Lactation Curve Research Articles

Test day yield, lactation curve and production potential of Gir cattle under hot and humid conditions of Tamil Nadu

Test day milk yield records (5130), milk production and milk composition traits from 19 lactations of Gir cows collected for two years (2019 and 2020) were used to understand the performance of Gir breed in hot and humid conditions of Tamil Nadu. Different lactation curve models were used for modelling test day records and model diagnostics like adjusted R-square, BIC and RMSE were used to obtain the model of best fit. The mean test day yield, fat per cent, SNF (%), total milk yield, peak yield, days to attain peak yield and calving interval observed were 5.78 kg, 5.05%, 7.65%, 1507 kg, 9.23 kg, 46.5 days and 447 days respectively. Ali and Shaeffer model offered the best fit for lactation curve in Gir cows. Mahadevan method and Gamma function were used to calculate the persistency of milk yield which was obtained as 1.33 and 6.348 respectively. Results of the study indicated that Gir cattle were able to adapt themselves through maintenance of reproductive traits comparable with that of the native tract but the new humid environment has caused a slight decrease in the performance of milk production traits.

Evaluation of Black Pied first-calf heifers` lactation of various genotypes

Purpose: Comparative assessment of the fullness of lactation of primarmels of different genotypes.Materials and methods. The article presents the results of the assessment of the lactation activities, which was carried out in the SEC "Kazminsky" Kochubeevsky district of the Stavropol region on the livestock of the black and motley breed of local and brown populations from the Vologda region from LLC "Zaozerier" (farm №. 1) and SHPK "Proseukhon" (farm №2). Three experienced animals groups of 30 goals were formed in each, studies were carried out according to generally accepted methods.Results. The greatest amount of milk for 305 days I lactation was obtained from the first elevations brought from LLC "Zaozerier" - 7368 kg, which is 3.64% more than from the cows of their own reproduction and 8.85% more than from animals grown in SEC "Proseukhonskoye". The lactation stability ratio was calculated in two ways, and in both cases there was more than 100, the factor of the fullness of lactation in the cows of the studied genotypes this indicator was also very high and amounted to 87.7-91.6, which indicates a high level of breeding and tribal work, and On the significant influence of genetic factors on the lactation activity of the studied animals. According to the nature of the lactation curve, the pilot of all three genotypes can be attributed to the I type - high stable lactation. However, the greatest amount of milk from cows was obtained in the third phase of lactation.Conclusion. Thus, it can be concluded that the period of adaptation did not have a significant impact on the lactation activity of the delivered first elements. The animals studied were characterized by high productivity and sustainable lactation.It is desirable when evaluating the cows, along with productivity for 305 days of lactation, consider individual qualities and the ability to hold high productivity to a large part of the lactation period. For more differentiated selection of cows in the breeding group, we recommend using the stability coefficients and the usefulness of lactation.

Characteristics of population genetic and breeding parameters of the traits of milk productivity of black-and-white and Holstein cows of the Republic of Kazakhstan

