Use of methane production data for genetic prediction in beef cattle: A review.

Methane (CH4) is a greenhouse gas that is produced and emitted from ruminant animals through enteric fermentation. Methane production from cattle has an environmental impact and is an energetic inefficiency. In the beef industry, CH4 production from enteric fermentation impacts all three pillars of sustainability: environmental, social, and economic. A variety of factors influence the quantity of CH4 produced during enteric fermentation, including characteristics of the rumen and feed composition. There are several methodologies available to either quantify or estimate CH4 production from cattle, all with distinct advantages and disadvantages. Methodologies include respiration calorimetry, the sulfur-hexafluoride tracer technique, infrared spectroscopy, prediction models, and the GreenFeed system. Published studies assess the accuracy of the various methodologies and compare estimates from different methods. There are advantages and disadvantages of each technology as they relate to the use of these phenotypes in genetic evaluation systems. Heritability and variance components of CH4 production have been estimated using the different CH4 quantification methods. Agreement in both the amounts of CH4 emitted and heritability estimates of CH4 emissions between various measurement methodologies varies in the literature. Using greenhouse gas traits in selection indices along with relevant output traits could provide producers with a tool to make selection decisions on environmental sustainability while also considering productivity. The objective of this review was to discuss factors that influence CH4 production, methods to quantify CH4 production for genetic evaluation, and genetic parameters of CH4 production in beef cattle.

Heritability and variance component estimation for feed and water intake behaviors of feedlot cattle.

Feed and water intake are two important aspects of cattle production that greatly impact the profitability, efficiency, and sustainability of producers. Feed and, to a lesser degree, water intake have been studied previously; however, there is little research on their associated animal behaviors and there is a lack of standardized phenotypes for these behaviors. Feed and water intakes obtained with an Insentec system (Hokofarm Group, The Netherlands) from 830 crossbred steers were used to compute five intake behaviors for both feed and water: daily sessions (DS), intake rate (IR), session size (SS), time per session (TS), and session interval (SI). Variance components and heritabilities were estimated for each trait. Heritabilities for feed intake behaviors were 0.50 ±â€…0.12, 0.63 ±â€…0.12, 0.40 ±â€…0.13, 0.35 ±â€…0.12, and 0.60 ±â€…0.12 for DS, IR, SS, TS, and SI, respectively. Heritabilities for water intake behaviors were 0.56 ±â€…0.11, 0.88 ±â€…0.07, 0.70 ±â€…0.11, 0.54 ±â€…0.12, and 0.80 ±â€…0.10 for NS, IR, SS, TS, and SI, respectively. Daily dry matter intake (DDMI) and daily water intake (DWI) had heritabilities of 0.57 ±â€…0.11 and 0.44 ±â€…0.11. Phenotypic correlations varied between pairs of traits (-0.83 to 0.82). Genetic correlations between DDMI and feed intake behaviors were moderate to high, while genetic correlations between DWI and water intake behaviors were low to moderate. Several significant single nucleotide polymorphisms (SNP) were identified for the feed and water intake behaviors. Genes and previously reported quantitative trait loci near significant SNPs were evaluated. The results indicated that feed and water intake behaviors are influenced by genetic factors and are heritable, providing one additional route to evaluate or manipulate feed and water intake.

Feed and water intake are important aspects of cattle production to understand because they impact producer profitability and sustainability. While feed intake and, to a lesser degree, water intake have previously been studied, the associated feeding and drinking behaviors are relatively unknown and lack standardized phenotypes. Using individual animal feed and water intake records, five behaviors were evaluated for feed and water intake from crossbred feedlot steers. The behaviors evaluated were daily sessions (no./d), session size (kg), time per session (s), intake rate (g/s), and session interval (min). The impact of season (winter vs. summer) and bunk management (ad libitum vs. slick) on feeding and drinking behaviors was evaluated. Heritability and variance components were estimated for all feeding and drinking behaviors. Pairwise phenotypic correlations between behaviors were discussed. The relationship between intake and feeding or drinking behaviors was evaluated with genetic correlations. A genome-wide association study identified several significant single nucleotide polymorphisms for feeding and drinking behaviors. The results indicate that feeding and drinking behaviors are heritable and may be one additional route to evaluate feed and water intake.

Characterization of the number of spot samples required for quantification of gas fluxes and metabolic heat production from grazing beef cows using a GreenFeed.

Enteric fermentation from cattle results in greenhouse gas production that is an environmental concern and also an energetic loss. Several methods exist to quantify gas fluxes; however, an open circuit gas quantification system (OCGQS) allows for unencumbered quantification of methane (CH4), carbon dioxide (CO2), and oxygen (O2) from grazing cattle. While previous literature has proven the accuracy of an OCGQS, little work has been done to establish the minimum number of spot samples required to best evaluate an individual grazing animal's gas fluxes and metabolic heat production. A GreenFeed system (C-Lock Inc.) was used to collect at least 100 spot samples each from 17 grazing cows. The mean gas fluxes and metabolic heat production were computed starting from the first 10 visits (forward) and increasing by increments of 10 until an animal had 100 visits. Mean gas fluxes and metabolic heat production were also computed starting from visit 100 (reverse) in increments of 10 using the same approach. Pearson and Spearman correlations were computed between the full 100 visits and each shortened visit interval. A large increase in correlations were seen between 30 and 40 visits. Thus, mean forward and reverse gas fluxes and metabolic heat production were also computed starting at 30 visits and increasing by 2 until 40 visits. The minimum number of spot samples was determined when correlations with the full 100 visits were greater than 0.95. The results indicated that the minimum numbers of spot samples needed for accurate quantification of CH4, CO2, and O2 gas fluxes are 38, 40, and 40, respectively. Metabolic heat production can be calculated using gas fluxes collected by the OCGQS with 36 spot samples. Practically, calculation of metabolic heat production will require 40 spot samples because the component gases for metabolic heat calculation require up to 40 spot samples. Published literature from nongrazing (confined) environments recommended a similar number of total spot samples. Large variation existed around the average number of spot samples for an animal per day, therefore a wide range of test durations may be needed to meet the same number of spot samples in different populations. For this reason, protocols for the OCGQS should be based on the total number of spot samples, rather than a test duration.

Enteric fermentation in ruminant livestock species produces methane (CH4), which has negative effects on the environment and producer profitability. Gas fluxes from livestock species can be quantified with an open-circuit gas quantification system (OCGQS) or GreenFeed (C-Lock Inc., Rapid City, SD). However, little work has been done to establish a standardized protocol for OCGQS use in grazing beef cows. The minimum number of spot samples for quantification of CH4, carbon dioxide (CO2), oxygen (O2), and metabolic heat production was determined for grazing beef cows. The minimum number of spot samples needed for accurate quantification of CH4 was 38. Forty spot samples were needed to quantify CO2 and O2. Metabolic heat production can be calculated using CH4, CO2, and O2 gas fluxes from the OCGQS with 36 spot samples. Approximately 30 d were needed for animals in the current study to obtain the recommended number of visits for gas quantification, but this could vary across studies depending on the frequency of animals visiting the unit. There was large variability in the duration needed to obtain the recommended number of spot samples. Therefore, OCGQS protocols should include a minimum number of spot samples rather than a test duration.