Feeding Behavior Traits Research Articles

Efficacy of statistical process control procedures to monitor deviations in physical behavior for preclinical detection of bovine respiratory disease in feedlot cattle

Opportunities exist to improve the efficacy of antimicrobial treatment and animal welfare standards through use of remote sensor technologies for early detection of bovine respiratory disease (BRD). A post-hoc analysis using statistical process control (SPC) procedures was performed on continuously-recorded physical activity data collected from BRD-diagnosed and healthy calves from Pillen et al. (2016). We hypothesized that SPC models that monitor physical activity traits (step count, motion index, standing time, lying bouts) would yield higher diagnostic accuracies compared to methods based on visual observation of clinical signs of illness for detecting the onset of BRD. Crossbred steers and bulls (n = 266; initial BW = 180 kg) at high risk for BRD were fitted with leg-attached accelerometers (IceQube, IceRobotics, Ltd.) upon arrival at a commercial feedlot and evaluated for 56 d Overall, calves experienced 48% morbidity, with the average day of first treatment occurring 16 d post-feedlot arrival. Shewhart charts were used to evaluate daily changes in each trait as univariate models and combined traits in principal component analysis (PCA)–constructed multivariate models, relative to the day of BRD diagnosis. Diagnostic test sensitivity and specificity were calculated for each model and compared. The univariate models had relatively low sensitivities (< 40%), with specificities ranging from 23 to 81%, and chart signaling occurred up to 2 d prior to visual diagnosis of BRD. The univariate model for step count had the highest accuracy (52.3%), while lying time had the lowest accuracy (32%). The multivariate models that included all 4 physical activity traits or only lying bout behavior had moderate sensitivities (44 to 57%), but low specificities (< 37%), and chart signaling occurred 2 d prior to visual diagnosis. The relatively low diagnostic test accuracies of the SPC models reported in this study may have been due to substantial within-animal daily variation in the physical activity traits and(or) the limited time for adequate model training prior to the onset of BRD cases. Future research should investigate SPC analysis of multifactorial algorithms using physical activity and feeding behavior traits to improve the accuracy of preclinical detection of BRD.

Impact of 100% organic diets on pig performance, carcass composition and carcass nutrient deposition efficiency

The ultimate objective of organic pig production is to use ingredients of 100% organic origin in the animals’ diets. However, this approach is challenging, especially when needing to ensure adequate quantities of essential amino acids (EAAs) and protein in grower-finisher diets. The current standard is 95% organic feed ingredients, but this percentage can be increased by reducing the EAA supply or by accepting an unbalanced EAA profile. A further incentive also exists to include forages in organic diets as a way to raise dietary crude fibre content. The current study therefore investigates three organic diets (T95: 5% of non-organic origin; T100: 0% of non-organic origin and T100-CF: T100 plus an increased crude fibre level), which were offered ad libitum to 48 pigs (16 per diet) weighing 22 to 110 kg. Comparison of the three diets revealed that increasing the crude fibre content (T100-CF) reduced growth, increased total feed intake and impaired feed and protein deposition efficiency, but the unbalanced EAA profile (T100) had no effect on growth traits and protein deposition efficiency. The T100 and T100-CF pigs differed from the T95 pigs in terms of feeding behaviour traits, as they displayed more frequent but shorter feeder visits, shorter between-meal intervals and smaller meals. Increasing the fibre content with press cake ingredients raised the degree of unsaturation of the backfat and might cause problems in meat processing. In conclusion, the results revealed that pigs could cope with a mild EAA imbalance.

Estimation of social genetic effects on feeding behaviour and production traits in pigs

Pigs are housed in groups during the test period. Social effects between pen mates may affect average daily gain (ADG), backfat thickness (BF), feed conversion rate (FCR), and the feeding behaviour traits of pigs sharing the same pen. The aim of our study was to estimate the genetic parameters of feeding behaviour and production traits with statistical models that include social genetic effects (SGEs). The data contained 3075 Finnish Yorkshire, 3351 Finnish Landrace, and 968 F1-crossbred pigs. Feeding behaviour traits were measured as the number of visits per day (NVD), time spent in feeding per day (TPD), daily feed intake (DFI), time spent in feeding per visit (TPV), feed intake per visit (FPV), and feed intake rate (FR). The test period was divided into five periods of 20 days. The number of pigs per pen varied from 8 to 12. Two model approaches were tested, i.e. a fixed group size model and a variable group size model. For the fixed group size model, eight random pigs per pen were included in the analysis, while all pigs in a pen were included for the variable group size model. The linear mixed-effects model included sex, breed, and herd*year*season as fixed effects and group (batch*pen), litter, the animal itself (direct genetic effect (DGE)), and pen mates (SGEs) as random effects. For feeding behaviour traits, estimates of the total heritable variation (T2± SE) and classical heritability (h2± SE, values given in brackets) from the variable group size model (e.g. period 1) were 0.34 ± 0.13 (0.30 ± 0.04) for NVD, 0.41 ± 0.10 (0.37 ± 0.04) for TPD, 0.40 ± 0.15 (0.14 ± 0.03) for DFI, 0.53 ± 0.15 (0.28 ± 0.04) for TPV, 0.66 ± 0.17 (0.28 ± 0.04) for FPV, and 0.29 ± 0.13 (0.22 ± 0.03) for FR. The effect of social interaction was minimal for ADG (T2 = 0.29 ± 0.11 and h2 = 0.29 ± 0.04), BF (T2 = 0.48 ± 0.12 and h2 = 0.38 ± 0.07), and FCR (T2 = 0.37 ± 0.12 and h2 = 0.29 ± 0.04) using the variable group size model. In conclusion, the results indicate that social interactions have a considerable indirect genetic effect on the feeding behaviour and FCR of pigs but not on ADG and BF.

