Effect of extrusion process on properties of cooked, fresh egg pasta

Journal of Food Engineering 92 (2009) 70–77

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Effect of extrusion process on properties of cooked, fresh egg pasta Stefano Zardetto a,*, Marco Dalla Rosa b a b

Quality Assurance, Research and Development Department VOLTAN SPA, Via Dosa 24, 30300 Olmo di Martellago (VE), Italy Dipartimento di Scienze degli Alimenti, Alma Mater Studiorum Università di Bologna, Piazza Goidanich, 60-47023 Cesena (FC), Italy

a r t i c l e

i n f o

Article history: Received 13 May 2008 Received in revised form 20 October 2008 Accepted 21 October 2008 Available online 5 November 2008 Keywords: Pasta Extrusion Near infrared NIR

a b s t r a c t The objective of this study was to evaluate the chemical and physical characteristics of cooked fresh egg pasta samples obtained using two different production methodologies: Extrusion and lamination. The samples of fresh egg pasta were produced in an industrial plant and subjected to the different lamination processes. The obtained pasta samples were then pasteurized and cooked in water. For each type of sample colour, cooking behaviour, texture, furosine content and pasta surface characteristic were evaluated. Besides, the two kinds of products were analyse using Fourier transform near-infrared (FT-NIR) spectroscopy. The extrude pasta were tougher than the sheet-rolled pasta, absorbed more water during the cooking and released more total organic matter (TOM) in the rinsing water. The colour difference between the two type of pasta after the heat treatment of pasteurization was reduced after the cooking, due to water absorption, and two samples showed to be more similar. The results obtained show that extrusion process led to a higher furosine content than sheet rolled processes. FT-NIR analysis suggests they have different matrix–water associations, different degrees of starch gelatinization, and also different surface structure characteristics. More differences between the two types of pasta were reduced by cooking, rendering them more similar and this result has been confirmed by sensory analysis. In fact under our experimental conditions extruded pasta was not discriminated from sheet rolled pasta by most of the sensory panelists (less than 29%). Ó 2008 Elsevier Ltd. All rights reserved.

1. Introduction In the industrial preparation of fresh pasta, the product can be subjected to one of two different lamination processes after leaving the kneading machine: sheet rolling or extrusion. Although both types of product are produced commercially, few scientific data on the differences between them are available. Some data for dry pasta suggest that the extrusion process causes the formation of a protein matrix with numerous discontinuities (Pagani et al., 1989), and the qualities that result in the best sheet-rolled pasta have been identified (Pagani et al., 1989). In this product, the gluten network is more developed (Matsuo et al., 1978; Dexter et al., 1979), and it is altogether of better quality than that of extruded pasta. In our previous work, we demonstrated that the two types of pasta have different characteristics in terms of colour and the degree of gelatinization, whereas no differences were demonstrated in their cooking qualities (Zardetto and Dalla Rosa, 2006). Furthermore, the products can be discriminated using Fourier transform near-infrared (FT-NIR) spectroscopy. A principal components anal* Corresponding author. Tel.: +39 041 546421; fax: +39 041 5464294. E-mail address: [email protected] (S. Zardetto). 0260-8774/$ - see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.jfoodeng.2008.10.027

ysis (PCA) approach was also used to detect the differences between extruded and sheet-rolled pasta. The rate for the correct classification of the mode of pasta preparation was 100%. NMR analysis has also demonstrated that sheet-rolled pasta is different from extruded pasta. The NMR and FT-NIR results suggest the presence of differing matrix–water associations, diverse levels of starch gelatinization, and distinct starch–gluten interactions in the two kinds of pasteurized samples (Zardetto et al., 2005). In order to better investigate if the two lamination techniques influence consumer sensorial perception, on the basis of previous results, we studied the effects of lamination technology on pasta structure by NIR spectroscopy and sensorial perception by sensorial analysis. Chemical and physical analysis on uncooked and cooked pasta were performed. Furthermore, in order to characterise the surface functionality of pasta in relation to the sauce keeping ability an objective method was developed.

2. Materials and methods The samples were produced on the industrial production line described in our previous work (Zardetto and Dalla Rosa, 2006). The fresh pasta was obtained by mixing durum wheat semolina

