Mathematical approach to assessing spelt cultivars ( Triticum aestivum subsp . spelt ) for pasta making
Descrição do Produto
International Journal of Food Science and Technology 2013, 48, 195–203
195
Original article Mathematical approach to assessing spelt cultivars (Triticum aestivum subsp. spelt) for pasta making Jelena Filipovic´,1,* Lato Pezo,2 Nada Filipovic´,3 Vladimir Filipovic´,3 Marija Bodrozˇa-Solarov1 & Miroslav Plancˇak4 1 2 3 4
Institute for Food Technology in Novi Sad, Bul. cara Lazara 1, 21000, Novi Sad, Serbia Institute of General and Physical Chemistry, University of Belgrade, Studentski Trg 12–16, 11000, Beograd, Serbia Faculty of Technology, University of Novi Sad, Bul. cara Lazara 1, 21000, Novi Sad, Serbia Novi Sad Fair, Quality Appraisal Department, Hajduk Veljkova 11, 21000, Novi Sad, Serbia (Received 7 June 2012; Accepted in revised form 14 July 2012)
Summary
This study investigates dough rheology of three wholemeal spelt flours cultivars and influence of egg quantity (0–248 g kg1) on the technological and sensory quality of wholemeal pasta. Standard scores (SS), based on assigning equal weight to applied parameters (rheological, chemical, technological and colour), has been calculated and the obtained values compared. Correlation coefficients of SS with alveograph data for P, L, G and W are 0.99, 0.98, 0.99 and 0.91, respectively, and warm pasta stability and retrogradation of starch correlated to SS at level 0.99. For PCA modelling, two 9 9 15 data matrices were divided into different rheological or integrated chemical, technological quality and colour evaluation methods data sets. Standard scores analysis points out that owing to its good rheology, pasta made by cultivar Austria has the best technological quality in relation to the technological quality of the other two cultivars (Nirvana and Eko).
Keywords
Pasta, quality, rheology, spelt, wholemeal.
Introduction
Spelt wheat (Triticum aestivum subsp. spelt) is an old European crop. That is a low input plant, suitable for growing without the use of pesticides in harsh ecological conditions and in marginal areas of cultivation. Spelt is currently grown mainly for use in organic foods because of the fact that primitive wheat species are more disease resistant and can produce healthier foods. Therefore, spelt was found to perform well under suboptimal growing conditions and to utilise better nutrients when grown in a low-input system. In comparison with Tr. aestivum, the nutritive value of spelt wholemeal flour is more highly appreciated because of the characteristics of the aleuronic layer (Bonafaccia et al., 2000; Bojanska & Francˇakova, 2002; Abdel-Aal et al., 2008). The dynamic way of living has the tendency to simplify and decrease the way of preparing healthy and organic meals. In organic food production, spelt wheat is a raw material suitable for products of altered nutritional characteristics compared to conventional wheat *Correspondent: E-mail: jelena.filipovic@fins.uns.ac.rs
products (Marconi et al., 2002; Olivera & Salvadori, 2006; Abdel-Aal et al., 2008). Pasta is a traditional food product dating back to the first century. Nowadays, it is commonly eaten not only in the Mediterranean, but also in all European countries and the US, as well in the Far East. The pasta is made by mixing semolina, tail maid flour or wholemeal flour with water. Pasta with preferable physical and sensory quality is characterised by strength and elasticity in the dough form, high tensile strength in dried form, minimum cooking loss, minimum stickiness and reasonable firmness after cooking. Pasta has an ease of transportation, cooking and storing properties. Nutritional situation in most industrialised countries is characterised by high energy density, little fibre and insufficient minerals and vitamins. In many countries during the last two decades, the consumption of food such as pasta has noticeably increased. Nutritionists recommend that in daily diet the greatest share should be of cereal products, particularly fibre-rich foods that help launching health and wellness trends. Therefore, bakery and pasta products would be suitable food for a diet correction. (Agnesi, 1996; Tudorica˘ et al., 2002; Mariangela De et al., 2007; Brennan & Tudorica,
doi:10.1111/j.1365-2621.2012.03177.x © 2012 The Authors. International Journal of Food Science and Technology © 2012 Institute of Food Science and Technology
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2008; Marco & Rosell, 2008; Filipovic´ & Filipovic´, 2010; Brandy et al., 2011; Jayasena & Nasar-Abbas, 2012). This study presents the rheology properties of three wholemeal spelt cultivars (Nirvana, Austria and Eco), as well as the technological and sensory characteristics of wholemeal spelt pasta, with the main goal to evaluate the effects of Mixolab and alveograph indicators best contribute to the pasta quality. Principal component analysis was applied to express the interrelation between the technological quality of wholemeal spelt and egg quantity. Standard scores for rheology characteristics and integrated pasta characteristics (chemical, technological quality and colour) were calculated and the corresponding score plot drawn.