Feed intake and feeding behavior traits for gestating sows recorded using electronic sow feeders.

Electronic sow feeding (ESF) systems are used to control feed delivery to individual sows that are group-housed. Feeding levels for gestating sows are typically restricted to prevent excessive body weight gain. Any alteration of intake from the allocated feeding curve or unusual feeding behavior could indicate potential health issues. The objective of this study was to use data recorded by ESF to establish and characterize novel feed intake and feeding behavior traits and to estimate their heritabilities. Raw data were available from two farms with in-house manufactured (Farm A) or commercial (Farm B) ESF. The traits derived included feed intake, time spent eating, and rate of feed consumption, averaged across or within specific time periods of gestation. Additional phenotypes included average daily number of feeding events (AFE), along with the cumulative numbers of days where sows spent longer than 30 min in the ESF (ABOVE30), missed their daily intake (MISSF), or consumed below 1 kg of feed (BELOW1). The appetite of sows was represented by averages of score (APPETITE), a binary value for allocation eaten or not (DA_bin), or the standard deviation of the difference between feed intake and allocation (SDA-I). Gilts took longer to eat than sows (15.5 ± 0.13 vs. 14.1 ± 0.11 min/d) despite a lower feed allocation (2.13 ± 0.00 vs. 2.36 ± 0.01 kg/d). The lowest heritability estimates (below 0.10) occurred for feed intake traits, due to the restriction in feed allocation, although heritabilities were slightly higher for Farm B, with restriction in the eating time. The low heritability for AFE (0.05 ± 0.02) may have reflected the lack of recording of nonfeeding visits, but repeatability was moderate (0.26 ± 0.03, Farm A). Time-related traits were moderately to highly heritable and repeatable, demonstrating genetic variation between individuals in their feeding behaviors. Heritabilities for BELOW1 (Farm A: 0.16 ± 0.04 and Farm B: 0.15 ± 0.09) and SDA-I (Farm A: 0.17 ± 0.04 and Farm B: 0.10 ± 0.08) were similar across farms. In contrast, MISSF was moderately heritable in Farm A (0.19 ± 0.04) but lowly heritable in Farm B (0.05 ± 0.07). Heritabilities for DA_bin were dissimilar between farms (Farm A: 0.02 ± 0.02 and Farm B: 0.23 ± 0.10) despite similar incidence. Individual phenotypes constructed from ESF data could be useful for genetic evaluation purposes, but equivalent capabilities to generate phenotypes were not available for both ESF systems.

FEEDING BEHAVIOR AS THE NEW BREEDING TRAITS IN PIGS

Pig breeding for improvements of growth and carcass traits, reproductive qualities as the main breeding criteria has been implemented in breeding practice for a long time. However, the used productivity traits do not involve a number of important economic indicators, in particular feed efficiency and behavioral characteristics of animals. The selection response for such traits is expected to give an additional increase in the accuracy of the breeding value of young animals when used at large nucleus farms. Undoubtedly, the transition to mass testing of animals at automatic feeding stations is currently the most accurate method for evaluating feed conversion rate and related traits of feeding behavior. This work aimed to study the genetic features of feeding behavior and growth traits of Duroc boars in relation to the residual feed intake (RFI) for use in the breeding process. The studies were carried out at Nucleus Farm TopGene for a population of 800 animals. Individual records for feed intake were collected using automatic feeding stations. Additionally, parameters of feeding behavior, average daily gain (ADG), and feed conversion rate (FCR) were recorded. To eliminate the influence of growing factors on the studied traits, a regression analysis was performed to correct feed conversion rate, as well as the calculation of genetic and paratypical variances. The RFI values were obtained based on the difference between the actual and predicted average daily feed intake, considering the average metabolic weight, and the body weight gain of animals according to the multiple linear regression equation. The average values and heritability of the main breeding traits were: feed conversion rate 2.20 kg/kg (h2 = 0.214, for the adjusted value), average daily feed intake 2.51 kg (h2 = 0.221), number of visits per day 7.9 units (h2 = 0.494), feed intake per visit 0.37 kg (h2 = 0.284), time spent in feeding per visit 11.3 min (h2 = 0.168), feeding rate 35.4 g/min (h2 = 0.269). For RFI, the ratio of genetic variation was h2 = 0.215. According to the ratio of RFI and ADG, the groups of Duroc boars were selected for desirable negative or low RFI values of -254.9 and -276.2 g vs. +266.8 and +353.9 g for positive RFI. Individuals that showed high gains (1057 g per day) with reduced feed intake (2.34 kg/day) can serve as the basis for developing a specialized line of pigs (group I) capable of efficient using feed energy for body growth. Boars with positive RFI values significantly differed for FCRcorr (-0.15 and 0.24 kg/kg), back fat (-1.90 and -2.49 mm), muscle eye area (+4.57 and +6.10 cm2);for feeding behavior, the differences were -2.8 and -8.0 minutes for time spent in feeding per day, +1.7 and +2.0 visits per day, and -2.7 and -4.2 minutes for time spent in feeding per visit. That is, the more frequent visits to feeding stations at less time spent in feeding per visit, the more efficient the use of feed. The estimation of breeding value showed the similar RFI pattern for the desired group of animals. The higher estimates for feed intake compensated the existing differences between the phenotype and genotype for the number of visits per day and feeding rate due to the identified genetic correlations with RFI, rg = 0.702 and rg = 0.033, respectively. Thus, the feeding behavior traits of pigs along with the residual feed intake (RFI) are genetically determined and can be used to improve pig populations for economically important and productive characteristics.

