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1.
J Environ Biol ; 2010 Jul; 31(4): 489-495
Article in English | IMSEAR | ID: sea-146449

ABSTRACT

This study was carried out in order to determine some quality traits such as thousand grain weight (TGW), hectoliter weight (HW), grain protein content (GPC), Zeleny sedimentation volume (ZSV) and stability of quality traits of 25 bread wheat genotypes. The experiment was conducted at seven environmental conditions during 2 growing periods (2003-2004 and 2004-2005) using randomized complete block design with four replicates. The ANOVA showed that out of the total sum of squares, 48.4, 28.0 and 23.6% for TGW, 71.4, 14.9 and 13.7% for HW, 54.4, 23.0 and 22.6% for GPC, 44.7, 41.7 and 13.6% for ZSV was attributable to E, G and G x E interaction effects, respectively. Thousand grain weight, hectoliter weight, grain protein content and Zeleny sedimentasyon volume of genotypes changed from 34.5 to 41.4 g, from 76.5 to 80.4 Kg, from 11.49 to 13.37% and from 22.1 to 46.0 ml, respectively. Seven stability parameters, covering a wide range of statistical approaches, were used so as to predict the genotypes. The study of genotypic stability showed that Bezostaya and advanced lines numbered 11 and 24 had high stability for quality traits and proved to be the best within the pool of the studied genotypes. Also, 8 and 17 numbered genotypes demonstrated high stability for TGW, HW, GPC and HW, GPC and ZSV, respectively.

2.
J Environ Biol ; 2009 Sept; 30(5suppl): 785-790
Article in English | IMSEAR | ID: sea-146298

ABSTRACT

In this research, leaf area prediction model was developed for some leaf-used maize (Zea mays L.) cultivars namely Coluna, Luce, Maveric, Ranchero, TTM-813, Zamora and RX-788 grown in Black Sea region of Turkey. Lamina width, length and leaf area were measured without destroying the leaf to develop the models. The actual leaf areas of the plants were measured by PLACOM Digital Planimeter, and multiple regression analysis with Excel 2003 computer package program was performed for the plants separately. The produced leaf area prediction models in the present study were formulized as LA= a - (b x W2) + [c x (W x L)] where LA is leaf area, W is leaf width, L is leaf length and a, b, c are coefficiencies. R2 values for maize cultivars tested varied with species from 0.95 in Luce to 0.98 in Maveric. All R² values and standard errors were found to be significant at the p<0.001 level.

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