Purpose: determination of the selection and genetic parameters of the daily milk productivity of black-and-white and Holstein cows to characterize the population.Materials and methods. The studies were carried out using a database formed on the basis of the information and analytical management system of animal husbandry in the Republic of Kazakhstan (RK) for daily control milking of Holstein and black-and-white cows. The sample included indicators of milk productivity for three lactations of animals bred in 43 herds: I lactation - 14 482 records (3130 cows and 391 bull fathers), II lactation - 13 656 records (2734 cows and 537 bull fathers), III lactation - 4,911 records (886 cows and 260 bull fathers).Results. Phenotypic variability indices (CvP) by lactation varied: daily milk yield - 34.1 ... 38.8%, MJ - 9.8 ... 11.6%, BMD - 6.7 ... 8.6%, SCS - 32.5 ... 37.8%. The additive genetic variability (CvA) was lower and ranged for: daily milk yield - 22.9 ... 27.0%, MJ - 3.8 ... 4.7%, BMD - 2.6 ... 3.1%, SCS - 13 , 8 ... 14.7%. The heritability of indicators of milk productivity on average for three lactations was: in terms of milk yield - h2 = 0.440, percentage of fat - h2 = 0.155, percentage of protein - h2 = 0.121, SCS - h2 = 0.161. Evaluation of the dynamics of changes in daily milk yield and SCS showed the standard nature of the shape of lactation curves with the values ​​of the determination coefficient of the phenotypic trend equation, respectively, R2 = 69.9 ... 86.4% and R2 = 11.8 ... 20.5%. An increase in the number of recorded days of control milking from 1 to 10 increased the accuracy of the forecast of the breeding value (EBV) of animals for signs of milk production by 1.7-2.4 times. Evaluation of cows by their own productivity for milk yield with optimal values ​​of forecast reliability over 70% can be carried out on the basis of 4 control milking units. At the same time, for the percentage of fat and protein, SCS, the number of observations to achieve reliable EBV results ranged from 8 to 10. Based on the average values ​​of the breeding value of cows, the population genetic characteristics of the farmed cattle in the Republic of Kazakhstan were determined in the context of breeds, country and region (population) origin. Holstein animals (+54.3 kg of milk) were characterized by the highest EBV values. Among imported cows, the best breeding value forecast was obtained for cows imported from Germany (+63.3 kg of milk). For the Kazakh population of cattle, leading positions in terms of genetic prognosis were achieved in East Kazakhstan region (KZF, +334.4 kg of milk). A principal component analysis based on an assessment of the breeding value of cows showed clear differentiation by breed level, country and region of origin of the livestock. The most significant differences were found for animals originated in the Kostanay region (KZP).Conclusion. Analysis of the results of population-genetic and breeding parameters of the characteristics of milk productivity of black-and-white and Holstein cattle showed that there are necessary prerequisites for the development of their own breeding base, increasing the efficiency of selection of animals for breeding groups.

Optimal value for the exponential term of Wilmink's function according to current Holstein lactation curves in Japan.

We compared values of Wilmink's exponential term to describe the lactation curves of Holstein cows in Japan. Data were a total of 100,971,798 test-day records from the first through fifth parities during 1991 through 2018. The lactation curve model used fourth-order Legendre polynomials and Wilmink's exponential term. In total, 810 analyses were executed to compare six values (-0.02, -0.03, …, -0.07) for the exponential term to select the one that yielded the smallest root mean square error. For all parities, daily milk yield and lactation persistency increased consistently and peak lactation days occurred later from year to year. For the years evaluated, the optimal exponential term was -0.05 for first and second parities, -0.04 for third parity, and -0.03 for fourth and fifth parities. The change in the exponential parameter with increasing year was related to delays in peak lactation.

Modelos lineares e não lineares para a descrição da curva de lactação da raça Girolando

Abstract The objective of this work was to compare the main linear and nonlinear models used to describe lactation curves and to evaluate the nonlinearity of the nonlinear models, in order to obtain the most adequate model to describe the lactation curves of the Girolando breed. Data from 165 lactations of 89 3/4 Holstein + 1/4 Gyr cows were used, and average yield was calculated every 20 days up to 310 days of lactation. Seventeen models of lactation curves available in the literature were compared. The selection of the best model was based on the curvature measures of Bates & Watts, the bias of Box, adjusted coefficient of determination, Akaike’s information criterion, and residual standard deviation. The linear model of Cobuci estimated a yield peak of 16.7 kg at 40 days of lactation, whereas the nonlinear model of Wood estimated a yield peak of 16.8 kg at 41 days of lactation and a persistence of 6.82. Nonlinearity measures were the most appropriate for selecting the most suitable nonlinear model for the description of lactation curves. To describe the lactation curves of the Girolando breed, the most suitable linear model is that of Cobuci and the nonlinear model is that of Wood.

