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Genetic and phenotypic relationships of feeding behavior and temperament with performance, feed efficiency, ultrasound, and carcass merit of beef cattle¹

J. D. Nkrumah^*,, D. H. Crews, Jr, J. A. Basarab, M. A. Price, E. K. Okine, Z. Wang, C. Li^, and S. S. Moore^,2

^* Igenity Livestock Production Business Unit, Merial Ltd.; and Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, Alberta, Canada, T6G 2P5; and Agriculture and Agri-Food Canada Research Centre, Lethbridge, Alberta, Canada, T1J 4B1; and and Alberta Agriculture, Food and Rural Development, Lacombe Research Centre, Lacombe, Alberta, Canada, T4L 1W1

	Abstract

Top Abstract INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 
Feeding behavior and temperament may be useful in genetic evaluations either as indicator traits for other economically relevant traits or because the behavior traits may have a direct economic value. We determined the variation in feeding behavior and temperament of beef cattle sired by Angus, Charolais, or Hybrid bulls and evaluated their associations with performance, efficiency, and carcass merit. The behavior traits were daily feeding duration, feeding head down (HD) time, feeding frequency (FF), and flight speed (FS, as a measure of temperament). A pedigree file of 813 animals forming 28 paternal half-sib families with about 20 progeny per sire was used. Performance, feeding behavior, and efficiency records were available on 464 animals of which 381 and 302 had records on carcass merit and flight speed, respectively. Large SE reflect the number of animals used. Direct heritability estimates were 0.28 ± 0.12 for feeding duration, 0.33 ± 0.12 for HD, 0.38 ± 0.13 for FF, and 0.49 ± 0.18 for FS. Feeding duration had a weak positive genetic (r_g) correlation with HD (r_g = 0.25 ± 0.32) and FS (r_g = 0.42 ± 0.26) but a moderate negative genetic correlation with FF (r_g = –0.40 ± 0.30). Feeding duration had positive phenotypic (r_p) and genetic correlations with DMI (r_p = 0.27; r_g = 0.56 ± 0.20) and residual feed intake (RFI; r_p = 0.49; r_g = 0.57 ± 0.28) but was unrelated phenotypically with feed conversion ratio [FCR; which is the reciprocal of the efficiency of growth (G:F)]. Feeding duration was negatively correlated with FCR (r_g = –0.25 ± 0.29). Feeding frequency had a moderate to high negative genetic correlation with DMI (r_g = –0.74 ± 0.15), FCR (r_g = –0.52 ± 0.21), and RFI (r_g = –0.77 ± 0.21). Flight speed was negatively correlated phenotypically with DMI (r_p = –0.35) but was unrelated phenotypically with FCR or RFI. On the other hand, FS had a weak negative genetic correlation with DMI (r_g = –0.11 ± 0.26), a moderate genetic correlation with FCR (r_g = 0.40 ± 0.26), and a negative genetic correlation with RFI (r_g = –0.59 ± 0.45). The results indicate that behavior traits may contribute to the variation in the efficiency of growth of beef cattle, and there are potential correlated responses to selection to improve efficiency. Feeding behavior and temperament may need to be included in the definition of beef cattle breeding goals, and approaches such as the culling of unmanageable cattle and the introduction of correct handling facilities or early life provision of appropriate experiences to improve handling will be useful.

Key Words: beef cattle • feed efficiency • feeding behavior • temperament

	INTRODUCTION

Top Abstract INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 
There are several ongoing worldwide research efforts directed toward genetic improvement in overall beef cattle production system efficiency to reduce production cost and improve profitability. Genetic parameter estimates on economically relevant traits (ERT) such as feed intake, feed conversion ratio (FCR), and fertility will provide the basic information required to develop selection strategies and to predict expected rates of direct and correlated responses to selection. Data on feeding behavior and temperament may be incorporated into genetic evaluations as indicator traits that show correlations with ERT or because the behavior traits may have a direct economic value. The feeding behavior of individual animals is generally consistent and repeatable and may be used to predict differences in animal performance and efficiency (Gibb et al., 1998; Oddy and Herd, 2001). There have been many reports relating animal feeding behavior to health (Sowell et al., 1998), performance, and FCR (Schwartzkopf-Genswein et al., 2003; Robinson and Oddy, 2004; Cammack et al., 2005).

