Hrušková M., Švec I. (2009): Wheat hardness in relation to other quality factors. Czech J. Food Sci., 27: 240-248.The analysis of the wheat hardness relation to other quality features was done with a set of 281 variety and commercial wheat samples, planted during the years of [2003][2004][2005][2006] in Central Bohemia and south Moravia areas. Technological quality was evaluated for grain, milling process, and flour analytics with the standard laboratory methods. The grain hardness was measured using NIR spectrophotometer Inframatic 8600. Tukey's test (ANOVA) of the grain hardness was performed for comparison between the means of wheat variety, wheat origin, crop year, growing locality, and farming intensity. As expected, the grain hardness of wheat varieties belonging to different quality classes was independent of either their classification or winter/spring type. Between all four locality means, the grain hardness among 281 samples differed insignificantly, while in the crops of 2004 and 2006 a provable increase of the kernel compactness was observed. The correlation analysis confirmed a role of the grain hardness in the milling quality assessment because of the proved correlation with 11 grain and milling quality features from the 12 tested. The strongest relation was calculated with the grain ash content, semolina yield, and flour protein content (-0.55, 0.52, 0.42, respectively).

Two samples of commercial wheat flour from the last year's harvest were stored for three months (in the period from November to April) under different conditions. The ambient temperature and humidity varied during the storage in the dependence on the year season. Certain analytical characteristics (moisture, wet gluten and its extensibility, acidity and falling number) and alveograph behaviour of flour were determined at regular intervals. Flour moisture, acidity, and falling number changed with the time of storage but no explicit influence of the storehouse conditions and the initial flour properties was proved. Viscoelastic properties of weaker flour samples changed during storage more markedly than those of stronger flours in the sense of a significant improvement of their quality.

No abstract

Wheat and flour quality is expressed by a variety of chemical and physical properties of dough, none of which serves as adequate by itself or is independent of others variables (P���� 1988). According to F����� (1978) "a flour of good quality for breadmaking should have high water absorption, a medium to medium -long mixing requirement, satisfactory mixing tolerance, and bread volume potential (considering protein content), and should yield a loaf with good internal grain and colour". T������ et al. (1982) identify the "ideal" bread flour as one that produces good bread over a wide range of processing conditions, that yields doughs with well-balanced handling properties and does not have long mixing requirements.Wheat , s breadmaking potential is derived largely from the quantity and quality of its protein. Protein quantity is influenced by environmental factors, while the quality of the protein is genetically determined. In wheat varieties that are grown under comparable environmental conditions, a high quality wheat will produce good bread over a fairly broad range of protein levels. A poor quality wheat will yield relatively low quality bread even at high protein contents.When flour and water are mixed into dough and this is kneaded thoroughly under water either by hand or by machine, a cohesive, extensible and rubbery mass is obtained that consists principally of protein and water. When this so-called "crude gluten" is treated with 70% alcohol, the gliadin fraction dissolves or disperses and can be separated in fairly pure form. Analytical quality parameters of wheat flour prepared from variety and commercial wheat samples (wheat harvest 1998, 1999, 2000 and 2001) were assessed by means of filter spectrograph Inframatic 8620 ASH (moisture and protein content) and Sedi-tester (Zeleny sedimentation value). The spectra of all samples were measured on spectrograph NIRSystem 6500. Calibration equations with cross and independent validation for all analytical characteristics were computed by NIR Software ISI Present WINISI II using MPLS and PLS method. The quality of prediction was evaluated by SEP and r parameters between the measured and the predicted values from cross and independent validation. In case of Inframatic 8620 ASH, validation was realised by NIRPRG software. A statistically significant dependence between the predicted and the measured values of protein content and Zeleny sedimentation (with probability P < 0.01) was determined in both variety and commercial flour sets in the case of cross and independent validation. Better accuracy of prediction was found with NIRSystem 6500. Both important parameters of wheat were successfully predicted by independent validation with nearly the same accuracy.

AbstractŠvec I., Hrušková M., Vítová M., Sekerová H. (2008): Colour evaluation of different pasta samples. Czech J. Food Sci., 26: 421-427.The colour of the laboratory prepared pasta was evaluated with respect to wheat flour types (M1 bright, M2 semibright, and M3 semolina), egg-ratio (0, 1, 2), and non-traditional cereals (archaic wheat species, tritordeum, spring barley, millet, lupin, buckwheat, and soya) supplements. The flour colour measurement confirmed its dependence on the wheat species milled − M3 obtained from durum wheat had a lower whiteness L* (89.6) and a higher yellowness b* (22.2) than the flour from common wheat (e.g. 93.6 and 8.1 for M1, respectively). As presumed, with the rising egg-ratio pasta yellowness increased − for M1-pasta, the calculated colour differences ∆e in pairs one-egg/eggless and two-egg/eggless were 1.1 and 4.7, respectively, while for M2-and M3-pasta ∆e values were only 0.8 and 1.5, respectively. The colour impacts of non-traditional cereals as 10% supplements differed between archaic wheat species, tritordeum, barley, and alternative cereals (millet, lupin, roasted buckwheat). In comparison to the standard, the greatest positive colour gain was brought by the lupin fortification (130% yellowness increase), while the worst appesred roasted buckwheat (10% decrease of whiteness, 210% increase of redness). At 20% non-traditional cereals supplements compared for M2-and M3-pasta, the highest positive increase of the pasta colour sensory perception was caused by corn and lupin additions in both pasta samples. The increase was slightly higher with M1-pasta (175%) than with M3-pasta (170%). In the mean of both pasta samples, yellowness L* increased from the standard pasta value 13.6 to 24.0 as measured for corn and lupin fortified pasta.