China is facing serious experimental monkey shortage during the COVID-19 lockdown.

This report aims to analyze the experimental monkey shortage generated by the COVID-19 lockdown. The supply capability of the monkey breeding farms is insufficient to meet demand, and the sales prices have skyrocketed since 2018. The contradiction will be further aggravated with import prohibition although the countermeasures suggested.

Assessment of reproductive and growth performance of pigs on commercial swine farms in southern Kyushu, Japan.

The objective of the present study was to assess the productivity of pigs to investigate the time-dependent change in productivity and compare productivity according to breeding company group and porcine reproductive and respiratory syndrome (PRRS) status on commercial swine farms in southern Kyushu, Japan. Data used in the present study were 245 annual productivity records from 2014 to 2018 obtained from 72 farms. Average sow inventory was 481.2 sows. Mean numbers of pigs weaned per sow per year and market pigs sold per sow per year were 23.7 and 21.6, respectively. Pigs born alive per litter increased from 11.1 to 11.9 pigs from 2014 to 2018 (p < .05). Farms using domestic breeding companies had similar numbers in 2016 to those using international breeding companies, but fewer pigs in 2014, 2015, 2017, and 2018 (p < .05). Farms with an unknown or unstable PRRS status had fewer pigs born alive per litter and pigs weaned per sow per year than those with stable or negative PRRS statuses (11.2 ± 0.06 vs. 11.8 ± 0.08 pigs and 22.6 ± 0.38 vs. 25.0 ± 0.22 pigs, respectively; p < .05). These results can be used to establish feasible targets and standards of performance to identify problem areas and improve production.

A description of blend electrolysis for treatment of canine distichiasis: 78 cases (2012-2017).

OBJECTIVE: To describe a population of dogs treated with blend electrolysis for distichiasis at The Royal Veterinary College and report the complications seen. METHODS: In part 1, records were reviewed from 2012 to 2017 and a population of 78 dogs with distichiasis treated using blend electrolysis (Sterex SX-B blend epilator) analysed. In part 2, 18 dogs treated with blend electrolysis were re-examined prospectively by a diplomate of the European College of Veterinary Ophthalmologists (ECVO). RESULTS: In part 1, brachycephalic breeds accounted for 62 per cent. English bulldog was the most common breed (42 per cent). In this population, 88 per cent of dogs were successfully treated with one treatment of electrolysis (successful treatment defined as resolution of clinical signs). Forty-five dogs had recurrent distichia on follow-up, mostly fine distichia without clinical discomfort. Twelve per cent required repeat electrolysis. Complications were infrequent: five dogs had scarring or hypopigmentation of the eyelid margin. In part 2, 18 dogs were re-examined. Ten had distichia recurrence, six had eyelid scarring and five had depigmentation associated with electrolysis. Two dogs had occasional clinical signs thought to be related to distichiasis. All owners perceived their dogs' ocular comfort to be improved following blend electrolysis. CONCLUSIONS: Brachycephalic breeds, most notably English bulldogs, are over-represented in this population. Blend electrolysis appears an effective treatment for resolution of clinical signs.

The influence of climate variability on demographic rates of avian Afro-palearctic migrants.

Climate is an important driver of changes in animal population size, but its effect on the underlying demographic rates remains insufficiently understood. This is particularly true for avian long-distance migrants which are exposed to different climatic factors at different phases of their annual cycle. To fill this knowledge gap, we used data collected by a national-wide bird ringing scheme for eight migratory species wintering in sub-Saharan Africa and investigated the impact of climate variability on their breeding productivity and adult survival. While temperature at the breeding grounds could relate to the breeding productivity either positively (higher food availability in warmer springs) or negatively (food scarcity in warmer springs due to trophic mismatch), water availability at the non-breeding should limit the adult survival and the breeding productivity. Consistent with the prediction of the trophic mismatch hypothesis, we found that warmer springs at the breeding grounds were linked with lower breeding productivity, explaining 29% of temporal variance across all species. Higher water availability at the sub-Saharan non-breeding grounds was related to higher adult survival (18% temporal variance explained) but did not carry-over to breeding productivity. Our results show that climate variability at both breeding and non-breeding grounds shapes different demographic rates of long-distance migrants.

Barriers to entering race training before 4 years of age for Thoroughbred horses born in the 2014 Australian foal crop.

Currently, there is a paucity of data on the barriers for Australian Thoroughbred horses transitioning from stud farm to racetrack. This paper reports the reasons why horses failed to enter race training and documents their exit destinations. Biographical records of Australian Thoroughbred horses born in 2014 were investigated to determine the number of horses that had not officially entered race training by the start of the 4-year old racing season (1 August 2018). Of the 13,677 foals born in 2014, 66% had commenced training and 51% had raced before the beginning of their 4-year-old season in Australia. A sampling frame based on the post code of the premises where foals were born and records from Racing Australia were used to select a geographically representative sample of the 2014 Australian Thoroughbred foal crop (n = 4,124). From the population eligible for sampling 1,275 horses that had not entered training were enrolled in the survey and their breeders were sent an online questionnaire with follow-up phone calls for those who had not responded. Of the 633 responses (50% of 1275) the most frequent outcomes for horses were: death (38%, n = 239), participation in the racing industry in their 4-year old racing season (24%, n = 154) and retirement (16%, n = 100) either as Australian Stud Book (ASB) bloodstock (n = 17), or as horses rehomed outside the Thoroughbred industry (n = 83). Illness or injury was the most frequent reason for horses not entering race training that were ASB bloodstock, rehomed or deceased. There was a loss of traceability at the point of sale with most horses sold at 1 year of age. This study provides important information on the reasons, alternative outcomes and gaps in traceability for horses not entering training prior to the 4-year-old racing season.

Prevalence of canine primary hyperparathyroidism recurrence in Keeshond and non-Keeshond dogs after curative parathyroidectomy.

BACKGROUND: Primary hyperparathyroidism (PHPT) is an uncommon condition in dogs, for which there is a documented genetic predisposition in Keeshonden and sporadic cases in other breeds. Secondary literature reports a 10 per cent prevalence for recurrence in patients successfully treated by surgical parathyroidectomy, however there is no published primary literature available on which to base this assertion. This study sought to document prevalence of recurrence within Keeshonden and non-Keeshonden breeds. The authors hypothesised that Keeshonden would have a higher rate of recurrence due to the genetic predisposition for the disease, as compared with sporadic cases in other breeds, and that Keeshonden might have an earlier age of detection of disease. METHODS: A retrospective review of medical records was undertaken to assess the prevalence of recurrence, the length of time after diagnosis that the recurrence occurred, and the age of initial diagnosis in both Keeshonden and non-Keeshonden breeds. RESULTS: The study found that Keeshonden were significantly more likely to develop recurrence (6/12, 50 per cent) than non-Keeshonden dogs (1/15, 7 per cent) (P=0.024), and were significantly younger (median 108 v 126 months, P=0.043) at initial disease detection. Recurrence in Keeshonden occurred at median 35 months after treatment. CONCLUSION: This suggests all dogs treated by curative parathyroidectomy for PHPT should be monitored lifelong for recurrence of disease, and that this is particularly pertinent in the Keeshond population. Earlier screening of younger, apparently healthy Keeshonden may also be advisable.

Comparison of two models to estimate genetic parameters for number of born alive in pigs.

The performance of the two-trait animal model that regards the first parity and later parities as two different traits in estimating genetic parameters for number of born alive (NBA) was examined using real and simulated data. Genetic parameters for NBA were estimated in purebred Landrace and Large White pigs using a single-trait repeatability model (Model 1) that regards all parities as the same trait and a two-trait animal model (Model 2) that regards the first and the later parities as different traits. For Model 2, the permanent environmental effect was fitted to only the records of the later parities. Heritability for NBA estimated using Model 1 was 0.12 for Landrace and 0.11 for Large White. Estimated heritability for NBA of the first parity and the later parities was 0.21 and 0.16, respectively, for Landrace; 0.18 and 0.16, respectively, for Large White obtained using Model 2, and higher than those in both breeds obtained using Model 1. Further results based on data simulated using the Monte Carlo method suggest that estimated additive genetic variance could be more biased using Model 2 than Model 1.

A method for deriving the genetic matrix needed for selection across combinations of breeds.

