SATIVUM is one of ITACyL's key projects; it consists in a free web app that helps farmers by providing data-driven insights to improve crop productivity and sustainability. It has three main features:

1. Access to soil, climate, and crop data: SATIVUM integrates information from sensors, satellites, weather data from AEMET, and databases (e.g. soils), in an easy-to-use interface, with the aim of help farmers manage their plots, increasing yields and productivity. Information is provided at plot scale.
2. Decision-making tools: It offers tools based on scientific data, agronomic models and legislation, among others. In this way, SATIVUM includes tools for the monitoring of the crops through Sentinel – 2 satellite images, a fertilization module, pest alert calendars, tools for zoning plots in order to make variable rate application (VRA), Farm Digital Notebook, information about soils, etc. These tools help farmers to reduce costs, emissions, and improve soil health.
3. Interoperability: SATIVUM’s data and models are accessible to third-party digital tools, promoting an open policy data reuse. The APIs are public. The continuous and modular development of the platform is allowing it to integrate with SIEX, which will be a set of interconnected databases and administrative registers, with information about agrarian holdings in Spain.

SATIVUM is accessible from any device (desktop computer, tablet or smartphone) equipped with an Internet browser. Users only need internet access to obtain satellite images and NDVI data for crop monitoring. After receiving the data, they can continue using the tool offline which works with the data stored in the web browser. The frontend is made in Vue (JavaScript) that communicates with the backend through REST services in Java. Some of the modules have been also in Python or flask. The data is stored in Oracle databases, and the searches use PostgreSQL.

• Tech #1 – SATIVUM

The ODOS solution for apple orchards, developed by Carbon Harvesters, is a comprehensive environmental management system designed to monitor, mitigate and report on carbon emissions and biodiversity impacts. This technology is primarily used to help orchard owners and managers improve their sustainability practices and comply with increasingly stringent environmental regulations. The solution consists of a sophisticated software platform that integrates data from various sources, including on-site sensors, satellite imagery, and manual inputs from farmers. This platform serves as a central hub for all environmental data related to the orchard's operations.

Key functionalities of the technology include: 

Environmental Impact Monitoring: The system tracks carbon emissions from various orchard activities, such as machinery use, fertilizer application and transportation. It also monitors biodiversity indicators, including soil health, pollinator populations, and native plant species. 

Mitigation Strategy Development: Based on collected data, the platform uses advanced algorithms to suggest tailored mitigation strategies. These may include
recommendations for optimizing irrigation, reducing chemical inputs, or implementing agroforestry practices.

Automated Reporting: The system generates comprehensive reports that comply with various environmental standards and regulations, saving time and ensuring accuracy in sustainability reporting.

Predictive Analytics: By analyzing historical data and current trends, the platform can forecast future environmental impacts and help farmers make proactive decisions. Integration with Existing Farm Management Systems: The solution can be seamlessly integrated with other farm management tools, providing a holistic view of the orchard's operations.

• ODOS Insight

Pastures must be maintained when cattle are raised for grazing. One of the operations is the disposal of plants that remain after grazing. Our technology enables the automation of this operation. The essence of the GrassGuard technology is the imaging of pastures using a flying drone, the creation of a georeferenced map, the detection of weed (ungrazed) areas to be mowed/mulched and their subsequent removal using a land drone.

The technology should be semi-autonomous. The flying drone takes pictures by taking off from a designated place, automatically photographing a designated area of pasture and returning back to the starting place. Subsequently, a georeferenced map of the scanned area is created, identifying places with weeds that have not been grazed by cattle on the map. According to the created georeferenced map, a route plan is created for mowing/mulching of the weeds by the land drone.

In order to make this technology available to the widest possible spectrum of farmers, we assume the use of cheap images from RGB cameras. These images are then combined in SW Pix4D into a geographically oriented orthophoto of the pasture. Using an algorithm developed using artificial intelligence, individual orthophotos are evaluated and ungrazed areas are determined.

Obtaining aerial images using flying drones is now at a very user-friendly level of development. Based on the experience gained from a pilot farm (ZD Kvetna – Czech Republic), it can be stated that by choosing a suitable flying drone, a farmer user can start using it almost immediately without previous experience except the knowledge of how to operate a mobile phone.

