Journals / Dicle Üniversitesi Fen Bilimleri Enstitüsü Dergisi / 2018 / Cilt: 7 - Sayı: 2

Evaluation of Relationships Between Yield and Yield Components with Physiological Parameters in Barley Hordeumvulgare L. Genotypes

Arpa Hordeum vulgare L. Genotiplerinde Verim ve Verim Unsurları ile Fizyolojik Parametreler Arasındaki İlişkilerin Değerlendirilmesi

Pages
61–66
Publication Date
2018-07-01
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

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

Grain yield showed significant r=0.989** relationships with canopy temperature

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This research was carried out to assess the relationships between yield and yield components with physiological traits which measured at the heading stage of some barley cultivars.
📊
Key Findings & Data:The field experiment was arranged as the complete block design with four replications during the 2015-2016 growing seasons under Sirnak ecological conditions.
💡
Conclusion & Impact:Grain yield showed significant r=0.989** relationships with canopy temperature
🔬Design:Research Article
📍Scope:2015-2016 Verileri
⚙️Variables:Barley · canopy temperature · Leaf area index

Abstract

This research was carried out to assess the relationships between yield and yield components with physiological traits which measured at the heading stage of some barley cultivars. The field experiment was arranged as the complete block design with four replications during the 2015-2016 growing seasons under Sirnak ecological conditions. Six-rowed and two-rowed Baris, Pandora barley cultivars were used as a material. Leaf area index LAI , SPAD, Normalized Differences Vegetative Index NDVI , Canopy Temperature CT , Protein Content, text weight, thousand kernel weight, starch content and grain yield were evaluated. According to the findings of research, differences between genotypes were found significant for protein content, starch content, yield, thousand kernel weight and test weight. The investigated traits ranged between 30.85-35.43 in SPAD, 1.70-2.30 in LAI, 0.505-0.533 in NDVI, 15.45°C-17.85 °C in CT, 1958-3093 kg ha-1 in grain yield, 32.55-46.27 g in thousand kernel weight, 66.35-73.40 kg hL-1 test weight, 8.1-9.1% in protein content, 63.13-66.49% in starch. Grain yield showed significant r=0.989** relationships with canopy temperature

Özet

Bu araştırma, bazı arpa çeşitlerinde başaklanma döneminde ölçülen fizyolojik özellikleri ile verim ve verim unsurları arasındaki ilişkileri değerlendirmek amacıyla yapılmıştır. Arazi çalışması, Şırnak ekolojik koşullarında 2015-2016 yetiştirme döneminde tesadüf blokları deneme desenine göre dört tekrarlamalı olarak yürütülmüştür. Materyal olarak iki sıralı Barış, Pandora ve altı sıralı arpa çeşitleri kullanılmıştır. Çalışmada, yaprak alanı indeksi YAI , SPAD, normalize edilmiş vejetasyon indeksi NDVI , bitki örtüsü sıcaklığı BÖS , protein içeriği, hektolitre ağırlığı, bin dane ağırlığı, nişasta içeriği ve tane verimi özellikleri değerlendirilmiştir. Araştırma bulgularına göre genotipler arasındaki farklar protein içeriği, nişasta içeriği, verim, bin tane ağırlığı ve hektolitre ağırlığı açısından önemli bulunmuştur. Arpa çeşitlerinde incelenen özelliklere göre SPAD değeri 30.85-35.43, YAI değeri 1.70-2.30, NDVI değeri 0.505-0.533, BÖS değeri 15.45 °C -17.85 °C, tane verimini 1958-3093 kg ha-1, bin dane ağırlığı 32.55-46.27 g, hektolitre ağırlığı 66.35-73.40 kg hL1, protein içeriği% 8.1-9.1, nişasta içeriği % 63.13-66.49 arasında bulunmuştur. Tane verimi ile bitki örtüsü sıcaklığı arasında önemli r = 0.989 ** ilişki bulunmuştur

🔖

Cite This Article

KIZILGEÇİ, F., YILDIRIM, M., AKINCI, C., ALBAYRAK, Ö., SESİZ, U., TAZEBAY, N. (2018). Evaluation of Relationships Between Yield and Yield Components with Physiological Parameters in Barley Hordeumvulgare L. Genotypes. Dicle Üniversitesi Fen Bilimleri Enstitüsü Dergisi, Cilt: 7 - Sayı: 2, 61–66. https://ajindex.com/articles/134374

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (13)

  1. R. A. Nilan and S.E. Ullrich, Barley: Chemistry and Technology. In: A.W. MacGregor & R.S. Bhatty (Eds.), Barley: Taxonomy, origin, distribution, production, genetics and breeding. pp. 1-30. St. Paul, Minnesota, USA: AACC Inc. (1993)
  2. FAO. http://www.fao.org/faostat/en/#data/QC (2016) (20.07.2018
  3. A. R. Huete and H.Q. Liu, An error and sensitivity analysis of the atmospheric-and soil-correcting variants of the NDVI for the MODIS-EOS. IEEE Transactions on Geoscience and Remote Sensing, 32(4): 897-905 (1994
  4. C. Leprieur, Y. H. Kerr, S. Mastorchio and J. C.Meunier, Monitoring vegetation cover across semi-arid regions: comparison of remote observations from various scales. International Journal of Remote Sensing, 21(2): 281-300 (2000)
  5. Q. Ling, W. Huang and P. Jarvis, Use of a SPAD502 meter to measure leaf chlorophyll concentration in Arabidopsis thaliana. Photosynthesis research, 107(2): 209-214 (2011)
  6. F. Kizilgeci, C. Akinci, O. Albayrak and M. Yıldırım, Investigation of Yield and Quality Parameters of Barley Genotypes in Diyarbakır and Mardin Conditions Iğdır Univ. J. Inst. Sci. & Tech. 6(3): 161-169 (2016)
  7. R. Raj Kumar, S. Marimuthu, D. Jayakumar and P. R. Jeyaramraja, In situestimation of leaf chlorophyll and its relationship with photosynthesis in tea. Indian journal of plant physiology, 7(4):367-371 (2002)
  8. A. Bannari, K. S. Khurshid, K. Staenz and J. W. Schwarz, A comparison of hyperspectral chlorophyll indices for wheat crop chlorophyll content estimation using laboratory reflectance measurements. IEEE Transactions on Geoscience and Remote Sensing, 45(10): 3063-3074 (2007)
  9. M. R. Schlemmer, D. D. Francis, J. F. Shanahan, and J. S. Schepers, Remotely measuring chlorophyll content in corn leaves with differing nitrogen levels and relative water content. Agronomy journal, 97(1), 106-112 (2005)
  10. F. Kizilgeci, M. Yıldırım, O. Albayrak and C. Akinci, Relationships of Grain Yield and Some Quality Parameters with Physiological Parameters in Some Triticale Advanced Lines Iğdır Univ. J. Inst. Sci. & Tech. 7(1): 337-345 (2017)
  11. H. V. Singh, S. N. Kumar, N. Ramawat and R. C. Harit, Response of wheat varieties to heat stress under elevated temperature environments. Journal of Agrometeorology, 19(1), 17. (2017)
  12. N. Shakya and Y. Yamaguchi, Drought monitoring using vegetation and LST indices in Nepal and northeastern India. In: Proc. 28th Asian Conference on Remote Sensing. (2007)
  13. M. Reynolds and R. Trethowan