A method is described for deriving the genetic matrix G needed for breeders to select across breeds for any breeding objective. The matrix comprises partitions among selection criteria (G11 ), between selection criteria and the breeding objective traits (G12 ), and among the breeding objective traits (G22 ). A weighting procedure is used to combine the G matrix of individual breeds with known breed differences. Between-breed variances are added to the diagonals of the matrix. Selection across many breeds can be quite different from that across a subset of the breeds. The particular breeds, and the numbers of each breed, that the breeder is prepared to consider in selection changes the genetic matrix and the selection index that should be used.

Improving genomic prediction accuracy for meat tenderness in Nellore cattle using artificial neural networks.

The goal of this study was to compare the predictive performance of artificial neural networks (ANNs) with Bayesian ridge regression, Bayesian Lasso, Bayes A, Bayes B and Bayes Cπ in estimating genomic breeding values for meat tenderness in Nellore cattle. The animals were genotyped with the Illumina Bovine HD Bead Chip (HD, 777K from 90 samples) and the GeneSeek Genomic Profiler (GGP Indicus HD, 77K from 485 samples). The quality control for the genotypes was applied on each Chip and comprised removal of SNPs located on non-autosomal chromosomes, with minor allele frequency <5%, deviation from HWE (p < 10-6 ), and with linkage disequilibrium >0.8. The FImpute program was used for genotype imputation. Pedigree-based analyses indicated that meat tenderness is moderately heritable (0.35), indicating that it can be improved by direct selection. Prediction accuracies were very similar across the Bayesian regression models, ranging from 0.20 (Bayes A) to 0.22 (Bayes B) and 0.14 (Bayes Cπ) to 0.19 (Bayes A) for the additive and dominance effects, respectively. ANN achieved the highest accuracy (0.33) of genomic prediction of genetic merit. Even though deep neural networks are recognized to deliver more accurate predictions, in our study ANN with one single hidden layer, 105 neurons and rectified linear unit (ReLU) activation function was sufficient to increase the prediction of genetic merit for meat tenderness. These results indicate that an ANN with relatively simple architecture can provide superior genomic predictions for meat tenderness in Nellore cattle.

Performance of pedigree and various forms of marker-derived relationship coefficients in genomic prediction and their correlations.

In recent years, with development and validation of different genotyping panels, several methods have been proposed to build efficient similarity matrices among individuals to be used for genomic selection. Consequently, the estimated genetic parameters from such information may deviate from their counterpart using traditional family information. In this study, we used a pedigree-based numerator relationship matrix (A) and three types of marker-based relationship matrices ( G ) including two identical by descent, that is G K and G M and one identical by state, G V as well as four Gaussian kernel ( GK ) similarity kernels with different smoothing parameters to predict yet to be observed phenotypes. Also, we used different kinship matrices that are a linear combination of marker-derived IBD or IBS matrices with A, constructed as K = λ G + 1 - λ A , where the weight ( λ ) assigned to each source of information varied over a grid of values. A Bayesian multiple-trait Gaussian model was fitted to estimate the genetic parameters and compare the prediction accuracy in terms of predictive correlation, mean square error and unbiasedness. Results show that the estimated genetic parameters (heritability and correlations) are affected by the source of the information used to create kinship or the weight placed on the sources of genomic and pedigree information. The superiority of GK-based model depends on the smoothing parameters (θ) so that with an optimum θ value, the GK-based model statistically yielded better performance (higher predictive correlation, lowest MSE and unbiased estimates) and more stable correlations and heritability than the model with IBD, IBS or A kinship matrices or any of the linear combinations.

Detection and density of breeding marsh birds in Iowa wetlands.

