Heat stress on breeding value prediction for milk yield and composition of a Brazilian Holstein cattle population.

Due to the high milk production of Holstein cows, many countries have chosen to import semen to improve local dairy herds. This strategy would be more effective if this semen was used in the same environment conditions in which the bulls were selected. If the effect of genotype by environment (G × E) interaction is not considered, the estimated breeding values (EBVs) may vary, potentially reducing the selection response. We evaluate the impact of heat stress on selection for milk yield and composition of Holstein cows using random regression models. To verify the interference of heat stress in milk yield (MY) and composition traits (fat, protein, total saturated, and total unsaturated fatty acids content in milk), temperature-humidity index (THI) on test-day milk records was used. The threshold value to divide the environments using test-day information from Brazilian Holstein cows was 72 units of THI, i.e., < 72 represented no heat stress and > 72 represented heat stress. Legendre polynomials of second-order (Leg 2) model and two lactation points (33 and 122 DIM) were used to estimate heritabilities and EBVs for five important dairy traits. The heritabilities of milk components and fatty acids were low (0.09-0.29), regardless of lactation period and degree of heat stress, with the exception of protein content (0.30-0.35). Fat content was the only milk component that was reduced according to the degree of heat stress and lactation period. The EBVs tended to decrease in heat stress conditions, thus animals with high genetic potential demonstrated evidence of G × E interaction. However, acclimatization of dairy cows to heat stress in the farm production systems may have been responsible for the low differences among genetic parameters and EBVs with and without heat stress found in this study.

Comparison of Marker Effects and Breeding Values at Two Levels at THI for Milk Yield and Quality Traits in Brazilian Holstein Cows.

Genomic tools can help in the selection of animals genetically resistant to heat stress, especially the genome-wide association studies (GWAS). The objective of this study was to compare the variance explained by SNPs and direct genomic breeding values (DGVs) at two levels of a temperature and humidity index (THI). Records of milk yield (MY), somatic cell score (SCS), and percentages of casein (CAS), saturated fatty acids (SFA), and unsaturated fatty acids (UFA) in milk from 1157 Holstein cows were used. Traditional breeding values (EBV) were determined in a previous study and used as pseudo-phenotypes. Two levels of THI (heat comfort zone and heat stress zone) were used as environments and were treated as "traits" in a bi-trait model. The GWAS was performed using the genomic best linear unbiased prediction (GBLUP) method. Considering the top 50 SNPs, a total of 36 SNPs were not common between environments, eight of which were located in gene regions related to the evaluated traits. Even for those SNPs that had differences in their explained variances between the two environments, the differences were very small. The animals showed virtually no rank order, with rank correlation values of 0.90, 0.88, 1.00, 0.88, and 0.97 for MY, CAS, SCS, SFA, and UFA, respectively. The small difference between the environments studied can be attributed to the small difference in the pseudo-phenotypes used between the environments, on-farm acclimation, the polygenic nature of the traits, and the THI values studied near the threshold between comfort and heat stress. It is recommended that future studies be conducted with a larger number of animals and at more extreme THI levels.

Genetic parameters for milk yield and quality traits of Brazilian Holstein cows as a function of temperature and humidity index.

Measurements of milk yield (MY), somatic cell score (SCS), percentage of fat (FP), protein (PP), lactose (LP), casein (CP) and percentage of palmitic (C16:0), stearic (C18:0), oleic (C18:1), total saturated (SFA), unsaturated (UFA), monounsaturated (MUFA) and polyunsaturated (PUFA) fatty acids in milk from 5,224 Holstein cows were evaluated as a function of a temperature and humidity index (THI). Legendre orthogonal polynomials from second to seventh order were tested. The best fit order for MY, PP and C18:0 was the third, whereas the second for all other traits. The heritability estimates decreased for MY (0.31 to 0.14), FP (0.28 to 0.16), LP (0.43 to 0.30), SCS (0.14 to 0.09), SFA (0.33 to 0.22) and C16:0 (0.31 to 0.26), whereas increased for CP (0.32 to 0.42), MUFA (0.08 to 0.13), UFA (0.07 to 0.11) and C18:1 (0.07 to 0.11) as the THI level increased. For PP, heritabilities (0.26 to 0.39) presented larger values in intermediate THI. For PUFA and C18:0, heritabilities were approximately constant (0.13 to 0.14 and 0.15, respectively). However, the greatest variations may have been the result of the limitations of Legendre polynomials at the extreme points of the curve, and the pattern of heritabilities curves was approximately constant for the evaluated traits. Spearman's rank correlations between breeding values in extreme THI levels were greater than 0.80 for all traits considering all animals, only cows and only bulls. When considering the top 1% and the top 50% animals (only cows, only bulls and all), Spearman correlations smaller than 0.70 were found, suggesting reranking of the animals. Although there was little variation in the variance components over THI, it is possible that there is no heat stress in the animals studied, because, on average, there was no great impact of the thermal load on the traits. One possible explanation is the use of herds with little climatic difference among herds, as well as the use of fans and sprinklers into the barns. However, the THI levels may be important factors in the selection process, as reranking of animals was verified.

