The economic viability of spot-spraying for pesticides: the case of Northwest Germany

IF 7.6 2区农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY

Precision Agriculture Pub Date : 2026-07-18 DOI:10.1007/s11119-026-10409-7

Jens Schots, Till Kuhn, Niklas Möhring

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引用次数: 0

Abstract

Purpose The reliance on pesticides for crop protection poses significant challenges, including biodiversity loss and environmental pollution. Despite the potential of precision farming technologies such as spot-sprayers for reducing pesticide applications, their adoption remains limited. Previous literature on the economic viability of precision spraying is sparse and did not account for relations between technology availability, prices, land use and adoption decisions. Methods We here analyze and compare the economic viability of different types of smart spot-sprayers for site-specific pesticide applications using a mixed-integer linear programming bio-economic farm model. We apply the model to typical cereal and sugar beet farms in North-Western Germany, which is one of the most productive agricultural regions in Europe. In our analysis, we account for key economic and performance parameters of precision sprayers and check the sensitivity of results regarding assumptions on technology and farm characteristics. Results The findings indicate that real-time spot-spraying of herbicides is economically viable for sugar beet farms exceeding 60-172 ha and cereal farms managing 300-400 ha. The large range of results reflects an important challenge for the adoption of spot sprayers. It highlights the sensitivity of economic viability to changes in technology type and performance and pesticide prices, which are often uncertain for farmers in advance. Broadening the use of the spot sprayer to multiple pesticide types and combining smaller and more precise spot-sprayers with broadcast sprayers improves the economic viability. Conclusions Overall, our results underscore the potential of smart spot-sprayers to contribute to sustainable agricultural practices by reducing pesticide use while maintaining profitability for farmers. Based on our results, we discuss how the adoption of these technologies could be facilitated to achieve environmental goals and improve farm economics.

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现场喷洒杀虫剂的经济可行性：以德国西北部为例

作物保护对农药的依赖带来了重大挑战，包括生物多样性丧失和环境污染。尽管精准农业技术具有潜力，如减少农药使用的定点喷雾器，但它们的采用仍然有限。以前关于精确喷洒的经济可行性的文献很少，并且没有考虑到技术可用性、价格、土地利用和采用决策之间的关系。方法采用混合整数线性规划生物经济农场模型，分析和比较不同类型的智能点喷雾器对特定地点农药应用的经济可行性。我们将该模型应用于德国西北部典型的谷物和甜菜农场，这是欧洲最具生产力的农业区之一。在我们的分析中，我们考虑了精密喷雾器的关键经济和性能参数，并检查了有关技术和农场特征假设结果的敏感性。结果实时现场喷洒除草剂对60 ~ 172公顷的甜菜场和300 ~ 400公顷的谷物场具有经济可行性。大范围的结果反映了采用点喷雾器的一个重要挑战。它突出了经济可行性对技术类型和性能以及农药价格变化的敏感性，而这些变化往往事先对农民来说是不确定的。将定点喷雾器的使用范围扩大到多种农药类型，并将更小、更精确的定点喷雾器与广播喷雾器相结合，提高了经济效益。总体而言，我们的研究结果强调了智能点喷雾器的潜力，通过减少农药使用，同时保持农民的盈利能力，为可持续农业实践做出贡献。根据我们的研究结果，我们讨论了如何促进采用这些技术来实现环境目标和改善农业经济。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Precision Agriculture 农林科学-农业综合

CiteScore

12.30

自引率

8.10%

发文量

103

审稿时长

>24 weeks

期刊介绍： Precision Agriculture promotes the most innovative results coming from the research in the field of precision agriculture. It provides an effective forum for disseminating original and fundamental research and experience in the rapidly advancing area of precision farming. There are many topics in the field of precision agriculture; therefore, the topics that are addressed include, but are not limited to: Natural Resources Variability: Soil and landscape variability, digital elevation models, soil mapping, geostatistics, geographic information systems, microclimate, weather forecasting, remote sensing, management units, scale, etc. Managing Variability: Sampling techniques, site-specific nutrient and crop protection chemical recommendation, crop quality, tillage, seed density, seed variety, yield mapping, remote sensing, record keeping systems, data interpretation and use, crops (corn, wheat, sugar beets, potatoes, peanut, cotton, vegetables, etc.), management scale, etc. Engineering Technology: Computers, positioning systems, DGPS, machinery, tillage, planting, nutrient and crop protection implements, manure, irrigation, fertigation, yield monitor and mapping, soil physical and chemical characteristic sensors, weed/pest mapping, etc. Profitability: MEY, net returns, BMPs, optimum recommendations, crop quality, technology cost, sustainability, social impacts, marketing, cooperatives, farm scale, crop type, etc. Environment: Nutrient, crop protection chemicals, sediments, leaching, runoff, practices, field, watershed, on/off farm, artificial drainage, ground water, surface water, etc. Technology Transfer: Skill needs, education, training, outreach, methods, surveys, agri-business, producers, distance education, Internet, simulations models, decision support systems, expert systems, on-farm experimentation, partnerships, quality of rural life, etc.