Data-driven dynamical modeling of dairy production oriented to herd management

This paper presents a data-driven modeling of dairy production oriented to decision-making for herd management. Database was obtained between 2016 and 2021, and contains 62596 observations corresponding to information from up to 4 lactations for 107 animals from the herd at Obonuco Research Center (CI Obonuco) of AGROSAVIA. The CI Obonuco is located at the Colombian high tropic. The lactation curve is a mathematical tool for graphical representation over time of the biological process of milk yield, which is useful for predicting total production over a period of time. For the construction of lactation curves parametric and explicitly time-dependent models are generally used to fit data. In this paper we propose a parametric dynamical linear model whose output variable depends on its previous values and whose parameters are found by means of an optimization process. The Particle Swarm Optimization technique is used to solve the optimization problem. The model is validated from data. In addition, a general architecture is proposed to use historical data to increase the learning about dairy production system and improve its prognosis using few new data for decision-making.

Influence of Lactation Number, Year and Season of Calving on Milk Productivity of Cows

The main characteristics of the milk productivity of Holstein dairy cattle differ in different countries due to differences in terrain, management and breeding objectives. At the same time, the manifestation of non-genetic (that is, environmental) factors during milk production, as a rule, mask the real breeding value of animals. The main goal of this study was to analyze the influence of lactation number, year and season of calving on the milk productivity of 238 Holstein cows during a 4-year period (2014-2017). The study was conducted using primary data on the dairy productivity of livestock in the conditions of PJSC Plemzavod Stepnoi of the Kamian-Dnipro district of the Zaporizhia region.The following characteristics were evaluated for each animal: duration of lactation, hope for 305 days of lactation, hope for the entire lactation, fat content and protein content in milk. P. Wood's model was used to approximate lactation curves within each subgroup. All signs of milk productivity were analyzed based on the algorithm of one- or two-factor analysis of variance with fixed factors using the statistical package STATISTICA v. 6.0 (Statsoft Inc.).Lactation number was found to have a significant effect on all milk yield traits that were examined (in all cases: p<0.001). Hope for 305 days of lactation increased with the growth of lactation number. The highest values of this characteristic were noted during the 2nd and 3rd lactations. The lowest estimate of milk yield for 305 days of lactation of dairy cows of this farm was obtained in 2014, and the highest in 2016. The calving season probably influenced the indicators of milk productivity (primarily, the content of fat and protein in milk) of firstborns. In addition, the milk yield score at 305 days of lactation was lower among winter- or spring-calved gilts compared to fall-calved animals. No influence of the calving season was noted among adult cows. Lactation number and year of calving probably influenced the estimates of the coefficients and parameters of P. Wood's model. The shape of the lactation curves of firstborns was flatter compared to mature cows. Estimates of peak milk yield were lower, but the index of constancy of the lactation curve was higher during the 1st lactation. Thus, we found that obtaining real (unbiased) estimates of milk productivity traits of Holstein cattle requires preliminary adjustment of data regarding the influence of lactation number, year and season of calving

СЕЗОННІ ЗМІНИ ПРОДУКТИВНОСТІ ПЕРВІСТОК ЗА РІЗНИХ УМОВ УТРИМАННЯ

The influence of the calving season on milk production was determined to be 0.9% for 305 days of lactation on average across all farms. In loose-housing, the influence of the season was smaller (0.4%) compared to stall housing (1.6-5.5%). Seasonal differences in the milk output of first calving cows for stall housing was equal to 437-816 kg, and for loose-housing 192-283 kg (р<0.05). In some farms animals of autumn and winter calving were distinguished by the best milk output, while in other farms spring-winter calving cows were more productive. It indicates a significant influence on the production of first-borns by the conditions of housing. The analysis of the indices of lactation constancy according to I. Johansen and A. Hanson indicates that the smallest decrease in milk output in the period of the next 14 weeks of lactation compared to the first 14 weeks of lactation was characterized by the first-borns of the experimental farm "Kutuzivka", and the largest by the animals of the experimental farm "Gontarivka". According to H. Turner's index, the differences between the peak monthly milk output and the milk output per lactation were the smallest in the first calving cows of the experimental farm "Stepne". Lactation curves of the cows that calved in the autumn-winter period had a steady character, which gradually decreased at maximum productivity for 3-4 months of lactation. In the first 3 months of lactation their herdmates of spring-summer calving also had an increase in milk output which fell dramatically in the following months when the animals were conveyed to winter-stall housing and a decrease in the completeness of feeding cows during this period. According to variance analysis, differences in daily milk output for each of the ten months of lactation were possible (p<0.001). The highest peak of daily output in all farms was obtained from first calving cows of spring calving which explained by the best conditions of housing and feeding during the calving period. Seasonal differences in the peak daily milk output of first calving cows ranged from 2.0 to 2.5 kg for stall housing and from 1.2 to 1.4 kg for loose-housing (p<0.001).

