Bazı Ekmeklik ve Makarnalık Buğday Çeşitlerinde Sarı Pas Hastalığının Fenolojik Dönemlere göre Hastalık-Verim İlişkisinin Çok Bantlı (Hiperspektral) Veriler Kullanılarak Araştırılması

Year 2023, Volume: 37 Issue: 2, 401 - 423, 08.12.2023

Metin Aydoğdu Kadir Akan

https://doi.org/10.20479/bursauludagziraat.1245805

Abstract

Bu çalışma, ekmeklik (Bayraktar 2000, Demir 2000, Eser ve Kenanbey) ve makarnalık (Çeşit-1252,
Eminbey, Kızıltan 91 ve Mirzabey 2000) buğday çeşitlerini kontrollü epidemi koşullarında farklı spor dozlarına (%0, %25, %50 ve %100) tabi tutarak farklı fenolojik dönemlerde sarı pas şiddetini değerlendirmeyi amaçlanmıştır. Araştırma 2018-2019 yetiştirme sezonunda Yenimahalle, Ankara, Türkiye'de yürütülmüştür. Çalışmada, kardeşlenmeden sapa kalkmaya kadar olan dönemde farklı spor dozu uygulamalarında el spektroradyometresi kullanılarak elde edilen yansıma değerleri ile test materyallerinin farklı fenolojik gelişim dönemlerinde sarı pas şiddetindeki morfolojik değişimler belirlenmiştir. Elde edilen bu yansıma değerleri matematiksel formüllerle ifade edilen vejetasyon indisi değerlerine dönüştürülerek verim tahminlerinin belirlenmesinde kullanılabilir hale getirilmiştir. Elde edilen sonuçlar dikkate alındığında, Kenanbey çeşidi (15 Haziran 2019, Feekes 10.5.4) hariç, tüm ekmeklik çeşitler için özellikle erken çiçeklenme döneminde (25 Mayıs 2019, Feekes 10.5.1) hesaplanan spektral indekslerin verim tahmininde etkili olduğu belirlenmiştir. Tüm ekmeklik ve makarnalık çeşitlerde verimi tahmin etmek için belirlenen tüm indeksleri içeren ve çiçeklenme başlangıcı olan 25 Mayıs 2019 (Feekes 10.5.1) tarihli spektral bant bölgesinin etkili olduğu tespit edilmiştir. Tane verimi tahmininde erken çiçeklenme başlangıç döneminden (Feekes 10.5.1) başlayarak tane bağlama dönemi (Feekes 10.5.3) ve süt olum dönemine (Feekes 10.5.4) doğru spektral indekslerin korelasyon değerlerinde azalma olduğu tespit edilmiştir. Elde edilen bu indeks değerleri ile verim değerleri arasındaki korelasyonlar incelendiğinde öne çıkan fenolojik dönemler ve bu dönemlere ilişkin yüksek korelasyona sahip indekslerinin hesaplanabildiği belirlenmiştir. Günümüzde artık geleneksel hastalık takip yöntemlerinin yerine optik sensör teknolojisinin kullanımı ile verim tahmininde multispektral ve hiperspektral kameraların üzerinde yer aldığı insansız hava araçları ile alınan görüntülerin yapay zeka ve derin öğrenme teknikleri kullanılarak yersel verilerle doğrulanması sonucu erken dönemde hızlı ve doğru bir şekilde verim tahminine yönelik yeni yaklaşımların geliştirilmesinin yolu açılmıştır.

Keywords

Buğday, hiperspektral veri, sarı pas (Puccinia striiformis f. sp. tritici) hastalığı, spektral indeks, verim tahmini

Project Number

YÖK Thesis No: 671046/Date: 25.05.2021.

Investigation of Disease-Yield Relationship of Yellow Rust in Some Bread and Durum Wheat Varieties by Phenological Periods Using Hyperspectral Data

Abstract

The aim of this study was to evaluate the severity of yellow rust in different phenological periods by
subjecting bread (Bayraktar 2000, Demir 2000, Eser and Kenanbey) and durum (Çeşit-1252, Eminbey, Kızıltan 91 and Mirzabey 2000) wheat varieties to different spore doses (0%, 25%, 50% and 100%) under controlled epidemic conditions. The research was conducted in Yenimahalle, Ankara, Turkey during the 2018-2019 growing season. In the study, the morphological changes in yellow rust severity were determined at different phenological developmental stages of the test materials with the reflectance values obtained by using handheld spectroradiometer in different spore dose applications during the period from tillering to stalk emergence. These reflectance values were converted into vegetation index values expressed by mathematical formulae and used in determining yield estimates. Considering the results obtained, it was determined that the spectral indices calculated especially in the early flowering period (25 May 2019, Feekes 10.5.1) were effective in yield estimation for all bread varieties except Kenanbey variety (15 June 2019, Feekes 10.5.4). It was determined that the spectral band region of 25 May 2019 (Feekes 10.5.1), which includes all indices determined to predict yield in all bread and durum varieties and which is the beginning of flowering, was effective. In grain yield estimation, it was determined that there was a decrease in the correlation values of the spectral indices starting from the early flowering period (Feekes 10.5.1) towards the grain setting period (Feekes 10.5.3) and milk maturity period
(Feekes 10.5.4). When the correlations between these index values and yield values were examined, it was
determined that prominent phenological periods and high correlation indices could be calculated for these periods. Nowadays, with the use of optical sensor technology instead of traditional disease surveillance methods, the way has paved the way for the development of new approaches for early, fast and accurate yield estimation as a result of the verification of images taken by unmanned aerial vehicles on which multispectral and hyperspectral cameras are located with ground data using artificial intelligence and deep learning techniques.

Keywords

Hyperspectral data, spectral indice, wheat, yellow rust desease (Puccinia striiformis f. sp. tritici), yield estimate

Supporting Institution

The Field Crop Research Center Institute in ANKARA ,The Soil, Fertilizer and Water Resources Central Resarch Institute

Project Number

YÖK Thesis No: 671046/Date: 25.05.2021.

Thanks

This study was carried out by Metin AYDOĞDU in the master's thesis "Determination of the Seasonal Effects of Different Iron and Zinc Applications on Yellow Rust (Puccinia striiformis f. sp. tritici) Disease in Winter Wheat Using Multi-Band Data" at Kırşehir Ahi Evran University, Institute of Science, Department of Agricultural Biotechnology. (YÖK Thesis No: 671046/Date: 25.05.2021).We would like to thank the Department of Plant Diseases of the Central Research Institute of Agricultural Control who contributed to the preparation and execution of the thesis, to Dr. Nilüfer AKCI, Thesis Jury members; from Harran University, Faculty of Agriculture, Department of Soil Science and Plant Nutrition Prof.Dr. Hikmet GÜNAL to Dr. Nurullah ACİR from Kırşehir Ahi Evran University, Faculty of Agriculture, Department of Soil Science and Plant Nutrition for his contributions.

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