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Impact of air humidity in industrial heating processes on selected quality attributes of bread rolls
Journal of Food Engineering 105 (2011) 647–655
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Journal of Food Engineering journal homepage: www.elsevier.com/locate/jfoodeng
Impact of air humidity in industrial heating processes on selected quality attributes of bread rolls M. Schirmer ⇑, W.B. Hussein, M. Jekle, M.A. Hussein, T. Becker Technische Universität München, Lehrstuhl für Brau- und Getränketechnologie, Weihenstephaner Steig 20, 85354 Freising-Weihenstephan, Germany
a r t i c l e
i n f o
Article history: Received 7 May 2010 Received in revised form 5 January 2011 Accepted 15 March 2011 Available online 29 March 2011 Keywords: Bread Baking Humidity Crispness
a b s t r a c t The object of this research was to study the real time percent humidity of the air and consequently to analyze this humidity influences on bread rolls. An industrial baking process was visualised by the use of a high-temperature humidity sensor to measure the level of percent humidity of the air (V% H2O) in relation to the different H2O-steam amounts (SA). In this study H2O-SA from 0 to 3.256 L(H2O) m3 of the oven volume were used. After steaming the results of gas moisture without product (GMWoP) showed a higher maximum (approx. 5%) of the percent humidity of the air than the gas moisture with product (GMWP). The trials reveal that the presence of products (bread rolls) is a factor in attaining an increase in the percent humidity of the air which influences product quality. Baking with adequate percent humidity of the air bread roll volume increased by 20% compared to trials without steam. New methods were used to quantify product parameters like crust thickness, compression-force and crispness and to find out correlations with the area under the GMWP curve (auc). Strongest correlations with auc GMWP were found for mean and maximum compression-force. Furthermore, it was shown that the increase in crust thickness, lightness and colour change is mutually dependent on an increase change in the total GMWP. Ó 2011 Elsevier Ltd. All rights reserved.
1. Introduction A Decisive factor in producing baked goods is the baking process since final product properties are defined in this stage. Bread rolls baking is a composite of several thermodynamic processes including conduction, convection, radiation of thermal energy, phase change and mass transfer (Sakin et al., 2009). The degree of induced heat, humidity level in the baking chamber and baking time have major impact on final product quality (Therdthai et al., 2002). Until now industrial baking ovens are traditionally controlled by time and temperature. Besides, steam has been proven to be a crucial point considering the heat transfer process (Kriems and Hermann, 1994). The thermodynamic activities during bread baking have to be known for a proper estimation of the energy transfer between steam and bread. The baking process is one of the most energy demanding processes (around 4 MJ kg1) compared with other thermal processes whereby 22–25% are used for the evaporation (Le-bail et al., 2010). Even today, steaming is still controlled by bakers´ experience. Thus it is unknown to which extent steam injection affects both final bread properties and energy balance in the oven. The knowledge about oven humidity ⇑ Corresponding author. Tel.: +49 8161 5271; fax: +49 8161 3883. E-mail addresses: [email protected], [email protected] (M. Schirmer). 0260-8774/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.jfoodeng.2011.03.020
profile during baking as affected by steam injection would help to create a defined and controllable baking environment to achieve optimal product quality. In recent publications, different baking processes were analysed only with regard to time–temperature dependency (Therdthai et al., 2002; Sommier et al., 2005; Purlis and Salvadori, 2009). However, there is broad consensus about the importance of steaming during baking, especially in the first few minutes. Some authors published results in which baking tests with and without steam are compared (Xue and Walker, 2003; Sommier et al., 2005), but up to now there are no publications about baking tests with different H2O steam amounts (SA). Moreover different H2O-SA and percent humidity of the air in the oven during baking time haven’t been subjected to investigations on final product parameters, yet. Solely (Walker et al., 2000) measured resident humidity at temperatures above 100 °C and stated it to be difficult, slow, expensive and inaccurate. Accurate real time humidity measurements are needed in order to document the effect of humidity on baking. Simultaneously, this demands for additional humidity control of ovens. Therefore, in this study a high temperature humidity probe able to measure temperatures up to 300 °C was used to measure percent humidity of the air and thus to evaluate its dependence products’ attributes. Bread rolls were chosen to evaluate easily quality parameters like crust development, firmness and crispness. Crispness is
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dependent on several factors as there is influence of ingredient composition (recipe, physical properties of the components) and structure properties of the baked goods (Vincent, 1998; Luyten et al., 2004). This mostly subjective impression is visualised by new special methods which allow profound insight into crispness perception and correlation to crust thickness, simultaneously. The major objective of this research was to study real time percent humidity of the air and consequently analyzing this specific humidity influence on products. Thereby innovative methods to evaluate crispness and crust thickness were applied. Finally the relationship between real time humidity and volume, colour, crust thickness and especially the crispness was analysed. The results of this study could be useful for reducing humidity to a low, still processible value which implies energy savings whilst obtaining optimum product quality.
2. Experimental 2.1. Bread rolls ingredients All experiments were carried out with commercial wheat flour of ‘‘Type 550’’ (Schapfen Mühle GmbH & Co., Ulm-Jungingen, Germany). The other ingredients were dry-yeast (Ferminpan, Casteggio, Italy), NaCl (Südsalz GmbH, Heilbronn, Germany), baking malt (Bib Ulmer Spatz, Bingen, Germany), shortening (Meister Marken, Brennen, Germany) and tap water. The bread rolls dough (water addition of 60 g (100 g flour)1) formulation is shown in Table 1. 2.2. Flour analysis Protein content, farinogram parameters and moisture content of the flour were analysed. Flour protein content (12.5 ± 0.5%) was determined according to the ICC-Standard method 105/1 (Digestrahl Digestion Apparatus, Hach Europa, Floriffoux, Belgium). Flour farinograph parameters (water binding of 59% at 500 FE) were analyzed according to the ICC 155/1 (EXEK/3, Brabender, Duisburg, Germany), flour moisture content (13.0%) was measured according to the AACC approved method 44-01 (AACC, 1999) by using a moisture analyzer (Moisture Analyser 51, Sartorius AG, Göttingen, Germany) and the ash content (0.596%) was measured according to the ICC 104/1-Standard. All flour analysis were conducted in duplicate and presented as the mean of it. 2.3. Dough preparation All ingredients were weighted and mixed (Diosna laboratory kneaders with group controller, Multimixing S.A. GmbH, Osnabrück) for 1 min at 53 rpm and for 6 min at 106 rpm. An optimum of the dough temperature of 28 °C, which is known as the general temperature for bread rolls baking, was maintained. At
Table 1 Ingredients of the bread rolls dough formulation. Ingredients
Weight (g)
Wheat flour (14% mb) Yeast NaCl Malt Shortening Tap watera
1000 16 20 30 5 586
a The amount of water was adjusted to the flour moisture content according to the AACC approved method 44-01 (AACC, 1999).
this dough temperature an optimum of protein and starch plasticity is warranted to form dough samples. After mixing the dough it was proved for 15 min at 30 °C and relative moisture of 80% (MS 80 GACO, Wachtel Stamm freezing B.V., Hilden, Germany). Subsequently bread rolls of 58 g were formed in the bread rolls forming machine (Optima, G.L. Eberhardt, München, Germany). Following 20 bread rolls were placed at one plate and rested again in the proofing room for 80 min. After 30 min of the resting time the rolls were cut in the middle (exactly 1 cm deep and 4 cm long – by hand, with a knife). 2.4. Bread rolls baking For all baking tests a deck oven (Matador Store 128, Werner & Pfleiderer GmbH, Sohland, Germany) was used. The volume of the baking chamber is 0.215 m3 and the hearth surface 1.92 m2. Each experiment was carried out by using two aluminium trays (60 80 cm, each with 20 rolls on it), a temperature of 225 °C, a baking time of 15 min and an occupation ratio of 1.208 kg m2. After 13 min of baking the chimney was opened to drag out the moisture. Table 2 shows the H2O-SA values of the tests. Distillated water was used for the injection of steam. The different amounts of water were measured before injection to the steaming box. In the steaming box (material: casting, temperature: around 300 °C) the water has been directly converted from fluid to gas (>100 °C) and injected into the oven. All measurements were done by three experiments with a sample size of 40 bread rolls. 2.5. High temperature humidity measuring The high-temperature humidity sensing system (Hygrophil Z, Type 1701-41, Bartec GmbH, Gotteszell, Germany) is a probe for measuring the level of percent humidity in the air. This dualelement-operation-sensor delivers reliable measurement results even under dust and dirt charged conditions and is suitable for gas temperatures up to 300 °C with a response time of 3 s. A calibration of the system was done before experimental series by the Physikalisch-Technische Bundesanstalt of Germany. The measuring sensor is equipped with two zirconium oxide/oxygen sensors. Both cells function as current-limiting oxygen sensors. While the one cell measures the oxygen content, the second is supplied with electricity so that the existing humidity (H2O-molecules) is decomposed (dissociated) electromechanically into hydrogen and oxygen. At high temperatures zirconium oxide becomes conductive in the manner of an electrolyte. A disc made of zirconium oxide and a number of additives are heated to 500–800 °C. The disc becomes conductive and adopts electrolytic characteristics governed by Nernst’s laws. The disc is fitted on both sides with gas-permeable noble-metal electrodes. An electromotive force (e.m.f. – a voltage) is created at the two electrodes when there is a difference in oxygen concentration on the two sides. The produced oxygen significantly increases the oxygen supply for this second cell, enabling it to be used for measurement purposes. With the usage
Table 2 Experimental L(H2O) m3.
