Environmental-Aware Intelligent Precision Agriculture: Fuzzy Logic and AI-Based Adaptive Herbicide Spraying Strategy for Ragweed

Abstract

The widespread presence of ragweed (Ambrosia artemisiifolia) poses a significant threat to agricultural productivity and biodiversity across multiple cropping systems. Traditional herbicide application methods often result in overuse, environmental contamination, and ineffective weed suppression, especially under variable environmental conditions such as fluctuating temperature, humidity, and wind speed. These conventional approaches apply uniform spray rates regardless of individual plant characteristics or local environmental factors, leading to substantial chemical waste and increased environmental risks. In this work, we propose an intelligent precision spraying control system that integrates a novel fuzzy logic controller to dynamically adjust herbicide application in real-time based on multiple input parameters. Unlike existing studies that rely on uniform broadcast rates or simple threshold-based activation, the proposed system performs per-plant adaptive mixing and dosage control, representing a novel decision layer in precision weed management. The fuzzy logic controller processes seven input parameters, including plant height, leaf area index, temperature, humidity, wind speed, water pH, and resistance risk, and generates optimized outputs for water amount, herbicide selection, surfactant type, adjuvant selection, and drift control agent. Simulation results using ten synthetic test cases representing diverse field conditions demonstrated an approximately 15% reduction in per-plant spray volume, and potential total-use reductions of 25–30% when combined with selective spot-spray activation compared with the conventional 100-200 L ha⁻¹ broadcast baseline derived from field guidelines and extension recommendations. The controller successfully adapted spray composition to varying plant sizes and environmental conditions, with taller plants and higher leaf area index receiving proportionally higher dosages while maintaining efficacy. These findings highlight the potential of adaptive fuzzy control to minimize chemical input, reduce spray drift, and improve environmental sustainability in precision agriculture systems. The proposed controller is scalable for autonomous UAVs and robotic agricultural platforms, making it a viable solution for precision ragweed management in modern farming operations.

Keywords

• Intelligent agricultural robotics
• Precision agriculture
• Adaptive decision systems
• Environmental-aware spraying
• Herbicide control
• Smart agriculture

Çevresel Farkındalıklı Akıllı Hassas Tarım: Pelin Otu İçin Bulanık Mantık ve Yapay Zekâ Tabanlı Uyarlanabilir Herbisit Püskürtme Stratejisi

Abstract

Ambrosia artemisiifolia (yabani pelin) türünün yaygın varlığı, tarımsal verimlilik ve biyolojik çeşitlilik için önemli bir tehdit oluşturmaktadır. Geleneksel herbisit uygulama yöntemleri genellikle aşırı kimyasal kullanımına, çevresel kirliliğe ve özellikle değişken çevre koşulları altında etkisiz yabancı ot bastırmasına yol açmaktadır. Bu çalışmada, herbisit uygulamasını gerçek zamanlı olarak dinamik biçimde ayarlayan yenilikçi bir bulanık mantık denetleyicisini entegre eden akıllı bir hassas püskürtme sistemi kontrolörü önerilmektedir. Mevcut çalışmalarda kullanılan sabit yayma oranlarının aksine, önerilen sistem bitki bazında uyarlanabilir karışım ve doz kontrolü gerçekleştirmekte olup, hassas yabancı ot yönetiminde yeni bir karar katmanı temsil etmektedir. Simülasyon sonuçları, önerilen sistemin, tarla kılavuzlarından alınan 100–200 L/ha’lık geleneksel yayma uygulamasına kıyasla toplam herbisit kullanımını ortalama %30 oranında azalttığını göstermiştir. Bu bulgular, uyarlanabilir bulanık denetimin kimyasal girdiyi en aza indirme, püskürtme sürüklenmesini azaltma ve çevresel sürdürülebilirliği geliştirme potansiyelini vurgulamaktadır. Önerilen denetleyici, otonom İHA’lar ve tarımsal robotik platformlara ölçeklenebilir niteliktedir ve modern tarımda hassas yabani ot yönetimi için uygulanabilir bir çözüm sunmaktadır.

Keywords

• Akıllı tarımsal robotik sistemler
• Hassas tarım
• Uyarlamalı karar verme sistemleri
• Çevresel koşullara duyarlı püskürtme
• Herbisit kontrolü
• Akıllı tarım

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