scholarly journals Software-Automatized Individual Lactation Model Fitting, Peak and Persistence and Bayesian Criteria Comparison for Milk Yield Genetic Studies in Murciano-Granadina Goats

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1505 ◽  
Author(s):  
María Gabriela Pizarro Inostroza ◽  
Francisco Javier Navas González ◽  
Vincenzo Landi ◽  
José Manuel León Jurado ◽  
Juan Vicente Delgado Bermejo ◽  
...  
Keyword(s):  
Milk Yield ◽  
Linear Models ◽  
Model Fitting ◽  
Goat Milk ◽  
Individual Performance ◽  
Individual Variability ◽  
Curve Shape ◽  
Lactation Curve ◽  
Future Challenges ◽  
The Individual

SPSS model syntax was defined and used to evaluate the individual performance of 49 linear and non-linear models to fit the lactation curve of 159 Murciano-Granadina goats selected for genotyping analyses. Lactation curve shape, peak and persistence were evaluated for each model using 3107 milk yield controls with an average of 3.78 ± 2.05 lactations per goat. Best fit (Adjusted R2) values (0.47) were reached by the five-parameter logarithmic model of Ali and Schaeffer. Three main possibilities were detected: non-fitting (did not converge), standard (Adjusted R2 over 75%) and atypical curves (Adjusted R2 below 75%). All the goats fitted for 38 models. The ability to fit different possible functional forms for each goat, which progressively increased with the number of parameters comprised in each model, translated into a higher sensitivity to explaining curve shape individual variability. However, for models for which all goats fitted, only moderate increases in explanatory and predictive potential (AIC, AICc or BIC) were found. The Ali and Schaeffer model reported the best fitting results to study the genetic variability behind goat milk yield and perhaps enhance the evaluation of curve parameters as trustable future selection criteria to face the future challenges offered by the goat dairy industry.

scholarly journals On designing the average lactation curve at the ascending phase

1962 ◽  
Vol 34 (1) ◽  
pp. 162-168
Author(s):  
Aarne Mäkelä
Keyword(s):  
Dairy Cows ◽  
Milk Yield ◽  
Lactation Period ◽  
Lactation Curve ◽  
The Mean ◽  
The Individual ◽  
Daily Milk Yield ◽  
Daily Milk

Comparisons are made between different methods to find the peak production (maximum daily milk yield) and methods to design the average lactation curve at the ascending phase in dairy cows. It was noted that in order to determine the height and location of the maximal producing capacity of a cow in a known lactation period, it is preferable to choose the peak production as a mean of three subsequent best days. It was also noted that the usual methods for drawing the average lactation curves do not give a true picture of the height and location of the peak. The author suggests a method for determining the average lactation curve at the ascending phase by using the averages of both milk productions and times involved in reaching the peak and known fractions (e.g. 1/8, 1/4, 1/2, 3/4, and 5/4) of it. In this lactation curve the peak production is the mean of the peaks of individual cows, and the time involved in reaching it is the mean of the durations of the ascending phases of the individual cows.

6.5 Dairy cow condition scoring

1981 ◽  
Vol 4 ◽  
pp. 349-353 ◽  
Author(s):  
P. M. Mulvany
Keyword(s):  
Milk Yield ◽  
Body Condition ◽  
Dairy Cow ◽  
Individual Performance ◽  
Animal Performance ◽  
Basic Part ◽  
Health Measures ◽  
Final Item ◽  
Body Condition Scoring ◽  
The Individual

Records on animal performance form a basic part of management. Without records it is not possible to measure the effect of changes in management nor assess the individual performance of an animal. Condition scoring provides a means of recording body condition and may assist in monitoring changes in body reserves. However, it is of limited use if other, more significant, records are not kept. It provides an enhancement to a recording scheme in which reproduction, production health and feeding/grazing records are kept. These records should be simple. Some data are required on calvings and inseminations, milk yield and/or rate of growth, preventative and curative health measures and on the probable feed available to an animal and how this feed is utilized. Body condition scoring will provide some data for this final item.

scholarly journals Goat Milk Nutritional Quality Software-Automatized Individual Curve Model Fitting, Shape Parameters Calculation and Bayesian Flexibility Criteria Comparison