ПОКАЗАТЕЛИ КОРМОВОГО ПОВЕДЕНИЯ КАК НОВЫЕ СЕЛЕКЦИОННЫЕ ПРИЗНАКИ В РАЗВЕДЕНИИ СВИНЕЙ

Pig breeding for improvements of growth and carcass traits, reproductive qualities as the main breeding criteria has been implemented in breeding practice for a long time. However, the used productivity traits do not involve a number of important economic indicators, in particular feed efficiency and behavioral characteristics of animals. The selection response for such traits is expected to give an additional increase in the accuracy of the breeding value of young animals when used at large nucleus farms. Undoubtedly, the transition to mass testing of animals at automatic feeding stations is currently the most accurate method for evaluating feed conversion rate and related traits of feeding behavior. This work aimed to study the genetic features of feeding behavior and growth traits of Duroc boars in relation to the residual feed intake (RFI) for use in the breeding process. The studies were carried out at Nucleus Farm TopGene for a population of 800 animals. Individual records for feed intake were collected using automatic feeding stations. Additionally, parameters of feeding behavior, average daily gain (ADG), and feed conversion rate (FCR) were recorded. To eliminate the influence of growing factors on the studied traits, a regression analysis was performed to correct feed conversion rate, as well as the calculation of genetic and paratypical variances. The RFI values were obtained based on the difference between the actual and predicted average daily feed intake, considering the average metabolic weight, and the body weight gain of animals according to the multiple linear regression equation. The average values and heritability of the main breeding traits were: feed conversion rate 2.20 kg/kg (h2 = 0.214, for the adjusted value), average daily feed intake 2.51 kg (h2 = 0.221), number of visits per day 7.9 units (h2 = 0.494), feed intake per visit 0.37 kg (h2 = 0.284), time spent in feeding per visit 11.3 min (h2 = 0.168), feeding rate 35.4 g/min (h2 = 0.269). For RFI, the ratio of genetic variation was h2 = 0.215. According to the ratio of RFI and ADG, the groups of Duroc boars were selected for desirable negative or low RFI values of -254.9 and -276.2 g vs. +266.8 and +353.9 g for positive RFI. Individuals that showed high gains (1057 g per day) with reduced feed intake (2.34 kg/day) can serve as the basis for developing a specialized line of pigs (group I) capable of efficient using feed energy for body growth. Boars with positive RFI values significantly differed for FCRcorr (-0.15 and 0.24 kg/kg), back fat (-1.90 and -2.49 mm), muscle eye area (+4.57 and +6.10 cm2);for feeding behavior, the differences were -2.8 and -8.0 minutes for time spent in feeding per day, +1.7 and +2.0 visits per day, and -2.7 and -4.2 minutes for time spent in feeding per visit. That is, the more frequent visits to feeding stations at less time spent in feeding per visit, the more efficient the use of feed. The estimation of breeding value showed the similar RFI pattern for the desired group of animals. The higher estimates for feed intake compensated the existing differences between the phenotype and genotype for the number of visits per day and feeding rate due to the identified genetic correlations with RFI, rg = 0.702 and rg = 0.033, respectively. Thus, the feeding behavior traits of pigs along with the residual feed intake (RFI) are genetically determined and can be used to improve pig populations for economically important and productive characteristics.

Social Network Analysis of Agonistic Behaviour and Its Association with Economically Important Traits in Pigs.

Simple SummaryAggression behaviour has several negative consequences on the performance and welfare of pigs. Here, a Social Network Analysis (SNA) approach was employed to (1) identify individual traits that describe the role of each animal in the aggression; (2) investigate the association of these traits with performance and feeding behaviour traits. The study was conducted on 326 Duroc pigs reared in 29 pens. Several individual centrality traits were identified and used to calculate the Social Rank Index. The Dominant, Subordinate, and Isolated animals represented 21.1%, 57.5% and 21.4%, respectively. No significant correlations were observed between out-degree (number of initiated agonistic behaviours) and growth traits, indicating the similarity of growth patterns for dominant and non-dominant animals. Furthermore, out-degree was correlated positively with average daily occupation time (time at the feeder/day) and average daily feeding frequency (number of visits to the feeder/day), but negatively with average daily feeding rate (gr/min). This may indicate the ability of non-dominant pigs to modify their behaviour to obtain their requirements. The Hamming distances between networks showed that there is no common behaviour pattern between pens. In conclusion, SNA showed potential for extracting behaviour traits that could be used to improve pig performance and welfare.Aggression behaviour has several negative consequences on the performance and welfare of pigs. Here, the Social Network Analysis (SNA) approach was employed to (1) identify individual traits that describe the role of each animal in the aggression; (2) investigate the association of these traits with performance and feeding behaviour traits. The study was conducted on 326 Duroc pigs reared in 29 pens. Several individual centrality traits were identified and used to calculate the Social Rank Index. The Dominant, Subordinate, and Isolated animals represented 21.1%, 57.5% and 21.4%, respectively. No significant correlations were observed between out-degree (number of initiated agonistic behaviours) and growth traits, indicating the similarity of growth patterns for dominant and non-dominant animals. Furthermore, out-degree was correlated positively with average daily occupation time (time at the feeder/day) and average daily feeding frequency (number of visits to the feeder/day) but negatively with average daily feeding rate (gr/min). This may indicate the ability of non-dominant pigs to modify their behaviour to obtain their requirements. The Hamming distances between networks showed that there is no common behaviour pattern between pens. In conclusion, SNA showed the potential for extracting behaviour traits that could be used to improve pig performance and welfare.

