Dataset Information

Towards Machine Vision for Insect Welfare Monitoring and Behavioural Insights.

ABSTRACT: Machine vision has demonstrated its usefulness in the livestock industry in terms of improving welfare in such areas as lameness detection and body condition scoring in dairy cattle. In this article, we present some promising results of applying state of the art object detection and classification techniques to insects, specifically Black Soldier Fly (BSF) and the domestic cricket, with the view of enabling automated processing for insect farming. We also present the low-cost "Insecto" Internet of Things (IoT) device, which provides environmental condition monitoring for temperature, humidity, CO₂, air pressure, and volatile organic compound levels together with high resolution image capture. We show that we are able to accurately count and measure size of BSF larvae and also classify the sex of domestic crickets by detecting the presence of the ovipositor. These early results point to future work for enabling automation in the selection of desirable phenotypes for subsequent generations and for providing early alerts should environmental conditions deviate from desired values.

SUBMITTER: Hansen MF

PROVIDER: S-EPMC8886630 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Towards Machine Vision for Insect Welfare Monitoring and Behavioural Insights.

Hansen Mark F MF Oparaeke Alphonsus A Gallagher Ryan R Karimi Amir A Tariq Fahim F Smith Melvyn L ML

Frontiers in veterinary science 20220215

Machine vision has demonstrated its usefulness in the livestock industry in terms of improving welfare in such areas as lameness detection and body condition scoring in dairy cattle. In this article, we present some promising results of applying state of the art object detection and classification techniques to insects, specifically Black Soldier Fly (BSF) and the domestic cricket, with the view of enabling automated processing for insect farming. We also present the low-cost "Insecto" Internet ...[more]

PMID: 35242842

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Project description:China's poultry industry faces challenges in adopting and sustaining cage-free systems for poultry production. Effective interventions are crucial to support producers transitioning from cages to alternative systems or maintaining cage-free systems to improve animal welfare. However, little is known about how Chinese poultry producers perceive animal welfare in relation to cage-free systems and the importance of animal welfare in poultry production. Through a qualitative interview study with 30 Chinese farm owners, managers and senior managers from large-scale egg and broiler farms using cages and non-cage systems (collectively referred to as "producers"), this paper explores Chinese poultry producers' attitudes and perceptions regarding animal welfare and welfare in different poultry housing systems. Template analysis was used to analyse the data from semi-structured interviews, which generated themes related to the participants' awareness and understanding of the concept of animal welfare, the factors that impacted their choices of different housing systems, and the perceived priorities in poultry production. The responses revealed that the participating producers had a strong awareness and knowledge of animal welfare. However, the participants' understanding of the term is heterogeneous: generally, egg producers emphasised natural behaviours, whereas broiler producers prioritised health and productivity. Nevertheless, profitability, leadership, and organisational policies primarily influenced housing system choices rather than animal welfare values. Economic motives drove egg producers towards cage-free systems, prompted by consumers' and companies' demand for cage-free eggs committed to transitioning away from cages by 2025. In conclusion, tailored interventions for different poultry sectors within China are necessary. While animal welfare values matter, economic incentives seem more promising for steering the shift towards and maintaining cage-free poultry production.

Dataset Information

Towards Machine Vision for Insect Welfare Monitoring and Behavioural Insights.

Publications

Towards Machine Vision for Insect Welfare Monitoring and Behavioural Insights.

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