Yem Bitkileri Üreticileri İçin Tarımsal İlaçlama Dronu Seçimi: Çok Kriterli Karar Verme Yaklaşımı

Öz

Tarımsal üretimde iş gücü yetersizliği, artan girdi maliyetleri ve sürdürülebilirlik gereksinimleri, insansız hava araçlarının (İHA) özellikle pestisit uygulamalarında kullanımını hızla yaygınlaştırmıştır. Buna karşın, tarımsal ilaçlama dronu seçimi; teknik performans, operasyonel verimlilik ve maliyet gibi çok sayıda ve birbiriyle çelişebilen kriterin birlikte değerlendirilmesini gerektiren karmaşık bir karar problemidir. Literatürde yem bitkileri üreticilerine odaklanan, sistematik ve bütünleşik karar modellerinin sınırlı olması bu çalışmanın temel çıkış noktasını oluşturmaktadır. Bu çalışmanın amacı, yem bitkileri üreticileri için en uygun tarımsal ilaçlama dronunun belirlenmesine yönelik bütünleşik bir Çok Kriterli Karar Verme (ÇKKV) modeli geliştirmektir. Bu kapsamda, İzmir ilinde faaliyet gösteren deneyimli üreticilerden elde edilen uzman görüşleri doğrultusunda kriter ağırlıkları Analitik Hiyerarşi Süreci (AHP) ve SWARA yöntemleriyle belirlenmiş; drone alternatiflerinin performansı ise ARAS ve TOPSIS yöntemleri kullanılarak analiz edilmiştir. Analiz sonuçları, her iki ağırlıklandırma yönteminde de püskürtme performansı, uçuş süresi ve menzil/kontrol menzilinin ilk üç sırada yer aldığını göstermiştir. ARAS–AHP ve TOPSIS–SWARA analizlerinde DJI Agras birinci, Mostaş Teknoloji ikinci ve XAG üçüncü sırada yer almıştır. Dört yöntem-ağırlık kombinasyonunda alternatif sıralamasının değişmemesi, yöntemler arası sağlamlığı desteklemiştir. Sonuç olarak çalışma, yem bitkileri üreticilerinin farklı dron alternatiflerini sistematik biçimde karşılaştırmalarına yardımcı olan uygulanabilir bir karar destek çerçevesi sunmaktadır.

Anahtar Kelimeler

• Tarımsal İHA
• Tarımsal İlaçlama Dronu
• Yem Bitkileri Üreticileri
• Çok Kriterli Karar Verme
• Dron Seçimi

Etik Beyan

“Yem Bitkileri Üreticileri İçin Tarımsal İlaçlama Dronu Seçimi: Çok Kriterli Karar Verme Yaklaşımı” başlıklı çalışmanın yazım sürecinde bilimsel kurallara, etik ve alıntı kurallarına uyulmuş; toplanan veriler üzerinde herhangi bir tahrifat yapılmamış ve bu çalışma herhangi başka bir akademik yayın ortamına değerlendirme için gönderilmemiştir. Gerekli olan etik kurul izinleri Dokuz Eylül Üniversitesi, İnsan Araştırmaları Kurulu’nun 17.12.2025 tarih ve 44 sayılı toplantısında alınmıştır. Çatışma Beyanı: Çalışmada herhangi bir potansiyel çıkar çatışması söz konusu değildir. Finansman: Bu çalışma için herhangi bir kurum veya kuruluştan destek alınmamıştır. Yapay Zeka ve Türleri Kullanım Beyanı: Bu makalenin yazımında yapay zeka ve türleri kullanılmamıştır. Veri Paylaşım Beyanı: Bu çalışmanın verilerini bulguların doğrulanması amacıyla makul bir talep üzerine “etik ilkeler ve yayın politikası”nın ilgili kısmında belirtilen şartlara göre paylaşabileceğimi beyan ederim.

Selection of Agricultural Spraying Drones for Forage Crop Producers: A Multi-Criteria Decision-Making Approach

Öz

The increasing labor shortages in agriculture, rising input costs, and the growing emphasis on sustainability have accelerated the adoption of unmanned aerial vehicles (UAVs), particularly for pesticide application processes. However, selecting an appropriate agricultural spraying drone constitutes a complex decision-making problem, as it requires the simultaneous evaluation of multiple and often conflicting criteria such as technical performance, operational efficiency, and cost. The limited number of systematic and integrated decision-support studies focusing specifically on forage crop producers highlights the necessity of this research. The aim of this study is to develop a comprehensive Multi-Criteria Decision-Making (MCDM) framework to determine the most suitable agricultural spraying drone for forage crop producers. In this context, expert evaluations obtained from experienced producers operating in İzmir Province were employed to determine criterion weights using the Analytic Hierarchy Process (AHP) and the Step-wise Weight Assessment Ratio Analysis (SWARA) methods. Subsequently, the performance of alternative drone models was assessed through the Additive Ratio Assessment (ARAS) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. The results showed that spraying performance, flight duration, and operational range were the three most important criteria in both weighting methods. In both the ARAS–AHP and TOPSIS–SWARA analyses, DJI Agras ranked first, Mostaş Teknoloji second, and XAG third. The unchanged alternative ordering across all four weighting–ranking combinations supported cross-method robustness. Overall, this study provides a reliable and practical decision-support tool for forage crop producers and contributes to agricultural modernization strategies as well as the development of domestic UAV technologies.

Anahtar Kelimeler

• Agricultural UAV
• Agricultural Spraying Drone
• Forage Crop Producers
• Multi-Criteria Decision-Making
• Drone Selection

Etik Beyan

During the writing process of the study “Selection of Agricultural Spraying Drones for Forage Crop Producers: A Multi-Criteria Decision-Making Approach” scientific rules, ethical and citation rules were followed. No falsification was made on the collected data and this study was not sent to any other academic publication medium for evaluation. Ethics Committee Permission is not required. In addition, permission was obtained from the Dokuz Eylül University Humanities Sciences Ethics Committee (Date: 17/12/2025 and Decision no: 44) to conduct the research. Declaration of Conflict: There is no potential conflict of interest in the study. Funding: No funding was received from any institution or organization for this study. Statement of Use for Artificial Intelligence and Its Types: Artificial intelligence and its various types were not used in the writing of this article. Data Sharing Statement: I declare that, upon reasonable request for the purpose of verifying the findings, I can share the data of this study according to the conditions specified in the relevant section of the "ethical principles and publication policy".

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