Artificial Intelligence in Agriculture Impact Factor 2026: 12.4, CiteScore 23.0, Q1
Artificial Intelligence in Agriculture impact factor is 12.4 with CiteScore 23.0. See the trend, SJR, and what that means.
Research Scientist, Agricultural AI
A research scientist focused on agricultural AI and bio-system engineering, spanning machine vision, precision agriculture, remote sensing, and decision-support systems. Has prepared and reviewed manuscripts for AI-in-agriculture and applied engineering journals where editors expect both credible model design and a real agricultural problem. Brings practical experience with validation design, deployment realism, and the fit boundary between generic machine learning, agricultural engineering, and food-system applications.
Journals reviewed for:
Artificial Intelligence in Agriculture, Computers and Electronics in Agriculture, Biosystems Engineering, Remote Sensing
Research published in:
Published across agricultural AI, remote sensing, and applied engineering venues
Artificial Intelligence in Agriculture impact factor is 12.4 with CiteScore 23.0. See the trend, SJR, and what that means.
Avoid desk rejection at AI in Agriculture by proving both the AI contribution and the agricultural contribution are real and operationally meaningful.
Avoid desk rejection at ISPRS Journal by proving a real geospatial contribution, strong validation, and value beyond one benchmark or local case.
Remote Sensing impact factor is 4.1 with a 5-year JIF of 4.8. See the rank, trend, and what that number means before submission.
Remote Sensing APC is CHF 2,700 in 2026. See the MDPI gold-OA fee, discounts, speed, and how it compares with stronger hybrid alternatives.
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