Precision agriculture technologies for soil site-specific nutrient management: A comprehensive review

被引:0
|
作者
Vullaganti, Niharika [1 ]
Ram, Billy G. [1 ]
Sun, Xin [1 ]
机构
[1] North Dakota State Univ, Dept Agr & Biosyst Engn, Fargo, ND 58102 USA
来源
基金
美国食品与农业研究所;
关键词
Modeling; On-the go sensing; Site-specific nutrient management; Soil nutrients; Spectroscopy; ON-THE-GO; ORGANIC-MATTER; IN-SITU; FERTILITY PARAMETERS; NIR SPECTROSCOPY; ONLINE MEASUREMENT; SENSOR DATA; CARBON; FUSION; PREDICTION;
D O I
10.1016/j.aiia.2025.02.001
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
Amidst the growing food demands of an increasing population, agricultural intensification frequently depends on excessive chemical and fertilizer applications. While this approach initially boosts crop yields, it effects long-term sustainability through soil degradation and compromised food quality. Thus, prioritizing soil health while enhancing crop production is essential for sustainable food production. Site-Specific Nutrient Management (SSNM) emerges as a critical strategy to increase crop production, maintain soil health, and reduce environmental pollution. Despite its potential, the application of SSNM technologies remain limited in farmers' fields due to existing research gaps. This review critically analyzes and presents research conducted in SSNM in the past 11 years (2013-2024), identifying gaps and future research directions. A comprehensive study of 97 relevant research publications reveals several key findings: a) Electrochemical sensing and spectroscopy are the two widely explored areas in SSNM research, b) Despite numerous technologies in SSNM, each has its own limitation, preventing any single technology from being ideal, c) The selection of models and preprocessing techniques significantly impacts nutrient prediction accuracy, d) No single sensor or sensor combination can predict all soil properties, as suitability is highly attribute-specific. This review provides researchers, and technical personnel in precision agriculture, and farmers with detailed insights into SSNM research, its implementation, limitations, challenges, and future research directions. (c) 2025 The Authors. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co., Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页码:147 / 161
页数:15
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