AgriEngineering MDPI

25/07/2025

🚨 Volume 7, Issue 6 released!

🚜 All 35 Articles published in AgriEngineering, Volume 7, Issue 6 (June 2025) are available in on:

🖇️ https://bit.ly/45d55vI

09/07/2025

📄 New paper online: Stone Detection on Agricultural Land Using Thermal Imagery from Unmanned Aerial Systems

Authors: Florian Thürkow, Mike Teucher, Detlef Thürkow and Milena Mohri

🖇️ Read it in : https://bit.ly/4lKwHPl

Abstract: Stones in agricultural fields pose a recurring challenge, particularly due to their potential to damage agricultural machinery and disrupt field operations. As modern agriculture moves toward automation and precision farming, efficient stone detection has become a critical concern. This study explores the potential of thermal imaging as a non-invasive method for detecting stones under varying environmental conditions. A series of controlled laboratory experiments and field investigations confirmed the assumption that stones exhibit higher surface temperatures than the surrounding soil, especially when soil moisture is high and air temperatures are cooling rapidly. This temperature difference is attributed to the higher thermal inertia of stones, which allows them to absorb and retain heat longer than soil, as well as to the evaporative cooling from moist soil. These findings demonstrate the viability of thermal cameras as a tool for stone detection in precision farming. Incorporating this technology with GPS mapping enables the generation of accurate location data, facilitating targeted stone removal and reducing equipment damage. This approach aligns with the goals of sustainable agricultural engineering by supporting field automation, minimizing mechanical inefficiencies, and promoting data-driven decisions. Thermal imaging thereby contributes to the evolution of next-generation agricultural systems.

🖇️ Read it in : https://bit.ly/4lKwHPl

Stones in agricultural fields pose a recurring challenge, particularly due to their potential to damage agricultural machinery and disrupt field operations. As modern agriculture moves toward automation and precision farming, efficient stone detection has become a critical concern. This study explor...

01/07/2025

🚀 New Section Launch in AgriEngineering!

🌿 Sustainable Bioresource and Bioprocess Engineering

🔧 Focused on engineering innovations in agricultural bioprocessing and bioresource utilization.

The Section Editor in Chief: Prof. Dr. Francesco Marinello

📝 Now open for submissions!

🔗 https://bit.ly/4lzD3RA

Key topics include engineering aspects of the following:

- Biofuels: production, modeling and other analyses of liquid and gaseous biofuels such as ethanol and biobutanol.

- Bioprocesses and Bioproducts: fermentation, biocatalysis, microbial and enzymatic processing, strain improvement and scale-up.

- Biomass Utilization: valorization of agricultural and industrial residues into energy, bioplastics, enzymes and platform chemicals.

- Environmental Protection: includes technologies for the biological treatment of waste, composting, anaerobic digestion and sustainable waste management.

- Thermochemical and Electrochemical Conversion: technologies for combustion, pyrolysis, gasification, catalysis and electrochemical valorization of biomass.

- Other Technological Systems: design and optimization of fermenters and bioreactors, bioprocess control, energy and mass balances and system integration.

- Sustainability Metrics: assessment of environmental impacts including carbon, water, energy, nitrogen and digitization footprints.

🔗 https://bit.ly/4lzD3RA

27/05/2025

👥 Meet AgriEngineering at the 60th Croatian and 20th International Symposium on Agriculture!
📆 1–6 June 2025
📌 Bol, Croatia

🙋‍♀️🙋‍♂️Our journal is excited to have the opportunity to connect with you in person.

More info: https://bit.ly/3HeHjXS

26/05/2025

☘️ The new Special Issue is online: "Digital Agroecology: Sensor and Data Technologies to Promote Regenerative Food Systems"

Editors: Gerardo Grasso, Marcello Biocca and Oriana Gava

Check more information and submit at:
🔗 https://bit.ly/4dzsdrW

13/05/2025

🚜 AgriEngineering's First Topical Collection: "Research Progress of Machinery Testing" is now online!

Editors: Prof. Dr. Kléber Pereira Lanças, Prof. Dr. Daniel Albiero, Prof. Dr. Alberto Kazushi Nagaoka and Prof. Dr. Francesco Marinello

📄 Read published papers or submit your own: https://brnw.ch/21wSBFr

21/03/2025

🚨 Volume 7, Issue 2 released!