Table 1 Mixolab parameters used in modified Chopin + protocol
Material and methods
(equivalent to 0, 3 or 6 eggs, respectively). Hydrated wholemeal entered an extrusion worm that moved the loose dough forward and simultaneously compress it into a homogeneous plastic mass prior to extrusion through a die with 1.4 mm diameter used for spaghetti. Mixing time was 15 min (Kaluerski & Filipovic´, 1998). Raw pasta was dried in a cabinet drier at controlled temperature that did not exceed 45 °C until pasta reached the moisture around 12.5%. Drying conditions and air flow were stringently controlled to avoid the creating of a discontinuity in the moisture gradient between the interior and exterior of spaghetti.
Wholemeal samples
Three spelt cultivars – Nirvana – cultivar 1, Austria – cultivar 2 and Eco 10 – cultivar 3, (particle size of wholemeal flours ranged between 200 and 300 lm) representing the average quality from producing areas grown in the years 2010–2011 in Serbia were used. Dough rheology
Dough rheology investigations were performed by Mixolab (Chopin, Tripette et Renaud, Paris, France), which simultaneously determines dough characteristics during the process of mixing at constant temperature, as well as during the period of constant heating and cooling. The required amount of flour for analysis was calculated by Mixolab software according to the input values of flour mixtures moisture, as well as water absorption (ICC STANDARD No. 173, 2006). All the measurements were performed using the modified Mixolab ‘Chopin’ protocol which parameters are presented in Table 1. The viscoelastic behaviour was also determined by the alveograph test, using an Alveograph (ChopinAlveograph) following the standard method (AACC, 1994). The monitored parameters were the deformation energy (W), tenacity of resistance to extension (P), dough extensibility (L), extensibility (G) and curve configuration ratio (P/L ratio). Preparation of pasta
Pasta was made using the device ‘La Parmigiana D45’ MAC 60. In a paddle mixer, wholemeal moisture was adjusted to 31.5% by adding water or water and liquid eggs. Liquid eggs were first mixed into a homogeneous mass. Based on wholemeal flour, applied quantity of eggs was 0, 124 or 248 g kg1
International Journal of Food Science and Technology 2012
Settings
Values
Mixing speed Dough weight Tank temperature Temperature 1st step Duration 1st step 1st temperature gradient Temperature 2nd sep Duration 2nd step 2nd temperature gradient Temperature 3rd step Duration 3rd step Total analysis time
80 rpm 90 g 30 °C 30 °C 8 min 15 mine 4 °C per min 90 °C 7 min 10 min4 °C per min 50 °C 5 min 45 min
Pasta quality
Quality of pasta was evaluated in terms of colour and cooking characteristics (water uptake, volume increase, cooking loss and stickiness). The method was described by Kaluerski & Filipovic´ (1998). Stickiness was evaluated by numeric scores 0–10 by a panel of trained panellists. High scores were allocated to pasta with smooth, non-sticky surface. Pasta colour
The absorbance of pasta colour (L*-brightness, a*-share of red colour if positive value and green colour if negative value, b*- share of yellow colour if positive value and blue colour if negative value, C*-differences in colouration, h - differences in tone, dominant wavelength) was measured by objectively tristimulus photo colorimeter MOM Colour 100. The colours were analysed in the CIELAB system (Pribisˇ , 1980). Chemical analyses
Basic chemical analyses – protein, starch, fat and reducing sugars of pasta spelt – were defined according
© 2012 The Authors International Journal of Food Science and Technology © 2012 Institute of Food Science and Technology
Spelt cultivars for pasta making J. Filipovic´ et al.
