Preference for feed bins shared with cows of the same or different parity and relationships with feeding behavior and feed efficiency.

Our objectives were to (1) evaluate cows' preferences for visiting feed bins limited to either same- versus mixed-parity social interactions, depending on their parity; (2) examine the effect of parity and bin social dynamic type on competition behavior and feeding patterns, and (3) investigate cow-level relationships between feed bunk competition behavior, feeding patterns, and feed efficiency. Twenty-eight primiparous and 28 multiparous (2.4 ± 0.6 lactations) lactating Holstein cows (127.8 ± 30.1 and 145.3. ± 10.4 DIM, respectively) were housed in a freestall pen with 28 roughage intake control bins (2:1 stocking density). Each cow was assigned to 2 bins, including 1 shared with 3 other cows of the same parity (SM) and 1 with 3 cows of mixed parities (MX, 50% primiparous and 50% multiparous). Feed bunk competition was recorded via video in the first hour after morning feed delivery for 2 d, and feeding patterns were recorded from 24-h roughage intake control data. Residual feed intake was calculated as the difference between predicted and observed dry matter intake after accounting for known energy sinks. Based on the first visit to the feed bunk after fresh feed delivery, multiparous cows tended to prefer the MX bin compared with the SM one; cows showed no other overall preference for bin type based on number of visits. Over time, multiparous cows remained consistent in their magnitude of preference for visiting each bin type, but involvement in competition was not consistent over time. Primiparous cows tended to be involved in more total competitive contacts and ate faster at the SM bin compared with the MX one. Those primiparous cows who visited the SM bin more often within the first hour after morning feed delivery tended to be less feed efficient. Multiparous cows initiated more successful replacements after a displacement at the MX versus SM bin, with no difference in feeding patterns between bin types. Regardless of parity or bin type, visiting the bunk sooner after feed delivery was correlated with involvement in more competitive interactions and more time eating within the first 30 min. Consuming more feed during a longer first visit to the bunk after fresh feed delivery was correlated with being less feed efficient. Overall, when given the choice of feeding from bins shared with cows of the same or mixed parities at a 2:1 stocking density, primiparous cows showed differences in behavior between those bin types, with implications for feed efficiency; these effects are perhaps an unintended consequence of compensatory strategies to avoid direct competition with multiparous cows.

Residual feed intake is related to metabolic and inflammatory response during the preweaning period in Italian Simmental calves.

Residual Feed Intake (RFI) is defined as the difference between measured and predicted intake. Understanding its biological regulators could benefit farm profit margins. The most-efficient animals (M-Eff) have observed intake smaller than predicted resulting in negative RFI, whereas the least-efficient (L-Eff) animals have positive RFI. Hence, this observational study aimed at retrospectively comparing the blood immunometabolic profile in calves with divergent RFI during the preweaning period. Twenty-two Italian Simmental calves were monitored from birth through 60 d of age. Calves received 3 L of colostrum from their respective dams. From 2 to 53 d of age, calves were fed a milk replacer twice daily, whereas from 54 to 60 d (i.e., weaning) calves were stepped down to only one meal in the morning. Calves had ad libitum access to concentrate and intakes were recorded daily. The measurement of BW and blood samples were performed at 0, 1, 7, 14, 21, 28, 35, 45, 54, and 60 d of age. Calves were ranked and categorized as M-Eff or L-Eff according to the median RFI value. Median RFI was -0.06 and 0.04 kg of DMI/d for M-Eff and L-Eff, respectively. No evidence for group differences was noted for colostrum and plasma IgG concentrations. Although growth rate was not different, as expected, (0.67 kg/d [95% CI = 0.57-0.76] for both L-Eff and M-Eff) throughout the entire preweaning period (0-60 d), starter intake was greater in L-Eff compared with M-Eff calves (+36%). Overall, M-Eff calves had a greater gain-to-feed ratio compared with L-Eff calves (+16%). Plasma ceruloplasmin, myeloperoxidase, and reactive oxygen metabolites concentrations were greater in L-Eff compared with M-Eff calves. Compared with L-Eff, M-Eff calves had an overall greater plasma concentration of globulin, and γ-glutamyl transferase (indicating a better colostrum uptake) and Zn at 1 d. Retinol and urea were overall greater in L-Eff. The improved efficiency in nutrient utilization observed in M-Eff was paired with a lower grade of oxidative stress and systemic inflammation. L-Eff may have had greater energy expenditure to support the activation of the immune system.

Genetic relationships between behavioral traits and feed efficiency traits in lactating Holstein cows.

