Modern sensor technologies can provide detailed information about soil variation which allows for more precise application of fertiliser to minimise environmental harm imposed by agriculture. However, growers should lose neither income nor yield from associated uncertainties of predicted nutrient concentrations and thus one must acknowledge and account for uncertainties. A framework is presented that accounts for the uncertainty and determines the cost–benefit of data on available phosphorus (P) and potassium (K) in the soil determined from sensors. For four fields, the uncertainty associated with variation in soil P and K predicted from sensors was determined. Using published fertiliser dose–yield response curves for a horticultural crop the effect of estimation errors from sensor data on expected financial losses was quantified. The expected losses from optimal precise application were compared with the losses expected from uniform fertiliser application (equivalent to little or no knowledge on soil variation). The asymmetry of the loss function meant that underestimation of P and K generally led to greater losses than the losses from overestimation. This study shows that substantial financial gains can be obtained from sensor-based precise application of P and K fertiliser, with savings of up to £121 ha⁻¹ for P and up to £81 ha⁻¹ for K, with concurrent environmental benefits due to a reduction of 4–17 kg ha⁻¹ applied P fertiliser when compared with uniform application.

现代传感器技术可以提供有关土壤变化的详细信息，从而可以更精确地施用肥料，从而最大限度地减少农业对环境造成的危害。然而，种植者不应因预测养分浓度的相关不确定性而损失收入或产量，因此必须承认并解释不确定性。提出了一个框架，该框架解释了传感器确定的土壤中有效磷（P）和钾（K）数据的不确定性并确定了成本效益。对于四个田地，确定了与传感器预测的土壤 P 和 K 变化相关的不确定性。使用已发布的园艺作物肥料剂量-产量响应曲线，量化了传感器数据估计误差对预期经济损失的影响。将最佳精确施肥的预期损失与均匀施肥（相当于对土壤变化知之甚少或根本不了解）的预期损失进行比较。损失函数的不对称性意味着低估 P 和 K 通常会比高估造成的损失更大。这项研究表明，通过基于传感器的磷肥和钾肥精确施用可以获得可观的财务收益，磷肥节省高达 121 ha ^-1英镑，钾肥节省高达 81 ha ^-1英镑，同时还带来环境效益与均匀施用相比，磷肥施用量减少 4–17 kg ha ⁻¹ 。