Animals ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 1693 ◽  
Author(s):  
María Gabriela Pizarro Inostroza ◽  
Francisco Javier Navas González ◽  
Vincenzo Landi ◽  
Jose Manuel León Jurado ◽  
Juan Vicente Delgado Bermejo ◽  
...  
Keyword(s):  
Somatic Cell ◽  
Dry Matter ◽  
Model Comparison ◽  
Minimum Mean Square Error ◽  
Goat Milk ◽  
Individual Performance ◽  
Information Criteria ◽  
Somatic Cell Counts ◽  
Cell Counts ◽  
The Individual

SPSS syntax was described to evaluate the individual performance of 49 linear and non-linear models to fit the milk component evolution curve of 159 Murciano-Granadina does selected for genotyping analyses. Peak and persistence for protein, fat, dry matter, lactose, and somatic cell counts were evaluated using 3107 controls (3.91 ± 2.01 average lactations/goat). Best-fit (adjusted R2) values (0.548, 0.374, 0.429, and 0.624 for protein, fat, dry matter, and lactose content, respectively) were reached by the five-parameter logarithmic model of Ali and Schaeffer (ALISCH), and for the three-parameter model of parabolic yield-density (PARYLDENS) for somatic cell counts (0.481). Cross-validation was performed using the Minimum Mean-Square Error (MMSE). Model comparison was performed using Residual Sum of Squares (RSS), Mean-Squared Prediction Error (MSPE), adjusted R2 and its standard deviation (SD), Akaike (AIC), corrected Akaike (AICc), and Bayesian information criteria (BIC). The adjusted R2 SD across individuals was around 0.2 for all models. Thirty-nine models successfully fitted the individual lactation curve for all components. Parametric and computational complexity promote variability-capturing properties, while model flexibility does not significantly (p > 0.05) improve the predictive and explanatory potential. Conclusively, ALISCH and PARYLDENS can be used to study goat milk composition genetic variability as trustable evaluation models to face future challenges of the goat dairy industry.

scholarly journals Modelling the lactation curve of dairy cows using the differentials of growth functions

2008 ◽  
Vol 146 (6) ◽  
pp. 633-641 ◽  
Author(s):  
M. H. FATHI NASRI ◽  
J. FRANCE ◽  
N. E. ODONGO ◽  
S. LOPEZ ◽  
A. BANNINK ◽  
...  
Keyword(s):  
Milk Yield ◽  
Goodness Of Fit ◽  
Statistical Evaluation ◽  
Parameter Estimates ◽  
Growth Functions ◽  
Lactation Curve ◽  
Significant Difference ◽  
Overall Evaluation ◽  
Mathematical Equations ◽  
The Individual

SUMMARYDescriptions of entire lactations were investigated using six mathematical equations, comprising the differentials of four growth functions (logistic, Gompertz, Schumacher and Morgan) and two other equations (Wood and Dijkstra). The data contained monthly milk yield records from 70 first, 70 second and 75 third parity Iranian Holstein cows. Indicators of fit were model behaviour, statistical evaluation and biologically meaningful parameter estimates and lactation features. Analysis of variance with equation, parity and their interaction as factors and with cows as replicates was performed to compare goodness of fit of the equations. The interaction of equation and parity was not significant for any statistics, which showed that there was no tendency for one equation to fit a given parity better than other equations. Although model behaviour analysis showed better performance of growth functions than the Wood and Dijkstra equations in fitting the individual lactation curves, statistical evaluation revealed that there was no significant difference between the goodness of fit of the different equations. Evaluation of lactation features showed that the Dijkstra equation was able to estimate the initial milk yield and peak yield more accurately than the other equations. Overall evaluation of the different equations demonstrated the potential of the differentials of simple empirical growth functions used in the current study as equations for fitting monthly milk records of Holstein dairy cattle.

