Farmers' Perceptions About Health and Welfare Issues in Turkey Production

The usual suspects: Co-occurrence of integument injuries in turkey flocks

The present study investigated the prevalence and co-occurrence of integument injuries in Canadian turkeys. Participating farmers scored 30 birds in their flock for integument injuries to the head/neck (HN), back/tail (BT), and footpad (FP) using a simplified scoring system (0: no sign of injury, 1: mild injury, 2: severe injury). Information from 62 flocks was used to calculate the prevalence of any (score ≥1) and severe (score 2) injuries on a flock- and individual-level. Chi-square analyses were performed to determine the likelihood of integument injury co-occurrence. The prevalence of each type of injury varied between flocks. While the majority of flocks reported injuries, the within-flock prevalence was relatively low and largely comprised of mild cases (score 1). Given their higher prevalence, the data indicate that FP injuries are overall more widespread and more severe among Canadian turkey flocks than HN and BT injuries. Co-occurrence of different integument injuries was observed in 7% of birds and 58.1% of flocks reported at least one bird with co-occurring injury types. Despite the low prevalence of multiple injury types, birds with one type of injury were more likely to present with other injury types. Indeed, birds with HN injuries were 4 times more likely to have BT injuries, and birds with FP injuries were 1.5 times more likely to have BT injuries compared to birds that do not have these respective injuries. The data increase our understanding of the co-occurrence of these common integument injuries which can help inform a holistic management approach to rear turkeys with healthy skin and feather cover.

Accuracy of genomic selection for reducing susceptibility to pendulous crop in turkey (Meleagris gallopavo)

Pendulous crop (PC) in the turkey occurs when the crop distends from its normal position, thereby preventing the movement of feed and water from the crop down into the digestive system. This condition negatively impacts the turkey industry at both production and welfare levels. In this study, we estimated the genetic parameters for PC incidence and its genetic correlation with 5 production traits. Additionally, we evaluated the prediction accuracy and bias of breeding values for the selection candidates using pedigree (BLUP) or pedigree-genomic (ssGBLUP) relationships among the animals. A total of 245,783 turkey records were made available by Hybrid Turkeys, Kitchener, Canada. Of these, 6,545 were affected with PC. In addition, the data included 9,634 records for breast meat yield (BMY); 5,592 records for feed conversion ratio (FCR) and residual feed intake (RFI) in males; 170,844 records for body weight (BW) and walking score (WS) between 18 and 20 wk of age for males (71,012) and females (99,832), respectively. Among this population, 36,830 were genotyped using a 65K SNP Illumina Inc. chip. While all animals passed the quality control criteria, only 53,455 SNP markers were retained for subsequent analysis. Heritability for PC was estimated at 0.16 ± 0.00 and 0.17 ± 0.00 using BLUP and ssGBLUP, respectively. The incidence of PC was not genetically correlated with WS or FCR. Low unfavourable genetic correlations with BW (0.12 and 0.14), BMY (0.24 and 0.24) and RFI (-0.33 and -0.28) were obtained using BLUP and ssGBLUP, respectively. Using ssGBLUP showed higher prediction accuracy (0.51) for the breeding values for the selection candidates than the pedigree-based model (0.35). Whereas the bias of the prediction was slightly reduced with ssGBLUP (0.33 ± 0.05) than BLUP (0.30 ± 0.08), both models showed a regression coefficient lower than one, indicating inflation in the predictions. The results of this study suggest that PC is a heritable trait and selection for lower PC incidence rates is feasible. Although further investigation is necessary, selection for BW, BMY, and RFI may increase PC incidence. Incorporating genomic information would lead to higher accuracy in predicting the genetic merit for selection candidates.

