Invited review: Disentangling residual feed intake-Insights and approaches to make it more fit for purpose in the modern context

Metagenomic insights into the relationship between intestinal flora and residual feed intake of meat ducks

In this study, we sought to determine the effects of intestinal flora on the feed efficiency of meat ducks by evaluating the correlation between intestinal flora and residual feed intake. The F2 generation of Cherry Valley ducks × Runzhou Crested White ducks was used as the study subjects, and feed consumption being recorded from d 21 to 42. RFI was calculated based on growth performance, and 20 low RFI and 20 high RFI ducks were randomly selected to characterize the effect of RFI on growth performance. To analyze the intestinal flora affecting RFI, 16s rDNA sequencing was performed on the contents of 5 intestinal segments from the HR and LR groups, and macrogenomic sequencing was performed on the cecal contents. Feed intake, average daily feed intake, feed conversion ratio, and residual feed intake were lower in low RFI. Analysis of the intestinal flora revealed the cecum to be more highly enriched in the carbohydrate metabolism pathway and less enriched with potentially pathogenic taxa than the other assessed intestinal regions. Further analysis of the cecal microbiota identified nine significantly differentially enriched intestinal flora. In this study, we accordingly identified a basis for the mechanisms underlying the effects of the intestinal flora on meat duck feed efficiency.

Feed intake in housed dairy cows: validation of a three-dimensional camera-based feed intake measurement system

Measuring feed intake accurately is crucial to determine feed efficiency and for genetic selection. A system using three-dimensional (3D) cameras and deep learning algorithms can measure the volume of feed intake in dairy cows, but for now, the system has not been validated for feed intake expressed as weight of feed. The aim of this study was to validate the weight of feed intake predicted from the 3D cameras with the actual measured weight. It was hypothesised that diet-specific coefficients are necessary for predicting changes in weight, that the relationship between weight and volume is curvilinear throughout the day, and that manually pushing the feed affects this relationship. Twenty-four lactating Danish Holstein cows were used in a cross-over design with four dietary treatments, 2 × 2 factorial arranged with either grass-clover silage or maize silage as silage factor, and barley or dried beet pulp as concentrate factor. Cows were adapted to the diets for 11 d, and for 3 d to tie-stall housing before camera measurements. Six cameras were used for recording, each mounted over an individual feeding platform equipped with a weight scale. When building the predictive models, four cameras were used for training, and the remaining two for testing the prediction of the models. The most accurate predictions were found for the average feed intake over a period when using the starting density of the feed pile, which resulted in the lowest errors, 6% when expressed as RMSE and 5% expressed as mean absolute error. A model including curvilinear effects of feed volume and the impact of manual feed pushing was used on a dataset including daily time points. When cross-validating, the inclusion of a curvilinear effect and a feed push effect did not improve the accuracy of the model for neither the feed pile nor the feed removed by the cow between consecutive time points. In conclusion, measuring daily feed intake from this 3D camera system in the present experimental setup could be accomplished with an acceptable error (below 8%), but the system should be improved for individual meal intake measurements if these measures were to be implemented.

Review: Environmental enrichment builds functional capacity and improves resilience as an aspect of positive welfare in production animals

The success of the animal in coping with challenges, and in harnessing opportunities to thrive, is central to its welfare. Functional capacity describes the capacity of molecules, cells, organs, body systems, the whole animal, and its community to buffer against the impacts of environmental perturbations. This buffering capacity determines the ability of the animal to maintain or regain functions in the face of environmental perturbations, which is recognised as resilience. The accuracy of physiological regulation and the maintenance of homeostatic balance underwrite the dynamic stability of outcomes such as biorhythms, feed intake, growth, milk yield, and egg production justifying their assessment as indicators of resilience. This narrative review examines the influence of environmental enrichments, especially during developmental stages in young animals, in building functional capacity and in its subsequent expression as resilience. Experience of enriched environments can build skills and competencies across multiple functional domains including but not limited to behaviour, immunity, and metabolism thereby increasing functional capacity and facilitating resilience within the context of challenges such as husbandry practices, social change, and infection. A quantitative method for measuring the distributed property of functional capacity may improve its assessment. Methods for analysing embedded energy (emergy) in ecosystems may have utility for this goal. We suggest functional capacity provides the common thread that links environmental enrichments with an ability to express resilience and may provide a novel and useful framework for measuring and reporting resilience. We conclude that the development of functional capacity and its subsequent expression as resilience is an aspect of positive animal welfare. The emergence of resilience from system dynamics highlights a need to shift from the study of physical and mental states to the study of physical and mental dynamics to describe the positive dimension of animal welfare.

