Agronomy | Feature Papers in Section “Precision and Digital Agriculture”

1. “Comparing Inception V3, VGG 16, VGG 19, CNN, and ResNet 50: A Case Study on Early Detection of a Rice Disease”
by Syed Rehan Shah, Salman Qadri, Hadia Bibi, Syed Muhammad Waqas Shah, Muhammad Imran Sharif and Francesco Marinello
Agronomy 2023, 13(6), 1633; https://doi.org/10.3390/agronomy13061633
Full text available online: https://www.mdpi.com/2073-4395/13/6/1633

2. “Multi-Stage Corn Yield Prediction Using High-Resolution UAV Multispectral Data and Machine Learning Models”
by Chandan Kumar, Partson Mubvumba, Yanbo Huang, Jagman Dhillon and Krishna Reddy
Agronomy 2023, 13(5), 1277; https://doi.org/10.3390/agronomy13051277
Full text available online: https://www.mdpi.com/2073-4395/13/5/1277

3. “Improving Deep Learning Classifiers Performance via Preprocessing and Class Imbalance Approaches in a Plant Disease Detection Pipeline”
by Mike O. Ojo and Azlan Zahid
Agronomy 2023, 13(3), 887; https://doi.org/10.3390/agronomy13030887
Full text available online: https://www.mdpi.com/2073-4395/13/3/887

4. “Applying IoT Sensors and Big Data to Improve Precision Crop Production: A Review”
by Tarek Alahmad, Miklós Neményi and Anikó Nyéki
Agronomy 2023, 13(10), 2603; https://doi.org/10.3390/agronomy13102603
Full text available online: https://www.mdpi.com/2073-4395/13/10/2603

5. “Deep Learning YOLO-Based Solution for Grape Bunch Detection and Assessment of Biophysical Lesions”
by Isabel Pinheiro, Germano Moreira, Daniel Queirós da Silva, Sandro Magalhães António Valente, Paulo Moura Oliveira Mário Cunha and Filipe Santos
Agronomy 2023, 13(4), 1120; https://doi.org/10.3390/agronomy13041120
Full text available online: https://www.mdpi.com/2073-4395/13/4/1120

6. “Complementary Use of Ground-Based Proximal Sensing and Airborne/Spaceborne Remote Sensing Techniques in Precision Agriculture: A Systematic Review”
by Angelos Alexopoulos, Konstantinos Koutras, Sihem Ben Ali, Stefano Puccio, Alessandro Carella, Roberta Ottaviano and Athanasios Kalogeras
Agronomy 2023, 13(7), 1942; https://doi.org/10.3390/agronomy13071942
Full text available online: https://www.mdpi.com/2073-4395/13/7/1942

7. “Challenges and Opportunities of Agriculture Digitalization in Spain”
by Ebrahim Navid Sadjadi and Roemi Fernández
Agronomy 2023, 13(1), 259; https://doi.org/10.3390/agronomy13010259
Full text available online: https://www.mdpi.com/2073-4395/13/1/259

8. “Efficiency of Fungicide Application and Using an Unmanned Aerial Vehicle and Pneumatic Sprayer for Control of Hemileia vastatrix and Cercospora coffeicola in Mountain Coffee Crops”
by Edney Leandro da Vitória, Cesar Abel Krohling, Felipe Ruela Pereira Borges, Luis Felipe Oliveira Ribeiro, Maria Eduarda Audizio Ribeiro, Pengchao Chen, Yubin Lan, Shizhou Wang, Hugo Marcus Fialho e Moraes and Marconi Ribeiro Furtado Júnior
Agronomy 2023, 13(2), 340; https://doi.org/10.3390/agronomy13020340
Full text available online: https://www.mdpi.com/2073-4395/13/2/340

9. “A Lightweight YOLOv8 Tomato Detection Algorithm Combining Feature Enhancement and Attention”
by Guoliang Yang, Jixiang Wang, Ziling Nie, Hao Yang and Shuaiying Yu
Agronomy 2023, 13(7), 1824; https://doi.org/10.3390/agronomy13071824
Full text available online: https://www.mdpi.com/2073-4395/13/7/1824

10. “Fruit Detection and Recognition Based on Deep Learning for Automatic Harvesting: An Overview and Review”
by Feng Xiao, Haibin Wang, Yueqin Xu and Ruiqing Zhang
Agronomy 2023, 13(6), 1625; https://doi.org/10.3390/agronomy13061625
Full text available online: https://www.mdpi.com/2073-4395/13/6/1625