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Abstract The effects of pelagic trawling on the health and welfare of Atlantic herring (Clupea harengus L.) were investigated on a refrigerated seawater vessel operating in the North Sea. A total of 495 Atlantic herring (Clupea harengus L.) were sampled during five hauls from two fishing trips in September 2021 and 2022. For assessments of consciousness and mortality, a Reflex Action Mortality Predictor test (i.e. RAMP-test) was used on herring collected following trawling and pumping. Inspections for external and internal damage or wounds were performed via morphological welfare indicators and analyses of photos and radiographs. In addition, blood samples were taken and analysed for haematological indicators of stress. Following trawling and pumping, only 5% of the investigated herring showed signs of external wounds associated with the morphological indicators of welfare, and no internal damage was observed in the radiographic inspections. However, 96% of the assessed herring scored 0 on all three reflexes included in the RAMP-test and were therefore judged dead. On average, herring lost 95% of their scales, while 95% of herring had a very high degree of ruptured red blood cells (i.e. haemolysis). Extensive scale loss results in a deterioration of the skin's protective barrier function, which in turn impairs the osmoregulatory capacity of the herring. This was evident by elevated levels of plasma osmolality and circulating chloride concentrations, which could also likely explain the high occurrence of haemolysis in captured herring. Extended trawling time and larger catch size proved to be two important factors to consider, as the former led to increased plasma levels of osmolality, whereas the latter was associated with elevated plasma levels of lactate and cortisol. In conclusion, the high mortality appears to be influenced by a combination of factors such as severe stress, loss of osmoregulatory ability, crowding density within the trawl, and extended trawling times. This study provides important information on the welfare of wild Atlantic herring caught using pelagic trawls and highlights areas where improvements can be made to safeguard the welfare of fish captured in pelagic fisheries in the future.

Canine hip dysplasia (CHD) screening relies on accurate positioning in the ventrodorsal hip extended (VDHE) view, as even mild pelvic rotation can affect CHD scoring and impact breeding decisions. This study aimed to assess the association between pelvic rotation and asymmetry in obturator foramina areas (AOFAs) and to develop a computer vision model for automated AOFA measurement. In the first part, 203 radiographs were analyzed to examine the relationship between pelvic rotation, assessed through asymmetry in iliac wing and obturator foramina widths (AOFWs), and AOFAs. A significant association was found between pelvic rotation and AOFA, with AOFW showing a stronger correlation (R2 = 0.92, p < 0.01). AOFW rotation values were categorized into minimal (n = 71), moderate (n = 41), marked (n = 37), and extreme (n = 54) groups, corresponding to mean AOFA ± standard deviation values of 33.28 ± 27.25, 54.73 ± 27.98, 85.85 ± 41.31, and 160.68 ± 64.20 mm2, respectively. ANOVA and post hoc testing confirmed significant differences in AOFA across these groups (p < 0.01). In part two, the dataset was expanded to 312 images to develop the automated AOFA model, with 80% allocated for training, 10% for validation, and 10% for testing. On the 32 test images, the model achieved high segmentation accuracy (Dice score = 0.96; Intersection over Union = 0.93), closely aligning with examiner measurements. Paired t-tests indicated no significant differences between the examiner and model’s outputs (p > 0.05), though the Bland–Altman analysis identified occasional discrepancies. The model demonstrated excellent reliability (ICC = 0.99) with a standard error of 17.18 mm2. A threshold of 50.46 mm2 enabled effective differentiation between acceptable and excessive pelvic rotation. With additional training data, further improvements in precision are expected, enhancing the model’s clinical utility.

Adequate radiographic positioning on the X-ray table is paramount for canine hip dysplasia (HD) screening. The aims of this study were to evaluate femoral parallelism on normal ventrodorsal hip extended (VDHE) view and the effect of femoral angulation (FA) on Norberg Angle (NA) and Hip Congruency Index (HCI). The femoral parallelism was evaluated comparing the alignment of the long femoral axis with the long body axis in normal VDHE views and the effect of FA on NA and HCI on repeated VDHE views with different levels of FA. The femoral long axis in normal VDHE views showed a ranged of FA from −4.85° to 5.85°, mean ± standard deviation (SD) of −0.06 ± 2.41°, 95% CI [−4.88, 4.76°]. In the paired views, the mean ± SD femur adduction of 3.69 ± 1.96° led to a statistically significant decrease NA, and HCI, and femur abduction of 2.89 ± 2.12 led to a statistically significant increase in NA and HCI (p

The alteration in the shape of the femoral neck is an important radiographic sign for scoring canine hip dysplasia (CHD). Previous studies have reported that the femoral neck thickness (FNT) is greater in dogs with hip joint dysplasia, becoming progressively thicker with disease severity. The main objective of this work was to describe a femoral neck thickness index (FNTi) to quantify FNT and to study its association with the degree of CHD using the Fédération Cynologique Internationale (FCI) scheme. A total of 53 dogs (106 hips) were randomly selected for this study. Two examiners performed FNTi estimation to study intra- and inter-examiner reliability and agreement. The paired t-test, the Bland-Altman plots, and the intraclass correlation coefficient showed excellent agreement and reliability between the measurements of the two examiners and the examiners’ sessions. All joints were scored in five categories by an experienced examiner according to FCI criteria. The results from examiner 1 were compared between FCI categories. Hips that were assigned an FCI grade of A (n = 19), B (n = 23), C (n = 24), D (n = 24), and E (n = 16) had a mean ± standard deviation FNTi of 0.809 ± 0.024, 0.835 ± 0.044, 0.868 ± 0.022, 0.903 ± 0.033, and 0.923 ± 0.068, respectively (ANOVA, p < 0.05). Therefore, these results show that FNTi is a parameter capable of evaluating proximal femur bone modeling and that it has the potential to enrich conventional CHD scoring criteria if incorporated into a computer-aided diagnosis capable of detecting CHD.

Accurate radiographic screening evaluation is essential in the genetic control of canine HD, however, the qualitative assessment of hip congruency introduces some subjectivity, leading to excessive variability in scoring. The main objective of this work was to validate a method-Hip Congruency Index (HCI)-capable of objectively measuring the relationship between the acetabulum and the femoral head and associating it with the level of congruency proposed by the Fédération Cynologique Internationale (FCI), with the aim of incorporating it into a computer vision model that classifies HD autonomously. A total of 200 dogs (400 hips) were randomly selected for the study. All radiographs were scored in five categories by an experienced examiner according to FCI criteria. Two examiners performed HCI measurements on 25 hip radiographs to study intra- and inter-examiner reliability and agreement. Additionally, each examiner measured HCI on their half of the study sample (100 dogs), and the results were compared between FCI categories. The paired t-test and the intraclass correlation coefficient (ICC) showed no evidence of a systematic bias, and there was excellent reliability between the measurements of the two examiners and examiners’ sessions. Hips that were assigned an FCI grade of A (n = 120), B (n = 157), C (n = 68), D (n = 38) and E (n = 17) had a mean HCI of 0.739 ± 0.044, 0.666 ± 0.052, 0.605 ± 0.055, 0.494 ± 0.070 and 0.374 ± 0.122, respectively (ANOVA, p < 0.01). Therefore, these results show that HCI is a parameter capable of estimating hip congruency and has the potential to enrich conventional HD scoring criteria if incorporated into an artificial intelligence algorithm competent in diagnosing HD.