Single-step genome-wide association analyses for milk urea concentration in Walloon Holstein cows.

The aims of this study were to conduct a single-step genome-wide association to identify genomic regions associated with milk urea (MU) and to estimate genetic correlations between MU and milk yield (MY), milk composition (calcium content [CC], fat percentage [FP], protein percentage [PP], and casein percentage [CNP]), and cheese-making properties (CMP; coagulation time [CT], curd firmness after 30 min from rennet addition [a30], and titratable acidity [TA]). The used data have been collected from 2015 to 2020 on 78,073 first-parity (485,218 test-day records) and 48,766 second-parity (284,942 test-day records) Holstein cows distributed in 671 herds in the Walloon Region of Belgium. Data of 565,533 SNP located on 29 BTA of 6,617 animals (1,712 males) were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic BLUP approach. The proportion of the total additive genetic variance explained by windows of 50 consecutive SNPs (with an average size of ∼216 kb) was calculated, and the top-3 genomic regions explaining the largest rate of the genetic variance were considered promising regions and used to identify potential candidate genes. Mean (SD) MU was 25.38 (8.02) mg/dL and 25.03 (8.06) mg/dL in the first and second lactation, respectively. Mean heritability estimates for daily MU were 0.21 and 0.23 for the first and second lactation, respectively. The genetic correlations estimated between MU and MY, milk composition, and CMP were quite low (ranged from -0.10 [CC] to 0.10 [TA] and -0.05 [CT] to 0.13 [TA] for the first and second lactations, respectively). The top-3 regions associated with MU were located from 80.61 to 80.74 Mb on BTA6, 103.26 to 103.41 Mb on BTA11, and 1.59 to 2.15 Mb on BTA14. Genes including KCNT1, MROH1, SHARPIN, TSSK5, CPSF1, HSF1, TONSL, DGAT1, SCX, and MAF1 were identified as positional candidate genes for MU. The findings of this study can be used for a better understanding of the genomic architecture underlying MU in Holstein cattle.

Prediction of body condition score throughout lactation by random regression test-day models.

Regular monitoring of body condition score (BCS) changes during lactation is a crucial management tool in dairy cattle; however, the current BCS measurements are often discontinuous and unevenly spaced in time. The aim of this study was to investigate the ability of random regression test-day models (RR-TDM) to predict BCS for the entire lactation in dairy cows even if the actual scoring is limited to one BCS record. The data consisted of test-day records of milk yield (MY), fat percentage (FP), protein percentage (PP) and BCS (based on a 9-point scale with unit increments; 1-9) collected from 2014 to 2022 in 128 herds in the Walloon Region of Belgium. In total, 20,698 test-day records on 2166 first-parity Holstein cows (2-12 with an average of 9.42 test-day records per cow) were available for MY, FP and PP; and 7985 records on the same animals (2-12 with an average of 3.68 records per cow) were available for BCS. To estimate the solutions, only one randomly selected BCS record per animal along with all her MY, FP and PP records were used, which were then used to predict BCS data (calibration set). The remaining BCS (1-11 with an average 2.86 BCS records per animal) were used to evaluate the goodness of the predictions (validation set). Multiple-trait RR-TDM was used to estimate (co)variance components through the average information restricted maximum likelihood (AI-REML) algorithm. Predicted BCS were grouped into nine classes as the original observed BCS used for comparison. Pearson correlation between the predicted and observed BCS, prediction error (PE), absolute prediction error (APE) and root mean squared prediction error (RMSE) were calculated. Mean (standard deviation; SD) BCS was 4.97 (1.01), 4.95 (1.07) and 4.98 (1.00) BCS units in the full, calibration and validation datasets, respectively. Pearson correlation between the observed and predicted BCS was 0.71, mean (SD) PE was 0.04 (0.52) BCS units, mean (SD) APE was 0.48 (0.53) BCS units and RMSE was 0.72 BCS units. These findings demonstrate the ability of RR-TDM to predict BCS for the entire lactation using a single BCS record along with available test-day records of milk yield and composition in Holstein dairy cows.

Single-step genome-wide association for selected milk fatty acids in Dual-Purpose Belgian Blue cows.

