Silvia Mironeasa

Wheat flour dough Alveograph characteristics predicted by Mixolab regression models

BACKGROUND In Romania, the Alveograph is the most used device to evaluate the rheological properties of wheat flour dough, but lately the Mixolab device has begun to play an important role in the breadmaking industry. These two instruments are based on different principles but there are some correlations that can be found between the parameters determined by the Mixolab and the rheological properties of wheat dough measured with the Alveograph. RESULTS Statistical analysis on 80 wheat flour samples using the backward stepwise multiple regression method showed that Mixolab values using the ‘Chopin S’ protocol (40 samples) and ‘Chopin + ’ protocol (40 samples) can be used to elaborate predictive models for estimating the value of the rheological properties of wheat dough: baking strength (W), dough tenacity (P) and extensibility (L). The correlation analysis confirmed significant findings (P < 0.05 and P < 0.01) between the parameters of wheat dough studied by the Mixolab and its rheological properties measured with the Alveograph. CONCLUSION A number of six predictive linear equations were obtained. Linear regression models gave multiple regression coefficients with R²(adjusted) > 0.70 for P, R²(adjusted) > 0.70 for W and R²(adjusted) > 0.38 for L, at a 95% confidence interval.

Variability and relationship among Mixolab and Falling Number evaluation based on influence of fungal α‐amylase addition.

BACKGROUND In bread-making technology, α-amylase activity is routinely measured with a Falling Number device to predict wheat flour quality. The aim of this study was to determine the possibility of using Mixolab parameters to assess the Falling Number (FN) index. The effects of different doses of fungal α-amylase addition on the Mixolab characteristics and FN index values were investigated. RESULTS Principal component analysis was performed in order to illustrate the relationships between the Mixolab parameters and the FN index. To highlight the linear combination between the FN index values and the Mixolab parameters used to evaluate starch pasting properties (C3, C4, C5 and point differences C34 and C54), a multivariate prediction model was developed. Greatest precision (R = 0.728) was obtained for the linear regression FN = f(C4, C54) model. This model was tested on a different sample set than the one on which it was built. A high correlation was obtained between predictive model and measured FN index values (r = 0.896, P = 0.01). CONCLUSION The model provides a framework to predict the evolution of the FN index, which is predicted by the torque for cooking stability (C4) and the difference between points C5 and C4 (C54). The obtained results suggested that the Mixolab device could be a reliable instrument for evaluation of the FN index values.

Optimization of Wheat-Grape Seed Composite Flour to Improve Alpha-Amylase Activity and Dough Rheological Behavior

In this work, the response surface methodology was used to determine the optimum level of input variables, gluten deformation index (mm) and the level of grape seed flour (%) addition in wheat flour that improve falling number index and Mixolab dough rheological parameters. The full factorial model was the best compatible model which fitted to each response. A replacement dose of 4.08% in wheat flour with gluten deformation index value of 8.27 mm was found optimal. The influence of optimum values of variables on dough microstructure has been investigated using epifluorescence light microscopy.

A New Simple Method for the Evaluation of Mineral Elements in Different Oilseeds

ABSTRACT A method for the analysis of seven mineral contents—that is, potassium (K), calcium (Ca), phosphorus (P), iron (Fe), manganese (Mn), zinc (Zn), and copper (Cu)—was investigated in some oilseeds like flax, sesame, pumpkin, quinoa, and yellow mustard. X-ray Spectral Analysis method with Spectrometer EDX-900HS was used for the analytical concentrations of the macro and micro elements of the oilseeds. A relatively high level of Zn content was found in sesame and pumpkin seeds, while the highest level of Fe content was found in mustard seeds. Regarding the macro elements (K, Ca, and P) content, the highest levels of concentration were found in flax and mustard seeds. The highest values of Cu were obtained in sesame seeds while those of Mn were in pumpkin and brown flax seeds. The results showed that the method is a reliable and simple analytical procedure to characterize mineral elements in oilseeds with a very high analytical performance.