classification
of
the
H2O-SA
Experimental number
H2O-SA (L(H2O) m3)
1 2 3 4 5 6 7 8
0.000 0.465 0.930 1.392 1.850 2.325 2.790 3.255
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of this dual sensor system it is possible to measure the moisture in gases containing no oxygen (100 V% H2O), e.g. inert gases, because the oxygen needed to measure the moisture is produced by the measuring cell itself by electrolysis of the existing water vapour. In this case the water vapour is directly proportional to the air humidity. Finally the signals of both cells are combined mathematically to form an overall measurement signal which is converted in volume percentage of water in the air. The reproducibility amounts to ±0.2 V% H2O and measurement error limits are 1 V% H2O. By using an analogue converter (USB 6255, National Instruments GmbH, München, Germany) and a data analyzer software (easy-link V.1.96, National Instruments GmbH, München, Germany) the sensor output can be converted from 0–20 mA into volume 0–100% of water in the air. The sensor was placed in the middle of the oven and the humidity measurements were done during the whole baking process from 0 to 15 min. 2.6. Surface colour-measuring The L⁄a⁄b⁄ colour space which is the most commonly used colour system in colorimeter data acquisition and image processing systems was used to show the colour changing of the bread rolls. The three coordinates of the L⁄a⁄b⁄ scale represent the lightness of the colour (L⁄ from 0 to 100), its position between red/magenta and green (a⁄ from 120 to 120) and its position between yellow and blue (b⁄ from 120 to 120) (León et al., 2006; Pedreschi et al., 2006). The colour of the bread rolls surface was measured by using a colourimeter (Spectro guide sphere gloss, BYK Additives & Instruments Gardner GmbH, Geretsried, Germany). The average of 20 samples from each experiment (n = 3) was taken to represent the colour in each step when H2O-SA was changed. Thereby all bread rolls were measured three times – one measurement was taken at the top and two at the side. The total colour change (DE) was calculated by the Eq. (1):
DE ¼
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ðL0 LÞ2 þ ða0 aÞ2 þ ðb0 bÞ2
ð1Þ
where L0 = 100, a0 = 0 and b0 = 0 (white). 2.7. Crust-thickness-measuring After cooling the bread rolls for two hours, they were cut at a height of 2 cm, thus the crumb and crust areas can be analyzed at the cut sections. To calculate the mean of the crust thickness, eight bread rolls from each experiment (n = 3) were analyzed at ten different points (q.v. Fig. 1B), resulting in a total number of 80 points per experiment (JPEG format, 640 480 pixels). The distributions of the three colour parameters (R, G, and B) with the number of pixel were used to estimate the crust thickness, following the test procedure described in Fig. 1A. The RGB colour model is an additive colour model in which red, green, and blue light are added together in various ways to reproduce a broad array of colours. First the image file was loaded and different x-stations (resulting the ten different points were the crust where measured) were chosen on it, as shown in Fig. 1B. Afterwards, the distribution of R, G, and B colour parameters is plotted for each x-station, as shown in Fig. 1C. As there is a visible separation between the colour values on the crust and its values on the crumb, the crust thickness can be distinctively estimated by setting a threshold equals 0.4 of the maximum colour volume. Finally, the mean crust thickness is calculated for all the x-stations to represent the average crust thickness of the bread rolls. Bread rolls containing some bubbles – which are easily detected by their low colour values – were filtered out of the crust calculation. Several experiments showed instead of proved that it is sufficient to use the B colour value to estimate the crust thickness,
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rather than using R, G, and B. The same analysis can be done by L⁄a⁄b⁄ colour system, but it needs high effort to measure these colour values over most of the pixels of the bread rolls. The developed algorithm was employed into a user friendly interface to be used in future analysis. 2.8. Volume detection After baking the bread rolls were cooled down to ambient temperature for 1 h. The bread rolls volumes were determined according to AACC 10-05 (2000) rapeseed procedure. This method is based on a volume displacement system. For each experiment (n = 3) 10 bread rolls were measured. 2.9. Acoustic and compression-force measurements The acoustic and compression-force tests were performed with a texture analyzer (TA-XT Plus, Stable Micro Systems Ltd., Surrey, UK). The bread rolls were fractured using a circular-shaped aluminium plate (diameter = 100 mm, and contact area = 7853 mm2) at a speed of 1 mm s1 and a total bread rolls deformation of 70%. This slow speed was chosen, after many tests, to cover the detailed and small crack developments which occur while pressing the bread rolls. The sound emitted during fracturing (in the audible range up to a frequency of 12.5 kHz) was recorded with a high frequency microphone (Type 2671, Brüel Kjaer, UK) in combination with an acoustic envelope detector (Stable micro systems, Godalming, UK). The sound recording was 200 points sec1. Different positions for the microphone were examined to have the best recording, hence the microphone was placed 70 mm from the centre of the texture analyzer platform with an elevation of 20 mm. Moreover, the fractures and sound tests were performed inside an echoic isolated chamber to avoid interference with an external source of sound. The envelope detector presented the changes in sound energy with time as well as the changes of the applied compression-force. The analogue sound signal and the data of the texture analyzer were digitized using an A/D converter (type 2827, Brüel Kjaer, UK) with a sampling rate of 200 Hz. Afterwards, the sounds were saved on a personal computer as wave files and a programme was developed to perform the required signal analyses. The signal was divided into (400–500) segments and each segment was multiplied by a Blackman window function (Eq. (2)) to reduce the spectral leakage and increase the amplitude accuracy.
wðnÞ ¼ 0:42 0:5 cos
2pn 4p n þ 0:08 cos N1 N1
ð2Þ
where w is the window function value at this point, N is the total number of points on the segment and n is the instantaneously point number. Accordingly, a technique was implemented, as shown in Fig. 2, based on Short Time Fourier Transform (Hussein et al., 2010), and applied to the consequent segments producing the instantaneously frequency contents of the acoustic signals, as shown in the sonogram given in Fig. 2. Once the signal is cleared out from the attached noise, all its features and parameters could be extracted and calculated. In this paper we focused on calculating the maximum and average sound levels and the sound energy (i.e., auc acoustic signal) of the acoustic signals. Whereby auc the integration of the acoustic signal of each measurement (with a sound recording of 200 points sec1) represents. In addition for the compression force–time-curves, the maximum and average force level will be calculated. The results are shown as mean value of sample size = 8 of each experiment (n = 3).
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Fig. 1. (A) Measurement algorithm for the crust thickness. (B) The x-stations which were chosen to measure the crust thickness of the bread rolls. (C) The distributions of R, G, and B colour values with the number of pixels, showing the crust thickness to contain the lowest colour values.
Fig. 2. (left) A schematic description for the algorithm used to detect the noise contents of the signals. (right) Sonogram for the recorded acoustic signal of experiment 8 = 3.255 L(H2O) m3.
2.10. Statistical analysis Statistical analyses were realised with the Software Statgraphics Centurion (Statpoint Technologies Inc., Warrenton, Virginia). A simple linear regression analysis was used to explore the relationships between the variables. Thereby correlations between H2O-SA, auc GMWP, colour change, crust thickness, lightness, max/mean compression-force as well as the sound level were analysed. The correlation coefficient was used to measure the degree of the correlation (Sachs, 2004) and to point out a strong significances (p < 0.001). 3. Results and discussion 3.1. Effect of H2O-SA on the real time humidity during the baking process A high-temperature humidity sensing system was used to measure the percent humidity of the air during baking. This humidity
taken as V% H2O was measured for gas moisture without product (GMWoP) and for gas moisture with product (GMWP). Pre-tests revealed that measuring at 9 different locations (in the baking room) resulted in deviations of negligible (±1%) V% H2O. Thus the same sensor position was chosen for all measurements. Directly after starting the baking programme the different H2OSA were injected. Fig. 4A shows that after steam injection V% H2O of all experiments of GMWoP increased unto a maximum specific for each experiment. These maxima depend on the different H2OSA and the saturation level. Further increasing the H2O-SA the peak of V% H2O rose until saturation level line-up between 80% and 90 %. After increasing V% H2O and attaining the peak, a polynomial decrease in humidity can be observed until opening the chimney. These characteristics are immanent for ‘‘open systems’’ with respect to the used baking oven and the dumping of H2O-SA at the beginning of the baking process. After opening the chimney GMWoP decreased to nearly 0 V% H2O. Fig. 4B represents the GMWP over to the baking time. After starting the baking process and injecting steam, an almost
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Fig. 3. The upper sound curve demonstrates the original sound level and the lower sound curve demonstrates the filtered sound level (removed noise frequencies between 20 and 30 Hz), exemplary for experiment 8 = 3.255 L(H2O) m3.
immediate increase in the V% H2O occurred, as it was observed in the GMWoP-tests. The maximum GMWP at the beginning (around 2 min) of the baking process was lower than for the GMWoP. This lower maximum of GMWP depends on steam condensation on the product surface which is due to a temperature gradient between steam (approx. 100 °C) and product surface (approx. 30 °C). After a slight decay in air moisture, the absolute air humidity stabilized to a common value between 68% and 80% until opening of the chimney. These inflexion points relay on the temperature interchange between hot air and bread rolls. On the one hand the condensation of water onto the bread rolls surface is vaporised instead of emitted and on the other hand water of the dough system is emitted in the air and both contribute to a humidity increase. These effects are shown by the humidity profile for GMWP with (h) experiment 1 (baking without steam) where a humidity increase were analyzed (q.v. Fig. 3B). After opening the chimney the V% H2O falls down to a range of 20–30 V% H2O. These results prove that the products are contributing to oven humidity. At a baking time of 10 min the V% H2O of GMWP is just about 60 V% H2O higher than for GMWoP.