Gut-brain bidirectional determination in regulating the residual feed intake of small-sized meat ducks

The gut-brain axis is essential in maintaining the homeostasis of neuronal system, endocrine system, and intestinal microbiota in both the afferent and efferent directions. This axis is considered to be a key mechanism that regulates feed efficiency (FE). This study aimed to investigate the regulatory mechanisms of gut-brain axis-related genes on the residual feed intake (RFI) in H-strain small-sized meat ducks. A total of 500 ducks with similar initial BW (635.2 ± 15.1 g) were selected and reared in the same experimental facility until slaughter at 42 d of age. RFI was calculated from the average daily gain (ADG), average daily feed intake (ADFI), and metabolic body weight (MBW0.75). Thirty high-RFI (H-RFI) and 30 low-RFI (L-RFI) birds were selected for further evaluation of growth performance, carcass characteristics, and blood biochemical parameter measurements. Six L-RFI and 6 H-RFI birds were then subjected to hypothalamic transcriptomic and cecal microbial sequencing analyses. Results indicated that L-RFI birds exhibited lower production performance (ADFI, FCR, and RFI) and blood biochemical indices (total cholesterol and ghrelin content) compared with H-RFI birds (P < 0.05). Gene expression differed significantly between the L-RFI and H-RFI birds, with 70 upregulated and 50 downregulated genes. The bacterial communities of L-RFI birds showed higher abundances of Bacteroides, Bifidobacterium, and Lactococcus, and lower abundances of Erysipelatoclostridium, Parasutterella, Fournierella, and Blautia compared with H-RFI birds (P < 0.05). Interactive analysis revealed bacterial communities associated with FE were significantly correlated with hypothalamic genes (P < 0.05), for example, Bacteroides was positively correlated with DGKH and LIPT2, while negatively correlated with CAPN9, GABRD, and PDE1A. Bifidobacterium showed significant correlations with ATP2A3, CALHM6, and TMEM121B. Overall, RFI was a crucial indicator of FE, regulated by interactions between brain gene expression and gut microbiota through cAMP signaling, neuroactive ligand-receptor interaction, and calcium signaling pathways. Notably, increased expression of hypothalamic genes and abundance of carbohydrate-utilization microbiota in L-RFI meat ducks improved FE by enhancing energy metabolism and volatile fatty acids absorption.

Changes in the physiological, hematological and parasitological parameters of Dorper sheep in relation to residual feed intake and confinement environment

The selection of animals with greater feed efficiency has unknown parasitological and physiological parameters when confined in full sun or shade. Thus, we aimed to assess the effect of residual feed intake (RFI) and the confinement environment on the hematological, parasitological and physiological parameters in male Dorper sheep (n = 60; 30 with positive RFI and 30 with negative RFI) distributed in 2 confinement environments (full sun and shade), in a 2 × 2 factorial scheme, with 15 animals for treatment. Animals kept in the shade showed an increase (P < 0.05) of erythrocytes, hemoglobin and albumin. Animals kept in full sun showed higherOocysts gamma glutamyltransferase, direct bilirubin, transaminase aspartate and respiratory rate (P<0.05). There was a higher incidence of Eimeria spp oocysts in RFI negative animals (P<0.05). Positive RFI animals increased respiratory rate (P<0.05). The RFI did not influence the blood parameters of Dorper sheep, however, it had an effect on respiratory rate and presence of Eimeria spp. oocysts. Thermal environment promoted changes in blood parameters and the physiological parameters of Dorper sheep.