to an approved method cited by Kaluerski & Filipovic´, 1998; Nitrogen was determined by Kjeldahl method (979.09) (AOAC, 1990) and converted to protein using factor of 5.75. Statistical analyses
Descriptive statistical analyses for all the obtained results were expressed as the mean ± standard deviation (SD). Furthermore, the evaluation of one-way ANOVA and PCA analyses of the obtained results were performed using Microsoft Excel software, 2007. Collected data were subjected to one-way analysis of variance (ANOVA) for the comparison of means, and significant differences are calculated according to Turkey’s HSD test at P < 0.05 level. Data were reported as means ± standard deviations. To get a more complex observation of the ranking of spelt wheat pasta quality, standard scores (SS) were evaluated using statistical approach by integrating the measured values generated from different rheological, chemical and technological quality and colour evaluation methods. Furthermore, principal component analysis (PCA) has been applied successfully to classify and discriminate the different cultivars of spelt wheat pasta. Pattern recognition technique was applied within results descriptors to characterise and differentiate all varieties of spelt wheat pasta. Determination of SS
Central tendency was the most widely used technique to compare various characteristics of complex food samples determined using multiple measurements (Sun & Tanumihardjo, 2007), where samples were ranked based on the ratio of mean value and standard deviation of the measurement used. As the units and the scale of the data from various rheological, chemical and technological quality and colour evaluation methods were different, the data in each data set should be transformed into standard scores, dimensionless quantity derived by subtracting the mean from the raw data divided by the standard deviation, according to the following equation: Standardscore ¼ ðx lÞ=r
ð1Þ
where x represents the raw data, l the mean and r the standard deviation. The standard scores of a sample for different measurements when averaged give a single unitless value termed as SS, which was a specific combination of data from different measuring methods with no unit limitation and no variance among methods. This approach also enables the ease of employing some other sets of pasta formulations to this elaboration.
Two standard scores were calculated for (i) rheological characteristics and (ii) for integrated chemical and technological quality and colour evaluation methods, and the corresponding score plot was drawn. Also, standard score for integrated chemical and technological quality and colour evaluation methods for pasta formulations of 0, 3 and 6 eggs and a bar graph was drawn. Results and discussion
Rheology of wholemeal spelt flour
The alveograph characteristics of three different wholemeal flour of spelt varieties dough are presented in Table 2. ANOVA and the following Turkey’s HSD test were evaluated for comparison of rheological parameters, and statistically significant differences were found in resistance to deformation for all the samples. Dough resistance to deformation or tenacity (P value) is an indicator of the dough’s ability to retain. The measured range for cultivar 1 is 75 ± 2 mm, in contrast to 105 ± 3 mm gained with cultivar 2. The resistance to deformation of cultivar 3 is 55 ± 2 mm, indicating that it may be a good tool in differentiating the quality of spelt as a raw material for pasta. Statistically significant differences are found while measuring dough extensibility among all the three samples of pasta and deformation energy. The extensibility of dough L is a predictor of the processing characteristics of dough. Statistically significant differences are found while measuring dough extensibility among all the three samples of pasta for cultivars 1, 2 and 3, respectively, and deformation energy depended on the spelt cultivar. The value of extensibility G for cultivar 3 is statistically different from both cultivars 1 and 2. The resulting effect on P and L became evident in the P/L ratio value, which provides information about the elastic resistance and extensibility balance of dough. The values of P/L are relatively uniform in cultivars and do not contribute to differentiating various spelt wholemeal flours. Most Mixolab measurements are statistically different among spelt wheat pasta formulations, dough development for cultivars 1, 2 and 3 respectively, dough stability, speed of weakening protein network because of warming, torsion maximum and speed of starch gelatinisation, which indicates that they are significantly influenced by different spelt cultivars, indicating again that these measurements positively contribute to determining tail made flour for pasta. Cultivar 3 has the lowest value for the speed of gelatinisation of starch. That is, the rate of enzymatic degradation that indicates the increased amylase activity and leads to the decreased stability of pasta (Table 2). Water absorption and dough elasticity of