The main barrier is represented by the processing of the photos the main effort in developing the technology is now focused on making this phase as simple as possible for farmers.

• Tech #3 – GrassGuard

The CERERE platform is an innovative Decision Support System (DSS) designed to enhance sustainable agriculture by addressing critical farming challenges, such as water scarcity, crop disease, and vegetation stress. By merging traditional farming methods with precision agriculture, CERERE empowers small to medium-sized farmers with datadriven tools that improve resource management, monitor crop health, and support timely, informed decision-making.

CERERE’s technology leverages data from local weather stations, satellite imagery, and AI-driven analytics to deliver real-time insights directly to farmers. The platform’s main interface includes a map view with key vegetative indexes like NDVI (Normalized Difference Vegetation Index) to assess crop vigor, identify stress zones, and allocate resources more efficiently, and a dashboard that compiles and visualizes data for easy access.

CERERE focuses on the integration of weather data, providing real-time and forecasted information from local stations, which includes temperature, humidity, precipitation, and wind conditions. This integration supports accurate irrigation management by calculating evapotranspiration rates, essential for understanding crop water needs. The platform provides targeted irrigation recommendations.

Additionally, CERERE’s disease monitoring module analyzes historical and forecasted weather data to predict conditions that may foster crop diseases, such as mycotoxins in corn and botrytis in strawberries. By identifying high-risk conditions, CERERE enables farmers to implement proactive crop protection measures, such as adjusting irrigation or applying fungicides.

CERERE equips farmers with actionable insights that respond to environmental challenges, promote efficient resource use, and support sustainable farming. Through its intuitive interface and predictive analytics, CERERE helps farmers adapt to climate variability, optimize crop management, and transition to more sustainable agricultural practices.

• Tech #4 – CERERE

The SwarmSense Beehive System is used for monitoring various parameters of beehives, such as temperature, humidity, and sound wave data. This technology aims to provide valuable information about the health of the bees and detect any potential dangers, such as predator species invading the hive.

This technology can solve several problems related to beekeeping, including: (i) reducing the need for frequent human intervention disturbing bees; (ii) providing early warnings about potential threats to the hive, such as predators or health issues; (iii) increasing the productivity of beehives by ensuring optimal conditions for the bees. 

The Beehive Monitoring System consists of sensors and software. The sensors are used to collect data on various parameters inside and out of beehive, while the software processes and analyses this data to provide insights and alerts to beekeepers.

The main functionalities of the technology are:

• Tech #5 – SwarmSense

FLOX Robotics provides a high-tech solution to manage human-wildlife conflicts in agriculture, using advanced AI and autonomous drones to protect crops from wildlife damage. Wildlife encroachment on farmlands leads to substantial crop loss, impacting farmers’ economic stability. FLOX’s innovative technology offers a scalable, efficient, and humane alternative to traditional methods like fencing or manual deterrents, which are often costly and labor-intensive.

At the core of FLOX’s solution are machine learning algorithms and AI combined with sensors, enabling precise detection and real-time species identification. Once animals are detected, the system applies species-specific acoustic signals to gently herd them away from fields, minimizing habituation and ensuring long-term effectiveness. This sophisticated system is accessible to users through an intuitive web and mobile platform, providing real-time updates, wildlife activity analytics, and a customizable platform that allows farmers to monitor and manage the solution from anywhere.

FLOX’s drones can autonomously patrol designated areas, ensuring continuous protection with minimal intervention. Future integrations with docking stations will support autonomous charging and data uploading, optimizing 24/7 operation. For farmers, the benefits are significant: FLOX’s service reduces crop losses, supports yield increase, and enhances sustainability by avoiding invasive barriers. By empowering farmers to prevent wildlife-related damages proactively, FLOX Robotics fosters a balanced coexistence between agriculture and nature, making farming more sustainable and economically viable.

