The DOI matches its Crossref record; 73 of the 73 references it cites were found in a registry or an index.
Application of Precision Agriculture Technologies for Sustainable Crop Production and Environmental Sustainability: A Systematic Review
Open accessAbstract
Precision agriculture technologies (PATs) transform crop production by enabling more sustainable and efficient agricultural practices. These technologies utilize data‐driven approaches to optimize the management of crops, soil, and resources, thus enhancing both productivity and environmental sustainability. This article reviewed the application of PATs for sustainable crop production and environmental sustainability around the globe. Key components of PAT include remote sensing, GPS‐guided equipment, variable rate technology (VRT), and Internet of Things (IoT) devices. Remote sensing and drones deliver high‐resolution imagery and data, enabling precise monitoring of crop health, soil conditions, and pest activity. GPS‐guided machinery ensures accurate planting, fertilizing, and harvesting, which reduces waste and enhances efficiency. VRT optimizes resource use by allowing farmers to apply inputs such as water, fertilizers, and pesticides at varying rates across a field based on real‐time data and specific crop requirements. This reduces over‐application and minimizes environmental impact, such as nutrient runoff and greenhouse gas emissions. IoT devices and sensors provide continuous monitoring of environmental conditions and crop status, enabling timely and informed decision‐making. The application of PAT contributes significantly to environmental sustainability by promoting practices that conserve water, reduce chemical usage, and enhance soil health. By enhancing the precision of agricultural operations, these technologies reduce the environmental impact of farming, while simultaneously boosting crop yields and profitability. As the global demand for food increases, precision agriculture offers a promising pathway to achieving sustainable crop production and ensuring long‐term environmental health.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Big Data in Smart Farming – A review
Wolfert, S., Ge, L., Verdouw, C., & Bogaardt, M.-J. (2017) · Agricultural Systems · doi:10.1016/j.agsy.2017.01.023 · Cited by 3,378
Remote sensing for agricultural applications: A meta-review
Weiss, M., Jacob, F., & Duveiller, G. (2020) · Remote Sensing of Environment · doi:10.1016/j.rse.2019.111402 · Cited by 1,877
Nutrients, eutrophication and harmful algal blooms along the freshwater to marine continuum
Wurtsbaugh, W. A., Paerl, H. W., & Dodds, W. K. (2019) · WIREs Water · doi:10.1002/wat2.1373 · Cited by 1,107
Machine Learning Applications for Precision Agriculture: A Comprehensive Review
Sharma, A., Jain, A., Gupta, P., & Chowdary, V. (2021) · IEEE Access · doi:10.1109/access.2020.3048415 · Cited by 1,102
From Smart Farming towards Agriculture 5.0: A Review on Crop Data Management
Saiz-Rubio, V., & Rovira-Más, F. (2020) · Agronomy · doi:10.3390/agronomy10020207 · Cited by 974
Extreme weather and climate events with ecological relevance: a review
Ummenhofer, C. C., & Meehl, G. A. (2017) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2016.0135 · Cited by 885
Precision Agriculture Techniques and Practices: From Considerations to Applications
Shafi, U., Mumtaz, R., García-Nieto, J., Hassan, S. A., Zaidi, S. A. R., & Iqbal, N. (2019) · Sensors · doi:10.3390/s19173796 · Cited by 792
The adaptation and mitigation potential of traditional agriculture in a changing climate
Altieri, M. A., & Nicholls, C. I. (2017) · Climatic Change · doi:10.1007/s10584-013-0909-y · Cited by 781
The Path to Smart Farming: Innovations and Opportunities in Precision Agriculture
Karunathilake, E. M. B. M., Le, A. T., Heo, S., Chung, Y. S., & Mansoor, S. (2023) · Agriculture · doi:10.3390/agriculture13081593 · Cited by 779
Balafoutis, A., Beck, B., Fountas, S., Vangeyte, J., Wal, T., Soto, I., Gómez-Barbero, M., Barnes, A., & Eory, V. (2017) · Sustainability · doi:10.3390/su9081339 · Cited by 672
Cited by
Mustafa, F., Smolarski, J., & Elamer, A. A. (2025) · Business Strategy and the Environment · doi:10.1002/bse.70090 · Cited by 51
Madjar, R. M., & Vasile Scăețeanu, G. (2025) · Sustainability · doi:10.3390/su17167368 · Cited by 37
Metadata
- Authors
- Getahun, S., Kefale, H., & Gelaye, Y.
- Venue
- The Scientific World Journal
- Publisher
- Wiley
- Published
- 2024-01
- Volume
- 2024
- Issue
- 1
- Pages
- 2126734-2126734
- ISSN
- 1537-744X (ISSN-L)
- 2356-6140
- OpenAlex
- W4403253227
- Cited by
- 414
- References
- 73
- FWCI
- 23.34
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Application of Precision Agriculture Technologies for Sustainable Crop Production and Environmental Sustainability: A Systematic Review. https://app.cochat.ai/papers/10.1155/2024/2126734
- The paper
- Getahun, S., Kefale, H., & Gelaye, Y. (2024). Application of Precision Agriculture Technologies for Sustainable Crop Production and Environmental Sustainability: A Systematic Review. The Scientific World Journal. https://doi.org/10.1155/2024/2126734
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.