S. Zardetto, M. Dalla Rosa / Journal of Food Engineering 92 (2009) 70–77

(76% w/w; 12 ± 1% w/w protein dry mass [dm]), pasteurized fresh egg (19% w/w), and water (5% w/w). Its composition was: moisture 31.5 ± 0.5%; protein 13.29 ± 0.14%; ash 1.01 ± 0.007%; and ether extract 3.76 ± 0.21%. The pasta was formed into a sheet in one or other of the following processes. (1) Extrusion was by continuous press (model K500, Monferrato, Asti, Italy), with a bronze die with circular punctures of 19 cm diameter and 2.5 cm breadth, using a partial vacuum (300 mmHg). The sheets were passed through the press until they reached the sheet-rolling stage, at the end of which the thickness of the product was 0.90 mm. (2) Lamination was performed where the pasta was rolled with four steel cylinders to form a sheet of thickness 1 cm, then passed to a second cylinder (with a cylinder diameter of 20 cm and rotation speed of 3.5 rpm), to produce a sheet with a thickness of 0.90 mm. After the formation process, the pasta sheets were pasteurized under the same temperature and time conditions (99 ± 1 °C for 3 , corresponding to an F 10 70 value of 700) by conveying the product through a 9 m long chamber with steam circulation and a working pressure of 9120 Pa. 2.1. Determination of sample colour Sample colour was measured using a Chromameter-2 Reflectance (Minolta, Osaka, Japan). The colour differences were recorded as CIELab L* (lightness), a* (redness–greenness), and b* (yellowness–blueness) values. The colorimeter was standardized with a white standard plate (X = 82.62; Y = 84.9; Z = 100.11). Four readings were made for each sample by serially rotating the dish 90° and taking readings at each position. To obtain a better correlation between the visual and colorimetric differences, the colorimetric difference (DE) for each sample was obtained using the following equation:

DE  ¼

qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi  ðDL Þ2 þ ðDa Þ2 þ ðDb Þ2 :

ð1Þ

2.2. Cooking behaviour Circular pasta sheet samples that had been cooked for 4 min were used to calculate the water absorption, using a previously described method (Zardetto et al., 2002). About 30 g of pasta (initial moisture 30 ± 0.5%) was placed in 500 ml of tap water (hardness of 40 °f, pH 7.1, total dissolved solids, TDS, 280 mg/l), in an approximately 1:10 pasta/water ratio. After it had been cooked for 4 min, the whole pasta sample was removed, drained, and weighed after 5 min. The results are expressed as grams of water absorbed per gram of pasta (g/g pasta).

based on washing the drained pasta with 500 ml of water at room temperature to remove the substance coating the surface of pasta cooked for 4 min. An aliquot of the washing water is evaporated at 80 °C. The organic matter in the residue is determined by titration with ferrous ammonium sulfate in an excess of potassium dichromate. The chemical method is from D’Egidio et al. (1976). The results are expressed as grams of starch obtained from 100 g of pasta, as follows:

  20 TOMðg=100gpastaÞ ¼ ðB  SÞ   Fd  0:00347; B

2.4. Pasta surface characteristics The different surface characteristics of the two types of pasta were investigated for their ability to hold sauce during consumption. The test was performed using pasta cut into circles with a 45 mm radius and 1 mm thickness, for a total surface area of 127 cm2 (about 8 g of pasta). The samples were cooked for 4 min in tap water with a hardness of 40 °f, pH 7.1, and 280 mg/l total dissolved solid. After they had been cooked, the samples were immersed perpendicularly for 30 s in tomato sauce at 50 °C (dry matter 5.7/100 g and sodium chloride 0.32/100 g, 1:100 pasta/sauce ratio, viscosity to 2.600 MPa). The viscosity of the tomato sauce at this temperature was measured with a Brookfield instrument using an rpm–torque equal to 20 rpm. The samples were removed and drained for 30 s without moving them; they were then weighed. Under these conditions, the total sauce that remained on the surfaces of the two samples depended on frictional force. The influence of the frictional force is expressed in the form of a frictional factor (f). The total force (F) due to friction is a function of the pasta surface area (A), kinetic energy (KE), and the friction factor

F ¼ AqðKEÞf :

MLW  100; DP  TDS

ð4Þ

The only force to vary under our conditions was the surface roughness. In fact, the other parameters (viscosity, area, and kinetic energy) were the same for the two samples. We expressed the results obtained for sauce quantity (SQ) that remained on the product in milligrams per square area of pasta. In the calculation, we subtracted the increase in the cooked weight resulting from water absorption from the final weight of the samples

SQðmg=cm2 Þ ¼

MLðg=100gdmÞ ¼

ð3Þ

where B = ferrous ammonium sulfate used for the blank (ml), S = ferrous ammonium sulfate used for the sample (ml), Fd = dilution factor, and 0.00347 is the factor calculated for the transformation of glucose into starch, correcting for the incomplete oxidation of starch (97.25%).

2.3. Matter loss and total organic matter (TOM) The matter loss of the pasta during cooking was evaluated as previously described (Zardetto et al., 2002). The measured matter loss was calculated, taking into consideration the different moisture levels observed for the two types of pasta and the dry matter in the tap water, as follows:

71

ðW c  WAÞ  WS ; 127

ð5Þ

where Wc = weight of the cooked pasta samples after immersion in tomato sauce, WA = increase in the cooked weight, and WS = weight of the pasta samples before cooking. 2.5. FT-NIR spectroscopy