Genetic association among feeding behavior, feed efficiency, and growth traits in growing indicine cattle.

This study aimed to estimate genetic parameters, including genomic data, for feeding behavior, feed efficiency, and growth traits in Nellore cattle. The following feeding behavior traits were studied (861 animals with records): time spent at the feed bunk (TF), duration of one feeding event (FD), frequency of visits to the bunk (FF), feeding rate (FR), and dry matter intake (DMI) per visit (DMIv). The feed efficiency traits (1,543 animals with records) included residual feed intake (RFI), residual weight gain (RWG), and feed conversion (FC). The growth traits studied were average daily gain (ADG, n = 1,543 animals) and selection (postweaning) weight (WSel, n = 9,549 animals). The (co)variance components were estimated by the maximum restricted likelihood method, fitting animal models that did (single-step genomic best linear unbiased prediction) or did not include (best linear unbiased prediction) genomic information in two-trait analyses. The direct responses to selection were calculated for the feed efficiency traits, ADG, and WSel, as well as the correlated responses in feed efficiency and growth by direct selection for shorter TF. The estimated heritabilities were 0.51 ± 0.06, 0.35 ± 0.06, 0.27 ± 0.07, 0.34 ± 0.06, and 0.33 ± 0.06 for TF, FD, FF, FR, and DMIv, respectively. In general, TF and FD showed positive genetic correlations with all feed efficiency traits (RFI, RWG, and FC), ADG, DMI, and WSel. Additionally, TF showed high and positive genetic and phenotypic correlations with RFI (0.71 ± 0.10 and 0.46 ± 0.02, respectively) and DMI (0.56 ± 0.09 and 0.48 ± 0.03), and medium to weak genetic correlations with growth (0.32 ± 0.11 with ADG and 0.14 ± 0.09 with WSel). The results suggest that TF is a strong indicator trait of feed efficiency, which exhibits high heritability and a weak positive genetic correlation with growth. In a context of a selection index, the inclusion of TF to select animals for shorter TF may accelerate the genetic gain in feed efficiency by reducing RFI but with zero or slightly negative genetic gain in growth traits.

Optimum roughage proportion in barley-based feedlot cattle diets: growth performance, feeding behavior, and carcass traits.

High grain diets are fed to finishing beef cattle to maximize animal performance in a cost-effective manner. However, a small amount of roughage is incorporated in finishing diets to help prevent ruminal acidosis, although few studies have examined optimum roughage inclusion level in barley-based diets. The objective of the study was to evaluate the effects of roughage proportion in barley-based finishing diets on growth performance, feeding behavior, and carcass traits of feedlot cattle. Crossbred beef steers (n = 160; mean body weight ± SD, 349.7 ± 21.4 kg) were allocated to 20 pens that were assigned randomly to four dietary treatments (five pens of eight steers per treatment). The treatment diets contained barley silage at 0%, 4%, 8%, and 12% of dietary dry matter (DM). The remainder of the diets (DM basis) consisted of 80%, 76%, 72%, and 68% barley grain, respectively, 15% corn dried distiller's grains, 5% mineral and vitamin supplement, and 32 mg monensin/kg diet DM. The diets were fed as total mixed rations for ad libitum intake (minimum of 5% refusal) once per day. Cattle were weighed on 2 consecutive days at the start and end of the experiment and on 1 d every 3 wk throughout the experiment (124 d). Two pens for each treatment group were equipped with an electronic feeding system (GrowSafe Systems Ltd., Calgary, Alberta) to monitor feed intake and feeding behavior of individual cattle. The data for dry matter intake (DMI), average daily gain (ADG), gain:feed (G:F) ratio, and carcass traits were analyzed as a completely randomized design with fixed effect of barley silage proportion and pen replicate as experimental unit. Feeding behavior data were analyzed similarly, but with animal as experimental unit. Averaged over the study, DMI increased linearly (11.1, 11.3, 11.7, 11.8 kg/d; P = 0.001) as barley silage proportion increased from 0%, 4%, 8%, and 12% of DM, but ADG was not affected (carcass-adjusted,1.90, 1.85, 1.87, 1.89 kg/d; P ≥ 0.30). Consequently, G:F ratio decreased linearly (carcass-adjusted, 168.9, 163.8, 158.5, 160.6 g/kg DMI; P = 0.023). When averaged over the study, proportion of barley silage in the diet had no linear or quadratic effects (P > 0.10) on meal frequency, duration of meals, intermeal duration, or meal size, but eating rate decreased linearly with increasing silage proportion (P = 0.008). There was no diet effect on liver abscesses (P ≥ 0.92), and effects on carcass characteristics were minor or nonexistent. We conclude that increasing the proportion of barley silage in a feedlot finishing diet at the expense of barley grain to minimize the incidence of ruminal acidosis may decrease feed conversion efficiency.

