Biplot Analiz Yöntemi ile Bazı Makarnalık Buğday Hatlarının Verim ve Kalite Özelliklerinin Değerlendirilmesi

Tekdal, Sertaç; Kendal, Enver; Aktaş, Hüsnü; Karaman, Mehmet; Doğan, Hasan Gökhan; Bayram, Sinan; Düzgün, Mehmet; Efe, Ahmet

doi:10.21566/tarbitderg.359162

Cited by 7 publications

(7 citation statements)

References 6 publications

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“…The GGE biplot has been used in only a few studies to analyze the MET data of durum wheat in Turkey (Tekdal et al, 2017;Kendal, 2019). In our research, E contributed 83% of the total variation in the data, whereas G and GEI contributed less.…”

Section: Discussionmentioning

confidence: 99%

“…However, little attention is given to the interaction of genotypes with unpredictable target environments. In this context, METs can help understand genotypes' performance in various environments by measuring the stability of genotypes (Gs) across environments (Es) (Tekdal et al, 2017;Scapim et al, 2000). But, MET data are rarely used to their full potential, even though data on most plant traits have been collected.…”

Section: Introductionmentioning

confidence: 99%

“…So far, GGE-biplot analysis has been applied to many crops such as soybean (Yan and Rajcan, 2002), rice (Samonte et al, 2005), bread wheat (Kaya et al, 2006;Roozeboom et al, 2008;Akcura et al, 2011;Nehe et al, 2019), barley (Dehghani et al, 2006;Mohammadi et al, 2009), peanuts (Putto et al, 2008), lentils (Sabaghnia et al, ), corn (İlker et al, 2009, oats (Yan et al, 2010) and sorghum (Rao et al, 2011). However, despite reports on GGE-biplot analysis in selecting superior genotypes or test environments in such crops, its application to durum wheat METs in Turkey is insufficient (Tekdal et al, 2017;Kendal, 2019;Mohammadi et al, 2021). Genotypes (i.e., breeding lines) are routinely tested to select ones adaptable to Turkey's Winter Durum Wheat Zone.…”

Section: Introductionmentioning

confidence: 99%

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GGE-BIPLOT Analysis of Durum Wheat Yield Trials

Kaya

2022

Black Sea Journal of Agriculture

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Durum wheat (Triticum durum L.) is a vital crop in the rain-fed areas of Turkey. In this study, the grain yield of twenty durum wheat genotypes (sixteen advanced lines with four checks) tested across 8 rain-fed environments during the 2008-2009 cropping season was evaluated using GGE (Genotype (G) Main Effect + Genotype by Environment Interaction (GEI)) Biplot Approach. Environment (E) captured most (83 %) of the grain yield (GY) variation, while the portions attributed to G and GEI were only 6 and 11 %, respectively. In addition, most of the testing Es were highly correlated. According to GGE-Biplot analysis, 'Which won where' pattern partitioned the testing Es into three mega-environments (ME): the first ME with six Es with G13 (the highest yielder) as the winning genotype; the second ME encompassed one environment (E1, Konya) with G4 (the lowest yielder) as the winning genotype, and the last ME represented by one location (E6, Altintas) with G10 (the higher yielder) as the winning genotype. GGE-Biplot analysis showed that although the Durum Wheat Yield Trials were conducted in many environments, outcomes alike can be obtained from one or two representatives of each ME. On the other hand, no correlation of these MEs with their geographic location was observed. In conclusion, the presence of cross-over GEI underscores that efforts should be given to identify specifically adapted genotypes rather than broadly adapted ones tested on multi-environment trials (METs).

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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GGE-BIPLOT Analysis of Durum Wheat Yield Trials

Kaya

2022

Black Sea Journal of Agriculture

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“…Güngör and Akgöl, (2015) and Bilgin et al, (2008) revealed that a high significant correlation of 1000 grain weight with grain yield implies that 1000 grain weight plays a very important role in the possible increase of the grain yield of new wheat genotypes in the Thrace Region. Öztürk and Korkut, (2017) and Tekdal et al, (2014) reported that TKW and TW had a positive effect on grain yield. The higher grain yields were found in examined varieties with the higher 1000-grain weight.…”

Section: Resultsmentioning

confidence: 98%

İleri Kademe Ekmeklik Buğday (Triticum aestivum L.) Mutant Hatlarının Verim ve Kalite Parametrelerine Göre Seleksiyonu