ð2Þ

where ML = matter loss (g/100 g dm), MLW = matter lost in water (g/500 ml), DP = dry pasta weight (g), and TDS = total dissolved solids (g/l). The results, expressed as grams of matter lost/100 g pasta dry matter, represent the averages of 10 determinations, measured in the rinsing water from four different cooking tests. Total organic matter (TOM) is the amount of organic matter released from cooked pasta during exhaustive rinsing. The method is

Circular pasta sheet samples (diameter 90 mm) were placed in Petri dishes after cooking, and were analysed directly by FT-NIR. The pasta samples were cooled under ambient conditions (25 ± 2 °C; relative humidity 85 ± 5%) before they were placed in the Petri dishes. The NIR spectra were recorded using an NIRLab N-200 spectrometer (FT-NIR, Büchi Labortechnik, Switzerland) in the reflectance mode. Spectra were recorded using an ISI ring cup. Data

S. Zardetto, M. Dalla Rosa / Journal of Food Engineering 92 (2009) 70–77

were recorded at 1000–2500 nm at 2 nm intervals, and were saved with three scans for each sample. The measurement and chemometric interpretation of the NIR spectral data were performed using NIRCal 4.21 chemometric software (Büchi). The data obtained were elaborated across an analysis of the principal components (PCA). The spectra were pre-treated using as functions the second normalization by closure and the first derivative BCAP (Buhler Chemical Analytic Package). The number of factors for the PCA calibrations was determined using the minimum prediction residual error sum of squares (PRESS) value. 2.6. Furosine The furosine content (mg/100 g of protein) was determined with the method reported by Resmini et al. (1990). 2.7. Texture analysis Texture analysis was performed with a Texture Analyzer TAXT2i (Stable Micro Systems Ltd., Godalming, UK) using a 25 kg load cell. A noodle tensile ring was used, and based on the results of preliminary trials, the texture parameters were set to a test speed of 3 mm/s and a trigger force of 0.05 N. The pasta was cut with a noodle blade (8 mm  300 mm) and clamped at the ends by rolling instruments. This design ensures that the sample is not split or cut during the test and that the break occurs along the extended part of the sample. At least eight replicates were performed for each sample. A probe was used to determine the maximum extensibility before the sample broke. The results are expressed by three different parameters: break load, break strain, and modulus. Break load (in MPa) is the maximum load applied to the sample shortly before it breaks. The results are expressed in N by area (MPa). Break strain (%) is the ratio between the maximum extensibility and the initial sample length. The modulus (in MPa) is calculated from the linear part of the tensile curve as the ratio between the tensile stress and the relative deformation. To obtain a good estimate of the overall type of pasta texture, measurements were made on four samples for each type of pasta, before and after cooking. 2.8. Sensory evaluation To determine whether a perceptible difference exists between the two pasta samples, the triangle test was used. The test was conducted in accordance with UNI 11073:2003. The statistical analysis was based on the tacit assumption that only the a-risk matters. This risk is the probability of concluding that a perceptible difference exists when one does not. The b-risk is the probability of concluding that no perceptible difference exists when one does exist. The number of panellists was determined by examining when the a-risk equalled 0.05, the b-risk equalled 0.05, and the proportion of distinguishers (pd) equalled 40% (Meilgaard et al., 1999). The criteria for the recruitment of the participants were that they regularly ate fresh pasta, had no food allergies (especially to eggs), and were available and willing to participate on the test day. The samples were identified with three-digit code numbers and were served in a polyethylene plastic dish in random order. All six possible combinations (ABB, BAA, AAB, BBA, ABA, and BAB) were prepared and presented to the subject in each session. The test was conducted in an environmentally controlled sensory laboratory with partitioned booths, illuminated with two blue incandescent bulbs. The chambers were free from environmental elements that could distort normal perception (UNI ISO 8589).

The samples were prepared before testing and kept at room temperature until they were served. They were cooked for 4 min in tap water (hardness of 40 °f and pH 7.1). 3. Results and discussion 3.1. Colour data Fig. 1 shows the difference in colour, DE, between the extruded and sheet-rolled pastas following the heat treatment and cooking processes. The data show that the differences were greater after the heat treatment but less pronounced after the product had been cooked. The same figure shows the changes in colour following the heat treatments and cooking compared with those of a non-pasteurized sample. As reported in our previous work (Zardetto and Dalla Rosa, 2006), the difference in the heat-treated sample is significantly greater for the extruded pasta than for the sheet-rolled pasta, whereas the cooking process caused a greater difference in the non-pasteurized pasta sample than in the sheet-rolled pasta. The difference between these two types of pasta was not significant in the cooked samples because cooking caused greater variability in the extruded pasta. Fresh pasta colour depends not only by the colour characteristics of the raw material (durum wheat and eggs), but also on the method of processing. In fact, the effects of the extrusion process on L*, a*, and b* resulted in a different colour of the final product. The changes in this colour parameter were not the same for the two types of pasta studied. The change of colour of the extruded pasta owing to the heat treatment was more evident than in sheet-rolled pasta probably due to the higher presence of components coming from depolymerisation of macro components able to develop to Maillard reaction. This causes a colour difference between the products that is easily perceptible by the consumer at the time of purchase. This factor is very important for fresh egg pasta, where product colour is strongly associated with egg content. After cooking, due to water absorption the difference between the two samples were more similar. 3.2. Texture analysis Table 1 shows the results of tensile tests carried out both before and after cooking the extruded pasta and the sheet-rolled pasta.