© 2012 The Authors International Journal of Food Science and Technology © 2012 Institute of Food Science and Technology
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Table 2 Rheology data of wholemeal spelt flour Rheology properties Alveograph characteristics Resistance to deformation P (mm) Dough extensibility L (mm) Extensibility G Deformation energy W (10E4J) Configuration curve ratio P/L Mixolab characteristics Water absorption (%) Dough development (min) Dough elasticity (Nm) Dough stability (min) Speed of weakening protein Networks because of warming (Nm min1) Maximum torque (Nm) Speed of starch gelatinisation (Nm min1) Speed of enzymatic degradation (Nm min1) Warm paste stability (Nm) Retrogradation of starch (Nm) Standard scores ()
Cultivar 1
Cultivar 2
105 ± 3 c 29 ± 2c 12.0 ± 1.8b 120 ± 2c 3.62
75 ± 2 b 25 ± 1b 11.1 ± 1.2b 74 ± 2b 3.00 60.5 8.47 0.09 9.83
± ± ± ±
0.074 ± 1.72 ± 0.680 ± 0.048 ± 1.40 ± 2.01 ± 0.285
Cultivar 3
0.5a 0.5b 0.1a 0.8c
60.0 8.72 0.08 9.55
0.002b 0.07b 0.010c 0.009a 0.06b 0.10b
± ± ± ±
0.024 ± 1.81 ± 0.522 ± 0.041 ± 1.46 ± 2.17 ± 0.577
0.4a 0.6c 0.1a 0.6b
55 ± 18 ± 9.4 ± 40 ± 3.06
2a 1a 1.1a 1a
± ± ± ±
0.4a 0.4a 0.1a 0.5a
60.5 4.30 0.08 5.42
0.088 ± 1.57 ± 0.438 ± 0.072 ± 1.02 ± 1.65 ± 0.861
0.005a 0.06c 0.019b 0.002a 0.04b 0.19b
0.005c 0.06a 0.023a 0.010b 0.10a 0.09a
Values with the same letter are not statistically different at the P < 0.05 level (Turkey’s HSD test).
a,b,c
various pasta formulations were not found statistically significantly different and can be considered optimal for pasta needs (Marco, Rosell 2008). Cultivar 2 gained the best standard score result, mainly for its resistance to deformation, dough extensibility, value of swelling and deformation energy. Negative results gained during SS evaluation are noticed in water absorption, dough elasticity and speed of starch gelatinisation. However, both water absorption and dough elasticity measurements are very similar to cultivars 1 and 3, with mutually low SD. A strong impact on SS is noticed. Quality of wholemeal spelt pasta
Both ANOVA and Turkey’s HSD test were conducted and statistically significant differences were found in water uptake for all the samples of pasta, so it can be related to Mixolab characteristic that points at the speed of starch gelatinisation. There are statistically significant differences in the values of water uptake depending on the spelt cultivars, (which is cultivar characteristics) and there is also statistically significant difference related to the amount of added eggs. The parameter volume increases which indicates the possibility of starch swelling. It in general shows small deviation, and this parameter is in its optimal range. There is no significant statistical difference for values of volume increase of the samples with different spelt cultivars and quantity of added eggs, probably due to the egg protein network capable of entrapping the constituents of wholemeal spelt, notably starch granules
International Journal of Food Science and Technology 2012
Table 3 Quality of wholemeal spelt pasta with eggs
Cultivar 1 0 egg 3 eggs 6 eggs Cultivar 2 0 egg 3 eggs 6 eggs Cultivar 3 0 egg 3 eggs 6 eggs
Water uptake (g)
Volume increase a (%)
Cooking loss R (% dm)
Stickiness*
144.0 ± 0.1a 164.1 ± 0.2b 147.8 ± 0.2c
2.7 ± 0.1a 2.9 ± 0.1b 2.7 ± 0.1a
6.7 ± 0.1a 8.3 ± 0.1c 7.0 ± 0.1b
7.1 ± 0.3b 8.7 ± 0.5a 9.1 ± 0.4a
167.3 ± 0,2b 125.7 ± 0.2a 168.5 ± 0.2c
2.9 ± 0.1a 2.5 ± 0.1b 3.1 ± 0.2a
8.6 ± 0.1a 8.6 ± 0.2a 7.8 ± 0.1b
7.1 ± 0.6a 7.6 ± 0.5ab 8.1 ± 0.3b
153.5 ± 0.2a 157.2 ± 0.1b 185.3 ± 0.2c
2.9 ± 0.1a 2.9 ± 0.1a 3.2 ± 0.1b
7.4 ± 0.2b 7.9 ± 0.1a 8.1 ± 0.1a
5.0 ± 0.3a 7.5 ± 0.5b 8.1 ± 0.3c
a,b,c Values with the same letter are not statistically different at the P < 0.05 level (Turkey’s HSD test). *Sensor testing, minimum score is 1, maximum score is 10.
