Details of the project EPI

An innovative plant production management system with particular emphasis on optimizing the operation of machines, fertilization and protection of biodiversity of agriculturally exploited soils.

15-06-2022 do 31-12-2024

3 557 386,00

EFRROW; national public funds; own funds

www.projektsfcftf.cgfp.pl

The project aims to develop an innovative information system that, through continuous collection and onging analysis of data, will support the agricultural farmer in decision-making when planning and conducting crop production for wheat, maize and canola using no-till technology. The support will take place in three areas: optimization of the fertilization system, support for the management of machines, and improvement of the process of harvesting, transporting and storing agricultural crops, with particular attention to the aspect of identifying each batch of products.

Establishment of experimental plots, periodical soil sampling. Determination of chemistry, biological activity and biodiversity of bacteria and fungi with genetic analyses in the studied soils. Bioinformatics and statistical analyses of the obtained results. Purchase of a framework-compatible FMIS and implementation of key functions. Purchase and implementation of equipment necessary for integration with the farm's agricultural machines. Enhancement of IT system for Analytical Application. Implementation of ML model assumptions, expansion of standard FMIS with additional modules.

Technological progress in agriculture and its surroundings resulting in acces to more and more information that can be used for optimizing production planning and management. CGFP Ltd. has implemented and developed advanced precision farming systems from 2014. As a result, a huge database that is constantly expanding has been gathered. The problem is how to make the best use of this data due to limited processing capabilities. The process of making decisions based on findings derived from available information has obvious limitations, resulting in only partial use of the data and a risk of large error in the conclusions. It became a necessity to look for possibilities to use the data in a different way. Therefore, there was a need to acquire a tool that meets several basic objectibes such as collecting and analyzing historical and current data from all available sources in one place, interpolating and extrapolating data in case of incompleteness, predicting events and values, and drawi

A favorable aspect in the implementation of the result achieved is the agricultural knowledge and experience of the Project Leader. CGFP Ltd. has implemented an advanced precision farming systems. The project was designed to eliminate many of the most common obstacles and inconveniences associated with the implementation of FMIS systems. The project will result in a new application suitable for implementation on farms with different levels of PF, open to customization. One of the main goals is to improve the processes involved in managing field production by predicting events and values, as well as drawing conclusions and initiating specific processes. This streamlines management, but also minimizes user involvement with the application itself. A small risk is associated with the short project period (two vegetation seasons) in relation to the scope of the study. The project teamt suggests continuing the research work in the next growing seasons, which can broaden conclusions, as we

The project will result in the elaboration of an information system that will support the agricultural farmer in the three main areas through continous data collection and ongoing analysis. The first is to optimize the fertilizer system to achieve the best economic effect, preserving soil fertility and biodiversity while reducing the costs associated with fertilizer application. The second is to support the management of machine operations, which will allow ti improve logistics processes, optimize the use of existing machine and tool resources and human resources, thereby reducing the consumption of fuel, machine working parts, or reducing the occurrence of failures due to improper operation. the third area of support will be improving process of harvesting, transporting and storing agricultural crops. Implementation of the project's results will contribute to both improving the economic effciency of production and protecting the environment, especially in terms of preserving biodiversity, which determines the soil fertility, and mitigating climate change by reducing emissions of harmful emissions to the environment.

The operation will result in the development of an information system dedicated to farm management support with extensive machine learning applications. By analyzing the factors affecting yield potential, the system will make yield predictions. Taking into account environmental and biological factors and their spatial variation, it will determine optimal fertilizer application rates. It will create varying fertilizer dosage scripts and send them to the machines. The machine management module will determine the reference values of parameters for each job under different conditions. This will allow streamlining logistics processes, optimizing the use of existing resources, and thus reducing machine labor costs. The process of harvesting, transporting and storing agricultural crops will be improved thanks to the recording and control function. Equipment and machinery (harvesters and transporters) will exchange the necessary data about the agricultural plot from which the crop was harvested. The application will collect the informations to the unloading location. Upon arrival at the warehouse, data regarding transportation will be loaded into the weighing system.

agricultural production system