Large variability in feeding behavior among crossbred growing cattle.

The purpose of this study was to define an extensive suite of feeding behavior traits in growing crossbred cattle and to investigate their phenotypic inter-relationships as well as relationships with other performance and efficiency traits. Time-series feeding behavior data, as well as feed intake and liveweight records, were available for 624 growing crossbred cattle, of which 445 were steers and 179 were heifers. Feeding behavior repeatability estimates were calculated using linear mixed models. Additionally, partial Spearman correlations were estimated among 14 feeding behavior traits, as well as between feeding behavior with both performance and feed efficiency traits, using residuals retained from linear mixed models. The marginal contribution of several feeding behavior traits to the variability in metabolizable energy intake (MEI) was also determined. Repeatability estimates of 0.57, 0.36, and 0.48 were calculated for the number of feed events per day, the total time spent feeding per day, and the feeding rate, respectively. Cattle that ate more frequently each day, ate at a faster rate and consumed less energy in each visit to the feed bunk. More efficient cattle fed less often per day and fed for a shorter duration per day; they also had a slower feeding rate and fed for longer in each visit to the feed bunk. Moreover, heavier cattle fed for a longer duration per day had a faster feeding rate, but fed less often per day; heavier animals also fed first in the pen after the fresh feed was offered. The number of feed events per day and feeding time per day together explained an additional 13.4 percentage points of the variability in MEI above that already explained by all of growth rate, liveweight, and backfat depth. The results from the present study suggest that several repeatable time-series-related feeding behavior traits, that are less resource intensive to measure, may have a role as useful predictor traits of important but relatively difficult to record traits, such as feed intake and efficiency.

Characterization of feeding behavior traits in steers with divergent residual feed intake consuming a high-concentrate diet.

The objective of this study was to examine the differences in feeding behavior patterns of steers with divergent phenotypes for residual feed intake (RFI). Three trials were conducted with 508 Angus-based composite crossbred steers (body weight [BW] = 309 ± 57 kg) fed a high-concentrate diet in pens equipped with electronic feed bunks (GrowSafe System). Initial and final carcass ultrasound measurements (intra-muscular fat, backfat depth, and rib-eye area) were collected on days 0 and 70, and BW measured at 14-d intervals. Individual dry matter intake (DMI) and feeding behavior traits were collected for 70 d, and RFI calculated as the residual from the regression of DMI on average daily gain (ADG) and mid-test BW0.75. Steers were ranked by RFI and assigned to low-, medium-, and high-RFI classes based on ± 0.5 SD from the mean RFI within the trial. The feeding behavior traits evaluated in this study included frequency and duration of bunk visit (BV) and meal events, head-down (HD) duration, mean meal length, time-to-bunk interval, the maximum nonfeeding interval, and the day-to-day variation of these traits, defined as the root mean squared error (RMSE) from linear regression of each trait on the day of trial. Additionally, three ratio traits were evaluated: BV events per meal, HD duration per BV event, and HD duration per meal event. Low-RFI (feed-efficient) steers consumed 16% less (P < 0.01) DMI, while BW and ADG were not different compared with high-RFI steers. Low-RFI steers had 18% fewer and 21% shorter (P < 0.01) BV events, and 11% fewer and 13% shorter (P < 0.01) meal events per day compared with high-RFI steers. Furthermore, low-RFI steers exhibited less (P < 0.05) day-to-day variance in DMI, as well as in frequency and duration of BV and meal events and HD duration compared with high-RFI steers. Differences in feeding behavior traits due to RFI were minimally affected by covariate adjustment for DMI, indicating that steers with divergent RFI have distinct feeding behavior patterns that are largely independent of differences in DMI. These results suggest that feeding behavior traits may be useful biomarkers for the prediction of feed efficiency in beef cattle.

Selection response and genetic parameter estimation of feeding behavior traits in Pekin ducks

Body weight–related traits and feeding behavior traits are important in poultry breeding and production. To investigate the heritability of feeding behavior and their genetic correlation with body weight–related traits in Pekin ducks, 5,594 Pekin ducks were selected. The information about body weight–related traits and feeding behavior from 3 to 6 wk of age were recorded by automatic electronic feeders. The heritability estimates for body weight, residual feed intake, and feeding behavior traits are relatively high (ranging from 0.29 to 0.65). We observed that total feed intake, meal feed intake, body weight at the age of 3 wk, and daily body weight gain had strong positive genetic correlations with body weight at the age of 6 wk. Moreover, body weight at the age of 3 wk also showed a positive genetic correlation with the feed conversion ratio (0.33). Total feeding time, daily feed intake, and feeding rate had significant positive phenotypic correlations with feed efficiency. However, the average interval between meals, the number of daily visits, and the number of meals all had a low genetic or phenotypic relationship with body weight and feed efficiency. In conclusion, our study revealed that body weight, residual feed intake, and feeding behavior traits were all highly heritable traits, and the selection for certain feeding behaviors could improve feed efficiency in Pekin ducks. This study is the first report about genetic parameter estimates about feeding behaviors in ducks based on large datasets and provides solid data for genetic study in ducks.