Month-wise variation and prediction of bulk tank somatic cell count in Brazilian dairy herds and its impact on payment based on milk quality.

BACKGROUND: Payment programs based on milk quality (PPBMQ) are used in several countries around the world as an incentive to improve milk quality. One of the principal milk parameters used in such programs is the bulk tank somatic cell count (BTSCC). In this study, using data from an average of 37,000 farms per month in Brazil where milk was analyzed, BTSCC data were divided into different payment classes based on milk quality. Then, descriptive and graphical analyses were performed. The probability of a change to a worse payment class was calculated, future BTSCC values were predicted using time series models, and financial losses due to the failure to reach the maximum bonus for the payment based on milk quality were simulated. RESULTS: In Brazil, the mean BTSCC has remained high in recent years, without a tendency to improve. The probability of changing to a worse payment class was strongly affected by both the BTSCC average and BTSCC standard deviation for classes 1 and 2 (1000-200,000 and 201,000-400,000 cells/mL, respectively) and only by the BTSCC average for classes 3 and 4 (401,000-500,000 and 501,000-800,000 cells/mL, respectively). The time series models indicated that at some point in the year, farms would not remain in their current class and would accrue financial losses due to payments based on milk quality. CONCLUSION: The BTSCC for Brazilian dairy farms has not recently improved. The probability of a class change to a worse class is a metric that can aid in decision-making and stimulate farmers to improve milk quality. A time series model can be used to predict the future value of the BTSCC, making it possible to estimate financial losses and to show, moreover, that financial losses occur in all classes of the PPBMQ because the farmers do not remain in the best payment class in all months.

Adulteration identification in raw milk using Fourier transform infrared spectroscopy.

Adulteration of milk is a common practice that concerns regulatory agencies, industry, and the population. Despite the growing need for checking adulteration, the current methods employed generally have low performance and are highly dependent on manual labor. This study aims to calibrate and validate a compact equipment (MilkoScan FT1) that adopts a Fourier transform infrared spectroscopy methodology to monitor adulteration in raw milk. Almost 2500 milk samples were used for reference spectrum construction and 1650 samples were used to validate the identification of the following five most commonly used adulterants (at three different concentrations each): (1) cornstarch, (2) sodium bicarbonate, (3) sodium citrate, (4) formaldehyde, and (5) saccharose, plus the additions of two levels of water or whey. To define the calibration with the best performance in milk adulteration identification, 12 calibrations involving 8, 10, 12, 14, 16, or 18 factors, with one or two outlier eliminations, were developed. The results of sensitivity and specificity analyses, as well as Kruskal-Wallis and Dunn multiple comparison tests, revealed that the calibration that best identified the adulterants was the one involving 14 factors, with a single elimination of outliers, exhibiting for all adulterants simultaneously, 84% sensitivity and 100% specificity. The calibration showed excellent sensitivity to cornstarch (>98%), sodium bicarbonate (100%), sodium citrate (99%), and formaldehyde (>84%), indicating that this calibration has good capacity for adulteration detection. Thus, this methodology is a viable option for the dairy industry to identify adulteration of raw milk.

Do Milk Samples Stored for 12 Days after Collection Exhibit a Change in Composition Related to the Initial Bacterial Load?

Total bacterial count (TBC) is a tool used to assess milk quality and is associated with not only the initial sample contamination but also the sample storage time and temperature. Several countries have reported milk samples with a high TBC, and the influence of TBC on milk preservation remains unclear. Thus, the aim of this study was to evaluate the impact of the initial bacterial contamination level on the macrocomponents and somatic cell count (SCC) of raw milk samples preserved with bronopol and maintained at two storage temperatures (7 and 25°C) for up to 12 days. Thus, we collected milk samples from 51 dairy farms, which were divided into two groups according to the initial bacterial load: low TBC (<100,000 CFU/ml) and high TBC (≥100,000 CFU/ml). We analyzed the sample composition for protein, fat, total solids, lactose, milk urea nitrogen, and the SCC. We did not observe an effect from TBC and storage time and temperature on the concentration of protein, fat, total solids, and lactose. SCC changes were not observed for samples maintained under refrigeration (7°C); however, samples maintained at room temperature (25°C) exhibited a decrease in the SCC beginning on day 6 of storage. For milk urea nitrogen, values increased when the samples were maintained at room temperature, beginning on the ninth storage day. Samples with the preservative bronopol added and maintained under refrigeration may be analyzed up to 12 days after collection, regardless of the milk microbial load.

Reaction norm model to describe environmental sensitivity across first lactation in dairy cattle under tropical conditions.

Reaction norm models have been widely used to study genotype by environment interaction (G × E) in animal breeding. The objective of this study was to describe environmental sensitivity across first lactation in Brazilian Holstein cows using a reaction norm approach. A total of 50,168 individual monthly test day (TD) milk yields (10 test days) from 7476 complete first lactations of Holstein cattle were analyzed. The statistical models for all traits (10 TDs and for 305-day milk yield) included the fixed effects of contemporary group, age of cow (linear and quadratic effects), and days in milk (linear effect), except for 305-day milk yield. A hierarchical reaction norm model (HRNM) based on the unknown covariate was used. The present study showed the presence of G × E in milk yield across first lactation of Holstein cows. The variation in the heritability estimates implies differences in the response to selection depending on the environment where the animals of this population are evaluated. In the average environment, the heritabilities for all traits were rather similar, in range from 0.02 to 0.63. The scaling effect of G × E predominated throughout most of lactation. Particularly during the first 2 months of lactation, G × E caused reranking of breeding values. It is therefore important to include the environmental sensitivity of animals according to the phase of lactation in the genetic evaluations of Holstein cattle in tropical environments.

Aflatoxin M1 in raw milk from different regions of São Paulo state--Brazil.

A total of 635 raw milk samples from 45 dairy farms, from three regions of São Paulo state - Brazil, were evaluated during 15 months for aflatoxin M1 (AFM1). AFM1 was determined by high performance liquid chromatograph with fluorescence detection. AFM1 was detected (>0.003 µg kg(-1)) in 72.9%, 56.3% and 27.5% of the samples from Bauru, Araçatuba and Vale do Paraíba regions, respectively. The mean AFM1 contamination considering all the samples was 0.021 µg kg(-1). Furthermore, the concentration of AFM1 was quite different among Bauru (0.038 µg kg(-1)), Araçatuba (0.017 µg kg(-1)) and Vale do Paraíba (<0.01 µg kg(-1)) regions. Only three samples (0.5%) had higher contamination than the tolerated limit in Brazil (0.50 µg kg(-1)) and 64 samples (10.1%) had a higher contamination than the maximum limit as set by the European Union (0.050 µg kg(-1)). The estimated AFM1 daily intake was 0.358 and 0.120 ng kg(-1) body weight per day for children and adults, respectively.

Aplicação de modelos de regressão aleatória utilizando diferentes estruturas de dados / Application of random regression models using different data structures

Foram utilizadas 3.202 primeiras lactações de vacas da raça Holandesa de quatro fazendas da região Sudeste, para verificar a influência da estrutura de dados de produção de leite sobre os parâmetros genéticos. Foram testados quatro arquivos com diferentes estruturas: controles semanais (CS), arquivo mensal (CM), bimestral (CB) e trimestral (CT), com 122.842, 30.883, 15.837 e 12.702 controles, respectivamente. Um modelo de regressão aleatória foi empregado nas análises, considerando os efeitos genético aditivo e o de ambiente permanente de animal, como aleatórios. Os efeitos fixos, grupos de contemporâneos (GC) foram comuns para todos os arquivos de dados e foram compostos por fazenda, mês e ano do controle, além da co-variável idade da vaca ao parto (regressão linear e quadrática). As estimativas de herdabilidade apresentaram tendências mais semelhantes entre os arquivos de dados CS, CM e CB. O arquivo de dados CB apresentou estimativas de parâmetros genéticos com as mesmas tendências e magnitudes que os arquivos CS e CM, permitindo afirmar que não houve influência da estrutura dos dados sobre as estimativas dos componentes de (co)variância e que o controle leiteiro poderia ser realizado em uma estrutura CB.

