Purpose
Understanding environmental performance at farm level is essential to delivering measurable sustainability across ABP’s supply chain. To build a robust, evidence-based view at Bromstead Farm, ABP partnered with X10AI to develop a digital model of the farm system using high-resolution remote sensing data and on-farm records.
Action
X10AI’s platform combines drone and satellite imagery with farm data to create a digital twin of the farm, providing a detailed picture of how nutrients, carbon, water, and natural capital interact across the system.
The technology focuses on mapping and measuring environmental flows—including nitrogen and phosphorus movement, carbon dynamics, and the condition of natural features such as hedgerows, woodland margins, and watercourses.
This enables farmers to understand not just inputs, but where nutrients go, how efficiently they are used, and what is lost to the environment, providing a clearer basis for decision-making. • The platform also supports measurement, reporting, and verification (MRV), generating consistent, audit-ready data that aligns with environmental schemes, regulatory requirements, and supply chain reporting.
At Bromstead Farm, this approach allows environmental performance to be assessed across the whole system—from soil and nutrient management through to carbon outcomes and biodiversity features—supporting more targeted and informed management decisions.
Impact
Across participating farms, X10AI is enabling a shift from estimated or retrospective reporting to accurate, verifiable measurement of environmental performance.
By providing a clear understanding of nutrient efficiency, carbon balance, water risk, and habitat features, the platform helps identify where changes in management can reduce losses, improve resource use, and strengthen environmental outcomes.
At supply chain level, this creates a consistent and trusted evidence base, allowing ABP to aggregate farm data, demonstrate progress against sustainability targets, and support outcome-based environmental programmes.
This collaboration demonstrates how digital twin technology can translate complex farm data into practical insight and verified impact, supporting farmers to make better decisions while strengthening environmental performance across the wider agricultural system.