Efficacy of statistical process control procedures to identify deviations in continuously measured physiologic and behavioral variables in beef steers experimentally challenged with Mannheimia haemolytica.

The objective of this experiment was to determine if statistical process control (SPC) procedures coupled with the remote continuous collection of feeding behavior patterns, accelerometer-based behaviors, and rumen temperature can accurately differentiate between animals experimentally inoculated with Mannheimia haemolytica (MH) or PBS. Thirty-six crossbred steers (BW = 352 ± 23 kg) seronegative for MH were randomly assigned to bronchoselective endoscopic inoculation with MH (n = 18) or PBS (n = 18). Electronic feed bunks were used to measure DMI and feeding behavior traits, accelerometer-based neck collars measured feeding- and activity-behavior traits, and ruminal thermo-boluses measured rumen temperature. Data were collected for 28 d prior to and following inoculation. Steers inoculated with MH exhibited elevated (P < 0.02) levels of neutrophils and rumen temperature indicating that MH challenge effectively stimulated immunologic responses. However, only nine of the MH steers exhibited increased serum haptoglobin concentrations indicative of an acute-phase protein response and one displayed clinical signs of disease. Shewhart charts (SPC procedure) were used for two analyses, and sensitivity was computed using all MH-challenged steers (n = 18), and a subset that included only MH-challenged haptoglobin-responsive steers (n = 9). Specificity was calculated using all PBS steers in both analyses. In the haptoglobin-responsive only analysis, DMI and bunk visit (BV) duration had the greatest accuracy (89%), with accuracies for head-down (HD) duration, BV frequency, time to bunk, and eating rate being less (83%, 69%, 53%, and 61%, respectively). To address the diurnal nature of rumen temperature, data were averaged over 6-h intervals, and quarterly temperature models were evaluated separately. Accuracy for the fourth quarter rumen temperature was higher (78%) than the other quarterly temperature periods (first = 56%, second = 50%, and third = 67%). In general, the accelerometer-based behavior traits were highly specific ranging from 82% for ingestion to 100% for rest, rumination, and standing. However, the sensitivity of these traits was low (0% to 50%), such that the accuracies were moderate compared with feeding behavior and rumen temperature response variables. These results indicate that Shewhart procedures can effectively identify deviations in feeding behavior and rumen temperature patterns to enable subclinical detection of BRD in beef cattle.

Indirect genetic effects on the relationships between production and feeding behaviour traits in growing Duroc pigs

Performance and feeding behaviour traits in growing pigs could be affected by social interaction effects when animals are raised in group. So, properly knowing the genetic correlations between direct and social interaction effects among performance and feeding behaviour traits could improve the accuracy of the genetic evaluations. Our aim was to explore the role of feeding behaviour traits (FBT) and indirect genetic effects (IGEs) in the genetic evaluations of growing pigs. Thus, genetic parameters were estimated for production traits (PT): average daily gain, average daily feed consumption, feed conversion ratio and backfat thickness; as well as for FBT: average daily feeding rate, average daily feeding frequency, average daily occupation time and average daily time between consecutive visits. Traits were recorded in 1144 Duroc pigs during the fattening period. Two bivariate models were fitted: classic animal model and an animal model fitting IGE. Estimations were done following Bayesian procedures. Heritability estimates obtained with classic animal model for all studied traits were medium-high. The additional heritable variation captured by IGE supposed that the ratios of total genetic variance to phenotypic variance (T2) were higher than the heritability estimates obtained with the classic model, except for occupation time trait, when a lower value (0.20 ± 0.19) was estimated. This is due to a high and negative correlation between IGE and direct genetic effects (DGEs) of this particular trait (−0.78 ± 0.27). Results from classic animal model do not evidence a clear role of FBT to improve the accuracy of breeding value predictions for PT; only average daily feeding rate seems to show a positive correlation (around 0.50 to 0.60) with average daily gain, average daily feed consumption and backfat thickness. However, when IGE model was fitted, the number of estimates of genetic correlations between FBT and PT showing a relevant magnitude increased, generally for the correlations between IGE of FBT and DGE of PT; or particularly for the correlations between IGE of average daily feeding frequency, and the IGE of all the PT, except average daily gain. Thus, in evaluations using the animal model with IGE fitted, the inclusion of FBT could aid the improvement of the accuracy of breeding value predictions for PT. This is a consequence of the improved genetic relationships between traits that can be fitted when considering such models.