16 Extruded pasta

14

Sheet-rolled pasta

12

Delta ECIE LAB

72

10 8 6 4 2 0

NP

P

C

Fig. 1. Colour differences (DE; average ± SD) between extruded and sheet-rolled pastas before and after heat treatment and cooking. NP, non-pasteurized pasta; P, pasteurized pasta; C, cooked pasta.

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S. Zardetto, M. Dalla Rosa / Journal of Food Engineering 92 (2009) 70–77 Table 1 Mechanical property (average ± SD) for extruded and sheet-rolled samples before and after cooking. Sample

Extruded pasta Sheet-rolled pasta a,b

Raw pasta

Cooked pasta

Break load (MPa)

Break strain (%)

Modulus (MPa)

Break load (MPa)

Break strain (%)

Modulus (MPa)

0.283 ± 0.04a 0.184 ± 0.02b

31.3 ± 8.0a 65.2 ± 9.2b

1.25 ± 0.22a 1.08 ± 0.48a

0.131 ± 0.01a 0.104 ± 0.008b

299 ± 48a 258 ± 11a

0.158 ± 0.03a 0.130 ± 0.01a

Averages with different letters indicate significant differences (P < 0.05) between the samples.

The break load (expressed in MPa), as an index of pasta toughness, was significantly different in the two kinds of pastas before and after cooking. The extruded pasta samples were tougher than the sheet-rolled pasta. Alamprese et al. (2005) reported that, for fresh lasagne, this toughness was attributable to the formation of a more compact protein network, which offered greater resistance to the application of tensile force. These results do not agree with those of Pagani et al. (1989) for dried pasta. The extrusion process causes breakage of the protein matrix, and, as a result, the product does not have a compact and continuous protein network. Rebello and Schaich (1999) studied the effects of extrusion on wheat flour proteins and reported the fragmentation and cross-linking of these proteins, with the production of new materials of low and high molecular weights. The processing conditions used by these authors were not the same as those used in the pasta process, but it is reasonable to assume that the extrusion process weakens the protein matrix, thereby influencing the microstructural properties of the pasta. Our NMR observations are consistent with this conclusion. In fact, in our previous work (Zardetto et al., 2005), we observed a stronger relationship between the water and the matrix in the extruded pasta than that in the sheet-rolled pasta, even when there was no difference in water activity. We hypothesize that a partially broken protein matrix and the production of new material in the extrusion process cause a greater affinity between the water and the matrix. The load value was always higher for the extruded pasta than for the sheet-rolled pasta. Alamprese et al. (2005) reported that this value depends on the intensity of the heat treatment and increases when the heat treatment is more severe. In our experiment, the pasta samples were submitted to the same heat treatment and any differences observed are therefore not attributable to the pasteurization process. The break strain (expressed in %) was significantly higher for the extruded pasta (65.2 ± 9.25%) than for the sheet-rolled pasta (31.3 ± 8.00%) before cooking. This index showed a significant (P < 0.05) increase with cooking, but in this case, the difference between the samples of each group (cooked extruded pasta and cooked sheet-rolled pasta) was not significant. Cooking increased the modulus value for both samples. Cooking the pasta resulted in less toughness and more hardness, and a significant increase in the extensibility of both samples. Moreover, the differences between the two types of pasta were reduced by cooking, rendering them more similar. 3.3. Cooking behaviour The data related to cooking behaviour, matter loss, and TOM for all the samples of fresh egg pasta analysed are shown in Table 2. The cooking behaviour, evaluated in terms of the increase in pasta weight, differed between the two types of samples. While in our previous work we used distiller water during pasta cooking and we did not found any differences between the pasta sample obtained by two lamination processes in this work we used tap water (water data previous reported in material and methods) and using this tape of cooking medium we were able to discrimi-

Table 2 Cooking behaviour and sauce-binding test (average ± SD) for extruded and sheetrolled samples. Sample

Extruded pasta Sheet-rolled pasta

Cooking behaviour

SQ

Weight increase (g/g)

Matter loss (g/100 g dm)

TOM (g/100 g dm)

Total sauce bound (mg/cm2)

0.704 ± 0.051a

1.42 ± 0.20a 0.570 ± 0.037a 6.90 ± 0.217a

0.619 ± 0.015b

1.28 ± 0.22a 0.487 ± 0.048b 6.71 ± 0.97b

a,b

Averages with different letters indicate significant differences (P < 0.05) between the samples.