The Prevalence of Integument Injuries and Associated Risk Factors Among Canadian Turkeys

Injurious pecking can cause a wide range of damage and is an important welfare and economic issue in turkey production. Aggressive pecking typically targets the head/neck (HN) area, and feather pecking typically targets the back/tail (BT) area; injuries in these separate areas could be used as a proxy for the level of aggressive and feather pecking in a flock. The objective of this study was to identify risk factors for integument injuries in Canadian turkey flocks. A survey containing a questionnaire about housing and management practices and a scoring guide was distributed to 500 turkey farmers across Canada. The farmer scored pecking injuries in two different body areas (HN and BT) on a 0-2 scale on a subset of birds within each flock. Multivariable logistic regression modeling was used to identify factors associated with the presence of HN and BT injuries. The prevalence of birds with integument injuries ranged widely between the flock subsets (HN = 0-40%, BT = 0-97%), however the mean prevalence was low (HN = 6%, BT = 10%). The presence of injuries for logistic regression was defined as flocks with an injury prevalence greater than the median level of injury prevalence in the dataset (3.3% HN and 6.6% BT). The final logistic regression model for HN injuries contained five variables: flock sex, flock age, number of daily inspections, number of different people during inspections, and picking up birds during inspections (N = 62, pR2 = 0.23, α = 0.05). The final logistic regression model for BT injuries contained six variables: flock sex, flock age, litter depth, litter condition, inspection duration, and use of hospital pens for sick/injured birds (N = 59, pR2 = 0.29, α = 0.05). Flock age, and to a lesser extent, sex was associated with both types of injuries. From a management perspective, aggressive pecking injuries appear to be influenced by variables related to human interaction, namely during inspections. On the other hand, the presence of feather pecking injuries, was associated with litter condition and other management factors like separating sick birds. Future research on injurious pecking in turkeys should focus on these aspects of housing and management to better describe the relationship between the identified variables and the prevalence and severity of these conditions.

Across-Species Pose Estimation in Poultry Based on Images Using Deep Learning

Animal pose-estimation networks enable automated estimation of key body points in images or videos. This enables animal breeders to collect pose information repeatedly on a large number of animals. However, the success of pose-estimation networks depends in part on the availability of data to learn the representation of key body points. Especially with animals, data collection is not always easy, and data annotation is laborious and time-consuming. The available data is therefore often limited, but data from other species might be useful, either by itself or in combination with the target species. In this study, the across-species performance of animal pose-estimation networks and the performance of an animal pose-estimation network trained on multi-species data (turkeys and broilers) were investigated. Broilers and turkeys were video recorded during a walkway test representative of the situation in practice. Two single-species and one multi-species model were trained by using DeepLabCut and tested on two single-species test sets. Overall, the within-species models outperformed the multi-species model, and the models applied across species, as shown by a lower raw pixel error, normalized pixel error, and higher percentage of keypoints remaining (PKR). The multi-species model had slightly higher errors with a lower PKR than the within-species models but had less than half the number of annotated frames available from each species. Compared to the single-species broiler model, the multi-species model achieved lower errors for the head, left foot, and right knee keypoints, although with a lower PKR. Across species, keypoint predictions resulted in high errors and low to moderate PKRs and are unlikely to be of direct use for pose and gait assessments. A multi-species model may reduce annotation needs without a large impact on performance for pose assessment, however, with the recommendation to only be used if the species are comparable. If a single-species model exists it could be used as a pre-trained model for training a new model, and possibly require a limited amount of new data. Future studies should investigate the accuracy needed for pose and gait assessments and estimate genetic parameters for the new phenotypes before pose-estimation networks can be applied in practice.

Are Turkeys (Meleagris gallopavo) Motivated to Avoid Excreta-Soiled Substrate?