The aim of this study was to estimate genetic parameters and identify genomic regions associated with selected individual and groups of milk fatty acids (FA) predicted by milk mid-infrared spectrometry in Dual-Purpose Belgian Blue cows. The used data were 69,349 test-day records of milk yield, fat percentage, and protein percentage along with selected individual and groups FA of milk (g/dL milk) collected from 2007 to 2020 on 7,392 first-parity (40,903 test-day records), and 5,185 second-parity (28,446 test-day records) cows distributed in 104 herds in the Walloon Region of Belgium. Data of 28,466 SNPs, located on 29 Bos taurus autosomes (BTA), of 1,699 animals (639 males and 1,060 females) were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic best linear unbiased prediction approach. The proportion of genetic variance explained by each 25-SNP sliding window (with an average size of ~2 Mb) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for candidate genes. Average daily heritability estimated for the included milk FA traits ranged from 0.01 (C4:0) to 0.48 (C12:0) and 0.01 (C4:0) to 0.42 (C12:0) in the first and second parities, respectively. Genetic correlations found between milk yield and the studied individual milk FA, except for C18:0, C18:1 trans, C18:1 cis-9, were positive. The results showed that fat percentage and protein percentage were positively genetically correlated with all studied individual milk FA. Genome-wide association analyses identified 11 genomic regions distributed over 8 chromosomes [BTA1, BTA4, BTA10, BTA14 (4 regions), BTA19, BTA22, BTA24, and BTA26] associated with the studied FA traits, though those found on BTA14 partly overlapped. The genomic regions identified differed between parities and lactation stages. Although these differences in genomic regions detected may be due to the power of quantitative trait locus detection, it also suggests that candidate genes underlie the phenotypic expression of the studied traits may vary between parities and lactation stages. These findings increase our understanding about the genetic background of milk FA and can be used for the future implementation of genomic evaluation to improve milk FA profile in Dual-Purpose Belgian Blue cows.

Single-step genome-wide association analyses for selected infrared-predicted cheese-making traits in Walloon Holstein cows.

This study aimed to perform genome-wide association study to identify genomic regions associated with milk production and cheese-making properties (CMP) in Walloon Holstein cows. The studied traits were milk yield, fat percentage, protein percentage, casein percentage (CNP), calcium content, somatic cell score (SCS), coagulation time, curd firmness after 30 min from rennet addition, and titratable acidity. The used data have been collected from 2014 to 2020 on 78,073 first-parity (485,218 test-day records), 48,766 second-parity (284,942 test-day records), and 21,948 third-parity (105,112 test-day records) Holstein cows distributed in 671 herds in the Walloon Region of Belgium. Data of 565,533 single nucleotide polymorphisms (SNP), located on 29 Bos taurus autosomes (BTA) of 6,617 animals (1,712 males), were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic BLUP approach. The proportion of the total additive genetic variance explained by windows of 50 consecutive SNPs (with an average size of ∼216 KB) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for positional candidate genes. Heritability estimates for the studied traits ranged from 0.10 (SCS) to 0.53 (CNP), 0.10 (SCS) to 0.50 (CNP), and 0.12 (SCS) to 0.49 (CNP) in the first, second, and third parity, respectively. Genome-wide association analyses identified 6 genomic regions (BTA1, BTA14 [4 regions], and BTA20) associated with the considered traits. Genes including the SLC37A1 (BTA1), SHARPIN, MROH1, DGAT1, FAM83H, TIGD5, MROH6, NAPRT, ADGRB1, GML, LYPD2, JRK (BTA14), and TRIO (BTA20) were identified as positional candidate genes for the studied CMP. The findings of this study help to unravel the genomic background of a cow's ability for cheese production and can be used for the future implementation and use of genomic evaluation to improve the cheese-making traits in Walloon Holstein cows.

Genome-wide association study and functional annotation analyses for nitrogen efficiency index and its composition traits in dairy cattle.

