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MORE PRECISE AND EFFECTIVE PREVENTION: DEALING WITH EXTREME WEATHER PHENOMENA IN FRUIT TREE GROWING


Agricultural activity is significantly conditioned by the climatic conditions of the area in which it is carried out, which determine the type of crops, irrigation needs, phytosanitary treatments or the phenological cycle, among other aspects.

However, in addition to the climate patterns of an area, farmers are often exposed to exceptional weather phenomena, which can wipe out a whole year's work in just a few minutes or hours. Extreme rainfall, hail, frost, episodes of wind... there are many circumstances that can condition the development of a campaign.

What are we doing at CYBELE?

With the advance of technology applied to the agricultural sector, one of the demands of farmers is to have more tools to predict and mitigate the effects of these extreme phenomena. In response to this need, the CYBELE project is working on experiments for the early detection of frost and hail phenomena, using supercomputing techniques applied to the huge flow of available production and agro-climatic data.

The trial is being carried out in the province of Valencia, located in the east of Spain, taking as a reference a series of plots belonging to the SAN BERNAT de Carlet and COFRUDECA (Bèlgida) cooperatives. Since 2020, our partner Federació Cooperatives Agro-alimentàries de la Comunitat Valenciana (CACV) has overseen weekly monitoring of the phenological state of different crops (early and extra-early fruit trees, persimmon, citrus fruits of different seasons, mandarins...). Likewise, weather stations have been installed in the area under study, which allow the sending of updated information every 15 minutes.


This information, aggregated with that of the phenological cycles and added to that of other sources, such as AGROSEGURO (an entity of the Spanish agricultural insurance system), is processed by GMV, another of the CYBELE project partners, having made considerable progress in recent months in the conceptualization and exploration of automatic learning methods for forecasting frost and hail. To find out in detail how the information collected is processed and what results are expected from it, please refer to the following article published in our blog.

Real impact and practical application

CYBELE aims to have a real impact on the agricultural sector, with results that can be transferred from research to the field, responding to the real needs of farmers. In this sense, the early detection of frost and hail phenomena can help, for example, to decide on bringing forward harvesting work or on the installation of preventive and protective elements (anti-hail nets or night-time heating systems, for example).

CYBELE, for this particular demonstration project, is working with the hypotheses of frost and hail prevention with a minimum of 48 hours in advance and a few meters of error. Once the CYBELE platform is operational, the Federation will present its results to different cooperatives and other entities interested in using this service.


Of course, the results obtained will be accompanied by different economic indicators that will make it possible to assess the relevance of using anti-freeze and/or anti-hail methods depending on the intensity forecast and the phenological moment of the fruit.

Before the end of the year, the Federation plans to carry out a campaign to disseminate and explain the results to find out first-hand the real opinions of the agricultural sector and the possibilities and opportunities that this new service opens up.

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