• Strategic Objectives 2024–2027

    We support the agri-food sector in its meaningful digital transformation

  • 1.

    How can new digital technologies help the agri-food sector?

  • 2.

    How can we use them to contribute to sustainability and resilience?

  • 3.

    Can they provide an opportunity to facilitate generational renewal?

The Catalan agri-food sector must undergo digitalisation with the aim of becoming more environmentally, socially and economically sustainable. We can be agents of change, not mere spectators.

What is happening?

Artificial intelligence, sensor technology, robotics and Industry 5.0 are rapidly changing our lives.

 

In the case of agriculture, livestock farming, aquaculture and the agri-food industry, digitalisation represents a revolution on a par with mechanisation or the introduction of plant protection products and fertilisers.

 

At IRTA, we want the Catalan agri-food sector to be a leading player in this digital revolution. We want new technologies to help it transform itself to become more sustainable:


Economically: We want digitalisation to contribute to the prosperity of producers and the industry in the face of major global challenges, such as climate change or geopolitical tensions.

 


Environmentally:
We want new technologies to be an ally in mitigating or reversing the environmental impact of the agri-food sector.

 


Socially: We want all of this to encourage new generations to join this sector, which is essential for the preservation of the rural world as the foundation of food self-sufficiency.

 

 


What are we working on?

We structure our work around the so-called data cycle:

Data captation using sensors

Data captation using sensors

  • Capturing data using sensors is the foundation of digitalisation
  • Sensors are already an integral part of many agricultural tools, instruments and machinery, as well as satellites and drones, and can be found at every stage of the agri-food chain
  • They are becoming increasingly accessible, both financially and technologically

 

Some examples of their applications:

  • Some allow us to determine the quality of a piece of fruit without damaging it
  • Others are installed on farms, or in aquaculture cages, tanks and ponds, to monitor animal health and welfare
  • And some are used in the food industry to assess the quality and condition of food

Wireless transmission

Wireless transmission

  • Sending data captured by sensors to the cloud is becoming increasingly affordable and rapid to: we call this the Internet of Things (IoT)
  • This is particularly useful in agriculture, where sensors may be mounted on vehicles and cannot be connected by cables
  • The cloud allows data collected from different points to be centralised and processed on high-performance servers

Collection in databases

Collection in databases

  • Data collection platforms allow data to be stored in large volumes
  • The data are managed securely and in a structured manner to facilitate traceability
  • The possibilities offered by the ability to analyse this data present both a challenge and a great opportunity

Analysis using artificial intelligence (AI)

Analysis using artificial intelligence (AI)

This offers a wide range of possibilities:

  • Identifying and detecting objects in images or videos to extract their characteristics, using what is known as computer vision
  • Predicting how the quality and safety of food products will evolve using predictive models, such as machine learning algorithms
  • Understanding and responding to queries made by humans, through large language models

 

We want to make all these possibilities available to the sector and make the most of them.

Applications in agriculture, aquaculture, livestock farming and the food industry

Applications in agriculture, aquaculture, livestock farming and the food industry

Making decisions based on the data we have collected and analysed enables us to be more precise and to adapt management strategies to the variability of crops, livestock or products. For example, we can:

  • Apply water, fertilisers or plant protection products precisely according to the characteristics of different areas within the same plot. This is known as precision agriculture
  • Provide each animal or group of animals, based on their individual or group needs, with a concrete quantity of specific feed. This is known as precision livestock farming or aquaculture
  • In the food industry, determine the quality of a product such as Serrano ham without altering it, using images and AI. This is known as smart or precision processing
  • Furthermore, the use of data and new technologies allows us to automate and free up repetitive, heavy or dangerous tasks through robotics

Despite their potential, there are still barriers to overcome in the aim of expanding the use of these technologies in the agri-food sector:

  • Clearly identify the added value they can bring
  • Train potential users so they can use them and know which ones to choose
  • Have the financial resources to implement them
  • Adapt them to the agri-food sector, as many of them were designed for other sectors

At IRTA, we aim to understand what technologies our agri-food sector needs at every stage of the data cycle and to provide accurate information so that every producer and every industry can make the most appropriate decisions with the focus on sustainability.

 

Until 2027, we have decided to prioritise research and innovation in the following areas:

  • Digital Agrolabs (1)

    We have created spaces at IRTA centres where we can test and experiment with new digital technologies.

    We conduct our own research in these spaces, and they are also available to companies and organisations in the sector.

  • Digital Agrolabs (2)

    We are launching a cloud-based platform to provide data and services to businesses in the sector.

    It will bring together all the research and innovation we are undertaking in the field of new technologies:

    – Two tools to recommend new varieties of fruit and cereals suited to our climatic conditions, which obtain data from the sensors we have installed across three thousand plots in Catalonia

    – A tool providing information and recommendations from IRTA professionals on the hundreds of digital products currently available on the market

    – A tool to help producers determine the best time to remove fruit from cold stores

    – A digital twin, or virtual replica, of apple orchards, which enables any explotation to be modelled and all its characteristics to be understood, allowing it to be managed with the utmost precision

    – A tool for assessing the risks of crop pests and diseases

    – A tool to predict the proliferation of toxic algae in mussel and bivalve farming

    – And the BDporcdatabase, which we have been managing for decades, and which will also be incorporated into this platform

    BDporc
  • Digital twins

    We are committed to virtual replicas in our sector.

    We will create a digital twin, or virtual replica, of apple orchards to learn how to manage them with the utmost precision.

    We will also explore the potential of digital twins on pig farms and within the food industry.

  • Precision agriculture

    We are preparing to become experts.

    With staff and infrastructure specialised in this field that is set to transform food systems.

And we are not doing this alone: we are doing it in partnership with organisations, companies and public authorities, because we are convinced that working together and with generosity is the only way to respond to the great challenges of our time.

Ongoing projects

ACTIVE PROJECT
  • Start date: 06/02/2024

  • End date: 22/09/2026

  • Project Code: V7049_15586

  • Acronym: FruitMeasureApp

FruitMeasureApp - FruitMeasureApp - Validation and prototyping of an AI-based mobile application to measure fruit in the field

View project

PROGRAM

RESPONSIBLE

PROJECT TYPE

  • DEMOS DACC
ACTIVE PROJECT
  • Start date: 01/09/2025

  • End date: 31/08/2029

  • Project Code: V7067_16819

  • Acronym: YIELD4CAST

YIELD4CAST - Advancements in predicting crop yields under climate change and water scarcity scenarios through the integration of crop models, remote sensing, and computer vision

View project

PROGRAM

RESPONSIBLE

PROJECT TYPE

  • Plan Estatal (Agencia Estatal de Investigación)