The aims of this study were (1) to identify genomic regions associated with a N efficiency index (NEI) and its composition traits and (2) to analyze the functional annotation of identified genomic regions. The NEI included N intake (NINT1), milk true protein N (MTPN1), milk urea N yield (MUNY1) in primiparous cattle, and N intake (NINT2+), milk true protein N (MTPN2+), and milk urea N yield (MUNY2+) in multiparous cattle (2 to 5 parities). The edited data included 1,043,171 records on 342,847 cows distributed in 1,931 herds. The pedigree consisted of 505,125 animals (17,797 males). Data of 565,049 SNPs were available for 6,998 animals included in the pedigree (5,251 females and 1,747 males). The SNP effects were estimated using a single-step genomic BLUP approach. The proportion of the total additive genetic variance explained by windows of 50 consecutive SNPs (with an average size of about 240 kb) was calculated. The top 3 genomic regions explaining the largest rate of the total additive genetic variance of the NEI and its composition traits were selected for candidate gene identification and quantitative trait loci (QTL) annotation. The selected genomic regions explained from 0.17% (MTPN2+) to 0.58% (NEI) of the total additive genetic variance. The largest explanatory genomic regions of NEI, NINT1, NINT2+, MTPN1, MTPN2+, MUNY1, and MUNY2+ were Bos taurus autosome 14 (1.52-2.09 Mb), 26 (9.24-9.66 Mb), 16 (75.41-75.51 Mb), 6 (8.73-88.92 Mb), 6 (8.73-88.92 Mb), 11 (103.26-103.41 Mb), 11 (103.26-103.41 Mb). Based on the literature, gene ontology, Kyoto Encyclopedia of Genes and Genomes, and protein-protein interaction, 16 key candidate genes were identified for NEI and its composition traits, which are mainly expressed in the milk cell, mammary, and liver tissues. The number of enriched QTL related to NEI, NINT1, NINT2+, MTPN1, and MTPN2+ were 41, 6, 4, 11, 36, 32, and 32, respectively, and most of them were related to the milk, health, and production classes. In conclusion, this study identified genomic regions associated with NEI and its composition traits, and identified key candidate genes describing the genetic mechanisms of N use efficiency-related traits. Furthermore, the NEI reflects not only its composition traits but also the interactions among them.

Validating genomic prediction for nitrogen efficiency index and its composition traits of Holstein cows in early lactation.

Nitrogen (N) use efficiency (NUE) is an economically important trait for dairy cows. Recently, we proposed a new N efficiency index (NEI), that simultaneously considers both NUE and N pollution. This study aimed to validate the genomic prediction for NEI and its composition traits and investigate the relationship between SNP effects estimated directly from NEI and indirectly from its composition traits. The NEI composition included genomic estimated breeding value of N intake (NINT), milk true protein N (MTPN) and milk urea N yield. The edited data were 132,899 records on 52,064 cows distributed in 773 herds. The pedigree contained 122,368 animals. Genotypic data of 566,294 SNP was available for 4514 individuals. A total of 4413 cows (including 181 genotyped) and 56 bulls (including 32 genotyped) were selected as the validation populations. The linear regression method was used to validate the genomic prediction of NEI and its composition traits using best linear unbiased prediction (BLUP) and single-step genomic BLUP (ssGBLUP). The mean theoretical accuracies of validation populations obtained from ssGBLUP were higher than those obtained from BLUP for both NEI and its composition traits, ranging from 0.57 (MTPN) to 0.72 (NINT). The highest mean prediction accuracies for NEI and its composition traits were observed for the genotyped cows estimated under ssGBLUP, ranging from 0.48 (MTPN) to 0.66 (NINT). Furthermore, the SNP effects estimated from NEI composition traits, multiplied by the relative weight were the same as those estimated directly from NEI. This study preliminary showed that genomic prediction can be used for NEI, however, we acknowledge the need for further validation of this result in a larger dataset. Moreover, the SNP effects of NEI can be indirectly calculated using the SNP effects estimated from its composition traits. This study provided a basis for adding genomic information to establish NEI as part of future routine genomic evaluation programs.

Genome-wide association study for selected cheese-making properties in Dual-Purpose Belgian Blue cows.

This study aimed to estimate genetic parameters and identify genomic region(s) associated with selected cheese-making properties (CMP) in Dual-Purpose Belgian Blue (DPBB) cows. Edited data were 46,301 test-day records of milk yield, fat percentage, protein percentage, casein percentage, milk calcium content (CC), coagulation time (CT), curd firmness after 30 min from rennet addition (a30), and milk titratable acidity (MTA) collected from 2014 to 2020 on 4,077 first-parity (26,027 test-day records), and 3,258 second-parity DPBB cows (20,274 test-day records) distributed in 124 herds in the Walloon Region of Belgium. Data of 28,266 SNP, located on 29 Bos taurus autosomes (BTA) of 1,699 animals were used. Random regression test-day models were used to estimate genetic parameters through the Bayesian Gibbs sampling method. The SNP solutions were estimated using a single-step genomic BLUP approach. The proportion of the total additive genetic variance explained by windows of 25 consecutive SNPs (with an average size of ∼2 Mb) was calculated, and regions accounting for at least 1.0% of the total additive genetic variance were used to search for candidate genes. Heritability estimates for the included CMP ranged from 0.19 (CC) to 0.50 (MTA), and 0.24 (CC) to 0.41 (MTA) in the first and second parity, respectively. The genetic correlation estimated between CT and a30 varied from -0.61 to -0.41 and from -0.55 to -0.38 in the first and second lactations, respectively. Negative genetic correlations were found between CT and milk yield and composition, while those estimated between curd firmness and milk composition were positive. Genome-wide association analyses results identified 4 genomic regions (BTA1, BTA3, BTA7, and BTA11) associated with the considered CMP. The identified genomic regions showed contrasting results between parities and among the different stages of each parity. It suggests that different sets of candidate genes underlie the phenotypic expression of the considered CMP between parities and lactation stages of each parity. The findings of this study can be used for future implementation and use of genomic evaluation to improve the cheese-making traits in DPBB cows.