Öztürk

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et al. 2020

Türk Tarım Ve Doğa Bilimleri Dergisi

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In the presented research, conventional gamma ray mutagenesis was used to develop new mutant line(s), which have such characters moderate and/or high yielding, semi dwarf and early maturing. Thus, Selimiye cultivar, TCI2066 and three sisters' line of TCI2021 were irradiated with 200 Gy gamma rays and segregated up to sixth generations. 15 advanced mutant lines from M 6 generation and their parent and five commercial wheat cultivars, which have superior characters than others were evaluated according to some agronomic parameters, such as grain yield (GY), thousand kernel weight (TKW), test weight (TW), protein content (PRT), hardness (HARD), days of heading and plant height, under field condition during 2012-2014 growing years in Edirne, Turkey. As a result of study, the highest grain yield was determined from the mutant lines derived from Selimiye wheat cultivar than commercial cultivars. The mutant lines of TCI2021-21M4-2 and TCI2021-23M5-2 were given the highest value in terms of protein content, and the highest hardness values were determined from the mutant lines of TCI2066-9M2-3, TCI2066-9M2-1 and TCI2021-21M4-2, respectively. The mutant line of TCI2021-12M3-8 was measured the shortest one among them. Additionally, a strong positive correlation was determined between GY and TKW, and TW in both growing season. In conclusion, gamma ray mutagenesis had efficiently used in local bread wheat improving programmes to develop mutant lines with superior characters, and TKW and TW could be used as selection criteria for maintaining grain yield under divers rainfall conditions of Trakya Region.

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“…Ayrıca Kanat [14]' yaptığı araştırmada 444,7-597,0 kg/da, diğer bir çalışmada 522,35-654,33 kg/da, aralığında değiştiğini bildirmektedirler [29]. Tane verimi daha çok genotiplerin genetik özelliğinden ve çevrenin etkisinden etkilendiği araştırıcılar tarafından bildirilmiştir [30].…”

Section: Verilerin Değerlendirilmesiunclassified

Sıvı Gübrelerin Makarnalık Buğdayda Verim, Verim Unsurları ve Kalite Özellikleri Üzerine Etkisinin Belirlenmesi

AYDIN,

KENDAL

2023

Dicle Üniversitesi Fen Bilimleri Enstitüsü Dergisi

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Yüksek verimli ve kaliteli ürünler elde etmek için uygun çeşit tercih edilmesinin yanında yetiştirme döneminde en uygun bakım şartlarının sağlanması ile mümkün olmaktadır. Bunlardan biri de bitkinin ihtiyaç duyduğu makro ve mikro besinlerin eksiksiz olarak uygulanmasıdır. Bu çalışma içerisinde makro ve mikro besin elementlerini birlikte içeren sıvı gübrenin makarnalık buğdayın verim, verim öğeleri ve kalite kriterlerine etkisini görmek üzere yürütülmüştür. Çalışma 2020-2021 yetiştirme sezonunda, Mardin ili Kızıltepe ilçesi Çağıl köyünde, çiftçi koşullarında, 3 adet makarnalık buğday çeşidinde sıvı gübre uygulama dozunun etkisi araştırılmıştır. Deneme Tesadüf Blokları Deneme Desenine göre 4 tekerrürlü olacak şekilde yürütülmüştür. Sıvı gübre uygulaması, çeşitler ve interaksiyon bakımından %0,1 ve % 0,5 seviyesinde önemli farklılıklar tespit edilmiştir. İncelenen özelliklerden metrekarede başak sayısı (368-439 adet/m2), bitki boyu (97-107 cm), başak uzunluğu (7,4-7,7 cm), başak verimi (25,2-26,0 g/başak), hektolitre ağırlığı (81,6-83,8 kg/hl), protein oranı (%11,8-14,0), yaş glüten oranı (%30,6-35,6) ve tane verimi (536,7-628,9 kg/da) bakımından sıvı gübre uygulamasının önemli, diğer parametreler bakımından önemsiz olduğu belirlenmiştir. Genel olarak bakıldığında araştırmadan elde edilen sonuçlara göre sıvı gübre uygulamasının makarnalık buğdaya etkisi önemli bulunmuştur. Ayrıca, biplot analizi ile genotipler ve uygulamalar arasındaki ilişki ile interaksiyon konusunda faydalı ve görsel sonuçlar elde edilmiştir.

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Biplot Analiz Yöntemi ile Bazı Makarnalık Buğday Hatlarının Verim ve Kalite Özelliklerinin Değerlendirilmesi

Cited by 7 publications

References 6 publications

GGE-BIPLOT Analysis of Durum Wheat Yield Trials

GGE-BIPLOT Analysis of Durum Wheat Yield Trials

İleri Kademe Ekmeklik Buğday (Triticum aestivum L.) Mutant Hatlarının Verim ve Kalite Parametrelerine Göre Seleksiyonu

Sıvı Gübrelerin Makarnalık Buğdayda Verim, Verim Unsurları ve Kalite Özellikleri Üzerine Etkisinin Belirlenmesi

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