The evaluation of dairy cow feed efficiency using residual feed intake accounts for known energy sinks. However, behavioral traits may also contribute to the variation in feed efficiency. Our objective was to estimate the heritability and repeatability of behavioral traits and their genetic correlations with feed efficiency and its components in lactating Holstein cows. The first data set consisted of 36,075 daily rumination and lying time records collected using a SMARTBOW ear tag accelerometer (Zoetis, Parsippany, NJ) and 6,371 weekly feed efficiency records of 728 cows from the University of Wisconsin-Madison. The second data set consisted of 59,155 daily activity records, measured as number of steps, recorded by pedometers (AfiAct; S.A.E. Afikim, Kibbutz Afikim, Israel), and 8,626 weekly feed efficiency records of 635 cows from the University of Florida. Feed efficiency and its components included dry matter intake, change in body weight, metabolic body weight, secreted milk energy, and residual feed intake. The statistical models included the fixed effect of cohort, lactation number, and days in milk, and the random effects of animal and permanent environment. Heritability estimates for behavioral traits using daily records were 0.19 ± 0.06 for rumination and activity, and 0.37 ± 0.07 for lying time. Repeatability estimates for behavioral traits using daily data ranged from 0.56 ± 0.02 for activity to 0.62 ± 0.01 for lying time. Both heritability and repeatability estimates were larger when weekly records instead of daily records were used. Rumination and activity had positive genetic correlations with residual feed intake (0.40 ± 0.19 and 0.31 ± 0.22, respectively) while lying time had a negative genetic correlation with this residual feed intake (-0.27 ± 0.11). These results indicate that more efficient cows tend to spend more time lying and less time active. Additionally, less efficient cows tend to eat more and therefore also tend to ruminate longer. Overall, sensor-based behavioral traits are heritable and genetically correlated with feed efficiency and its components and, therefore, they could be used as indicators to identify feed efficient cows within the herd.

Feed Efficiency Estimation from Stochastic Feed Requirement Frontier.

Feed accounts 40 to 70 percent of livestock production cost. Therefore, improving feed efficiency of production animals will promote farm profitability. To this end, precise estimation of animal level feed efficiency is important. Considering some limitations of residual feed intake (RFI) as indicator of animal level feed efficiency, an alternative approach is suggested. The approach involves estimation of a stochastic feed requirement frontier (SFRF), which explicitly allows for feed efficiency and statistical noise in the same specification. As a result, a SFRF naturally leads to feed efficiency indicator free from statistical noise. Furthermore, the feed efficiency indicator it generates is nonnegative and it can easily be expressed in terms of surplus feed intake (SFI) caused by feed inefficiency. Simulation experiment was used to illustrate the problems that arise from RFI-based feed efficiency estimation and the improvements that can be expected from the alternative approach. The experimental results showed that RFI tends to overestimate feed efficiency of animals. The overestimation gets worse as the contribution of feed inefficiency to feed intake variation increases. The results from the experiment also showed SFRF provides consistent feed efficiency estimates and associated SFI. Finally, further benefits of the alternative approach in feed efficiency estimation at animal level are presented.

Estimation of genetic parameters for maintenance energy requirements and residual feed intake in Nellore cattle.

We estimated heritabilities and genetic and phenotypic correlation estimates for maintenance energy requirements (NEmR), residual feed intake (RFI), growth, carcass and reproductive indicator traits, using data from 41 feed efficiency trials in Brazil, comprising 4381 males and females. Continuous traits were analysed using a linear animal model and threshold traits were analysed using a threshold animal model. The heritability estimates were low for RFI (0.190) and NEmR (0.193); other heritabilities were mainly moderate (growth and carcass traits) or high (sexual precocity traits). The genetic correlation of RFI with NEmR was high (0.701). The genetic correlations of NEmR were low with carcass and reproductive traits, and moderate with growth traits. Thus, selection to improve weaning weight and female sexual precocity indicator traits would not affect maintenance energy requirement. Genetic selection to reduce maintenance energy requirements is feasible and would also reduce DMI and RFI. Selection to improve RFI can be used to identify animals with lower maintenance energy requirements. Long-term selection to reduce RFI and NEmR would have favourable effects on yearling weight, carcass muscle indicator traits and female sexual precocity. Genetic (co)variance component estimates for NEmR, in conjunction with economic values of selection criteria, may be used to develop novel approaches for genetic selection to improve efficiency of beef production.

Estimation of genetic correlations of two key feed efficiency traits with production traits in male Hu sheep.

Increased body growth and feed efficiency are important for breeding due to expensive feed costs. This study estimated the genetic parameters for two feed efficiency traits [the feed conversion ratio (FCR) and the residual feed intake (RFI)] and other important economic traits in male Hu sheep using 1642 male Hu lambs. The heritability of the RFI was estimated at 0.31 (±0.10)-0.54 (±0.1) and the heritability of the FCR was 0.05 (±0.07)-0.77 (±0.12). There was a negative genetic correlation between rib-eye muscle area traits and RFI. A positive genetic correlation was found between fat deposition traits and feed efficiency traits. The digestive tract weight decreased with the direction of RFI: however, the FCR showed the opposite: A low FCR was accompanied by a high digestive tract weight. The genetic correlation between feed efficiency (RFI and FCR) and rumen weight was negative. Heritability estimates for feed efficiency generate fluctuations with different experimental intervals. The weight of other traits should be reasonably allocated to avoid losses in production and feed efficiency in the selection of feed efficiency traits. The present study added to our understanding of the genetic parameters of sheep under the condition of house feeding.

