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Journals / Türk Uzaktan Algılama ve CBS Dergisi / 2023 / Cilt: 4 Sayı: 2

Evaluation of Yellow Rust Reactions in some Bread and Durum Wheat Varieties by Using Spectral Band Regions

Bazı Ekmeklik ve Makarnalık Buğday Çeşitlerinde Spektral Bant Bölgeleri Kullanılarak Sarı Pas Hastalık Reaksiyonlarının Değerlendirilmesi

Metin AYDOĞDU
Kadir AKAN
Pages
166–186
Publication Date
2023-09-28
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Kızıltan 91 variety in Red+Red Edge+NIR region, Çeşit-1252 variety in Green+Red region, Eminbey and Mirzabey 2000 varieties in Green+Red+Red Edge were effective in band ranges in the region and showed an increase (+) in disease severity reactions.

📌 3 Key Takeaways

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Objective & Hypothesis:Yellow rust (caused by Puccinia striiformis f. sp. tritici) is an important fungal disease affecting wheat production and quality.
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Key Findings & Data:The purpose of this study was to identify the spectral band regions that influence how the disease changes throughout the year by determining how the plant responds to yellow rust when it is applied to test materials at various doses (0%, 25%, 50%, and 100%).
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Conclusion & Impact:Kızıltan 91 variety in Red+Red Edge+NIR region, Çeşit-1252 variety in Green+Red region, Eminbey and Mirzabey 2000 varieties in Green+Red+Red Edge were effective in band ranges in the region and showed an increase (+) in disease severity reactions.
🔬Design:Research Article
📍Scope:2000 Verileri
⚙️Variables:Buğday · Sarı pas (Puccinia striiformis f. sp. tritici) · Çok bantlı veri

Abstract

Yellow rust (caused by Puccinia striiformis f. sp. tritici) is an important fungal disease affecting wheat production and quality. The purpose of this study was to identify the spectral band regions that influence how the disease changes throughout the year by determining how the plant responds to yellow rust when it is applied to test materials at various doses (0%, 25%, 50%, and 100%). Eser, Bayraktar 2000 and Demir 2000 varieties showed high correlation in the early-mid period of the study for bread varieties, while Kenanbey variety exhibited high correlation in the mid-late period. Effective band region for all bread types are The Red+Red Edge+ Near Infrared (NIR) range and NIR range of the Kenanbey variety both showed an increase (+) in disease severity values. Eminbey and Çeşit-1252 varieties for durum varieties displayed high correlation in the early period, followed by Mirzabey 2000 variety in the early to medium period and Kızıltan-91 variety the mid to late period. Kızıltan 91 variety in Red+Red Edge+NIR region, Çeşit-1252 variety in Green+Red region, Eminbey and Mirzabey 2000 varieties in Green+Red+Red Edge were effective in band ranges in the region and showed an increase (+) in disease severity reactions.

Özet

Sarı pas (Etmen: Puccinia striiformis f. sp. tritici) hastalığı, buğday da üretim ve kaliteyi olumsuz yönde etkileyen önemli fungal bir hastalıktır. Bu araştırmanın amacı; test materyallerine farklı dozlarda (%0, %25, %50, %100) uygulanan sarı pas hastalığına karşı bitkinin gösterdiği reaksiyonların spektral özellikler yardımıyla belirlenmesi ve hastalığın mevsim içindeki değişimini etkileyen spektral bant bölgelerinin ortaya çıkarılmasıydı. Çalışma kapsamında, Ekmeklik çeşitler için; Eser, Bayraktar 2000 ve Demir 2000 çeşitleri erken-orta dönemde, Kenanbey çeşidi ise orta-geç dönemde yüksek korelasyon göstermiştir. Bütün ekmeklik çeşitler için etkili bant bölgesi olan Kırmızı+Kırmızı Kenar+ Yakın Kızıl Ötesi (NIR) aralığında, Kenanbey çeşidi ise NIR aralığında hastalık şiddeti değerlerinde artış (+) göstermiştir. Makarnalık çeşitler için; Eminbey ve Çeşit-1252 çeşitleri erken dönemde, Mirzabey 2000 çeşidi erken-orta dönemde, Kızıltan 91 çeşidi ise orta-geç dönemde yüksek korelasyon göstermiştir. Kızıltan 91 çeşidi ise Kırmızı+Kırmızı Kenar+NIR bölgede, Çeşit-1252 çeşidi Yeşil+Kırmızı bölgede, Eminbey ve Mirzabey 2000 çeşidi Yeşil+Kırmzı+Kırmızı Kenar bölgedeki, bant aralıklarında etkili olmuş ve hastalık şiddeti reaksiyonlarında artış (+) göstermiştir.