Accounting for imperfect detection is an important process when obtaining estimates of density or abundance for breeding birds, and this is particularly true when researchers are monitoring birds to assess the success of restored wetlands. Due to the dramatic decline in areal cover and habitat quality, wetland restoration in the Prairie Pothole Region (PPR) is critically important to breeding birds. The Shallow Lakes Restoration Project (SLRP), a partnership between the Iowa Department of Natural Resources and Ducks Unlimited, Inc., aims to restore degraded shallow lakes throughout the Iowa PPR. We conducted unlimited-radius point counts with call-broadcast surveys for breeding marsh birds at 30 shallow lakes in various stages of restoration in 2016 and 2017. Our goals were to assess the impact of covariates on detection probability and estimate density of these species at non-restored, younger (1-5 years since restoration), and older (6-11 years since restoration) restorations. Detection probability ranged between 0.07 ± 0.009 (SE) for Red-winged Blackbird and 0.40 ± 0.09 (SE) for Common Yellowthroat. Percent cattail had a positive quadratic effect on detection probability for four species, with detection decreasing sharply as percent cattail increased and increasing slightly with 100% cattail cover. Wind speed negatively influenced the detection probability of Pied-billed Grebes but had a negative quadratic effect on the detection probability of Marsh Wrens. Both restored shallow lakes had greater densities of breeding Pied-billed Grebes, Marsh Wrens, and Yellow-headed Blackbirds than non-restored shallow lakes, but there was no significant difference between younger and older restorations. Including both habitat and environmental covariates on models for detection probability can improve the precision of estimates for density and should be considered when assessing bird populations pre- and post-restoration of shallow lakes.

Farmers' choice of genotypes and trait preferences in tropically adapted chickens in five agro-ecological zones in Nigeria.

This study aimed at determining chicken genotypes of choice and traits preference in chicken by smallholder farmers in Nigeria. Data were obtained from a total of 2063 farmers using structured questionnaires in five agro-ecological zones in Nigeria. Chi square (χ2) statistics was used to explore relationships between categorical variables. The mean ranks of the six genotypes and twelve traits of preference were compared using the non-parametric Kruskal-Wallis H (with Mann-Whitney U test for post hoc separation of mean ranks), Friedman, and Wilcoxon signed-rank (with Bonferroni's adjustments) tests. Categorical principal component analysis (CATPCA) was used to assign farmers into groups. Gender distribution of farmers was found to be statistically significant (χ2 = 16.599; P ≤ 0.002) across the zones. With the exception of Shika Brown, preferences for chicken genotypes were significantly (P ≤ 0.01) influenced by agro-ecological zone. However, gender differentiated response was only significant (P ≤ 0.01) in Sasso chicken with more preference by male farmers. Overall, FUNAAB Alpha, Sasso, and Noiler chicken were ranked 1st, followed by Kuroiler (4th), Shika Brown (5th), and Fulani birds (6th), respectively. Within genotypes, within and across zones and gender, preferences for traits varied significantly (P ≤ 0.005 and P ≤ 0.01). Traits of preference for selection of chicken breeding stock tended towards body size, egg number, egg size, and meat taste. Spearman's rank order correlation coefficients of traits of preference were significant (P ≤ 0.01) and ranged from 0.22 to 0.90. The two PCs extracted, which explained 65.3% of the variability in the dataset, were able to assign the farmers into two groups based on preference for body size of cock and hen and the other ten traits combined. The present findings may guide the choice of appropriate chicken genotypes while the traits of economic importance may be incorporated into future genetic improvement and conservation programs in Nigeria.

Longitudinal analysis of body weight and average daily feed intake during the feedlot test period in Angus cattle.

The objectives of this study were to compare different models for analysing body weight (BW) and average daily feed intake (ADFI) data collected during a 70-day feedlot test period and to explore whether genetic parameters change over time to evaluate the implications of selection response. (Co)variance components were estimated using repeatability and random regression models in 2,071 Angus steers. Models included fixed effects of contemporary group, defined as herd-year-observation_date-age, with additive genetic and permanent environmental components as random effects. Models were assessed based on the log likelihood, Akaike's information criterion and the Bayesian information criterion. For both traits, random regression models (RRMs) presented a better fit, indicating that genetic parameters change over the test period. Using a two-trait RRM, the heritability from day 1 up to day 70 for BW increased from 0.40 to 0.50, while for ADFI, it decreased from 0.44 to 0.33. The genetic correlation increased from 0.53 at day 1 up to 0.79 at day 70. Selection based on an index assuming no change in genetic parameters would yield a 2.78%-3.13% lower selection response compared to an index using parameters estimated with RRMs and assuming these genetic parameters are correct. Results imply that it may be beneficial to implement RRMs to account for the change of parameters across the feedlot period in feed efficiency traits.