The temperament of an animal may be defined as its behavioral response to handling (Burrow and Corbet, 2000). Burrow et al. (1988) developed flight speed (FS, the time to cover a fixed distance while exiting a confined area) as an objective measure of temperament. Subsequently, many studies have been conducted to obtain genetic parameter estimates for flight speed (Burrow and Corbet, 2000) and to determine its relationships with performance, FCR, carcass merit, and meat quality (Burrow and Dillon, 1997; Voisinet et al., 1997; Fox et al., 2004).

The objective of this study was to estimate the genetic variation in feeding behavior and temperament and to determine the genetic and phenotypic relationships of the measures of behavior with growth, BW, feed intake, FCR, and carcass merit of beef cattle.

	MATERIALS AND METHODS

Top Abstract INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 
Animals and Management
The animals used in the study were cared for according to the guidelines of the Canadian Council on Animal Care (CCAC, 1993).

Growth, feed intake, feeding behavior, temperament, ultrasound, and carcass merit data were collected on composite steers sired by Angus, Charolais, or University of Alberta Hybrid bulls from 2002 to 2005. The dams used were produced from crosses among 3 composite cattle lines, namely beef synthetic 1, beef synthetic 2, and dairy x beef synthetic (DBS). Briefly, beef synthetic 1 was composed of 33% Angus, 33% Charolais, and about 20% Galloway, with the remainder from other beef breeds. The beef synthetic 2 composite was made up of about 60% Hereford and 40% other beef breeds. The dairy x beef synthetic was composed of approximately 60% dairy breeds (Holstein, Brown Swiss, or Simmental) and 40% beef breeds, mainly Angus and Charolais (Goonewardene et al., 2003). The experimental dam population was produced over 30 yr of selection following all possible crosses among the different composite lines. Details of the procedures for the feedlot tests were given by Nkrumah et al. (2004, 2006). Briefly, the animals were managed and tested under feedlot conditions using the Growsafe automated feeding system (Growsafe Systems Ltd., Airdrie, Alberta, Canada; Basarab et al., 2003) at the University of Alberta’s Kinsella Research Station. The animals had BW of 353 (SD = 61) kg and were 252 (SD = 42) d of age at the beginning of testing. Two tests made up of approximately 80 animals per test were conducted each year.

Year 1 steers were fed free-choice a backgrounding diet of mainly alfalfa-brome hay with oats, supplemented with corn grain and a feedlot mineral supplement to promote growth rates of < 1.0 kg/d for approximately 30 d. This period was followed by a 30-d pretest adjustment period, in which the amount of corn in the backgrounding diet was gradually increased to introduce the steers to the test diet and the feeding system. This was done to allow them to adapt to the diet and learn to feed from the Growsafe test facility. The test diet in yr 1 was composed of 80.0% dry-rolled corn, 13.5% alfalfa hay pellet, 5% feedlot supplement (32% CP beef supplement), and 1.5% canola oil, supplying approximately 2.90 Mcal/kg of ME and 12.5% CP (as-fed basis). In yr 2 and 3, the same test procedures were used, but the test diet contained 64.5% barley grain, 20% oat grain, 9.0% alfalfa hay pellet, 5.0% beef feedlot supplement, and 1.5% canola oil, supplying 14.0% CP and 2.91 Mcal/kg of ME (as-fed basis). Corn was used in yr 1 instead of barley and oats because of a feed barley shortage that particular year.

Traits, Definitions, and Their Derivations
Procedures for obtaining the measures of feedlot performance and FCR have been described previously in (Nkrumah et al., 2006). Linear regression (SAS Institute Inc., Cary, NC, version 9.1.3) of weekly or fortnightly BW measurements against time (d) was used to derive ADG, final BW, and midtest metabolic BW (MWT, BW^0.75) for each animal. The total feed intake of each animal over a 70-d test period was used to compute the daily DMI. Feed conversion ratio was computed as the ratio of daily DMI to ADG on test, which is the reciprocal of the efficiency of gain, or G:F. The partial efficiency of growth (PEG; i.e., efficiency for ADG above maintenance) of each animal was computed as the ratio of ADG to the difference between average daily DMI and expected DMI for maintenance (Arthur et al., 2001), where DMI for maintenance was computed according to the NRC (1996).

