Management Factors Affecting Puberty in the Heifer

2021 ◽  
pp. 71-89
Author(s):  
J.E. Kinder ◽  
M.S. Roberson ◽  
M.W. Wolfe ◽  
T.T. Stumpf
2007 ◽  
Vol 2007 ◽  
pp. 102-102
Author(s):  
P.T. Kelly ◽  
K. O’Sullivan ◽  
D.P. Berry ◽  
B. O’Brien ◽  
E.J. O’Callaghan ◽  
...  

The Irish milk payment system penalises against high milk somatic cell count (SCC). Previous studies have related farm management practices to herd SCC (Barkema et al., 1998); however similar study has never been undertaken in Ireland. Furthermore, these previous studies have generally been conducted in confined systems. The objective of this study was to investigate potential management factors affecting herd SCC in Irish, spring calving, grass based dairy herds.


1951 ◽  
Vol 10 (4) ◽  
pp. 841-866 ◽  
Author(s):  
G. L. Robertson ◽  
L. E. Casida ◽  
R. H. Grummer ◽  
A. B. Chapman

1982 ◽  
Vol 62 (3) ◽  
pp. 827-835
Author(s):  
A. H. FREDEEN ◽  
G. K. MacLEOD ◽  
I. McMILLAN ◽  
D. G. GRIEVE

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


2020 ◽  
Vol 1 (1) ◽  
pp. 32
Author(s):  
Alva Yuventus Lukas ◽  
Jusuf Wilson Meynerd Rafael

The purpose of this study is to determine the resource management factors that affect labor productivity as well as the dominant factors, with research sites on construction projects in eastern Indonesia, particularly in East Nusa Tenggara. This research is aimed at construction workers, such as masons, chief craftsmen, foremen, and workers. This study uses a survey method. Primary data were collected through a questionnaire, then formulated and processed. Data processing in the form of respondents' opinions and attitudes towards problems that exist in construction projects related to productivity, data analysis techniques use factor analysis methods and multiple linear regression analysis with the SPSS statistical program. Results of processing and discussion of data, it is found that : (A) Human Resource Management Factors that affect Labor Productivity in several construction projects in East Nusa Tenggara are About Age, X1, about Work Experience, X2, Level of Education, X3,  about Wages, X4, Total Family Count, X5, Working Health and Safety, X6, Relationship Workers, X7, about Managerial, X8, and about Influential Motivations, X9, together form the equation Y = 12,776 – 0,217.X1 + 0,151.X2 – 0,087.X3 - 0,074.X4 - 0,263.X5 - 0,468X6 - 0,058.X7 + 0,129.X8 + 0,384.X9 .    (B)  The dominant factors affecting respectively are the Occupational Health & Safety of Workers, X6, Subject to the Number of Dependents in the Family, X5, and Subjects of Motivation, X9.


2010 ◽  
Vol 1 (1) ◽  
pp. 169-169
Author(s):  
L.G. Baird ◽  
D.N. Logue ◽  
A.F. Carson ◽  
M.A. McCoy ◽  
N.E. O'Connell

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