• Tech #6 – Wildlife herd

EcoWard is a technology developed to help small to medium livestock farms manage and monitor their greenhouse gas (GHG) emissions more effectively. The main goal is to provide small farmers with a practical and affordable way to monitor emissions accurately. EcoWard consists of a methane NIR (Near Infrared) detector (often referred to as a “sniffer”) that is installed in the automatic milking system (AMS) feed bin, and a software platform for data interpretation and visualization. The hardware device measures methane concentration by detecting eructation peaks (which account for most methane emissions from digestion) and reports GHG emission rates (ppm/day). The software component processes the collected data and combines it with life cycle analysis (LCA). Farmers provide information on their livestock, feeding, and manure management practices, and the platform applies IPCC calculations to assess the GHG balance.

EcoWard aims to improve cooperative planning by allowing cooperatives to track sustainability across multiple farms, promoting strategies to reduce emissions. One significant advantage is that cooperatives, rather than individual farmers, take on the responsibility of training and data handling. This reduces the burden on small farms, which often operate with minimal labour resources. EcoWard addresses a major market gap as existing commercial GHG sensors cost ten times more and have annual fees of €10,000 per unit. With this more accessible technology, farmers can identify animals with lower emissions, helping them select more efficient, high-yield cattle, which not only improves productivity but also reduces the carbon footprint of dairy production. This approach supports cooperatives as they work toward offering low-carbon footprint dairy products and ensures that even small farms can remain viable and competitive in an increasingly sustainability-driven market.

• Tech #7 – EcoWard

Biodiversity above and below ground has a direct effect on any farm. Monitoring biodiversity using traditional methods can be costly and is often time sensitive (e.g. can only be done during flowering seasons) and requires expert knowledge. Furthermore, a large section of organisms in the soil are microscopic and part of the invisible biodiversity of a farm. We are therefore developing a technology called environmental DNA (eDNA) that uses molecular biology methods to detect DNA-molecules that organisms leave behind in the environment. These genetic traces can provide biodiversity data in a more cost-efficient way than traditional methods. In GUARDIANS we are applying the technology on farms practicing semi-natural grazing and are focusing the development on analysis of vascular plants, and the seed bank of the soil (dormant seeds receding in the soil). In addition, soil health, represented by the composition of the microbial community, is also incorporated in the analysis.

Our solution consists of:

1) sampling equipment and methods that can be used by non-experts,
2) molecular biology methods for handling DNA and
3) bioinformatic practices for analyzing data.

The technology is envisioned to enhance the farm's credibility in promoting biodiversity, and potentially boost meat sales volume and allow for premium pricing. As a complement to certification, the technology can provide direct data on the effects on biodiversity of management practices associated with a product.

• Tech #8 – Genetic Biodiversity Survey

Chainspector is a customizable traceability platform for small and medium sized farmers, enabling them to showcase the origin and quality of their products. As part of the GUARDIANS project, Chainspector focuses on three key objectives: adaptability across different products, empowering small farmers to highlight the unique story of their products and delivering reliable environmental impact data directly to consumers.

Chainspector’s adaptability will be tested across diverse products, allowing continuous improvement based on real-world use. This will offer farmers a "white canvas" to communicate their product's origin, quality, and sustainability practices—an advantage that small farmers, like family-owned cattle and vegetable farms, can use to reach consumers who value transparency. With Chainspector, these farms aim to expand direct-to-consumer and online sales, differentiating their products and increasing profitability. Chainspector also integrates carbon footprint metrics, enabling consumers to access reliable environmental impact data. This transparency distinguishes products from those with “greenwashed” claims, reinforcing consumer trust in sustainably produced foods.

Chainspector’s core technology securely saves data on a blockchain and stores it in a decentralized system. Another feature helps protect sensitive information by securely managing blockchain transactions. Producers use a registration app to log traceability events while consumers access product histories via a consultation app by scanning a unique identifier. This consumer app displays trace data as linked cards with visuals, certifications, and impact data. Chainspector’s flexibility allows it to capture a range of data types, including fair income and social impact metrics, supporting small farms in presenting an authentic, transparent story to the market.

• Tech #9 – Chainspector

The implementation of the innovative technologies depends on whether farmers know, are willing to use and finally can use those technologies, and whether they can be optimized to each context.

Once a prototype of a technology is released, a preliminary evaluation under controlled conditions (in a testbed) will help to adjust it to the final user needs and conditions and validate the technology at Technology Readiness Level (TRL) 5.

