Soil2Cover:覆盖路径规划,最大限度地减少可持续农业的土壤压实。

IF 5.4 2区 农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY
Precision Agriculture Pub Date : 2025-01-01 Epub Date: 2025-06-03 DOI:10.1007/s11119-025-10250-4
Gonzalo Mier, Sergio Vélez, João Valente, Sytze de Bruin
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引用次数: 0

摘要

重型农业机械造成的土壤压实使土壤健康退化,降低作物生产力,破坏环境动态,对可持续农业构成重大挑战。现场交通优化有助于减少压实,但传统算法主要关注最小化路线长度,而忽略了其成本函数中的土壤压实动态。本研究介绍了一种将控制交通耕作原理与SoilFlex模型相结合的方法,通过优化机械路径来最大限度地减少土壤压实。Soil2Cover优先考虑机械通过特定区域的频率,同时整合土壤力学特性来量化压实影响。对1000块农田的测试结果表明,我们的方法在单种作物和间作情况下可将路线长度减少4-6%,同时将岬角的土壤压实程度降低30%。优化的路线提高了作物产量,同时降低了运营成本,降低了燃料消耗,减少了农业生产的整体环境足迹。实现代码将与Fields2Cover的第三版一起发布,Fields2Cover是一个用于农业环境中覆盖路径规划问题的开源库。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Soil2Cover: Coverage path planning minimizing soil compaction for sustainable agriculture.

Soil compaction caused by heavy agricultural machinery poses a significant challenge to sustainable farming by degrading soil health, reducing crop productivity, and disrupting environmental dynamics. Field traffic optimization can help abate compaction, yet conventional algorithms have mostly focused on minimizing route length while overlooking soil compaction dynamics in their cost function. This study introduces Soil2Cover, an approach that combines controlled traffic farming principles with the SoilFlex model to minimize soil compaction by optimizing machinery paths. Soil2Cover prioritizes the frequency of machinery passes over specific areas, while integrating soil mechanical properties to quantify compaction impacts. Results from tests on 1000 fields demonstrate that our approach achieves a reduction in route length of up to 4-6% while reducing the soil compaction on headlands by up to 30% in both single-crop and intercropping scenarios. The optimized routes improve crop yields whilst reducing operational costs, lowering fuel consumption and decreasing the overall environmental footprint of agricultural production. The implementation code will be released with the third version of Fields2Cover, an open-source library for the coverage path planning problem in agricultural settings.

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来源期刊
Precision Agriculture
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.
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