Towards a true conservation zero tillage system: “A proposed solution based on computer vision to herbicide resistance.”

🌱 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 detection during herbicide application. 🌱 The focus? Troublesome species like Amaranthus palmeri, Echinochloa crus-galli, Eleusine indica, Parietaria debilis, and Conyza sumatrensis. 🌿
🤖 We employed cutting-edge machine learning with features like SIFT, K-means, and Bag of Features, coupled with Support Vector Machine for classification. 📊 The result? A remarkable accuracy of 89% to 98%, paving the way for targeted herbicide application and reducing environmental impact! 🎉
🚀 But there’s more! Virtual binary maps from weed patches are set to be implemented through the ISOBUS protocol, revolutionizing weed control in ZT agriculture. 🗺️ This research marks a significant stride towards sustainable and efficient weed management in the ZT system! 🌱💡


Let’s cultivate a future where agriculture and conservation go hand in hand!

 

More info: https://doi.org/10.1016/j.compag.2023.108576

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