and fibres. These data are in accordance with the cooking loss. There is a significant statistical difference among values of volume increase of pasta samples made from cultivar 2 and maximum added eggs and values of pasta made from cultivars 2 and 3 with no added eggs. These data are in accordance with Mixolab concerning data on the rate of enzymatic degradation, which had the lowest value in two varieties (0.68 Nm min1) and maximum values for the stability of the hot paste (1.4 Nm) (Table 2) compared to other cultivars. Unexpected statistical differences of values of
© 2012 The Authors International Journal of Food Science and Technology © 2012 Institute of Food Science and Technology
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cooking loss of pasta samples (Table 3) for cultivars 1 and 3 are probably due to the increased activity of proteolytic enzymes that is indicated by alveograph characteristics, particularly P and W. Statistically different stickiness (Table 3) was experienced for each cultivar with different quantity of added eggs, which indicated that quantity of eggs significantly influenced stickiness, while different cultivars did not show significant difference in stickiness scores. On the whole, stickiness of pasta without added eggs could be related to Mixolab data, Table 2, related to warm pasta stability. ANOVA and Turkey’s HSD test are shown in Table 4 and, as expected, statistically significant differences were found in protein content among the values of samples with 0 eggs compared to pastas with 3 and 6 eggs. Addition of eggs in pasta technology is beneficial to the sensory quality and the biological value of the product, as well as the amount of essential amino acids. Therefore, eggs in pasta positively contribute to the amino acids balance in the diet on a daily basis, as they build and break down every day (www.atkins.com). There were no statistically significant differences in the values of starch, cellulose and sugar content of samples made of different cultivars and content of added eggs, which indicated that different cultivars and eggs do not influence these nutrients. Wholemeal spelt pasta has more indigestible fibres, particularly cellulose, which improves the colon and creates a feeling of fullness, but does not give energy. Lipid contents for all the cultivars are found to have statistically significant differences among all formulations. This indicates that the addition of eggs, owing to yolk composition, significantly affects the lipid content in the pasta and is highly appreciated as a source of monounsaturated fatty acids and x three fatty acids that are
necessary for normal functioning of the human organism (Juric´ et al., 2005). Pasta colour is the most important as it is the first quality parameter perceived by the consumer at the point of sale. Colour differences among wholemeal pasta samples are readily apparent by eye. Use of a tristimulus colorimeter permits simultaneous measurements of brightness and yellowness, the most appreciated pasta attributes. Various colour coordinates are found to have statistically different values for different pasta formulations (Table 5). Brightness coordinates are found to have statistically insignificant difference among all the three pasta formulations, probably due to