Effect of feed efficiency on growth performance, body composition, and fat deposition in growing Hu lambs.

The present study aimed to investigate the relationship between growth performance, body composition, and fat deposition factors, and feed efficiency in growing lambs. We measured average daily feed intake (ADFI) and body weight (BW) from 653 Hu sheep that were fed a pellet diet. The residual feed intake (RFI) not significantly genetic and phenotypic correlated with the metabolic body weight (MBW) and average daily gain (ADG), but it was significantly genetic and phenotypic correlated with ADFI and the feed conversion ratio (FCR) (p < 0.01). However, the FCR was significantly associated with growth traits (p < 0.01). With the same ADG, body fat deposition was greater in animals with low feed efficiency compared with high feed efficiency. Therefore, excessive fat deposition can affect the feed efficiency of the body, and organ weight and gut-weight have a greater impact on the feed efficiency of lambs. The reticulum stomach and jejunum of lambs with a low RFI were smaller compared with that in the high RFI, indicating that lambs with a low RFI have less intake and a higher absorption rate. Small organs, such as the liver, of lambs with high FE might be associated with low energy expenditure and slow metabolism. This study provides a new perspective to study the biological processes responsible for feed efficiency variation in lambs.

Relationship between feed efficiency and resilience in dairy ewes subjected to acute underfeeding.

Selection of dairy sheep based on production levels has caused a loss of rusticity, which might compromise their future resilience to nutritional challenges. Although refocusing breeding programs toward improved feed efficiency (FE) is expected, more-efficient ewes also seem to be more productive. As a first step to examine the relationship between FE and resilience in dairy sheep, in this study we explored the variation in the response to and the recovery from an acute nutritional challenge in high-yielding Assaf ewes phenotypically divergent for FE. First, feed intake, milk yield and composition, and body weight changes were recorded individually over a 3-wk period in a total of 40 sheep fed a total mixed ration (TMR) ad libitum. Data were used to calculate their FE index (FEI, defined as the difference between the actual and predicted intake estimated through net energy requirements for maintenance, production, and weight change). The highest and lowest FE ewes (H-FE and L-FE groups, respectively; 10 animals/group) were selected and then subjected to the nutritional challenge (i.e., withdrawing the TMR and limiting their diet only to the consumption of straw for 3 d). Afterward, sheep were fed again the TMR ad libitum. Temporal patterns of variation in performance traits, and ruminal fermentation and blood parameters were examined. A good consistency between FEI, residual feed intake, and feed conversion ratio was observed. Results supported that H-FE were more productive than L-FE sheep at similar intake level. Average time trends of milk yield generated by a piecewise model suggest that temporal patterns of variation in this trait would be related to prechallenge production level (i.e., H-FE presented quicker response and recovery than L-FE). Considering all studied traits, the overall response to and recovery from underfeeding was apparently similar or even better in H-FE than in L-FE. This would refute the initial hypothesis of a poorer resilience of more-efficient sheep to an acute underfeeding. However, the question remains whether a longer term feed restriction might impair the ability of H-FE ewes to maintain or revert to a high-production status, which would require further research.

Genomic evaluation of feed efficiency in US Holstein heifers.

There is growing interest in improving feed efficiency traits in dairy cattle. The objectives of this study were to estimate the genetic parameters of residual feed intake (RFI) and its component traits [dry matter intake (DMI), metabolic body weight (MBW), and average daily gain (ADG)] in Holstein heifers, and to develop a system for genomic evaluation for RFI in Holstein dairy calves. The RFI data were collected from 6,563 growing Holstein heifers (initial body weight = 261 ± 52 kg; initial age = 266 ± 42 d) for 70 d, across 182 trials conducted between 2014 and 2022 at the STgenetics Ohio Heifer Center (South Charleston, OH) as part of the EcoFeed program, which aims to improve feed efficiency by genetic selection. The RFI was estimated as the difference between a heifer's actual feed intake and expected feed intake, which was determined by regression of DMI against midpoint MBW, age, and ADG across each trial. A total of 61,283 SNPs were used in genomic analyses. Animals with phenotypes and genotypes were used as training population, and 4 groups of prediction population, each with 2,000 animals, were selected from a pool of Holstein animals with genotypes, based on their relationship with the training population. All traits were analyzed using univariate animal model in DMU version 6 software. Pedigree information and genomic information were used to specify genetic relationships to estimate the variance components and genomic estimated breeding values (GEBV), respectively. Breeding values of the prediction population were estimated by using the 2-step approach: deriving the prediction equation of GEBV from the training population for estimation of GEBV of prediction population with only genotypes. Reliability of breeding values was obtained by approximation based on partitioning a function of the accuracy of training population GEBV and magnitudes of genomic relationships between individuals in the training and prediction population. Heifers had DMI (mean ± SD) of 8.11 ± 1.59 kg over the trial period, with growth rate of 1.08 ± 0.25 kg/d. The heritability estimates (mean ± SE) of RFI, MBW, DMI, and growth rate were 0.24 ± 0.02, 0.23 ± 0.02, 0.27 ± 0.02, and 0.19 ± 0.02, respectively. The range of genomic predicted transmitted abilities (gPTA) of the training population (-0.94 to 0.75) was higher compared with the range of gPTA (-0.82 to 0.73) of different groups of prediction population. Average reliability of breeding values from the training population was 58%, and that of prediction population was 39%. The genomic prediction of RFI provides new tools to select for feed efficiency of heifers. Future research should be directed to find the relationship between RFI of heifers and cows, to select individuals based on their lifetime production efficiencies.