Defining a nitrogen efficiency index in Holstein cows and assessing its potential effect on the breeding program of bulls.

The purposes of this study were (1) to explore the relationship between 3 milk mid-infrared predicted features including nitrogen intake (NINT), milk true protein N (MTPN), and milk urea-N yield (MUNY); (2) to integrate these 3 features into an N efficiency index (NEI) and analyses approximate genetic correlations between the NEI and 37 traits (indices) of interest; and (3) to assess the potential effect of including the NEI into breeding programs of bulls. The edited data were 1,043,171 test-day records on 342,847 cows in 1,931 herds and 143,595 test-day records on 53,660 cows in 766 herds used for estimating breeding values (EBV) and variance components, respectively. The used records were within 5 to 50 d in milk. The records were grouped into primiparous and multiparous. The genetic parameters for the included mid-infrared features and EBV of the animals included in the pedigree were estimated using a multiple-trait repeatability animal model. Then, the EBV of the NINT, MTPN, MUNY were integrated into the NEI using a selection index assuming weights based on the N partitioning. The approximate genetic correlations between the NEI and 37 traits of interest were estimated using the EBV of the selected bulls. The bulls born from 2011 to 2014 with NEI were selected and the NEI distribution of these bulls having EBV for the 8 selected traits (indices) was checked. The heritability and repeatability estimates for NINT, MTPN, and MUNY ranged from 0.09 to 0.13, and 0.37 to 0.65, respectively. The genetic and phenotypic correlations between NINT, MTPN, and MUNY ranged from -0.31 to 0.87, and -0.02 to 0.42, respectively. The NEI ranged from -13.13 to 12.55 kg/d. In total, 736 bulls with reliability ≥0.50 for all included traits (NEI and 37 traits) and at least 10 daughters distributed in at least 10 herds were selected to investigate genetic aspects of the NEI. The NEI had positive genetic correlations with production yield traits (0.08-0.46), and negative genetic correlations with the investigated functional traits and indices (-0.71 to -0.07), except for the production economic index and functional type economic index. The daughters of bulls with higher NEI had lower NINT and MUNY, and higher MTPN. Furthermore, 26% of the bulls (n = 50) with NEI born between 2011 to 2014 had higher NEI and global economic index than the average in the selected bulls. Finally, the developed NEI has the advantage of large-scale prediction and therefore has the potential for routine application in dairy cattle breeding in the future.

Genetic analysis of milk urea concentration and its genetic relationship with selected traits of interest in dairy cows.

The aim of this study was to estimate genetic parameters of milk urea concentration (MU) and its genetic correlations with milk production traits, longevity, and functional traits in the first 3 parities in dairy cows. The edited data set consisted in 9,107,349 MU test-day records from the first 3 parities of 560,739 cows in 2,356 herds collected during the years 1994 to 2020. To estimate the genetic parameters of MU, data of 109 randomly selected herds, with a total of 770,016 MU test-day records, were used. Genetic parameters and estimated breeding values were estimated using a multiple-trait (parity) random regression model. Herd-test-day, age-year-season of calving, and days in milk classes (every 5 d as a class) were used as fixed effects, whereas effects of herd-year of calving, permanent environment, and animal were modeled using random regressions and Legendre polynomials of order 2. The average daily heritability and repeatability of MU during days in milk 5 to 365 in the first 3 parities were 0.19, 0.22, 0.20, and 0.48, 0.48, 0.47, respectively. The mean genetic correlation estimated among MU in the first 3 parities ranged from 0.96 to 0.97. The average daily estimated breeding values for MU of the selected bulls (n = 1,900) ranged from -9.09 to 7.37 mg/dL. In the last 10 yr, the genetic trend of MU has gradually increased. The genetic correlation between MU and 11 traits of interest ranged from -0.28 (milk yield) to 0.28 (somatic cell score). The findings of this study can be used as the first step for development of a routine genetic evaluation for MU and its inclusion into the genetic selection program in the Walloon Region of Belgium.

