Black soldier fly larvae (BSFL) are considered a commercially viable solution for global organic waste problems. The objective of this study was to assess the feasibility of rearing BSFL on a wide range of low-value waste streams and its potential to transform them into high-quality animal feed and fertilizer. Six waste streams of different origins were selected and each tested in triplicate. Several parameters were analysed: growth performance, waste reduction index (WRI), conversion efficiency (ECI) and larval composition. Frass composition was also analysed. Larvae reared on fast food waste (FFW) had the highest ECI and WRI and the lowest values when reared on pig manure slurry mixed with silage grass (PMLSG) and slaughter waste (SW). The highest protein content was found for larvae reared on mushroom stems (MS) although this substrate had the lowest protein content. Moreover, the frass nutritional profile was proportionally related to the substrate’s nutritional profile: the protein-rich substrate (SW) resulted in protein-rich frass and the low-protein substrate (MS) resulted in protein-poor frass. The same was true for the lipid content. In conclusion, this study showed that BSFL can be successfully reared on a wide range of waste streams that can affect the larval and frass chemical compositions.

Walking ability of broilers can be improved by selective breeding, but large-scale phenotypic records are required. Currently, gait of individual broilers is scored by trained experts, however, precision phenotyping tools could offer a more objective and high-throughput alternative. We studied whether specific walking characteristics determined through pose estimation are linked to gait in broilers. We filmed male broilers from behind, walking through a 3 m × 0.4 m (length × width) corridor one by one, at 3 time points during their lifetime (at 14, 21, and 33 d of age). We used a deep learning model, developed in DeepLabCut, to detect and track 8 keypoints (head, neck, left and right knees, hocks, and feet) of broilers in the recorded videos. Using the keypoints of the legs, 6 pose features were quantified during the double support phase of walking, and 1 pose feature was quantified during steps, at maximum leg lift. Gait was scored on a scale from 0 to 5 by 4 experts, using the videos recorded on d 33, and the broilers were further classified as having either good gait (mean gait score ≤2) or suboptimal gait (mean gait score >2). The relationship of pose features on d 33 with gait was analyzed using the data of 84 broilers (good gait: 57.1%, suboptimal gait: 42.9%). Birds with suboptimal gait had sharper hock joint lateral angles and lower hock-feet distance ratios during double support on d 33, on average. During steps, relative step height was lower in birds with suboptimal gait. Step height and hock-feet distance ratio showed the largest mean deviations in broilers with suboptimal gait compared to those with good gait. We demonstrate that pose estimation can be used to assess walking characteristics during a large part of the productive life of broilers, and to phenotype and monitor broiler gait. These insights can be used to understand differences in the walking patterns of lame broilers, and to build more sophisticated gait prediction models.

Phenotypes on individual animals are required for breeding programs to be able to select for traits. However, phenotyping individual animals can be difficult and time-consuming, especially for traits related to health, welfare, and performance. Individual broiler behavior could serve as a proxy for these traits when recorded automatically and reliably on many animals. Sensors could record individual broiler behavior, yet different sensors can differ in their assessment. In this study a comparison was made between a passive radio frequency identification (RFID) system (grid of antennas underneath the pen) and video tracking for the determination of location and movement of 3 color-marked broilers at d 18. Furthermore, a systems comparison of derived behavioral metrics such as space usage, locomotion activity and apparent feeding and drinking behavior was made. Color-marked broilers simplified the computer vision task for YOLOv5 to detect, track, and identify the animals. Animal locations derived from the RFID-system and based on video were largely in agreement. Most location differences (77.5%) were within the mean radius of the antennas' enclosing circle (≤128 px, 28.15 cm), and 95.3% of the differences were within a one antenna difference (≤256 px, 56.30 cm). Animal movement was not always registered by the RFID-system whereas video was sensitive to detection noise and the animal's behavior (e.g., pecking). The method used to determine location and the systems' sensitivities to movement led to differences in behavioral metrics. Behavioral metrics derived from video are likely more accurate than RFID-system derived behavioral metrics. However, at present, only the RFID-system can provide individual identification for non-color marked broilers. A combination of verifiable and detailed video with the unique identification of RFID could make it possible to identify, describe, and quantify a wide range of individual broiler behaviors.