Table 3 shows the V% H2O during baking time which is calculated by the integration of GMWoP values. The total value of the area under the GMWoP curve (auc) increased but the differences between the tests decreased above a H2O-SA of 1.395 L(H2O) m3 (experiment 4). These effects are related on the total saturation of air with water vapour. When the saturation point is reached the percent humidity of the air decreases constantly due to the ‘‘open system’’. 3.2. Effect of percent humidity of the air (auc GMWP) on the bread rolls quality parameters 3.2.1. Bread rolls volume expansion Rising of dough during baking is based on CO2 production and the expansion of gas contained in the cells of the fermented dough (especially CO2) (Lucas et al., 2007). In detail, yeast will continue CO2 production during the first minutes until its interaction temperature of 55 °C is reached. Further temperature increase up to 65 °C leads to gas cell expansion caused by CO2 and including H2O vaporisation mainly. The so called oven rise corresponds to a volume increase of the bread rolls which is almost linear to time
1 Fig. 4. Humidity profile for (A) GMWoP in VH2O V 1 baking room (%) and (B) GMWP in VH2O V baking room (%) by different H2O-SA in relation to the baking time of 15 min (after 13 min the take-off was opened). All measurements show the mean of three experiments. h experiment 1, j experiment 2, } experiment 3, experiment 4, s experiment 5, d experiment 6, 4 experiment 7, N experiment 8.
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Table 3 Auc of the V% H2O during baking time for GMWoP and GMWP in relation to the different experimental number respectively H2O-SA. The results are shown as mean value of sample size = 3, with standard deviation. Experimental number
H2O-SA (L(H2O) m3)
Auc GMWoP; V H2O during time (% min)
Auc GMWP; V H2O during time (% min)
1 2 3 4 5 6 7 8
0.000 0.465 0.930 1.392 1.850 2.325 2.790 3.255
30.8 ± 0.5 243.9 ± 4.6 373.6 ± 9.6 437.5 ± 6.1 447.5 ± 5.5 479.5 ± 1.5 490.8 ± 1.9 495.7 ± 6.0
517.2 ± 9.0 661.9 ± 14.0 810.3 ± 16.7 913.9 ± 10.5 969.1 ± 2.8 1006.3 ± 7.7 1081.0 ± 18.7 1286.5 ± 23.1
Fig. 5. Bread rolls volume depending on the different auc GMWP (from experiment 1–8). The results are shown as mean value of sample size = 30, with standard deviation.
during the first baking step (Fan et al., 1999; Lucas et al., 2007; Zhang et al., 2007). Both brought forward by steaming. During steam condensation on the product surface energy is transferred to the bread rolls which also mediates volume increase. To find out the relation between the volume of the bread rolls and the different auc GMWP the total bread rolls volume was measured after baking. Fig. 5 shows a distinct increase in bread rolls volume until experiment 3 with a moisture content of approximately 810% min. The total volume of the bread rolls for the following experiments features almost the same range. Baking without steam (517 % min) in comparison to experiment 3 (810% min) reveals a volume increase by nearly 20%. Tearing of the crust was observed for low steaming. With regard to Table 4 it can be seen that the final bread rolls volume (310.6 ± 4.4 mL) can already be achieved by the use of only 0.930 L(H2O) m3. The enthalpy of condensation transferred from the vapour to bread rolls surface is adequate for the oven rise. Additionally, the bread rolls surface is thus flexible enough to undergo the bread rolls volume expansion.
3.2.2. Colour detection on the bread rolls surface Steaming is also relevant for the surface appearance of bread rolls which includes colour and lightness. Fig. 6 shows that the lightness increases if auc GMWP increase. Besides that, Fig. 6 presents the colour change based on L⁄ (lightness), a⁄ (red–green) and b⁄ (yellow–blue) by the different auc GMWP on the bread rolls surface. The bread rolls surface becomes lighter and the colour changes by increasing auc GMWP. This statement is assisted by Ahrné et al. (2007) who reported that crust colour depends on baking temperature and humidity. On the one hand an increasing of humidity blocks the direct temperature transmission to the product. So the crust temperature during baking is lower and the product colour is lighter. On the other hand with the humidity during the baking process, structural changes (especially in the crust) take place (Ahrné et al., 2007). For example the starch of the crust is degrading to dextrin, mono- and disaccharides (Belitz and Schieberle, 2001). The most important structural changes bear on the changing of the dextrin’s and melanoidins’ constitution. Melanoidins (brown-coloured polymers) commonly exist in the bread curst and arise out of the Maillard reaction (Borrelli et al., 2003). 3.2.3. Crust thickness measuring Table 4 shows the increase in crust thickness in dependence on auc GMWP increase. This rise in crust thickness depends on the energy transmission by steam. As presented in Table 3 an increase in percent humidity of the air is closely connected with an increase in auc GMWP. The standard deviation decreases by increasing auc GMWP. This effect depends on consistent heat distribution on the bread rolls surface due to steam condensation on the bread rolls surface. Mohd Jusoh et al. (2009) approved these correlations between lightness and crust thickness of bread. The heat transfer at the condensation-front is complex. By steaming the crust temperature and colour change decrease (q.v. Fig. 6). It is expected that steam increases the water content in the crust surface (due to a temperature gradient between steam (approx. 100 °C) and product surface (approx. 30 °C) at the beginning of baking) – shown at the lower maximum of GMWP against GMWoP (q.v. Fig. 4) – resulting in better heat conduction compared to a dry surface. The higher energy transfer is based on the fact that the heat transmission coefficient of water and steam may be higher than the heat transmission coefficient of air (Chemieingenieurwesen, 2006). 3.2.4. Acoustic and compression-force detection Former publications dealt with product composites in connection to the product crispness and hardness (Primo-Martín et al., 2009; Salvador et al., 2009). To visualise product changes due to the percent humidity of the air, crispness sound was used. This method was used to evaluate differences on the crispness of bread crust in dependence on the auc GMWP. On the one hand the bread rolls crispness depends on crust structure and on the other hand on crumb properties. The sound and compression-force, needed to compress the bread rolls by 70% and the resulting sound level was measured.
Table 4 Relationship between bread rolls quality parameters and the real time humidity (auc GMWP) of experiment 1–8. The results are shown as mean value of sample size = 3, with standard deviation. Auc GMWP (% min) H2O-SA (L(H2O) m3) Volume (mL) Lightness (-) Colour change (-) Crust thickness (mm) Max. force (N) Mean force (N)
517.3 0.000 246.3 ± 0.9 60.0 ± 1.9 53.5 ± 0.5 1.1 ± 1.0 17.7 ± 0.9 14.8 ± 2.0
661.9 0.465 279.4 ± 8.0 62.3 ± 2.1 50.9 ± 1.1 1.6 ± 0.8 22.5 ± 1.7 18.9 ± 0.7
810.3 0.930 310.6 ± 4.4 61.9 ± 2.1 51.2 ± 0.4 2.5 ± 0.7 25.4 ± 2.1 21.1 ± 1.4
914.0 1.392 313.1 ± 4.4 64.0 ± 1.6 49.2 ± 1.6 2.9 ± 0.5 28.6 ± 1.7 22.9 ± 2.0
969.2 1.850 304.7 ± 0.4 64.8 ± 1.4 48.1 ± 0.4 3.4 ± 0.2 28.0 ± 3.7 23.5 ± 1.3
1006.4 2.325 310.2 ± 7.3 66.1 ± 1.4 47.1 ± 1.1 3.9 ± 0.3 30.8 ± 3.1 24.2 ± 1.6
1081.1 2.790 317.5 ± 8.8 66.3 ± 1.6 46.9 ± 0.8 4.2 ± 0.3 32.0 ± 3.1 25.5 ± 1.5
1268.5 3.255 305.6 ± 4.4 67.0 ± 2.0 46.2 ± 0.7 4.6 ± 0.5 33.9 ± 2.0 26.6 ± 1.2
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Fig. 6. j Colour formation () and } lightness () depending on the auc GMWP from experiment 1–8. The results are shown as mean value of sample size = 60. Significant (p < 0.001) linear correlation of colour formation r = 0.954 and the lightness r = 0.954.
As an example curve Fig. 7 shows compression-force and the sound in relation to the compression rate by reference to experiment 8. This force-sound-distance-diagram was obtained during the fracturing process of bread rolls. The sound curve shows multiple peaks of varying amplitude which reveal the presence of a brittle cellular structure (Vincent, 1998). Unto a certain limit the applied uniaxial mechanical energy is dissipated. Crust fracture occurs after exceeding the limit whereas excess energy is emitted as sound (Vincent et al., 1991; Luyten et al., 2004). During compression the curves present two main regions where the crust breaks, the pre-creasing point and the breaking point. At the pre-cracking point little curst cracks occur and low acoustic level is emitted. This could be explained by an incipiently fracture of the crust break (the upper area of the bread rolls). Along with breaking sounds maxima in braking force could be detected at the same points. Incipiently fracture causes force development to pause shortly and to increase afterwards unto final breaking point. There the real crust deformation begins and the compression-force stayed constant. The most intensive acoustic signal emerged during breaking
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point. At this point the pressure of the circular-shape-plate and the advanced compression was already enough to crack the crust at all. After total break the compression-force increases again which is not represented in the calculations. At lower auc GMWP curve progression is similar to the one shown in Fig. 7, but with different compression-force and sound values. The different auc GMWP has great effect on crust crispness and hardness. The effect on the crust hardness is shown in Table 4. Maximum compression-forces as well as the mean compressionforces increase by a rise of auc GMWP. These effects depend on the same physical properties as seen for crust thickness: constant heat distribution on the bread rolls surface by increased auc GMWP and the condensation on the bread rolls surface. Thus a higher energy transfer occurs. The crispness of bread rolls could be described by the sound level. Fig. 8 shows the maximum sound level and the auc sound level depending on the auc GMWP. With increasing total percent humidity of the air during baking maximum sound significantly increases (p < 0.01) (r = 0.842). Until an auc GMWP of 810% min a high slope in the maximum sound was exhibited. Similar to the volume the crust crispness is very high for the first tests. By further increased auc GMWP structural crust changes are much smaller as in the lower auc GMWP. Fig. 9 demonstrates the highly significant (p < 0.001) linear correlations between the maximum force and the maximum sound (r = 0.930) as it was expected due to the results found in literature (Primo-Martín et al., 2008). In contrast Fig. 8 reveals that the area under the sound level curve (auc) has a polynomial characteristic in relation to auc GMWP (r = 0.975). Owing to increased steam injection and thus higher energy transfer crust thickness could have gained. Highest auc sound level was achieved at approximately 914% min where the energy transfer was sufficient to build up a perfect crust-thickness (around 3.0 mm) and therefore crispness. Beyond the maximum at 914% min the crust structure cannot be developed sufficiently due to excessive humidity in the oven. From the maximum sound at 77 dB up to 1286% min the maximum sound increase tends to stagnate. This decrease depends on the crust growth which is revealed
Fig. 7. d Compression-force (N), – sound level (dB) detection in relation to the distance for a compression process at 70% of the bread rolls, exemplary for experiment 8. At pre-creasing point (PCP) some small crust breaks take place. At breaking point (BP) the basic crust deformation begins. Between the two vertical lines the relevant values of the analysis are shown.
