Validation of an automatic scoring system for the assessment of hock burn in broiler.

This study aimed to develop and validate a camera vision score that could detect macroscopic alterations of the hock, to identify errors and to assess possible factors that could influence the assessment. Two hundred hocks in the first (calibration) phase and 500 hocks in the second (validation) phase were collected at slaughter, visually assessed, placed back into the evisceration line and assessed by a camera system with 2 software systems. The size of the alteration in percent (%) measured by the camera system was evaluated ("camera score", CS). Additionally, temperature, humidity, and light intensities were measured. In the calibration phase, threshold values of camera scores for respective macro scores were defined and performance measures evaluated. In the validation phase, the generated threshold values were validated, occurring errors, as well as possible impacts of climatic factors analyzed. The results showed that the generated thresholds predict the camera score values at which the respective macro score has the highest probability of appearance. Small hock burn lesions ≤0.5 cm have the highest probability at a camera score of ≥0.2 (original CS) or ≥0.1 (updated CS), and lesions >0.5 cm have the highest probability at a camera score of ≥0.7 (original CS) or ≥1.1 (updated CS). Large lesions (>0.5 cm) are more reliably identified by the system than small lesions. The risks of errors in assessing reference areas and lesions showed a correct identification of lesions to be the most probable result even if the reference area is not correctly identified. The probability of a correct identification of lesions by the camera system was slightly higher (not significant) with the updated software (risk = 0.66 [0.62-0.70]) than with the original software (risk = 0.63 [0.58-0.67]). Automatic assessment systems at slaughter could be adjusted to the presented threshold values to classify hock burn lesions. Software adaptations can improve the performance measures of diagnosis and reduce the probability of errors.

Footpad Monitoring: Reliability of an Automated System to Assess Footpad Dermatitis in Turkeys (Meleagris gallopavo) During Slaughter.

Footpad dermatitis (FPD) is an indicator of animal welfare in turkeys, giving evidence of the animals' physical integrity and providing information on husbandry management. Automated systems for assessing FPD at slaughter can present a useful tool for objective data collection. However, using automated systems requires that they reliably assess the incidence. In this study, the feet of turkeys were scored for FPD by both an automated camera system and a human observer, using a five-scale score. The observer reliability between both was calculated (Krippendorff's alpha). The results were not acceptable, with an agreement coefficient of 0.44 in the initial situation. Therefore, pictures of 3,000 feet scored by the automated system were evaluated systematically to detect deficiencies. The reference area (metatarsal footpad) was not detected correctly in 55.0% of the feet, and false detections of the alteration on the footpad (FPD) were found in 32.9% of the feet. In 41.3% of the feet, the foot was not presented straight to the camera. According to these results, the algorithm of the automated system was modified, aiming to improve color detection and the distinction of the metatarsal footpad from the background. Pictures of the feet, now scored by the modified algorithm, were evaluated again. Observer reliability could be improved (Krippendorff's alpha = 0.61). However, detection of the metatarsal footpad (50.9% incorrect detections) and alterations (27.0% incorrect detections) remained a problem. We found that the performance of the camera system was affected by the angle at which the foot was presented to the camera (skew/straight; p < 0.05). Furthermore, the laterality of the foot (left/right) was found to have a significant effect (p < 0.001). We propose that the latter depends on the slaughter process. This study also highlights a high variability in observer reliability of human observers. Depending on the respective target parameter, the reliability coefficient (Krippendorff's alpha) ranged from 0.21 to 0.82. This stresses the importance of finding an objective alternative. Therefore, it was concluded that the automated detection system could be appropriate to reliably assess FPD at the slaughterhouse. However, there is still room to improve the existing method, especially when using FPD as a welfare indicator.

Automatic Assessment of Keel Bone Damage in Laying Hens at the Slaughter Line.

Keel bone damage (KBD) can be found in all commercial laying hen flocks with a wide range of 23% to 69% of hens/flock found to be affected in this study. As KBD may be linked with chronic pain and a decrease in mobility, it is a serious welfare problem. An automatic assessment system at the slaughter line could support the detection of KBD and would have the advantage of being standardized and fast scoring including high sample sizes. A 2MP stereo camera combined with an IDS imaging color camera was used for the automatic assessment. A trained human assessor visually scored KBD in defeathered hens during the slaughter process and compared results with further human assessors and automatic recording. In a first step, an algorithm was developed on the basis of assessments of keel status of 2287 hens of different genetics with varying degrees of KBD. In two optimization steps, performance data were calculated, and flock prevalences were determined, which were compared between the assessor and the automatic system. The proposed technique finally reached a sensitivity of 0.95, specificity of 0.77, accuracy of 0.86 and precision of 0.81. In the last optimization step, the automatic system scored on average about 10.5% points lower KBD prevalences than the human assessor. However, a proposed change of scoring system (setting the limit for KBD at 0.5 cm deviation from the straight line) would lower this deviation. We conclude that the developed automatic scoring technique is a reliable and potentially valuable tool for the assessment of KBD.