scholarly journals Linear modeling analysis using for determining the factors affecting 305-day milk yield

2021 ◽  
Vol 73 (4) ◽  
pp. 949-954
Author(s):  
S. Genç ◽  
M. Mendeş
Keyword(s):  
Dairy Cows ◽  
Milk Yield ◽  
Modeling Technique ◽  
Linear Modeling ◽  
Data Set ◽  
Factors Affecting ◽  
Lactation Length ◽  
Modeling Analysis

ABSTRACT The purpose of this study was to model the factors affecting the 305-day milk yield of dairy cows by using Automatic Linear Modeling Technique (ALM). The data set of this study consisted of eight different cow breeds grown in eight province of Turkey. Results of ALM showed that the accuracy of the model was 64.2 % means that 64.2% of the variation in the 305-day milk yield could be explained by the constructed model. Created model was consisted of four factors namely the Breed, Lactation Length, Parity, and Province. Therefore, those selected factors were more efficient than the others in predicting the 305-day milk yield

scholarly journals Determining the Factors Affecting 305-Day Milk Yield of Dairy Cows with Regression Tree

2021 ◽  
Vol 9 (6) ◽  
pp. 1154-1158
Author(s):  
Serdar Genç ◽  
Mehmet Mendes
Keyword(s):  
Dairy Cows ◽  
Milk Yield ◽  
Regression Tree ◽  
Dry Period ◽  
Data Set ◽  
Tree Analysis ◽  
Factors Affecting ◽  
Lactation Length ◽  
Regression Tree Analysis ◽  
Service Period

The purpose of this study was to determine the factors affecting the 305-day milk yield of dairy cattle by using Regression Tree Analysis (RTA). The data set of this study consisted of 8 different cattle breeds grown in Turkey. Breed (B), Province (P), Lactation Length (LL), Service Period (SP), Dry Period (DP), Parity (PR), Calving Year (CY), Calving Age (CA) and Calving Month (CM) were used to predict the 305-day milk yield. Results of RTM showed that the usage of this method might be appropriate for determining the important factors that would be able to affect the 305-day milk yield (R2=71.3%). It was seen that the most important factors affecting the 305-day milk yield were the Breed, Lactation Length, Province, and Parity. Therefore, those selected factors were more efficient than the others in predicting the 305-day milk yield. RTA results also indicated that the lowest milk yield was estimated for Jersey, Jersey Crossbred, and Yerli Kara. Among the highest 305-day milk yield cows, the milk yield estimates of the cows in the second, third, fourth, fifth, and the sixth parities were found significantly higher than that of the cows in the first and seventh parities.

Devising a Selection Strategy for the Jamunapari Goat for Improving Lactation Performance

2021 ◽  
Author(s):  
Mahesh Shivanand Dige ◽  
P. K. Rout ◽  
S. Bhusan ◽  
G. R. Gowane
Keyword(s):  
Milk Yield ◽  
Selection Criterion ◽  
Selection Strategy ◽  
Yield Traits ◽  
Lactation Performance ◽  
Data Set ◽  
Yield Attributes ◽  
Lactation Length ◽  
Genetic Potential ◽  
Average Information

Abstract This study aims to evaluate the genetic potential of the Jamunapari goat and formulate a new selection strategy for improving the lactation traits. The data set included 4049 phenotypic records for lifetime milk yield at 90 days (MY90) and 140 days (MY140), total milk yield (TMY), and lactation length (LL) obtained from the progeny of 83 sires and 1643 dams between 1990 and 2019. Animal model employing average information restricted maximum likelihood (AIREML) was used to estimate genetic parameters for milk yield traits and LL. The direct additive heritability estimates for lifetime lactation traits, that used repeatability model were 0.10 ± 0.03, 0.08 ± 0.03 and 0.12 ± 0.02 for MY90, MY140 and TMY, respectively, while it was low for LL (0.06 ± 0.02). The repeatability estimates were moderate ranging from 0.17 to 0.22 for milk yield traits and LL, indicating persistent performance over the parities. Animal permanent environment influence (c2) was significant in milk yield attributes, whereas additive maternal genetic effects were absent. As the early selection criteria based on first parity records is essential, we analysed the data for the first parity separately and obtained moderate h2 estimates viz. 0.26 ± 0.05, 0.26 ± 0.06 and 0.25 ± 0.06 for MY90, MY140 and TMY, respectively. These estimates augurs further positive scope of selection in Jamunapari goats for higher milk yield. High and positive genetic correlation of MY90 with MY140 (0.97 ± 0.01) and TMY (0.91 ± 0.05) revealed the scope of using MY90 as the selection criterion.Based on these results, we recommend use of MY90 as a single trait selection criterion for genetic improvement of all lactation traits in Jamunapari goat.