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Fig. 8. } Maximum sound level (dB) and j auc sound level during time (dB min) depending on the auc GMWP from experiment 1–8 obtained by 70% compression of the bread rolls. The results are shown as mean value of sample size = 24. Significant (p < 0.001) linear correlation max – r = 0.842 and polynomial correlation auc sound r = 0.975.
Fig. 9. Correlation between max. force (N) and max. sound level (dB) depending on experiment 1–8 obtained by 70% compression of the bread rolls. The results are shown as mean value of sample size = 24. Significant (p < 0.001) linear correlation r = 0.883.
in Table 4 and relies on crust thickness. Until the sound level optimum a crispiness increase is detected. During further crust formation the crispness sound decreases and excites only strong single break sounds. 3.3. Correlations between H2O-SA, percent humidity of the air and bread rolls quality parameters Having examined humidity course during baking (auc GMWP) and effects on the bread rolls properties by using different steam amounts analyses of correlations between both were made to find out the interdependence (Table 5). Table 5 Correlation matrix between H2O-SA, measured humidity during baking time and the bread rolls crust parameters. In all cases high significant (p < 0.001) linear correlations (r) were found. H2OSA
colour change
Auc GMWP 0.979 0.954 H2O-SA 0.968 Colour change Crust thickness Lightness Max force
crust thickness
Lightness Max force
Mean force
0.984 0.991 0.966
0.952 0.970 0.998
0.968 0.949 0.958
0.973 0.953 0.966
0.964
0.969
0.974
0.957
0.958 0.989
As shown in Figs. 5 and 8 no linear relationship between the auc GMWP and bread rolls volume as well as the auc sound level was found. But poorly significant (p < 0.05) linear relationship between the auc GMWP and the maximum sound level (r = 0.842) was found. In all other cases high significant (p < 0.001) linear correlations were detected. As a result high correlations are shown between the auc GMWP, the mean (r = 0.973)/max (r = 0.968) force obtained by 70% compression of the bread rolls and the crust thickness (r = 0.984). These correlations depend on the increase in crust thickness (Table 4) which is corroborated by the correlations of crust thickness and mean (r = 0.974)/max (r = 0.969) compression-force. Thus, crust parameters depend on percent humidity of the air during baking. Higher heat and mass transfer due to increased percent humidity of the air during baking causes thicker crust formation and higher compression-force are to be applied. A model for the crust formation during baking was already presented by (Jefferson et al., 2007) which were used from Jefferson et al. (2006) to show that raising the vaporisation temperature gives a rise to a thicker crust. In the experiments high percent humidity of the air means an increase of the vaporisation temperatures additional with higher energy transfer into the bread rolls (Jefferson et al., 2006). This is based on the fact that the heat transmission coefficient of steam and humid air is higher than for dry air. Additionally, correlations between auc GMWP and the lightness (r = 0.952) as well as a negative relationship with the colour change (r = 0.958) were detected. Colour change correlated negatively (r = 0.966) with crust thickness as it was also reported by Jusho et al. (2009). They also confirmed a strong positive correlation between both, crust thickness and colour change, by increasing baking temperature. As shown in Table 5, correlations between H2O-SA and product quality are in the same range like those for auc GMWP and the product quality. This is indicated by the high significant (p < 0.001) linear correlation (r = 0.979) between H2O-SA and auc GMWP. These data reveal that the product quality can either be monitored by injected steam amount (H2O-SA) or total resulting humidity (auc GMWP) which is additionally due to evaporated water of baking goods.
4. Conclusion In general time and temperature are used as control parameters during the baking process. Steam amount, thus humidity level in the baking chamber was introduced as a further parameter to analyse the influence on the end product quality. For judging the quality of bread rolls the volume of the final product and their crust properties were used as key parameters. During the baking process, it was analysed that the baking goods themselves contribute essentially to the humidity in the oven. Further, water condensation on the bread roll surface and the product water release during baking were shown by real time humidity measurement. Nearly the same product water output could be observed in all experiments. Thus, it can be proven that humidity is a relevant factor at the beginning of the baking process. By increasing the steam amount and consequently the auc GMWoP several bread roll properties, like the bread roll volume, crust lightness, colour change, crust thickness, firmness and the sound level were positively affected. It is known that the formation of a stable crust is one of the most important factors of the baking process. Therefore special methods were used to quantify the crust thickness as well as the compression-force and the crispness. Without a stable crust the product is not able to maintain its shape. Additional the crust is very important for the flavour of bread rolls (Purlis and Salvadori, 2007; Mohd Jusoh et al., 2009; Vanin et al.,
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2009). It can be seen that by increasing the auc GMWoP, the crust thickness, the compression-forces and the maxima sound level increased. Moreover by increasing the auc GMWoP the auc sound level increased up to a humidity amount of 913% min. At this point the sound level stagnated and finally decreased. The experiments showed that a humidity amount of approximately 925% min is adequate to receive a maximal volume and crispiness. The study also demonstrates that the steam amount has a significant influence on the properties of the end product. The new approach of the real time humidity measurement shows high interdependency between product quality and percent humidity of the air. Furthermore the product quality can be affected by injected steam amount (H2O-SA) or total resulting percent humidity of the air (auc GMWP). In summary, an inline monitoring tool like the used high humidity measuring system provides an opportunity to control the baking process by reducing humidity level up to the lowest still processible value, which allows to save energy and to provide products of good quality. With regard to these first correlation further work is necessary to determine and to analyse the heat transition process by humidity independent of the product. Acknowledgements This research project was supported by the German Ministry of Economics and Technology (via AiF) and the FEI (Forschungskreis der Ernährungsindustrie e.V., Bonn). Project AiF 15659N. References Ahrné, L., Andersson, C.-G., Floberg, P., Rosén, J., Lingnert, H., 2007. Effect of crust temperature and water content on acrylamide formation during baking of white bread: steam and falling temperature baking. LWT – Food Science and Technology 40 (10), 1708–1715. Borrelli, R.C., Mennella, C., Barba, F., Russo, M., Russo, G.L., Krome, K., Erbersdobler, H.F., Faist, V., Fogliano, V., 2003. Characterization of coloured compounds obtained by enzymatic extraction of bakery products. Food and Chemical Toxicology 41 (10), 1367–1374. Chemieingenieurwesen, V.-G.V.u., 2006. VDI-Wärmeatlas. Springer Verlag, p. 10. Fan, J., Mitchell, J.R., Blanshard, J.M.V., 1999. A model for the oven rise of dough during baking. Journal of Food Engineering 41 (2), 69–77. Belitz, H.-D., Schieberle, P., 2001. Lehrbuch der Lebensmittelchemie, p. 5. Hussein, W.B., Hussein, M.A., Becker, T., 2010. Detection of the red palm weevil using its bioacoustics features. Journal of Bioacoustics 19 (3), 177–194. Jefferson, D.R., Lacey, A.A., Sadd, P.A., 2006. Understanding crust formation during baking. Journal of Food Engineering 75 (4), 515–521. Jefferson, D.R., Lacey, A.A., Sadd, P.A., 2007. Crust density in bread baking: mathematical modelling and numerical solutions. Applied Mathematical Modelling 31 (2), 209–225.