the bran colour that deter its use in light-colour food. The share of red colour coordinate is found to have statistically significant difference among all the three pasta formulations for cultivars. Statistically significant differences for cultivar 2 among all pasta formulations are observed, while all pasta formulations for cultivar 3 are found to be statistically different. The share of yellow colour coordinate is found to have statistically significant difference among the cultivars with 0 eggs compared to formulations with 3 and 6 eggs. The increasing value of yellow colour in wholemeal pasta with eggs (Table 5) is the result of the pigment present in the egg yolk. These pigments are recognised as natural antioxidants that positively contribute to free radicals elimination. They are also anticarcinogenic agents that reduce serum cholesterol and thus prevent the development of cardiovascular diseases (Narahari, 2003). Statistically significant differences in tone, parameter h for cultivars 2 and 3 for all the pasta formulations are observed. Dominant wavelength is found to have statistically significant difference between cultivar 1 with six eggs compared to
Table 4 Chemical composition of wholemeal spelt pasta with eggs Content (% dm)
Cultivar 1 0 egg 3 eggs 6 eggs Cultivar 2 0 egg 3 eggs 6 eggs Cultivar 3 0 egg 3 eggs 6 eggs
Protein
Starch
Cellulose
Sugars
Lipids
19.49 ± 0.22b 21.06 ± 0.59a 21.13 ± 0.47a
56.29 ± 0.79a 55.79 ± 0.12a 55.79 ± 0.41a
2.39 ± 0.94a 2.74 ± 0.17a 1.9 ± 0.89a
4.95 ± 1.16a 4.66 ± 1.15a 4.23 ± 1.02a
1.77 ± 0.56a 2.79 ± 0.27b 4.18 ± 0.20c
18.20 ± 0.14a 19.39 ± 0.32b 20.41 ± 0.13c
56.46 ± 0.19a 55.36 ± 1.34a 55.14 ± 0.95a
2.64 ± 0.17b 2.14 ± 0.34a, 1.84 ± 0.61a
18.01 ± 0.51a 18.25 ± 0.46a 19.97 ± 0.28b
56.94 ± 0.12b 56.22 ± 0.40a 56.12 ± 0.21a
1.96 ± 0.79a 2.23 ± 1.18a 2.18 ± 0.4a
b
3.66 ± 0.10a, 3.5 ± 0.13a 3.74 ± 0.13b 3.78 ± 0.12a 4.99 ± 0.40b 3.58 ± 0.18a
b
1.34 ± 0.24a 3.13 ± 0.10b 4.91 ± 0.63c 1.39 ± 0.10a 3.02 ± 0.29b 4.44 ± 0.32c
Values with the same letter are not statistically different at the P < 0.05 level (Turkey’s HSD test).
a,b,c
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Table 5 Colour characteristics of wholemeal pasta with eggs
Cultivar 1 0 egg 3 eggs 6 eggs Cultivar 2 0 egg 3 eggs +6 eggs Cultivar 3 0 egg 3 eggs 6 eggs
L brightness
a*Share of red colour
70.69 ± 0.40a 70.15 ± 0.48a 70.90 ± 1.07a
3.88 ± 0.25a, 4.12 ± 0.30b 3.71 ± 0.28a
67.78 ± 0.73b 69.65 ± 0.17a 69.77 ± 0.58a
4.64 ± 0.10b 4.09 ± 0.12c 3.69 ± 0.13a
69.04 ± 1.09a 69.97 ± 0.66a, 70.51 ± 0.43b
b
4.41 ± 0.30b 4.37 ± 0.18a, 4.06 ± 0.16a
b
b*Share of yellow colour
C*Differences in colouration
h Difference in tone
Dominant wavelength
15.51 ± 0.47b 16.63 ± 0.38a 16.63 ± 0.19a
15.99 ± 0.50b 17.14 ± 0.43a 17.04 ± 0.16a
75.97 ± 0.59a 76.12 ± 0.71a 77.41 ± 1.02b
580.14 ± 0.19a 580.13 ± 0.22a 579.76 ± 0.29b
16.04 ± 0.30a 16.16 ± 0.14a 16.1 ± 0.13a
73.17 ± 0.70a 75.35 ± 0.43b 76.75 ± 0.39c
580.99 ± 0.20c 580.33 ± 0.13b 579.92 ± 0.11a
15.96 ± 0.48b 16.90 ± 0.26a 16.81 ± 0.30a
73.95 ± 0.65a 75.02 ± 0.41b 76.03 ± 0.49c
580.75 ± 0.21c 580.46 ± 0.14b 580.15 ± 0.15a
15.36 ± 0.34a 15.64 ± 0.14a, 15.67 ± 0.11b
b
b
15.33 ± 0.41b 16.32 ± 0.23a 16.32 ± 0.30a
Values with the same letter are not statistically different at the p < 0.05 level (Turkey’s HSD test).