Combined mechanistic and genetic modelling to benchmark body reserve traits as proxies of dairy cows' lifetime efficiency in grass-based production systems

Improving lifetime lactation efficiency of dairy cows by selection is difficult due to the complexity of this trait and the existence of genotype-by-environment interactions. This study aimed at assessing the relevance of traits derived from body reserves as lifetime efficiency indicators under contrasting nutritional environments. Given the absence of large-scale datasets covering a panel of feeding regimes, phenotypes were simulated for populations of 20 000 dairy cows using a mechanistic bioenergetic model. Ten phenotypes were computed for third-lactation cows. Analysed phenotypes comprised total milk production, lactation efficiency, BW at calving (BWcalv), DM intake (DMI) and interval between first insemination and conception. Five traits described levels and changes of body reserves at different periods during lactation. Lifetime lactation efficiency was computed for all cows (Life_Eff). Three nutritional environments were defined considering a grass-based production system with seasonal calving: a high non-limiting scenario (HS) mimicking ad libitum access to feed and two limiting environments with moderate (MS) and low (LS) feed offer. Variance components were estimated for all traits within and between environments using REML. Heritabilities estimated for milk production, lactation efficiency, BWcalv and DMI were moderate in the different environments (0.27-0.35 ± 0.04). The heritability of body reserve levels and dynamics were moderate in the HS and MS scenarios (0.23-0.30 ± 0.03) and lower in the LS scenario (0.14-0.25 ± 0.03). The heritability of Life_Eff was low in the HS environment (0.07 ± 0.01) and slightly increased in the limiting environments. All genetic correlations estimated between environments were moderate to high (≥0.66 ± 0.07), suggesting low to moderate genotype-by-environment interactions. Estimated genetic correlations were moderate between Life_Eff and body reserve levels (from 0.39 to 0.51 ± 0.08) and moderate but negative between Life_Eff and change in body reserves traits (-0.27 to -0.37 ± 0.09) in the HS environment. The genetic correlations between Life_Eff and body reserve levels increased to higher values in the limiting environments. In contrast, genetic correlations between Life_Eff and the changes in body reserves were closer to zero. In conclusion, this study showed that body reserve levels were relevant proxies of lifetime irrespective of the environment. In contrast, changes in body reserves that reflected energy mobilisation in early lactation were less informative about lifetime efficiency in environments with severe feed restrictions.

Estimating breeding values for feed efficiency in dairy cattle by regression on expected feed intake

The efficiency with which a dairy cow utilises feed for the various physiological and metabolic processes can be evaluated by metrics that contrast realised feed intake with expected feed intake. In this study, we presented a new metric - regression on expected feed intake (ReFI). This metric is based on the idea of regressing DM intake (DMI) on expected DMI using a random regression model, where energy requirement formulations are applied for the calculation of expected DMI covariables. We compared this new metric with the metrics residual feed intake (RFI) and genetic residual feed intake (gRFI), by applying them on 18 581 feed efficiency records from 654 primiparous Nordic Red dairy cows. We estimated variance components for the three metrics and their respective genetic correlations with intake and production traits. In addition, we examined the phenotypes of superior cows. With ReFI, we estimated for feed efficiency a higher genetic variation (4.7%) and heritability (0.23) compared to applying RFI or gRFI. The ReFI metric was genetically uncorrelated with DMI and negatively correlated within energy-corrected milk (ECM), whereas the RFI metric was genetically positively correlated with DMI and metabolic BW. The gRFI metric was genetically positively correlated with DMI and uncorrelated with energy sink traits. Overall, the estimated SE were large. The ReFI metric resulted in a different ranking of cows compared to those based on RFI or gRFI and was superior in selecting the most efficient animals. When the selection was based on ReFI breeding values, then the 10% most efficient cows produced 12.3% more ECM per unit metabolisable energy intake, whereas the corresponding values were only 4.3 or 5.9% when using RFI or gRFI breeding values, respectively. Based on ReFI, superior cows had also higher milk production, whereas based on RFI or gRFI milk production either decreased or was unaffected, respectively. The superiority of the ReFI metric in selecting efficient cows was due to a better modelling of the expected feed intake. The ReFI metric simplified modelling of feed utilisation efficiency in dairy cattle and resulted in breeding values that are equal to percentages of feed saved.