Any shortcomings highlighted during this testing phase will prompt an iterative development process of the digital tools until all technologies can be further moved to the pilot cases.

The innovative technologies in the GUARDIANS project can be categorized into two groups based on the outcomes: those requiring physical testing at the farm level and those relying on datasets from Regional Service for Agri-food Research and Development (SERIDA) located in Asturias (northwest Spain).

Four experimental farms owned by SERIDA work as testbeds in the GUARDIANS project. They represent diverse European environmental and socioeconomic contexts, and key agricultural typologies (arable crops, woody crops, regenerative agriculture and grazed grasslands for livestock). Each farm is tailored to specific agricultural practices and can be used to address diverse technological challenges.

Regarding the preliminary tests for technologies based on artificial intelligence or developments, the datasets obtained from prior scientific studies developed in the experimental farms can either improve new or existing models, or even adjust existing ones to new contexts.

• Testbeds for GUARDIANS

Regenerative agriculture, as defined by EIT Food (2024), is a system of farming principles and practices that increases biodiversity, enriches soils, improves watersheds and enhances ecosystem services. Resulting in increased yields, increased resilience to extreme weather events and climate change, and higher health and vitality for the rural communities.

Regenerative agriculture works according to a whole ecosystem approach, meaning aiming to work with nature instead of against it. For farm management decisions, the whole farming ecosystem is considered. All the stakeholders that are affected are also taken into consideration and mutually beneficial relationships are established between them. The farm is a dynamic environment and continuous improvement, and growth is pursued to utilize the full potential of the farm, community and individuals.

The most important aspect of regenerative agriculture is soil health in a holistic agroecosystem. In the end, your soil is the most valuable asset of the farm. If you take care of your soil, it will take care of you. Minimizing soil disturbance by adopting conservation tillage and minimizing chemicals and biological activities are fundamental practices of regenerative agriculture. Large amounts of CO2 are released during plowing activities and at the same time the soil is exposed to erosion. 

Five principles that guide the approach, as outlined by Khangura et al. (2023), are as follows:

Minimum tillage and no-tillage is a farming practice that involves disturbing the soil as little as possible while still preparing it for planting crops. Unlike traditional tillage methods that deeply disturb the soil through plowing or cultivation, minimum tillage aims to maintain soil structure, reduce soil erosion, and preserve soil moisture by minimizing soil disturbance.

A global meta-analysis, utilizing data from 678 peer-reviewed publications, evaluated the impact of various crops and environmental variables on no-tillage yields relative to conventional tillage. The study highlighted regional variations, with yield reductions observed in tropical regions with maize-based systems, while arid regions with moisture limitations experienced yield improvements (Pittelkow et al., 2015).

Although it's established that no-tillage leads to surface-layer increases in soil organic carbon, this increment could be offset by declines in soil organic carbon between depths of 10 to 60 cm due to slower incorporation of crop residue into these soil layers under no-tillage. Consequently, it may take up to a decade to observe a net benefit of no-tillage compared to intensive tillage (Burgess et al., 2023).

Despite the benefits of no-tillage practices in boosting soil organic content, concerns persist regarding heightened N2O emissions (Khangura et al., 2023). Another major issue with no-tillage is the overuse of herbicides for weed control, which could cause environmental pollution and resistant weeds, and threatens human health. (Khangura et al., 2023).

While reduced tillage practices exhibit mixed effects on soil biodiversity and ecosystem services, further studies are warranted, given the variations observed not only across organism groups but also among soils, regions, and specific management practices (EASAC, 2022).

Cover crops are cultivated plants grown during the off-season, typically replacing bare fallow periods, and are often plowed into the soil as green manure before the next main crop is sown. There are two main categories of cover crops: those consisting of legumes, which have the potential to increase soil nitrogen levels, and those comprising non-leguminous plants. Interest in the use of multi-species mixtures for cover cropping is also on the rise (Burgess et al., 2023).