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Kriems, P., Hermann, C., 1994. New information on the effect of baking temperature, the turbo effect, and oven air moisture content on crust and crumb development in mixed rye bread. Getreide, Mehl und Brot 48 (1), 41–46. Le-bail, A., Dessev, T., Jury, V., Zuniga, R., Park, T., Pitroff, M., 2010. Energy demand for selected bread making processes: conventional versus part baked frozen technologies. Journal of Food Engineering 96 (4), 510–519. León, K., Mery, D., Pedreschi, F., León, J., 2006. Color measurement in L⁄a⁄b⁄ units from RGB digital images. Food Research International 39 (10), 1084–1091. Lucas, T., Le Ray, D., Peu, P., Wagner, M., Picard, S., 2007. A new method for continuous assessment of CO2 released from dough baked in ventilated ovens. Journal of Food Engineering 81 (1), 1–11. Luyten, H., Johan, P., Ton Van, V., 2004. Crispy/crunchy crusts of cellular solid foods: a literature review with discussion. Journal of Texture Studies 35 (5), 445–492. Mohd Jusoh, Y.M., Chin, N.L., Yusof, Y.A., Abdul Rahman, R., 2009. Bread crust thickness measurement using digital imaging and L a b colour system. Journal of Food Engineering 94 (3–4), 366–371. Pedreschi, F., León, J., Mery, D., Moyano, P., 2006. Development of a computer vision system to measure the color of potato chips. Food Research International 39 (10), 1092–1098. Primo-Martín, C., de Beukelaer, H., Hamer, R.J., Van Vliet, T., 2008. Fracture behaviour of bread crust: effect of ingredient modification. Journal of Cereal Science 48 (3), 604–612. Primo-Martín, C., Sözer, N., Hamer, R.J., Van Vliet, T., 2009. Effect of water activity on fracture and acoustic characteristics of a crust model. Journal of Food Engineering 90 (2), 277–284. Purlis, E., Salvadori, V.O., 2007. Bread browning kinetics during baking. Journal of Food Engineering 80 (4), 1107–1115. Purlis, E., Salvadori, V.O., 2009. Bread baking as a moving boundary problem. Part 1: mathematical modelling. Journal of Food Engineering 91 (3), 428–433. Sachs, L., 2004. Angewandte Statistik, 11 Auflage. Springer Verlag. Sakin, M., Kaymak-Ertekin, F., Ilicali, C., 2009. Convection and radiation combined surface heat transfer coefficient in baking ovens. Journal of Food Engineering 94 (3–4), 344–349. Salvador, A., Varela, P., Sanz, T., Fiszman, S.M., 2009. Understanding potato chips crispy texture by simultaneous fracture and acoustic measurements, and sensory analysis. LWT – Food Science and Technology 42 (3), 763–767. Sommier, A., Chiron, H., Colonna, P., Della Valle, G., Rouillé, J., 2005. An instrumented pilot scale oven for the study of French bread baking. Journal of Food Engineering 69 (1), 97–106. Therdthai, N., Zhou, W., Adamczak, T., 2002. Optimisation of the temperature profile in bread baking. Journal of Food Engineering 55 (1), 41–48. Vanin, F.M., Lucas, T., Trystram, G., 2009. Crust formation and its role during bread baking. Trends in Food Science and Technology 20 (8), 333–343. Vincent, J.F.V., 1998. The quantification of crispness. Journal of the Science of Food and Agriculture 78 (2), 162–168. Vincent, J.F.V., Jeronimidis, G., Khan, A.A., Luyten, H., 1991. The wedge fracture test a new method for measurement of food texture. Journal of Texture Studies 22 (1), 45–57. Walker, C.E., Kalitsis, J., Bok, S., 2000. Common sensors: measuring humidity. European Baker 36 (2), 18, 20, 22. Xue, J., Walker, C.E., 2003. Humidity change and its effects on baking in an electrically heated air jet impingement oven. Food Research International 36 (6), 561–569. Zhang, L., Lucas, T., Doursat, C., Flick, D., Wagner, M., 2007. Effects of crust constraints on bread expansion and CO2 release. Journal of Food Engineering 80 (4), 1302–1311.
Contents lists available at ScienceDirect
Journal of Food Engineering journal homepage: www.elsevier.com/locate/jfoodeng
Impact of air humidity in industrial heating processes on selected quality attributes of bread rolls M. Schirmer ⇑, W.B. Hussein, M. Jekle, M.A. Hussein, T. Becker Technische Universität München, Lehrstuhl für Brau- und Getränketechnologie, Weihenstephaner Steig 20, 85354 Freising-Weihenstephan, Germany
a r t i c l e
i n f o
Article history: Received 7 May 2010 Received in revised form 5 January 2011 Accepted 15 March 2011 Available online 29 March 2011 Keywords: Bread Baking Humidity Crispness
a b s t r a c t The object of this research was to study the real time percent humidity of the air and consequently to analyze this humidity influences on bread rolls. An industrial baking process was visualised by the use of a high-temperature humidity sensor to measure the level of percent humidity of the air (V% H2O) in relation to the different H2O-steam amounts (SA). In this study H2O-SA from 0 to 3.256 L(H2O) m3 of the oven volume were used. After steaming the results of gas moisture without product (GMWoP) showed a higher maximum (approx. 5%) of the percent humidity of the air than the gas moisture with product (GMWP). The trials reveal that the presence of products (bread rolls) is a factor in attaining an increase in the percent humidity of the air which influences product quality. Baking with adequate percent humidity of the air bread roll volume increased by 20% compared to trials without steam. New methods were used to quantify product parameters like crust thickness, compression-force and crispness and to find out correlations with the area under the GMWP curve (auc). Strongest correlations with auc GMWP were found for mean and maximum compression-force. Furthermore, it was shown that the increase in crust thickness, lightness and colour change is mutually dependent on an increase change in the total GMWP. Ó 2011 Elsevier Ltd. All rights reserved.
1. Introduction A Decisive factor in producing baked goods is the baking process since final product properties are defined in this stage. Bread rolls baking is a composite of several thermodynamic processes including conduction, convection, radiation of thermal energy, phase change and mass transfer (Sakin et al., 2009). The degree of induced heat, humidity level in the baking chamber and baking time have major impact on final product quality (Therdthai et al., 2002). Until now industrial baking ovens are traditionally controlled by time and temperature. Besides, steam has been proven to be a crucial point considering the heat transfer process (Kriems and Hermann, 1994). The thermodynamic activities during bread baking have to be known for a proper estimation of the energy transfer between steam and bread. The baking process is one of the most energy demanding processes (around 4 MJ kg1) compared with other thermal processes whereby 22–25% are used for the evaporation (Le-bail et al., 2010). Even today, steaming is still controlled by bakers´ experience. Thus it is unknown to which extent steam injection affects both final bread properties and energy balance in the oven. The knowledge about oven humidity ⇑ Corresponding author. Tel.: +49 8161 5271; fax: +49 8161 3883. E-mail addresses: [email protected], [email protected] (M. Schirmer). 0260-8774/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.jfoodeng.2011.03.020
profile during baking as affected by steam injection would help to create a defined and controllable baking environment to achieve optimal product quality. In recent publications, different baking processes were analysed only with regard to time–temperature dependency (Therdthai et al., 2002; Sommier et al., 2005; Purlis and Salvadori, 2009). However, there is broad consensus about the importance of steaming during baking, especially in the first few minutes. Some authors published results in which baking tests with and without steam are compared (Xue and Walker, 2003; Sommier et al., 2005), but up to now there are no publications about baking tests with different H2O steam amounts (SA). Moreover different H2O-SA and percent humidity of the air in the oven during baking time haven’t been subjected to investigations on final product parameters, yet. Solely (Walker et al., 2000) measured resident humidity at temperatures above 100 °C and stated it to be difficult, slow, expensive and inaccurate. Accurate real time humidity measurements are needed in order to document the effect of humidity on baking. Simultaneously, this demands for additional humidity control of ovens. Therefore, in this study a high temperature humidity probe able to measure temperatures up to 300 °C was used to measure percent humidity of the air and thus to evaluate its dependence products’ attributes. Bread rolls were chosen to evaluate easily quality parameters like crust development, firmness and crispness. Crispness is
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dependent on several factors as there is influence of ingredient composition (recipe, physical properties of the components) and structure properties of the baked goods (Vincent, 1998; Luyten et al., 2004). This mostly subjective impression is visualised by new special methods which allow profound insight into crispness perception and correlation to crust thickness, simultaneously. The major objective of this research was to study real time percent humidity of the air and consequently analyzing this specific humidity influence on products. Thereby innovative methods to evaluate crispness and crust thickness were applied. Finally the relationship between real time humidity and volume, colour, crust thickness and especially the crispness was analysed. The results of this study could be useful for reducing humidity to a low, still processible value which implies energy savings whilst obtaining optimum product quality.
2. Experimental 2.1. Bread rolls ingredients All experiments were carried out with commercial wheat flour of ‘‘Type 550’’ (Schapfen Mühle GmbH & Co., Ulm-Jungingen, Germany). The other ingredients were dry-yeast (Ferminpan, Casteggio, Italy), NaCl (Südsalz GmbH, Heilbronn, Germany), baking malt (Bib Ulmer Spatz, Bingen, Germany), shortening (Meister Marken, Brennen, Germany) and tap water. The bread rolls dough (water addition of 60 g (100 g flour)1) formulation is shown in Table 1. 2.2. Flour analysis Protein content, farinogram parameters and moisture content of the flour were analysed. Flour protein content (12.5 ± 0.5%) was determined according to the ICC-Standard method 105/1 (Digestrahl Digestion Apparatus, Hach Europa, Floriffoux, Belgium). Flour farinograph parameters (water binding of 59% at 500 FE) were analyzed according to the ICC 155/1 (EXEK/3, Brabender, Duisburg, Germany), flour moisture content (13.0%) was measured according to the AACC approved method 44-01 (AACC, 1999) by using a moisture analyzer (Moisture Analyser 51, Sartorius AG, Göttingen, Germany) and the ash content (0.596%) was measured according to the ICC 104/1-Standard. All flour analysis were conducted in duplicate and presented as the mean of it. 2.3. Dough preparation All ingredients were weighted and mixed (Diosna laboratory kneaders with group controller, Multimixing S.A. GmbH, Osnabrück) for 1 min at 53 rpm and for 6 min at 106 rpm. An optimum of the dough temperature of 28 °C, which is known as the general temperature for bread rolls baking, was maintained. At
Table 1 Ingredients of the bread rolls dough formulation. Ingredients
Weight (g)
Wheat flour (14% mb) Yeast NaCl Malt Shortening Tap watera
1000 16 20 30 5 586
a The amount of water was adjusted to the flour moisture content according to the AACC approved method 44-01 (AACC, 1999).
