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

Year 2018, Volume: 7 Issue: 2, 61 - 66, 01.07.2018

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

References

  • [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, Physiological interventions in breeding for adaptation to abiotic stress. Frontis 21: 127-144 (2007).
  • [14] B. Bahar, M. Yildirim, C. Barutcular and I. Genc, Effect of canopy temperature depression on grain yield and yield components in bread and durum wheat. NotulaeBotanicaeHortiAgrobotaniciClujNapoca 36(1): 34 (2008).
  • [15] J. L. Araus, G. A. Slafer, C. Royo, and M. D. Serret, Breeding for Yield Potential and Stress Adaptation in Cereals. Critical Reviews in Plant Sciences 27(6): 377- 412 (2008).
  • [16] M. Farooq, A. Wahid, N. Kobayashi, D. Fujita and S. Basra, Plant drought stress: effects, mechanisms and management. In Sustainable Agriculture, 153-188 (2009).
  • [17] M. S. Lopes and M. P. Reynolds, Partitioning of assimilates to deeper roots is associated with cooler canopies and increased yield under drought in wheat. Functional Plant Biology 37(2): 147-156 (2010).
  • [18] C. Saint Pierre, J. Crossa, Y. Manes and M. P. Reynolds, Gene action of canopy temperature in bread wheat under diverse environments. Theoretical and Applied Genetics 120(6): 1107-1117 (2010).
  • [19] C. M. Cossani and M. P. Reynolds, Physiological traits for improving heat tolerance in wheat. Plant physiology 160(4): 1710-1718 (2012).
  • [20] G. J. Rebetzke, A. R.Rattey, G. D. Farquhar, R. A. Richards and A. T. G. Condon, Genomic regions for canopy temperature and their genetic association with stomatal conductance and grain yield in wheat. Functional Plant Biology 40(1): 14-33 (2013).
  • [21] S. Mondal, R. E. Mason, T. Huggins and D. B. Hays, QTL on wheat (Triticumaestivum L.) chromosomes 1B, 3D and 5A are associated with constitutive production of leaf cuticular wax and may contribute to lower leaf temperatures under heat stress. Euphytica 201(1): 123-130 (2015).
  • [22] D. Saxena, S. S. Prasad, R. Chatrath, S. Mishra, M. Watt, R. Prashar, A. Wason, A. Gautam and P. Malviya, Evaluation of root characteristics, canopy temperature depression and stay green trait in relation to grain yield in wheat under early and late sown conditions. Indian Journal of Plant Physiology 19(1): 43-47 (2014).
  • [23] V. Ginkel, M. Reynolds, M. Trethowan, R. & Hernandez, E. Complementing the breeders eye with canopy temperature measurements. In International Symposium on Wheat Yield Potential, 134. (2008).
  • [24] M. P. Reynolds, C. S. Pierre, A. S. Saad, M. Vargas and A. G. Condon, Evaluating potential genetic gains in wheat associated with stress-adaptive trait expression in elite genetic resources under drought and heat stress. Crop Science 47(3): 172-189 (2007).
  • [25] P. Gupta, H. Balyan, V. Gahlaut and P. Kulwal, Phenotyping, genetic dissection, and breeding for drought and heat tolerance in common wheat: status and prospects. Plant Breeding Reviews, Volume 36: 85-168 (2012).
  • [26] R. S. Pinto, M. P. Reynolds, K. L. Mathews, C. L. McIntyre, J. J. Olivares-Villegas and S. C. Chapman, Heat and drought adaptive QTL in a wheat population designed to minimize confounding agronomic effects. Theoretical and Applied Genetics 121(6): 1001-1021 (2010).
  • [27] R. S. Pinto and M. P. Reynolds, Common genetic basis for canopy temperature depression under heat and drought stress associated with optimized root distribution in bread wheat. Theoretical and Applied Genetics 128(4): 575-585 (2015).
  • [28] M. Kumari, V. Singh, R. Tripathi and A. Joshi, Variation for staygreen trait and its association with canopy temperature depression and yield traits under terminal heat stress in wheat. In Wheat Production in Stressed Environments, 357-363 (2007).
  • [29] E. Kendal and H. Dogan, Impact of Row Number in Barley Head on Yield, Some Quality and Morphological Parameters in Barley Turkish Journal of Agricultural and Natural Sciences 1(2): 132–142 (2014)
  • [30] F. Kizilgeci, C. Akinci, O. Albayrak, B. T. Biçer, F. Başdemir and M. Yıldırım, Investigation of Yield and Quality Parameters of Barley Genotypes in Diyarbakır and Şanlıurfa Conditions Journal of Field Crops Central Research Institute, 2016, 25 (Special issue): 146-150 (2016)
  • [31] H. Aktas, Evaluation of Some Barley (Hordeum vulgare L.) Cultivars Commonly Cultivated in Turkey Under Supplemented İrrigation and Rainfall Conditions Journal of Tekirdag Agricultural Faculty14 (03) 86-97 (2017).
  • [32] E. Kendal and Y. Dogan, Evaluation of Some Spring Barley Genotypes In Terms of Yield and Quality YYU J. AGR. SCI. 2012, 22(2): 77-84 (2014).
  • [33] L. K., Fenstermaker-Shaulis, A. Leskys and D. A. Devitt, Utilization of Remotely Sensed Data to Map and Evaluate Turfgrass Stress Associated with Drought. Journal of Turfgrass Management. 2:65-81(1997).

