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Advanced monitoring and management systems for improving sustainability in precision irrigation

机译:先进的监控和管理系统,可提高精确灌溉的可持续性

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摘要

Globally, the irrigation of crops is the largest consumptive user of fresh water. Water scarcity is increasing worldwide, resulting in tighter regulation of its use for agriculture. This necessitates the development of irrigation practices that are more efficient in the use of water but do not compromise crop quality and yield. Precision irrigation already achieves this goal, in part. The goal of precision irrigation is to accurately supply the crop water need in a timely manner and as spatially uniformly as possible. However, to maximize the benefits of precision irrigation, additional technologies need to be enabled and incorporated into agriculture. This paper discusses how incorporating adaptive decision support systems into precision irrigation management will enable significant advances in increasing the efficiency of current irrigation approaches. From the literature review, it is found that precision irrigation can be applied in achieving the environmental goals related to sustainability. The demonstrated economic benefits of precision irrigation in field-scale crop production is however minimal. It is argued that a proper combination of soil, plant and weather sensors providing real-time data to an adaptive decision support system provides an innovative platform for improving sustainability in irrigated agriculture. The review also shows that adaptive decision support systems based on model predictive control are able to adequately account for the time-varying nature of the soil–plant–atmosphere system while considering operational limitations and agronomic objectives in arriving at optimal irrigation decisions. It is concluded that significant improvements in crop yield and water savings can be achieved by incorporating model predictive control into precision irrigation decision support tools. Further improvements in water savings can also be realized by including deficit irrigation as part of the overall irrigation management strategy. Nevertheless, future research is needed for identifying crop response to regulated water deficits, developing improved soil moisture and plant sensors, and developing self-learning crop simulation frameworks that can be applied to evaluate adaptive decision support strategies related to irrigation.
机译:在全球范围内,农作物灌溉是淡水的最大消耗者。世界范围内的水资源短缺现象日益严重,导致对农业用水的监管更加严格。这就需要发展在水的利用方面更有效但又不损害作物质量和产量的灌溉方式。精确灌溉已经部分实现了这一目标。精确灌溉的目标是及时,尽可能地在空间上准确地供应作物水。但是,为了使精确灌溉的利益最大化,需要启用其他技术并将其纳入农业。本文讨论了将自适应决策支持系统纳入精确灌溉管理将如何在提高当前灌溉方法效率方面取得重大进展。从文献综述中可以发现,精确灌溉可用于实现与可持续性相关的环境目标。然而,在田间作物生产中,精确灌溉所显示的经济利益微乎其微。有人认为,土壤,植物和天气传感器的适当组合可为自适应决策支持系统提供实时数据,从而为提高灌溉农业的可持续性提供了创新的平台。审查还表明,基于模型预测控制的自适应决策支持系统能够充分考虑土壤-植物-大气系统的时变性质,同时在确定最佳灌溉决策时考虑操作限制和农艺目标。结论是,通过将模型预测控制纳入精确灌溉决策支持工具中,可以显着提高作物产量和节水量。通过将缺水灌溉作为整体灌溉管理策略的一部分,也可以实现节水的进一步改善。尽管如此,仍需要进一步的研究来确定农作物对调节的水亏的反应,开发改良的土壤水分和植物传感器,以及开发可用于评估与灌溉有关的自适应决策支持策略的自学农作物模拟框架。

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