Abstract
Traditionally, laying hen farmers monitor health, welfare and productivity of their flockbased on feed and water intake of the birds, flock productive output, climatefactors, and behavioural observations. Due to the growing number of birds per layer farmand the decreased availability of personnel with sufficient knowledge on poultry, itbecomes increasingly difficult to safeguard and control bird health andwelfare. Concurrently, there is a global trend towards more sustainable livestock farmingwith amongst others profitable and efficient animal production with a low ecologicalfootprint. To keep up with these developments, farmers can benefit from state-of-the-artsensor technology, serving as artificial nose, ears and eyes that gather 24/7 data on flockhealth, welfare and productivity. This project aims to improve laying hen welfare byearly stress detection based on continuous assessment of reliable, predictive (animalbased)indicators. As a first step, a qualitative, multi-stakeholder survey was preparedto determine current and future sensor use and automation in aviaries to support on-farmhealth and welfare assessment. Knowledgeable laying hen farmers, practicing poultryveterinarians and experienced poultry experts specialised in e.g. nutrition, genetics andwelfare, all working in West-Europe and Canada, were selected for participation. Using apurposive heterogenous sampling approach, maximum diversity was createdamong our homogenous candidate group. Participants completed an online questionnaireand participated in a semi-structured interview consisting of narrative questions andfollow-up probing questions. The questionnaire aimed to identify several variables thatcould underly the answers given during the interview, such as sociodemographiccharacteristics. Laying hen farmers were additionally asked about farm management andhousing characteristics, while poultry veterinarians and experts were asked about detailson their profession and frequency of contact with the commercial poultry sector. Duringthe interview, participants were encouraged to identify relevant health and welfare issues,including their causal stressors and predictive indicators, to describe currentuse of sensor (data) during health and welfare assessment and to describe their interest infuture technologies. Qualitative content of the interviews is analysed, using an inductivecoding approach and summarized per stakeholder. Quantitative analysis includes variableranking and comparison between stakeholders, a binary logistic regression and a Fisherstest. Preliminary results will be shown during the WIAS Annual Conference. Final results will be used during consecutive steps of the project.
Original language | English |
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Title of host publication | WIAS Annual Conference 2022 |
Subtitle of host publication | Collective Action |
Publisher | Wageningen University & Research |
Pages | 45-45 |
Publication status | Published - 11 Feb 2022 |
Event | 27th WIAS Annual Conference 2022: Collective Action - Conference Centre De Werelt, Lunteren, Netherlands Duration: 11 Feb 2022 → 11 Feb 2022 |
Conference
Conference | 27th WIAS Annual Conference 2022 |
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Country/Territory | Netherlands |
City | Lunteren |
Period | 11/02/22 → 11/02/22 |