Sensors | Highly Cited Papers in 2024–2025 in the “Smart Agriculture” Section

The Section “Smart Agriculture” of Sensors (ISSN 1424-8220) publishes original peer-reviewed papers on state-of-the-art agriculture sensors, sensing systems, and emerging technologies such as artificial intelligence, IoT, UAVs, and robots, and their applications in the field of smart farming, precision livestock management, aquaculture, greenhouse technology, etc. In addition, any articles related to smart agriculture are welcome which highlight technological innovation in software and hardware development applied to crop and animal production. Paper types of original research, short communications, and comprehensive reviews are all acceptable.

As all of the articles published in our journal are of an open access format, you have free and unlimited access to the full texts. We welcome you to read our most highly cited papers published in 2024 and 2025, listed below:

1. “Trends of Soil and Solution Nutrient Sensing for Open Field and Hydroponic Cultivation in Facilitated Smart Agriculture”
by Md Nasim Reza, Kyu-Ho Lee, Md Rejaul Karim, Md Asrakul Haque, Emmanuel Bicamumakuba, Pabel Kanti Dey, Young Yoon Jang and Sun-Ok Chung
Sensors 2025, 25(2), 453; https://doi.org/10.3390/s25020453
Available online: https://www.mdpi.com/1424-8220/25/2/453

2. “Calibration of Low-Cost Capacitive Soil Moisture Sensors for Irrigation Management Applications”
by Ahmed A. Abdelmoneim, Christa M. Al Kalaany, Roula Khadra, Bilal Derardja and Giovanna Dragonetti
Sensors 2025, 25(2), 343; https://doi.org/10.3390/s25020343
Available online: https://www.mdpi.com/1424-8220/25/2/343

3. “Evaluating the Soil Quality Index Using Three Methods to Assess Soil Fertility”
by Hiba Chaudhry, Hiteshkumar Bhogilal Vasava, Songchao Chen, Daniel Saurette, Anshu Beri, Adam Gillespie and Asim Biswas
Sensors 2024, 24(3), 864; https://doi.org/10.3390/s24030864
Available online: https://www.mdpi.com/1424-8220/24/3/864

4. “Recent Methods for Evaluating Crop Water Stress Using AI Techniques: A Review”
by Soo Been Cho, Hidayat Mohamad Soleh, Ji Won Choi, Woon-Ha Hwang, Hoonsoo Lee, Young-Son Cho, Byoung-Kwan Cho, Moon S. Kim, Insuck Baek and Geonwoo Kim
Sensors 2024, 24(19), 6313; https://doi.org/10.3390/s24196313
Available online: https://www.mdpi.com/1424-8220/24/19/6313

5. “Internet of Things-Based Automated Solutions Utilizing Machine Learning for Smart and Real-Time Irrigation Management: A Review”
by Bryan Nsoh, Abia Katimbo, Hongzhi Guo, Derek M. Heeren, Hope Njuki Nakabuye, Xin Qiao, Yufeng Ge, Daran R. Rudnick, Joshua Wanyama, Erion Bwambale et al.
Sensors 2024, 24(23), 7480; https://doi.org/10.3390/s24237480
Available online: https://www.mdpi.com/1424-8220/24/23/7480

6. “Intrarow Uncut Weed Detection Using You-Only-Look-Once Instance Segmentation for Orchard Plantations”
by Rizky Mulya Sampurno, Zifu Liu, R. M. Rasika D. Abeyrathna and Tofael Ahamed
Sensors 2024, 24(3), 893; https://doi.org/10.3390/s24030893
Available online: https://www.mdpi.com/1424-8220/24/3/893

7. “Chlorophyll Fluorescence Imaging for Environmental Stress Diagnosis in Crops”
by Beomjin Park, Seunghwan Wi, Hwanjo Chung and Hoonsoo Lee
Sensors 2024, 24(5), 1442; https://doi.org/10.3390/s24051442
Available online: https://www.mdpi.com/1424-8220/24/5/1442

8. “A Systematic Review on the Advancements in Remote Sensing and Proximity Tools for Grapevine Disease Detection”
by Fernando Portela, Joaquim J. Sousa, Cláudio Araújo-Paredes, Emanuel Peres, Raul Morais and Luís Pádua
Sensors 2024, 24(24), 8172; https://doi.org/10.3390/s24248172
Available online: https://www.mdpi.com/1424-8220/24/24/8172

9. “An Innovative Smart and Sustainable Low-Cost Irrigation System for Anomaly Detection Using Deep Learning”
by Rabaie Benameur, Amine Dahane, Bouabdellah Kechar and Abou El Hassan Benyamina
Sensors 2024, 24(4), 1162; https://doi.org/10.3390/s24041162
Available online: https://www.mdpi.com/1424-8220/24/4/1162

10. “Computer-Vision-Based Sensing Technologies for Livestock Body Dimension Measurement: A Survey”
by Weihong Ma, Yi Sun, Xiangyu Qi, Xianglong Xue, Kaixuan Chang, Zhankang Xu, Mingyu Li, Rong Wang, Rui Meng and Qifeng Li
Sensors 2024, 24(5), 1504; https://doi.org/10.3390/s24051504
Available online: https://www.mdpi.com/1424-8220/24/5/1504