Animal welfare assessment through smartphone applications : challenges and opportunities

Summary The AWIN applications are specifically designed to allow the on-farm data collection and to provide an immediate and clear visual output on the welfare status of each assessed farm. To apply the protocol in a robust and reliable way specific training is needed on how to assess and score the welfare indicators. Introduction Providing environmental and management conditions that favour animal welfare is not only expected by consumers and the general public, but is also related to achieving system-appropriate levels of health, performance and profitability. Animal welfare assessment is thus one of the pillars of productive, efficient and sustainable production systems. Initially welfare monitoring schemes were largely based on resource-based and management-based measures which should be considered as risk factors that might affect welfare; in order to assess animal welfare at farm level, it is crucial to develop and use animal-based measures. These indicators provide a more accurate welfare assessment as they give direct information about the response of, and the effects on, the animal (1). Animal-based measures are considered to be “the most appropriate indicators of animal welfare and a carefully selected combination of animal-based measures can be used to assess the welfare of a target population in a valid and robust way” (2). The first welfare assessment protocols built on animal-based measures were developed by the Welfare Quality® project for pigs, poultry, dairy and beef cattle (3,4,5). In the 7th Framework Programme, the European Commission required the development, integration and dissemination of animal-based indicators, including pain, in commercially important husbandry species not yet covered in previous projects. Results In 2011 the AWIN (Animal Welfare Indicators) project was funded by European Commission with the overall goal of improving animal welfare of sheep, goats, horses, donkeys and turkeys by developing, integrating and disseminating information about animal welfare indicators. These animal species offered challenges since they have been less studied and thus there was generally less information available on well-validated welfare indicators. In addition, the heterogeneity of the farming systems and environments in which these animals live may make the assessment more difficult. The welfare assessment protocols developed by AWIN (6,7,8,9,10) provide a toolbox of sound, feasible and practical animal-based indicators to assess animal welfare in order to promote improvements in animal production systems. The protocols were developed for species with broadly different rearing systems, ranging from intensive to pasture based systems, and different production settings, ranging from intensive milk production to extensive meat production or working animals. Moreover, with the aim to improve the efficiency of on-farm data collection, AWIN researchers, in collaboration with DAIA Intelligent Solutions S.L., developed dedicated smartphone applications (e.g. AWINHorse, AWINGoat, AWINSheep and IWatch Turkey), freely available at Google Play. Conclusion The AWIN apps are specifically designed to guide the user step-by-step in the on-farm data collection and to provide an immediate and clear visual output on the welfare status of each assessed farm. Collected data can be stored on the device and, when needed, they can be easily converted in a CSV file, and then sent by email. The visual output (a bar chart) emphasizes positive feedback on the welfare conditions of the animals, allowing the comparison with welfare data of a reference population or other groups of animals of the same farm. One of the objectives of the use of an immediate visual output is to start a dialogue with farmers on the welfare of their animals and the actions needed to improve it. However, there are still some important challenges to be addressed. First of all, to make the reference population more geographically representative, data collection must be undertaken on a larger scale and be more widely distributed. Secondly, even if minimal training is needed to use the apps, no individual or organization can be considered capable of applying the protocol in a robust and reliable way without specific training on how to assess and score the welfare indicators. Finally, in order to increase animal welfare outcomes and enforce animal welfare policies throughout the world, a worldwide server is required to store and analyze the welfare data in a harmonized way. References 1) Blokhuis, H.J., Jones, R.B., Veissier, I., Geers, R. (2006). COST Action 846 Measuring and Monitoring farm animal welfare. K.U. Leven. 2) EFSA (2012). Statement on the use of animal-based measures to assess the welfare of animals. Panel on Animal Health and Welfare (AHAW), EFSA Journal, 10(6):2767, 29 pp. 3) Welfare Quality® Protocol (2009).Welfare Quality® Assessment Protocol for pig (sows and piglets, growing and finishing pigs). Welfare Quality® Consortium, Lelystad, The Netherlands, 122 pp. 4) Welfare Quality® Protocol (2009). Welfare Quality® Assessment Protocol for poultry (broilers, laying hens). Welfare Quality® Consortium, Lelystad, The Netherlands, 114 pp. 5) Welfare Quality® Protocol (2009) . Welfare Quality® Assessment Protocol for cattle. Welfare Quality® Consortium, Lelystad, The Netherlands, 180 pp. 6) AWIN (2015). AWIN welfare assessment protocol for goats. Università degli Studi di Milano, Milan, Italy. DOI: 10.13130/AWIN_GOATS_2015. 70 pp. 7) AWIN (2015). AWIN welfare assessment protocol for sheep. Università degli Studi di Milano, Milan, Italy. DOI: 10.13130/AWIN_SHEEP_2015, 72pp 8) AWIN (2015). AWIN welfare assessment protocol for horses. Università degli Studi di Milano, Milan, Italy. DOI: 10.13130/AWIN_HORSES_2015, 80pp. 9) AWIN (2015). AWIN welfare assessment protocol for donkeys. Università degli Studi di Milano, Milan, Italy. DOI: 10.13130/AWIN_DONKEYS_2015, 69 pp. 10) AWIN (2015). AWIN welfare assessment protocol for turkey. Università degli Studi di Milano, Milan, Italy. DOI: 10.13130/AWIN_TURKEY_2015 45pp.