P31 | Implementation of the APPàre technological platform: applications for smart and safe farms to promote data-driven innovation throughout the food chain

Purpose. The study was developed within the framework of the e.INS project - Ecosystem of Innovation for Next Generation Sardinia (code ECS 00000038) funded by the MUR under the PNRR (www.einsardinia.eu) Next Generation EU - PNRR - M4 C2 I1.5 CUP: J83C21000320007. The objective is aimed at strengthening the link between businesses and innovative research, which is useful for supporting technological innovation processes and facilitating the transfer of data and information between primary companies and the production system. The project, implemented in the Sardinian sheep supply chain, aims to provide primary producers and processors with an application accessible from various digital systems, serving as a working tool that allows them to identify and resolve critical issues in the different production phases. Methods. The first phase of the project was conducted on 20 livestock farms thru a beta test, which was necessary to test the system, share data collection, and define the main indicators to be included in the application. Meetings were held with stakeholders to share an operational proposal to be addressed to primary producers and processors and to gather input from supply chain actors and institutions. The indicators were divided into three sections: animal production, animal health, and food safety. Animal production data were linked to the BDN with references to the herd, feeding, and milk production. The animal health section contains data related to the management of medical control over the flock and individual animals (age, BCS, production category, calving history, diseases, days in gestation, etc.). Finally, the food safety data refers to bulk milk and includes: total bacterial count, somatic cell count, composition data (fat, protein, lactose, caseins, and urea), and finally, on a selection of farms, experimentally, the assessment of spore presence and aflatoxin M1 positivity. Results. Currently, the APPàre platform is structured to allow the farmer to view data related to the herd's status, with specific details on each individual animal associated with the rumen bolus code (age, sex, weight, production category, last calving date, etc.), including the history of medical checks and the results of examinations performed on the selected individual. Finally, for milk production, the platform can process data indicating averages and estimates of total bacterial count, somatic cell count, composition data, and M1 aflatoxins, both for individual farms and in aggregate across the various farms that supply a dairy. Conclusions. The platform's potential is multifaceted, even in relation to different stakeholders. Indeed, it is possible to obtain data for the breeder on their flock, but also, for all interested parties, data on production in relation to regional averages. Partner dairies will be able to know how much milk is produced regionally, what the quality characteristics of the milk produced are, and what the general health situation of the farms is. Furthermore, they will be able to compare their companies with the regional sector, monitoring seasonal and annual trends and planning corrective actions.