Optimizing accuracy of protocols for measuring dry matter and nutrient yield of forage crops

Farmers around the world must precisely manage nutrients applied to and removed from crop fields to maintain production and without causing nutrient pollution. This study is the first to quantify the baseline accuracy of current industry measurement protocols and achievable accuracy from intensifying protocols for measuring dry matter (DM), nitrogen (N), potassium (K), and phosphorus (P) yields from forage crops harvested for silage. The 'true' DM and nutrient yields of three fields each of corn, sorghum, and small grain were intensively measured by weighing and sampling every truckload of harvested forage. Simulations quantified the accuracy of practical sampling protocols by repeatedly subsampling the complete dataset for each field to measure average truckload weight and average DM and nutrient concentrations. Then uncertainty was propagated to DM, N, P, and K yield calculations using standard error equations. Yields measured using current industry protocols diverged from the true yields of some fields by more than ±40%, emphasizing the need for improved protocols. This study shows that improving average DM and nutrient concentration measurements is unlikely to improve accuracy of yield measurements if average load weight is not precisely measured. Accuracy did not come within 27% of true yields without weighing all truckloads on some fields even when DM and nutrient concentration measurements were perfectly accurate. Once all truckloads were weighed, the timing of forage sample collection to measure average DM concentration had the greatest impact on accuracy; precision improved by an average of 6.2% when >3 samples were evenly spaced throughout the harvest compared to the same number of consecutive samples. All crop fields are affected by within field variation in growing conditions that results in heterogeneity in DM and nutrient yield. Globally, this study provides foundational methodology to quantitatively evaluate and improve yield measurement protocols that ultimately support sustainable crop production.