Growth performance, carcass traits, meat quality, and blood variables of small-sized meat ducks with different feed efficiency phenotypes

The study investigated the effects of feed efficiency (residual feed intake, RFI and residual intake and gain, RIG) on the production performance of small-sized meat ducks. Ninety ducks with intermediate and extreme (high and low) RFI values were selected from 1,083 male ducks of similar body weight, and the 3 groups were then redivided according to RIG. For both efficiency measures, the feed conversion ratio (FCR) and average daily feed intake (ADFI) of efficient ducks were significantly lower than those of inefficient ducks (P < 0.05), while the residual body weight gain (RG) was significantly higher in efficient ducks (P < 0.05). Inefficient-RFI animals showed greater skin fat yield (P < 0.05), but no other differences in carcass traits were observed (P > 0.05). RIG had positive effects on the pH1 value of the breast muscle (P < 0.05), but feed efficiency did not affect the other meat quality traits (P > 0.05). With regard to blood biochemical parameters, efficient ducks had significantly lower triglycerides (TG) (P < 0.05). Correlation analysis demonstrated that RFI was positively correlated with average daily feed intake and feed conversion ratio (P < 0.05), while RIG exhibited a strong negative correlation with both (P < 0.05). The average daily body weight gain was positively correlated with RIG (P < 0.05). RIG had a positive effect on the pH1 value of the breast muscle (P < 0.05). Furthermore, triglyceride and high-density lipoprotein cholesterol levels correlated with both efficiency classifications (P < 0.05). Overall, the efficiency measures did not affect the carcass and meat quality of small-sized meat ducks but could identify ducks with lower feed consumption and fast growth.

On-farm evaluation of models to predict herbage intake of dairy cows grazing temperate semi-natural grasslands

The objective of the present on-farm study was to evaluate the adequacy of existing models in predicting the pasture herbage DM intake (PDMI) of lactating dairy cows grazing semi-natural grasslands. The prediction adequacy of 13 empirical and semi-mechanistic models, which were predominantly developed to represent stall-fed cows or cows grazing high-quality pastures, were evaluated using the mean bias, relative prediction error (RPE), and partitioning of mean square error of prediction, where models with an RPE ≤ 20% were considered adequate. The reference dataset comprised n = 233 individual animal observations from nine commercial farms in South Germany with a mean milk production, DM intake, and PDMI (arithmetic means ± one SD) of 24 kg/d, (±5.6), 21 kg/d (±3.2), and 12 kg/d (±5.1), respectively. Despite their adaptation to grazing conditions, the behaviour-based and semi-mechanistic grazing-based models had the lowest prediction adequacy among the evaluated models. Their underlying empirical equations likely did not fit the grazing and production conditions of low-input farms using semi-natural grasslands for grazing. The semi-mechanistic stall-based model Mertens II with slight modifications achieved the highest and a satisfactory modelling performance (RPE = 13.4%) when evaluated based on the mean observed PDMI, i.e., averaged across animals per farm and period (n = 28). It also allowed for the adequate prediction of PDMI on individual cows (RPE = 18.5%) that were fed < 4.8 kg DM of supplement feed per day. Nevertheless, when used to predict PDMI of individual animals receiving a high supplementation level, the model Mertens II also did not meet the threshold for an acceptable adequacy (RPE = 24.7%). It was concluded that this lack of prediction adequacy for animals receiving greater levels of supplementation was due to a lack of modelling precision, which mainly could be related to inter-animal and methodological limitations such as the lack of individually measured supplement feed intake for some cows. The latter limitation is a trade-off of the on-farm research approach of the present study, which was chosen to represent the range in feed intake of dairy cows across the diverse low-input farming systems using semi-natural grasslands for grazing.

Genomic prediction ability and genetic parameters for residual feed intake calculated using different approaches and their associations with growth, reproductive, and carcass traits in Nellore cattle

This study aimed to estimate prediction ability and genetic parameters for residual feed intake (RFI) calculated using a regression equation for each test (RFI_test) and for the whole population (RFI_pop) in Nellore beef cattle. It also aimed to evaluate the correlations between RFI_pop and RFI_test with growth, reproductive, and carcass traits. Genotypic and phenotypic records from 8354 animals were used. An analysis of variance (ANOVA) was performed to verify the adequacy of the regression equations applied to estimate the RFI_test and RFI_pop. The (co)variance components were obtained using the single-step genomic best linear unbiased prediction under single and two-trait animal model analyses. The genetic and phenotypic correlations between RFI_test and RFI_pop with dry matter intake, frame, growth, reproduction, and carcass-related traits were evaluated. The prediction ability and bias were estimated to compare the RFI_test and RFI_pop genomic breeding values (GEBV). The RFI_pop ANOVA showed a higher significance level (p < 0.0001) than did the RFI_test for the fixed effects. The RFI_pop displayed higher additive genetic variance estimated than the RFI_test, although the RFI_pop and RFI_test displayed similar heritabilities. Overall, the RFI_test showed higher residual correlations with growth, reproductive, and carcass traits, while the RFI_pop displayed higher genetic correlations with such traits. The GEBV for the RFI_test was slightly biased than GEBV RFI_pop. The approach to calculate the RFI influenced the decomposition and estimation of variance components and genomic prediction for RFI. The application of RFI_pop would be more appropriate for genetic evaluation purpose to adjust or correct for non-genetic effects and to decrease the prediction bias for RFI.

An evaluation of detailed animal characteristics influencing the lactation production efficiency of spring-calving, pasture-based dairy cattle

Selection for feed efficiency, the ratio of output (e.g., milk yield) to feed intake, has traditionally been limited on commercial dairy farms by the necessity for detailed individual animal intake and performance data within large animal populations. The objective of the experiment was to evaluate the effects of individual animal characteristics (animal breed, genetic potential, milk production, body weight (BW), daily total dry matter intake (TDMI), and energy balance) on a cost-effective production efficiency parameter calculated as the annual fat and protein (milk solids) production per unit of mid-lactation BW (MSperBW_lact). A total of 1,788 individual animal intake records measured at various stages of lactation (early, mid, and late lactation) from 207 Holstein-Friesian and 200 Jersey × Holstein-Friesian cows were used. The derived efficiency traits included daily kilograms of milk solids produced per 100 kg of BW (dMSperBW_int) and daily kilograms of milk solids produced per kilogram of TDMI (dMSperTDMI). The TDMI per 100 kg of BW was also calculated (TDMI/BW_int) at each stage of lactation. Animals were subsequently either ranked as the top 25% (Heff) or bottom 25% (Leff) based on their lactation production efficiency (MSperBW_lact). Dairy cow breed significantly affected animal characteristics over the entire lactation and during specific periods of intake measurements. Jersey crossbred animals produced more milk, based on a lower TDMI, and achieved an increased intake per kilogram of BW. Similarly, Heff produced more milk over longer lactations, weighed less, were older, and achieved a higher TDMI compared with the Leff animals. Both Jersey × Holstein-Friesian and Heff cows achieved superior production efficiency due to lower maintenance energy requirements, and consequentially increased milk solids production per kilogram of BW and per kilogram of TDMI at all stages of lactation. Indeed, within breed, Heff animals weighed 20 kg less and produced 15% more milk solids over the total lactation than Leff. In addition, Heff achieved increased daily milk solids yield (+0.16 kg) and milk solids yield per kilogram of TDMI (+ 0.23 kg/kg DM) during intake measurement periods. Moreover, the strong and consistently positive correlations between MSperBW_lact and detailed production efficiency traits (dMSperBW_int, dMSperTDMI) reported here demonstrate that MSperBW_lact is a robust measure that can be applied within commercial grazing dairy systems to increase the selection intensity for highly efficient animals.