Social interactions, feeding patterns, and feed efficiency of same- and mixed-parity groups of lactating cows.

Social dynamics in group-housed animals can have important effects on their welfare, feed efficiency, and production potential. Our objectives were to: (1) evaluate the effects of parity and social grouping on competition behavior, feeding patterns, and feed efficiency, and (2) investigate cow-level relationships between competition and feeding behavior, production, and feed efficiency. Fifty-nine Holstein cows (144.5 ± 21.8 starting days in milk, mean ± SD) were housed in a freestall pen with 30 Roughage Intake Control (RIC) bins. We evaluated the effects of parity (primiparous [PR, n = 29] vs. multiparous [MU, n = 30]) and group composition at the feed bunk (same-parity [SM, n = 39] vs. mixed-parity [MX, n = 20, 50% of each parity]) with a 2 × 2 factorial design (SM-MU: n = 20; SM-PR: n = 19; MX-MU: n = 10; MX-PR: n = 10) on competition behavior, feeding patterns, and feed efficiency. Within the pen, groups of 9 to 10 cows were considered subgroups and assigned to treatments defined by sets of 5 assigned bins (2:1 stocking density). Feed bunk competition and feeding patterns were recorded via continuous video in the first hour after morning feed delivery and 24-h RIC data, respectively. Residual feed intake (RFI) was calculated as the difference between predicted and observed dry matter intake (DMI) after accounting for known energy sinks. Linear models were used to evaluate the effects and interactions of parity and group composition on competition, feeding behavior, and feed efficiency. Within-cow correlations were performed between competition, feeding behavior, and RFI. Cows in MX, compared with SM, were involved in more competitive interactions [mean (95% CI): competitive contacts: 11.5 (8.1, 16.3) vs. 7.2 (5.5, 9.3) events; displacements: 4.0 (3.0, 5.3) vs. 2.1 (1.7, 2.7) events, and replacements: 3.5 (2.6, 4.7) vs. 1.9 (1.5, 2.5) events]. Cows in MX vs. those in SM had more bunk visits/meal ( 4.3 [3.9, 4.8] vs. 3.7 [3.4, 3.9] visits/meal) and longer meals (31.2 vs. 27.4 ± 0.9 min/meal) and tended to have higher RFI (0.41 ± 0.3 vs. -0.21 ± 0.2) and were therefore less feed efficient. Multiparous versus PR cows had greater DMI per day (29.3 ± 0.6 vs. 25.5 ± 0.4 kg/d) and per meal (4.2 [4.0, 4.4] vs. 3.4 [3.2, 3.6] kg/meal), faster eating rates (0.14 [0.13, 0.15] vs. 0.12 [0.11, 0.13] kg/min), and fewer bunk visits/d (26.6 [24.0, 29.4] vs. 32.8 [29.7, 35.9]). Regardless of grouping or parity, cows with shorter latencies to first visit the bunk after feed delivery were involved in more competition and tended to be less feed efficient. Overall, individual cow- and group-level relationships among competition, feeding behavior, and feed efficiency play an important role in feed bunk social dynamics. At a competitive 2:1 stocking density, mixed-parity groups for lactating cows may have potentially negative animal welfare and feed efficiency implications that should be considered when selecting grouping strategies on the farm.

Novel genetic parameters for genetic residual feed intake in dairy cattle using time series data from multiple parities and countries in North America and Europe.