Objective: The aim of our study was to determine the associations of heifer reproductive performance with survival up to the first calving, first-lactation milk yield, and the probability of being culled within 50 days after first calving.Methods: Data from 33 large Holstein-Friesian commercial dairy herds were gathered from the official milk recording database in Hungary. The data of heifers first inseminated between January 1, 2011 and December 31, 2014 were analyzed retrospectively, using Cox proportional hazards models, competing risks models, multivariate linear and logistic mixed-effects models.Results: Heifers (n = 35,128) with younger age at conception were more likely to remain in the herd until calving, and each additional month in age at conception increased culling risk by 5.1%. Season of birth was related to first-lactation milk yield (MY1; n = 19,931), with cows born in autumn having the highest milk production (p<0.001). The highest MY1 was achieved by heifers that first calved between 22.00 and 25.99 months of age. Heifers that calved in autumn had the highest MY1, whereas calving in summer was related to the lowest milk production (p<0.001). The risk of culling within 50 days in milk in first lactation (n = 21,225) increased along with first calving age, e.g. heifers that first calved after 30 months of age were 5.52-times more likely to be culled compared to heifers that calved before 22 months of age (p<0.001). Calving difficulty was related to higher culling risk in early lactation (p<0.001). Heifers that required caesarean section were 24.01-times more likely to leave the herd within 50 days after first calving compared to heifers that needed no assistance (p<0.001).Conclusion: Reproductive performance of replacement heifers is closely linked to longevity and milk production in dairy herds.

Impaired walking ability and leg health are commonly seen in broilers and can negatively impact their welfare. Commonly, walking ability and leg health are assessed manually, but this is time consuming and can be subjective. Automated approaches for scoring walking ability and leg health at the individual level could therefore have great added value. Here, we studied whether automatically extracted top-view walking features of broilers can be used as a proxy for walking ability and leg health. Top-view videos were collected of unmarked broilers walking through a corridor that was placed inside the home pen. From these videos, four top-view features were derived: 1) lateral body oscillation, calculated as deviations from the movement trajectory of the bird, 2) step count, 3) completion time, and 4) length-width ratio of the virtual bounding box encapsulating the bird while walking as an indicator of wing support. We assessed the relationship of these computer vision-based features with manual gait and leg health scores, including hock burn (HB) and footpad dermatitis (FPD). We observed that birds with worse gait scores (GS) had longer completion times, higher step counts and a trend for higher lateral body oscillation levels in the walkway setup. Unsupervised clustering using the K-means algorithm with these walking features showed potential to distinguish birds with GS3+, although differentiating between GS1 and GS2 proved more challenging. We concluded that the length-width ratio of the bounding box during walking was not a suitable proxy for poor gait. We found no relationship between top-view walking features and mild cases of HB and FPD in broilers. Overall, the results of this study indicate that top-view video recordings can provide insight into birds' walking ability, using features related to movement speed, step count and lateral body oscillation, making automated scoring more feasible on a larger scale in practice. However, these top view features provide little information about mild HB and FPD.

Ketosis is a metabolic disorder associated with high production and low energy intake in dairy cows. Fat reserves are mobilized, and gluconeogenesis occurs. Traditionally, rapid tests for blood, milk or urine are used to detect increased ketone body levels in case of ketosis. Breath analysis is relatively new and relevant for the development of automatic sensor systems for early warning. This study aims to determine whether and when a postpartum rise in ketone bodies occurs in breath with elevated blood β-hydroxybutyrate (BHB) in cows at risk of ketosis. Postpartum breath, blood, urine and milk samples were taken daily until day 7, with one prepartum sample excluding milk, and ketone body concentrations were determined. Concentrations of blood BHB were 0.4–2.6 mmol/L (lab) and 0.3–3.1 mmol/L (rapid test), breath acetone was 2.3–20.0 ppm, urine acetoacetate 0–8 mmol/L and milk BHB 0–500 µmol/L. A rise in blood BHB was related to that in urine acetoacetate and milk BHB and followed by a rise in breath acetone. However, breath acetone levels of ketotic and non-ketotic cows were similar. We conclude that rising ketone bodies can be detected in blood, urine, milk and breath, but to use breath analysis as an alternative to rapid tests, longitudinal sampling is needed.