Residual feed intake (RFI) was calculated both from phenotypic regression (RFIp; Arthur et al., 2001) and genetic regression (RFIg; Hoque et al., 2004; Crews, 2005) of ADG and MWT on DMI. The calculation of RFIp takes into account the phenotypic co(variances) between ADG and MWT, whereas the calculation of RFIg takes into account the appropriate genetic co(variances). Test group (6 levels) was included as an independent variable in the calculation of RFI. In each case, individual RFI was computed as actual DMI minus the expected DMI predicted from the appropriate phenotypic or genetic regression model. Ultrasound backfat thickness, LM area, and marbling score were predicted by linear regression against time of measurements obtained every 28 d with an Aloka 500V real-time ultrasound with a 17 cm, 3.5-MHz linear array transducer (Overseas Monitor Corporation Ltd., Richmond, British Columbia, Canada).

The feedlot behavior traits studied were daily feeding duration, daily feeding head down time, daily feeding frequency, and mean flight speed (FS; as a measure of temperament). Procedures for determining feeding behavior from the Growsafe system have previously been described (Basarab et al., 2003). Briefly, daily feeding duration was computed as the sum of the difference between feeding event end-times and start-times per day for each animal; it was equal to the total number of minutes each day spent in feeding-related activities (prehension, chewing, backing away from the bunk and chewing, socializing, scratching, or licking) at the feedbunk. Head down time refers to the sum of the number of times the electronic identification (transponder) of the animal was detected by the Growsafe system during a feeding event multiplied by the scanning time of the system, in which scanning time is system-dependent and ranges from 1.0 to 6.3 s. Daily feeding frequency in this study was defined as the number of independent feeding events for a particular animal in a day. A feeding event began when the transponder of an animal was first detected and ended when the time between the last 2 transponder readings was greater than 300 s, the transponder was detected at another bunk, or when a different transponder number was encountered. Flight speed was calculated from the time in seconds taken to traverse a fixed distance of 2.44 m after exiting a squeeze chute. Infrared sensors were used to trigger the start and stop of the timing system (Burrow et al., 1988). Flight speed data was recorded for each animal every 28 d over the course of the test period and was used to estimate the mean flight speed.

At the end of each FCR test, steers were weighed (i.e., the slaughter BW) and shipped to a commercial plant for processing. Carcass traits were evaluated according to the Canadian beef carcass grading system (Agriculture Canada, 1992). Carcass weight of each animal was determined as the combined weights of the left and right halves of the carcass. Carcass grade fat was measured at the 12th to 13th rib of each carcass. Carcass marbling score (CMAR) is a measure of carcass i.m. fat and was derived from carcass quality grade scores, such that 1 to <2 CMAR units = trace marbling (Canada A quality grade); 2 to <3 CMAR units = slight marbling (Canada AA quality grade); 3 to <4 CMAR units = small to moderate marbling (Canada AAA quality grade); and 4 CMAR units = slightly abundant or more marbling (Canada Prime). Lean meat yield is an estimate of saleable meat and was calculated according to the equation: lean meat yield, % = 63.65 + [1.05 x (muscle score)] – [0.76 x (grade fat)]. Yield grade is the proportion of lean meat and is classified as Y1 59%; Y2 = 54 to 58%; and Y3 < 54%.

Statistical Analyses
There were 464 steers with performance, FCR, feeding behavior, and ultrasound records, of which 381 and 302 had records for carcass merit and flight speed, respectively (Tables 1 and 2). The total number of steers including parents without records was 813. The steers in the study were primarily paternal half-sibs. The steers were classified into high, medium, and low RFIp groups based on ± 0.5 SD above and below the mean. This was done to determine the actual differences in behavior traits among steers grouped into different classes of RFIp.

