scholarly journals The effect of extended lactation on parameters of Wood’s model of lactation curve in dairy Simmental cows

2020 ◽  
Author(s):  
Tomáš Kopec ◽  
Gustav Chládek ◽  
Daniel Falta ◽  
Josef Kučera ◽  
Milan Večeřa ◽  
...  
Keyword(s):  
Lactation Curve ◽  
Extended Lactation

Modeling the lactation curve for test-day milk yield in Murciano-Granadina goats

2002 ◽  
Vol 46 (1) ◽  
pp. 29-41 ◽  
Author(s):  
C Fernández ◽  
A Sánchez ◽  
C Garcés
Keyword(s):  
Milk Yield ◽  
Lactation Curve

scholarly journals Lactation curve models for estimating gene effects over a timeline

2011 ◽  
Vol 94 (1) ◽  
pp. 442-449 ◽  
Author(s):  
E.M. Strucken ◽  
D.J. de Koning ◽  
S.A. Rahmatalla ◽  
G.A. Brockmann
Keyword(s):  
Gene Effects ◽  
Lactation Curve

The control of appetite in lactating cows

1972 ◽  
Vol 14 (3) ◽  
pp. 263-281 ◽  
Author(s):  
L. S. Monteiro
Keyword(s):  
Body Weight ◽  
Food Intake ◽  
Milk Yield ◽  
Closed Loop ◽  
Loop System ◽  
Closed Loop System ◽  
Lactating Cows ◽  
Body Reserves ◽  
Lactation Curve ◽  
Rate Of Increase

SUMMARYA closed-loop system is proposed for the control of voluntary food intake in lactating cows, and an expression is deduced relating the response of food intake to changes in milk yield and body-weight gain.A closed-loop system necessarily involves a delay in the response to changes in production. The rate of increase of food intake is there- fore slower than the rate of increase in milk yield. The consequent deficit in energy during the rising part of the lactation curve is met by the mobilization of body reserves, which are partly accounted for by losses in body weight. During the declining part of the lactation the delay effect leads to an excess of energy intake and to the replacement of body reserves and, consequently, of body weight.The expression deduced from the model was fitted to four different types of lactation curve corresponding to long and short lactations of Friesians and Jerseys fed ad libitum on a complete diet. The expected food intake based on the control model was contrasted with a linear regression model. The former gave a better account of the variation in food intake in all four types of lactation.The total change in body weight during lactation was partitioned between changes in weight due to the mobilization and replacement of reserves and gain directly attributable to food intake. There was, in general, good agreement between the observed losses in weight occurring at the beginning of lactation and those predicted from the mobilization of reserves for milk production.The physiological implications of the model and the values estimated for the parameters are discussed.

scholarly journals Extended lactation in high-yielding dairy cows. I. Effects on reproductive measurements

2019 ◽  
Vol 102 (1) ◽  
pp. 799-810 ◽  
Author(s):  
G. Niozas ◽  
G. Tsousis ◽  
I. Steinhöfel ◽  
C. Brozos ◽  
A. Römer ◽  
...  
Keyword(s):  
Dairy Cows ◽  
Extended Lactation

scholarly journals The use of dijkstra mechanistic model for genetic analysis of the lactation curve characteristics and their relationships with age at first calving and somatic cell score of Iranian dairy cows

2020 ◽  
Vol 42 ◽  
pp. e50181
Author(s):  
Mahdi Elahi Torshizi ◽  
Homayoun Farhangfar
Keyword(s):  
Somatic Cell ◽  
Genetic Correlation ◽  
Milk Yield ◽  
Mechanistic Model ◽  
Genetic Correlations ◽  
Somatic Cell Score ◽  
Specific Rate ◽  
Lactation Period ◽  
Age At First Calving ◽  
Lactation Curve

The objective of this study was to estimate lactation curve parameters with Dijkstra mechanistic model and to evaluate genetic and phenotypic relationships between the parameters and the average somatic cell count in primiparous cows. The finding indicated that heritability estimates for partial milk yield (PMY1, PMY2 and PMY3), total 305-day milk yield (TMY305), decay parameter (λ2), age at first calving (AFC) and peak yield (PY) were moderate while the heritability of persistency (PS%), average somatic cell score (AVGSCS), time to peak yield (TP), initial milk production (λ0), specific rate of cell proliferation at parturition (λ1), and specific rate of cell death (λ3) were quite low. Genetic correlations between both AFC and PS% traits with average somatic cell scores was negative (-0.047 and -0.060) but low positive genetic correlation were between partial milk yields (PMY1 and PMY3) while negative genetic correlation (-0.06) was obtained between TMY305 and AVGSCS. Differences between TMY305 of cows with less than 100000 cells mL-1 and cows with >1,500,000 cells mL-1 was approximately 708 Kg and is equivalent to 8% loss of milk yield/cow during lactation period and also loss of persistency (11.1 %( was shown for the extreme classes of SCC in this study.

scholarly journals Comparison of different lactation curve models in Holstein cows raised on a farm in the south-eastern Anatolia region

2008 ◽  
Vol 51 (4) ◽  
pp. 329-337
Author(s):  
Ö. Koçak ◽  
B. Ekiz
Keyword(s):  
Milk Yield ◽  
Goodness Of Fit ◽  
Mean Squared Error ◽  
Exponential Model ◽  
Eastern Anatolia ◽  
Mean Squared Errors ◽  
Squared Error ◽  
Lactation Curve ◽  
Daily Milk Yield ◽  
Daily Milk

Abstract. The objective of this study was to compare the goodness of fit of seven mathematical models (including the gamma function, the exponential model, the mixed log model, the inverse quadratic polynomial model and their various modifications) on daily milk yield records. The criteria used to compare models were mean R2, root mean squared errors (RMSE) and difference between actual and predicted lactation milk yields. The effect of lactation number on curve parameters was significant for models with three parameters. Third lactation cows had the highest intercept post-calving, greatest incline between calving and peak milk yield and greatest decline between peak milk yield and end of lactation. Latest peak production occurred in first lactation for all models, while third lactation cows had the earliest day of peak production. The R2 values ranged between 0.590 and 0.650 for first lactation, between 0.703 and 0.773 for second lactation and between 0.686 and 0.824 for third lactation, depending on the model fitted. The root mean squared error values of different models varied between 1.748 kg and 2.556 kg for first parity cows, between 2.133 kg and 3.284 kg for second parity cows and between 2.342 kg and 7.898 kg for third parity cows. Lactation milk yield deviations of Ali and Schaeffer, Wilmink and Guo and Swalve Models were close to zero for all lactations. Ali and Schaeffer Model had the highest R2 for all lactations and also yielded smallest RMSE and actual and predicted lactation milk yield differences. Wilmink and Guo and Swalve Models gave better fit than other three parameter models.

scholarly journals CHARACTERISTICS OF LACTATION CURVE IN DAMASCUS GOATS IN JORDAN

2013 ◽  
Vol 4 (8) ◽  
pp. 479-491
Author(s):  
E. Ayasrah ◽  
S. Abou-Bakr ◽  
M. Ibrahim
Keyword(s):  
Lactation Curve

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.

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