Characterization of the Lactation Curve in Shami Cows

Characterization of the Lactation Curve in Shami Cows

Estimation of lactation curves of Gyr cattle and some associated production parameters in the Colombian low tropic

Background: The Gyr breed is widely used in Colombian low tropic dairy production systems. During the last 10 years, the Asociación Colombiana de Criadores de Ganado Cebú† - ASOCEBU, has been leading a dairy milk control program which led to the creation of a dataset that permits to carry out the first analysis of milk yield in Gyr cattle in the country using records from several herds. Objectives: To study milk production dynamics of Gyr cattle in the Colombian low tropic through the estimation of lactation curves and four derived production parameters: total milk yield between 5 and 305 days (TMY305), peak milk yield (PMY), days at peak (DP) and persistency (P). Methods: 13,798 daily milk yield records from 1,510 cows performing in 103 herds were used; the total number of lactations was 2,480. Four models were considered: Wood, Wiltmink, Papajcsik & Bordero, and a second-degree polynomial. Mean square error, mean absolute error, mean square error of prediction, Akaike and Bayesian information criteria were used to select the model better describing each lactation using the majority rule, that is, the model selected by most criteria was the chosen one. The shape of each fitted lactation curve was checked using basic results from calculus which permitted the classification of the estimated curves into two groups: typical and atypical; only typical functions were used to compute the four aforementioned production parameters. Results: The second-order polynomial was the model most frequently selected, while the Papajcsik & Bordero model had the lowest frequency. Average TMY305, PMY, DP and P were 3,489.86 kg, 17.28 kg, 57.17 days, and 0.83, respectively, with coefficients of variation: 0.27, 0.21, 0.41, and 0.16. Conclusions: This study permitted to identify individuals with outstanding phenotypic performance. To the best of our knowledge, this is the first study of this kind involving thousands of lactations from Gyr cows performing in several regions of Colombian low tropic.

Feed behavior and milk productivity in cows of different fattening

The results of feed behavior and milk productivity in the cows of Ukrainian black-speckled dairy breed of different fattening of the first and second lactations from the first month to the end of lactation are given. The analysis of the herd showed that the highest milk productivity in cows of the first lactation was found in the group of fattening from 3 to 4 points, which was by 9.2 % (P ≥ 0.99) higher, compared to the group of cows with fattening 4 points and more. The milk yield in cows of the second lactation with fattening from 3 to 4 points exceeded the milk yield of cows with fattening 4 points and more by 12.9 % (P ≥ 0.95). The content of fat and protein in milk was higher in the cows with higher fattening, compared to the cows with lower fattening. The highest average daily milk yield was found in cows of the first lactation with fattening from 3 to 4 points. Depending on the month, it was by 5.5–11.7 % (P ≥ 0.95 – P ≥ 0.999) higher, compared to the cows with fattening 4 points and more, while it was by 6.9–10.0 % (P ≥ 0.95 – P ≥ 0.999) higher in cows of the second lactation. The gestation period of cows has a significant effect on the reduction of milk yield. The milk yield of cows in connection with the term of their gestation are reduced by 0.1 kg per day during the second month after insemination, by 0.2 kg per day during the third month, by 0.3 kg per day during the fourth month, by 0.6 kg per day during the fifth month, by 1.0 kg per day during the sixth month, by 1.7 kg per day during the seventh month and by 2.8 kg per day during the eighth month. The analysis of the dynamics of monthly milk yield shows that lactation curves of cows increase from the first day of lactation to its peak, which occurs in the 2nd – 4th month after calving. The lactation curve in the cows with fattening from 3 to 4 points has a higher peak in the 2nd –3d month of lactation, compared to the cows with higher (more than 4 points) fattening. The animals of all groups, except for cows of the second lactation (with fattening 4 and more points) showed the maximum productivity in the 2nd –3d month of lactation; then the lactation curve decreased with different intensity. The index of constancy of lactation and the index of falling milk yield are the important indicators that characterize the stability of lactation curves. The constancy of lactation curves having been determined by I. Johansson-Hansson index was higher in the cows with fattening 4 and more points, compared to the indicator of the cows with fattening from 3 to 4 points. The studies of behavioral reactions have shown that the animals of the first lactation with an average (from 3 to 4 points) fattening consume feed during 208.5 minutes, which is by 17 minutes (P ≥ 0.999) longer than the animals with higher average fattening, and by 14.5 minutes (P ≥ 0.99) longer than the animals of the second lactation.

