by stress hyperglycemia. However, factors such as body weight, hypoproteinemia, and increased serum thyroid hormone concentration can alter fructosamine concentration. The goal of this retrospective study was to compare the fructosamine concentrations in diabetic and nondiabetic cats with and without uncontrolled hyperthyroidism. A secondary goal was to determine the effect of sex, age, different populations of cats, and diabetes on the variability of fructosamine. We found that the mean (±SE) serum fructosamine of hyperthyroid diabetic cats (332 ± 24 µmol/L, 95% CI 291–379 µmol/L) was within the population-based reference interval (200–360 µmol/L) and significantly lower in comparison to euthyroid diabetic cats (527 ± 10 µmol/L, 95% CI 515–553 µmol/L). Additionally, in this study, diabetes accounted only for approximately 50% of the variance in serum fructosamine, while age, sex, and population made a minor contribution to this variance. In conclusion, finding serum fructosamine that is within the population-based reference interval in an uncontrolled diabetic cat should alert the veterinarian to the possibility of concurrent hyperthyroidism. Additionally, the veterinary clinician should consider that serum fructosamine might be substantially affected by factors other than diabetes.