Factors affecting milk yield and prolificacy of Karagouniko sheep in West Thessaly (Greece)

1990 ◽  
Vol 24 (2) ◽  
pp. 181-186 ◽  
Author(s):  
I Hatziminaoglou ◽  
A Georgoudis ◽  
A Karalazos
Keyword(s):  
Milk Yield ◽  
Factors Affecting

Factors affecting milk yield and composition of Tunisian camels (Camelus dromedarius) over complete lactation

2020 ◽  
Vol 52 (6) ◽  
pp. 3187-3194
Author(s):  
Latifa Chamekh ◽  
Touhami Khorchani ◽  
Mohamed Dbara ◽  
Mohamed Hammadi ◽  
Mohamed Habib Yahyaoui
Keyword(s):  
Milk Yield ◽  
Camelus Dromedarius ◽  
Factors Affecting

scholarly journals THE FACTORS AFFECTING MILK YIELD IN DIARY FARMING IN GREATER GUWAHATI REGION OF ASSAM

2021 ◽  
Vol 9 (08) ◽  
pp. 723-728
Author(s):  
Heman Sarmah ◽  
◽  
Jnanashree Borah ◽  
Tirthankar Sarma ◽  
◽  
...  
Keyword(s):  
Regression Analysis ◽  
Dairy Cattle ◽  
Milk Production ◽  
Milk Yield ◽  
Policy Maker ◽  
Production Cost ◽  
Relative Importance ◽  
Factors Affecting ◽  
Micro Level ◽  
Farming Households

The production of milk is conceived of several factors and a very multifarious process. The knowledge of relative importance of the resource inputs influencing in milk production is essential for the dairy farmer for introducing desirable change in his operation at micro level and for the policy maker for formulating plans for improvements in dairy cattle productivity based on sound economic principles at the macro level (Rao, 1985).The income level of the dairy household is determined by the production of milk they produce at their farms. Generally, the income of the dairy household increases when the milk production cost decreases or when the milk production increases .For this it is essential to study the factors which directly or indirectly effect the milk production. Household samples have been selected both from the municipal wards of Guwahati Municipal Corporation area. Out of 672 dairy farming households, 201 household have been selected for the survey. Regression analysis has been used for the study of factors affecting milk production in greater Guwahati region of Assam.

Factors affecting milk yield and lactation curve fitting in the creole sheep of Chiapas-Mexico

2005 ◽  
Vol 58 (3) ◽  
pp. 265-273 ◽  
Author(s):  
Marisela Peralta-Lailson ◽  
Arturo Ángel Trejo-González ◽  
Pastor Pedraza-Villagómez ◽  
José M. Berruecos-Villalobos ◽  
Carlos G. Vasquez
Keyword(s):  
Milk Yield ◽  
Curve Fitting ◽  
Factors Affecting ◽  
Lactation Curve ◽  
Fitting In

Evaluation of extent and amount of heterogeneous variance for milk yield in Uruguayan Holsteins

2001 ◽  
Vol 72 (2) ◽  
pp. 259-268 ◽  
Author(s):  
J. I. Urioste ◽  
D. Gianola ◽  
R. Rekaya ◽  
W. F. Fikse ◽  
K. A. Weigel
Keyword(s):  
Milk Yield ◽  
Phenotypic Variance ◽  
Simple Method ◽  
Factors Affecting ◽  
Lorenz Curves ◽  
Gini Coefficients ◽  
Adjustment Procedure ◽  
Contemporary Group ◽  
Lactation Length ◽  
Log Linear

AbstractThe extent and amount of heterogeneous phenotypic variance for milk yield in the Uruguayan Holstein population were evaluated and a simple method of accounting for heterogeneity was developed. Lactation records (159 169) collected between 1989 and 1998 by two recording schemes were used to form 8955 herd-year-season-parity-lactation length contemporary groups. A log-linear model was used to identify factors affecting heterogeneity of phenotypic variance. The model included effects of production level, contemporary group size, recording scheme, herd, season of calving, parity number, calving year period and length of lactation and accounted for 50% of the variation in log variances. Estimates from this model were used in a Bayesian manner, to obtain posterior mean estimates of within-contemporary-group variances, which were then used to standardize records to a baseline variance. Effects of the adjustment were assessed by comparing coefficients of variation before and after correction, by correlation and regression between mean and standard deviations, and by using Gini coefficients and Lorenz curves. The adjustment procedure reduced heteroscedasticity primarily by decreasing the frequency of low-variance contemporary groups. Lorenz curves and Gini coefficients indicated that the largest impact of the standardization procedure was related to the size of the contemporary group. Some differences in the effect of the correction were found between recording schemes. The method for adjusting records is simple and easy to adapt to current genetic evaluation procedures.

