Making Timely Precision Farming Interventions Easier Through a Big Data Platform: ABACO Group Sheds Light on Its Involvement in the STELAR project
The agrifood data space is a fruitful ground for innovation. The planned Knowledge Lake Management System that will be developed within the STELAR project will provide players from the agrifood value chain with different useful outcomes. Among them is the assistance provided to farmers in developing agricultural strategies by planning timely precision farming interventions.
That is where ABACO Group steps in, as one of STELAR’s partners and leader of Pilot C: Timely precision farming interventions.
This Italian company develops software solutions for management and control of land resources.
ABACO’s Bid Manager and Business Developer Christian Schingo and Project Manager Marco Bonfigli give insight below on the main obstacles when it comes to timely precision farming interventions and how farmers can use data effectively. Moreover, they shed light on the main factors to keep in mind when developing agricultural strategies, and how the planned STELAR platform will help mitigate global food insecurity.
What are the primary obstacles encountered when implementing precision farming interventions in a timely manner?
When it comes to implementing precision farming interventions in a timely manner, one of the primary obstacles lies in effectively training and educating farmers about the proper utilisation of the platform. Ensuring that farmers understand the functionalities, benefits, and best practices associated with precision farming technology is crucial for successful implementation.
What are the key difficulties farmers face when utilising data for early crop predictions?
Farmers encounter key difficulties when it comes to leveraging data for early crop predictions. One significant challenge they face is grasping the significance of the data in making accurate predictions at an early stage of crop growth. Additionally, farmers may also struggle with understanding how to effectively interpret and utilise the data to make informed decisions about their farming practices.
What are the factors considered when selecting data for the development of agricultural strategies in the context of timely precision farming interventions?
Several factors are taken into consideration when selecting data for the development of agricultural strategies within the context of timely precision farming interventions. These factors include the specific typology of the field, the expected yield of the crops, and the geographical area in which the farming activities are taking place. Considering these elements helps tailor the precision farming strategies to suit the unique characteristics and requirements of each agricultural setting.
How will ABACO Group‘s the integration of Internet of Things (IoT) data into the Knowledge and Learning Management System (KLMS) facilitate the collection of real-time data and its subsequent analysis to support timely precision farming interventions?
By incorporating IoT data, the KLMS enables the acquisition of more comprehensive and up-to-date information, allowing for better understanding and evidence-based decision-making in precision farming practices.
How will the KLMS’s management of water, fertiliser, and pesticide data contribute to addressing the global issue of food insecurity and promoting sustainable agriculture?
Through efficient data management, the KLMS can help optimise the utilisation of these resources, minimising waste and ensuring their appropriate application based on specific crop requirements. By promoting responsible resource management, the KLMS contributes to enhancing food security and fostering sustainable agricultural practices.
Which countries have been designated for the pilot program’s implementation, aiming to test and validate its effectiveness?
Italy has been designated as one of the countries for the pilot program’s implementation, aimed at testing and validating its effectiveness. By choosing Italy as a participant in the pilot program, specific regional factors can be considered. This allows for a more comprehensive assessment of the program’s viability and effectiveness in diverse agricultural contexts, providing valuable insights for potential future expansion and adaptation.