Transcriptome Profiling of the Liver in Nellore Cattle Phenotypically Divergent for RFI in Two Genetic Groups

The identification and selection of genetically superior animals for residual feed intake (RFI) could enhance productivity and minimize environmental impacts. The aim of this study was to use RNA-seq data to identify the differentially expressed genes (DEGs), known non-coding RNAs (ncRNAs), specific biomarkers and enriched biological processes associated with RFI of the liver in Nellore cattle in two genetic groups. In genetic group 1 (G1), 24 extreme RFI animals (12 low RFI (LRFI) versus 12 high RFI (HRFI)) were selected from a population of 60 Nellore bulls. The RNA-seq of the samples from their liver tissues was performed using an Illumina HiSeq 2000. In genetic group 2 (G2), 20 samples of liver tissue of Nellore bulls divergent for RFI (LRFI, n = 10 versus HRFI, n = 10) were selected from 83 animals. The raw data of the G2 were chosen from the ENA repository. A total of 1811 DEGs were found for the G1 and 2054 for the G2 (p-value ≤ 0.05). We detected 88 common genes in both genetic groups, of which 33 were involved in the immune response and in blocking oxidative stress. In addition, seven (B2M, ADSS, SNX2, TUBA4A, ARHGAP18, MECR, and ABCF3) possible gene biomarkers were identified through a receiver operating characteristic analysis (ROC) considering an AUC > 0.70. The B2M gene was overexpressed in the LRFI group. This gene regulates the lipid metabolism protein turnover and inhibits cell death. We also found non-coding RNAs in both groups. MIR25 was up-regulated and SNORD16 was down-regulated in the LRFI for G1. For G2, up-regulated RNase_MRP and SCARNA10 were found. We highlight MIR25 as being able to act by blocking cytotoxicity and oxidative stress and RMRP as a blocker of mitochondrial damage. The biological pathways associated with RFI of the liver in Nellore cattle in the two genetic groups were for energy metabolism, protein turnover, redox homeostasis and the immune response. The common transcripts, biomarkers and metabolic pathways found in the two genetic groups make this unprecedented work even more relevant, since the results are valid for different herds raised in different ways. The results reinforce the biological importance of these known processes but also reveal new insights into the complexity of the liver tissue transcriptome of Nellore cattle.

Metagenomic insights into the relationship between gut microbiota and residual feed intake of small-sized meat ducks

Introduction

The objective of this study was to determine the regulatory effects of gut microbiota on the feed efficiency (FE) of small-sized meat ducks by evaluating correlations between gut microbiota and residual feed intake (RFI).

Methods

A total of 500 21-day-old healthy male ducks with similar initial body weights (645 ± 15.0 g) were raised contemporaneously in the same experimental facility until slaughter at 56 days of age. In total, nine low-RFI (LR) and nine high-RFI (HR) birds were selected for further gut microbiota composition and functional analyses based on the production performance, and the RFI was calculated from 22 to 56 days of age.

Results

Growth performance results indicated a significantly lower RFI, feed conversion ratio, feed intake, and average daily feed intake in the LR ducks (P < 0.05). Taxonomy results of gut microbiota showed the identification of 19 kinds of phyla and more than 250 kinds of genera in all samples. No significant discrepancies in cecal bacterial α-diversity were discovered between the LR and HR groups, which indicated that the microbial modulatory effects on RFI may be attributed to the bacterial composition, rather than the species diversity. Differential analysis of bacterial communities between the LR and HR groups showed a significant increment of Firmicutes and a significant decline of Bacteroidetes in the LR group (P < 0.05). Specifically, genera of Erysipelatoclostridium, Parasutterella, Fournierella, and Lactococcus significantly proliferated, while Bacteroides significantly decreased in the LR group (P < 0.05). Furthermore, correlation analysis showed that the RFI was significantly correlated with carbohydrate metabolism-related bacteria including Bacteroides, Alistipes, Bifidobacterium, Ruminiclostridium_9, Sellimonas, Oscillibacter, Escherichia-Shigella, Lactococcus, and Streptococcus.

Conclusion

In conclusion, the communities related to carbohydrate metabolism had positive regulatory effects on the FE of small-sized meat ducks, promoting it by improving the relative abundance and utilization of these communities. The present study provides valuable insight into the dynamics of gut microbiota underlying the variations in the FE of small-sized meat ducks.