Incidence patterns of orofacial clefts in purebred dogs.

Cleft lip (CL), cleft palate (CP) and cleft lip and palate (CLP) are the most common types of orofacial clefts in dogs. Orofacial clefts in dogs are clinically relevant because of the associated morbidity and high newborn mortality rate and are of interest as comparative models of disease. However, the incidence of CL, CP and CLP has not been investigated in purebred dogs, and the financial impact on breeders is unknown. The aims of this study were to document the incidence patterns of CL, CP and CLP in different breeds of dogs, determine whether defect phenotype is associated with skull type, genetic cluster and geographic location, and estimate the financial impact in breeding programs in the United States by means of an anonymous online survey. A total of 228 orofacial clefts were reported among 7,429 puppies whelped in the 12 preceding months. Breeds in the mastiff/terrier genetic cluster and brachycephalic breeds were predisposed to orofacial clefts. Certain breeds in the ancient genetic cluster were at increased odds of orofacial clefts. Male purebred dogs were at increased odds of CPs. Results confirm that brachycephalic breeds are overrepresented among cases of orofacial clefts. Furthermore, geographic region appeared to be a relevant risk factor and orofacial clefts represented a considerable financial loss to breeders. Improved understanding of the epidemiology of orofacial clefts (frequency, causes, predictors and risk factors) may help in identifying ways to minimize their occurrence. Information gained may potentially help veterinarians and researchers to diagnose, treat and prevent orofacial clefts.

Optimizing the procedure of grain nutrient predictions in barley via hyperspectral imaging.

Hyperspectral imaging enables researchers and plant breeders to analyze various traits of interest like nutritional value in high throughput. In order to achieve this, the optimal design of a reliable calibration model, linking the measured spectra with the investigated traits, is necessary. In the present study we investigated the impact of different regression models, calibration set sizes and calibration set compositions on prediction performance. For this purpose, we analyzed concentrations of six globally relevant grain nutrients of the wild barley population HEB-YIELD as case study. The data comprised 1,593 plots, grown in 2015 and 2016 at the locations Dundee and Halle, which have been entirely analyzed through traditional laboratory methods and hyperspectral imaging. The results indicated that a linear regression model based on partial least squares outperformed neural networks in this particular data modelling task. There existed a positive relationship between the number of samples in a calibration model and prediction performance, with a local optimum at a calibration set size of ~40% of the total data. The inclusion of samples from several years and locations could clearly improve the predictions of the investigated nutrient traits at small calibration set sizes. It should be stated that the expansion of calibration models with additional samples is only useful as long as they are able to increase trait variability. Models obtained in a certain environment were only to a limited extent transferable to other environments. They should therefore be successively upgraded with new calibration data to enable a reliable prediction of the desired traits. The presented results will assist the design and conceptualization of future hyperspectral imaging projects in order to achieve reliable predictions. It will in general help to establish practical applications of hyperspectral imaging systems, for instance in plant breeding concepts.

Genetic evaluation of milking buffaloes (Bubalus bubalis): bull ranking / Avaliação genética de búfalas leiteiras (Bubalus bubalis): classificação de touros

The objective of this study was to evaluate genetic aspects related to production and reproductive efficiency of Murrah and Mediterranean buffaloes and their crosses. A ranking of bulls from Embrapa Eastern Amazonia was also composed to guide assisted mating. Birth records of 2,322 Murrah, Mediterranean, and crossbred buffaloes from the Embrapa Eastern Amazon herd, from 1953 to 2013, as well as information on production and reproductive traits were used. Genetic analyzes were performed in the WOMBAT software using the animal model with two-trait analysis. While heritability (h2) for total milk production (TMP) and fat milk percentage (F) were generally high, for reproductive traits h2 tended to be low. Genetic correlations for TMP with the other traits were low and negative, except for TMP with calving interval (CI) and service period (SP) in the Mediterranean breed and with age at first calving (AFC) and SP in crossbred, which were positive and high. Bull 1001 had high predicted transmitting ability (PTA) for TMP, so it should transmit a greater volume of milk to his offspring, although it had a lower PTA for F. There was sufficient variability within the herd to work with genetic management for both production and reproductive efficiency.(AU)