Residual feed intake is viewed as an important trait in breeding programs that could be used to enhance genetic progress in feed efficiency. In particular, improving feed efficiency could improve both economic and environmental sustainability in the dairy cattle industry. However, data remain sparse, limiting the development of reliable genomic evaluations across lactation and parity for residual feed intake. Here, we estimated novel genetic parameters for genetic residual feed intake (gRFI) across the first, second, and third parity, using a random regression model. Research data on the measured feed intake, milk production, and body weight of 7,379 cows (271,080 records) from 6 countries in 2 continents were shared through the Horizon 2020 project Genomic Management Tools to Optimise Resilience and Efficiency, and the Resilient Dairy Genome Project. The countries included Canada (1,053 cows with 47,130 weekly records), Denmark (1,045 cows with 72,760 weekly records), France (329 cows with 16,888 weekly records), Germany (938 cows with 32,614 weekly records), the Netherlands (2,051 cows with 57,830 weekly records), and United States (1,963 cows with 43,858 weekly records). Each trait had variance components estimated from first to third parity, using a random regression model across countries. Genetic residual feed intake was found to be heritable in all 3 parities, with first parity being predominant (range: 22-34%). Genetic residual feed intake was highly correlated across parities for mid- to late lactation; however, genetic correlation across parities was lower during early lactation, especially when comparing first and third parity. We estimated a genetic correlation of 0.77 ± 0.37 between North America and Europe for dry matter intake at first parity. Published literature on genetic correlations between high input countries/continents for dry matter intake support a high genetic correlation for dry matter intake. In conclusion, our results demonstrate the feasibility of estimating variance components for gRFI across parities, and the value of sharing data on scarce phenotypes across countries. These results can potentially be implemented in genetic evaluations for gRFI in dairy cattle.

Estimates of genetic and phenotypic parameters for feeding behaviour and feed efficiency-related traits in Nelore cattle.

The objective of this study was to obtain (co)variance components, heritability, and genetic and phenotypic correlation estimates for feed efficiency and feed behaviour-related indicator traits. Further, it aimed to predict the direct and correlated responses for feed efficiency traits when selection was applied for feeding behaviour-related traits in Nelore cattle. Phenotypic records (n = 4840) from 125 feed efficiency tests (RFI: Residual feed intake and DMI: Dry matter intake) carried out between 2011 and 2018 were considered in this study. Animals belonged to five farms located in two Brazilian geographical regions (Midwest and Southeast). Animals under similar management and environmental conditions in the feedlot were evaluated when they attained an average of 13.5 ± 4.15 months of age. Feed behaviour-related traits were also obtained, including meal criteria (MC), meal frequency (MF), average meal duration (AMD), meal duration (MD), average consumption per meal (ACM), and consumption rate (CR) through the GrowSafe System® electronic bunk system. The contemporary groups for all traits were composed of farm, management group, feed efficiency test, sex, and birth year. The (co)variance components were estimated using the restricted maximum likelihood method considering a multi-trait (n = 8) animal model. The heritability estimates for RFI (0.23 ± 0.02), DMI (0.31 ± 0.02), MF (0.65 ± 0.02), AMD (0.29 ± 0.02), ACM (0.24 ± 0.02), MD (0.41 ± 0.02), MC (0.48 ± 0.02), and CR (0.42 ± 0.02) were moderate to high. The highest genetic correlation was obtained between CR and MD (-0.91 ± 0.04), MD and AMD (0.73 ± 0.03), CR and AMD (-0.68 ± 0.04), and RFI and DMI (0.81 ± 0.02). The highest phenotypic correlation was between ACM and AMD (0.76 ± 0.02), DMI and MD (0.77 ± 0.02), and DMI and RFI (0.77 ± 0.02). Genetic improvement for feed efficiency and feeding behaviour-related traits is feasible and the results obtained herein provided valuable information regarding the genetic background of Nelore feeding behaviour-related traits. The genetic association between feeding behaviour and feed efficiency-related traits suggested that animals spending less time feeding at a low feeding rate also had lower DMI and higher feed efficiency (RFI), and likely had lower energy maintenance requirements. The relative efficiency of selection showed that feeding behaviour-related traits were not adequate indicator traits to improve RFI and DMI. The DMI might be an effective selection criterion to improve RFI and reduce the herd's maintenance requirements.

Impact of multi-output and stacking methods on feed efficiency prediction from genotype using machine learning algorithms.

Feeding represents the largest economic cost in meat production; therefore, selection to improve traits related to feed efficiency is a goal in most livestock breeding programs. Residual feed intake (RFI), that is, the difference between the actual and the expected feed intake based on animal's requirements, has been used as the selection criteria to improve feed efficiency since it was proposed by Kotch in 1963. In growing pigs, it is computed as the residual of the multiple regression model of daily feed intake (DFI), on average daily gain (ADG), backfat thickness (BFT), and metabolic body weight (MW). Recently, prediction using single-output machine learning algorithms and information from SNPs as predictor variables have been proposed for genomic selection in growing pigs, but like in other species, the prediction quality achieved for RFI has been generally poor. However, it has been suggested that it could be improved through multi-output or stacking methods. For this purpose, four strategies were implemented to predict RFI. Two of them correspond to the computation of RFI in an indirect way using the predicted values of its components obtained from (i) individual (multiple single-output strategy) or (ii) simultaneous predictions (multi-output strategy). The other two correspond to the direct prediction of RFI using (iii) the individual predictions of its components as predictor variables jointly with the genotype (stacking strategy), or (iv) using only the genotypes as predictors of RFI (single-output strategy). The single-output strategy was considered the benchmark. This research aimed to test the former three hypotheses using data recorded from 5828 growing pigs and 45,610 SNPs. For all the strategies two different learning methods were fitted: random forest (RF) and support vector regression (SVR). A nested cross-validation (CV) with an outer 10-folds CV and an inner threefold CV for hyperparameter tuning was implemented to test all strategies. This scheme was repeated using as predictor variables different subsets with an increasing number (from 200 to 3000) of the most informative SNPs identified with RF. Results showed that the highest prediction performance was achieved with 1000 SNPs, although the stability of feature selection was poor (0.13 points out of 1). For all SNP subsets, the benchmark showed the best prediction performance. Using the RF as a learner and the 1000 most informative SNPs as predictors, the mean (SD) of the 10 values obtained in the test sets were: 0.23 (0.04) for the Spearman correlation, 0.83 (0.04) for the zero-one loss, and 0.33 (0.03) for the rank distance loss. We conclude that the information on predicted components of RFI (DFI, ADG, MW, and BFT) does not contribute to improve the quality of the prediction of this trait in relation to the one obtained with the single-output strategy.