A total of 3.035 lactations of Holstein cows from four farms in the Southeast, to check the influence of data structure of milk yield on the genetic parameters. Four dataset with different structures were tested, weekly controls (CW) with 122.842 controls, monthly controls (CM) 30.883, bimonthly controls (CB) with 15,837 and quarterly controls (CQ) with 12,702. The random regression model was used and was considered as random additive genetic and permanent environment effects, fixed effects of the contemporary groups (herd-year-month of test-day) and age of cow (linear and quadratic effects). Heritability estimates showed similar trends among the data files analyzed, with the greatest similarity between dataset CS, CM and CB. The dataset submitted all the CB estimates of genetic parameters analyzed with the same trend and similar magnitude to the CS and CM dataset, allowing the claim that there was no influence of the data structure on estimates of covariance components for the dataset CS, CM and CB. Thus, milk recording could be accomplished in a CB structure.

Concordance analysis between estimation methods of milk fatty acid content.

Considering the milk fatty acid influence on human health, the aim of this study was to compare gas chromatography (GC) and Fourier transform infrared (FTIR) spectroscopy for the determination of these compounds. Fatty acid content (g/100g of fat) were obtained by both methods and compared through Pearson's correlation, linear Bayesian regression, and the Bland-Altman method. Despite the high correlations between the measurements (r=0.60-0.92), the regression coefficient values indicated higher measures for palmitic acid, oleic acid, unsaturated and monounsaturated fatty acids and lower values for stearic acid, saturated and polyunsaturated fatty acids estimated by GC in comparison to FTIR results. This inequality was confirmed in the Bland-Altman test, with an average bias varying from -8.65 to 6.91g/100g of fat. However, the inclusion of 94% of the samples into the concordance limits suggested that the variability of the differences between the methods was constant throughout the range of measurement. Therefore, despite the inequality between the estimates, the methods displayed the same pattern of milk fat composition, allowing similar conclusions about the milk samples under evaluation.

Prediction of bovine milk true protein content by mid-infrared spectroscopy / Estimativa do teor de proteína verdadeira do leite bovino por espectroscopia na região do infravermelho médio

The aim of this study was to estimate the concentration of milk true protein (TP) by mid-infrared absorbance method (MIR) in samples from bulk tank of dairy herds, and to determine the correlation between the results of TP of milk determined by Kjeldahl and MIR. Forty nine dairy herds were selected (17 Holstein, 6 Jersey and 26 Girolando) for monthly collections of samples from bulk tanks during the period of one year (284 samples). Fat, lactose, crude protein and total solids were firstly determined by MIR, and then analyzed for total and true protein by Kjeldahl method. The regression equation to estimate TP contents based on MIR crude protein determination was as follows: TP=0.0021+(1.0104xCP), where: TP is the content of true protein, CP is the crude protein content determined by the MIR method, and 0.0155 is the model error term.

O objetivo deste estudo foi estimar o teor de proteína verdadeira (PV) do leite por meio de metodologia de espectroscopia na região do infravermelho médio (IVM), em amostras de tanque de rebanhos leiteiros comerciais, e determinar a correlação entre os resultados de proteína verdadeira do leite determinados pelo método de Kjeldahl e por IVM. Foram selecionados 49 rebanhos leiteiros (17 da raça Holandesa, seis da raça Jersey e 26 da raça Girolando) para coletas mensais de amostras de leite de tanque durante o período de um ano, totalizando 284 amostras analisadas. As amostras de leite foram analisadas inicialmente em relação aos teores de gordura, lactose, proteína bruta e sólidos totais por IVM, sendo em seguida analisadas quanto ao teor de PB e PV pelo método de Kjeldahl. A equação de regressão para estimativa do teor de PV com base nos teores de proteína bruta foi a seguinte: PV=0,0021+(1,0104xPB); em que: PV é o teor de proteína verdadeira estimado; PB é o teor de proteína bruta pelo método IVM e 0,0155 é o erro apresentado pelo modelo.

