Agricultural Soil Analysis
Explore how teams apply the project in different contexts. These demo analyses apply a simple, privacy-preserving algorithm to datasets from individual fields on the Azores Islands and in inland Portugal. Each card summarizes key structural and fertility indicators derived from raw soil measurements—without exposing sensitive or granular data. The algorithm counts farms, fields, analysis events, and measurement density to create a high-level diagnostic snapshot.
These basic insights help teams understand typical data flows in the agriculture data space, explore Compute-to-Data execution, and evaluate how soil information can support decisions on fertilization, irrigation, and crop management.
Featured cases
Monitoring soil health in a dairy cow silage system (Azores, Portugal)
This pilot focuses on monitoring soil health in a dairy cow production system dedicated to maize and ryegrass silage in the Azores. Its main goal is to assess how conventional, high-input management practices affect soil quality and microbial activity, and to establish a baseline for transitioning towards regenerative practices. The pilot emphasizes the use of measurable soil indicators to support evidence-based decision-making while ensuring that farmers retain full ownership and control over their data. More info
Monitoring regenerative pasture practices in dairy goat farming (Beira Baixa, Portugal)
This pilot focuses on monitoring the impact of regenerative pasture management in a dairy goat farming system in the Beira Baixa region. Its main goal is to demonstrate how biodiverse, low-disturbance pastures improve soil health, biodiversity, and nutrient cycling under Mediterranean conditions. The pilot supports the adoption of regenerative practices by providing objective soil health evidence, while preserving farmers’ data sovereignty and control over how their information is used. More info
Monitoring grazing and soil disturbance regimes in beef cattle systems (Beira Baixa, Portugal)
This pilot focuses on monitoring soil health under different grazing and soil disturbance regimes in an organic beef cattle system in Beira Baixa. Its main goal is to compare grazed, no-till, and ungrazed plots to better understand how management choices influence soil functionality and microbial communities over time. The pilot enables data-driven evaluation of regenerative grazing practices while ensuring full data ownership and control remain with the farmer. More info
Effect of rotational grazing systems and regenerative practices in soil health (Alentejo, Portugal)
This pilot assesses the benefits of rotational grazing and long-term regenerative practices in the Alentejo region. The focus is on optimizing grazing efficiency through rotational paddocks to allow grass recovery. The study highlights that grazing alone is not sufficient; soil analysis and correction are essential to restore soil function and long-term productivity. More info
Comparative analysis of grazing regimes in soil health (Beira Baixa, Portugal)
This pilot compares soil health outcomes under different grazing regimes in an organic farm in Beira Baixa. It demonstrates that organic management alone is not sufficient to resolve soil nutrition and productivity issues. The use of adaptive grazing and techniques like bale grazing are essential to improve organic matter and micronutrient availability. More info
Comparative analysis of different management regenerative practices in different plots (Azores, Portugal)
This pilot explores the variability of soil properties and microenvironments within a single farm in the Azores. By comparing different management practices and implementing direct sowing, it shows how localized soil analysis and regenerative practices are fundamental to restore productivity and mitigate biotic risks in diverse environments. More info
Implications of the introduction of Barbela wheat with covercrops (Alentejo, Portugal)
This pilot assesses the influence of autochthonous Barbela wheat and cover crops on soil health in a transitioning regenerative operation in Alentejo. It highlights the benefits of using resilient, indigenous crop species to improve soil nutrition, increase total nitrogen, and reduce the C:N ratio, favoring more active organic matter. More info
Extended Multi-Farm Dataset (23 analyses / 9 farms)
Extended Soil Monitoring Across Multiple Farms
This use case showcases a more advanced algorithm designed to operate on a richer dataset containing 23 analyses across 9 farms. The extended workflow aggregates measurements by farm, field, and date, identifying temporal patterns, variability, and soil-health baselines at regional scale.
By processing more diverse agronomic data—nutrients, structure, moisture, conductivity, organic matter—the algorithm generates multi-farm comparison indicators and longitudinal trends. It demonstrates how the platform enables scalable analytics, secure federated processing, and data-sovereign collaboration between multiple landowners.
Questionary-Based Analysis (sensitive scientific study)
Privacy-Preserving Social & Perception Analytics (Questionary Dataset)
This case applies our simple derivative-data algorithm to a research questionnaire from a scientific study on regenerative agriculture. Because the survey contains sensitive, non-publishable responses, the algorithm intentionally produces only aggregated, non-identifying indicators such as counts, category distributions, and answer frequencies.
The resulting outputs comply with data-protection requirements and enable safe publication of insights about attitudes, environmental concerns, knowledge of regenerative agriculture, perception of food systems, and acceptance of new technologies such as blockchain. This case demonstrates how Compute-to-Data can support scientific studies by enabling analytics on protected datasets without exposing personal or raw survey information.