Case studies
2012, washout, 4 of 4 high-confidence regions correct
The worst UK wheat year in a generation: a relentlessly wet summer wrecked grain fill and drove disease. The model called all 4 high-confidence regions below-average. Predicted −0.46, actual −0.84 t/ha, directionally right and conservatively sized.
2014, bumper year, 3 of 3 correct (bullish)
Not a doom call. A near-record harvest, called correctly as above-average in all 3 high-confidence regions. Predicted +0.27, actual +1.70 t/ha. The case that proves CropIntel is a directional forecaster, not a one-sided pessimist.
2019, disaster year, 8 of 9 regions correct
A wet autumn drilling window, cold tillering in the east, and a hot, dry June. UK average yield fell to 7.0 t/ha, the worst since 2012. The model flagged 8 of 9 regions below-average ahead of the May checkpoint. Predicted −0.73, actual −1.12 t/ha.
2023, wet harvest, 6 of 6 high-confidence regions correct
An unusually wet July and August, textbook compound stress at flowering and ripening. The model called 6 of 6 high-confidence regions below-average, intensifying the call in close to real time as the wet July developed. Predicted −0.33, actual −0.77 t/ha.
2018, where we got it wrong, 2 of 6 correct
The cleanest miss in the backtest. The model read 2018's hot, dry summer as heat stress and called mildly bearish (−0.23); UK wheat actually had a bumper year (+1.52) because the dry weather suppressed disease. Honest writeup of why the compound-stress model was blind to the low-disease bonus, and how the sentiment layer addresses the gap.
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