Influence of Cracked, Coarse Ground or Fine Ground Corn on Digestion, Dry Matter Intake and Milk Yield in Holstein Cows

2009 ◽  
Vol 35 (2) ◽  
pp. 149-154 ◽  
Author(s):  
A. Plascencia ◽  
V. M. González-Vizcarra ◽  
M. A. López-Soto ◽  
D. May ◽  
L. C. Pujol ◽  
...  
1991 ◽  
Vol 74 (5) ◽  
pp. 1609-1622 ◽  
Author(s):  
J.E. Wohlt ◽  
S.L. Chmiel ◽  
P.K. Zajac ◽  
L. Backer ◽  
D.B. Blethen ◽  
...  

Animals ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 104
Author(s):  
Shulin Liang ◽  
Chaoqun Wu ◽  
Wenchao Peng ◽  
Jian-Xin Liu ◽  
Hui-Zeng Sun

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.


2010 ◽  
Vol 39 (7) ◽  
pp. 1548-1557 ◽  
Author(s):  
Nelson Massaru Fukumoto ◽  
Julio Cesar Damasceno ◽  
Fermino Deresz ◽  
Carlos Eugênio Martins ◽  
Antônio Carlos Cóser ◽  
...  

The objective of this study was to evaluate milk yield and composition, dry matter intake, and stocking rate in pastures with tanzania grass (Panicum maximum cv. Tanzânia), star grass (Cynodon nlemfuensis cv. Estrela-Africana), and marandu grass (Brachiaria brizantha cv. Marandu). The grasses were managed in a rotational grazing system with Holstein x Zebu crossbreed cows, with a 30-day resting period and three days of paddock occupation. The pastures were fertilized with 1,000 kg/ha/year using the 20:05:20 (NPK) formula, split in three applications during the rainy season. It was used a complete random block experimental design with three factors being studied and two replications. In the experiment, four cows/paddock were used and, when it was necessary, regulator animals were added in order to obtain a supply of 7% body weight green forage dry matter. The animals were individually fed concentrate at 2 kg/day during the experimental period. Milk yield did not differ among the three grasses, with values of 9.1; 9.1; and 8.7 kg/cow/day for pastures with tanzania grass, star grass and marandu grass, respectively. Similarly, grass did not affect milk chemical composition. Stocking rate was similar among the three grasses, with values of 4.6; 4.5 and 5.0 UA/ha for tanzania grass, star grass and marandu grass, respectively. The highest dry matter intake was observed for tanzania grass with 2.6% of the body weight while stargrass (2.3%) and marandu grass (2.4%) did not differ among each other. The highest dry matter intake on tanzania grass pasture was not reflected on milk yield per animal. Milk yield and composition and stocking rate are similar among the evaluated grasses.


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