管理区划定:克服作物-牧场轮作挑战的建议

IF 5.4 2区 农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY Precision Agriculture Pub Date : 2025-01-07 DOI:10.1007/s11119-024-10214-0
Henrique Oldoni, Paulo S. G. Magalhães, Agda L. G. Oliveira, Joaquim P. Lima, Gleyce K. D. A. Figueiredo, Edemar Moro, Lucas R. Amaral
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引用次数: 0

摘要

在作物-牧场轮作(CPR)系统中,很少有策略能够有效地划定管理区域(MZs),以便使用单一地图对多种作物进行特定地点的管理。本研究旨在提出和评估几种特征选择方法,这些方法考虑了CPR系统中的多种作物,并提出了CPR系统中MZ描绘的框架,从而产生单个MZ地图。特征选择方法基于属性(土壤、作物和地形属性)与产量变量(粮食和牧草产量、产量空间趋势和产量时间稳定性)之间的空间相关性。本研究选取了一个以大豆和牧草为特色的农牧一体化系统。结果表明,基于产量时间稳定性的方法对于在CPR系统中选择用于MZ描述的相关属性是最有效的,导致MZ之间的差异更大。需要更多的MZ数量(四个区域),强调根据方差减少和产量差异仔细选择数量的重要性,以确保最终的MZ地图反映所有作物的可变性,并指导其综合管理。提出的框架是第一个使用产率时间稳定性进行特征选择的框架之一,专门用于描绘CPR系统中的mz。该方法提高了在mz划定过程中选择重要属性的能力,为提高投入物使用效率和最大化粮食和牧草产量提供了更好的解决方案。
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Management zones delineation: a proposal to overcome the crop-pasture rotation challenge

Few strategies have been developed to effectively delineate management zones (MZs) in crop-pasture rotation (CPR) systems that accommodate site-specific management for multiple crops using a single map. This study aimed to propose and evaluate several feature selection approaches that account for multiple crops in CPR systems and propose a framework for MZ delineation in CPR systems that results in a single MZ map. The feature selection approaches were based on the spatial correlation between attributes (soil, crops, and terrain attributes) and yield variables (grain and pasture yield, spatial trend of yield, and yield temporal stability). This study was conducted in an area with an integrated crop-livestock system, featuring the CPR of soybean and pasture. The results showed that the approach based on yield temporal stability was the most effective for selecting relevant attributes used in the MZ delineation in CPR systems, resulting in greater differentiation among MZs. A higher number of MZs was needed (four zones), emphasizing the importance of carefully selecting the number based on variance reduction and yield differences to ensure that the final MZ map reflects the variability across all crops and guides their integrated management. The proposed framework is one of the first to use yield temporal stability for feature selection specifically aimed at delineating MZs in CPR systems. This approach improves the ability to select significant attributes used in the MZs delineation process, providing a better solution for improving input use efficiency and maximizing grain and pasture yield in integrated farming systems.

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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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