Genome-wide association for metabolic clusters in early-lactation Holstein dairy cows.

The aim of this study was to detect the genomic region or regions associated with metabolic clusters in early-lactation Holstein cows. This study was carried out in 2 experiments. In experiment I, which was carried out on 105 multiparous Holstein cows, animals were classified through k-means clustering on log-transformed and standardized concentrations of blood glucose, insulin-like growth factor I, free fatty acids, and ß-hydroxybutyrate at 14 and 35 d in milk (DIM), into metabolic clusters, either balanced (BAL) or other (OTR). Forty percent of the animals were categorized in the BAL group, and the remainder were categorized as OTR. The cows were genotyped for a total of 777,962 SNP. A genome-wide association study was performed, using a case-control approach through the GEMMA software, accounting for population structure. We found 8 SNP (BTA11, BTA23, and BTAX) associated with the predicted metabolic clusters. In experiment II, carried out on 4,267 second-parity Holstein cows, milk samples collected starting from the first week until 50 DIM were used to determine Fourier-transform mid-infrared (FT-MIR) spectra and subsequently to classify the animals into the same metabolic clusters (BAL vs. OTR). Twenty-eight percent of the animals were categorized in the BAL group, and the remainder were classified in the OTR category. Although daily milk yield was lower in BAL cows, we found no difference in daily fat- and protein-corrected milk yield in cows from the BAL metabolic cluster compared with those in the OTR metabolic cluster. In the next step, a single-step genomic BLUP was used to identify the genomic region(s) associated with the predicted metabolic clusters. The results revealed that prediction of metabolic clusters is a highly polygenic trait regulated by many small-sized effects. The region of 36,258 to 36,295 kb on BTA27 was the highly associated region for the predicted metabolic clusters, with the closest genes to this region (ANK1 and miR-486) being related to hematopoiesis, erythropoiesis, and mammary gland development. The heritability for metabolic clustering was 0.17 (SD 0.03), indicating that the use of FT-MIR spectra in milk to predict metabolic clusters in early-lactation across a large number of cows has satisfactory potential to be included in genetic selection programs for modern dairy cows.

Adding behavior traits to select for heat tolerance in dairy cattle.

The increase in periods of heat waves leads to an increase in heat stress events in dairy cattle leading to welfare issues, production losses, and health issues. However, the low frequency of milk recording data makes genetic evaluation for heat tolerance still a challenge. A possible solution could be to add behavior data captured through sensors which are recorded permanently, mostly reported on a daily basis. The objective of this study was to evaluate the potential gain of adding behavior traits as proxies for genetic evaluation of heat tolerance. Behavior traits including activity time (ACT), rumination time (RUM), and eating time (EAT) were recorded for 453 Holstein cows equipped with SenseHub (Allflex Livestock Intelligence) collars from October 2019 to July 2022 in 6 herd located in the Walloon Region of Belgium. A multitrait reaction norm model based on separate temperature and humidity index (THI) thresholds was used. Results showed that behavior traits present not only interesting characteristics for genetic evaluation of heat tolerance but also for heat stress detection in farms. Indeed, sensors allow recording of behavior for all events of heat stress in lactating and nonlactating animals. Moderate heritability values were also found for the behavior traits (0.14 for ACT, 0.19 for RUM, and 0.12 for EAT), and a high ratio between the general and thermotolerance additive genetic variances was obtained. In addition, positive correlations of thermotolerance for ACT and EAT with thermotolerance for milk production (fat- and protein-corrected milk: 0.45 and 0.28, respectively) and negative genetic correlations of thermotolerance for ACT with somatic cells (somatic cell score: -0.39) were estimated. The genetic correlation matrix allows us to explain a high part of the variation for the reaction to heat stress of 2 economic traits (fat- and protein-corrected milk: 59% and somatic cell score: 31%) based on behavior data. Based on these results, behavior traits could be used to assess heat stress in nonlactating cattle for which the number of genetic evaluations for heat tolerance is still limited.

Association between dry period length and lactation performance, lactation curve, calf birth weight, and dystocia in Holstein dairy cows in Iran.