Genetic (co)variances were obtained with the statistical software ASREML (Gilmour et al., 2000). A preliminary univariate analysis for each trait was carried out to obtain starting (co)variance parameters that were then fitted in subsequent REML bivariate analyses. Pairwise bivariate analyses were performed for each behavioral trait and the other test traits. The 2-trait individual animal model used to estimate (co)variance components included fixed effects of test group and breed, random additive genetic and residual effects, and linear covariate for age. Genetic variances and heritability estimates for any particular trait were calculated as the average value of the estimates from all pairwise bivariate analyses performed against all traits, whereas their SE were the medians of the SE estimates.

	RESULTS

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The level of variation in the various growth, feed intake, FCR, ultrasound, and carcass merit traits among the steers made it appropriate for determining their relationships with the different measures of behavior in the study (Tables 1 and 2). Daily feeding frequency (events/d) was significantly greater (P = 0.02) in Charolais (31.49 ± 0.86) compared with Angus (28.86 ± 0.55) and Hybrid (28.70 ± 0.53) steers. Daily feeding duration (min/d) and head down time (min/d), respectively, were not significantly different (P > 0.10) between Charolais (66.57 ± 1.65; 37.23 ± 1.38) and Angus (63.99 ± 2.60; 36.64 ± 2.16) or Hybrid (65.11 ± 1.40; 35.71 ± 1.10) steers. Flight speed (m/s) did not differ significantly between Charolais (2.61 ± 0.14) and Angus (2.50 ± 0.08) or Hybrid (2.45 ± 0.09) steers.

Estimates of heritability and genetic and phenotypic relationships among measures of feeding behavior and temperament are shown in Table 3. Heritability estimates for feeding duration, feeding head down time, feeding frequency, and flight speed were 0.28, 0.33, 0.38, and 0.49, respectively. Daily feeding duration was positively correlated phenotypically with head down time (P < 0.001) and feeding frequency (P < 0.05) but was unrelated phenotypically to flight speed. Head down time had a moderate positive phenotypic correlation with feeding frequency (P < 0.001) but tended to have a weak negative phenotypic correlation with flight speed (P < 0.10). Feeding frequency was phenotypically unrelated to flight speed. Daily feeding duration had a low positive genetic correlation with head down time and a moderate positive genetic correlation with flight speed, but its genetic relationship with feeding frequency was moderate and negative. Head down time had a moderate positive genetic correlation with feeding frequency and a high negative genetic correlation with flight speed. However, the genetic correlation of feeding frequency with flight speed was not different from zero. Differences among steers with high, medium, or low RFIp in feeding behavior and flight speed are shown in Table 4, whereas correlations of the different measures of feeding behavior and temperament with feed intake and different measures of efficiency are presented in Table 5. Daily feeding duration and head down time had positive phenotypic correlations with DMI, RFIp, and RFIg and a negative phenotypic correlation with PEG (P < 0.001) but were unrelated phenotypically with FCR. Indeed, steers with high RFIp consistently had greater feeding durations and head down times, respectively, compared with steers with low RFIp (P < 0.001). Feeding frequency had a low negative phenotypic correlation with DMI and FCR, but its phenotypic relationships with RFIp and RFIg were positive (P < 0.05).

The relationships of the different measures of behavior with growth, BW, and ultrasound traits are shown in Table 6. Feeding duration had a low positive phenotypic correlation with ADG, BW, ultrasound backfat, LM area, and marbling score (P < 0.01). Similarly, feeding head down time was positively phenotypically correlated with ADG and ultrasound backfat (P < 0.05) but was unrelated to BW, ultrasound LM area, or marbling score. Feeding frequency had a negative phenotypic correlation with BW and a positive correlation with ultrasound LM area (P < 0.05) but was unrelated to ADG, ultrasound backfat, or ultrasound marbling score (P > 0.10). Flight speed was phenotypically negatively related to ADG and positively related to ultrasound LM area (P < 0.01) but was unrelated to BW, ultrasound backfat, or marbling score (P > 0.10).

The relationships of the different measures of behavior with measures of carcass merit are shown in Table 7. Daily feeding duration was positively correlated phenotypically with carcass weight, grade fat, LM area, yield grade, and marbling score but was negatively correlated with lean meat yield (P < 0.01). On the other hand, feeding head down time was phenotypically unrelated to carcass traits (P > 0.10) except a tendency toward a negative correlation with carcass LM area (P < 0.10). Feeding frequency had low negative phenotypic correlations with carcass weight, grade fat, marbling score, and yield grade but positive phenotypic correlations with lean meat yield; feeding frequency was unrelated to carcass LM area. Flight speed was negatively correlated phenotypically with carcass weight, grade fat, marbling score, and yield grade but positively correlated with carcass LM area and lean yield (P < 0.05).