Genetic association between feed efficiency, growth, scrotal circumference, and carcass traits in Guzerat cattle.

The objective of this study was to estimate the genetic parameters for feed efficiency-related traits and their genetic correlations with growth, male fertility, and carcass traits using multi-trait analysis in Guzerat cattle. Further, it aimed to predict the direct and correlated responses for feed efficiency traits when selection was applied for growth, male fertility, and carcass traits. The evaluated traits were adjusted weight at 120 (W120), 210 (W210), 365 (W365), and 450 days of age (W450), adjusted scrotal circumference at 365 days of age (SC365) and at 450 days of age (SC450), scrotal circumference, ribeye area (REA), backfat thickness (BFT), rump fat thickness (RFT), residual feed intake (RFI), and dry matter intake (DMI). The genetic parameters were obtained by the restricted maximum likelihood method (REML), using an animal model in multi-trait analyses. The heritability estimates for W120, W210, W365, W450, SC365, and SC450 varied from low to high (0.17 to 0.39). The carcass traits, REA, BFT, and RFT, displayed low to moderate heritability estimates, 0.27, 0.10, and 0.31, respectively. The heritability estimates for RFI (0.15) and DMI (0.23) were low and moderate, respectively. The RFI showed low genetic correlations with growth traits, ranging from - 0.07 to 0.22, from 0.03 to 0.05 for scrotal circumference, and from - 0.35 to 0.16 for carcass, except for DMI, which ranged from 0.42 to 0.46. The RFI and DMI presented enough additive genetic variability to be used as selection criteria in Guzerat breed genetic improvement program. Additionally, the response to selection for RFI would be higher when selection is performed directly for this trait. The selection for residual feed intake would not promote unfavorable correlated responses for scrotal circumference, carcass (yield and finish), and growth traits. Therefore, the selection for more efficient animals would not compromise the productive, reproductive, and carcass performance, contributing to reduce the production costs, increasing the profitability and sustainability of beef cattle production in tropical areas.

Genome-wide association studies identified loci associated with both feed conversion ratio and residual feed intake in Yorkshire pigs.

Feed occupies a significant proportion in the production cost of pigs, and the feed efficiency (FE) in pigs is of utmost economic importance. Hence, the objective of this study is to identify single-nucleotide polymorphisms (SNPs) and candidate genes associated with FE-related traits, including feed conversion ratio (FCR) and residual feed intake (RFI). A genome-wide association study was conducted for FCR and RFI in 169 Yorkshire pigs using whole-genome sequencing data. A total of 23 and 33 suggestive significant SNPs (P < 1 × 10-6) were detected for FCR and RFI, respectively. However, none of SNPs achieved the genome-wide significance threshold (P < 5 × 10-8). Importantly, three common SNPs (SSC7:7987268, SSC13:42350250, and SSC13:42551718) were associated with both FCR and RFI. Additionally, the NEDD9 gene related to FCR and RFI traits was overlapped. This study detected novel SNPs on SSC7 and SSC13 common for FCR and RFI. These results provide new insights into the genetic mechanisms and candidate genes of FE-related traits in pigs.

Polymorphism in ovine ADCY8 gene and its association with residual feed intake in Hu sheep.

Feed efficiency makes up a large part of sheep production, which also has a crucial impact on the economic benefits of producers. This study explores the polymorphism of Adenylyl cyclase 8 gene associated with feed efficiency and detects the expression characteristics of ADCY8 in ten tissues of Hu sheep. The polymorphism of ADCY8 was recognized by using PCR amplification and Sanger sequencing, KASPar technology was used for genotyping subsequently, and the relationship between SNP and RFI is also studied. The results indicated that an intronic mutation g.24799148 C > T (rs 423395741) was identified in ADCY8, and association analysis showed that the SNP g.24799148 C > T (rs 423395741) was significantly associated with RFI at 100-120, 100-140, 100-160, and 100-180 days (p < 0.05). The quantitative real-time PCR (qRT-PCR) result showed that ADCY8 was expressed in ten tissues, and the expression of ADCY8 gene in rumen tissue was significantly higher than in the other tested tissues. Therefore, these results indicated that the ADCY8 mutation locus may be used as a candidate molecular marker for evaluating the feed efficiency of Hu sheep.