O objetivo deste estudo foi avaliar os aspectos genéticos relacionados à produção e à eficiência reprodutiva de búfalas das raças Murrah, Mediterrâneo e suas cruzas. Uma classificação de touros da Embrapa Amazônia Oriental também foi composta para orientar os cruzamentos assistidos. Foram utilizados 2.322 registros de nascimento de búfalas das raças Murrah, Mediterrâneo e cruzadas do rebanho da Embrapa Amazônia Oriental, de 1953 a 2013, bem como características produtivas e reprodutivas. As análises genéticas foram realizadas pelo software Wombat, utilizando-se o modelo animal com análise de duas características. Enquanto a herdabilidade (h 2 ) para a produção total de leite (PTL) e para a porcentagem de gordura (G) foi alta, para as características reprodutivas a h 2 tendeu a ser baixa. As correlações genéticas da PTL com as demais características foram baixas e negativas, exceto para a PTL com intervalo entre partos (IP) e período de serviço (PS) na raça Mediterrâneo e com idade ao primeiro parto (IPP) e PS nas cruzadas, que foram positivas e altas. O touro 1001 apresentou alta capacidade de transmissão predita (CTP) para a PTL, então deve transmitir um maior volume de leite para seus descendentes, embora com um menor conteúdo transmissível de CTP para G. Portanto, existe variabilidade suficiente dentro do rebanho para trabalhar com o manejo genético para a produção e a eficiência reprodutiva.(AU)

Evaluating sire effects on cow fertility: Timed AI and repeat-breeder dairy cows.

In this single herd observational study, there is investigation of the effects of 81 sires (with 11,424 artificial inseminations) on conception rates in 1790 Holstein cows for 5 years. Sires were catagorized based on the published sire conception rate (SCR) into different sire fertility groups (low, average and high fertility sires). The performance of different-sire fertility groups was assessed in timed artificial insemination (TAI) and repeat-breeder (RB) cows. With this aim, two logistic regression models with sire, inseminator, cow, and lactation random effects were applied to data on pregnancies assessed at days 30 and 70 post-insemination. Fixed effects of sire fertility group, sire breed, cow-fertility status, insemination type, postpartum problems, milk yield, temperature humidity index, and year were evaluated. Results from the analysis indicated there was a significant individual sire effect on conception rates, and large heterogeneity in values for this variable among sires. Results indicate that SCR could be assessed to predict low fertility sires reasonably well, and the predicted probabilities for pregnancy per AI (P/AI) at 30 and 70 days post-insemination for high fertility sires were consistent for the most part with values for the SCR. The sire breed did not affect conception rates at days 30 and 70 post-insemination nor its interactions with insemination type (estrous detection AI (EDAI) compared with TAI) and cow-fertility status (RB compared with non-RB). Predicting response probabilities for sires with at least 100 inseminations in each insemination group resulted in greater conception probabilities in cows in which there was EDAI than those in the TAI group.

Genomic selection strategies for breeding adaptation and production in dairy cattle under climate change.

Livestock production both contributes to and is affected by global climate change, and substantial modifications will be required to increase its climate resilience. In this context, reliance on dominant commercial livestock breeds, featuring small effective population sizes, makes current production strategies vulnerable if their production is restricted to environments, which may be too costly to support under future climate scenarios. The adaptability of animal populations to future environments will therefore become important. To help evaluate the role of genetics in climate adaptation, we compared selection strategies in dairy cattle using breeding simulations, where genomic selection was used on two negatively correlated traits for production (assumed to be moderately heritable) and adaptation (assumed to have low heritability). Compared with within-population breeding, genomic introgression produced a more positive genetic change for both production and adaptation traits. Genomic introgression from highly adapted but low production value populations into highly productive but low adaptation populations was most successful when the adaptation trait was given a lower selection weight than the production trait. Genomic introgression from highly productive population to highly adapted population was most successful when the adaptation trait was given a higher selection weight than the production trait. Both these genomic introgression schemes had the lowest risk of inbreeding. Our results suggest that both adaptation and production can potentially be improved simultaneously by genomic introgression.