Genetic evaluation of lactation persistency in the Gyr breed by using a two-trait random regression model

Context Lactation persistency (LP) is an economically important characteristic to include in the selection objectives of the Gyr breed. Two persistency measures were tested to establish their contribution to the genetic evaluation of milk production in this genotype. The second measure of persistency studied would be the more appropriate measure to use in the genetic evaluation of lactation persistency. Aim The aim of this work was to study LP in Gyr cows by using a random regression model (RRM) in two-trait analysis. Methods Test-day milk yields (TDMY) of the first two lactations of Gyr cows were analysed. RRM was performed by Bayesian inference using the GIBBS3F90 program. Fourth-order Legendre polynomials were used to describe the random additive genetic and permanent environmental effects of the animal. The fixed effects included in the model were contemporary group and, as covariates, age of cow at calving and the regression function according to the TDMY class of lactation as the average trajectories of lactation curve, distinguished by calving order. Two persistency measures (PSi, i.e. PS1 and PS2) were used in the analyses. Rank correlations were calculated between the predicted breeding values for PSi, 305-day lactation milk yield (MY305), and the regression coefficients a0 and a1, to determine the percentage of matching animals between rankings when different selection intensities are applied on the basis of the ranking for MY305. Key results The heritability estimates for PS1, PS2 and for MY305 were 0.19, 0.12 and 0.41 respectively, in the first lactation, and 0.43, 0.27 and 0.38 in the second lactation. The genetic correlation between MY305 and PS1 was negative and of low magnitude. The rank correlation between breeding values for PSi, obtained for bulls with at least five daughters with production records, was higher than 0.80 in the two lactation periods. Conclusions The results indicated that PS2 is the more suitable of the two persistency measures used in this work, for inclusion in genetic evaluations of lactation persistency in Brazilian Gyr cows. Implications PS2 must be included as a selection criteria in a breeding program for the Gyr breed.

Evaluation of Non-linear Models to Predict Potential Milk Yield of Beef Cows According to Parity Order Under Grazing.