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

2021 ◽  
Vol 8 ◽  
Author(s):  
Matheus Fellipe de Lana Ferreira ◽  
Luciana Navajas Rennó ◽  
Isabela Iria Rodrigues ◽  
Sebastião de Campos Valadares Filho ◽  
Luiz Fernando Costa e Silva ◽  
...  
Keyword(s):  
Milk Yield ◽  
Milk Fat ◽  
Linear Models ◽  
Nonlinear Models ◽  
Information Criterion ◽  
Beef Cows ◽  
Total Solids ◽  
Lactation Curve ◽  
Non Linear ◽  
Milking Machine

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.

scholarly journals Comparison of the parameters of the lactation curve between normal and difficult calvings in Iranian Holstein cows

2019 ◽  
Vol 17 (1) ◽  
pp. e0401
Author(s):  
Navid Ghavi Hossein-Zadeh
Keyword(s):  
Dairy Cows ◽  
Milk Yield ◽  
Goodness Of Fit ◽  
Linear Models ◽  
Information Criterion ◽  
Holstein Cows ◽  
Coefficient Of Determination ◽  
Lactation Curve ◽  
Non Linear ◽  
Best Fit

To evaluate effect of dystocia on the lactation curve characteristics for milk yield and composition in Holstein cows, six non-linear models (Brody, Wood, Sikka, Nelder, Dijkstra and Rook) were fitted on 5,917,677 test day records for milk yield (MY), fat (FP) and protein (PP) percentages, fat to protein ratio (FPR) and somatic cell score (SCS) of 643,625 first lactation Holstein cows with normal calving or dystocia from 3146 herds which were collected by the Animal Breeding Center of Iran. The models were tested for goodness of fit using adjusted coefficient of determination, root means square error, Akaike’s information criterion and Bayesian information criterion. Rook model provided the best fit of the lactation curve for MY and SCS in normal and difficult calvers and dairy cows with dystocia for FP. Dijkstra model provided the best fit of the lactation curve for PP and FPR in normal and difficult calvers and dairy cows with normal calving for FP. Dairy cows with dystocia had generally lower 100-d, 200-d and 305-d cumulative milk yield compared with normal calvers. Time to the peak milk yield was observed later for difficult calvers (89 days in milk vs. 79 days in milk) with lower peak milk yield (31.45 kg vs. 31.88 kg) compared with normal calvers. Evaluation of the different non-linear models indicated that dystocia had important negative effects on milk yield and lactation curve characteristics in dairy cows and it should be reduced as much as possible in dairy herds.

Comparing biological and linear models to estimate milk yields and lactation curve parameters

2005 ◽  
Vol 2005 ◽  
pp. 113-113
Author(s):  
B. Albarran-Portillo ◽  
G. E. Pollott
Keyword(s):  
Dairy Cows ◽  
Milk Production ◽  
Milk Yield ◽  
Linear Models ◽  
Computational Effort ◽  
Reasonable Accuracy ◽  
Early Predictors ◽  
Lactation Curve ◽  
Total Milk ◽  
Mathematical Equations

The genetic evaluation of dairy cows is based primarily on milk production and its constituents. Many models have been developed and evaluated in order to estimate total milk yield (CTMY) and other characteristics of lactation curves. Frequently, the models are based on complex mathematical equations and their use demands a huge computational effort. The development of simple models as early predictors of TMY with a reasonable accuracy is important. The objective of this research was to compare the biological model described by Pollott (2000) with two linear models.

scholarly journals Conditioning Factors of Linearized Wood’s Function Lactation Curve Shape Parameters, Milk Yield, Fat and Protein Content in Murciano-Granadina Primiparous Does

Animals ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 2115
Author(s):  
Juan Vicente Delgado Bermejo ◽  
Francisco Antonio Limón Pérez ◽  
Francisco Javier Navas González ◽  
Jose Manuel León Jurado ◽  
Javier Fernández Álvarez ◽  
...  
Keyword(s):  
Milk Yield ◽  
Milk Fat ◽  
Random Regression ◽  
Total Production ◽  
Curve Shape ◽  
Conditioning Factors ◽  
Lactation Length ◽  
Lactation Curve ◽  
Daily Milk Yield ◽  
Daily Milk

A total of 137,927 controls of 22,932 Murciano-Granadina first lactation goats (measured between 1996–2016) were evaluated to determine the influence of the number of kids, season, year and farm on total milk yield, daily milk yield, lactation length, total production of fat and protein and percentages of fat and protein. All factors analyzed had a significant effect on the variables studied, except for the influence of the number of kids on the percentages of fat and protein, where the variation was very small. Goats with two offspring produced nearly 15% more milk, fat and protein per lactation compared to goats with simple kids. Kiddings occurring in summer–autumn resulted in average milk, fat and protein yields nearly 14, 19 and 23% higher when compared to winter–spring kiddings. Lactation curves were evaluated to determine the effects of the number of kids and season, using the linearized version of the model of Wood in random regression analyses. Peak Yield increased by about 0.3 kg per additional offspring at kidding, but persistence was higher in goats with single offspring. The kidding season significantly influenced the lactation curve shape. Hence summer-kidding goats were more productive, and peak occurred earlier, while a higher persistence was observed in goats kidding during autumn.

