Yabancı Ot Biliminde İnovasyon ve Teknolojik Eğilimler: Bibliyometrik Bir Analiz

Year 2025, Volume: 1 Issue: 1, 33 - 43, 30.09.2025

Harun Alptekin , Ramazan Gürbüz

Abstract

Yabancı otlar, tarımın başlangıcından bu yana bitkisel üretimde önemli sorunların başında gelmektedir. Bu nedenle, yabancı otların neden olduğu olumsuz etkileri en aza indirmek amacıyla çeşitli mücadele yöntemleri uygulanmaktadır. Ancak geleneksel yöntemler olan mekanik toprak işleme ve yoğun herbisit kullanımı, zamanla toprak bozulmasına, verimliliğin azalmasına ve çevresel kirliliğin artmasına yol açmaktadır. Bu olumsuzluklar, sürdürülebilir yabancı ot yönetimini sağlamak için teknoloji ve inovasyona dayalı yeni yaklaşımların geliştirilmesini zorunlu kılmıştır. Bilgisayar teknolojileri ve otomasyondaki ilerlemeler, yabancı otları kültür bitkilerinden ayırmayı ve hassas yabancı ot kontrolünü mümkün kılan makine görüşü ile küresel konumlama sistemlerine dayalı yeni yöntemlerin ortaya çıkmasına neden olmuştur. Bu teknolojiler, ister kimyasal ister mekanik temelli olsun, etkili ve verimli yabancı ot yönetimi için önemli fırsatlar sunmaktadır. Bu çalışmada, yabancı ot bilimi alanında inovasyona ve yeni teknolojilere yönelik araştırmalar bibliyometrik yöntemlerle analiz edilmiştir. Analiz sonuçları, son yıllarda “machine learning”, “deep learning” ve “smart agriculture” gibi kavramların öne çıktığını ve dijital tarım teknolojilerine yönelimin giderek arttığını göstermektedir. Elde edilen bulgular, yabancı ot mücadelesinde inovasyonun geleneksel kimyasal yöntemlerden uzaklaşıp sürdürülebilir, teknoloji odaklı ve entegre yaklaşımlara evrildiğini ortaya koymaktadır. Bu durum, gelecekte yapay zekâ ve hassas tarım uygulamalarının yabancı ot biliminin araştırma gündeminde daha belirgin bir şekilde yer alacağını işaret etmektedir.

Keywords

Akıllı tarım , Hassas tarım , Herbisit dayanıklılığı , Yabancı ot

Innovation and Technological Trends in Weed Science: A Bibliometric Analysis

Abstract

Weeds have been a major problem in crop production since the dawn of agriculture. Therefore, various control methods have been implemented to minimize the negative effects of weeds. However, traditional methods of mechanical tillage and intensive herbicide use have led to soil degradation, decreased fertility, and increased environmental pollution over time. These challenges have necessitated the development of new approaches based on technology and innovation to ensure sustainable weed management. Advances in computer technologies and automation have led to the emergence of new methods based on machine vision and global positioning systems that enable the separation of weeds from crops and precise weed control. These technologies, whether chemically or mechanically based, offer significant opportunities for effective and efficient weed management. This study analyzes research on innovation and new technologies in weed science using bibliometric methods. The analysis results demonstrate the prominence of concepts such as "machine learning," "deep learning," and "smart agriculture" in recent years, and the increasing focus on digital agricultural technologies. The findings reveal that innovation in weed control is evolving away from traditional chemical methods and toward sustainable, technology-driven, and integrated approaches. This suggests that artificial intelligence and precision agriculture applications will feature more prominently in the weed science research agenda in the future.

Keywords

Smart agriculture , Precision agriculture , Herbicide resistance

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