An analysis of the variation between dairy-sire progeny-groups for milk yield and fat content

1958 ◽  
Vol 1958 ◽  
pp. 19-29 ◽  
Author(s):  
Alan Robertson ◽  
S. S. Khishin
Keyword(s):  
Milk Yield ◽  
Comparison Method ◽  
Fat Content ◽  
Fat Percentage ◽  
Simple Method ◽  
Factors Affecting ◽  
Special Cases ◽  
The Mean ◽  
Milk Marketing ◽  
The Relationship

The past few years have seen the development in Great Britain of the ‘contemporary comparison’ method for evaluating progeny tests of dairy sires (Macarthur, 1954; Robertson, Stewart and Ashton 1956). The final overall figure attached to a sire is the mean difference between the yield of his daughters and that of other heifers milking in the same herd in the same year, with due regard for the numbers of animals in the two groups. Although it has some imperfections in special cases, this is probably the most informative simple method of evaluating a sire for yield and, fortunately, one which could be easily integrated with the existing recording system. The method has been turned into a simple routine in the Bureau of Records of the Milk Marketing Board and several thousand bulls have now been evaluated. In this paper, we shall be mostly concerned to use this material to investigate the heritabilities of milk yield and fat content and the relationship between the two in the different breeds. The information that we shall use consists, for each bull, of the mean contemporary comparison, with its effective ‘weight’, and the average fat percentage of the daughters. Before we deal with the observed results, we should go into rather more detail into the nature of these two figures and into the factors affecting them.

Partial milking of cattle in smallholder herds on the Accra Plains: some factors affecting daily partial milk yield and milk composition

1992 ◽  
Vol 54 (1) ◽  
pp. 15-21 ◽  
Author(s):  
S. A. Okantah
Keyword(s):  
Milk Yield ◽  
Milk Composition ◽  
Dry Season ◽  
Sub Saharan Africa ◽  
Factors Affecting ◽  
Stage Of Lactation ◽  
Lactation Length ◽  
Sub Saharan ◽  
Quadratic Effects ◽  
Accra Plains

AbstractDaily partial milk yield of Sanga cows in 13 smallholder agropastoralist herds at two locations on the Accra Plains was recorded through monthly sampling. Estimates of mean daily partial milk yield and milk composition were computed from 1266 observations. The unadjusted mean daily partial milk yield was 875 (s.e. 11) g. The composition of milk: total solids (TS), fat (F) and solid-not-fat (SNF) were 131 (s.e. 14), 41 (s.e. 11) and 90 (s.e. 7) g/kg respectively. Least squares estimate of mean daily partial milk yield were 808·2 and 462·4 g with average s.e. of 41·8 for wet and dry season respectively. The wet and dry season differences in daily partial milk yield, TS and F were highly significant (P < 0·01). Seasonal difference in SNF was not significant.Herd difference in partial milk yield, TS, F and SNF were highly significant (P < 0·02). There were no significant effects of location on daily partial milk yield and SNF, although location effects on F and TS were significant (P < 0·05). The highest milk yield was observed in cows in third lactation and the lowest in cows in seventh lactation (P < 0·01). Daily partial milk yield peaked in the 3rd month of lactation. On average, lactation length was 210 to 240 days. Both linear and quadratic effects of stage of lactation were highly significant (P < 0·01). Lactation curve parameters for partially milked cows were also estimated. The implications of the results for milk production in sub-Saharan Africa were discussed.

Factors affecting weight and age at first calving, first lactation milk yield in Gir cows

2016 ◽  
Author(s):  
Basdev Singh ◽  
Pushkraj Sawant ◽  
Dhruvaraj Sawant ◽  
Sachin Todkar ◽  
Richa Jain
Keyword(s):  
Genetic Correlation ◽  
Milk Yield ◽  
Dairy Farm ◽  
Madhya Pradesh ◽  
Age At First Calving ◽  
Factors Affecting ◽  
Phenotypic Correlations ◽  
Heritability Estimates

The present study was undertaken on data of 113 Gir cows maintained at Kasturba Gram Dairy Farm, Indore, Madhya Pradesh, India over a period of 18 years from 1995 to 2012, based on age at first calving. The overall means for weight at first calving (WFC), age at first calving (AFC), and first lactation milk yield (FLMY) were 402.22± 1.28 kg, 1709.04± 51.92 days and 1664.95± 280.72 litres respectively. The heritability estimates for WFC, AFC and FLMY were 0.248± 0.234, 0.307± 0.206 and 0.112± 0.252 respectively. The genetic correlation between WFC and AFC was positive and significant, while it was negative in between WFC and FLMY. The genetic correlation between AFC and FLMY was low and negative. The phenotypic correlations between all traits were positive.

Use of ordered logit model with time series data for determining the factors affecting the milk yield of Holstein Friesians

2019 ◽  
Author(s):  
Özge Akkuş ◽  
Volkan Sevinç
Keyword(s):  
Time Series ◽  
Milk Yield ◽  
Logit Model ◽  
Time Series Data ◽  
Series Data ◽  
Ordered Logit ◽  
Factors Affecting ◽  
Ordered Logit Model ◽  
Lactation Length ◽  
Cattle Breeders

This article aims to introduce the use of ordered logit model with time series data in milk productivity studies and determine the important factor levels affecting the milk yield of Holstein Friesians. The data consists of 2002 records collected for the years 2009-2015 from the reports of the Cattle Breeders’ Association of Turkey (CBAT) in Muðla province in Turkey. The direct and marginal effects of the variables: parity, lactation length and year of calving on milk yield are investigated and the probabilities regarding the milk yield production for a given specific parity, lactation length and calving year are calculated. The results show that milk yield slightly increases on the 4th parity of cows. As far as the years concerned, although there had mostly been a steady amount of milk production between 2009 and 2015 years, there was a significant decrease in 2011 and increase in 2014.

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