Zeytin Verim Tahmininde Kullanılan Sayısal Modellere İlişkin Bir Literatür Araştırması

Year 2021, Issue: 24, 351 - 358, 15.04.2021

İnanç Kabasakal , Murat Özaltaş

https://doi.org/10.31590/ejosat.900368

Abstract

Verim tahmini, tarımsal ürünlerin pazarlanmasında üreticiler ve diğer paydaşlar için önemli girdi sağlamaktadır. Zeytin verim tahmini çalışmalarında çeşitli yöntemler ile meteorolojik ve fenolojik ölçümlere dayalı verilerin incelendiği görülmektedir. Bu çalışmada, zeytin verim tahminleme çalışmalarına ilişkin bir derleme sunularak, bu kapsamda kullanılmış yaygın yöntemler ele alınmaktadır. İncelenen çalışmalar, polen endeksi ve zeytin verimi tahmini odaklı modeller biçiminde iki ana grupta toplanmıştır. Bununla birlikte, sunulan modellerde yaygın olarak kullanılan yöntemler ile incelenen nitelikler ele alınmış, İzmir’de başlayan zeytin verim tahmini projesi kapsamında elde edilen öncü veriler sunulmuştur. Son olarak, zeytin verim tahmini modellerinde incelenen nitelikler ve kullanılan yöntemlere ilişkin değerlendirmelere yer verilmiştir.

Keywords

Zeytin Verim Tahmini, Tahminleme Modelleri, Zeytin

Supporting Institution

T.C. Tarım ve Orman Bakanlığı

Project Number

TAGEM/TSKA D/B/18/A9/P6/1246

Thanks

Bu çalışma, Türkiye Cumhuriyeti Tarım ve Orman Bakanlığı tarafından desteklenen ve Bornova Zeytincilik Araştırma Enstitüsü tarafından yürütülen 'Zeytin Verim Tahmininde Polen Konsantrasyonu ve Bazı İklim Verileri Arasındaki İlişkilerin Belirlenmesi' projesi kapsamında gerçekleştirilmiştir.

A Review of Literature on the Quantitative Methods for Olive Yield Forecasting

Abstract

Yield forecasting is a task that provides critical inputs for producers and other stakeholders in agricultural marketing. Various methods have been applied to forecast olive yield in prior studies that primarily analyze datasets involving meteorological and phenological measurements. Our study reviews the prior literature on olive yield forecasting and explores the prominent methods employed in this context. Accordingly, we categorize prior models into two broad groups: pollen index forecasting and olive yield forecasting models. Moreover, our study highlights the popular methods and attributes involved in previous research, and reports the initial findings of the ongoing olive-yield forecasting project held in İzmir, Turkey. Finally, a discussion is presented regarding the techniques utilized and the attributes analyzed in forecasting models.

Keywords

Olive Yield Forecasting, Forecasting Models, Olive

Project Number

TAGEM/TSKA D/B/18/A9/P6/1246

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