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.

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.

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.

REGRESSION ANALYSIS OF FACTORS AFFECTING MILK YIELD OF DAIRY COWS

1982 ◽  
Vol 62 (3) ◽  
pp. 827-835
Author(s):  
A. H. FREDEEN ◽  
G. K. MacLEOD ◽  
I. McMILLAN ◽  
D. G. GRIEVE
Keyword(s):  
Dairy Cows ◽  
Milk Yield ◽  
Nutrient Intake ◽  
Negative Influence ◽  
Positive Influence ◽  
Forward Selection ◽  
Factors Affecting ◽  
Multiple Regression Technique ◽  
Management Factors ◽  
Daily Milk Yield

By using a forward selection multiple regression technique, 60% of the total sums of squares (SS) in either average daily milk yield (DCA) or average BCA milk among 56 Ontario dairy herds was accounted for by selected feeding and management factors. Herd average body weight had a strong positive influence on both DCA and BCA milk and was associated with higher nutrient intake. High production was associated with shorter calving intervals (CI) and therefore shorter lactations. Whereas average days in lactation had a strong negative influence on DCA, average CI adversely affected both DCA and BCA milk. Differences in feed quality and nutrient intake (primarily energy) accounted for most of the remaining variation in milk yield between herds. The inability of dairymen to monitor intake of energy-dense feeds was an important factor limiting herd yield. Key words: Milk yield, dairy cows, feeding and management factors

Productive and reproductive performance of crossbred and indigenous dairy cows at smallholdings in selected towns of Jimma Zone, Ethiopia

2021 ◽  
Vol 61 (1) ◽  
pp. 92
Author(s):  
Belay Duguma
Keyword(s):  
Dairy Cattle ◽  
Dairy Cows ◽  
Milk Yield ◽  
Reproductive Performance ◽  
Management Practices ◽  
Production Systems ◽  
Management Strategies ◽  
Factors Affecting ◽  
Jimma Zone ◽  
Improvement Programs

Context Evaluation of the performance of dairy cows kept in different production systems is essential for the development of appropriate breeding strategies. Aims To examine milk production and reproductive performance of crossbred (CB) and indigenous (I) dairy cows, farmers’ traits preference for CB and I breeding females, and factors affecting the performance of dairy cattle on smallholdings in selected towns of Jimma Zone, Ethiopia. Methods In total, 52 smallholder dairy cattle farmers were randomly sampled and data were collected through individual face-to-face interviews by using structured questionnaires. The traits studied were daily milk yield (DMY), lactation milk yield (LMY), lactation length (LL), age at first service (AFS), age at first calving (AFC), calving interval (CI), days open (DO), and number of service per conception (NSC), all being factors affecting performance of dairy cattle and farmers’ preferred dairy traits. Results On average, CB cows had significantly (P &lt; 0.05) higher DMY (6.0 ± 0.33 vs 1.8 ± 0.07 L/cow), LMY (1466.7 ± 1.13 vs 376.0 ± 21.02 L (L)), LL (8.1 ± 0.41 vs 6.9 ± 0.22 months), and lower AFS (2.69 ± 0.1 vs 3.3 ± 0.07 years), AFC (3.7 ± 0.13 vs 4.3 ± 0.07 years) and CI (21.2 ± 1.37 vs 29.8 ± 1.30 months) than did I cows. However, DO and NSC were not significantly (P &gt; 0.05) affected by genotype. In order of perceived importance, high milk yield (mean rank = 0.306), LL (0.292) and fertility (0.199) were farmers’ most preferred traits for CB breeding cows, and the corresponding preferred traits for I cows were high milk yield (0.253), adaptability (0.229) and LL (0.192). The most important factors perceived by farmers affecting the performance of dairy cattle were breed, nutrition, diseases, breeding and management practices Conclusions The findings of the study indicated that even though CB cows performed better, the performance of both breeds of dairy cows in the study area was found to be generally low due to delayed AFS, late AFC, long CI, shorter LL, low daily and LMY and high NSC. Implications The study highlighted that there is a potential for increasing the performance of dairy cows in the study area, through improved management strategies leading to shorter AFS, AFC, CI and lower NSC. Furthermore, future breed-improvement programs should take into consideration farmers’ trait preferences in design of sustainable improvement programs.

