| Autor: |
van Gastelen S; Top Institute Food and Nutrition, PO Box 557, 6700 AN Wageningen, the Netherlands; Animal Nutrition Group, Wageningen University & Research, PO Box 338, 6700 AH Wageningen, the Netherlands. Electronic address: sanne.vangastelen@wur.nl., Mollenhorst H; Qlip B.V., PO Box 119, 7200 AC Zutphen, the Netherlands., Antunes-Fernandes EC; Top Institute Food and Nutrition, PO Box 557, 6700 AN Wageningen, the Netherlands; Food Quality and Design Group, Wageningen University & Research, PO Box 17, 6700 AH Wageningen, the Netherlands., Hettinga KA; Food Quality and Design Group, Wageningen University & Research, PO Box 17, 6700 AH Wageningen, the Netherlands., van Burgsteden GG; Qlip B.V., PO Box 119, 7200 AC Zutphen, the Netherlands., Dijkstra J; Animal Nutrition Group, Wageningen University & Research, PO Box 338, 6700 AH Wageningen, the Netherlands., Rademaker JLW; Qlip B.V., PO Box 119, 7200 AC Zutphen, the Netherlands. |
| Jazyk: |
angličtina |
| Zdroj: |
Journal of dairy science [J Dairy Sci] 2018 Jun; Vol. 101 (6), pp. 5582-5598. Date of Electronic Publication: 2018 Mar 15. |
| DOI: |
10.3168/jds.2017-13052 |
| Abstrakt: |
The objective of the present study was to compare the prediction potential of milk Fourier-transform infrared spectroscopy (FTIR) for CH 4 emissions of dairy cows with that of gas chromatography (GC)-based milk fatty acids (MFA). Data from 9 experiments with lactating Holstein-Friesian cows, with a total of 30 dietary treatments and 218 observations, were used. Methane emissions were measured for 3 consecutive days in climate respiration chambers and expressed as production (g/d), yield (g/kg of dry matter intake; DMI), and intensity (g/kg of fat- and protein-corrected milk; FPCM). Dry matter intake was 16.3 ± 2.18 kg/d (mean ± standard deviation), FPCM yield was 25.9 ± 5.06 kg/d, CH 4 production was 366 ± 53.9 g/d, CH 4 yield was 22.5 ± 2.10 g/kg of DMI, and CH 4 intensity was 14.4 ± 2.58 g/kg of FPCM. Milk was sampled during the same days and analyzed by GC and by FTIR. Multivariate GC-determined MFA-based and FTIR-based CH 4 prediction models were developed, and subsequently, the final CH 4 prediction models were evaluated with root mean squared error of prediction and concordance correlation coefficient analysis. Further, we performed a random 10-fold cross validation to calculate the performance parameters of the models (e.g., the coefficient of determination of cross validation). The final GC-determined MFA-based CH 4 prediction models estimate CH 4 production, yield, and intensity with a root mean squared error of prediction of 35.7 g/d, 1.6 g/kg of DMI, and 1.6 g/kg of FPCM and with a concordance correlation coefficient of 0.72, 0.59, and 0.77, respectively. The final FTIR-based CH 4 prediction models estimate CH 4 production, yield, and intensity with a root mean squared error of prediction of 43.2 g/d, 1.9 g/kg of DMI, and 1.7 g/kg of FPCM and with a concordance correlation coefficient of 0.52, 0.40, and 0.72, respectively. The GC-determined MFA-based prediction models described a greater part of the observed variation in CH 4 emission than did the FTIR-based models. The cross validation results indicate that all CH 4 prediction models (both GC-determined MFA-based and FTIR-based models) are robust; the difference between the coefficient of determination and the coefficient of determination of cross validation ranged from 0.01 to 0.07. The results indicate that GC-determined MFA have a greater potential than FTIR spectra to estimate CH 4 production, yield, and intensity. Both techniques hold potential but may not yet be ready to predict CH 4 emission of dairy cows in practice. Additional CH 4 measurements are needed to improve the accuracy and robustness of GC-determined MFA and FTIR spectra for CH 4 prediction.
(Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.) |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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