this dough temperature an optimum of protein and starch plasticity is warranted to form dough samples. After mixing the dough it was proved for 15 min at 30 °C and relative moisture of 80% (MS 80 GACO, Wachtel Stamm freezing B.V., Hilden, Germany). Subsequently bread rolls of 58 g were formed in the bread rolls forming machine (Optima, G.L. Eberhardt, München, Germany). Following 20 bread rolls were placed at one plate and rested again in the proofing room for 80 min. After 30 min of the resting time the rolls were cut in the middle (exactly 1 cm deep and 4 cm long – by hand, with a knife). 2.4. Bread rolls baking For all baking tests a deck oven (Matador Store 128, Werner & Pfleiderer GmbH, Sohland, Germany) was used. The volume of the baking chamber is 0.215 m3 and the hearth surface 1.92 m2. Each experiment was carried out by using two aluminium trays (60 80 cm, each with 20 rolls on it), a temperature of 225 °C, a baking time of 15 min and an occupation ratio of 1.208 kg m2. After 13 min of baking the chimney was opened to drag out the moisture. Table 2 shows the H2O-SA values of the tests. Distillated water was used for the injection of steam. The different amounts of water were measured before injection to the steaming box. In the steaming box (material: casting, temperature: around 300 °C) the water has been directly converted from fluid to gas (>100 °C) and injected into the oven. All measurements were done by three experiments with a sample size of 40 bread rolls. 2.5. High temperature humidity measuring The high-temperature humidity sensing system (Hygrophil Z, Type 1701-41, Bartec GmbH, Gotteszell, Germany) is a probe for measuring the level of percent humidity in the air. This dualelement-operation-sensor delivers reliable measurement results even under dust and dirt charged conditions and is suitable for gas temperatures up to 300 °C with a response time of 3 s. A calibration of the system was done before experimental series by the Physikalisch-Technische Bundesanstalt of Germany. The measuring sensor is equipped with two zirconium oxide/oxygen sensors. Both cells function as current-limiting oxygen sensors. While the one cell measures the oxygen content, the second is supplied with electricity so that the existing humidity (H2O-molecules) is decomposed (dissociated) electromechanically into hydrogen and oxygen. At high temperatures zirconium oxide becomes conductive in the manner of an electrolyte. A disc made of zirconium oxide and a number of additives are heated to 500–800 °C. The disc becomes conductive and adopts electrolytic characteristics governed by Nernst’s laws. The disc is fitted on both sides with gas-permeable noble-metal electrodes. An electromotive force (e.m.f. – a voltage) is created at the two electrodes when there is a difference in oxygen concentration on the two sides. The produced oxygen significantly increases the oxygen supply for this second cell, enabling it to be used for measurement purposes. With the usage
Table 2 Experimental L(H2O) m3.
classification
of
the
H2O-SA
Experimental number
H2O-SA (L(H2O) m3)
1 2 3 4 5 6 7 8
0.000 0.465 0.930 1.392 1.850 2.325 2.790 3.255
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of this dual sensor system it is possible to measure the moisture in gases containing no oxygen (100 V% H2O), e.g. inert gases, because the oxygen needed to measure the moisture is produced by the measuring cell itself by electrolysis of the existing water vapour. In this case the water vapour is directly proportional to the air humidity. Finally the signals of both cells are combined mathematically to form an overall measurement signal which is converted in volume percentage of water in the air. The reproducibility amounts to ±0.2 V% H2O and measurement error limits are 1 V% H2O. By using an analogue converter (USB 6255, National Instruments GmbH, München, Germany) and a data analyzer software (easy-link V.1.96, National Instruments GmbH, München, Germany) the sensor output can be converted from 0–20 mA into volume 0–100% of water in the air. The sensor was placed in the middle of the oven and the humidity measurements were done during the whole baking process from 0 to 15 min. 2.6. Surface colour-measuring The L⁄a⁄b⁄ colour space which is the most commonly used colour system in colorimeter data acquisition and image processing systems was used to show the colour changing of the bread rolls. The three coordinates of the L⁄a⁄b⁄ scale represent the lightness of the colour (L⁄ from 0 to 100), its position between red/magenta and green (a⁄ from 120 to 120) and its position between yellow and blue (b⁄ from 120 to 120) (León et al., 2006; Pedreschi et al., 2006). The colour of the bread rolls surface was measured by using a colourimeter (Spectro guide sphere gloss, BYK Additives & Instruments Gardner GmbH, Geretsried, Germany). The average of 20 samples from each experiment (n = 3) was taken to represent the colour in each step when H2O-SA was changed. Thereby all bread rolls were measured three times – one measurement was taken at the top and two at the side. The total colour change (DE) was calculated by the Eq. (1):
DE ¼
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ðL0 LÞ2 þ ða0 aÞ2 þ ðb0 bÞ2
ð1Þ
where L0 = 100, a0 = 0 and b0 = 0 (white). 2.7. Crust-thickness-measuring After cooling the bread rolls for two hours, they were cut at a height of 2 cm, thus the crumb and crust areas can be analyzed at the cut sections. To calculate the mean of the crust thickness, eight bread rolls from each experiment (n = 3) were analyzed at ten different points (q.v. Fig. 1B), resulting in a total number of 80 points per experiment (JPEG format, 640 480 pixels). The distributions of the three colour parameters (R, G, and B) with the number of pixel were used to estimate the crust thickness, following the test procedure described in Fig. 1A. The RGB colour model is an additive colour model in which red, green, and blue light are added together in various ways to reproduce a broad array of colours. First the image file was loaded and different x-stations (resulting the ten different points were the crust where measured) were chosen on it, as shown in Fig. 1B. Afterwards, the distribution of R, G, and B colour parameters is plotted for each x-station, as shown in Fig. 1C. As there is a visible separation between the colour values on the crust and its values on the crumb, the crust thickness can be distinctively estimated by setting a threshold equals 0.4 of the maximum colour volume. Finally, the mean crust thickness is calculated for all the x-stations to represent the average crust thickness of the bread rolls. Bread rolls containing some bubbles – which are easily detected by their low colour values – were filtered out of the crust calculation. Several experiments showed instead of proved that it is sufficient to use the B colour value to estimate the crust thickness,
649
rather than using R, G, and B. The same analysis can be done by L⁄a⁄b⁄ colour system, but it needs high effort to measure these colour values over most of the pixels of the bread rolls. The developed algorithm was employed into a user friendly interface to be used in future analysis. 2.8. Volume detection After baking the bread rolls were cooled down to ambient temperature for 1 h. The bread rolls volumes were determined according to AACC 10-05 (2000) rapeseed procedure. This method is based on a volume displacement system. For each experiment (n = 3) 10 bread rolls were measured. 2.9. Acoustic and compression-force measurements The acoustic and compression-force tests were performed with a texture analyzer (TA-XT Plus, Stable Micro Systems Ltd., Surrey, UK). The bread rolls were fractured using a circular-shaped aluminium plate (diameter = 100 mm, and contact area = 7853 mm2) at a speed of 1 mm s1 and a total bread rolls deformation of 70%. This slow speed was chosen, after many tests, to cover the detailed and small crack developments which occur while pressing the bread rolls. The sound emitted during fracturing (in the audible range up to a frequency of 12.5 kHz) was recorded with a high frequency microphone (Type 2671, Brüel Kjaer, UK) in combination with an acoustic envelope detector (Stable micro systems, Godalming, UK). The sound recording was 200 points sec1. Different positions for the microphone were examined to have the best recording, hence the microphone was placed 70 mm from the centre of the texture analyzer platform with an elevation of 20 mm. Moreover, the fractures and sound tests were performed inside an echoic isolated chamber to avoid interference with an external source of sound. The envelope detector presented the changes in sound energy with time as well as the changes of the applied compression-force. The analogue sound signal and the data of the texture analyzer were digitized using an A/D converter (type 2827, Brüel Kjaer, UK) with a sampling rate of 200 Hz. Afterwards, the sounds were saved on a personal computer as wave files and a programme was developed to perform the required signal analyses. The signal was divided into (400–500) segments and each segment was multiplied by a Blackman window function (Eq. (2)) to reduce the spectral leakage and increase the amplitude accuracy.
wðnÞ ¼ 0:42 0:5 cos
2pn 4p n þ 0:08 cos N1 N1
ð2Þ
where w is the window function value at this point, N is the total number of points on the segment and n is the instantaneously point number. Accordingly, a technique was implemented, as shown in Fig. 2, based on Short Time Fourier Transform (Hussein et al., 2010), and applied to the consequent segments producing the instantaneously frequency contents of the acoustic signals, as shown in the sonogram given in Fig. 2. Once the signal is cleared out from the attached noise, all its features and parameters could be extracted and calculated. In this paper we focused on calculating the maximum and average sound levels and the sound energy (i.e., auc acoustic signal) of the acoustic signals. Whereby auc the integration of the acoustic signal of each measurement (with a sound recording of 200 points sec1) represents. In addition for the compression force–time-curves, the maximum and average force level will be calculated. The results are shown as mean value of sample size = 8 of each experiment (n = 3).
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Fig. 1. (A) Measurement algorithm for the crust thickness. (B) The x-stations which were chosen to measure the crust thickness of the bread rolls. (C) The distributions of R, G, and B colour values with the number of pixels, showing the crust thickness to contain the lowest colour values.
Fig. 2. (left) A schematic description for the algorithm used to detect the noise contents of the signals. (right) Sonogram for the recorded acoustic signal of experiment 8 = 3.255 L(H2O) m3.
2.10. Statistical analysis Statistical analyses were realised with the Software Statgraphics Centurion (Statpoint Technologies Inc., Warrenton, Virginia). A simple linear regression analysis was used to explore the relationships between the variables. Thereby correlations between H2O-SA, auc GMWP, colour change, crust thickness, lightness, max/mean compression-force as well as the sound level were analysed. The correlation coefficient was used to measure the degree of the correlation (Sachs, 2004) and to point out a strong significances (p < 0.001). 3. Results and discussion 3.1. Effect of H2O-SA on the real time humidity during the baking process A high-temperature humidity sensing system was used to measure the percent humidity of the air during baking. This humidity
taken as V% H2O was measured for gas moisture without product (GMWoP) and for gas moisture with product (GMWP). Pre-tests revealed that measuring at 9 different locations (in the baking room) resulted in deviations of negligible (±1%) V% H2O. Thus the same sensor position was chosen for all measurements. Directly after starting the baking programme the different H2OSA were injected. Fig. 4A shows that after steam injection V% H2O of all experiments of GMWoP increased unto a maximum specific for each experiment. These maxima depend on the different H2OSA and the saturation level. Further increasing the H2O-SA the peak of V% H2O rose until saturation level line-up between 80% and 90 %. After increasing V% H2O and attaining the peak, a polynomial decrease in humidity can be observed until opening the chimney. These characteristics are immanent for ‘‘open systems’’ with respect to the used baking oven and the dumping of H2O-SA at the beginning of the baking process. After opening the chimney GMWoP decreased to nearly 0 V% H2O. Fig. 4B represents the GMWP over to the baking time. After starting the baking process and injecting steam, an almost
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Fig. 3. The upper sound curve demonstrates the original sound level and the lower sound curve demonstrates the filtered sound level (removed noise frequencies between 20 and 30 Hz), exemplary for experiment 8 = 3.255 L(H2O) m3.
immediate increase in the V% H2O occurred, as it was observed in the GMWoP-tests. The maximum GMWP at the beginning (around 2 min) of the baking process was lower than for the GMWoP. This lower maximum of GMWP depends on steam condensation on the product surface which is due to a temperature gradient between steam (approx. 100 °C) and product surface (approx. 30 °C). After a slight decay in air moisture, the absolute air humidity stabilized to a common value between 68% and 80% until opening of the chimney. These inflexion points relay on the temperature interchange between hot air and bread rolls. On the one hand the condensation of water onto the bread rolls surface is vaporised instead of emitted and on the other hand water of the dough system is emitted in the air and both contribute to a humidity increase. These effects are shown by the humidity profile for GMWP with (h) experiment 1 (baking without steam) where a humidity increase were analyzed (q.v. Fig. 3B). After opening the chimney the V% H2O falls down to a range of 20–30 V% H2O. These results prove that the products are contributing to oven humidity. At a baking time of 10 min the V% H2O of GMWP is just about 60 V% H2O higher than for GMWoP.