Global meta-analyses have consistently shown that cover cropping, whether with legumes or non-leguminous plants, can substantially enhance soil carbon levels compared to leaving fields fallow, typically within a three-year timeframe (Abdalla et al., 2019; Morugán-Coronado et al., 2020; Jian et al., 2020). Additionally, cover cropping promotes similar or greater plant biodiversity compared to leaving fields fallow (Guzmán et al., 2019) and can lead to increases or alterations in fungal biomass (Drost et al., 2020; Murrell et al., 2019). It also has the potential to suppress weed growth (Osipitan et al., 2019), although some studies show no significant effect on arthropod and earthworm communities (Fiorini et al., 2022).

Apart from improving soil fertility, cover crops play a crucial role in carbon sequestration, and widespread adoption could potentially reduce agricultural greenhouse gas emissions by up to 10%, which is comparable to the impact of practices such as no-till farming (Kay and Quemada, 2017). However, significant increases in soil carbon may take several years to manifest (Poeplau and Don, 2018).

Abdalla, M., Hastings, A., Cheng, K., Yue, Q., Chadwick, D., Espenberg, M., Truu, J., Rees, R.M., Smith, P. (2019). A critical review of the impacts of cover crops on nitrogen leaching, net greenhouse gas balance and crop productivity. Global Change Biology 25, 2530-2543.

Polyculture refers to a farming or gardening practice where multiple species of plants are cultivated together in the same area, as opposed to monoculture, which involves growing just one type of crop. In polyculture, different plant species are strategically chosen and intermixed based on their complementary traits and interactions, such as nutrient uptake, growth habits, and pest resistance. Polyculture can take various forms, including intercropping, agroforestry, and mixed cropping, and is often employed in sustainable agriculture and permaculture systems. EASAC (2022) has identified several polyculture practices and assessed their contributions to carbon capture and increased biodiversity:

Crop rotation is a farming practice where different types of crops are grown sequentially on the same piece of land over a defined period. Planting different crops in succession results in yield benefits compared to continuous cropping, with the effect greatest if the crops come from different botanical families. Relative to continuous cereal cropping, the practice also results in higher biodiversity and soil carbon (Burgess et al., 2023). Crop rotation is providing nutritional benefits and break the pest–disease–weed cycle (Khangura et al., 2023). A meta-analysis of 122 studies on the effects of crop rotation on soil biological properties found that rotation significantly increased the soil microbial biomass C and N by 20.7 and 26.1%, respectively (McDaniel, et al., 2014).

Some research has found that diversified crop rotation improves plant resource use efficiency by increasing microbial functions (D’Acunto et al., 2018). To increase soil organic content and improve soil health, rotational grazing is preferred over continuous grazing (Khangura et al., 2023).

Burgess. P.J., Redhead, J., Girkin, N., Deeks, L., Harris, J.A., Staley, J. (2023). Evaluating agroecological farming practices. Report from the “Evaluating the productivity, environmental sustainability and wider impacts of agroecological compared to conventional farming systems” project SCF0321 for DEFRA. 20 February 2023. Cranfield University and UK Centre for Ecology and Hydrology.

D’Acunto, L., Andrade, J.F., Poggio, S.L., Semmartin, M. (2018). Diversifying crop rotation increased metabolic soil diversity and activity of the microbial community. Agric. Ecosyst. Environ., 257, 159–164.

Khangura, R., Ferris, D., Wagg, C., Bowyer, J. (2023). Regenerative agriculture—A literature review on the practices and mechanisms used to improve soil health. Sustainability 15(3), 2338.

Grazing is a method of feeding livestock, such as cattle, sheep, or goats, by allowing them to consume vegetation in a pasture or range area. It involves the controlled movement of animals through designated grazing areas to ensure they have access to sufficient forage while preventing overgrazing and ecosystem degradation.

Land-use change from arable land to grasslands increases carbon capture and storage as well as biodiversity. It is essential to distinguish between its effects on above-ground and soil biodiversity, which may or may not be correlated. The positive impacts of transitioning from arable land to grasslands often do not align with agricultural production, representing a significant trade-off (EASAC, 2022).