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Cite This Article

AYDOĞDU, M., AKAN, K. (2023). Evaluation of Yellow Rust Reactions in some Bread and Durum Wheat Varieties by Using Spectral Band Regions. Türk Uzaktan Algılama ve CBS Dergisi, Cilt: 4 Sayı: 2, 166–186. https://ajindex.com/articles/963471

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References (11)

  1. Abburu, S., & Golla, S. B. (2015). Satellite image classification methods and techniques: A review. International Journal of Computer Applications, 119(8), 20-24.
  2. Akan, K. (2019). Sarı pas (Puccinia striiformis f. sp. tritici) hastalığına dayanıklı makarnalık buğday hatlarının geliştirilmesi. Türk Tarım ve Doğa Bilimleri Dergisi, 6(4), 661-670.
  3. Aktaş, H., Karaman, M., Tekdal, S., Kılıc, H., & Kendal, E. (2012, August). Evaluating of yield losses caused by yellow rust pressure in some bread wheat genotypes. In 13th International Cereal Rusts and Powdery Mildews Conference, 2012. Proceedings. (pp. 16). Bravo, C., Moshou, D., West, J., McCartney, A., & Ramon, H. (2003). Early disease detection in wheat fields using spectral reflectance. Biosystems Engineering, 84(2), 137-145.
  4. Broge, N. H., & Leblanc, E. (2001). Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density. Remote Sensing of Environment, 76(2), 156-172.
  5. Chen, J. M., & Cihlar, J. (1996). Retrieving leaf area index of boreal conifer forests using Landsat TM images. Remote Sensing of Environment, 55(2), 153-162.
  6. Chen, X. M. (2005). Epidemiology and control of stripe rust [Puccinia striiformis f. sp. tritici] on wheat. Canadian Journal of Plant Pathology, 27(3), 314-337.
  7. Delwiche, S. R., & Kim, M. S. (2000, December). Hyperspectral imaging for detection of scab in wheat. In Biological Quality and Precision Agriculture II, 2000. Proceedings. (pp. 13-20).
  8. SPIE. Devadas, R., Lamb, D. W., Simpfendorfer, S., & Backhouse, D. (2009). Evaluating ten spectral vegetation indices for identifying rust infection in individual wheat leaves. Precision Agriculture, 10, 459-470.
  9. Dusunceli, F., Cetin, L., Albustan, S., & Beniwal, S. P. S. (1996, September). Occurrence and impact of wheat stripe rust (Puccinia striiformis) in Turkey in 1994/95 crop season. In 9th European and Mediterranean Cereal Rusts and Powdery Mildews Conference, 1996. Proceedings. (pp. 309). Duveiller, G., Weiss, M., Baret, F., & Defourny, P. (2011). Retrieving wheat Green Area Index during the growing season from optical time series measurements based on neural network radiative transfer inversion. Remote Sensing of Environment, 115(3), 887-896.
  10. FAO. (2020) FAOSTAT Statistical Database. Retrieved from https://www.fao.org/faostat/en/#home.
  11. Feng, W., Shen, W., He, L., Duan, J., Guo, B., Li, Y., Wang, C., & Guo, T. (2016). Improved remote sensing d