In this study, 65,971 lactations on 41,842 cows in 64 herds were used to determine the association between dry period length (DPL) and lactation performance, lactation curve, calf birth weight, and the incidence of calving difficulty during the subsequent parity in Holstein dairy cows in Iran. The length of the dry period was classified into 7 categories: 0 to 35d, 36 to 50d, 51 to 60d, 61 to 70d, 71 to 85d, 86 to 110d, and 111 to 160d. Cows with the standard DPL (51 to 60d) produced more 305-d milk, fat, and protein over the next lactation compared with those with shorter dry periods. Shorter dry periods (0 to 35d and 36 to 50d) were associated with lower initial milk yield, steeper inclining and declining slopes of the lactation curve, and higher milk persistency compared with dry period length of 51 to 60d. Peak lactation was achieved later in cows with 0- to 35-d and 36- to 50-d dry period length than in those with dry period length of 51 to 60d. We also observed a relationship between DPL and calf birth weight: smaller calf birth weight was recorded with a dry period of 51 to 60d compared with longer dry periods. The incidence of calving difficulty did not differ in cows with 51- to 60-d dry period compared with cows with 0- to 35-d and 36- to 50-d dry periods. In conclusion, the results of this study did not support previous findings that suggested a shorter dry period could be beneficial to dairy production.

Prestorage in ovo injection of biological buffers: an approach to improve hatchability in long-term stored eggs.

A hypothesis was tested that the in ovo injection of biological buffers may reinforce the buffering capacity of albumen, thereby withstanding the increase in albumen pH during storage and improving hatchability and chick quality in long-term stored eggs. Hatching eggs (n = 2,420) were randomly assigned to 11 treatment groups (4 replicates of 55 eggs each) and injected (d 1) with distilled water, 25 or 50 mM HEPES (H25 and H50), Bicine (B25 and B50), Tris (T25 and T50), and Bis-Tris-propane (BTP25 and BTP50) solutions or were not injected (intact: control; or pricked with a needle: N). The eggs were then stored for 14 d during which the egg internal characteristics were evaluated at 1, 2, 3, 4, 5, 8, and 13 d of storage (n = 924 in total) and the remaining eggs (n = 1,496) were incubated. A decrease in albumen pH was found for H25, H50, B50, and BTP25 groups from 2 through 5 d postinjection. Eggs receiving H25, H50, and B50 recorded a higher albumen index (at 13 d of storage) and Haugh unit (between 8 and 13 d of storage) compared with the control. Interestingly, the hatchability of fertile eggs was influenced by the treatment effect (P = 0.0001) where the eggs receiving H25 (88.3%), H50 (88.9%), B50 (88.4%), and BTP25 (87.6%) recorded higher values than that of control (82.1%), associated with a decreased early embryonic mortality rate (P < 0.0001). In ovo injection of Tris buffer, however, profoundly decreased the hatchability (47.2 and 29.0% for T25 and T50, respectively) and percentage of first-grade chicks (67.5 and 63.6% for T25 and T50, respectively) compared with the control (90.1%). In conclusion, prestorage in ovo injection of H25, H50, B50, and BTP25 improved hatchability in long-term stored eggs in which a decreased albumen pH during the d 2 through 5 of storage period might be involved.

Oral exposure of broiler breeder hens to extra thyroxine modulates early adaptive immune responses in progeny chicks.

Based on the findings of a recent study suggesting a decreased cold-induced ascites incidence in broiler progeny from hyperthyroid (HYPER) breeder hens, and a controversy on the effects of hyperthyroidism on immunocompetence, the present study was conducted to determine the probable adverse effect of induced maternal hyperthyroidism on immune function in progeny chicks. Breeder hens (n = 88) were randomly allotted to the control or HYPER groups and received common or thyroxine (T4)-added (1 mg/L) water, respectively. The hens were artificially inseminated, and hatching eggs (n = 924) were incubated. Thereafter, the male hatchlings (n = 288) were reared for 42 d, and several cellular and humoral immune responses were evaluated at standard or low ambient temperature. Prevaccination antibody titers to Newcastle disease, infectious bronchitis, and infectious bursal disease virus were higher in HYPER chicks during 1 wk of age, although not different in their dams. For primary response to SRBC administered at 7 d of age, HYPER chicks recorded higher total, IgM (d 14), and IgG (d 21) anti-SRBC antibody titers. Higher cutaneous basophilic hypersensitivity response in HYPER chicks (d 10) was not observed at 35 d of age. Carbon clearance assay showed no difference, but in vitro lymphoproliferative response to concanavalin A was higher in 19-d-old HYPER chicks, independent of temperature treatment. An increase in lymphocyte percentage coincided with a decreased heterophil percentage and heterophil to lymphocyte ratio (d 14) in the HYPER group. The weight of lymphoid organs in progeny was not influenced by the oral exposure of dams to extra T4. Independent of T4 treatment, cold exposure was generally associated with decreased immune functions at early stages. The data suggested that oral exposure of broiler breeder hens to 1 mg/L of T4 not only had no adverse effect on immune function, but also modulated early adaptive immune responses in progeny chicks for which the causal mechanisms remain to be unraveled.

