Estimation of dry matter intake by n-alkanes in dairy cows fed TMR: effect of dosing technique and faecal collection time

2014 ◽  
Vol 54 (10) ◽  
pp. 1747 ◽  
Author(s):  
P. Bani ◽  
F. Piccioli Cappelli ◽  
A. Minuti ◽  
V. Ficuciello ◽  
V. Lopreiato ◽  
...  
Keyword(s):  
Dairy Cows ◽  
Dry Matter ◽  
Dairy Farms ◽  
Sampling Time ◽  
Dry Matter Intake ◽  
Lactating Cows ◽  
Lactating Dairy Cows ◽  
Faecal Samples ◽  
Source Of Error ◽  
Collection Time

Estimation of individual intakes in dairy cows would be beneficial to select animals according to efficiency of milk production. The n-alkanes technique has been used to estimate intake by dairy cows in free stall barns, limiting faecal samples to one or two per day, but diurnal variation in the ratio of dosed to natural alkanes in faeces represents a source of error. We aimed to adapt this technique to estimate feed intake on a large number of lactating dairy cows housed on commercial dairy farms. Using a change-over design, six lactating cows fed a TMR diet were given a dose of 0.5 g/day of C32 n-alkane administered once a day as a drench (DRE) or top fed (TP). Feed offered and refused were weighed daily. After the lead-in phases, faeces were collected at 0700 hours, 1400 hours and 1900 hours on the last 5 days of each dosing period. Dry matter intake (DMI) was estimated from C31, C33 and C32 concentrations in feeds and in faeces for each dosing system and sampling time. DMI estimated from C31 : C32 ratio was better correlated with measured individual DMI than estimates from C33 : C32 ratio. For DRE, the best correlation was for sampling at 1400 hours (R2 = 0.96, P < 0.001), but estimated DMI for the 1400 hours sampling was much higher than the actual DMI. For TP, the best correlation was for sampling at 0700 hours (R2 = 0.83, P < 0.001). Feeding C32 n-alkane and collecting faeces once a day at the same time (0700 hours) represents a valuable protocol to measure individual intake on a large number of animals.

EFFECT OF ABRUPTLY ADDING BUFFERS TO THE RATIONS OF LACTATING DAIRY COWS

1985 ◽  
Vol 65 (2) ◽  
pp. 521-523 ◽  
Author(s):  
ELLIOT BLOCK ◽  
L. D. MULLER
Keyword(s):  
Sodium Bicarbonate ◽  
Dairy Cows ◽  
Magnesium Oxide ◽  
Milk Fat ◽  
Dry Matter ◽  
Rumen Fluid ◽  
Dry Matter Intake ◽  
Milk Fat Depression ◽  
Lactating Cows ◽  
Lactating Dairy Cows

Feeding 0.23 kg of sodium bicarbonate plus 0.07 kg of magnesium oxide per day to cows with a milk fat depression tended to reduce dry matter intake temporarily. Milk production declined by 1.2 kg/day, milk fat increased by 0.43%, and rumen fluid pH increased as a result of buffer additions. There was also a trend toward higher blood alkaline indices. Key words: Buffers, lactating cows, sodium bicarbonate, magnesium oxide, milk fat depression

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.

Near-infrared reflectance spectroscopy for estimating food intake in housed dairy cows

1999 ◽  
Vol 1999 ◽  
pp. 93-93
Author(s):  
Y. Unal ◽  
P. C. Garnsworthy
Keyword(s):  
Dairy Cows ◽  
Dry Matter ◽  
Near Infrared ◽  
Reflectance Spectroscopy ◽  
Dry Matter Intake ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Infrared Reflectance Spectroscopy ◽  
Faecal Samples

Dry matter intake (DMI) is a major limitation to milk production in dairy cows, but is difficult to measure under commercial conditions where cows are housed and fed in groups. Several methods have been developed to estimate DMI by individual cows, such as using inert markers, where dual markers can be used to predict digestibility and faecal output simultaneously. However, their scope is limited by the laboratory analyses required and there are problems with marker dosing and recovery. Predictions of DMI by near-infrared reflectance spectroscopy (NIRS) have been reported, but they have been based on scanning forage samples to predict intake potential. Since DMI is a function of the animal as well as the diet, it is more logical to scan samples of faeces when predicting individual intakes. The objective of this study was to see whether NIRS could accurately predict DMI from faecal samples of individual cows.

scholarly journals Effects of Prepartum Dry Matter Intake and Forage Percentage on Postpartum Performance of Lactating Dairy Cows

2001 ◽  
Vol 84 (9) ◽  
pp. 2051-2058 ◽  
Author(s):  
C.S. Holcomb ◽  
H.H. Van Horn ◽  
H.H. Head ◽  
M.B. Hall ◽  
C.J. Wilcox
Keyword(s):  
Dairy Cows ◽  
Dry Matter ◽  
Dry Matter Intake ◽  
Lactating Dairy Cows ◽  
Postpartum Performance
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