77 REPRODUCTIVE PERFORMANCE OF DAIRY COWS DIFFERING IN THE INTERVAL FROM CALVING TO THE FIRST OVULATION IN THE POSTPARTUM PERIOD

2012 ◽  
Vol 24 (1) ◽  
pp. 151
Author(s):  
M. Yamaguchi ◽  
S. Takahashi ◽  
H. Koyama ◽  
O. Dochi
Keyword(s):  
Dairy Cows ◽  
Milk Yield ◽  
Reproductive Performance ◽  
Postpartum Period ◽  
Body Condition Score ◽  
Early Recovery ◽  
Factors Affecting ◽  
Condition Score ◽  
Peripartum Period ◽  
Days Open

In recent years, reproductive performance of dairy cows has declined worldwide. The reproductive characteristics of dairy cows should be evaluated to improve their fertility. Dochi et al. (2010) had reported that dairy cows that exhibited early first ovulation gave a low milk yield, had an early recovery of body condition score (BCS) in the postpartum period and a shorter number of days open. The objective of this study was to evaluate the effect of BCS on the functional recovery of reproduction after the birth of the calves. In this study, lactating Holstein cows were placed in free-stall housing equipped with an automatic milking system. The data presented in this study were collected from 48 cows that had calved between December 2007 and October 2010 with an average parity of 3.4 (range 2–6). The reproductive performance and the BCS during the different intervals between calving and the first ovulation were analysed using ANOVA. The conception rate at the first service was 38.1%. The average milk yield (305 days) was 12 299 kg. The first ovulation and oestrus were determined by ultrasonography. The results of the different intervals to the first ovulation are presented in Table 1. The average interval from the start of days in milk (DIM) to the first ovulation, first oestrus and first service; the number of days open; the number of services per conception and the milk yield (kg day–1, by 90 DIM) were 37.4, 54.7 and 110.3 days; 168.2 days open; 2.5 times; and 42.1 kg day–1, respectively. The cows that exhibited early first ovulation (≤21 DIM) in the postpartum period had significantly shorter intervals between the start of DIM and the first oestrus (P < 0.01). However, the days to first service, the number of days open, the number of services per conception and the milk yield (kg day–1, by 90 DIM) did not differ significantly. The BCS in the peripartum period of different intervals to the first ovulation decreased from 3.1 to 2.4 by 150 DIM. This study showed that average BCS of preparturient 50–10 DIM is 3.0. Moreover, the average BCS of parturition is declining to 2.5 (parturition from 70 to 150 DIM). The cows became pregnant after an increase in the BCS (>150 DIM). In conclusion, these results suggest that the delay to the first ovulation in the postpartum period tended to have delayed the oestrus expression in the cows. Moreover, the low level of BCS in the peripartum period, regardless of the number of days of the first ovulation and the first oestrus, potentially influenced the prolongation in the number of days open. To improve the fertility of the cows, it is important to elucidate the factors affecting the fluctuations in the BCS during the peripartum period. Table 1.Reproductive performance of dairy cows differing in interval to postpartum first ovulation

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