Modelos de dimensão finita para a estimação de parâmetros genéticos para a produção de leite de primeiras lactações de vacas da raça Holandesa / Finite dimension models to estimate genetic parameters for first lactation milk yields of Holstein cows

Foram estimados parâmetros genéticos para produção de leite acumulada até 305 dias (P305) e produção de leite no dia do controle (PLDC) de 50.171 controles mensais de 9.281 primeiras lactações de vacas da raça Holandesa. A P305 e as PLDC foram analisadas por meio de modelo animal uni e bicaracterísticas. Para a P305 o modelo incluiu como aleatório, o efeito genético e como efeitos fixos o grupo de contemporâneos e a covariável idade da vaca ao parto. Para as PLDC foi usado o mesmo modelo descrito para a P305, incluindo como covariável o número de dias em lactação. Os componentes de variância foram estimados pelo Método da Máxima Verossimilhança Restrita. As estimativas de herdabilidade (h²) para as PLDC oscilaram entre 0,07 e 0,19 em análises unicaracterísticas e, de 0,12 a 0,22 nas bicaracterísticas. Para a P305, as h² resultantes das análises uni-característica e bicaracterística foram 0,26 e 0,27, respectivamente. As correlações genéticas das PLDC com a P305 foram todas positivas e elevadas, variando de 0,63 a 1,00. As correlações genéticas entre as PLDC variaram de 0,30 a 1,00. A seleção para a P305 parece ser o melhor critério de seleção a ser adotado, uma vez que proporciona maiores ganhos genéticos para as produções de leite em, praticamente, todos os controles da lactação.

Genetic parameters for 50,171 first lactation test-day milk yields and 305 day milk yield (Y305) of 9,281 Holstein cows were estimated, applying uni and bi-trait animal models. The model for Y305 included the additive genetic effect as random and the fixed effects of contemporary group and age of cow at calving as covariable. For TDMY the same animal model described for Y305 was used, including days in milk as covariable. Variance components were estimated by Restricted Maximum Likelihood. Heritability estimates obtained for TDMY ranged from 0.07 to 0.19 and from 0.12 to 0.22 by uni-trait and bi-trait analysis, respectively. Heritability for Y305 was 0.26 by uni-trait and 0.27 by bi-trait analysis. The genetic correlations between TDMY and Y305 were all positive and high, ranging from 0.63 to 1.00. The genetic correlations between TDMY ranged from 0.30 to 1.00. Selection for Y305 seems to be the best selection criterion to be adopted, since it provides larger genetic gain for milk productions in, practically, all test days.

Determinaçäo do número mínimo de amostragens mensais de leite, para pagamento por qualidade / Determination of minimum samples of milk to the payment by quality

Devido à total ausência de trabalhos relativos ao número de amostragens necessárias, o objetivo foi determinar o número mínimo para que o pagamento de leite aos produtores no Brasil seja adequado. Para isto, foram coletadas semanalmente amostras de leite do tanque, proveniente do rebanho de vacas leiteiras do Departamento de Produçäo Animal, da ESALQ/USP, por 27 meses, totalizando 134 amostras, que foram analisadas, no mesmo dia da coleta, pela Clínica do Leite, para verificar as concentraçöes de gordura, proteína e sólidos totais e a contagem de células somáticas (CCS). O desvio na média dos componentes do leite, em funçäo do tamanho da amostra, foi calculado a partir da variância amostral. O maior ganho na precisäo ocorre quando da coleta de 4-5 amostras mensais, considerando o cálculo da média por mês, bimestral ou trimestral. Entretanto, com base nas classes utilizadas pela indústria, seriam necessárias 13 amostras mensais para uma estimativa precisa da média mensal, 9 para a média bimestral e 7 para a média trimestral, considerando que a porcentagem de gordura é a maior limitante para o pagamento do leite.

Efeito do nível de células somáticas sobre os constituintes do leite I-gordura e proteína / Effects of somatic cell levels on milk components I-fat and protein

Foram analisadas eletronicamente 6.112 amostras de leite para CCS e concentração de gordura e proteína com o objetivo de verificar como estes teores são alterados pelo aumento da CCS. A CCS foi transformada para escore linear. O aumento do escore levou a um aumento da concentração de gordura, e a um aumento da concentração de proteína. Estes aumentos foram altamente significativos (p<0,0001), porém apenas 6,97 por cento da variação da concentração de gordura e 12,3 por cento da variação da concentração de proteína foram devidos à variação das CCS.