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

Year 2018, Volume: 7 Issue: 2, 61 - 66, 01.07.2018

Abstract

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

References

  • [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, Physiological interventions in breeding for adaptation to abiotic stress. Frontis 21: 127-144 (2007).
  • [14] B. Bahar, M. Yildirim, C. Barutcular and I. Genc, Effect of canopy temperature depression on grain yield and yield components in bread and durum wheat. NotulaeBotanicaeHortiAgrobotaniciClujNapoca 36(1): 34 (2008).
  • [15] J. L. Araus, G. A. Slafer, C. Royo, and M. D. Serret, Breeding for Yield Potential and Stress Adaptation in Cereals. Critical Reviews in Plant Sciences 27(6): 377- 412 (2008).
  • [16] M. Farooq, A. Wahid, N. Kobayashi, D. Fujita and S. Basra, Plant drought stress: effects, mechanisms and management. In Sustainable Agriculture, 153-188 (2009).
  • [17] M. S. Lopes and M. P. Reynolds, Partitioning of assimilates to deeper roots is associated with cooler canopies and increased yield under drought in wheat. Functional Plant Biology 37(2): 147-156 (2010).
  • [18] C. Saint Pierre, J. Crossa, Y. Manes and M. P. Reynolds, Gene action of canopy temperature in bread wheat under diverse environments. Theoretical and Applied Genetics 120(6): 1107-1117 (2010).
  • [19] C. M. Cossani and M. P. Reynolds, Physiological traits for improving heat tolerance in wheat. Plant physiology 160(4): 1710-1718 (2012).
  • [20] G. J. Rebetzke, A. R.Rattey, G. D. Farquhar, R. A. Richards and A. T. G. Condon, Genomic regions for canopy temperature and their genetic association with stomatal conductance and grain yield in wheat. Functional Plant Biology 40(1): 14-33 (2013).
  • [21] S. Mondal, R. E. Mason, T. Huggins and D. B. Hays, QTL on wheat (Triticumaestivum L.) chromosomes 1B, 3D and 5A are associated with constitutive production of leaf cuticular wax and may contribute to lower leaf temperatures under heat stress. Euphytica 201(1): 123-130 (2015).
  • [22] D. Saxena, S. S. Prasad, R. Chatrath, S. Mishra, M. Watt, R. Prashar, A. Wason, A. Gautam and P. Malviya, Evaluation of root characteristics, canopy temperature depression and stay green trait in relation to grain yield in wheat under early and late sown conditions. Indian Journal of Plant Physiology 19(1): 43-47 (2014).
  • [23] V. Ginkel, M. Reynolds, M. Trethowan, R. & Hernandez, E. Complementing the breeders eye with canopy temperature measurements. In International Symposium on Wheat Yield Potential, 134. (2008).
  • [24] M. P. Reynolds, C. S. Pierre, A. S. Saad, M. Vargas and A. G. Condon, Evaluating potential genetic gains in wheat associated with stress-adaptive trait expression in elite genetic resources under drought and heat stress. Crop Science 47(3): 172-189 (2007).
