Author name: Hugo Moreno

The integration of artificial intelligence (AI) with mechanical and chemical techniques is revolutionizing weed management in agriculture. This technological convergence offers more effective, precise, and sustainable solutions that align with the demand for environmentally responsible farming practices. AI enables precise weed identification using advanced tools like computer vision, robotic platforms, drones, and sensors. This facilitates […]

Hortícola Norte 2025, held on January 15, 2025, at the Sala Cultural Alfonsa de la Torre, brought together leading experts, researchers, and professionals to showcase the latest innovations shaping the agricultural sector. Organized by Interempresas Media, this event addressed critical challenges and opportunities, providing a platform for collaboration and knowledge exchange. A key highlight of

The images from the tomato fields in Badajoz during harvest, overrun by weeds despite herbicide applications, serve as a stark reminder of the pressing need for effective weed control in agriculture. Weeds, as relentless competitors for essential resources, can significantly impact crop yields and jeopardize the sustainability of farming practices. In some cases, uncontrolled weed

Take a closer look at these images (at the end of the text) from the experimental tomato commercial fields in Badajoz, where a significant weed infestation is evident. This infestation is a result of the reduced efficacy of traditional herbicide treatments, underscoring the urgent need for more effective weed management strategies. In response to this

Dr. Dionisio Andújar recently presented the latest results of the SWEET project (Sustainable Weed Management by Agroecological and Technical Approaches) at the Euroleague for Life Sciences Study Group on Robotic Weeding (10 – 14 June 2024 – University of Hohenheim, UHOH). The Workshop was organized by Dr. Gerhards, Dr. Petenaitos, and Dr. Andújar. This presentation

Creating a comprehensive weed image dataset for tomato fields is essential for training deep learning algorithms, such as Convolutional Neural Networks (CNNs). These CNN models are particularly effective when trained on RGB images of various weed species. In our study, we focused on both monocotyledonous (Cyperus rotundus L., Echinochloa crus galli L., Setaria verticillata L.)

🌿 Updates from the XIX Congress of the Spanish Society of Weed Science (SEMh) in Beja, Portugal. Dr. Hugo Moreno and Dr. Dionisio Andújar have presented the progress of their research on the SWEET project (Sustainable Weed Management by Agroecological and Technical Approaches). This initiative aims to transform weed management by implementing artificial intelligence techniques

We are pleased to announce the start of the tomato planting season in Badajoz, Extremadura. Then, to pave the way for the next sampling campaign for site-specific weed management, employing advanced artificial intelligence technologies. This project will involve sampling various weeds as part of an effort to implement deep learning techniques for their classification and

🌱 Exciting News in Sustainable Agriculture! 🌾Embracing Zero Tillage (ZT) for greener fields! 🚜 This revolutionary agricultural approach aims at soil conservation, reduced fossil fuel usage, and mitigating pollution. 🌍 But there’s a challenge – resistant weed species threatening ZT success! 🌾🔍 Our 15-year study in Cordoba, Argentina, using ZT management delves into automatic weed

Greetings, agricultural aficionados! Agritechnica 2023 in Hannover is not only a showcase of cutting-edge agricultural technologies but also a stage for the remarkable contributions of the Sweet project (Sustainable weed management by agroecological and technical approaches). This year, members of the Sweet project have played a pivotal role in advancing sustainable agriculture, adding an extra