nated the two type of pasta. In particular extrusion samples increase the water absorption during the cooking more than sheet rolled pasta. In relation to the effect of the tap of water D’Egidio et al. (1981) reported that the distilled water is unable to distinguish pasta products in terms of their quality, whereas tap water is very efficient in doing so. Several workers have show that, with increase water hardness cooked pasta has higher stickiness values (Dexter et al., 1983), higher total organic matters in the rinse and cooking water (D’Egidio et al. 1981) and higher cooking losses (Malcolmson and Matsuo, 1993). According we those author this behaviour it was mainly due to the higher pH and higher calcium–magnesium ions content of tap water compared to distiller water. As reported by Chung et al. (1978) and Feillet (1984) the water pH seem to influencing the electrostatic interactions between the proteins and gelatinized starch and a weakly acid water (approximately pH 6.0) favors this interactions, preventing the leaching of starch into the cooking medium and determine an artificial starch–protein matrix quality. In fact, the weight increase during cooking is an index of the starch–protein matrix quality, which is used in studies of pasta. During pasta cooking, the protein network limits the diffusion of water and limits the swelling of the starch granules in the central zone of the pasta (Fardet et al., 1998). The lack of a continuous protein network causes high hydration of the starch material, together with an increase in the weight of the pasta. Table 2 reports the matter lost in the rinsing water. The average value for sheet-rolled pasta, 1.28/100 g dm, is lower than that measured for extruded pasta, 1.42/100 g dm, although these data are not significantly different. The average value differs from that previously reported for fresh sheet-rolled pasta samples of 1.1/ 100 g dm (Zardetto et al., 2002) because in previous work we use distiller water. The matter loss data were analysed for different productive days to calculate the difference between the average values. Extruded pasta released in the rinsing water 0.243/100 g dm (standard deviation 0.036, n = 5) of matter more than sheet-rolled pasta. The TOM test was developed to estimate the stickiness of dried pasta after cooking. This method closely predicts the stickiness of cooked pasta because it has been observed that higher firmness is generally associated with less stickiness, because of the better molecular structure of the starch–protein network on the pasta

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S. Zardetto, M. Dalla Rosa / Journal of Food Engineering 92 (2009) 70–77

surface. Therefore, the less material lost during cooking, the better the pasta quality (Cubadda et al., 2007). No published data are available for fresh pasta evaluated with the TOM test. The average TOM value for the extruded pasta (0.57/100 g dm) was higher than the average value for the sheet-rolled pasta (0.487/100 g dm). However, the values obtained were both lower than those observed for dry pasta of good quality (less than 1.4/ 100 g, as reported by Massini et al., 1998). Because no published data are available, it is difficult to use such values as a reference for fresh pasta quality. There was a good correlation (r2 = 0.85) for both samples between matter loss and TOM (data not shown), and these data agree with those reported earlier by D’Egidio et al. (1976) for dry pasta. In this research the extruded pasta sample absorbed more water during the cooking, release more substance and more total organic matter in the rising water then sheet rolled pasta. Fardet et al. (1998) showed that during pasta cooking, the protein network limits the diffusion of water and limits the swelling of the starch granules in the central zone of the pasta. The presence in the extruded pasta of lack in the continuous protein network causes during pasta cooking high hydration of the starch material with an increase in the weight of the pasta, matter loss and total organic matter in the rinsing water. Moreover, the shear effect of extrusion processes could be determine a depolymerisation of the pasta starch with production of water soluble molecule with higher leaching of organic matter into the cooking medium. The literature contains no information about the relationship between weight increase and other cooking parameters in fresh pasta. Therefore, we pooled all the cooking data according to the production date, for the extruded and sheet-rolled pasta samples examined in the current study, and calculated simple correlation coefficients between weight increase and the other qualities of cooking. Weight increase had a strong positive correlation only with matter loss. Interestingly, the relationship between the two parameters did not seem to follow the same trend in the two types of pasta (Fig. 5). In the extruded pasta, an increase in the cooked weight correlated with an increase in matter loss, whereas in the sheet-rolled pasta, the two parameters were inversely correlated. From the premise that the two pasta samples have different structural matrices, we can infer the relationship between the increase in weight and matter loss. The decreased matter loss in the sheet-rolled pasta accompanied by a weight increase after cooking may be attributable to the presence of a protein network that traps starch granules. Therefore, rolled pasta achieves better product hydration without increased matter loss in boiling water. However, extruded pasta exhibits the opposite behaviour because it lacks a continuous protein phase. More research is required to understand this difference in the behaviour of the two types of pasta.

from different structural behaviour. This difference can be identified by measuring the total sauce binding to the pasta surface. 3.5. FT-NIR spectroscopy The same approach used in our previous work was used here to detect the differences between the extruded and the sheet-rolled pasta. The accuracy of the classification models was assessed based on the number of false positive and false negative results produced by each. A false positive result occurs when a sample is wrongly identified as belonging to a specific class; conversely, a false negative result occurs when a sample that does belong to a class is not classified as such. A total of 42 samples were considered during the randomized calibration procedure. Thirty samples were assigned to the calibration set and the remaining 12 samples constituted the validation set. The percentage of samples in which the cooking pasta model was correctly classified was 100% with this method. The scatter plots of principal component 1 (PC1) vs. PC2 of the 90 NIR spectra for uncooked pasta used in our previous work (Zardetto and Dalla Rosa, 2006) and of the 42 NIR spectra for cooked pasta are shown in Fig. 2. Our objective was to investigate the difference between not only the two types of laminated pasta, but also the differences between these pastas before and after cooking. NIR clearly separates the population samples into four groups based on their different structural characteristics. PC1 is the component that better separates the uncooked pasta from the cooked pasta for both pasta types. Fig. 3 shows the two loading factors for the extruded and sheet-rolled samples.