Observational study on associations between resilience indicators based on daily milk yield in first lactation and lifetime profitability

Resilience is the ability of cows to be minimally affected by disturbances, such as pathogens, heat waves, and changes in feed quality, or to quickly recover. Obvious advantages of resilience are good animal welfare and easy and pleasant management for farmers. Furthermore, economic effects are also expected, but these remain to be determined. The goal of this study was to investigate the association between resilience and lifetime gross margin, using indicators of resilience calculated from fluctuations in daily milk yield using an observational study. Resilience indicators and lifetime gross margin were calculated for 1,325 cows from 21 herds. These cows were not alive anymore and, therefore, had complete lifetime data available for many traits. The resilience indicators were the natural log-transformed variance (LnVar) and the lag-1 autocorrelation (r_auto) of daily milk yield deviations from cow-specific lactation curves in parity 1. Good resilience is indicated by low LnVar (small yield response to disturbances) and low r_auto (quick yield recovery to baseline). Lifetime gross margin was calculated as the sum of all revenues minus the sum of all costs throughout life. Included revenues were from milk, calf value, and slaughter of the cow. Included costs were from feed, rearing, insemination, management around calving, disease treatments, and destruction in case of death on farm. Feed intake was unknown and, therefore, lifetime feed costs had to be estimated based on milk yield records. The association of each resilience indicator with lifetime gross margin, and also with the underlying revenues and costs, was investigated using analysis of covariance (ANCOVA) models. Mean daily milk yield in first lactation, herd, and year of birth were included as covariates and factors. Natural log-transformed variance had a significantly negative association with lifetime gross margin, which means that cows with stable milk yield (low LnVar, good resilience) in parity 1 generated on average a higher lifetime gross margin than cows that had the same milk yield level but with more fluctuations. The association with lifetime gross margin could be mainly attributed to higher lifetime milk revenues for cows with low LnVar, due to a longer lifespan. Unlike LnVar, r_auto was not significantly associated with lifetime gross margin or any of the underlying lifetime costs and revenues. However, it was significantly associated with yearly treatment costs, which is important for ease of management. In conclusion, the importance of resilience for total profit generated by a cow at the end of life was confirmed by the significant association of LnVar with lifetime gross margin, although effects of differences in feed efficiency between resilient and less resilient cows remain to be studied. The economic advantage can be mainly ascribed to benefits of long lifespan.

CNV detection and their association with growth, efficiency and carcass traits in Santa Inês sheep

Copy number variations (CNV) are an important source of genetic variation. CNV has been increasingly studied and frequently associated with diseases and productive traits in livestock animals. However, CNV-based genome-wide association studies (GWAS) in Santa Inês sheep, one of the principal sheep breeds in Brazil, have not yet been reported. Thus, the aim of this study was to investigate the association between CNV and growth, efficiency and carcass traits in sheep. The Illumina OvineSNP50 BeadChip array was used to detect CNV in 491 Santa Inês individuals. Then, CNV-based GWAS was performed with a linear mixed model approach considering a genomic relationship matrix, for ten traits: (1) growth: body weight at three (W3) and six (W6) months of age; (2) efficiency: residual feed intake (RFI) and feed efficiency (FE) and (3) carcass: external carcass length (ECL), leg length (LL), carcass yield (CY), commercial cuts weight (CCW), loin eye area (LEA) and subcutaneous fat thickness (SFT). We identified 1,167 autosomal CNV in 438 sheep, with 294 non-redundant CNV, ranging from 21.8 to 861.9 kb, merged into 216 distinct copy number variation regions (CNVRs). One significant CNV segment (p_FDR -value<0.05) in OAR3 was associated with CY, while another significant CNV in OAR6 was associated with RFI. Additionally, another 5 CNV segments were considered relevant for investigation in the future studies. The significant segments overlapped 4 QTLs and spanned 8 genes, including the SPAST, TGFA and ADGRL3 genes, involved in cell differentiation and energy metabolism. Therefore, the results of the present study increase knowledge about CNV in sheep, their possible impacts on productive traits, and provide information for future investigations, being especially useful for those interested in structural variations in the sheep genome.

