A note on some of the factors that affect the water consumption of lactating dairy cows at pasture

1983 ◽  
Vol 36 (2) ◽  
pp. 303-306 ◽  
Author(s):  
C. R. Stockdale ◽  
K. R. King
Keyword(s):  
Dairy Cows ◽  
Water Intake ◽  
Water Consumption ◽  
Dry Matter ◽  
Dry Matter Intake ◽  
Total Water ◽  
Total Water Consumption ◽  
Lactating Dairy Cows ◽  
Dry Matter Concentration ◽  
Matter Concentration

ABSTRACTThe influence of the level of dry-matter intake and the dry-matter concentration in the diet on the water consumption of dairy cows in early lactation was investigated for a 2-month period from early August to early October. The importance of the various components of weather on voluntary water intake was also examined. The cows used in the experiment either grazed pasture alone, or were offered pasture and pasture hay supplements. Mean voluntary water intake increased by 2·30 kg per cow per day for every additional kg dry matter consumed and also increased by 0·053 kg per cow per day for each g/kg increase in dry matter concentration. Of the climatic factors, rainfall had the greatest single influence on the daily fluctuations in voluntary water intake and this was negative. Intake was also negatively related to minimum temperature, relative humidity and wind, and positively related to sunshine and evaporation. Although maximum temperature per se had no apparent influence on intake, it showed a positive relationship after the removal of the effects of rainfall. A model for the prediction of total water consumption is:Total water consumption (kg per cow per day) = 11·34 + 4·63 dry-matter intake (kg per cow per day) –0·036 dry-matter concentration (g/kg) + 0·84 mean temperature (°C).This can only be used to predict the water requirements of lactating dairy cows in different environments.

scholarly journals Effects of transient changes in silage dry matter concentration on lactating dairy cows

2013 ◽  
Vol 96 (6) ◽  
pp. 3924-3935 ◽  
Author(s):  
L.R. McBeth ◽  
N.R. St-Pierre ◽  
D.E. Shoemaker ◽  
W.P. Weiss
Keyword(s):  
Dairy Cows ◽  
Dry Matter ◽  
Lactating Dairy Cows ◽  
Dry Matter Concentration ◽  
Matter Concentration

scholarly journals Predicting Daily Dry Matter Intake Using Feed Intake of First Two Hours after Feeding in Mid and Late Lactation Dairy Cows with Fed Ration Three Times Per Day

Animals ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 104
Author(s):  
Shulin Liang ◽  
Chaoqun Wu ◽  
Wenchao Peng ◽  
Jian-Xin Liu ◽  
Hui-Zeng Sun
Keyword(s):  
Dairy Cows ◽  
Milk Yield ◽  
Dry Matter ◽  
Prediction Equation ◽  
Dry Matter Intake ◽  
Validation Dataset ◽  
Nutrient Requirements ◽  
Independent Dataset ◽  
Lactating Dairy Cows ◽  
Proposed Model

The objective of this study was to evaluate the feasibility of using the dry matter intake of first 2 h after feeding (DMI-2h), body weight (BW), and milk yield to estimate daily DMI in mid and late lactating dairy cows with fed ration three times per day. Our dataset included 2840 individual observations from 76 cows enrolled in two studies, of which 2259 observations served as development dataset (DDS) from 54 cows and 581 observations acted as the validation dataset (VDS) from 22 cows. The descriptive statistics of these variables were 26.0 ± 2.77 kg/day (mean ± standard deviation) of DMI, 14.9 ± 3.68 kg/day of DMI-2h, 35.0 ± 5.48 kg/day of milk yield, and 636 ± 82.6 kg/day of BW in DDS and 23.2 ± 4.72 kg/day of DMI, 12.6 ± 4.08 kg/day of DMI-2h, 30.4 ± 5.85 kg/day of milk yield, and 597 ± 63.7 kg/day of BW in VDS, respectively. A multiple regression analysis was conducted using the REG procedure of SAS to develop the forecasting models for DMI. The proposed prediction equation was: DMI (kg/day) = 8.499 + 0.2725 × DMI-2h (kg/day) + 0.2132 × Milk yield (kg/day) + 0.0095 × BW (kg/day) (R2 = 0.46, mean bias = 0 kg/day, RMSPE = 1.26 kg/day). Moreover, when compared with the prediction equation for DMI in Nutrient Requirements of Dairy Cattle (2001) using the independent dataset (VDS), our proposed model shows higher R2 (0.22 vs. 0.07) and smaller mean bias (−0.10 vs. 1.52 kg/day) and RMSPE (1.77 vs. 2.34 kg/day). Overall, we constructed a feasible forecasting model with better precision and accuracy in predicting daily DMI of dairy cows in mid and late lactation when fed ration three times per day.

scholarly journals Effect of Heat Stress on Bacterial Composition and Metabolism in the Rumen of Lactating Dairy Cows

Animals ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. 925
Author(s):  
Zhao ◽  
Min ◽  
Zheng ◽  
Wang
Keyword(s):  
Heat Stress ◽  
Dairy Cows ◽  
Milk Production ◽  
Dry Matter ◽  
16S Rrna Genes ◽  
Dry Matter Intake ◽  
Rrna Genes ◽  
Bacterial Composition ◽  
Rumen Ph ◽  
Lactating Dairy Cows

Heat stress negatively impacts the health and milk production of dairy cows, and ruminal microbial populations play an important role in dairy cattle’s milk production. Currently there are no available studies that investigate heat stress-associated changes in the rumen microbiome of lactating dairy cattle. Improved understanding of the link between heat stress and the ruminal microbiome may be beneficial in developing strategies for relieving the influence of heat stress on ruminants by manipulating ruminal microbial composition. In this study, we investigated the ruminal bacterial composition and metabolites in heat stressed and non-heat stressed dairy cows. Eighteen lactating dairy cows were divided into two treatment groups, one with heat stress and one without heat stress. Dry matter intake was measured and rumen fluid from all cows in both groups was collected. The bacterial 16S rRNA genes in the ruminal fluid were sequenced, and the rumen pH and the lactate and acetate of the bacterial metabolites were quantified. Heat stress was associated with significantly decreased dry matter intake and milk production. Rumen pH and rumen acetate concentrations were significantly decreased in the heat stressed group, while ruminal lactate concentration increased. The influence of heat stress on the microbial bacterial community structure was minor. However, heat stress was associated with an increase in lactate producing bacteria (e.g., Streptococcus and unclassified Enterobacteriaceae), and with an increase in Ruminobacter, Treponema, and unclassified Bacteroidaceae, all of which utilize soluble carbohydrates as an energy source. The relative abundance of acetate-producing bacterium Acetobacter decreased during heat stress. We concluded that heat stress is associated with changes in ruminal bacterial composition and metabolites, with more lactate and less acetate-producing species in the population, which potentially negatively affects milk production.

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