Precision Agriculture

Aims & Scope

Precision Agriculture promotes the most innovative results coming from the research in the field of precision agriculture.

It provides an effective forum for disseminating original and fundamental research and experience in the rapidly advancing area of precision farming.

There are many topics in the field of precision agriculture; therefore, the topics that are addressed include, but are not limited to: Natural Resources Variability: Soil and landscape variability, digital elevation models, soil mapping, geostatistics, geographic information systems, microclimate, weather forecasting, remote sensing, management units, scale, etc.

Managing Variability: Sampling techniques, site-specific nutrient and crop protection chemical recommendation, crop quality, tillage, seed density, seed variety, yield mapping, remote sensing, record keeping systems, data interpretation and use, crops (corn, wheat, sugar beets, potatoes, peanut, cotton, vegetables, etc.), management scale, etc.

Engineering Technology: Computers, positioning systems, DGPS, machinery, tillage, planting, nutrient and crop protection implements, manure, irrigation, fertigation, yield monitor and mapping, soil physical and chemical characteristic sensors, weed/pest mapping, etc.

Profitability: MEY, net returns, BMPs, optimum recommendations, crop quality, technology cost, sustainability, social impacts, marketing, cooperatives, farm scale, crop type, etc.

Environment: Nutrient, crop protection chemicals, sediments, leaching, runoff, practices, field, watershed, on/off farm, artificial drainage, ground water, surface water, etc.

Technology Transfer: Skill needs, education, training, outreach, methods, surveys, agri-business, producers, distance education, Internet, simulations models, decision support systems, expert systems, on-farm experimentation, partnerships, quality of rural life, etc.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	6.6
2024	5.40

SJR (SCImago Journal Rank)

Year	Value
2024	1.337

Quartile

Year	Value
2024	Q1

h-index

Year	Value
2024	98

Journal Rank

Year	Value
2024	2941

Journal Citation Indicator

Year	Value
2024	2622

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Agricultural and Biological Sciences, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• The application of small unmanned aerial systems for precision agriculture: a review

  Citation: 1437

  Authors: Chunhua, John M.

• Future Directions of Precision Agriculture

  Citation: 577

  Authors: Alex, Brett, Tihomir, Johan

• Precision Agriculture and Sustainability

  Citation: 533

  Authors: R., J.

• Evaluation of Digital Photography from Model Aircraft for Remote Sensing of Crop Biomass and Nitrogen Status

  Citation: 441

  Authors: E. Raymond, Michel, Craig S. T., James E., Charles L.

• Deep learning for real-time fruit detection and orchard fruit load estimation: benchmarking of ‘MangoYOLO’

  Citation: 354

  Authors: A., K. B., Z., C.

• Factors influencing the adoption of precision agricultural technologies: a review for policy implications

  Citation: 319

  Authors: Yeong Sheng, Mark

• Identification of yellow rust in wheat using in-situ spectral reflectance measurements and airborne hyperspectral imaging

  Citation: 294

  Authors: Wenjiang, David W., Zheng, Yongjiang, Liangyun, Jihua

• Mapping crop water stress index in a ‘Pinot-noir’ vineyard: comparing ground measurements with thermal remote sensing imagery from an unmanned aerial vehicle

  Citation: 293

  Authors: J., P. J., J., E.

• Automation in Agriculture by Machine and Deep Learning Techniques: A Review of Recent Developments

  Citation: 285

  Authors: Muhammad Hammad, Johan, Khalid Mahmood

• Using high resolution UAV thermal imagery to assess the variability in the water status of five fruit tree species within a commercial orchard

  Citation: 280

  Authors: V., P., E., P. A., J. J., D. S., E.

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