Prediction of enteric methane emissions from Holstein dairy cows fed various forage sources

Abstract

Milk fatty acid (FA) profile has been previously used as a predictor of enteric CH 4 output in dairy cows fed diets supplemented with plant oils, which can potentially impact ruminal fermentation. The objective of this study was to investigate the relationships between milk FA and enteric CH 4 emissions in lactating dairy cows fed different types of forages in the context of commonly fed diets. A total of 81 observations from three separate 3 × 3 Latin square design (32-day periods) experiments including a total of 27 lactating cows (96 ± 27 days in milk; mean ± SD) were used. Dietary forages were included at 60% of ration dry matter and were as follows: (1) 100% corn silage, (2) 100% alfalfa silage, (3) 100% barley silage, (4) 100% timothy silage, (5) 50 : 50 mix of corn and alfalfa silages, (6) 50 : 50 mix of barley and corn silages and (7) 50 : 50 mix of timothy and alfalfa silages. Enteric CH 4 output was measured using respiration chambers during 3 consecutive days. Milk was sampled during the last 7 days of each period and analyzed for components and FA profile. Test variables included dry matter intake (DMI; kg/day), NDF (%), ether extract (%), milk yield (kg/day), milk components (%) and individual milk FA (% of total FA). Candidate multivariate models were obtained using the Least Absolute Shrinkage and Selection Operator and Least-Angle Regression methods based on the Schwarz Bayesian Criterion. Data were then fitted into a random regression using the MIXED procedure including the random effects of cow, period and study. A positive correlation was observed between CH 4 and DMI (r = 0.59, P < 0.001), whereas negative associations were observed between CH 4 and cis9-17:1 (r = − 0.58, P < 0.001), and trans8, cis13-18:2 (r = − 0.51, P < 0.001). Three different candidate models were selected and the best fit candidate model predicted CH 4 with a coefficient of determination of 0.84 after correction for cow, period and study effects and was: CH 4 (g/day) = 319.7 − 57.4 × 15:0 − 13.8 × cis9-17:1 − 39.5 × trans10-18:1 − 59.9 × cis11-18:1 − 253.1 × trans8, cis12-18:2 − 642.7 × trans8, cis13-18:2 − 195.7 × trans11, cis15-18:2 + 16.5 × DMI. Overall and linear prediction biases of all models were not significant ( P > 0.19). Milk FA profile and DMI can be used to predict CH 4 emissions in dairy cows across a wide range of dietary forage sources.

Prediction of methane emission from lactating dairy cows using milk fatty acids and mid-infrared spectroscopy

“…Although these studies, with exception of Williams et al , show that MFA hold potential to reflect changes in rumen fermentation, due to discrepancies between studies, it remains unclear which MFA have the greatest potential as biomarker for CH 4 emission. Similar reservations hold for the CH 4 prediction equations given in several studies . The predictive power of the prediction equations range between 47% and 95% (Table ), but the MFA included in these equations often differ between studies, with only C17:1 cis ‐9 and C18:1 cis ‐11 appearing in two or more equations.…”

“…Several studies have related individual MFA (g 100 g −1 FA) to CH 4 emission in dairy cows . Straight short‐ and medium‐chain fatty acids (SMCFA) in milk arise almost exclusively from de novo synthesis in the mammary gland from acetate and β ‐hydroxybutyrate produced in the rumen .…”

“…The relation between MFA and CH 4 emission has resulted in the suggestion that MFA composition can be used to predict CH 4 emission in lactating dairy cows. Table summarises the studies that have investigated the predictive power of MFA composition for CH 4 emission and derived multi‐variate models to predict CH 4 emission . In all studies, MFA profile was elucidated using gas chromatography (GC), and detailed information regarding the GC method used to determine the MFA profile is provided in the respective studies.…”

Invited review: Large-scale indirect measurements for enteric methane emissions in dairy cattle: A review of proxies and their potential for use in management and breeding decisions

“…Currently, data are available from 9 studies: Chilliard et al Dijkstra et al (2016), and Rico et al (2016). Most of these studies have been extensively reviewed by Van Gastelen and Dijkstra (2016).…”

“…This indicates that the relation between milk FA profile and CH 4 emission in dairy cows fed grass-and grass silage-based diets differs from that with other types of diets, and suggests that diet-specific prediction equations may need to be developed or diet composition may need to be included in the prediction equations. Rico et al (2016) combined feed intake, diet composition (i.e., CP content, NDF content, starch content, and fat content), and milk production with milk FA to develop CH 4 prediction equations. The best fit was observed for the model combining milk FA, feed intake, diet composition, and milk production (R 2 = 0.84), which was slightly better than the model combining only milk FA and diet composition (R 2 = 0.80).…”