This study aimed to evaluate the effect of parity order on milk yield (MY) and composition over time of grazing beef cows and to evaluate non-linear models to describe the lactation curve. Thirty-six pregnant Nellore cows (12 nulliparous, 2 years; 12 primiparous, 3 years; and 12 multiparous, 4–6 years) were included in the study. With calving day assigned as day 0, milking was performed using a milking machine to estimate MY on days 7, 14, 21, 42, 63, 91, 119, 154, and 203. Dummy variable analyses were applied to estimate its effects on MY, composition (kg and percentage), afternoon/morning, and afternoon/total proportions. Since multiparous cows had higher MY than nulliparous and primiparous cows, two different groups were used for lactation curve analysis: Mult (multiparous) and Null/Prim (nulliparous and primiparous). The MY estimated by the last edition of BR-Corte (Nutrient Requirements of Zebu and Crossbred Cattle) equation was compared with the observed values from this study. Five nonlinear models proposed by Wood (WD), Jenkins & Ferrell (JF), Wilmink (WK), Henriques (HR) and Cobby & Le Du (CL) were evaluated. Models were validated using an independent dataset of multiparous and primiparous cows. The estimates for parameters a, b, and c of the CL equation were compared between groups, and the BR-Corte equation used the model identity methodology. Nulliparous and primiparous cows displayed similar MY (P > 0.05); however, multiparous cows had an average MY that is 0.70 kg/day greater than that of nulliparous and primiparous cows (P < 0.05). Milk protein and total solids were higher for multiparous cows (P < 0.05). Effect of days in milking was found for milk fat, protein, and total solids (P < 0.05). The yield of all milk components was higher for multiparous cows than for nulliparous and primiparous cows. The afternoon/morning and afternoon/total proportions of milk production were not affected by parities and days in milking (P > 0.05), with an average of 0.76 and 0.42, respectively. The BR-Corte equation did not correctly estimate the MY (P < 0.05). The equations of WD, WK, and CL had the best estimate of MY for both Mult and Null/Prim datasets. The equations had a very similar Akaike's information criterion with correction and mean square error of prediction.

Influence of environmental factors and parity on milk yield dynamics in barn-housed dairy cattle

We investigated the effects of environmental factors on average daily milk yield and day-to-day variation in milk yield of barn-housed Scottish dairy cows milked with an automated milking system. An incomplete Wood gamma function was fitted to derive parameters describing the milk yield curve including initial milk yield, inclining slope, declining slope, peak milk yield, time of peak, persistency (time in which the cow maintains high yield beyond the peak), and predicted total lactation milk yield (PTLMY). Lactation curves were fitted using generalized linear mixed models incorporating the above parameters (initial milk yield, inclining and declining slopes) and both the indoor and outdoor weather variables (temperature, humidity, and temperature-humidity index) as fixed effects. There was a higher initial milk yield and PTLMY in multiparous cows, but the incline slope parameter and persistency were greatest in primiparous cows. Primiparous cows took 54 d longer to attain a peak yield (mean ± standard error) of 34.25 ± 0.58 kg than multiparous (47.3 ± 0.45 kg); however, multiparous cows yielded 2,209 kg more PTLMY. The best models incorporated 2-d lagged minimum temperature. However, effect of temperature was minimal (primiparous decreased milk yield by 0.006 kg/d and multiparous by 0.001 kg/d for each degree increase in temperature). Both primiparous and multiparous cows significantly decreased in day-to-day variation in milk yield as temperature increased (primiparous cows decreased 0.05 kg/d for every degree increase in 2-d lagged minimum temperature indoors, which was greater than the effect in multiparous cows of 0.008 kg/d). Though the model estimates for both indoor and outdoor were different, a similar pattern of the average daily milk yield and day-to-day variation in milk yield and milk yield's dependence on environmental factors was observed for both primiparous and multiparous cows. In Scotland, primiparous cows were more greatly affected by the 2-d lagged minimum temperature compared with multiparous cows. After peak lactation had been reached, primiparous and multiparous cows decreased milk yield as indoor and outdoor minimum temperature increased.

Dairy productivity of holstein cattle with different genotypes of the kappa-casein gene (CSN3)

The purpose of research was to study the polymorphism of the CSN3 gene and its effect on milk yield, fat and protein mass fractions in milk, as well as on the lactation curve characteristics in the first lactation of Holstein cows. The experiment was carried out on the biological material of 146 cows of of Integrated Agricultural Production Centre “Stud farm named after Lenin” of the Atninsky district of the Republic of Tatarstan in the laboratory of agrobiological research of Tatar Research Institute of Agriculture of FRC KazanSC of RAS. DNA diagnostics by PCR-RFLP method of the CSN3 gene testified that the livestock under study is genetically diverse. The herd contains animals of all genotypes: АA – 41,1%, АВ – 47,9%, ВВ – 11,0%. The frequency of occurrence for allele A was 0.651, for allele B – 0.349. The genetic equilibrium in the population is not disturbed, the chi-square criterion is below the critical value. The analysis of milk productivity indicators of cow-heifers with different genotypes of the CSN3 gene shows the superiority of animals with the AB genotype in milk yield per standard lactation (6908.5 kg), with the BB genotype in the content of the protein mass fraction (4.05%) and protein yield (267.8 kg). Individuals with the AA genotype are characterized by an increased mass fraction and milk fat yield (3.65% and 244.4 kg). Cows have different lactation curves depending on the genotype of the CSN3 gene.