	DISCUSSION

Top Abstract INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 
Characterization of groups of individual animals into different feeding behavior and temperament groups would provide useful insights into sources of variation in animal performance, FCR, and carcass merit. This information is useful for developing appropriate feedbunk management practices and may be employed in selection programs to address any potentially adverse correlated responses in behavior after selection for certain ERT. In the current study, we have determined the levels of genetic and phenotypic variation in feeding behavior and determined their relationships with measures of performance, FCR, and carcass merit. The results of the current study confirm previous findings that the feeding behavior of cattle is generally consistent (Gibb et al., 1998; Oddy and Herd, 2001) and are under genetic regulation. The results of the study also indicate that there is considerable variation in behavior traits that may contribute to the observed variation in FCR of beef cattle, and there are potential correlated responses to selection to improve efficiency.

The direct heritability estimates for feeding duration and feeding frequency reported in the current study were comparable to values reported for ram lambs (h² = 0.35 – 0.36; Cammack et al., 2005). The heritability estimates obtained in the current study are somewhat lower than those reported by Robinson and Oddy (2004) for daily feeding duration (h² = 0.36) and daily feeding sessions (h² = 0.44) for tropically adapted or temperate heifers and steers. Indeed, the heritability estimates reported by Robinson and Oddy (2004) for feed intake, RFI, and FCR, respectively, were 0.27, 0.18, and 0.06 and are somewhat considerably different from many of the published estimates for these traits in the literature. The differences in findings may be related to the differences in the biological backgrounds of the animals and to the fact that the genetic parameters reported by Robinson and Oddy (2004) were obtained using the combination of data on both the tropically adapted and temperate cattle. As well, differences in the production systems used in the 2 studies may explain part of these differences.

The phenotypic correlations between feeding duration and feeding frequency reported in this study tended to be lower than those reported in ram lambs (0.25; Cammack et al., 2005). The negative genetic correlation between feeding duration and feeding frequency reported in the current study are in contrast to the strong positive relationship reported by Cammack et al. (2005) in ram lambs. These differences may be related to differences in the feeding patterns of sheep and cattle or to differences in the test facilities and housing conditions used in each study.

The flight speed values reported in the current study are consistent with values reported by Burrow and Corbet (2000) for calves born to a range of Bos taurus and Bos indicus sires as well as values reported by Curley et al. (2004) for Brahman heifers. The direct heritability estimate for flight speed reported in the current study tended to be greater than that reported (0.35) by Burrow and Corbet (2000) but was more like that reported (h² = 0.40 – 0.44) by Burrow (2001). Shrode and Hammack (1971) analyzed subjective temperament scores, using data on bulls and heifers restrained in squeeze chutes. They did not find any breed differences in temperament assessed by the scores but observed differences among Angus sire groups with a heritability of 0.40 ± 0.30 for the trait. Sato (1981) reported a heritability estimate of 0.45 for temperament in a paternal half-sib population of Japanese Black and Japanese Shorthorn cattle. Finally, Stricklin et al. (1980) studied temperament of beef cattle by assigning subjective scores to resistance to handling in a squeeze chute and estimated heritability from paternal half-sibs to be 0.48 ± 0.29 for purebred bulls and 0.44 ± 0.18 from crossbred calves.

No report was in the literature comparing a measure of temperament with feeding behavior. The results obtained in this study indicate, however, that even though feeding behavior may be phenotypically independent of temperament, the 2 classes of behavior traits may not be genetically independent. The positive genetic correlation between feeding duration and temperament may indicate a commonality in the genetics of the 2 traits, whereas there may be an inverse relationship between the genetic factors that affect temperament and those directly related to feed consumption. This is not only evident from the negative genetic correlation between flight speed and head down time but also from the phenotypic and genetic correlations between flight speed and DMI. The phenotypic relationship of feeding duration with feed intake in this study was similar to that found by Schwartzkopf-Genswein et al. (2002) and Robinson and Oddy (2004), who observed a moderate positive relationship (r = 0.30) between feed intake and feeding duration. The results suggest that the longer animals spend at the bunk, the more feed they consumed.