  • [25] P. Gupta, H. Balyan, V. Gahlaut and P. Kulwal, Phenotyping, genetic dissection, and breeding for drought and heat tolerance in common wheat: status and prospects. Plant Breeding Reviews, Volume 36: 85-168 (2012).
  • [26] R. S. Pinto, M. P. Reynolds, K. L. Mathews, C. L. McIntyre, J. J. Olivares-Villegas and S. C. Chapman, Heat and drought adaptive QTL in a wheat population designed to minimize confounding agronomic effects. Theoretical and Applied Genetics 121(6): 1001-1021 (2010).
  • [27] R. S. Pinto and M. P. Reynolds, Common genetic basis for canopy temperature depression under heat and drought stress associated with optimized root distribution in bread wheat. Theoretical and Applied Genetics 128(4): 575-585 (2015).
  • [28] M. Kumari, V. Singh, R. Tripathi and A. Joshi, Variation for staygreen trait and its association with canopy temperature depression and yield traits under terminal heat stress in wheat. In Wheat Production in Stressed Environments, 357-363 (2007).
  • [29] E. Kendal and H. Dogan, Impact of Row Number in Barley Head on Yield, Some Quality and Morphological Parameters in Barley Turkish Journal of Agricultural and Natural Sciences 1(2): 132–142 (2014)
  • [30] F. Kizilgeci, C. Akinci, O. Albayrak, B. T. Biçer, F. Başdemir and M. Yıldırım, Investigation of Yield and Quality Parameters of Barley Genotypes in Diyarbakır and Şanlıurfa Conditions Journal of Field Crops Central Research Institute, 2016, 25 (Special issue): 146-150 (2016)
  • [31] H. Aktas, Evaluation of Some Barley (Hordeum vulgare L.) Cultivars Commonly Cultivated in Turkey Under Supplemented İrrigation and Rainfall Conditions Journal of Tekirdag Agricultural Faculty14 (03) 86-97 (2017).
  • [32] E. Kendal and Y. Dogan, Evaluation of Some Spring Barley Genotypes In Terms of Yield and Quality YYU J. AGR. SCI. 2012, 22(2): 77-84 (2014).
  • [33] L. K., Fenstermaker-Shaulis, A. Leskys and D. A. Devitt, Utilization of Remotely Sensed Data to Map and Evaluate Turfgrass Stress Associated with Drought. Journal of Turfgrass Management. 2:65-81(1997).
There are 33 citations in total.

Details

Primary Language Turkish
Journal Section Research Article
Authors

Ferhat Kızılgeçi This is me

Mehmet Yıldırım This is me

Cuma Akıncı This is me

Önder Albayrak This is me

Uğur Sesiz This is me

Nihan Tazebay This is me

Publication Date July 1, 2018
Published in Issue Year 2018 Volume: 7 Issue: 2

Cite

IEEE F. Kızılgeçi, M. Yıldırım, C. Akıncı, Ö. Albayrak, U. Sesiz, and N. Tazebay, “Arpa Hordeum vulgare L. Genotiplerinde Verim ve Verim Unsurları ile Fizyolojik Parametreler Arasındaki İlişkilerin Değerlendirilmesi”, DUFED, vol. 7, no. 2, pp. 61–66, 2018.


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