This work is focused on the characterization and rapid analytical determination of cereal flour quality with regard to nutritional and breadmaking quality. Starch, protein and non-starch polysaccharides are the main c...This work is focused on the characterization and rapid analytical determination of cereal flour quality with regard to nutritional and breadmaking quality. Starch, protein and non-starch polysaccharides are the main components of cereals. The content and quality of proteins and content of damaged starch is important because of the technological quality of flours. The high content of high molecular weight proteins is substantial for bread technology especially, while soluble protein fractions and non-starch polysaccharides are important for nutrition. The set of wheat, barley and rye flours and their blends were analyzed and their properties and their qualitative parameters were determined. Principal component analysis （PCA） was used on Fourier transform-infrared （FT-IR） spectra in the 1,200-800 cm1 wavenumber region and significant correlations of various nutritional and breadmaking parameters were observed. Results showed that the FT-IR spectroscopy and PCA can serve for rapid screening and classification of cereal flour quality.展开更多
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
文摘This work is focused on the characterization and rapid analytical determination of cereal flour quality with regard to nutritional and breadmaking quality. Starch, protein and non-starch polysaccharides are the main components of cereals. The content and quality of proteins and content of damaged starch is important because of the technological quality of flours. The high content of high molecular weight proteins is substantial for bread technology especially, while soluble protein fractions and non-starch polysaccharides are important for nutrition. The set of wheat, barley and rye flours and their blends were analyzed and their properties and their qualitative parameters were determined. Principal component analysis （PCA） was used on Fourier transform-infrared （FT-IR） spectra in the 1,200-800 cm1 wavenumber region and significant correlations of various nutritional and breadmaking parameters were observed. Results showed that the FT-IR spectroscopy and PCA can serve for rapid screening and classification of cereal flour quality.
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.