0.15 0.1 0.05 0

PC2

-0.05 -0.1

Sheet-rolled

-0.15

Extruded -0.2 -0.25 -0.13

-0.03

0.07

PC1

Fig. 2. Score plot of extruded and sheet-rolled pasta samples on PCA loadings 1 and 2.

70

1.5

3.4. Surface pasta characteristics

50

1

30

Loading PC1

To obtain a good estimate of SQ, measurements were made on five samples of each type of pasta produced on different days, and five replicates were performed for each sample. Under our conditions, the extruded pasta bound more sauce than did the sheet-rolled pasta (Table 2). The increase in weight was probably exclusively attributable to the superficial dough characteristics because of the short sauce-immersion time used (30 s) and our experimental conditions. The surface pasta characteristics are mainly the result of the starch that remains after cooking (stickiness) or the physical characteristics of the surface (the degree of smoothness). No correlations were observed under our conditions between matter loss and SQ or between TOM and SQ (data not shown). Thus, the different processes of lamination seem to produce different surface characteristics, probably resulting

Sheet-rolled cooked Extruded cooked

0.5 10 0 1000

1500

2000

-0.5

2500 -10 -30

-1

-50 -70

-1.5

Wavelength (nm) Fig. 3. PCA loading 2 for cooked samples (blue line sheet-rolled pasta; pink line extruded pasta).

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S. Zardetto, M. Dalla Rosa / Journal of Food Engineering 92 (2009) 70–77 Table 3 Summary of spectral features and correlations.

Extruded pasta Sheet-rolled pasta

1139

1326 1326

1139 Decrease

1382

1410 1410

1687 1880

0.1

1880 1934

The NIR spectra of the cooked pasta are highly dominated by the water signal. Compared with the pasta that had not been cooked, the fully hydrated samples have much higher baselines. The major water peaks, found at 1410 and 1934 nm, increase with cooking. The peak at 1139 may also be ascribed to water, although Sirieix and Downey (1993) reported that the absorbance at 1160 in a wheat flour product corresponded to a C@O stretch in gluten. Table 3 compares the key spectral features of the factor loadings difference plot for each of the pastas studied. As can be seen from the table, the cooking processes for the two samples did not cause the same variations in the NIR spectra, indicating the possibility that two different matrices are involved. The wavelengths around 1326, 1410, and 1880 are common to both samples studied. In the extruded pasta, cooking caused an increase in the spectral absorbance at 1139, 1326, 1410, and 1382 nm, and a decrease at 1687 and 1880 nm. In the sheet-rolled pasta, the absorbance values increase at wavelengths of 1326, 1410, and 1880 nm, and only decreased at 1934 nm. The peaks located at 1139, 1382, and 1687 nm may be associated with protein vibration. These peaks mainly characterize modifications related to gluten bonds, whereas absorption at 1410, 1880, and 1934 nm can be assigned to water or water–starch bonding. We previously found a strong correlation between the degree of gelatinization in fresh pasta and absorption peaks at 1410 and 1880 nm (Zardetto, 2004). The absorption peak at 1410 nm can be attributed to the vibration of the OAH bond. In this case, the chemical effect of gelatinization is related to an increase in the depolymerization of starch molecules, with a consequent increase in the number of free OAH bonds. In the cooked extruded pasta, the modifications are principally attributed to the protein network, whereas in the cooked sheetrolled pasta, the changes involve the different states of water and water bound to starch. This result confirmed that extruded pasta does not show a continuous protein network, and that during cooking there is a crosslinking of the fragmented proteins obtained during the extrusion process. The degree of starch gelatinization was higher in the extruded pasta than in the sheet-rolled pasta, and the swelling and gelatinization of starch during cooking might be less important in the extruded pasta (starch gelatinisation data have been reported in previous work, Zardetto and Dalla Rosa 2006). In the sheet-rolled pasta, the protein network was not broken and could entrap starch granules. However, the physical constraints of the matrix may have limited the swelling of the starch granules and the leaching of material into the cooking water. Because the fresh pasta does not experience a drying-temperature effect (which causes starch transformation and protein coagulation) and the cooking time is not as long as it is for dried pasta, the processes of starch swelling and gelatinization in this product, might be more important than the process of protein coagulation. The loading plot (Fig. 4), within certain limits of the PC1 (which, however, represents the more significant component in the classification points), shows that the difference between the two types of cooked pasta is predominantly influenced by the spectral zone relative to the first band combination of water (1880 nm), OH stretching in water (1934 nm), CAH stretching overtone in gluten (1687 nm), and the ANH bond of protein (1382 nm).

