The consumer's appreciation of solid food foams such as bread is strongly linked to their texture. Bubble growth and coalescence phenomena during fermentation and baking govern bread texture creation, which in turn determines mechanical properties as well as sensory properties like their feeling in the mouth. Mechanisms governing the cellular structure development and setting need to be better understood, which requires a systematic and accurate mapping of microstructural characteristics. For this purpose, X-ray tomography appears to be a well-suited technology to overcome difficulties encountered with more classical imaging techniques (invasive, 2D, poor contrast, and artefacts in the sample preparation). Very recently, it has been applied to imaging the final structure of cellular food products [1,2]. The originality of the present work is to use in situ X-ray tomography in order to assess the bubble structure development during the fermentation and baking of bread dough.

The experiment was carried out at the BM05 beamline using a specifically-designed "fast" tomography technique. The energy was 18 keV and the spatial resolution 15 µm. Exposure time of a single projection of 20 milliseconds allowed a scan of 400 projections over 180 degrees within 30 seconds. Product changes during this interval could reasonably be discarded in comparison with its overall evolution during total fermentation time. Scans were recorded every 5 or 10 minutes during 2 or 3 hours (depending on the yeast content), to obtain a "movie" of the whole process. Bread dough of different compositions was studied to highlight the role of the ingredients (flour, water, sucrose, oil and yeast). The fermentation step was performed for a longer time than usual to observe the coalescence mechanisms until low densities were reached. A trial of in situ observation of bread baking was also achieved in a small 'tomographic' oven, at a 5°C/mn heating rate.

Typical evolution of the microstructure of bread dough during the fermentation stage is displayed on Figure 143a. For the sake of clarity, only five 2D pictures among the overall twenty-five recorded, are shown. During the first part of the fermentation, growing spherical bubbles can clearly be identified. In the second part, bubble coalescence leads to a more heterogeneous structure with complex shape cells.

 

Fig. 143: Evolution during the bread dough fermentation of: a) the microstructure b) the void fraction of different formulations and c) the bubble diameter for different initial sizes.

 

Evolutions of macroscopic (void fraction) or microscopic (cell size distribution) characteristics were calculated over the whole fermentation time. Figure 143b presents the evolution of the void fraction for four compositions. The one containing 1.5% of yeast (black points) led to a slower evolution than the three others with 3% of yeast (among them the "French baguette" recipe (red points)). The evolution of different initial bubble sizes can be fitted by the equation R(t) = R0ekt where k is directly related to process and material variables (internal gas pressure, dough matrix viscosity) (Figure 143c).

Figure 144 represents images extracted from the baking experiment, at the end of which a bread crumb, Ø 8 mm base and a few mm thick was obtained. It can be shown that foam setting, here dough/crumb transition, occurs for temperature close to 70°C.

 

Fig. 144: Microstructure evolution during the first minutes of baking.

This work is still in progress: the complete quantitative analysis of the data will allow a better understanding of the physical mechanisms governing the growth and coalescence phenomena. It will also provide essential data for the validation of numerical models of bubbles growth during food texturing processes. In particular, dough images captured at different proofing stages leading to the same density can be numerised in order to determine the influence of microstructure by FEM simulation. Complementary sensorial characterisation is also planned for the products. Further prospects encompass a reverse engineering approach: starting from the expected sensory properties, textural properties are targeted in order to select relevant processing conditions and composition which would meet these specifications.

References
[1] P. Babin, G. Della Valle, R. Dendievel and L. Salvo, Proceedings of the 5th International Conference Engineering and Food, Montpellier France (2004).
[2] P.M. Falcone, A. Baiano, F. Zanini, L. Mancini, G. Tromba, F. Montanari and M.A. Del Nobile, J. Food Science 69, 38 (2004).

Authors
P. Babin (a,b), H. Chiron (c), J. Hoszowska (d), P. Cloetens (d), P. Pernot (d), AL. Réguerre (c), L. Salvo (a), R. Dendievel (a) and G. Della Valle (c).
(a) GPM2, INP Grenoble (France)
(b) Science Computers Consultants, St Etienne (France)
(c) URPOI, INRA Nantes (France)
(d) ESRF