Simple Summary

Commercial turkeys are raised in large barns at stocking densities that cause excreta (or feces) to quickly accrue in the turkeys’ environment. Even though commercial turkeys spend most, if not all, of their time in contact with their excreta, we do not know how turkeys perceive this soiled environment. Therefore, our study used six pens of four turkeys, dividing each pen with a barrier that contained two one-way push-doors. This created two compartments: a “home” compartment containing soiled wood shavings, and a “treatment” (T) compartment containing fresh pine and spruce wood shavings (FP), soiled pine and spruce wood shavings (SP), ammonia reductant-treated soiled pine and spruce wood shavings (TSP), no substrate (NS), or a feed treatment. To establish the turkeys’ motivation to access these resources, we weighed the door to T with 0%, 20% or 40% of the turkeys’ body weight. The number of turkeys that pushed the maximum door weight was used as an indicator for their motivation. Additionally, time spent in T and the odds of visiting T were examined to determine how the turkeys responded to increasing challenge. We found that the turkeys preferred feed over all other resources and showed equal motivation for all floor substrate treatments.

Abstract

The soiling of bedding on modern turkey farms combined with turkeys’ reduced ability and opportunity to perch and roost at elevation, forces them to spend most, if not all, of their time in contact with their excreta. To determine turkeys’ perspective on these conditions and the value they place on unsoiled bedding vs. soiled litter (collectively, substrates), we used twenty-four eleven-week-old turkey hens divided into six two-compartment pens. In the “home” compartment (H), we placed soiled wood shavings, while the “treatment” compartment (T) contained no substrate (NS), fresh pine and spruce wood shavings (FP), soiled pine and spruce wood shavings (SP), ammonia reductant-treated soiled pine and spruce wood shavings (TSP), or a feed treatment. One-way push-doors separated the two compartments. The door leading to T weighed an additional 0%, 20% or 40% of the turkeys’ body weight while the door to H remained unweighted. All birds were exposed to each resource and door weight combination in a systematic order. We measured the turkeys’ motivation based on the number of birds that pushed the maximum weight to access each resource, the amount of time spent in T, and the number of visits to T. Our findings show that turkeys worked harder to access feed compared to all the floor substrate treatments. Additionally, they were equally motivated to access all the substrate treatments.

Housing and Management of Turkey Flocks in Canada

Simple Summary

Relatively little is known about how farmers house and manage turkey flocks. To address this knowledge gap, a cross-sectional survey on housing and management practices of turkey flocks was conducted among farmers in Canada. Data were collected from 53 hen flocks (64%) and 30 tom flocks (36%), giving a total of 83 turkey flocks across the country. Flock age ranged between 7–14 weeks (interquartile range). The majority of turkey flocks were kept in indoor barns with automated ventilation. Bedding was provided to all flocks, and litter management was mostly focused on avoiding wet litter (e.g., adding dry litter or heat to avoid caking litter). Practices related to feed/water management and environmental control were relatively consistent between farms. More variation was observed between farmers in terms of flock health management and biosecurity practices. These results can benchmark current management practices within the Canadian turkey farming sector and present a foundation for future research.

Abstract

An increased understanding of the turkey sector and how farmers manage flocks can help maintain and improve the health and welfare of turkeys. We conducted a cross-sectional survey among turkey farmers in Canada to gain information regarding general farm characteristics, housing aspects (incl. lighting, ventilation), litter management, feed and water management, flock characteristics, and flock health management. The survey was distributed to 500 farmers through the Turkey Farmers of Canada in April–December 2019. A total of 83 final responses (response rate approx. 20%) were used for a descriptive analysis to determine the frequency of housing and management practices (77 commercial flocks, 6 breeder flocks). Hen flocks (n = 53) had a median age of eight weeks (IQR: 7–12 weeks) and tom flocks (n = 30) had a median age of 12 weeks (IQR: 9–14 weeks). Turkey flocks within Canada are typically kept in indoor barn systems on a concrete floor (87.5%), with bedding (e.g., straw, wood shavings) provided (100%). The majority followed a brood and move growing system (68.8%), and a large proportion of farmers indicated that they raised turkeys under the ‘Raised Without Antibiotics/Antibiotic Free’ or the ‘Responsible Use of Antibiotics’ certification (70.5%). Possible room for improvement could be found in terms of litter management and biosecurity practices, however, further research is needed to make clear recommendations.