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Dergiler / Journal of Agricultural Biotechnology / 2025 / Cilt: 6 Sayı: 2

Entegre Zararlı Yönetimi Çalışmalarında Akıllı Tarım Sistemlerinin Kullanım Olanakları

Possibilities of Using Smart Agricultural Systems in Integrated Pest Management Studies

Ceyda Güler(Sakarya Uygulamalı Bilimler Üniversitesi, Lisansüstü Eğitim Enstitüsü, Bitki Koruma Anabilim Dalı, Türkiye)0000-0003-1395-3380
Bahadır Şin(SAKARYA UYGULAMALI BİLİMLER ÜNİVERSİTESİ, ZİRAAT FAKÜLTESİ, BİTKİ KORUMA BÖLÜMÜ)0000-0002-0109-3662
Salih Karabörklü(SAKARYA UYGULAMALI BİLİMLER ÜNİVERSİTESİ, ZİRAAT FAKÜLTESİ, BİTKİ KORUMA BÖLÜMÜ)0000-0003-4737-853X
Sayfa
81–97
Yayın Tarihi
2025-12-30
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Bu çalışma kapsamında, entegre zararlı yönetiminde akıllı tarım sistemlerinin kullanım olanakları ele alınmış ve zararlı böceklere yönelik yapılan araştırmalar derlenmiştir.

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Amaç & Hipotez:Entegre zararlı yönetimi (EZY),tarımsal üretimdeki zararlı popülasyonlarını ekonomik ve ekolojik açıdan makul seviyelerde tutmayı amaçlayan bir yaklaşımdır.
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Temel Bulgular & Veri:Tarım alanlarında zararlıların erken dönemde tespit edilmesi, popülasyon yoğunluğu artmadan gerekli önlemlerin alınması, uygun mücadele yönteminin belirlenmesi, verim ve kalite kayıplarının önlenmesi açısından büyük önem taşımaktadır.
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Sonuç & Katkı:Bu çalışma kapsamında, entegre zararlı yönetiminde akıllı tarım sistemlerinin kullanım olanakları ele alınmış ve zararlı böceklere yönelik yapılan araştırmalar derlenmiştir.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Akıllı Tarım Sistemleri · Entegre Zararlı Yönetimi · Zararlı Böcekler

Özet

Entegre zararlı yönetimi (EZY),tarımsal üretimdeki zararlı popülasyonlarını ekonomik ve ekolojik açıdan makul seviyelerde tutmayı amaçlayan bir yaklaşımdır. EZY, yalnızca zararlılarla mücadele etmeyi değil; çevre ve insan sağlığını korumayı, doğal düşmanları desteklemeyi ve ekonomik kayıpları minimize etmeyi hedeflemektedir. Günümüzde dijital teknolojilerin hızla gelişimi tarımsal alanlarda zararlı böceklerin hızlı ve doğru şekilde tespit edilmesine olanak tanımıştır. Tarım alanlarında zararlıların erken dönemde tespit edilmesi, popülasyon yoğunluğu artmadan gerekli önlemlerin alınması, uygun mücadele yönteminin belirlenmesi, verim ve kalite kayıplarının önlenmesi açısından büyük önem taşımaktadır. Nesnelerin interneti (IoT), sensörler, dronlar, görüntü işleme teknikleri, yapay zekâ destekli karar destek sistemleri ve otomasyon uygulamaları sayesinde zararlıların erken tespiti, popülasyon dinamiklerinin izlenmesi ve hedefe yönelik mücadeleyi mümkün hale getirmektedir. Bu teknolojiler, makine öğrenmesi ve derin öğrenme algoritmalarıyla birleştirildiğinde, zararlı popülasyonlarının izlenmesi, stres belirtilerinin tanımlanması ve mücadele stratejilerinin optimize edilmesi açısından önemli kazanımlar sağlamaktadır. Görüntü işleme ve sensör tabanlı sistemlerle yapılan çalışmalar, bitkilerde zararlı kaynaklı stresin spektral, termal veya akustik değişimlerle belirlenebildiğini ortaya koymaktadır. Özellikle dron tabanlı görüntüleme sistemleri ve otonom robotlar, geniş tarım alanlarında hızlı veri toplama ve yerinde değerlendirme olanağı sunarak klasik gözlem yöntemlerinin ötesine geçmektedir. Bu yaklaşım, yalnızca zararlı kontrolünde değil; aynı zamanda iklim değişikliğine uyum, kaynak verimliliği ve sürdürülebilir tarım hedeflerinin gerçekleştirilmesinde de stratejik bir öneme sahiptir. Bu durum hem pestisit kullanımının azaltılması hem de çevre dostu ve ekonomik bir üretim sürecinin desteklenmesine katkı sağlayacaktır. Bu çalışma kapsamında, entegre zararlı yönetiminde akıllı tarım sistemlerinin kullanım olanakları ele alınmış ve zararlı böceklere yönelik yapılan araştırmalar derlenmiştir.

Abstract

Integrated pest management (IPM) is an approach that aims to maintain pest populations in agricultural production at economically and ecologically reasonable levels. IPM aims not only to control pests but also to protect environmental and human health, support natural enemies, and minimize economic losses. Today, the rapid development of digital technologies has enabled the rapid and accurate detection of pests in agricultural areas. Early detection of pests in agricultural areas is crucial for taking the necessary precautions before population density increases, determining the appropriate control method, and preventing yield and quality losses. The Internet of Things (IoT), sensors, drones, image processing techniques, artificial intelligence-based decision support systems, and automation applications enable early detection of pests, monitoring population dynamics, and targeted control. When combined with machine learning and deep learning algorithms, these technologies provide significant benefits in monitoring pest populations, identifying stress symptoms, and optimizing control strategies. Studies using image processing and sensor-based systems have revealed that pest-induced stress in plants can be determined by spectral, thermal, or acoustic changes. Drone-based imaging systems and autonomous robots, in particular, offer rapid data collection and on-site assessment capabilities across large agricultural areas, surpassing traditional observation methods. This approach is strategically important not only for pest control but also for achieving climate change adaptation, resource efficiency, and sustainable agriculture goals. This will contribute to reducing pesticide use and supporting environmentally friendly and economical production processes. Based on this study, the potential use of smart agricultural systems in integrated pest management and compiles research on insect pests.

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Bu Makaleye Atıf Yap

Güler, C., Şin, B., Karabörklü, S. (2025). Entegre Zararlı Yönetimi Çalışmalarında Akıllı Tarım Sistemlerinin Kullanım Olanakları. Journal of Agricultural Biotechnology, Cilt: 6 Sayı: 2, 81–97. https://doi.org/10.58728/joinabt.1831254

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