Precision agriculture (PA) has great potential to increase agricultural productivity and profitability while reducing input costs and environmental impacts. Within PA, site‐specific crop management (SSCM) is considered the main premise, in which tillage operations and precise crop inputs (such as seed, fertiliser, water, pesticide and agrochemical) are applied according to field variability. The main aim of this review was to highlight the methods and tools used for spatial crop monitoring, soil and weather data influencing crop productivity and to support the adoption of SSCM technology. To achieve this goal: we discussed the main five components of SSCM, methods for monitoring crop and soil data, delineating field management zones (FMZs) and variable rate technologies (VRT) such as precision planting and digital smart sensors used for SSCM application. The review summarised that recent advances in plant and soil sensing systems, artificial intelligence (AI) and machine learning should be used in retrieving and analysing GIS big data for optimised crop inputs supply. Within VRT, light‐bar systems, automatic controllers and sensors are user‐friendly technologies that should be employed in SSCM solution. The authors highlight that adoption of PA can be increased through proper training and education of the farmers, and developing simple, affordable and efficient PA technologies. The review suggests five criteria that should be strictly adopted to get maximum benefits from SSCM: (i) all factors influencing crop yields can be identified; (ii) their effects on crop yields can be determined by using appropriate digital tools and crop modelling; (iii) variable rate crop inputs (VRCIs) should be calculated based on accurate information obtained from plant, soil and environment; (iv) targeted crop inputs should be exercised through global positioning system (GPS) enabled automatic controllers or wireless sensors network (WSN); and (v) right doses of crop inputs (e.g., nitrogen and irrigation) must be applied at the right time and place.

中文翻译：

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特定地点作物管理的广泛范围和遥感技术在其中的具体作用——​​回顾


精准农业（PA）在提高农业生产力和盈利能力、同时降低投入成本和环境影响方面具有巨大潜力。在 PA 中，特定地点作物管理（SSCM）被认为是主要前提，其中根据田间变化进行耕作操作和精确的作物投入（例如种子、肥料、水、农药和农用化学品）。本次综述的主要目的是强调用于空间作物监测、影响作物生产力的土壤和天气数据的方法和工具，并支持 SSCM 技术的采用。为了实现这一目标：我们讨论了 SSCM 的主要五个组成部分、监测作物和土壤数据的方法、划定田间管理区 (FMZ) 和可变速率技术 (VRT)，例如用于 SSCM 应用的精准种植和数字智能传感器。该评论总结说，植物和土壤传感系统、人工智能 (AI) 和机器学习的最新进展应用于检索和分析 GIS 大数据，以优化作物投入供应。在 VRT 中，灯条系统、自动控制器和传感器是用户友好的技术，应在 SSCM 解决方案中采用。作者强调，通过对农民进行适当的培训和教育，以及开发简单、负担得起和高效的 PA 技术，可以增加 PA 的采用。 审查建议应严格采用五个标准，以从 SSCM 中获得最大效益：(i) 可以确定影响作物产量的所有因素； (ii) 它们对作物产量的影响可以通过使用适当的数字工具和作物模型来确定； (iii) 可变比率作物投入（VRCI）应根据从植物、土壤和环境获得的准确信息进行计算； (iv) 应通过全球定位系统（GPS）自动控制器或无线传感器网络（WSN）进行有针对性的作物投入； (v) 必须在正确的时间和地点施用正确剂量的作物投入（例如氮肥和灌溉）。