scholarly journals Current Dairy Herd Management Practices and their Influence on Milk Yield and Subclinical Ketosis in an Intensive Dairy Production Region of Uganda

2020 ◽  
Vol 24 (1) ◽  
pp. 1-10
Author(s):  
Takeshi MIYAMA ◽  
Joseph BYARUHANGA ◽  
Ikuo OKAMURA ◽  
Hiroki NAKATSUJI ◽  
Toshihiko NAKAO ◽  
...  
Keyword(s):  
Milk Yield ◽  
Management Practices ◽  
Dairy Herd ◽  
Dairy Production ◽  
Herd Management ◽  
Subclinical Ketosis ◽  
Production Region

scholarly journals Effect of Business and Dairy Herd Management Practices on the Variable Cost of Producing Milk

1987 ◽  
Vol 70 (8) ◽  
pp. 1701-1709 ◽  
Author(s):  
C.B. Williams ◽  
P.A. Oltenacu ◽  
C.A. Bratton ◽  
R.A. Milligan
Keyword(s):  
Management Practices ◽  
Dairy Herd ◽  
Variable Cost ◽  
Herd Management

A survey on dairy heifer farm management practices in a Western-European plainland, the French Pays de la Loire region

2012 ◽  
Vol 150 (4) ◽  
pp. 518-533 ◽  
Author(s):  
Y. LE COZLER ◽  
O. RECOURSÉ ◽  
E. GANCHE ◽  
D. GIRAUD ◽  
J. DANEL ◽  
...  
Keyword(s):  
Management Practices ◽  
Experimental Studies ◽  
Herd Size ◽  
Detection Methods ◽  
Herd Management ◽  
Production Region ◽  
Qualitative Survey ◽  
Small Set ◽  
Dairy Heifer ◽  
The Impact

SUMMARYDespite practical information and applied results from numerous experimental studies and/or field observations, there is a persistent gap between scientific recommendations and on-farm reality. There are numerous published reports on the impact of dairy heifer herd management conditions on short-term, medium-term and long-term performances, but few studies on actual dairy heifer herd management practices – particularly in France. In an attempt to address this shortfall, a survey was conducted in 2010 on 449 herds located in the second largest dairy production region, the Pays de la Loire region (Western France). Economic-related aspects of heifer farming were not addressed. The essentially qualitative survey information was collected by 107 independent agricultural technologists. A quantitative analysis based on a small set of the most representative key production criteria was also conducted on a representative sub-sample of 286 herds. Mean herd size, at 46·6 cows per farm, and milk production, at 7953 kg milk/cow/lactation, were close to French national averages (47·3 cows per farm and 8109 kg milk/cow/lactation). The survey covered nine core themes and confirmed an all-round lack of precise monitoring on animal growth, as reported in earlier studies performed outside France. Most of the farmers surveyed considered animal weight a useful indicator for estimating growth performance. However, very few actually weighed their animals, despite the fact that 0·80 of the farmers surveyed aimed to calve their heifers before 30 months of age, with 0·55 of them setting a minimum calving weight target of at least 610 kg. Mean calf age at weaning was 2·9 months, but in practice this was >3·5 months in 0·31 of cases. Although farmers differ on certain practices, common core foci emerged: weight or age targets for pre-determined growth and development stages (at weaning or at service), recycling non-marketable milk for feeding young calves, essentially visual oestrus detection methods, and others. Based on the farmers’ declarations, the estimated time spent rearing a heifer from birth to calving ranges from 12 to 15 h per animal, with most farmers spending an estimated 0–2 h/day rearing their heifers. While almost two-thirds of farmers stated that rearing heifers was a necessity, 0·36 of this survey population claimed they enjoyed the work, whereas 0·02 of the farmers felt the work was purely a chore. Mirroring the conclusions from other countries, dairy heifer herd performances could be improved through better animal monitoring and management.

Dynamic probabilistic simulation of dairy herd management practices. II. Comparison of strategies in order to change a herd's calving pattern

1993 ◽  
Vol 37 (1-2) ◽  
pp. 133-152 ◽  
Author(s):  
A.W. Jalvingh ◽  
J.A.M. van Arendonk ◽  
A.A. Dijkhuizen ◽  
J.A. Renkema
Keyword(s):  
Management Practices ◽  
Dairy Herd ◽  
Herd Management ◽  
Probabilistic Simulation

scholarly journals Körperkondition und Stoffwechselstabilität als Grundlage für eine hohe Milchleistung bei ungestörter Fruchtbarkeit und allgemeiner Gesundheit von Milchkühen

2003 ◽  
Vol 46 (6) ◽  
pp. 513-526 ◽  
Author(s):  
R. Staufenbiel ◽  
U. Schröder ◽  
C.-C. Gelfert ◽  
L. Panicke
Keyword(s):  
Dairy Cows ◽  
Milk Yield ◽  
Body Condition ◽  
General Health ◽  
Dairy Herd ◽  
Negative Energy ◽  
Backfat Thickness ◽  
Herd Management ◽  
Standard Curve ◽  
High Production

Abstract. Title of the paper: Body condition and metabolic stability as basis of high milk yield, reproductive performance, and general health in dairy cows The target of this study was to describe the interactions between body condition and various descriptors of yield and fertility. It was aimed to identify an optimal conditional range to be used in herd management which combines high milk yield with acceptable fertility traits and general health. For this purpose, backfat thickness was measured by ultrasound at 46111 dairy cows on 78 different farms and was subsequently related to production variables. Negative energy balance is getting more intense and prolonged with increasing milk yield. However a conditional nadir below 10 mm leads to decreased milk production. To reach a high production level without an increasing incidence of health disorders, conditional nadir should not decline below 13 mm backfat thickness on herd average. Lower value only lead to negligibly higher milk yield but cause a distinctively higher risk of fertility problems and culling. High herd yields do not have to be at expense of reproduction performance and can be achieved without extreme body condition losses. An efficient herd management can offset depression in fertility, which commonly is combined with increasing milk yield. It is suggested a standard curve for backfat thickness throughout lactation to be used in dairy herd management.

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