人工智能优化化肥使用的叙述性回顾:一个改变游戏规则的机会

IF 0.8 Q3 AGRONOMY
Sarmistha Saha, Alok Bhardwaj
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引用次数: 0

摘要

工业革命之后的绿色革命提高了单位土地的作物产量,但也增加了对合成肥料和杀虫剂的需求,降低了地下水位,加剧了盐碱化。为了提高农业生产力,土壤肥力是至关重要的,为了保持土壤肥力,提高产量,提高收获质量,肥料是必不可少的。土壤肥力下降是全球范围内提高粮食生产的一个关键制约因素,而不当的养分管理是造成这一问题的一个重要原因。农业生态系统将需要采用现代技术,以便生产足够的粮食并减轻化学施肥对环境的有害影响。因此,农业食品行业正在逐步利用人工智能(AI)来提高生产率、效率和可持续性。人工智能使用计算模型来处理数据,并识别预测或决策的模式。本文着重介绍了人工智能技术如何用于粪便成分预测,以提高食品安全和质量。我们的目标是确定人工智能的作用和实地研究的支持证据,以表征有效作物生产和最低植物毒性的肥料控制组合。此外,我们还讨论了人工智能在粮食和农业部门的限制和挑战。综上所述,基于人工智能的方法和田间研究表明,有机肥和无机肥配合施用可以协同改善作物生长和产量参数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A narrative review of artificial intelligence to optimize the use of fertilizers: A game changing opportunity

The green revolution, which came after the industrial revolution, boosted the crop yields produced per unit of land, but it also increased the need for synthetic fertilizers and pesticides and lowered the water table and increased salinization. In order to improve farm productivity, soil fertility is crucial and for preserving soil fertility, boosting yields, and enhancing harvest quality, fertilizer is essential. The decline in the fertility of the soil is a key constraint in enhancing food production worldwide, and improper nutrient management is a significant cause of this problem. Agroecosystems will need to implement contemporary technologies in order to produce enough food and mitigate the detrimental effects of chemical fertilization on the environment. Hence, the agri-food industry is progressively utilizing artificial intelligence (AI) to increase productivity, efficiency, and sustainability. AI uses computational models to process data and identifies patterns for predictions or decision-making. This review emphasizes how AI technology could be used for the predictions of manure compositions for improvement of food safety and quality. We aimed to identify the role of AI and the supporting evidences of field studies to characterize the controlled combinations of fertilizers for the efficient crop production with lowest possible plant toxicity. Also, we discuss the constraints and challenges of AI in the food and agricultural sector. In conclusion, AI-based approaches and field studies suggested that combining organic and inorganic fertilizers can synergistically improve crop growth and yield parameters.

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来源期刊
Crop, Forage and Turfgrass Management
Crop, Forage and Turfgrass Management Agricultural and Biological Sciences-Agronomy and Crop Science
CiteScore
1.30
自引率
16.70%
发文量
49
期刊介绍: Crop, Forage & Turfgrass Management is a peer-reviewed, international, electronic journal covering all aspects of applied crop, forage and grazinglands, and turfgrass management. The journal serves the professions related to the management of crops, forages and grazinglands, and turfgrass by publishing research, briefs, reviews, perspectives, and diagnostic and management guides that are beneficial to researchers, practitioners, educators, and industry representatives.
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