Loading PC1

Increase

1382

0.2

Wavelength, nm (correlation sign)

1326

0

1500

1000

2000

2500

-0.1

1410 -0.2 -0.3

1880

-0.4

Wavelength (nm) Fig. 4. PCA loading 1 for cooked samples.

1.6

1.7 1.6

1.5

Matter loss (g/100g dm)

Sample

0.3

1.5 1.4

1.4

y = -1.36904+3.90102x r 2 =0.83

1.3 1.3 1.2 1.2

1.1 1

1.1 0.9

y =10.3602-14.6124x

r 2 =0.94

0.8

1 0.6

0.65

0.7

0.75

0.8

Weight increase (g/g) Fig. 5. Linear correlation plot of matter loss for the extruded pasta (s) and the sheet-rolled pasta (D) samples vs. weight increase.

By comparing the results for uncooked pasta obtained in our previous work, we see that the spectral region around 2000 nm is not important for separating the two types of pasta (extruded and sheet-rolled pasta) in the cooked samples, but is so in the uncooked samples (Zardetto and Dalla Rosa, 2006). In fact, uncooked pasta samples also show a high correlation at 1400, 1894, and 1870 nm. However, in these samples, other spectral regions made positive contributions (1997 and 2258 nm). Structural molecular dates obtained by NIR generally confirmed the results published by other authors the investigated pasta structure using other analytical approaches (scanning electronic microscopy, rheological test) (Pagani et al.,1989; Alamprese et al., 2005; Matsuo et al., 1978). 3.6. Sensory evaluation We conducted a 40-respondent triangle test according to an established test protocol (UNI 11073:2003). The sensory booths were prepared with blue light to mask colour differences. Twelve panelists were scheduled for each of three sessions, and four panelists were scheduled for the fourth and final session. Of the 40 respondents, 14 correctly picked the extruded pasta. The critical number of correct responses required in a triangle test with 40 respondents and a = 0.05 is 20. Therefore, a total of only 14 correct responses indicate, with 99% confidence, that the proportion of the population who can perceive a difference is less than 29%. However, the conditions used did not allow the panelists to evaluate two parameters: the appearance (above all, the colour) and SQ (produced without the panellist’s desired seasoning). As previously shown, both of these parameters result in significant differences

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Table 4 Furosine values (average ± SD) for extruded and sheet-rolled samples before cooking. Sample

Furosine (mg/100 g protein)

NP pasta Extruded pasta Sheet-rolled pasta

9.86 ± 1.3a 12.71 ± 1.4b 10.96 ± 1.2a

NP, non-pasteurized pasta. a,b Averages with different letters indicate significant differences (P < 0.05) between the samples.

between the two pasta types (extruded and sheet-rolled pasta), and they could significantly influence the acceptability of the two products, thereby modifying the results obtained in the sensory analysis. 3.7. Furosine Furosine levels were determined as an index of heat damage in the different products. The furosine values measured for the two types of pasta are reported in Table 4. The content of furosine in the dough before heat treatment was 9.86 mg/100 g of protein. This value is less than the previously reported range of 11–19 mg/100 g of protein in fresh egg pasta (Zardetto et al., 2003). After heat treatment, the dough samples had levels of furosine of 10–13 mg/ g of protein. The extruded pasta samples had 12.71 mg furosine per 100 g of protein. In these samples, the value was significantly higher than that for the sheet-rolled pasta. Because these samples were produced in the same manner and with the same components, the detected values might be attributable to the different lamination processes. The two most important factors relating to the difference in furosine values between the two types of pasta (extruded and sheet-rolled pasta) are probably water content and matrix modification by the extrusion process. As in extrusion cooking, pasta extrusion leads to the fragmentation of starch (Lintas and D’Appollonia, 1973) and the fragmentation of wheat flour proteins (Rebello and Schaich, 1999). As reported in our previous work (Zardetto and Dalla Rosa, 2006), the specific mechanical energy (SME) transferred to the product under extrusion operating conditions was between 50 and 65 kJ/kg under the operating conditions used. This value is extremely low compared with that applied by a twin screw extrusion cooker (300–900 kJ/kg), but it is similar to the SME necessary for kneading processes, of about 40 kJ/kg (Axford et al., 1963). The intensity of the Maillard reaction (and thus the furosine content) for equal reagent concentrations is also controlled by the water content of the product. Pagani et al. (1995) have pointed out that at temperatures above 75 °C, the key parameter is the moisture of the pasta. The Maillard reaction has more effect at low moisture levels. Heat treatment causes a significant increase in moisture, more so for sheet-rolled pasta than for extruded pasta (Zardetto et al., 2005). Moreover, it is also possible that discontinuous matrix proteins and the presence of broken protein fibrils facilitate heat penetration into the matrix, changing the apparent thermal coefficient. 4. Conclusion In our previous work (Zardetto and Dalla Rosa, 2006), we demonstrated that the two analysed processes (extrusion and sheet rolling) influence some pasta characteristics. In addition the investigation reported in this paper has shown that extruded pasta absorbed more water during the cooking, released more substance and more total organic matter in the rinsing water then sheet

