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Unveiling Insights: Collaborative Thinking in Kent

THOMAS GATE

Back in early December, 5 farmers and our team from YAGRO met to share value and insights from accurate farm data – on this occasion, specifically exploring rotational analysis. 

This group have been meeting for the past 3 years and were initially brought together by a mutual desire to enable knowledge sharing among likeminded farmers, with practical insights and verified farm data analysis taking centre stage. 

Growers present on the day (December 4, 2023) were members of Saint Nicholas Court Farms, A Hinge & Sons, Fridays Ltd and AA Clifton.  

As one of the YAGRO Data Analysts, I had prepared detailed farm specific overviews to provide bespoke insight for those present. This enabled the individual farms to receive a full overview of their rotations and its effect on harvest 2023.  

This analysis largely focused on Winter Wheat, looking into performances and Costs of Production following previous crops.  

Continuing, by using amalgamated wider data sets, those present were provided the chance to accurately benchmark their performances in detail with ease to one another. 

Top 5 Grower Questions that Sparked Conversation at the Kent Virtual Group.   

  • Are we all adjusting our fertiliser depending on the previous crop? 

  • Are you putting much digestate on your break crops? 

  • How are you using cover crops?  

  • What are you going to do differently in 2024?

  • Do any of you use variable rate Nitrogen?  

Farm Specific Analysis  

As the Data Analyst present, I knew each farm would benefit from their own rotational analysis specific to their site. Using visual box plots and bar graphs, I began the day by displaying breakdowns of each farms’ rotations.  

I took care to include details of all previous crops, plus number of fields featured going back up to 5 years in the rotation.  

Being able to visualise cropping statistics, such as rotational performance, is a seamless way to empower detailed knowledge of a farming operation and helps reach informed decisions quickly.   

Digging into Performance: The Data-Driven Approach 

The day revolved around how previous crops effect Wheat performance, with numerous other factors being raised throughout – such as frequent flooding, and differing soil types. All contributing to understanding which rotation yields the best results in terms of output, cost-effectiveness and risk mitigation.  

One area of interest early on was the impact of maize as a break-crop, which is featuring at one of the farms present. Causing other curious growers to learn more about this decision and its impact on their strategy.  

Notably, conversations backed by data can lead directly to outcome driven decisions. For example, I associated Winter Barley as previous crop to a 15% drop in yield and 9% increase in COP/t for Winter Wheat. This caused one grower to ask “should we be considering Wheat following Winter Barley as Second Wheat? Considering the yield penalty it seems to carry...”  

Listening and responding to farm data is the surest path to making the most informed decisions possible.  

Field Level Data 

I chose to use normalised data to account for outlying differences in farm-wide averages, with normalised Costs per Tonne representing a reliable combination of costs & performance. But the value of understanding performance at a field level was grasped by the group.  

One grower remarked that “cost per Tonne is important when considering farm variables and yield potential. There’s no point paying and pushing for an 11t yield in an 8t field.” This caused another grower to agree and concede “we were blanket applying Nitrogen before analysing our field level data. 5 years of data, and we’ve got some constructive achievements.”  

Comparing an 11t yield to your farm average, for example, may seem exceptional. But comparing that field to itself, 11t could be average. Drilling into the historic performance of individual fields allows you to maximise the potential of each hectare, thus treating each field as its own profit centre. 

Associating Costs with Each Decision 

Later, the focus turned to analysing Second Wheat and debating high versus low-input models for rotations. I provided analysis on spend (£/ha & £/t) for taking Wheat to harvest dependant on previous crop.  

As predicted, Legumes as previous crop did generally lead to improved Nitrogen use efficiency for the following Wheat crop – with slightly lower rates still able to achieve yield due to the Nitrogen fixed by the Legume.  

Taking this analysis further, however, it was clear that translating this into profit depended on the gross margin achieved for Legume crops (and other break crops) plus the end markets of different Wheat varieties.  

OSR as a previous crop also displayed positive trends, with beneficial normalised yields and slightly lower COP for following Wheat. However, with the threat of Cabbage Stem Flea Beetle, several growers questioned the ongoing viability of OSR as a reliable break crop. 

Key Takeaways and Shared Discussions 

Throughout the day, all present shared practical insights. One grower highlighted consistent losses due to Autumn flooding, prompting thoughts about shifting to Spring Barley. They were able to garner advice and data from others in the room to support this decision process. 

There was a collective effort to understand how various factors, like fertiliser adjustments based on previous crops, impacted COP/t. A different grower mentioned using digestate for increasing Nitrogen availability in Oats, sparking discussion around optimal Nitrogen usage across different crops.  

This kind of practical knowledge exchange emphasised the value of these shared discussions, as learnings could be taken from pooled experience in the room.  

Conclusion: Real Insights for Informed Decisions  

This collaboration was more than just talking. It was practical solutions. The day proved that accurate farm data analysis can enhance farming decisions and taking the opportunity to collaborate bolsters knowledge further.  

This down-to-earth exercise for learning and exchanging insights offers a new standard for farming progress. As these growers head back to their fields, they carry with them increased knowledge to inform their decision making and enable more efficient, profitable and sustainable farming practices.  

Thomas Gate is an Analyst in the Data Team. With a passion for data and agriculture, Thomas grew up around farming and agronomy. With a day-to-day role of cleaning, processing and analysing complex data sets for bespoke farm projects, Thomas and the data team are exploring the endless possibilities of how data can be best used to aid and inform farmers. Outside of work...Thomas enjoys getting outdoors through playing football, running or a bit of gardening. He also likes to expand his programming skills with a variety of small projects.