Genetic relationship of conformation traits with average somatic cell score at 150 and 305 days in milk in Holstein cows of Iran.

Genetic, environmental, and phenotypic correlations among average somatic cell score (SCS) at different stages of lactation and conformation traits were estimated. Data consisted of the lactational average of SCS at 150 (SCS(150)) and 305 (SCS(305)) d in milk and 19 conformation traits recorded on 57,154 primiparous Holstein cows, that calved from 1996 to 2009 in 119 herds in Iran. Variance components were estimated using the restricted maximum likelihood procedure based on multiple-trait animal models. Udder depth (-0.32), fore udder attachment (-0.22), and udder width (0.34) showed moderate genetic correlation with SCS(150). Heart girth (0.17), body depth (0.14), chest width (0.26), and angularity (0.19), showed modest genetic correlation with SCS(150). The estimated heritabilities for SCS(150) and SCS(305) were 0.06 and 0.08, respectively. The heritability of the conformation traits ranged from 0.09 to 0.29. Genetic and environmental correlations between SCS(150) and SCS(305) were very high (means ± SE; 0.99±0.01 and 0.89±0.01, respectively), which indicates that recording SCS over a shorter period of lactation is an alternative approach for involving many herds in SCS data collection. The low heritability of SCS indicated that indirect selection for some of udder and body traits might be helpful to reduce the SCS. Additionally, selection for udder traits may help reduce SCS in developing countries where SCS data are sparsely recorded.

Using an incomplete gamma function to quantify the effect of dystocia on the lactation performance of Holstein dairy cows in Iran.

The aim of the present study was to estimate the effect of dystocia on lactation performance, using an incomplete gamma function. Data from March 2000 to April 2009 comprising 100,628 lactations of 65,421 cows in 204 dairy herds collected by the Animal Breeding Center of Iran were used. Of 100,628 births, 91.8% required no assistance, whereas 8.2% required assistance of some sort. Factors associated with the presence of dystocia were calving season, calving year, herd, calf sex, parity, and age of dam. Peak yield for primiparous cows with dystocia at calving occurred on d 87.2 [standard error (SE) 0.47], and for primiparous cows with easy calving, the peak of lactation was on d 83.3 (0.25). Peak yield was lowered by 0.39 (SE 0.07), 2.20 (SE 0.15), 2.22 (SE 0.21), and 2.54 (SE 0.32) kg for cows with incidence of dystocia compared with normal cows in parity 1 to 4, respectively. Dystocia was associated with decreased 305-d lactation performance in all parities, mostly in early lactation. Although more difficult births occurred in heifer calvings, loss in lactation performance was greater in second or later lactations following a difficult birth.

Does preincubational in ovo injection of buffers or antioxidants improve the quality and hatchability in long-term stored eggs?

A hypothesis was tested that providing buffer solutions or antioxidants during egg storage may help embryos in combating the harmful effect of longer holding periods. Hatching eggs were obtained from a breeder flock (35 wk) and stored for 13 d before setting. In experiment 1, the eggs were injected (d 4) with bicarbonate buffer solution (BBS) or PBS. For experiment 2, l-carnitine (LC), vitamin E (VE), and vitamin C (VC) were injected (d 7) at 3 different doses. The egg internal quality characteristics were evaluated at 2-d intervals after injection and the remaining eggs were incubated for 21 d under standard conditions. At 21 d, hatchability was recorded and unhatched eggs were broken open to assess the fertility and stage of embryonic mortality. No differences were noted in albumen pH due to using buffer solutions or antioxidants except for a decreased pH at 2 d postinjection of the high dose of VC (75 mg). In ovo injection of BBS increased the albumen index and Haugh unit at d 6 postinjection; however, the response to PBS was not different from that in the control group. In ovo injection of antioxidants did not influence the albumen index, Haugh unit, and yolk index; however, the yolk percentage was partly affected. Irrespective of the dosage, hatchability was greatly decreased following in ovo injection of buffers or antioxidants (as low as 4.3 vs. 87.5% in control), with the highest mortality percentage recorded at early embryonic stages (d 0 to 6). Data suggested that, despite improvement in certain egg internal qualities, preincubational in ovo injection of BBS, PBS, LC, VE, or VC was associated with a profoundly decreased hatchability for which the underlying mechanism(s) remain(s) to be clarified.