rolled pasta. The difference behaviour were probably due to two different extrusion processes effects: the formation of lack in the continuous protein network and the shear effect with a degradation of the pasta starch. For both type of pasta cooking behaviour were different that we obtained in our previous works were we used distiller water. These findings confirm that tap water to be permit a better discrimination between pasta samples. The degradation of the macro components during extrusion processes was probably the reason of different furosine content after the heat treatment in the two type of pasta. In fact, the extruded pasta presents a furosine value higher than sheet roller pasta. The difference was probably due to the formation of components coming able to contribute to Maillard reaction. In our condition extruded pasta seem to have a different degree of surface smoothness that increase the total sauce fastened on the product. The two lamination type determines some difference on pasta texture: the break load it was only rheological index significant different in the two type of pasta before and after the cooking. It is an index of pasta toughness and in the extruded pasta was higher than sheet rolled pasta. The cooking processes reduced the differences between the two type of pasta rendering them more similar. NIR analysis confirmed a difference in the matrix structures of the two pasta types. In fact, the changes in their spectra involved different wavelengths. The extruded pasta differs from the sheetrolled pasta in its water–matrix interactions and the coagulation of the protein network. PCA loading revealed that the difference involves NAH bonds, H bonds between the wheat components and water molecules, CH bonds, and the C@O stretch in wheat gluten. In extruded pasta, cooking causes an increase in the number of bonds among proteins, whereas in the sheet-rolled pasta, cooking increases the amount of water bounds within the matrix. However, the differences in the structural properties of the two pasta, do not cause a strong sensory difference and are probably not perceived by most consumers. References Alamprese, C., Iametti, S., Rossi, M., Bergonzi, D., 2005. Role of pasteurization heat treatment on rheological and protein structural characteristics of fresh egg pasta. European Food Research Technology 221, 759–767. Axford, D.W.E., Chamberlain, N., Collin, T.H., Elton, G.A.H., 1963. Continuos breadmaking-The Chorleywood process. Cereal Science Today 8, 265–268. Chung, O.K., Pomeranz, Y., Finney, K.F., 1978. Wheat flour lipids in bread making. Cereal Chemistry 55, 598–599. Cubadda, R.E., Carcea, M., Marconi, E., Trivisonno, M.C., 2007. Influence of gluten proteins and drying temperature on the cooking quality of durum wheat pasta. Cereal Chemistry 84, 48–55. D’Egidio, M.G., De Stefanis, E., Fortini, S., Galterio, G., Sgrulletta, D., 1981. Quality of spaghetti cooked in different kinds of water. Tecnica Molitoria 32, 505–511. D’Egidio, M.G., Sgrulletta, D., Mariani, B.M., Galterio, G., De Stefanis, E., Fortini, S., 1976. Quantitative evaluation of stickiness and spaghetti quality. Tecnica Molitoria 27, 89–93. Dexter, JE., Matsuo, RR., Dronzek, BL., 1979. A scanning electron microscopy study of Japanese noodles. Cereal Chemistry 56, 202–208. Dexter, JE., Matsuo, RR., Morgan, BC., 1983. Spaghetti stickiness: some factors influencing stickiness and relationship to other cooking quality characteristics. Journal Food Science 48, 1545–1559. Fardet, A., Baldwin, P.M., Bertrand, D., Bouchet, B., Gallant, D.J., Barry, J., 1998. Textural images analysis of pasta protein network to determine influence of technological processes. Cereal Chemistry 75, 699–704. Feillet, P., 1984. The biochemical basis of pasta cooking quality- Its consequences for durum wheat breeders. Science Aliments 4, 551–555. Lintas, C., D’Appollonia, B.D., 1973. Effect of spaghetti processing on semolina carbohydrates. Cereal Chemistry 50, 563–570. Malcolmson, L.J., Matsuo, R.R., 1993. Effects of cooking water composition on stickiness and cooking loss of spaghetti. Cereal Chemistry 70, 272–275. Massini, R., De Pilli, T., Di Fabio, G., 1998. Selection and training of an expert panel for the objective sensory evaluation of dry pasta. Tecnica Molitoria 1, 13–22. Matsuo, RR., Dexter, JE., Dronzeek, BL., 1978. Scanning electron microscopy study of spaghetti processing. Cereal Chemistry 55, 744–753. Meilgaard, M., Civile, G.V., Carr, T.B., 1999. Sensory Evaluation Techniques. CRC Press, USA.

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