Generation of Agronomic Data from Experimental Crops

Organisations developing agricultural technologies need to test and validate their solutions under real agricultural conditions to assess their performance before deployment in commercial farming, This service provides access to AGACAL-CIAM´s experimental crops and research infrastructure for testing and validating agricultural technologies, including AI, machine learning, robotics and other digital applications. Agronomic data generated through experimental trials and field observations are available as a complementary resource to support these activities. This help users to: Test agricultural technologies under real growing conditions. Assess the accuracy, performance and reliability of their solutions. Use complementary agronomic data to support testing and validation. Identify limitations and reduce development risks before deploying technologies in commercial agricultural settings.

The service consists of generating and providing agronomic data from AGACAL-CIAM’s experimental research trials according to the customer’s requirements and data availability. Current-season data are generated according to the crop calendar, while historical agronomic data can be provided for crops previously studied. For seasonal crops, the service typically covers one complete growing cycle (approximately 5 to 6 months), from crop establishment to harvest. For applications requiring the monitoring of annual or perennial cropping systems, the service can be extended to cover up to one full year. The service is provided by AGACAL-CIAM (Mabegondo, A Coruña, Spain). There are no geographical restrictions for customers, as data are delivered digitally. To deliver the service, AGACAL-CIAM reviews each customer request to assess the availability of the requested data, taking into account the relevant expeirmental trials, observation periods and variables of interest. The scope of the service, including the data to be provided, the delivery format and the expected delivery timeframe, is agreed with the customer based on this assessment. For current-season data, delivery depends on the crop calendar and the progress of the relevant trials. Historical date are subject to availability and applicable data-sharing and intellectual property condicions. The customer will receive the agreed agronomic data together with available documentation describing the experimental conditions, measured variables, data collection methods, and any other relevant information. Data can be provided in mutually agree standard fromats, either as raw or processed data, depending on the service requirements. Data and accompanying documentation are delivered digitally through an agreed alectronic channel. To request the service, the customer should specify the intended application, crop(s), variables of interest, and the required observation period. The scope of the service will be agreed according to data availability, ongoing research activities, and the applicable data-sharing and intellectual property conditions.

The service can be customised according to the customer’s objectives and data requirements, including crop type, variety, observation period (current season, historical records, or both), agronomic variables, and level of data preparation. Where available, additional information such as environmental observations, soil characteristics, crop management practices, or data from available technologies and external data sources can be included. The final scope of the service will be agreed with AGACAL-CIAM in consultation with the leader of the relevant research line, who will assess the availability of data, resources and the feasibility of any additional data generation. Current-season data generation is subject to the agricultural calendar and the growing cycle of the selected crop. Historical data are limited to the existing records from AGACAL-CIAM experimental research programmes. The availability of specific datasets and variables depends on the scope, technology available and methods of the relevant experiments.