Characterization of Lactation Curve Patterns using Non-linear Models in Crossbred Dairy Cattle

2021 ◽  
Author(s):  
Tassew Mohammed Ali ◽  
Raman Narang ◽  
P.P. Dubey ◽  
Simarjeet Kaur
Keyword(s):  
Dairy Cattle ◽  
Milk Yield ◽  
Linear Models ◽  
Biological Efficiency ◽  
Lactation Curve ◽  
Non Linear ◽  
Crossbred Dairy Cattle ◽  
Daily Milk Yield ◽  
Curve Patterns ◽  
Daily Milk

Background: Lactation curve patterns are currently integrated in dairy cow’s management software. Lactation curve modeling is useful for monitoring individual yields for diet planning, determining optimum strategies for insemination and genetic evaluation. It also helps for predicting expected missing values on field records and gives concise summary of biological efficiency and persistency of dairy cows.Methods: The study was aimed to characterize the lactation curve pattern for crossbred dairy cattle using different non-linear models. During the period 1991 to 2018, daily milk yield (DMY) consisted of 281698 records of 750 crossbred dairy cows maintained at Livestock Farms. GADVASU, Ludhiana, were collected for the study. Different non-linear models viz. exponential decline function (EDF), parabolic exponential model (PEM), inverse polynomial model (IPM), gamma-type function (GTF), mixed log function (MLF) and Ali and Schaeffer model (ASF) were used for the analysis. The model(s) that best fit and describe the curve characteristics was selected on the basis of coefficient of determination (R2), coefficient of variation (CV), Akaike information criterion (AIC) and mean square error (MSE).Result: The study clearly revealed that the PRM gave highest fit to DMY data with R2, MSE, AIC and CV values of 98.10%, 0.087, -743.31 and 2.37%, respectively. The IPM had also best fitted the observed DMY data with highest R2 (98.05%), lower MSE (0.089), low AIC (-735.8972) and lower CV (2.40%) values. The fitting of observed DMY data with predicted DMY were also found to be higher in the MLF (R2= 96.46%, MSE= 0.159, AIC= -558.16 and CV= 3.21%) and GTF (R2= 95.85%, MSE= 0.190, AIC= -505.24 and CV= 3.50%), whilst the EDF and PEM Models depicted relatively low fit to the DMY data when compared with the other non-linear models. However, IPM and GTF models can be used for accurate prediction of daily milk yield in the crossbred cattle population because they were typical standard lactation curves.

scholarly journals UDDER SIZE AND MILK PRODUCTION POTENTIALS OF GOATS AND SHEEP IN THE SOUTH WEST OF NIGERIA

2021 ◽  
Vol 24 (2) ◽  
pp. 175-179
Author(s):  
J. O. Agbede ◽  
A. G. Ologun ◽  
J. A. Alokan
Keyword(s):  
Milk Production ◽  
Milk Yield ◽  
Coefficient Of Variation ◽  
Milk Protein ◽  
Goat Milk ◽  
West African ◽  
Production Potential ◽  
South West ◽  
Lactation Curve ◽  
Lactating Goats

Twelve adult lactating goats and sheep (2 to 2 ½ years old) comprising three groups of four each of West African Dwarf (WAD) goats and sheep and Yankasa ewes used for a nine week trial. The animals kidded and lambed between January and March. During these periods the udder sizes of the dams were measured weekly before hand milking thrice a week to derermine the milk yield. Samples of the milk were analysed for their composition. The results showed that the udder size increased with increasing milk yield (112 – 248ml) up to the peak of lactation which was between weeks 3 and 4 after parturition. Thereafter it decreased in size till the end of the experiment. The coefficient of variation (CV) of the udder size was influenced by breed. Udder size was positively correlated with milk yield. Milk yields were generally low or and ranged between 39 and 70ml and this was dependent on the behavior of the lactation curve. The milk protein and ash contents for the three breeds were comparable to those of the temperate breeds. Though Yankasa sheep exhibited the highest milk production potential, yet the peculiar characteristics of goat milk cannot be overlooked.

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