Basarab et al. (2002) looked at the relationship between feed intake and feeding behavior traits in feedlot cattle. Their results indicated that mean phenotypic correlations were 0.69, 0.59, and 0.31 for the relationship between daily feed intake and daily feeding duration, head down time, and frequency, respectively. The corresponding estimates between DMI and feeding duration and head down time were positive but lower in the current study, whereas the correlation of DMI with feeding frequency in the current study was negative. Cammack et al. (2005) reported lower genetic and phenotypic correlations between feed intake and feeding duration. Robinson and Oddy (2004) observed a weak positive phenotypic correlation (r = 0.18) but no genetic correlation between feed intake and daily feeding duration. Generally, the relationships between the measures of feeding behavior with RFI and PEG were greater than those with FCR and DMI. Schwartzkopf-Genswein et al. (2002) observed a negative relationship between feeding duration and FCR (r = –0.17). In the current study, animals with low phenotypic RFI had 24 and 14% lower feeding duration, 29 and 18% lower head down time, as well as 14 and 10% lower feeding frequency compared with animals with high or medium phenotypic RFI, respectively. Very similar relationships were observed between genetic RFI and the feeding behavior traits.

The relationships of RFI with feeding duration and feeding frequency were also observed by Basarab et al. (2003), though in the study by these authors, the differences observed between different RFI classes and both feeding behavior traits were not significant. Cammack et al. (2005) reported positive genetic and phenotypic correlations between RFI and feeding duration and feeding frequency, though their correlation coefficients were lower than observed in this study. Robinson and Oddy (2004) reported weak positive phenotypic correlations between RFIp and daily feeding duration and feeding sessions and moderate positive genetic correlations of daily feeding duration and feeding sessions with RFIp. In the same study, as in the current study, phenotypic correlations of feeding behavior traits with FCR were not different from zero, but the corresponding genetic correlations were high. Linear regression analysis indicated that only about 55% of the daily feeding duration may actually be related to feed consumption (feeding head down time), whereas the remainder may be spent in other feeding-related activities at the feedbunk.

The relationships of feeding duration with ADG and final BW observed in the current study are consistent with the findings of Schwartzkopf-Genswein et al. (2002), who reported a weak but significant positive phenotypic correlation between ADG and feeding duration (r = 0.14). In the same study, Schwartzkopf-Genswein et al. (2002) reported that low-gaining Holstein steers had greater feeding durations, though not significantly so; the same authors reported that the opposite relationship was observed in Charolais steers. In addition, Robinson and Oddy (2004) reported a weak positive but significant phenotypic correlation between feeding duration and ADG, though the corresponding genetic correlation was not different from zero. The current study did not find any phenotypic correlation between ADG and feeding frequency, and the genetic correlation between the 2 traits was negative. This is in contrast to the findings of Schwartzkopf-Genswein et al. (2003) in cattle and that of Cammack et al. (2005), who reported positive correlations between ADG and feeding frequency. Similarly, Robinson and Oddy (2004) reported weak but significant positive phenotypic correlation but no genetic correlation between ADG and daily feeding sessions.

The relationship of flight speed with DMI and ADG in the current study is consistent with the findings of Fox et al. (2004), who observed negative phenotypic correlations between flight speed and DMI (r = –0.34, –0.17) and ADG (r = –0.25, –0.25) for Bonsmara bulls and Santa Gertrudis steers, respectively. In addition, Burrow and Dillon (1997) reported that animals with slow flight speeds gained BW more rapidly and had heavier slaughter weights than animals with fast flight speeds in B. indicus crossbred cattle. Also, Voisinet et al. (1997) observed that cattle that became agitated during handling had 14% lower BW gains compared with calmer animals. On the contrary, Burrow (2001) did not detect any phenotypic or genetic relationships between flight speed and birth weight, weaning weight, yearling BW, final BW, or ADG in a tropically adapted composite breed of cattle grazed at pasture in the tropics.

