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Cited by 522

The DOI matches its Crossref record; 110 of the 110 references it cites were found in a registry or an index.

Soil Sensors and Plant Wearables for Smart and Precision Agriculture

Yin, Heyu, Cao, Yunteng, Marelli, Benedetto, Zeng, Xiangqun, Mason, Andrew J., Cao, Changyong·2021·Advanced Materials

Abstract

Soil sensors and plant wearables play a critical role in smart and precision agriculture via monitoring real‐time physical and chemical signals in the soil, such as temperature, moisture, pH, and pollutants and providing key information to optimize crop growth circumstances, fight against biotic and abiotic stresses, and enhance crop yields. Herein, the recent advances of the important soil sensors in agricultural applications, including temperature sensors, moisture sensors, organic matter compounds sensors, pH sensors, insect/pest sensors, and soil pollutant sensors are reviewed. Major sensing technologies, designs, performance, and pros and cons of each sensor category are highlighted. Emerging technologies such as plant wearables and wireless sensor networks are also discussed in terms of their applications in precision agriculture. The research directions and challenges of soil sensors and intelligent agriculture are finally presented.

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Crossref · 10.1002/adma.202007764

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Metadata

Authors
Yin, H., Cao, Y., Marelli, B., Zeng, X., Mason, A. J., & Cao, C.
Venue
Advanced Materials
Publisher
Wiley
Published
2021-04-07
Volume
33
Issue
20
Pages
e2007764-e2007764
ISSN
  • 0935-9648 (ISSN-L)
  • 1521-4095
OpenAlex
W3141912187
Cited by
522
References
110
FWCI
39.10
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Soil Sensors and Plant Wearables for Smart and Precision Agriculture. https://app.cochat.ai/papers/10.1002/adma.202007764
The paper
Yin, H., Cao, Y., Marelli, B., Zeng, X., Mason, A. J., & Cao, C. (2021). Soil Sensors and Plant Wearables for Smart and Precision Agriculture. Advanced Materials. https://doi.org/10.1002/adma.202007764

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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