Turning Grain Supply Into Verified, Field-Level Sustainability Data
A grain merchant created a verified, field-level dataset linking cultivation, quality, and carbon performance across their grower group, strengthening customer relationships and enabling more informed supply chain decisions.
The Problem
Sustainability reporting is becoming a commercial requirement across the food supply chain. For this merchant, it presented a clear opportunity to differentiate, but also a significant data challenge.
The required data existed, but it was fragmented. Cropping data sat on farm. Quality data sat with the manufacturer. Carbon data was not being calculated at all. There was no consistent way to bring these elements together across a distributed grower network.
At scale, this wasn’t just a technical issue. Any solution needed to work for farmers as well as the supply chain, without adding unnecessary complexity or burden.
The Requirement
To deliver a credible, differentiated offer, the merchant needed to create a system that connected data across the supply chain and stood up to scrutiny.
This required:
Consistent cultivation data collected across the grower group
Field-level linkage between farm data and grain quality data
A verified, auditable view of carbon performance
Outputs that could support reporting and decision-making
A model that worked commercially for farmers
The Approach
The merchant introduced a structured grower programme, built around both data and incentives.
Farmers were offered a premium for providing cultivation data, ensuring strong participation while aligning with existing farm workflows. Key variables such as variety, nitrogen application, tillage, straw management, and yield were captured in a consistent format.
This cultivation data was then linked with grain quality data, creating a joined-up view at farm level. From there, the dataset was cleaned, standardised, and prepared for analysis.
Crucially, the model worked at scale. Around 80% of participating farms had data that could be successfully linked, resulting in a large, auditable dataset across the grower group.
The Outcome
The programme created a level of visibility that had not previously been possible.
A verified dataset linking cultivation practices, grain quality, and carbon performance
The ability to analyse emissions per tonne across the grower group
A structured evidence base to support customer reporting requirements
A commercially viable model, with farmers incentivised to participate
The result was a differentiated offer in supply chain conversations, grounded in real, verifiable data rather than assumptions.
The Impact
With a consistent, field-level dataset in place, the merchant gained clear insight into the drivers of both carbon and performance.
Nitrogen application emerged as the dominant driver of emissions, accounting for most of the variation in carbon per tonne. As application rates increased, emissions rose faster than both yield and protein, highlighting a clear efficiency threshold.
Tillage practices also showed a measurable impact. Minimum tillage was associated with higher yields and lower emissions per tonne, while variety choice revealed trade-offs between yield, protein performance, and carbon outcomes.
Other factors played a role. Straw baling was linked to reduced emissions per tonne, and lighter soil types consistently showed lower emissions. Across the group, emissions per tonne were below available UK benchmarks, supported by above-average yields.
The result was not just better reporting, but a commercially differentiated supply chain, one where sustainability data is verified, repeatable, and directly linked to every tonne supplied.