a,b,c
formulations with 0 and 3 eggs pasta formulations. Statistically significant differences for both cultivars 2 and 3 are notified for all pasta formulations. SS analysis of spelt pasta quality
Standard scores is the mean value of standard score transformed from the initial data generated with different methods for each spelt wheat item. SS was calculated assigning each applied measuring parameter the equal weight. Also, by comparing the various, different characteristics methods of three commonly consumed spelt wheat (Nirvana, Austria and Eco), it is demonstrated that the SS correlated strongly with each method. The significant correlation of SS with an independent data set further confirmed that SS is a valid tool to assess spelt wheat pasta quality. The key advantage of this integrated approach is that SS is in a numerical scale with no units and has a consistent agreement with rheological, chemical and technological quality and colour evaluation methods. Although it is a relative index and may not represent a specific property of different spelt wheat pasta items, SS provides a reasonably accurate rank of spelt wheat pasta. In this article, standard scores are calculated for rheological characteristics and for integrated chemical and technological quality and colour evaluation methods for 0 eggs pasta formulation and a corresponding score plot is drawn, Fig. 1. Rheological characteristics of SS are presented on abscissa, and integrated chemical, technological quality and colour evaluation of SS are presented on ordinate axis. The first quadrant (I) stands for the high-standard rheological, chemical and technological quality and colour characteristics. Spelt wheat pasta properties positioned in this quadrant
International Journal of Food Science and Technology 2012
Integrated chemical, technological and color score
200
II quadrant
I quadrant 0.2 Rheological score
0.0 –1.0
–0.5
0.0
0.5
1.0
Cultivar 1 –0.2 III quadrant
Cultivar 2 Cultivar 3 IV quadrant
Figure 1 Standard scores analysis of wholemeal spelt pasta cultivars.
show more competitive qualities compared to pasta situated elsewhere. Spelt wheat pasta in the second quadrant (II) is attributed with negative standard score for rheological characteristic, while spelt wheat pasta in the fourth quadrant is of low chemical, technological quality and colour characteristics. Some additives or additional mechanical treatment could be used for improving pasta properties, either presented in the second or in the fourth quadrant (IV). Pasta samples located in the third quadrant (III) are those having negative scores for both rheological and integrated chemical, technological quality and colour characteristics. Additives and/or additional mechanical treatment could be adopted to reduce the negative impact of their properties on the final score. Using the standard score analysis and revealing the coordinates of different spelt pasta formulations can not only realise their position regarding other formulations, but also have a reference for developing strategies for improving their characteristics.
© 2012 The Authors International Journal of Food Science and Technology © 2012 Institute of Food Science and Technology
Spelt cultivars for pasta making J. Filipovic´ et al.
0.6 0.4 0.2
Cul.1-3 Cul.3-6 Cul.2-0 Cul.1-0
Cul.3-3
Cul.1-6
Cultivar No. –0.2
–0.6
2.5 2.0
P/L
1.5
Cultivar 2 Speed weak.
1.0
W
0.5 0.0 –0.5 –1.0
Cultivar 3
P
L Max.tor. G Speed enz. Ret. sta. Dough dev. Dough sta.
–1.5
0
–0.4
ent varieties of spelt wheat pasta formulations that give complimentary information. All varieties contain different amount of eggs as predicted by PCA score plot (Fig. 3). The full autoscaled data matrix consisting of three different varieties of spelt wheat cultivars with 0.3 and six eggs formulations are submitted to PCA. For PCA modelling, two 9 9 15 data matrix are divided into different rheological or integrated chemical, technological quality and colour evaluation methods data sets. All the samples in different categories are selected randomly. All the results are determined in spelt wheat pasta samples. The variability of results for all the parameters in nine varieties are large, so the different categories of pastas are formed according to the rheological or integrated chemical, technological quality and colour evaluation methods. For visualising the data trends and the discriminating efficiency of the used descriptors, a scatter plot of samples using the first two principal components (PCs) issued from PCA of the data matrix is obtained (Fig. 3 for rheological measurements, and Fig. 4 for integrated chemical, technological quality and colour evaluation methods). As can be seen, there is a neat separation of the nine varieties of spelt wheat pasta formulations, according to measuring methods for all rheological and integrated chemical, technological quality and colour evaluation methods. Rheological measuring results show that the first two principal components, accounting for 66.05% of the total variability, can be considered sufficient for data representation, and the first two principal components for integrated chemical, technological quality and colour evaluation methods show 100% of total variability. Protein content is the dominant variable in the first