Comparison of 3-breed rotational crossbreds of Montbéliarde, Viking Red, and Holstein with Holstein cows fed 2 alternative diets for dry matter intake, production, and residual feed intake.

The objective of this study was to compare 3-breed rotational crossbred (CB) cows of the Montbéliarde, Viking Red, and Holstein (HO) breeds with HO cows fed 2 alternative diets for dry matter intake (DMI), fat plus protein production (CFP), body weight (BW), body condition score (BCS), feed efficiency, and residual feed intake (RFI) from 46 to 150 days in milk (DIM) during first lactation. The CB cows (n = 17) and HO cows (n = 19) calved from September 2019 to March 2020. Cows were fed either a traditional total mixed ration diet (TRAD) or a higher fiber, lower starch total mixed ration diet (HFLS). The HFLS had 21% more corn silage, 47% more alfalfa hay, 44% less corn grain, and 43% less corn gluten feed than the TRAD. The 2 diets were analyzed for dry matter content, crude protein, forage digestibility, starch, and net energy for lactation. The BW and BCS were recorded once weekly. Daily milk, fat, and protein production were estimated from twice monthly milk recording with random regression. Measures of efficiency were CFP per kilogram of DMI and DMI per kilogram of BW. The RFI from 46 to 150 DIM was the residual error from regression of DMI on milk energy, metabolic BW, and the energy required for change in BW. Statistical analysis of all variables included the fixed effects of diet, breed group, and the interaction of diet and breed group. The CB cows fed HFLS had less DMI (-12%) and lower DMI/BW (-14%) compared with the HO cows fed TRAD. For CFP, CB and HO cows were not different when fed TRAD or HFLS. Furthermore, the CB cows fed HFLS had higher BW (+50 kg) compared with HO cows fed HFLS. The CB cows fed TRAD had higher BCS than HO cows fed TRAD and HO cows fed HFLS (+0.46 and +0.62, respectively). The HO cows fed TRAD had more DMI (+14%) and lower CFP per kilogram of DMI (-12%) compared with the HO cows fed HFLS. In addition, mean RFI from 46 to 150 DIM was lower and more desirable for CB cows fed HFLS (-120.0 kg) compared with HO cows fed TRAD (85.3 kg). Dairy producers may feed either TRAD or HFLS to CB cows without loss of CFP.

Effect of diet energy level and genomic residual feed intake on bred Holstein dairy heifer growth and feed efficiency.

The objective of this study was to determine growth, feed intake, and feed efficiency of postbred dairy heifers with different genomic residual feed intake (RFI) predicted as a lactating cow when offered diets differing in energy density. Postbred Holstein heifers (n = 128, ages 14-20 mo) were blocked by initial weight (high, medium-high, medium-low, and low) with 32 heifers per block. Each weight block was sorted by RFI (high or low) to obtain 2 pens of heifers with high and low genomically predicted RFI within each block (8 heifers per pen). Low RFI heifers were expected to have greater feed efficiency than high RFI heifers. Dietary treatments consisted of a higher energy control diet based on corn silage and alfalfa haylage [HE; 62.7% total digestible nutrients, 11.8% crude protein, and 45.6% neutral detergent fiber; dry matter (DM) basis], and a lower energy diet diluted with straw (LE; 57.0% total digestible nutrients, 11.7% crude protein, and 50.1% neutral detergent fiber; DM basis). Each pen within a block was randomly allocated a diet treatment to obtain a 2 × 2 factorial arrangement (2 RFI levels and 2 dietary energy levels). Diets were offered in a 120-d trial. Dry matter intake by heifers was affected by diet (11.0 vs. 10.0 kg/d for HE and LE, respectively) but not by RFI or the interaction of RFI and diet. Daily gain was affected by the interaction of RFI and diet, with low RFI heifers gaining more than high RFI heifers when fed LE (0.94 vs. 0.85 kg/d for low and high RFI, respectively), but no difference for RFI groups when fed HE (1.16 vs. 1.19 kg/d for low and high RFI, respectively). Respective feed efficiencies were improved for low RFI compared with high RFI heifers when fed LE (10.6 vs. 11.8 kg of feed DM/kg of gain), but no effect of RFI was found when fed HE (9.4 vs. 9.5 kg of DM/kg of gain for high and low RFI, respectively). No effect of RFI or diet on first-lactation performance through 150 DIM was observed. Based on these results, the feed efficiency of heifers having different genomic RFI may be dependent on diet energy level, whereby low RFI heifers utilized the LE diet more efficiently. The higher fiber straw (LE) diet controlled intake and maintained more desirable heifer weight gains. This suggests that selection for improved RFI in lactating cows may improve feed efficiency in growing heifers when fed to meet growth goals of 0.9 to 1.0 kg of gain/d.

