Decision-making for pest management in agriculture can be assisted by sampling plans that guide users in determining the need for an intervention. The tomato leafminer, Tuta absoluta, is easily recognizable by most tomato growers and several sampling plans have been developed. Yet, the adoption of decision-making systems for this pest is still incipient. Market uncertainty and farmers’ risk aversion are two potential obstacles that could be tackled by sampling plans that allow for the scheduling of interventions according to rough estimates of economic thresholds and to farmers’ intuition and experience. In this study, we used computer simulations and greenhouse trials to compare the efficiencies of four sampling plans both to estimate the mean number of larvae per plant and to classify pest populations according to a predefined economic threshold. We also analyzed the time spent and the number of plants examined by volunteers when applying each plan on a leafminer-infested tomato crop slightly over a predefined economic threshold. We show here that sampling plans giving the most precise classifications are not necessarily those yielding accurate pest density estimations. While computer simulations showed that the best plans for classification are those for estimation, results with humans evidenced the opposite. However, the average number of samples required by sampling plans does not reflect the time spent by humans sampling real plants. Our results show, for the first time, that sampling plans based on counts rather than on binary data can provide reliable information on the current level of a T. absoluta infestation relative to a decision threshold. We suggest that sampling plans promoting the creation of farmers’ memory, such as those based on counts, may be more suitable both to reduce risk aversion and to increase adaptability to market uncertainty.

可以通过指导用户确定干预措施需求的抽样计划来协助制定农业有害生物管理决策。番茄切叶机，Tuta absoluta大多数番茄种植者容易识别，并且已经制定了一些采样计划。但是，对于这种害虫的决策系统仍处于起步阶段。市场不确定性和农民的风险规避是可以通过抽样计划解决的两个潜在障碍，抽样计划允许根据对经济门槛的粗略估计以及对农民的直觉和经验的安排来安排干预措施。在这项研究中，我们使用计算机模拟和温室试验来比较四种采样计划的效率，既可以估算每株幼虫的平均数量，又可以根据预定义的经济阈值对虫害种群进行分类。我们还分析了将每种计划应用到略超过预定义的经济门槛的，对以挖矿机侵害的番茄作物上的每种计划时所花费的时间和志愿者检查的植物数量。我们在这里表明，给出最精确分类的采样计划不一定是产生准确虫害密度估计值的采样计划。虽然计算机模拟表明，最好的分类计划是进行估计，但人类的结果却相反。但是，采样计划所需的平均样本数量并不反映人类对真实植物进行采样所花费的时间。我们的结果首次显示，基于计数而不是基于二进制数据的采样计划可以提供有关当前样本水平的可靠信息。我们在这里表明，给出最精确分类的采样计划不一定是产生准确虫害密度估计值的采样计划。虽然计算机模拟表明，最好的分类计划是进行估计，但人类的结果却相反。但是，采样计划所需的平均样本数量并不反映人类对真实植物进行采样所花费的时间。我们的结果首次显示，基于计数而不是基于二进制数据的采样计划可以提供有关当前样本水平的可靠信息。我们在这里表明，给出最精确分类的采样计划不一定是产生准确虫害密度估计值的采样计划。虽然计算机模拟表明，最好的分类计划是进行估计，但人类的结果却相反。但是，采样计划所需的平均样本数量并不反映人类对真实植物进行采样所花费的时间。我们的结果首次显示，基于计数而不是基于二进制数据的采样计划可以提供有关当前样本水平的可靠信息。采样计划所需的平均样本数量并不反映人类对真实植物进行采样所花费的时间。我们的结果首次显示，基于计数而不是基于二进制数据的采样计划可以提供有关当前样本水平的可靠信息。采样计划所需的平均样本数量并不反映人类对真实植物进行采样所花费的时间。我们的结果首次显示，基于计数而不是基于二进制数据的采样计划可以提供有关当前样本水平的可靠信息。T. absoluta相对于决策阈值的侵扰。我们建议，促进建立农民记忆的抽样计划（例如基于计数的抽样计划）可能更适合于减少风险规避和提高对市场不确定性的适应性。