Feeding glycerol-enriched yeast culture improves lactation performance, energy status, and hepatic gluconeogenic enzyme expression of dairy cows during the transition period1

2016 ◽  
Vol 94 (6) ◽  
pp. 2441-2450
Author(s):  
G. Ye ◽  
J. Liu ◽  
Y. Liu ◽  
X. Chen ◽  
S. F. Liao ◽  
...  
2020 ◽  
pp. 1-8
Author(s):  
Amira Rachah ◽  
Olav Reksen ◽  
Nils Kristian Afseth ◽  
Valeria Tafintseva ◽  
Sabine Ferneborg ◽  
...  

Abstract The objective of the study was to evaluate the potential of Fourier transform infrared spectroscopy (FTIR) analysis of milk samples to predict body energy status and related traits (energy balance (EB), dry matter intake (DMI) and efficient energy intake (EEI)) in lactating dairy cows. The data included 2371 milk samples from 63 Norwegian Red dairy cows collected during the first 105 days in milk (DIM). To predict the body energy status traits, calibration models were developed using Partial Least Squares Regression (PLSR). Calibration models were established using split-sample (leave-one cow-out) cross-validation approach and validated using an external test set. The PLSR method was implemented using just the FTIR spectra or using the FTIR together with milk yield (MY) or concentrate intake (CONCTR) as predictors of traits. Analyses were conducted for the entire first 105 DIM and separately for the two lactation periods: 5 ≤ DIM ≤ 55 and 55 < DIM ≤ 105. To test the models, an external validation using an independent test set was performed. Predictions depending on the parity (1st, 2nd and 3rd-to 6th parities) in early lactation were also investigated. Accuracy of prediction (r) for both cross-validation and external test set was defined as the correlation between the predicted and observed values for body energy status traits. Analyzing FTIR in combination with MY by PLSR, resulted in relatively high r-values to estimate EB (r = 0.63), DMI (r = 0.83), EEI (r = 0.84) using an external validation. Only moderate correlations between FTIR spectra and traits like EB, EEI and dry matter intake (DMI) have so far been published. Our hypothesis was that improvements in the FTIR predictions of EB, EEI and DMI can be obtained by (1) stratification into different stages of lactations and different parities, or (2) by adding additional information on milking and feeding traits. Stratification of the lactation stages improved predictions compared with the analyses including all data 5 ≤ DIM ≤105. The accuracy was improved if additional data (MY or CONCTR) were included in the prediction model. Furthermore, stratification into parity groups, improved the predictions of body energy status. Our results show that FTIR spectral data combined with MY or CONCTR can be used to obtain improved estimation of body energy status compared to only using the FTIR spectra in Norwegian Red dairy cattle. The best prediction results were achieved using FTIR spectra together with MY for early lactation. The results obtained in the study suggest that the modeling approach used in this paper can be considered as a viable method for predicting an individual cow's energy status.


1998 ◽  
Vol 1998 ◽  
pp. 206-206
Author(s):  
R.J. Dewhurst ◽  
D. Wadhwa ◽  
L.P. Borgida ◽  
D.W.R. Davies ◽  
W.J. Fisher

Falling prices for cereals and beneficial effects on milk protein concentrations may promote greater inclusions of rapidly fermented ingredients in dairy rations. There is, however, a limit to the inclusion of these feeds into dairy rations beyond which performance declines due to sub-acidosis and related disorders. The feed compounder will need to be able to set limits on levels of feeding concentrates according to these risks. The objective of this experiment was to evaluate the effect of feeds of different acidogenicity (Wadhwa et al., 1998) on lactation performance of dairy cows offered diets based on grass- or maize-silage.Twelve multiparous Holstein-Friesian cows in the third month of lactation were used for this experiment. The experimental design involved adaptation and covariance recording on a standard diet (grass silage and 10 kg concentrates per day), followed by three 21-day experimental periods arranged as four 3x3 Latin Squares. The Latin Squares were constrained to a single forage to avoid difficulties in changeovers between grass silage and maize silage.


2016 ◽  
Vol 94 (suppl_5) ◽  
pp. 730-731
Author(s):  
L. F. Ferraretto ◽  
C. S. Ballard ◽  
C. J. Sniffen ◽  
I. Shinzato

Antioxidants ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1478
Author(s):  
Tainara Cristina Michelotti ◽  
Erminio Trevisi ◽  
Johan S. Osorio

The objective of the present study was to evaluate the effects of an antioxidant and anti-inflammatory compound found in rosemary plants (Salvia rosmarinus) named carnosic acid during the transition period of dairy cows. From day 1 to 3 after calving, 16 multiparous Holstein cows received a daily intravenous infusion of either 500 mL of saline (NaCl 0.9%; Saline; n = 8) or carnosic acid at a rate of 0.3 mg/kg of BW supplied in 500 mL of saline (CA; n = 8). Blood samples were taken at –7, 2, 5, 7, 14, and 21 d relative to parturition, then analyzed for metabolites related to energy metabolism, muscle mass catabolism, liver function, inflammation, and oxidative stress. CA infusion tended to improve milk performance; however, DMI was unaffected by treatment. At 2 d relative to parturition, CA cows had lower blood concentrations of haptoglobin, paraoxonase, FRAP, and NO2– than saline cows. After treatment infusions, haptoglobin remained lower in CA cows than saline at 5 d relative to parturition. Our results demonstrate that carnosic acid promoted positive responses on inflammation and oxidative stress biomarkers and may promote beneficial effects on lactation performance in peripartal dairy cows.


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