Factor 2: 21.91%
Integrated chemical, technological and color score
The best scores are calculated for pasta with cultivar 2 (Austria), while for pasta with cultivar 1 (Nirvana), scores are also positive. Pasta with cultivar 3 (Eco) gained negative scores for rheological and integrated chemical, technological quality and colour characteristics. Standard scores for integrated chemical, technological quality and colour evaluation methods for pasta formulations with 0.3 and 6 eggs are calculated, and a bar graph is drawn, Fig. 2. As seen, the addition of eggs to spelt wheat pasta formulations strongly influences the final score result. Cultivar score increased with 3 eggs addition, but this effect is quite opposite for 6 eggs formulation. Cultivar 2 pasta scores are turned to low values when adding both, 3 and 6 eggs to the pasta formulation. Almost linear increasing of standard scores is noticed when adding 3 or 6 eggs to cultivar three pasta formulation. Stepwise regression among evaluated rheological SS and the used rheological methods revealed that most of these measurements matched SS, and that the correlations among SS and used parameters are highly significant (P < 0.05 level). The correlation analysis demonstrated that the correlation coefficients of SS with resistance to deformation, dough extensibility, extensibility and deformation energy are 0.90, 0.98, 0.99 and 0.91, respectively. Mixolab characteristics are also tested for correlation to SS, and the results were as follows: dough development gained 0.99 correlation to SS, stability dough was 0.97 correlated, maximum of torsion reached 0.98, while speed of enzymatic degradation, hot paste stability and retrogradation of starch are correlated at 0.99 level to SS. Correlation analysis is also conducted with integrated chemical, technological quality and colour evaluation methods and evaluated SS, and the results showed that protein content correlates SS at 0.91 level, while stickiness and starch content reached 0.98 correlation. The PCA allows a considerable reduction in a number of variables and the detection of structure in the relationship between measuring parameters and differ-
Cul.2-6
Cul.3-0
Speed gel.
Cultivar 1 Dough ela.
–2.5 –6
–5
–4
–3
–2
–1
0
1
2
3
4
Factor 1: 78.09%
Cul.2-3
Figure 2 Standard scores analysis wholemeal spelt pasta cultivars with 0, 3 and 6 eggs.
Wat.abs.
–2.0
Figure 3 Biplot for rheological characteristics of wholemeal spelt pasta cultivars.
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•
4 3 2
Factor 2: 17.72%
202
1
C
b Stick. Lip. Prot.
0
Cul.3-3
Cul.2-0 a Dom.wav.
PCA allows a considerable reduction in number of variables and the detection of structure in relationship between measuring parameters and different varieties of spelt pasta formulations, thus contributing to the variety of organic food with both health and wellness attributes.
Star. Cul.2-6
h L
–1
Upt.wat. Vol.inc. Loss cook. Cul.3-6 Cell. Cul.1-3
Acknowledgements
Sugar Cul.1-6
Cul.2-3
These results are part of the project supported by the Ministry of Education and Science of the Republic of Serbia, TRI 46005, TR 31055.
Cul.3-0
–2
Cul.1-0 –3
References
–4 –6
–4
–2
0
2
4
6
Factor 1: 48.33%
Figure 4 Biplot for integrated chemical, technological quality and colour evaluation methods of wholemeal spelt pasta cultivars with 0.3 and 6 eggs.
principle component, while the cooking loss R is the most dominant variable in the second principle component. Conclusion
Based on the investigation concerning the usefulness of spelt cultivars Nirvana, Austria and Eco 10 for wholemeal pasta, it can be concluded as follows: • Owing to statistically significant differences among samples and related pasta quality, alveograph and Mixolab data proved to be useful tools in characterising spelt for pasta making. • By using the standard score analysis (SS) and revealing the coordinates of different spelt pasta, the position regarding quality data and directions for the improving of their characteristics can be realised. • The significant correlation of SS with an independent data set (0.90–0.99) further confirms that this is a valid, but up to now not experienced, tool to assess spelt wheat quality, as well as its interaction with eggs. • Stepwise regression between evaluated alveograph and Mixolab data revealed that most matched SS and the correlations between SS and the used parameters are highly significant (correlation coefficients of SS with alveograph data: P, L and G are 0.99, 0.98, 0.99 and 0.91, respectively). Warm pasta stability and retrogradation of starch correlated to SS at level 0.99.
International Journal of Food Science and Technology 2012
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