Comparative efficiency of five mathematical functions in modelling the first lactation milk yield of Kankrej cattle

Modelling of first lactation milk yield of Kankrej cattle was done using five different non-linear mathematical functions viz., exponential decline function (EDF), gamma function (GF), inverse polynomial function (IPF), mixed log function (MLF) and parabolic exponential function (PEF). We compared their efficiency in describing variations in first lactation milk yield of animals maintained under field conditions. A total of 3994 fortnightly daily milk records of 203 Kankrej cattle calved during the years between 2011 and 2017 at farmers? herds in the Banaskantha region of Gujarat State, India were utilized for the study. The PROC NLIN procedure of Statistical Analysis Software (SAS) using Newton method of iteration was applied to generate the model parameters and corresponding standard errors. Different parameters like adjusted R2 -value, root mean square error (RMSE), Durbin?Watson (DW) statistic, Akaike information criterion (AIC) and Bayesian information criterion (BIC) were used to compare the efficiency of different models. Results inferred that mixed log function was the best non-linear mathematical function for explaining variations in the first lactation milk yield of Kankrej cattle followed by gamma function and parabolic exponential function. The exponential decline function was the least efficient in fitting the lactation curve in Kankrej cattle, followed by inverse polynomial function.

PSV-14 Using Bayesian Hamiltonian Monte Carlo and a nonlinear model for the estimation of genetic parameters for lactation curves in goats

Abstract Hamiltonian Monte Carlo (HMC) is an algorithm of the Markov Chain Monte Carlo (MCMC) method that uses dynamics to propose samples that follow a target distribution. This algorithm enables more effective and consistent exploration of the probability interval and is more sensitive to correlated parameters. Therefore, Bayesian-HMC is a promising alternative to estimate individual parameters of complex functions such as nonlinear models, especially when using small datasets. Our objective was to estimate genetic parameters for milk traits defined based on nonlinear model parameters predicted using the Bayesian-HMC algorithm. A total of 64,680 milk yield test-day records from 2,624 first, second, and third lactations of Saanen and Alpine goats were used. First, the Wood model was fitted to the data. Second, lactation persistency (LP), peak time (PT), peak yield (PY), and total milk yield [estimated from zero to 50 (TMY50), 100(TMY100), 150(TMY150), 200(TMY200), 250(TMY250), and 300(TMY300) days-in-milk] were predicted for each animal and parity based on the output of the first step (the individual phenotypic parameters of the Wood model). Thereafter, these predicted phenotypes were used for estimating genetic parameters for each trait. In general, the heritability estimates across lactations ranged from 0.10 to 0.20 for LP, 0.04 to 0.07 for PT, 0.26 to 0.27 for PY, and 0.21 to 0.28 for TMY (considering the different intervals). Lower heritabilities were obtained for the nonlinear function parameters (A, b and l) compared to its predicted traits (except PT), especially for the first and second lactations (range: 0.09 to 0.18). Higher heritability estimates were obtained for the third lactation traits. To our best knowledge, this study is the first attempt to use the HMC algorithm to fit a nonlinear model in animal breeding. The two-step method proposed here allowed us to estimate genetic parameters for all traits evaluated.