A strategy known as multi-paddock grazing has garnered increasing attention in recent years. It refers to rangeland management where the grazing unit has livestock on it for less than 10% of the time (Rhodes, 2017). It is also known as “holistic planned grazing” (Teague et al., 2016) and has been called a regenerative practice (Teague and Barnes, 2017). Like most grazing systems it minimises soil tillage and bare ground, but it also includes more complex rotations. It has also been termed “pulse grazing” and a “permaculture approach to rangeland management” (Rhodes, 2017). In terms of increasing soil carbon and retaining nitrogen stocks, adaptive multi-paddock grazing outperforms conventional grazing (Mosier et al., 2021).

The net effect of grazing on agroecosystems depends on various factors, including grazing intensity, animal type, habitat type, and characteristics of the grazing regime such as timing and duration (D'Ottavio et al., 2018; Bengtsson et al., 2019).

Bengtsson, J., Bullock, J.M., Egoh, B., Everson, C., Everson, T., O’Connor, T., O’Farrell, P.J., Smith, H.G., Lindborg, R. (2019). Grasslands — more important for ecosystem services than you might think. Ecosphere 10 (2), e02582.

Semi-natural grazing refers to a form of livestock management that integrates livestock grazing with the maintenance or restoration of semi-natural grasslands or other ecosystems. Unlike intensive or continuous grazing systems commonly associated with modern agriculture, semi-natural grazing seeks to mimic the historical grazing patterns of wild herbivores in natural ecosystems.

Approximately 30% of agricultural land in the EU falls under High Nature Value (HNV) farming management (Keenleyside et al., 2014), yet CAP support for 'Management of landscape, pastures, and HNV' covers only 8% of the utilized agricultural area (Strohbah et al., 2015).

Farming systems in these HNV areas provide productive, environmental, and societal services, showcasing a multifunctional role that merits recognition from both society and policymakers. Spatial and temporal diversification of these habitats, ideally in a mosaic of land covers with diverse species composition and structure, enhances local biodiversity and the provision of ecosystem services (Bullock et al., 2006). Semi-natural grasslands stand as some of Earth’s most species-rich ecosystems, exemplifying how enduring, low-intensity human activities may lead to an outstanding biodiversity (Wilson et al. 2012; Habel et al. 2013; Dengler et al. 2014). Alongside climatic, topographic, and edaphic conditions, management practices significantly influence plant species richness
in semi-natural grasslands. Traditional, extensive management methods, such as grazing or mowing, typically sustain high diversity, not only among plants (EASAC, 2022).

Bullock, J.M., Pywell, R.F., Walker, K.J. (2006). Long-term enhancement of agricultural production by restoration of biodiversity. Journal of Applied Ecology 44 (1), 6-12.

Dengler J., Janišová M., Török P., Wellstein C. (2014). Biodiversity of Palaearctic grasslands: a synthesis. Agriculture, Ecosystems & Environment 182, 1-14.

Pollinators play a crucial role in agriculture by facilitating the process of pollination, which is essential for the reproduction of many flowering plants, including a significant portion of crop species.

The cultivation of pollinator-dependent crops has seen global expansion, heightening our reliance on insect pollination (Osterman et al., 2021). Recognizing the important role of pollinators in agriculture, it becomes imperative to conserve and safeguard pollinator populations and their habitats. Implementing measures such as maintaining diverse landscapes, reducing pesticide usage, providing nesting sites and forage resources, and promoting pollinator-friendly agricultural practices are crucial steps towards supporting pollinator health and ensuring their sustained contribution to agriculture.

There are not only wild pollinators, the society also manages pollinators. Global trends in the number and diversity of managed pollinator species have been studied by Osterman et al. (2021). While the Western honeybee (Apis mellifera) stands as one of the most closely monitored insects, the status of other managed pollinators remains less well documented. Osterman et al. (2021) identify 66 insect species either currently managed for crop pollination or considered to have potential for such management. To ensure sustainable and integrated pollination management in agricultural landscapes, it is imperative to carefully assess both the risks and benefits associated with both old and novel managed pollinator species.

Osterman, J., Aizen, M.A., Biesmeijer, J.C., Bosch, J., Howlett, B.G., Inouye, D.W., Jung, C., Martins, D.J., Medel, R., Pauw, A., Seymour, C.L., Paxton, R.J. (2021). Global trends in the number and diversity of managed pollinator species. Agriculture, Ecosystems and Environment 322, 107653.