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Shared Evidence

Evidence

Identify collect, share and visualise meaningful metrics

The explanatory framework drives the metrics and measures we should collect and compare.

By working together across multiple farms and with connected spatial datasets like soil, weather and satellite data we can enable real time dynamic benchmarking of performances guided by the context of an individual farm.  Easy data collection and exchange with instant insightful analytics enables engagement at scale, maximising the power of data analysis to generate knowledge and hypotheses from the connected data.   

The YEN has pioneered the approach to generating and sharing data across a network of farms for common interest.

There are a wide range of sensors and data solutions that can be deployed. Working with Assimila we can generate satellite derived meaningful crop metrics for any land parcel anywhere.

Measure what matters

Focus on the meaningful metrics for the questions and context being tackled for relevant results. Agree simple protocols for specific measures that can be easily replicated and shared.

BOFIN has had great success in co-designing "citiizen science" type measures that farmers can take but give real biological meaning for scientists, from counting slugs to shovelomics rooting measures.

In the YEN growers take soil, crop & samples at key times for lab analysis. 

Collect

Use data that's already collected in farm management software where possible. Companies like Yagro, Omnia and Map of Ag help integrate data.  

A wide range of available spatial datasets for soil, weather and satellite imagery can be used for underlying contextual metrics.  Assimila can provide satellite derived crop metrics for any field. 

There are apps that can help with manual in-field data collection including fieldmargin, CropTrak. Specific apps to support flexible data collection for on-farm research are being developed.

A wide range of sensors and tools are potentially useful for collecting data on soils (eg PES), crops (eg Dualex) and the environment (eg Agrisound, Sencrop, AgroSense). 

Share & compare

Once data is collected maximum value can be generated from sharing and comparing your performance to others, and understanding differences.

Benchmarking is well established from a financial perspective, supported by tools like Yagro & FBN, and with benchmarking groups like ADHB Farm bench.  We see the value in technical benchmarking. 

The YEN provides benchmarking reports at the end of each season on a wide range of crop metrics. Dynamic Benchmarking has recently been developed to enable online comparisons with filtering across the full dataset.  Ideally we want to provide useful information back to growers with an insightful visualisation as soon as data is entered. 

Ag Analyst can create insightful dashboards

YEN-3

The YEN approach

The Yield Enhancement Network (YEN) is a leading example of how farm data can be collected, shared, and interpreted to generate practical insights. By bringing together farmers, advisors, researchers, and industry partners, YEN encourages participants to measure key aspects of their crop performance — from yield components and nutrient use to soil and weather conditions.

Each participant’s data is benchmarked anonymously against others in the network, enabling them to understand not just how their crop performed, but why. The approach combines structured data collection with agronomic interpretation, helping farmers identify yield-limiting factors and opportunities for improvement.

[show image of benchmarking resports etc]

Explore YEN

How can ARC help?

Work with researchers, ag technologists, data scientists and people who measure

We can pull together bespoke teams and solutions whatever your question and starting point. We can help

  • Define what to measure
    • We work with farmers and stakeholders to agree on metrics that matter — based on clear questions, explanatory frameworks, and practical relevance to farming systems.
    • Working with scientists, agronomists and facilitators we co-design simple practical protocols for measurements that matter.
  • Support data collection and integration
    • From simple observations to high-resolution yield maps and satellite data, we help design data flows that combine farm-level, environmental, and spatial data with minimal effort
  • Use Innovative sensors & technologies
    • we work with ag-tech developers to test and utilise new sensing technologies. If there are sensors you'd like to try, or if you are developing technologies you'd like to test on-farm, then get in touch 
  • Enable benchmarking and comparison
    • We work with farmer groups and digital platforms to compare performance with peers, using dynamic visualisations for maximum insight for the farmer
  • Analyse and interpret results
    • We work with data scientists and statisticians with advanced analytics to analyse data sets for maximum learnings and agronomic insights, testing what's already known and providing hypotheses for future testing.

Contact us now

If you'd like help with on-farm research for an agronomic project then get in touch now using the form below, or just email daniel@arcagsci.com