Table 3 shows the V% H2O during baking time which is calculated by the integration of GMWoP values. The total value of the area under the GMWoP curve (auc) increased but the differences between the tests decreased above a H2O-SA of 1.395 L(H2O) m3 (experiment 4). These effects are related on the total saturation of air with water vapour. When the saturation point is reached the percent humidity of the air decreases constantly due to the ‘‘open system’’. 3.2. Effect of percent humidity of the air (auc GMWP) on the bread rolls quality parameters 3.2.1. Bread rolls volume expansion Rising of dough during baking is based on CO2 production and the expansion of gas contained in the cells of the fermented dough (especially CO2) (Lucas et al., 2007). In detail, yeast will continue CO2 production during the first minutes until its interaction temperature of 55 °C is reached. Further temperature increase up to 65 °C leads to gas cell expansion caused by CO2 and including H2O vaporisation mainly. The so called oven rise corresponds to a volume increase of the bread rolls which is almost linear to time
1 Fig. 4. Humidity profile for (A) GMWoP in VH2O V 1 baking room (%) and (B) GMWP in VH2O V baking room (%) by different H2O-SA in relation to the baking time of 15 min (after 13 min the take-off was opened). All measurements show the mean of three experiments. h experiment 1, j experiment 2, } experiment 3, experiment 4, s experiment 5, d experiment 6, 4 experiment 7, N experiment 8.
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Table 3 Auc of the V% H2O during baking time for GMWoP and GMWP in relation to the different experimental number respectively H2O-SA. The results are shown as mean value of sample size = 3, with standard deviation. Experimental number
H2O-SA (L(H2O) m3)
Auc GMWoP; V H2O during time (% min)
Auc GMWP; V H2O during time (% min)
1 2 3 4 5 6 7 8
0.000 0.465 0.930 1.392 1.850 2.325 2.790 3.255
30.8 ± 0.5 243.9 ± 4.6 373.6 ± 9.6 437.5 ± 6.1 447.5 ± 5.5 479.5 ± 1.5 490.8 ± 1.9 495.7 ± 6.0
517.2 ± 9.0 661.9 ± 14.0 810.3 ± 16.7 913.9 ± 10.5 969.1 ± 2.8 1006.3 ± 7.7 1081.0 ± 18.7 1286.5 ± 23.1
Fig. 5. Bread rolls volume depending on the different auc GMWP (from experiment 1–8). The results are shown as mean value of sample size = 30, with standard deviation.
during the first baking step (Fan et al., 1999; Lucas et al., 2007; Zhang et al., 2007). Both brought forward by steaming. During steam condensation on the product surface energy is transferred to the bread rolls which also mediates volume increase. To find out the relation between the volume of the bread rolls and the different auc GMWP the total bread rolls volume was measured after baking. Fig. 5 shows a distinct increase in bread rolls volume until experiment 3 with a moisture content of approximately 810% min. The total volume of the bread rolls for the following experiments features almost the same range. Baking without steam (517 % min) in comparison to experiment 3 (810% min) reveals a volume increase by nearly 20%. Tearing of the crust was observed for low steaming. With regard to Table 4 it can be seen that the final bread rolls volume (310.6 ± 4.4 mL) can already be achieved by the use of only 0.930 L(H2O) m3. The enthalpy of condensation transferred from the vapour to bread rolls surface is adequate for the oven rise. Additionally, the bread rolls surface is thus flexible enough to undergo the bread rolls volume expansion.
3.2.2. Colour detection on the bread rolls surface Steaming is also relevant for the surface appearance of bread rolls which includes colour and lightness. Fig. 6 shows that the lightness increases if auc GMWP increase. Besides that, Fig. 6 presents the colour change based on L⁄ (lightness), a⁄ (red–green) and b⁄ (yellow–blue) by the different auc GMWP on the bread rolls surface. The bread rolls surface becomes lighter and the colour changes by increasing auc GMWP. This statement is assisted by Ahrné et al. (2007) who reported that crust colour depends on baking temperature and humidity. On the one hand an increasing of humidity blocks the direct temperature transmission to the product. So the crust temperature during baking is lower and the product colour is lighter. On the other hand with the humidity during the baking process, structural changes (especially in the crust) take place (Ahrné et al., 2007). For example the starch of the crust is degrading to dextrin, mono- and disaccharides (Belitz and Schieberle, 2001). The most important structural changes bear on the changing of the dextrin’s and melanoidins’ constitution. Melanoidins (brown-coloured polymers) commonly exist in the bread curst and arise out of the Maillard reaction (Borrelli et al., 2003). 3.2.3. Crust thickness measuring Table 4 shows the increase in crust thickness in dependence on auc GMWP increase. This rise in crust thickness depends on the energy transmission by steam. As presented in Table 3 an increase in percent humidity of the air is closely connected with an increase in auc GMWP. The standard deviation decreases by increasing auc GMWP. This effect depends on consistent heat distribution on the bread rolls surface due to steam condensation on the bread rolls surface. Mohd Jusoh et al. (2009) approved these correlations between lightness and crust thickness of bread. The heat transfer at the condensation-front is complex. By steaming the crust temperature and colour change decrease (q.v. Fig. 6). It is expected that steam increases the water content in the crust surface (due to a temperature gradient between steam (approx. 100 °C) and product surface (approx. 30 °C) at the beginning of baking) – shown at the lower maximum of GMWP against GMWoP (q.v. Fig. 4) – resulting in better heat conduction compared to a dry surface. The higher energy transfer is based on the fact that the heat transmission coefficient of water and steam may be higher than the heat transmission coefficient of air (Chemieingenieurwesen, 2006). 3.2.4. Acoustic and compression-force detection Former publications dealt with product composites in connection to the product crispness and hardness (Primo-Martín et al., 2009; Salvador et al., 2009). To visualise product changes due to the percent humidity of the air, crispness sound was used. This method was used to evaluate differences on the crispness of bread crust in dependence on the auc GMWP. On the one hand the bread rolls crispness depends on crust structure and on the other hand on crumb properties. The sound and compression-force, needed to compress the bread rolls by 70% and the resulting sound level was measured.
Table 4 Relationship between bread rolls quality parameters and the real time humidity (auc GMWP) of experiment 1–8. The results are shown as mean value of sample size = 3, with standard deviation. Auc GMWP (% min) H2O-SA (L(H2O) m3) Volume (mL) Lightness (-) Colour change (-) Crust thickness (mm) Max. force (N) Mean force (N)
517.3 0.000 246.3 ± 0.9 60.0 ± 1.9 53.5 ± 0.5 1.1 ± 1.0 17.7 ± 0.9 14.8 ± 2.0
661.9 0.465 279.4 ± 8.0 62.3 ± 2.1 50.9 ± 1.1 1.6 ± 0.8 22.5 ± 1.7 18.9 ± 0.7
810.3 0.930 310.6 ± 4.4 61.9 ± 2.1 51.2 ± 0.4 2.5 ± 0.7 25.4 ± 2.1 21.1 ± 1.4
914.0 1.392 313.1 ± 4.4 64.0 ± 1.6 49.2 ± 1.6 2.9 ± 0.5 28.6 ± 1.7 22.9 ± 2.0
969.2 1.850 304.7 ± 0.4 64.8 ± 1.4 48.1 ± 0.4 3.4 ± 0.2 28.0 ± 3.7 23.5 ± 1.3
1006.4 2.325 310.2 ± 7.3 66.1 ± 1.4 47.1 ± 1.1 3.9 ± 0.3 30.8 ± 3.1 24.2 ± 1.6
1081.1 2.790 317.5 ± 8.8 66.3 ± 1.6 46.9 ± 0.8 4.2 ± 0.3 32.0 ± 3.1 25.5 ± 1.5
1268.5 3.255 305.6 ± 4.4 67.0 ± 2.0 46.2 ± 0.7 4.6 ± 0.5 33.9 ± 2.0 26.6 ± 1.2
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Fig. 6. j Colour formation () and } lightness () depending on the auc GMWP from experiment 1–8. The results are shown as mean value of sample size = 60. Significant (p < 0.001) linear correlation of colour formation r = 0.954 and the lightness r = 0.954.
