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Assess trial quality at scale with standardized traits

Trial-level quality indices to flag outliers and re-score problematic plots automatically.

A standardized quality index that flags problem plots before analysis

Weak trials waste entire seasons, and the flaws — poor establishment, uneven emergence, border effects — are frequently spotted only once the yield data refuses to make sense. By then the season is gone and the investment is lost.

The Literal platform combines standardised traits from UAV and ground imagery into a per-plot and per-trial quality index: establishment, uniformity, canopy homogeneity and anomaly flags. Problematic plots are surfaced automatically as the season progresses.

Teams can intervene while it still matters — re-scoring, re-sampling or excluding plots on objective grounds — and enter analysis with a trial whose quality is documented rather than assumed.

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