The aims of this study were to estimate the genetic parameters for leg and foot health and mobility in purebred turkey lines and their genetic correlations with BW. Traits were gait score (GS) as an overall measure of leg health, footpad dermatitis (FPD), and 2 skeletal leg health traits, namely, valgus and varus deformities (VVD) and tibial dyschondroplasia (TD). Data from 4 different lines, comprising 3 yr of phenotypic records and 4 yr of pedigree information per line, were used. The sex average BW for the lines at 18 wk ranged from 19.1 kg (line A) to 12.4 kg (line D). The prevalence of VVD ranged from 5.2 to 14.6% and for TD from 4.1 to 23.2%. The average score for FPD on a scale of 0 to 100 ranged from 48.5 to 61.1. Gait Score was scored on a scale of 1 to 5, standardized to a mean of 3 and SD of 1. Heritabilities were estimated at 0.08 to 0.13 for GS, 0.01 to 0.07 for VVD, 0.06 to 0.12 for TD, and 0.10 to 0.15 for FPD (all SE ≤ 0.02). Estimates of the genetic correlations between VVD and TD ranged from 0.03 to 0.21 (all SE ≤ 0.08), and estimates of these with GS ranged from 0.07 to 0.87 (all SE ≤ 0.09). The genetic correlations of FPD with GS ranged from 0.00 to 0.34 (all SE ≤ 0.04), and with the skeletal leg health traits from -0.06 to 0.33 (all SE ≤ 0.06). Body weight showed estimated genetic correlations ranging from 0.28 to 0.51 (all SE ≤ 0.06) with GS, -0.06 to 0.50 (all SE ≤ 0.13) with VVD/TD and 0.05 to 0.34 (all SE ≤ 0.05) with FPD. The results suggest that selection for improved leg health can be incorporated effectively in a commercial turkey breeding program using balanced breeding goals, in which production traits and leg health traits are considered simultaneously.

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The regulation of the drinking behavior of animals is usually overlooked, and the traits associated with it are not well defined. We used a unique data set of measurements of individual drinking behavior in turkeys 1) to validate the system of data generation, 2) to develop a methodology to allow clustering of drinking events and splitting behavior into bouts, and 3) to develop traits related to drinking behavior and its regulation and investigate how these traits may be affected by bird genotype. Visits to drinkers were generated by an electronic, custom-made equipment that automatically measures the individual drinking behavior of a large number of turkeys from 3 different genetic lines. The overall reliability of the electronic system was estimated from video observations and resulted in a predictability of 98.8% and sensitivity of 98.6%. A novel method based on mixture distribution models allowed clustering of drinking events and splitting behavior into bouts by estimating the shortest interval between visits to the drinker that was considered to be part of a bout (bout criterion). The method predicted that after the end of a given bout the probability of the bird initiating the next bout was low but increased with time since the last bout. As a result, drinking bouts were not randomly distributed but were predicated on the physiological principle of satiety, suggesting that they constitute biologically appropriate units for expressing drinking behavior. The applied method resulted in bout criteria estimates of 665, 672, and 602 s for genetic lines A, B, and C, respectively. On the basis of this methodology, a number of drinking behavior traits, such as bout duration and frequency, and water intake per bout were identified that revealed differences ( < 0.01) in the drinking behavior between the turkey genetic lines. Similarly, time accumulation patterns of drinking behavior traits within a day differed ( < 0.01) within and between genetic lines, suggesting that variation in drinking behavior exists and birds use different behavioral strategies to meet their water intake requirements. Development of drinking behavior over time was similar between the lines, suggesting conservation of this behavioral organization. As well as providing ideas about the regulation of drinking behavior, the developed behavioral traits may be of practical relevance because water utilization, along with feed efficiency, is part of overall biological efficiency.

BackgroundOptimal contributions selection (OCS) provides animal breeders with a framework for maximising genetic gain for a predefined rate of inbreeding. Simulation studies have indicated that the source of the selective advantage of OCS is derived from breeding decisions being more closely aligned with estimates of Mendelian sampling terms () of selection candidates, rather than estimated breeding values (EBV). This study represents the first attempt to assess the source of the selective advantage provided by OCS using a commercial pig population and by testing three hypotheses: (1) OCS places more emphasis on compared to EBV for determining which animals were selected as parents, (2) OCS places more emphasis on compared to EBV for determining which of those parents were selected to make a long-term genetic contribution (r), and (3) OCS places more emphasis on compared to EBV for determining the magnitude of r. The population studied also provided an opportunity to investigate the convergence of r over time.ResultsSelection intensity limited the number of males available for analysis, but females provided some evidence that the selective advantage derived from applying an OCS algorithm resulted from greater weighting being placed on during the process of decision-making. Male r were found to converge initially at a faster rate than female r, with approximately 90% convergence achieved within seven generations across both sexes.ConclusionsThis study of commercial data provides some support to results from theoretical and simulation studies that the source of selective advantage from OCS comes from . The implication that genomic selection (GS) improves estimation of should allow for even greater genetic gains for a predefined rate of inbreeding, once the synergistic benefits of combining OCS and GS are realised.Electronic supplementary materialThe online version of this article (10.1186/s12711-018-0392-z) contains supplementary material, which is available to authorized users.

BackgroundThere is increasing interest in the definition, measurement and use of traits associated with water use and drinking behaviour, mainly because water is a finite resource and its intake is an important part of animal health and well-being. Analysis of such traits has received little attention, due in part to the lack of appropriate technology to measure drinking behaviour. We exploited novel equipment to collect water intake data in two lines of turkey (A: 27,415 and B: 12,956 birds). The equipment allowed continuous recording of individual visits to the water station in a group environment. Our aim was to identify drinking behaviour traits of biological relevance, to estimate their genetic parameters and their genetic relationships with performance traits, and to identify drinking behaviour strategies among individuals.ResultsVisits to the drinkers were clustered into bouts, i.e. time intervals spent in drinking-related activity. Based on this, biologically relevant traits were defined: (1) number of visits per bout, (2) water intake per bout, (3) drinking time per bout, (4) drinking rate, (5) daily bout frequency, (6) daily bout duration, (7) daily drinking time and (8) daily water intake. Heritability estimates for most drinking behaviour traits were moderate to high and the most highly heritable traits were drinking rate (0.49 and 0.50) and daily drinking time (0.35 and 0.46 in lines A and B, respectively). Genetic correlations between drinking behaviour and performance traits were low except for moderate correlations between daily water intake and weight gain (0.46 and 0.47 in lines A and B, respectively). High estimates of breeding values for weight gain were found across the whole range of estimated breeding values for daily water intake, daily drinking time and water intake per bout.ConclusionsWe show for the first time that drinking behaviour traits are moderately to highly heritable. Low genetic and phenotypic correlations with performance traits suggest that current breeding goals have not and will not affect normal water drinking behaviour. Birds express a wide range of different drinking behaviour strategies, which can be suitable to a wide range of environments and production systems.