Individual Feed Efficiency Monitoring of Charolaise Candidate Young Bulls in Relation to Feeding Behavior and Self-Performance Test Results

This study evaluated the effect of differences in residual feed intake (RFI) of Charolaise candidate young bulls on feeding behavior and self-performance test results. Bulls were classified into high and low RFI (H-RFI, L-RFI) groups. Bulls were fed in a HOKOFARM system to measure individual animal intake and behavior. L-RFI bulls had significantly lower feed intakes (p = 0.002) and higher gain to feed ratio (p = 0.001), lower intake per day/kg DM (dry matter) (p = 0.002) and lower intake g/body weight/day (p < 0.001). L-RFI animals had lower visits number per day (p = 0.02), but spent longer time per visit (p = 0.02), and tended to have higher intake g/visit (p = 0.06) on feeders. The correlation between RFI and DMI (dry matter intake)/bodyweight/day as well as intake per day/kg were large and positive. Back-loin length and rump length, and moreover muzzle width and frame, showed negative correlations with RFI value. However, bulls with better RFI values associated with lower legs score. Results reveal that RFI was shown beneficial correlations with economically relevant self-performance traits. Further investigations are needed to seek additional indicator traits that are predictive for RFI.

Combining datasets in a dynamic residual feed intake model and comparison with linear model results in lactating Holstein cattle

A new method to estimate residual feed intake (RFI) was recently developed based on a multi-trait random regression model. This approach deals with the dynamic nature of the lactation, which is in contrast with classical linear approaches. However, an issue remains: pooling data across sites and years, which implies dealing with different (and sometimes unknown) diet energy contents. This will be needed for genomic evaluation. In this study, we tested whether merging two individual datasets into a larger one can lead to valuable results in comparison to analysing them on their own with the multi-trait random regression model. Three datasets were defined: the first one with 1 063 lactations, the second one with 205 lactations from a second farm and the third one combining the data of the two first datasets (1 268 lactations). The model was applied to the three datasets to estimate individual RFI as well as variance components and correlations between the four traits included in the model (fat and protein corrected milk production, BW, feed intake and body condition score), and a fixed month-year-farm effect was used to define the contemporary group. The variance components and correlations between animal effects of the four traits were very similar irrespective of the dataset used with correlations higher than 0.94 between the different datasets. The RFI estimates for animals from their single farm only were also very similar (r > 0.95) to the ones computed from the merged dataset (Dataset 3). This highlights that the contemporary group correction in the model adequately accounts for differences between the two feeding environments. The dynamic model can thus be used to produce RFI estimates from merged datasets, at least when animals are raised in similar systems. In addition, the 205 lactations from the second farm were also used to estimate the RFI with a linear approach. The RFI estimated by the two approaches were similar when the considered period was rather short (r = 0.85 for RFI for the first 84 days of lactation) but this correlation weakened as the period length grew (r = 0.77 for RFI for the first 168 days of lactation). This weakening in correlations between the two approaches when increasing the used time-period reflects that only the dynamic model permits the regression coefficients to evolve in line with the physiological changes through the lactation. The results of this study enlarge the possibilities of use for the dynamic RFI model.

An alternative interpretation of residual feed intake by phenotypic recursive relationships in dairy cattle

There has been increasing interest in residual feed intake (RFI) as a measure of net feed efficiency in dairy cattle. Residual feed intake phenotypes are obtained as residuals from linear regression encompassing relevant factors (i.e., energy sinks) to account for body tissue mobilization. By rearranging the single-trait linear regression, we showed a causal RFI interpretation underlying the linear regression for RFI. It postulates recursive effects in energy allocation from energy sinks on dry matter intake, but the feedback or simultaneous effects are nonexistent. A Bayesian recursive structural equation model was proposed for directly predicting RFI and energy sinks and estimating relevant genetic parameters simultaneously. A simplified Markov chain Monte Carlo algorithm was described. The recursive model is asymptotically equivalent to one-step linear regression for RFI, yet extends the analytical capacity to multiple-trait analysis.