RUC-APS · Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems

Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems

Currently in INIA in Chile, in collaboration with partners from CNR-ISPA, ULIV, BDI and FEDCOVA, new tomato rootstocks with high nutrient use efficiency (NUE) and tolerance to drought and saline stress conditions. Moreover, UNLP, is currently testing Horticultures crops from UE countries , in specific: arugula (Diplotaxis tenuifolia), top of rapa (Brassica rapa subsp. sylvestris var. esculenta), colored cauliflowers (Brassica oleracea. var. botrytis), as well as certain local italian radiccios (Cichorium intybus var. foliosum), and parsnip (Pastinaca sativa) and tendersteam from UK. Different types of tomatoes and peppers from Italy and Spain too. Aligned to this, ALSIA team, is currently working on two plant species to establish the first varietal behavior models: Peach and Strawberry, These plants were chosen due to their economic importance in Basilicata region. In fact, Basilicata is the first producer of Strawberry in Italy and it is cultivated on about 1,000 hectares while peaches production is made on roughly 6,000 hectares.Therefore, the partner AINIA, technological center ,has collaborated with BDI, in the elaboration and development of an action plan with which to know with greater precision, the best moment for the harvesting of the pumpkin. In order to ensure a higher quality and durability of this vegetable, researchers from AINIA have analyzed Data Analytics (Artificial Intelligence applied to data analysis) data on cultivation and preservation of pumpkins of the Red Kuri variety. Within this, it is possible to determine the moment of harvest of pumpkins with technology 4.0. It has been shown an example of how Big Data can be applied to identify market trends and provide complementary qualitative information in order to understand the market. Taking into account the aim of ALSIA of technology transference, it has explained to ALSIA team that BIG DATA can be applied to do technological surveillance in a structured way. The objectives of the project RUC-APS are performing healthy and running smoothly. Moreover, and as part of the continuous research and innovation process, a set of high-level questions have been produced in order to gather the relevant information for each objective. These are established in the three domains: Agriculture, Supply Chain and ICT, which addressed the key generic information and that are relevant to be collected, especially to get a proper understanding from each agribusiness dimension in terms of: SO1: To support the varietal behaviour in a variety of agro-climatic zones in terms of cost and production cycle; SO2: To optimise the agronomic management by understanding the incorporation of specialized machinery in the processes of sowing, transplanting and fertilizing; SO3: To analyse and refine quality standards to ensure the safety of the final agriculture based product under high risk and uncertain conditions; SO4: To evaluate the environmental conditions for enhancing soil management technologies and planting management; SO5: To model and optimise smarts and innovative collaborative production-transport planning solutions of horticulture products across the full value chain structure; SO6: To generate horizontal and vertical knowledge exchange mechanisms across the agriculture value chain. This is explained in the following video links: https://www.youtube.com/watch?v=cPcQvM0bra4#action=share, https://www.youtube.com/watch?v=p8iEOSZV2vQ#action=share, http://www.youtube.com/watch?v=vugnVmgeiOs#action=share

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз