The research was carried out with 9 triticale, 3 bread wheat, 3 durum wheat and 3 barley varieties and advanced lines in Tekirdag, Edime and Silivri locations during three years. In the study, the data obtained from c...The research was carried out with 9 triticale, 3 bread wheat, 3 durum wheat and 3 barley varieties and advanced lines in Tekirdag, Edime and Silivri locations during three years. In the study, the data obtained from combined variance analysis were performed and the significance of the differences between the averages was determined by LSD multiple comparison test. GGE biplot analysis and graphics were made by using the statistical package program. The genotypes G2 and G3 for thousand kernel weight, genotype G1 for the heading time and test weight, genotypes G14 and G15 for the maturation time, number of spikelets per spike and grain weight per spike and G13 for the plant height, spike length and grain yield per hectare decare revealed the highest values. The genotypes G6, GS, G4, G14, G9, G8 and G7 gave lower values than the average in terms of grain yield, whereas the other genotypes gave higher values than the general average. According to biplot graphical results, while locations 1 and 8 were closely related, locations 9, 2 and 7 were positively related to these environments. Although the location 7 is slightly different from the other 4 locations, these 5 locations can be seen as a mega environment. Genotypes G12, G2, G3 and G10 for this mega-environment showed the best performances. According to the results of grain yields obtained from 9 different locations, the location 5 was the most discriminating area while the location 1 was the least discriminating. Location 2 was the best representative location, while locations 4 and 7 were with the lowest representation capability. The locations that are both descriptive and representative are good test locations for the selection of adapted genotypes. Test environments, such as location 8, with low ability to represent are useful for selecting genotypes that perform well in specific regions if the target environments can be subdivided into sub-environments.展开更多
Thirty bread wheat genotypes were used as material during the 2014-2015 cropping season. The experimental layout was a randomized complete block design with 3 replications. The sowing rate was 500 seeds square meter. ...Thirty bread wheat genotypes were used as material during the 2014-2015 cropping season. The experimental layout was a randomized complete block design with 3 replications. The sowing rate was 500 seeds square meter. Sowing was done in plots of 6 rows （1.2 m × 5 m, spaced 20 cm apart） in Namlk Kemal University, Faculty of Agriculture, Field Crops Department experimental area. Two sowing times were performed. First sowing was made in November suggested usual （standard） and second one was made in January as delayed sown in order to push growing stages of plants into periods in which heat stress is expected will be effected. Sowing times were allotted to main-plots while genotypes were allotted to sub-plots. When the bread wheat varieties and lines used in the experiment are evaluated in terms of tolerance to high temperature, it was shown that Dropia and Nota varieties and CIMMYT-HTN 2014/15-2, CIMMYT-HTN 2014/15 -6, CIMMYT-HTN 2014/15 - 10 lines were better tolerance to high temperature. However, it was noticed that these genotypes were not included in the first groups in terms of grain yield. It is possible to utilize these genotypes as a genitor in cross-breeding programs for breeding studies for tolerance to high temperatures.展开更多
AMMI analysis was performed to assess yield stability of twenty-five bread wheat （Triticum aestivum L.） genotypes grown in a 5 ×5 Lattice Square Design at seven sites under irrigation during 2009 season. AMMI A...AMMI analysis was performed to assess yield stability of twenty-five bread wheat （Triticum aestivum L.） genotypes grown in a 5 ×5 Lattice Square Design at seven sites under irrigation during 2009 season. AMMI ANOVA for grain yield indicated that genotypes, environments and G×E interaction were significantly different （P 〈 0.001）. Environments, genotypes and GxE accounted for 78.9, 4.6 and 16.4% of the treatment sum of squares, respectively. The proportion of environmental and G×E interaction variation for grain yield was larger than genotypes main effects. Genotype dendogram showed nine clusters with a yield range of 6,373.546 kg·ha-1 to 7,687.243 kg.hal. W1494/6/1, SC Sky and W2045/6/13 had high yields and exhibited negligible interactions with the environment. These were widely adapted and stable across high yielding sites. RARS （Normal）, ART （Normal） and ART （Deficit） were best yielding sites among eight environmental groups. ART （Deficit） had the best mean （9,764.479 kg·ha-1） followed by RARS （Normal） at 9,522.119 kg·ha-1 Chiredzi （Group 6） had the lowest mean yield （4,393.400 kg.hal）. Results show that high yields （〉 9,000 kg·ha-1） are achievable in high altitude areas of Zimbabwe （≥1,200 masl）. Dendograms were used to characterize both genotypes and environments and the AMMI model was used to select genotypes with specific or broad adaptation.展开更多
文摘The research was carried out with 9 triticale, 3 bread wheat, 3 durum wheat and 3 barley varieties and advanced lines in Tekirdag, Edime and Silivri locations during three years. In the study, the data obtained from combined variance analysis were performed and the significance of the differences between the averages was determined by LSD multiple comparison test. GGE biplot analysis and graphics were made by using the statistical package program. The genotypes G2 and G3 for thousand kernel weight, genotype G1 for the heading time and test weight, genotypes G14 and G15 for the maturation time, number of spikelets per spike and grain weight per spike and G13 for the plant height, spike length and grain yield per hectare decare revealed the highest values. The genotypes G6, GS, G4, G14, G9, G8 and G7 gave lower values than the average in terms of grain yield, whereas the other genotypes gave higher values than the general average. According to biplot graphical results, while locations 1 and 8 were closely related, locations 9, 2 and 7 were positively related to these environments. Although the location 7 is slightly different from the other 4 locations, these 5 locations can be seen as a mega environment. Genotypes G12, G2, G3 and G10 for this mega-environment showed the best performances. According to the results of grain yields obtained from 9 different locations, the location 5 was the most discriminating area while the location 1 was the least discriminating. Location 2 was the best representative location, while locations 4 and 7 were with the lowest representation capability. The locations that are both descriptive and representative are good test locations for the selection of adapted genotypes. Test environments, such as location 8, with low ability to represent are useful for selecting genotypes that perform well in specific regions if the target environments can be subdivided into sub-environments.
文摘Thirty bread wheat genotypes were used as material during the 2014-2015 cropping season. The experimental layout was a randomized complete block design with 3 replications. The sowing rate was 500 seeds square meter. Sowing was done in plots of 6 rows （1.2 m × 5 m, spaced 20 cm apart） in Namlk Kemal University, Faculty of Agriculture, Field Crops Department experimental area. Two sowing times were performed. First sowing was made in November suggested usual （standard） and second one was made in January as delayed sown in order to push growing stages of plants into periods in which heat stress is expected will be effected. Sowing times were allotted to main-plots while genotypes were allotted to sub-plots. When the bread wheat varieties and lines used in the experiment are evaluated in terms of tolerance to high temperature, it was shown that Dropia and Nota varieties and CIMMYT-HTN 2014/15-2, CIMMYT-HTN 2014/15 -6, CIMMYT-HTN 2014/15 - 10 lines were better tolerance to high temperature. However, it was noticed that these genotypes were not included in the first groups in terms of grain yield. It is possible to utilize these genotypes as a genitor in cross-breeding programs for breeding studies for tolerance to high temperatures.
文摘AMMI analysis was performed to assess yield stability of twenty-five bread wheat （Triticum aestivum L.） genotypes grown in a 5 ×5 Lattice Square Design at seven sites under irrigation during 2009 season. AMMI ANOVA for grain yield indicated that genotypes, environments and G×E interaction were significantly different （P 〈 0.001）. Environments, genotypes and GxE accounted for 78.9, 4.6 and 16.4% of the treatment sum of squares, respectively. The proportion of environmental and G×E interaction variation for grain yield was larger than genotypes main effects. Genotype dendogram showed nine clusters with a yield range of 6,373.546 kg·ha-1 to 7,687.243 kg.hal. W1494/6/1, SC Sky and W2045/6/13 had high yields and exhibited negligible interactions with the environment. These were widely adapted and stable across high yielding sites. RARS （Normal）, ART （Normal） and ART （Deficit） were best yielding sites among eight environmental groups. ART （Deficit） had the best mean （9,764.479 kg·ha-1） followed by RARS （Normal） at 9,522.119 kg·ha-1 Chiredzi （Group 6） had the lowest mean yield （4,393.400 kg.hal）. Results show that high yields （〉 9,000 kg·ha-1） are achievable in high altitude areas of Zimbabwe （≥1,200 masl）. Dendograms were used to characterize both genotypes and environments and the AMMI model was used to select genotypes with specific or broad adaptation.