Evaluation of Milk Production and Milk Composition at Different Stages of Saanen Dairy Goats

Milk is an important elements due to its high nutritious and balanced in human diet. In Asian, goat milk is the most consumed because of the unique taste, more nutritious than cow milk. However, milk production and composition values differ at every stage of lactation in goats. Thus, determining the highest milk production and producing the best quality goat milk is essential to satisfy the local market demands. The objective of the present study is to determine the milk yield and milk composition at different lactation stages and to evaluate the lactation curves in Saanen goats. The lactation stages can be categorized into three, early (less than 80 days), mid (80 – 140 days) and late (over 140 days) days in milk (DIM). In total, 90 milk samples were collected from 15 goats representing early (n=5), mid (n=5), and late (n=5) stages of lactation. The Saanen goats were raised under the same conditions, and milking was done early in the morning (9.00am).The milk yield from Saanen goats were collected and measured weekly at each stage of lactation. Milk samples were analyzed for fat, protein, solid non-fat, and lactose. Current result illustrated, there were significant different (p ˂ 0.05) among three stages of lactation in milk yield, solid non-fat, fat, protein and lactose. In terms of food regulation, the Saanen goats almost fully met the standard requirements for milk production and composition. In addition, this study also observes the lactation curves in Saanen goats and analyse the curve shapes and patterns. The average milk yields from three different stages develops a concave downward curve. The results indicated that mid yield increased from early to mid- lactation and decreased thereafter until the end of lactation.

Short communication: Variance and autocorrelation of deviations in daily milk yield are related with clinical mastitis in dairy cows

Daily milk production, and fluctuations therein, can provide information on health and resilience of dairy cows. We studied variance and autocorrelation of deviations in daily milk yield in relation to the occurrence of clinical mastitis (no, early or later in lactation). Individual lactation curves were fitted to 305-d lactations of 414 dairy cows using quantile regression. Log-transformed variance (lnVar) and autocorrelation of the quantile residuals of daily milk yield (predicted – observed) were evaluated for intervals until 30 and until 305 days in milk (DIM). Cows were classified as having no mastitis (n = 249), early mastitis that first occurred before 30 DIM (n = 29); or later mastitis (n = 136). Subsequently, linear models were used to assess effects of mastitis and parity class (primiparous or multiparous) on lnVar and autocorrelations; and logistic regression analyses were performed to predict mastitis from lnVar or autocorrelation and parity. From 10 to 30 DIM, lnVar was greater for cows with early mastitis than for cows with no or late mastitis, and autocorrelation tended to be lower for cows with early mastitis than for cows with no mastitis. The lnVar and autocorrelation from 10 to 30 DIM were not predictive of late mastitis. From 10 to 305 DIM, lnVar was greater and autocorrelation was lower for both cows with early and late mastitis than for cows with no mastitis; and both were predictive of having mastitis in the 305-d lactation. Primiparous cows had lower lnVar than multiparous cows. In cows without mastitis, autocorrelation values were positively correlated with lnVar. Results confirm that increased lnVar is associated with clinical mastitis.

Milk production and quality patterns of double-purpose goats grazing in arid rangelands.

Lactation curves are a valuable tool for improving flock production efficiency, adjusting flock sizes, and improving farmers' income in grazing-based livestock production. Therefore, we used natural cubic splines to estimate (a) a general flock production pattern throughout a year, (b) an average lactation curve, and (c) patterns of milk chemical components in dual-purpose goats grazing in arid plant communities in the Sierra de San Francisco, Baja California Peninsula, during years of abundant precipitation. Also, milk chemical composition was compared between flocks. Annual flock milk production showed a wiggly pattern with two greater waves in summer and spring. The average individual lactation curve (kg/doe/day) and production curves of fat, protein, lactose, and ashes (g/doe/day) showed a decreasing and wiggly pattern across 35-week lactation; the greatest average daily production was in week 2. Milk, protein, lactose, and ash production curves had similar persistency values that were greater than those of the fat production curve. Milk production had a high-positive correlation with fat production and very high-positive correlations with protein, lactose, and ash production. Density (g/ml) and fat, protein, lactose, and ash contents (%) showed a ditch-shaped pattern across lactation, with greater values at the end. Goat flocks grazing across plant communities produced different quality milk. Thus, native plant communities are a valuable resource that favors a great fat content and moderate protein content in local goat milk. Also, breeding programs must pay attention that an increment in individual milk production could decrease fat and protein production, which are valuable for cheesemaking.