Multiple-trait random regression modeling of feed efficiency in US Holsteins.

Residual feed intake (RFI) and feed saved (FS) are important feed efficiency traits that have been increasingly considered in genetic improvement programs. Future sustainability of these genetic evaluations will depend upon greater flexibility to accommodate sparsely recorded dry matter intake (DMI) records on many more cows, especially from commercial environments. Recent multiple-trait random regression (MTRR) modeling developments have facilitated days in milk (DIM)-specific inferences on RFI and FS, particularly in modeling the effect of change in metabolic body weight (MBW). The MTRR analyses, using daily data on the core traits of DMI, MBW, and milk energy (MilkE), were conducted separately for 2,532 primiparous and 2,379 multiparous US Holstein cows from 50 to 200 DIM. Estimated MTRR variance components were used to derive genetic RFI and FS and DIM-specific genetic partial regressions of DMI on MBW, MilkE, and change in MBW. Estimated daily heritabilities of RFI and FS varied across lactation for both primiparous (0.05-0.07 and 0.11-0.17, respectively) and multiparous (0.03-0.13 and 0.10-0.17, respectively) cows. Genetic correlations of RFI across DIM varied (>0.05) widely compared with FS (>0.54) within either parity class. Heritability estimates based on average lactation-wise measures were substantially larger than daily heritabilities, ranging from 0.17 to 0.25 for RFI and from 0.35 to 0.41 for FS. The partial genetic regression coefficients of DMI on MBW (0.11 to 0.16 kg/kg0.75 for primiparous and 0.12 to 0.14 kg/kg0.75 for multiparous cows) and of DMI on MilkE (0.45 to 0.68 kg/Mcal for primiparous and 0.36 to 0.61 kg/Mcal for multiparous cows) also varied across lactation. In spite of the computational challenges encountered with MTRR, the model potentially facilitates an efficient strategy for harnessing more data involving a wide variety of data recording scenarios for genetic evaluations on feed efficiency.

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

Residual feed intake (RFI) is commonly used to measure feed efficiency but individual intake recording systems are needed. Feeding behavior may be used as an indicator trait for feed efficiency using less expensive precision livestock farming technologies. Our goal was to estimate genetic parameters for feeding behavior and the genetic correlations with feed efficiency in Holstein cows. Data consisted of 75,877 daily feeding behavior records of 1,328 mid-lactation Holstein cows in 31 experiments conducted from 2009 to 2020 with an automated intake recording system. Feeding behavior traits included number of feeder visits per day, number of meals per day, duration of each feeder visit, duration of each meal, total duration of feeder visits, intake per visit, intake per meal [kg of dry matter (DM)], feeding rate per visit, and feeding rate per meal (kg of DM per min). The meal criterion was estimated as 26.4 min, which means that any pair of feeder visits separated by less than 26.4 min were considered part of the same meal. The statistical model included lactation and days in milk as fixed effects, and experiment-treatment, animal, and permanent environment as random effects. Genetic parameters for feeding behavior traits were estimated using daily records and weekly averages. Estimates of heritability for daily feeding behavior traits ranged from 0.09 ± 0.02 (number of meals; mean ± standard error) to 0.23 ± 0.03 (feeding rate per meal), with repeatability estimates ranging from 0.23 ± 0.01 (number of meals) to 0.52 ± 0.02 (number of feeder visits). Estimates of heritability for weekly averages of feeding behavior traits ranged from 0.19 ± 0.04 (number of meals) to 0.32 ± 0.04 (feeding rate per visit), with repeatability estimates ranging from 0.46 ± 0.02 (duration of each meal) to 0.62 ± 0.02 (feeding rate per visit and per meal). Most of the feeding behavior measures were strongly genetically correlated, showing that with more visits or meals per day, cows spend less time in each feeder visit or meal with lower intake per visit or meal. Weekly averages for feeding behavior traits were analyzed jointly with RFI and its components. Number of meals was genetically correlated with milk energy (0.48), metabolic body weight (-0.27), and RFI (0.19). Duration of each feeder visit and meal were genetically correlated with milk energy (0.43 and 0.44, respectively). Total duration of feeder visits per day was genetically correlated with DM intake (0.29), milk energy (0.62), metabolic body weight (-0.37), and RFI (0.20). Intake per visit and meal were genetically correlated with DM intake (0.63 and 0.87), milk energy (0.47 and 0.69), metabolic body weight (0.47 and 0.68), and RFI (0.31 and 0.65). Feeding rate was genetically correlated with DM intake (0.69), metabolic body weight (0.67), RFI (0.47), and milk energy (0.21). We conclude that measures of feeding behavior could be useful indicators of dairy cow feed efficiency, and individual cows that eat at a slower rate may be more feed efficient.