The lack of phenotypic correlations of flight speed with FCR and RFI was consistent with the findings of Fox et al. (2004), who did not observe any correlations between flight speed and net FCR. However, the current study detected moderate to strong favorable genetic correlations between RFI and PEG with flight speed but an unfavorable relationship with FCR, indicating that there may be a need to include temperament in any genetic selection programs involving FCR. The biological reasons underlying the difference between the genetic relationship of FS with RFI and PEG compared with the relationship with FCR are currently unknown. The current study confirmed the fact that RFI and PEG were phenotypically and genetically independent of maintenance (Arthur et al., 2001). It is possible that the adjustment of RFI and PEG for growth and maintenance indirectly eliminates the negative effects of animals with poor temperament on intake and efficiency. This point may be reiterated by the relationship of FS with growth and carcass weight observed in the study.

The phenotypic correlations of measures of feeding behavior with ultrasound and carcass traits were mostly low but generally different from zero. The corresponding genetic correlations were greater than the phenotypic correlations. There are very few reports in the literature relating measures of feeding behavior with ultrasound and carcass traits. Robinson and Oddy (2004) observed that the phenotypic correlations of feeding behavior traits with ultrasound i.m. fat, rump fat, rib fat, and LM area were not different from zero. The same authors showed that daily feeding duration had a low negative genetic correlation with ultrasound i.m. fat and a moderate positive genetic correlation with LM area. Voisinet et al. (1997) showed that cattle that became agitated during handling had 10% lower carcass weights compared with calmer animals. In addition, Burrow and Dillon (1997) reported that B. indicus crossbred cattle with slow flight speeds had heavier carcass weights than animals with fast flight speeds. The relationships of the behavior traits with the carcass traits generally reflected the relationships among growth rate, feed intake, and body composition. Animals that spent more time eating in a day generally had fatter carcasses, whereas those that spent less time eating had leaner carcasses but lower ADG. The relationships of marbling with feeding behavior may be due to the correlated indirect relationship with body fatness in general.

The degree of genetic variability observed in the study as well as the relationships among the feeding behavior traits and with other traits point to the fact that variation in frequency of feeding and feeding duration or nonfeeding periods occur under the modulation of an underlying genetically controlled continuous variable. The observed relationships of the feeding behavior traits with feed intake and efficiency suggest that this underlying quantitative trait may be associated with biologically relevant signals that control hunger and satiety in the short-term. It may be that short-term feeding behavior (related to event feeding duration) combine with cues that originate from the overall energy balance status of the animal (body composition) to define when the next feeding event occurs and how long the animal actually spends eating. These dynamic processes may, however, be modulated by factors such as bunk space per animal, BW, age, and size as well as temperament of pen mates, which are important in deciding the degree of competition and dominance in a social setting. At present, the eventual effect of behavior on carcass merit and meat quality is poorly characterized. The results of this study, however, point generally to the fact that differences in behavior may affect overall energy metabolism and therefore product quality. Most of the physiological or metabolic pathways leading to these variations and relationships are, however, very poorly defined, and further research efforts are required to establish them. There is a need to define these relationships more clearly to determine what factors are relevant in the definition of beef breeding objectives to ensure overall production system efficiency and acceptable product quality.

In conclusion, there is considerable genetic and phenotypic variation in beef cattle in measures of feeding behavior and temperament, which are also related to measures of performance, FCR, and carcass merit. The genetic and phenotypic relationships of these traits need to be fully characterized and given serious considerations in any program to select animals for improved FCR. Feeding behavior and temperament may need to be included in the definition of breeding goals.

	Footnotes

 
¹ This work is part of the Bovine Genome Project supported through grants BBRC 2002C030R, AARI 2002L030R, AAC-99AB343, and CABIDF 2000AB364 awarded to Stephen. S. Moore through the Canada-Alberta Beef Industry Development Fund, Beef Cattle Research Council, Alberta Beef Producers, and Alberta Cattle Commission.

² Corresponding author: stephen.moore{at}ualberta.ca

Received for publication September 26, 2006. Accepted for publication June 15, 2007.

	LITERATURE CITED

Top Abstract INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION LITERATURE CITED

 


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