PSII-2 Application of partial least squares regression to predict feed efficiency and intake using feeding behavior patterns in growing steers and heifers

Abstract Objectives of this study were to evaluate the use of feeding behavior traits to predict individual-animal RFI and DMI of growing cattle fed high-grain finishing diets. Performance, DMI, and feeding behavior data were collected from 1 study utilizing 498 Angus-based composite steers (Study 1), and 2 studies utilizing 408 heifers (Study 2) and 321 steers (Study 3) composed of Brangus, Braford, Simbrah, and Angus breeds. DMI and feeding behavior traits were measured using a GrowSafe system, and RFI calculated within trial. Seventeen feeding behavior traits were evaluated: Frequency and duration of bunk visit (BV) and meal events, head-down duration (HDD), average meal length, maximum non-feeding interval, corresponding day-to-day variation (SD) of these traits, and ratios of HDD per BV duration, HDD per meal duration, and BV events per meal event. Partial least squares regression (PLSR) models for DMI and RFI were calibrated using data from Study 1 and 2, and independently validated using Study 3. Independent variables for the DMI models included mid-test BW0.75, ADG, frame size, and ultrasound traits, with and without feeding behavior traits, and for the RFI model included frame size, ultrasound, and feeding behavior traits. For prediction of DMI, validation R2 (R2v) of the base model (Mid-test BW0.75, ADG, frame size, and ultrasound) was 0.46. Inclusion of feeding behavior traits to the base model increased R2v to 0.66. For prediction of RFI, R2v was low (0.37), but the model classified 51% of calves into the correct RFI group (± 0.50 SD), with only 7% incorrectly classified across 2 RFI groups. Ongoing development of biosensor-based technologies to quantify feeding behavior patterns provides opportunities to predict DMI in support of precision nutrition, and reduce costs of identifying feed-efficient cattle. Further research is warranted to evaluate the robustness of PLSR-based models to predict RFI and DMI in cattle.

93 Feeding behavior as predictive traits of fertility and lifetime productivity in replacement beef heifers

Abstract Fertility and longevity traits in beef cows are difficult and expensive to measure. The use of other traits to predict fertility and longevity traits in beef cows will enable selection for efficient reproduction earlier in an animal’s life. The objective of this study is to identify feeding behaviours with predictive relationships to fertility, longevity, and lifetime productivity in beef cows. This study used 421 Bos taurus commercial replacement heifers born from 2004 to 2014 and followed over 1050 mating opportunities, 11 production cycles and 5 parities. Heifers were weaned at 6–7 mo of age and developed on a 90% barley silage, 10% rolled barley diet in pens equipped with 16 electronic feed bunks to monitor feed intake and feeding behaviors. Feed intake (FI), feeding frequency (FREQ), duration (DUR), head-down time (HD) and time-to-bunk (TTB) were collected over the course of the feeding trial. Phenotypic correlations indicate that as FI increased during the heifer development stage, so did subsequent cow pre-breeding and pre-calving body condition score (BCS; r = 0.43, 0.36 respectively) and total lifetime productivity (r = 0.40). As FREQ increased, pre-breeding and pre-calving BCS decreased (r = -0.16 and -0.20, respectively), as did calf birth weight (r = -0.15). As DUR increased, weak positive correlations were observed with days in herd (r = 0.10), age at first calving (r = 0.17) and calf birth weight (0.13). Increased HD would lead to increased pre-breeding and pre-calving BCS (r = 0.16, 0.23 respectively), and greater lifetime productivity (r = 0.16). Time-to-bunk was positively correlated with days in the herd (r = 0.15), and with decreased calf birth weight (r = -0.23) and pre-calving cow weight (r = -0.33). These feeding behaviour traits, collected early in life, are worthy of further investigation into multi trait regression, genetic correlations and genomic selection.

PSXIV-20 Effects of Saccharomyces cerevisiae CNCM I-1077 on growth efficiency, feeding behavior, physiology, and carcass quality of yearling steers fed a high-grain diet

Abstract The objective of this study was to evaluate the effects of Levucell SC (LY; Saccharomyces cerevisiae CNCM I-1077) supplementation on performance, feed efficiency, ruminal temperature, feeding behavior, and carcass quality traits in yearling steers. Forty-eight crossbred steers were randomly allocated into two treatments: (1) Control and (2) LY with two pen replicates per treatment (12 steers per pen). Steers were housed in pens equipped with GrowSafe and fitted with reticulo-rumen boluses. All steers were maintained on their respective dietary treatments until harvest to assess carcass traits. There were no differences amongst treatments in DMI, ADG, morbidity or mortality rates, ruminal temperature or F:G. Live-yeast supplemented steers had 17% greater (P = 0.05) backfat thickness than control steers, which resulted in a 13% increase in yield grade, with no differences in all other carcass traits. Live-yeast steers exhibited different feeding behavior patterns than control steers, such that LY steers approached the bunk 25 minutes earlier (P = 0.01) than control steers, had 22% greater (P &amp;lt; 0.05) bunk visit (BV) duration, 41% increased (P &amp;lt; 0.05) head down duration, 18% slower (P &amp;lt; 0.05) BV eating rates, and a tendency for 9% lower BV frequency. Meal criterion was 47% longer (P = 0.01) for LY steers resulting in a reduction (P = 0.07) in meal frequency. Additionally, LY steers consumed 27% longer meals (P &amp;lt; 0.05) that tended to be larger in size (P = 0.09). Although DMI was not different throughout the trial, LY displayed 10% decreased (P &amp;lt; 0.05) meal-eating rates due to longer meal lengths. Overall, LY steers approached the feed bunk sooner following feed delivery, ate fewer, but larger meals at a slower rate, and spent more time eating compared to control steers. Live-yeast supplementation clearly altered feeding behavior patterns, suggesting more favorable fermentation and the capability to mitigate metabolic stress in steers fed high-grain diets by altering meal patterns.