🐔 All 27 Articles published in AgriEngineering, Volume 7, Issue 2 (February 2025) are available in on:

🖇️ https://bit.ly/4iow78E

26/02/2025

🛰️ New Article is online: "Integrating Statistical and Earth in Small Farming Systems for "

Authors: Theodore Tsiligiridis and Katerina Ainali from Γεωπονικό Πανεπιστήμιο Αθηνών - Agricultural University of Athens -Οfficial

🖇️Read it in : https://www.mdpi.com/3193706

"An integrated method for providing crop estimates in the context of small farming systems is developed and implemented. The combined data are derived from a novel (RS) approach, the geodatabase of farmers' declarations for subsidies, and official statistics. Fast monitoring of cultivation changes can also be mapped."

🖇️Read it in : https://www.mdpi.com/3193706

The present work unveils the role of small farming plots (less than 5 ha) in the context of food security. It determines their contribution by estimating the spatial distribution (location), the crop types (diversity), the crop area extent (acreage), and the yield (production), factors that remain u...

12/02/2025

🚨 Volume 6, Issue 4 released!

🍇 All 83 Articles published in AgriEngineering, Volume 6, Issue 4 (December 2024) are available in on:

🖇️ https://bit.ly/3CNYjlK

17/12/2024

🌾The New Article is online: "Using Data-Driven Techniques to Improve Wheat Yield Prediction"

Authors: Merima Smajlhodžić-Deljo, Madžida Hundur Hiyari, Lejla Gurbeta Pokvić, Nejra Merdović, Faruk Bećirović, Lemana Spahić from Verlab Institute and Željana Grbović, Dimitrije Stefanović, Ivana Miličić, Oskar Marko from BioSense Institute

🖇️Read it in : https://bit.ly/49Fi8rg

Abstract: Accurate ear counting is essential for determining wheat yield, but traditional manual methods are labour-intensive and time-consuming. This study introduces an innovative approach by developing an automatic ear-counting system that leverages machine learning techniques applied to high-resolution images captured by unmanned aerial vehicles (UAVs). Drone-based images were captured during the late growth stage of wheat across 15 fields in Bosnia and Herzegovina. The images, processed to a resolution of 1024 × 1024 pixels, were manually annotated with regions of interest (ROIs) containing wheat ears. A dataset consisting of 556 high-resolution images was compiled, and advanced models including Faster R-CNN, YOLOv8, and RT-DETR were utilised for ear detection. The study found that although lower-quality images had a minor effect on detection accuracy, they did not significantly hinder the overall performance of the models. This research demonstrates the potential of digital technologies, particularly machine learning and UAVs, in transforming traditional agricultural practices. The novel application of automated ear counting via machine learning provides a scalable, efficient solution for yield prediction, enhancing sustainability and competitiveness in agriculture.

Keywords: ; ; ; ; -timeprocessing;

🖇️Read it in : https://bit.ly/49Fi8rg

13/12/2024

🌱 New Article is online: "Development and Evaluation of a Laser System for Autonomous Weeding Robots"

Authors: Vitali Czymmek, Jost Völckner and Stephan Hussmann from Fachhochschule Westküste

🖇️Read it in : https://bit.ly/3OVK8xi

Abstract: Manual w**d control is becoming increasingly costly, necessitating the development of alternative methods. This work investigates the feasibility of using laser technology for autonomous w**d regulation. We developed a system utilizing a laser scanner to target and eliminate w**ds, which was first tested using a pilot laser for accuracy and performance. Subsequently, the system was upgraded with a high-power fiber laser. Experimental results demonstrated a high w**d destruction accuracy with real-time capabilities. The system achieved efficient w**d control with minimal environmental impact, providing a potential alternative for sustainable agriculture.

Keywords: ; **dcontrol; ; ;

🖇️Read it in : https://bit.ly/3OVK8xi

Manual w**d control is becoming increasingly costly, necessitating the development of alternative methods. This work investigates the feasibility of using laser technology for autonomous w**d regulation. We developed a system utilizing a laser scanner to target and eliminate w**ds, which was first t...

19/11/2024

🌟 AgriEngineering Outstanding Reviewer Award 🌟

Each year, we honor one exceptional reviewer for their dedication, professionalism, and timeliness in reviewing papers.

🏆 Prize: – CHF 500 – Free article processing voucher (valid 1 year) – Certificate

📅 Winner announcement: 31 March 2025

All reviewers from the past year are eligible—evaluated on the quality, quantity, and timeliness of reviews.

🖇 More information: https://bit.ly/4fwL5b3