Maternal hyperthyroidism is associated with a decreased incidence of cold-induced ascites in broiler chickens.

A hypothesis was tested that providing the breeder hens with exogenous thyroxine (T(4)) would help their offspring to better survive the ascites-inducing condition during the growing period. In total, 132 broiler breeder hens were randomly assigned to one of 3 treatments: control (CON), hypothyroid [HYPO; 6-N-propyl-2-thiouracil (PTU)-treated], and hyperthyroid (HYPER; T(4)-treated). The hens were artificially inseminated, and the hatching eggs (n = 1,320) were incubated. No eggs in the HYPO group hatched. The 1-d-old male chicks (n = 288) from other groups were reared for 42 d under standard or low ambient temperature to induce ascites. Blood samples were drawn from the hens, embryos, and broilers for determination of T(4) and triiodothyronine (T(3)). The hematocrit was also determined in broilers. The PTU-treated hens had an increased BW along with lower plasma T(3) and T(4) concentrations. Plasma T(4) was higher in the HYPER hens compared with CON hens, but T(3) concentration was not different between these groups. The fertility rate was not affected by either hypo- or hyperthyroidism. The embryos in the HYPO group had lower plasma T(3) and T(4) concentrations at d 18 of embryonic development and internal pipping. Higher plasma T(4) was recorded in the HYPER birds at internal pipping, although plasma T(3) concentration was not affected at this stage. Maternal hyperthyroidism decreased the overall incidence of ascites in the cold-exposed chickens (10.0 vs. 33.4% for HYPER and CON groups, respectively). Although the effect of maternal PTU or T(4) treatment on plasma thyroid hormones and on the right ventricle-to-total ventricular weight ratio in the broilers was not significant, the cold-exposed healthy CON chicks showed higher hematocrit values, compared with the HYPER birds. It was concluded that maternal hyperthyroidism could decrease the incidence of cold-induced ascites in broiler chickens; however, probable causal mechanisms remain to be elucidated.

Prediction of first test day milk yield using historical records in dairy cows.

The transition between two lactations remains one of the most critical periods during the productive life of dairy cows. In this study, we aimed to develop a model that predicts the milk yield of dairy cows from test day milk yield data collected in the previous lactation. In the past, data routinely collected in the context of herd improvement programmes on dairy farms have been used to provide insights in the health status of animals or for genetic evaluations. Typically, only data from the current lactation is used, comparing expected (i.e., unperturbed) with realised milk yields. This approach cannot be used to monitor the transition period due to the lack of unperturbed milk yields at the start of a lactation. For multiparous cows, an opportunity lies in the use of data from the previous lactation to predict the expected production of the next one. We developed a methodology to predict the first test day milk yield after calving using information from the previous lactation. To this end, three random forest models (nextMILKFULL, nextMILKPH, and nextMILKP) were trained with three different feature sets to forecast the milk yield on the first test day of the next lactation. To evaluate the added value of using a machine-learning approach against simple models based on contemporary animals or production in the previous lactation, we compared the nextMILK models with four benchmark models. The nextMILK models had an RMSE ranging from 6.08 to 6.24 kg of milk. In conclusion, the nextMILK models had a better prediction performance compared to the benchmark models. Application-wise, the proposed methodology could be part of a monitoring tool tailored towards the transition period. Future research should focus on validation of the developed methodology within such tool.

Preparations of PAN-based adsorbers for separation of cesium and cobalt from radioactive wastes.

Ion-exchange adsorbers are widely used for radioisotope separation, as well as for the removal of hazardous fission products from aqueous waste prior to discharge to the environment. Inorganic exchangers are of particular interest because of their resistance to radiolytic damage and selectivity for specific fission products. Composite inorganic-organic adsorbers represent a group of inorganic ion exchangers modified by using binding organic material, polyacrylonitrile, for preparation of larger size particles with higher granular strength. At the same time, kinetics of ion exchange and sorption capacity of such composite adsorbers are not influenced by the binding polymer. The contents of active component in composite adsorber were varied over a very broad range of 5-95% of the dry weight of the composite adsorber, and tested for separation and concentration of various stimulated wastes. Three different inorganic sorbents, granular hexacyanoferrate-based ion exchanger, were developed for the removal of Cs and Co ions from waste solutions containing different complexing agents as detergents. Radiation and thermal stability studies show that these adsorbents can be used for medium-active waste treatment.