31 Characterization of feeding-behavior patterns and application of chemometrics to predict residual feed intake based on feeding-behavior traits in growing Holstein heifers

Abstract Objectives of this study were to characterize feeding-behavior (FB) patterns in growing dairy heifers with divergent RFI phenotypes (±0.50 SD) and to evaluate the accuracy of partial least squares regression (PLSR) models to predict RFI based on FB traits. Performance, DMI, and FB traits were measured for 70 to 100 d in 15 trials with Holstein heifers (n = 611) fed a corn-silage based ration. Seventeen FB traits were evaluated: frequency and duration of bunk visit (BV) and meal events, head-down duration (HDD), meal length, maximum non-feeding interval, corresponding day-today variation (SD) of these traits, and ratios of HDD per BV duration and meal duration, HDD per meal duration, and BV events per meal event. Data was analyzed using a mixed model that included RFI group and trial. The PLSR model for RFI was developed using cross-validation procedures (Leave-One-Out) in JMP (SAS), with FB traits as independent variables. LowRFI heifers consumed 24% less (P &lt; 0.01) DMI and had lower (P &lt; 0.01) day-to-day DMI variation than high-RFI heifers. Distinct differences were observed in FB patterns between low- and high-RFI heifers (Table 1). Eight of 17 FB traits were included [selected based on variable of importance (VIP) score &gt; 0.80] in the PLSR model that explained 33% of the variation in RFI. Head-down duration had the highest VIP score; accordingly, low-RFI animals had 44% lower HDD and 30 and 40% lower ratios of HDD per BV duration and meal duration, respectively. Additionally, low-RFI animals had 20 and 18% fewer BV and meal events per day, spent 21% less time eating during BV events, and had reduced day-to-day variation in HDD and meal frequency. For this study, distinctive differences were observed in the FB patterns of Holstein heifers with divergent RFI, which explained 33% of the between-animal variation in RFI.

181 Characterization of feeding-behavior patterns and application of chemometrics to predict residual feed intake based on feeding-behavior traits in growing Holstein heifers

Abstract Objectives of this study were to characterize feeding-behavior (FB) patterns in growing dairy heifers with divergent RFI phenotypes (±0.50 SD) and to evaluate the accuracy of partial least squares regression (PLSR) models to predict RFI based on FB traits. Performance, DMI, and FB traits were measured for 70 to 100 d in 15 trials with Holstein heifers (n = 611) fed a corn-silage based ration. Seventeen FB traits were evaluated: frequency and duration of bunk visit (BV) and meal events, head-down duration (HDD), meal length, maximum non-feeding interval, corresponding day-to-day variation (SD) of these traits, and ratios of HDD per BV duration and meal duration, HDD per meal duration, and BV events per meal event. Data were analyzed using a mixed model that included RFI group and trial. The PLSR model for RFI was developed using cross-validation procedures (Leave-One-Out) in JMP (SAS), with FB traits as independent variables. Low-RFI heifers consumed 24% less (P &lt; 0.01) DMI and had lower (P &lt; 0.01) day-to-day DMI variation than high-RFI heifers. Distinct differences were observed in FB patterns between low- and high-RFI heifers (Table 1). Eight of 17 FB traits were included [selected based on variable of importance (VIP) score &gt; 0.80] in the PLSR model that explained 33% of the variation in RFI. Head-down duration had the highest VIP score; accordingly, low-RFI animals had 44% lower HDD and 30 and 40% lower ratios of HDD per BV duration and meal duration, respectively. Additionally, low-RFI animals had 20 and 18% fewer BV and meal events per day, spent 21% less time eating during BV events, and had reduced day-to-day variation in HDD and meal frequency. For this study, distinctive differences were observed in the FB patterns of Holstein heifers with divergent RFI, which explained 33% of the between-animal variation in RFI.

Estimation of heritability of feeding behaviour traits and their correlation with production traits in Finnish Yorkshire pigs.

A major proportion of the costs of pork production is related to feed. The feed conversion rate (FCR) or residual feed intake (RFI) is thus commonly included in breeding programmes. Feeding behaviour traits do not directly have economic value but, if correlated with production traits, can be used as auxiliary traits. The aim of this study was to estimate the heritability of feeding behaviour traits and their genetic correlations with production traits in the Finnish Yorkshire pig population. The data were available from 3,235 pigs. Feeding behaviour was measured as the number of visits per day (NVD), time spent in feeding per day (TPD), daily feed intake (DFI), time spent feeding per visit (TPV), feed intake per visit (FPV) and feed intake rate (FR). The test station phase was divided into five periods. Estimates of heritabilities of feeding behaviour traits varied from 0.17 to 0.47. Strong genetic correlations were obtained between behaviour traits in all periods. However, only DFI was strongly correlated with the production traits. Interestingly, a moderate positive genetic correlation was obtained between FR and backfat thickness (0.1-0.5) and between FR and average daily gain (0.3-0.4), depending on the period. Based on the results, there is no additional benefit from including feeding-related traits other than those commonly used (FCR and RFI) in the breeding programme. However, if correlated with animal welfare, the feeding behaviour traits could be valuable in the breeding programme.