Short Communication Heritability of predicted daily enteric methane emissions from growing Nellore cattle

Abstract

ABSTRACT. The objective of this study was to estimate the heritability of predicted daily enteric methane emissions (PME) from growing Nellore cattle. Dry matter intake (DMI) records of 955 Nellore animals that were born between 2004 and 2013, which were obtained in a postweaning performance test lasting 83 ± 15 days, were used. The PME of each animal, obtained as MJ/day and converted to g/day, was estimated using three equations: PME 1 (MJ/day) = 2.29 + 0.647 x DMI (kg/day), PME 2 (MJ/day) = 3.96 + 0.561 x DMI (kg/day), and PME 3 (MJ/day) = 4.41 + 0.50 x DMI (kg/day). The heritability (h 2 ) of PME obtained using the three equations was identical to the h 2 of DMI, regardless of whether the model included the effect of mid-test weight (h 2 = 0.32 ± 0.069) or not (h 2 = 0.48 ± 0.069). The equations were based exclusively on variations in DMI, and detected variations in this trait without taking into consideration individual differences in enteric methane emission caused by differences in fermentation and digestion capacity. Therefore, prediction equations of enteric methane emission from DMI are not adequate to estimate differences between 14124 T.L.P. Sobrinho et al.

Genetic and phenotypic parameter estimates for feed intake and pulmonary arterial pressure12

“…This estimate of ADG was within the range of previous findings (0.16 to 0.43) ( Fan et al, 1995 ). Correspondingly, the heritability estimate for ADMI was lower than the range of previous findings (0.32 to 0.40; Rolfe et al, 2011 ; Sobrinho et al, 2015 ). The differences between previously reported estimates for DMI heritability and our findings can be explained through data inconsistencies revolving around startup of the Growsafe system and the management plan inconsistencies during the first few years of the study.…”

Genetic and genomic analyses for predicted methane‐related traits in Japanese Black steers

“…Many studies have estimated genetic parameters and performed GWAS for CH 4 predicted by DMI, milk yield and maintenance traits (de Haas et al., 2011; Pickering, Chagunda, et al, 2015; Yin et al., 2015), milk fat composition (van Engelen, Bovenhuis, Dijkstra, Van Arendonk, & Visker, 2015), and milk mid‐infrared spectra (Kandel et al., 2017) in dairy cattle, and one study has estimated genetic parameters in beef cattle using DMI (Sobrinho et al., 2015). These studies suggested that predicted methane‐related traits can be available in genetic and genomic studies.…”

“…In addition, methane yield traits, which are the proportion of energy lost from the diet, are globally suggested to use for mitigating CH 4 from cattle and are also important indicators for feed efficiency (IPCC, 2006). Recently, moderate heritabilities for CH 4 and methane yield traits from approximately 0.1–0.5 in beef (Donoghue, Bird‐Gardiner, Arthur, Herd, & Hegarty, 2016; Hayes et al., 2016; Sobrinho et al., 2015) and dairy cattle (Breider, Wall, & Garnsworthy, 2019; de Haas et al., 2011; Lassen & Løvendahl, 2016; Pickering, Chagunda, et al, 2015; Yin, Pinent, Brügemann, Simianer, & König, 2015) were reported, and thus genetic selection of these methane‐related traits can contribute to mitigate CH 4 from cattle.…”