As an example curve Fig. 7 shows compression-force and the sound in relation to the compression rate by reference to experiment 8. This force-sound-distance-diagram was obtained during the fracturing process of bread rolls. The sound curve shows multiple peaks of varying amplitude which reveal the presence of a brittle cellular structure (Vincent, 1998). Unto a certain limit the applied uniaxial mechanical energy is dissipated. Crust fracture occurs after exceeding the limit whereas excess energy is emitted as sound (Vincent et al., 1991; Luyten et al., 2004). During compression the curves present two main regions where the crust breaks, the pre-creasing point and the breaking point. At the pre-cracking point little curst cracks occur and low acoustic level is emitted. This could be explained by an incipiently fracture of the crust break (the upper area of the bread rolls). Along with breaking sounds maxima in braking force could be detected at the same points. Incipiently fracture causes force development to pause shortly and to increase afterwards unto final breaking point. There the real crust deformation begins and the compression-force stayed constant. The most intensive acoustic signal emerged during breaking
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point. At this point the pressure of the circular-shape-plate and the advanced compression was already enough to crack the crust at all. After total break the compression-force increases again which is not represented in the calculations. At lower auc GMWP curve progression is similar to the one shown in Fig. 7, but with different compression-force and sound values. The different auc GMWP has great effect on crust crispness and hardness. The effect on the crust hardness is shown in Table 4. Maximum compression-forces as well as the mean compressionforces increase by a rise of auc GMWP. These effects depend on the same physical properties as seen for crust thickness: constant heat distribution on the bread rolls surface by increased auc GMWP and the condensation on the bread rolls surface. Thus a higher energy transfer occurs. The crispness of bread rolls could be described by the sound level. Fig. 8 shows the maximum sound level and the auc sound level depending on the auc GMWP. With increasing total percent humidity of the air during baking maximum sound significantly increases (p < 0.01) (r = 0.842). Until an auc GMWP of 810% min a high slope in the maximum sound was exhibited. Similar to the volume the crust crispness is very high for the first tests. By further increased auc GMWP structural crust changes are much smaller as in the lower auc GMWP. Fig. 9 demonstrates the highly significant (p < 0.001) linear correlations between the maximum force and the maximum sound (r = 0.930) as it was expected due to the results found in literature (Primo-Martín et al., 2008). In contrast Fig. 8 reveals that the area under the sound level curve (auc) has a polynomial characteristic in relation to auc GMWP (r = 0.975). Owing to increased steam injection and thus higher energy transfer crust thickness could have gained. Highest auc sound level was achieved at approximately 914% min where the energy transfer was sufficient to build up a perfect crust-thickness (around 3.0 mm) and therefore crispness. Beyond the maximum at 914% min the crust structure cannot be developed sufficiently due to excessive humidity in the oven. From the maximum sound at 77 dB up to 1286% min the maximum sound increase tends to stagnate. This decrease depends on the crust growth which is revealed
Fig. 7. d Compression-force (N), – sound level (dB) detection in relation to the distance for a compression process at 70% of the bread rolls, exemplary for experiment 8. At pre-creasing point (PCP) some small crust breaks take place. At breaking point (BP) the basic crust deformation begins. Between the two vertical lines the relevant values of the analysis are shown.
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Fig. 8. } Maximum sound level (dB) and j auc sound level during time (dB min) depending on the auc GMWP from experiment 1–8 obtained by 70% compression of the bread rolls. The results are shown as mean value of sample size = 24. Significant (p < 0.001) linear correlation max – r = 0.842 and polynomial correlation auc sound r = 0.975.
Fig. 9. Correlation between max. force (N) and max. sound level (dB) depending on experiment 1–8 obtained by 70% compression of the bread rolls. The results are shown as mean value of sample size = 24. Significant (p < 0.001) linear correlation r = 0.883.
in Table 4 and relies on crust thickness. Until the sound level optimum a crispiness increase is detected. During further crust formation the crispness sound decreases and excites only strong single break sounds. 3.3. Correlations between H2O-SA, percent humidity of the air and bread rolls quality parameters Having examined humidity course during baking (auc GMWP) and effects on the bread rolls properties by using different steam amounts analyses of correlations between both were made to find out the interdependence (Table 5). Table 5 Correlation matrix between H2O-SA, measured humidity during baking time and the bread rolls crust parameters. In all cases high significant (p < 0.001) linear correlations (r) were found. H2OSA
colour change
Auc GMWP 0.979 0.954 H2O-SA 0.968 Colour change Crust thickness Lightness Max force
crust thickness
Lightness Max force
Mean force
0.984 0.991 0.966
0.952 0.970 0.998
0.968 0.949 0.958
0.973 0.953 0.966
0.964
0.969
0.974
0.957
0.958 0.989
As shown in Figs. 5 and 8 no linear relationship between the auc GMWP and bread rolls volume as well as the auc sound level was found. But poorly significant (p < 0.05) linear relationship between the auc GMWP and the maximum sound level (r = 0.842) was found. In all other cases high significant (p < 0.001) linear correlations were detected. As a result high correlations are shown between the auc GMWP, the mean (r = 0.973)/max (r = 0.968) force obtained by 70% compression of the bread rolls and the crust thickness (r = 0.984). These correlations depend on the increase in crust thickness (Table 4) which is corroborated by the correlations of crust thickness and mean (r = 0.974)/max (r = 0.969) compression-force. Thus, crust parameters depend on percent humidity of the air during baking. Higher heat and mass transfer due to increased percent humidity of the air during baking causes thicker crust formation and higher compression-force are to be applied. A model for the crust formation during baking was already presented by (Jefferson et al., 2007) which were used from Jefferson et al. (2006) to show that raising the vaporisation temperature gives a rise to a thicker crust. In the experiments high percent humidity of the air means an increase of the vaporisation temperatures additional with higher energy transfer into the bread rolls (Jefferson et al., 2006). This is based on the fact that the heat transmission coefficient of steam and humid air is higher than for dry air. Additionally, correlations between auc GMWP and the lightness (r = 0.952) as well as a negative relationship with the colour change (r = 0.958) were detected. Colour change correlated negatively (r = 0.966) with crust thickness as it was also reported by Jusho et al. (2009). They also confirmed a strong positive correlation between both, crust thickness and colour change, by increasing baking temperature. As shown in Table 5, correlations between H2O-SA and product quality are in the same range like those for auc GMWP and the product quality. This is indicated by the high significant (p < 0.001) linear correlation (r = 0.979) between H2O-SA and auc GMWP. These data reveal that the product quality can either be monitored by injected steam amount (H2O-SA) or total resulting humidity (auc GMWP) which is additionally due to evaporated water of baking goods.
4. Conclusion In general time and temperature are used as control parameters during the baking process. Steam amount, thus humidity level in the baking chamber was introduced as a further parameter to analyse the influence on the end product quality. For judging the quality of bread rolls the volume of the final product and their crust properties were used as key parameters. During the baking process, it was analysed that the baking goods themselves contribute essentially to the humidity in the oven. Further, water condensation on the bread roll surface and the product water release during baking were shown by real time humidity measurement. Nearly the same product water output could be observed in all experiments. Thus, it can be proven that humidity is a relevant factor at the beginning of the baking process. By increasing the steam amount and consequently the auc GMWoP several bread roll properties, like the bread roll volume, crust lightness, colour change, crust thickness, firmness and the sound level were positively affected. It is known that the formation of a stable crust is one of the most important factors of the baking process. Therefore special methods were used to quantify the crust thickness as well as the compression-force and the crispness. Without a stable crust the product is not able to maintain its shape. Additional the crust is very important for the flavour of bread rolls (Purlis and Salvadori, 2007; Mohd Jusoh et al., 2009; Vanin et al.,
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2009). It can be seen that by increasing the auc GMWoP, the crust thickness, the compression-forces and the maxima sound level increased. Moreover by increasing the auc GMWoP the auc sound level increased up to a humidity amount of 913% min. At this point the sound level stagnated and finally decreased. The experiments showed that a humidity amount of approximately 925% min is adequate to receive a maximal volume and crispiness. The study also demonstrates that the steam amount has a significant influence on the properties of the end product. The new approach of the real time humidity measurement shows high interdependency between product quality and percent humidity of the air. Furthermore the product quality can be affected by injected steam amount (H2O-SA) or total resulting percent humidity of the air (auc GMWP). In summary, an inline monitoring tool like the used high humidity measuring system provides an opportunity to control the baking process by reducing humidity level up to the lowest still processible value, which allows to save energy and to provide products of good quality. With regard to these first correlation further work is necessary to determine and to analyse the heat transition process by humidity independent of the product. Acknowledgements This research project was supported by the German Ministry of Economics and Technology (via AiF) and the FEI (Forschungskreis der Ernährungsindustrie e.V., Bonn). Project AiF 15659N. References Ahrné, L., Andersson, C.-G., Floberg, P., Rosén, J., Lingnert, H., 2007. Effect of crust temperature and water content on acrylamide formation during baking of white bread: steam and falling temperature baking. LWT – Food Science and Technology 40 (10), 1708–1715. Borrelli, R.C., Mennella, C., Barba, F., Russo, M., Russo, G.L., Krome, K., Erbersdobler, H.F., Faist, V., Fogliano, V., 2003. Characterization of coloured compounds obtained by enzymatic extraction of bakery products. Food and Chemical Toxicology 41 (10), 1367–1374. Chemieingenieurwesen, V.-G.V.u., 2006. VDI-Wärmeatlas. Springer Verlag, p. 10. Fan, J., Mitchell, J.R., Blanshard, J.M.V., 1999. A model for the oven rise of dough during baking. Journal of Food Engineering 41 (2), 69–77. Belitz, H.-D., Schieberle, P., 2001. Lehrbuch der Lebensmittelchemie, p. 5. Hussein, W.B., Hussein, M.A., Becker, T., 2010. Detection of the red palm weevil using its bioacoustics features. Journal of Bioacoustics 19 (3), 177–194. Jefferson, D.R., Lacey, A.A., Sadd, P.A., 2006. Understanding crust formation during baking. Journal of Food Engineering 75 (4), 515–521. Jefferson, D.R., Lacey, A.A., Sadd, P.A., 2007. Crust density in bread baking: mathematical modelling and numerical solutions. Applied Mathematical Modelling 31 (2), 209–225.
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