Genetic variability in the feeding behavior of crossbred growing cattle and associations with performance and feed efficiency

Abstract

The objectives of the present study were to estimate genetic parameters for several feeding behavior traits in growing cattle, as well as the genetic associations among and between feeding behavior and both performance and feed efficiency traits. An additional objective was to investigate the use of feeding behavior traits as predictors of genetic merit for feed intake. Feed intake and live-weight data on 6,088 growing cattle were used of which 4,672 had ultrasound data and 1,548 had feeding behavior data. Feeding behavior traits were defined based on individual feed events or meal events (where individual feed events were grouped into meals). Univariate and bivariate animal linear mixed models were used to estimate (co)variance components. Heritability estimates (± SE) for the feeding behavior traits ranged from 0.19 ± 0.08 for meals per day to 0.61 ± 0.10 for feeding time per day. The coefficient of genetic variation per trait varied from 5% for meals per day to 22% for the duration of each feed event. Genetically heavier cattle, those with a higher daily energy intake (MEI), or those that grew faster had a faster feeding rate, as well as a greater energy intake per feed event and per meal. Better daily feed efficiency (i.e. lower residual energy intake) was genetically associated with both a shorter feeding time per day and shorter meal time per day. In a validation population of 321 steers and heifers, the ability of estimated breeding values (EBV) for MEI to predict (adjusted) phenotypic MEI was demonstrated; EBVs for MEI were estimated using multi-trait models with different sets of predictor traits such as liveweight and/or feeding behaviors. The correlation (± SE) between phenotypic MEI and EBV for MEI marginally improved (P < 0.001) from 0.64 ± 0.03 to 0.68 ± 0.03 when feeding behavior phenotypes from the validation population were included in a genetic evaluation that already included phenotypic mid-test metabolic live-weight from the validation population. This is one of the largest studies demonstrating that significant exploitable genetic variation exists in the feeding behavior of young crossbred growing cattle; such feeding behavior traits are also genetically correlated with several performance and feed efficiency metrics. Nonetheless, there was only a marginal benefit to the inclusion of time-related feeding behavior phenotypes in a genetic evaluation for MEI to improve the precision of the EBVs for this trait.

Estimates of genetic parameters for feeding behavior traits and their associations with feed efficiency in Holstein cows

“…Most of the feeding behavior measures demonstrated strong genetic correlations, showing that with more visits or more meals per day, cows spend less time at each feeder visit or meal with a lower intake per visit or meal. Similarly, strong genetic and phenotypic correlations among number of visits and duration and intake per visit have been reported in beef cattle and pigs (Kavlak and Uimari, 2019;Kelly et al, 2021). Because feeding rate is a ratio of the weight of DM consumed and time, strong estimated genetic correlations with duration of each visit or meal (−0.58 and −0.98), total duration of visits and meals (−0.97 and −0.98), and intake per visit or meal (0.74) were also expected.…”

“…To our knowledge, Lin et al ( 2013) is the only published genetic study of feeding behavior in dairy cattle; these authors reported heritability estimates of 0.45 to 0.50 for number of visits, feeding duration, feeding rate, and intake per visit in dairy heifers. Moderate to high heritability estimates have also been reported for feeding behavior in beef cattle (Nkrumah et al, 2007;Chen et al, 2014;Benfica et al, 2020;Kelly et al, 2021) and pigs (Lu et al, 2017;Kavlak and Uimari, 2019;Herrera-Cáceres et al, 2020). For example, Benfica et al (2020) reported heritability estimates from 0.27 to 0.35 for frequency of bunk visits, DMI per visit, feeding rate, and duration of each feeding event in Nellore cattle.…”

“…Comparing the same feeding behavior traits using the visit and meal concepts, we found little association between number of visits and number of meals (genetic and phenotypic correlations of 0.15 and 0.10), a weak association between duration of each visit and duration of each meal (genetic and phenotypic correlations of 0.30 and 0.09), and a moderate association between intake per visit and intake per meal (genetic and phenotypic correlations of 0.36 and 0.32). In beef cattle, Kelly et al (2021) also reported a very low genetic correlations of 0.06 between duration of a feeding event and a meal. In contrast, the respective genetic and phenotypic correlations between feeding rate per visit and per meal (0.99 and 0.82; Figure 1) showed that the different feeding behavior definitions using either meals or visits potentially have little influence on defining feeding rate.…”

“…No studies have been published in dairy cattle involving genetic parameters for feeding behavior defined as a meal concept. However, Kelly et al (2021) used a similar approach in crossbred growing cattle, and they also observed greater heritability estimates for direct measures of feeding behavior traits than those defined using a meal criterion. Despite the lack of a commonly agreed upon meal definition, the approach considered in the present study has been used in nutrition, management, and welfare studies in lactating dairy cows, with a meal criterion ranging from 20 to 35 min (Tolkamp and Kyriazakis, 1999;DeVries et al, 2003;DeVries and Chevaux, 2014).…”

“…However, little is known about the genetic variation of feeding behavior traits and their genetic correlations with feed efficiency traits in lactating dairy cows, as most studies have been reported in beef cattle and pigs, and studies involving dairy cattle have been limited. Studies in meat animals have shown high heritability estimates for feeding behavior traits, ranging from 0.17 to 0.61 (Kavlak and Uimari, 2019;Benfica et al, 2020;Herrera-Cáceres et al, 2020;Kelly et al, 2021;Olson et al, 2021), as well as strong genetic correlations between feeding behavior and feed efficiency. Therefore, feeding behavior may be used as an indicator trait for feed efficiency, using less expensive wearable sensors or computer vision systems that do not require measurement of individual intake and could be implemented on commercial farms to generate a greater number of phenotypic records.…”