Empiric rheology is considered a useful tool for assessing the technological quality of wheat. Over the decades, several tests have been adapted from common to durum wheat, and new approaches have been proposed to meet the needs of the players of the durum wheat value chain. It is here provided an overview of the strengths and weaknesses of the rheological tests currently used to evaluate the quality of durum wheat semolina.
1. Introduction
Durum wheat semolina is considered the ideal raw material to produce dry pasta; this statement is well accepted by all the players of the durum wheat value chain, from breeders to pasta-makers and consumers. This is true not only in Italy, Greece, and France—where only semolina can be used to produce dry pasta legally—but also outside of the Mediterranean area. Specifically, the suitability of semolina for pasta-making is due to the ability of the corresponding dough to withstand the numerous physical stresses occurring during processing
[1]. This property is mainly due to the quantity and quality of its protein fractions. Indeed, the combination of protein quantity and quality results in—after cooking—a continuous and coagulated protein network that surrounds the gelatinized starch granules. As described by Resmini and Pagani
[2] in the 1980s, on the basis of ultrastructure observations and confirmed in more recent years by several authors
[3][4][5], pasta is considered to be of good quality, i.e., with high firmness (i.e., the degree of resistance to the first bite) and no stickiness (i.e., the adhesion rate of pasta to tongue, teeth, palate, and/or fingers) and no or minimal bulkiness (i.e., the adhesion rate of cooked pasta strands among them), if after cooking, a three-dimensional, continuous, almost non-deformable and elastic protein network surrounds each starch granule. This optimal structure is guaranteed if proteins coagulate before starch swelling (due to the large availability of water and high temperatures), so that the starchy material will remain mostly trapped within the protein network, with negligible amylose release into the cooking water and equally limited quantities of amylopectin on the surface of pasta
[3][6].
The quality of raw materials and processing conditions are responsible for the cooking behavior of pasta. The role of drying temperature in enhancing the formation of a regular protein structure around the starch granules has been elsewhere described
[5][7][8][9][10][11].
2. Defining Gluten Quality
The amount of protein in durum wheat is the first parameter that dry pasta producers consider when choosing the raw material. According to the voluntary classification used in Italy
[12] in the field of durum wheat, semolina is classified into three classes: for the lowest quality class protein content ranges from 10.5% to 11.9%; the medium class includes samples with 12.0–13.5% protein content, while the excellent semolina quality exhibits at least 13.5% protein. A high amount of protein, in fact, is the prerequisite for a dough in which the gluten matrix is sufficiently thick and well developed even in conditions of non-optimal hydration, like those used in pasta-making (i.e., 30–32% moisture content).
Although the high protein—and consequently gluten (about 30% wet basis; >11% dry basis)—content is an important quality requirement
[7][10], this characteristic is not enough to guarantee the good cooking behavior of the corresponding pasta. Indeed, regardless the particle size and protein content, pasta made with common wheat differs in structure and/or firmness from that made with good durum wheat semolina. Moreover, Fuad and Prabhasankar
[13] stated that the use of common wheat flour in pasta-making is associated with good cooking quality when additives and optimized technologies are used. The superiority of durum wheat over common wheat is not, in fact, only related to protein content (on average two percentage points higher than common wheat), but to the composition of protein fractions. In this regard it has been shown that the suitability of durum wheat in pasta-making is related to specific combinations of alleles at the storage protein loci: glutenin alleles at low molecular weight (LMW) locus Glu-B3 and at high molecular weight (HMW) locus Glu-B1
[14]. With regard to common wheat, HMW glutenins (HMW-GS) are crucial in guaranteeing the formation of a gluten network suitable for bread-making above all for the presence of Glu-D1 locus that is absent in durum wheat
[14][15]. On the other hand, in durum wheat, the formation of a structure suitable for pasta-making is related to the high density of cross links between the shorter chains of LMW glutenins (LMW-GS)
[16].
At this point it is necessary to clarify what “suitable for pasta-making” means. Several researchers have used different terms to describe the features of durum wheat gluten that mainly affect pasta quality: strength, tenacity, and elasticity (
Table 1). All of them refer to the dough and/or gluten rheological properties, which describe the interactions between the different macromolecules that lead to the formation of the gluten network and, therefore, of the dough. The protein network developed during the mixing and kneading phase of pasta-processing is stabilized by both covalent bonds (disulfide bonds) and bonds of lower energy, such as hydrogen bonds and hydrophobic interactions between non-polar amino acid residues
[17][18][19]. The adjective “strong” is often referred to gluten characterized by high tenacity and/or strength, whereas the adjective “weak” is used to describe gluten with low tenacity and/or strength, and high extensibility.
Table 1. The main attributes used to describe the properties of gluten of durum wheat dough.
Gluten Property
|
General Definition
|
Applied to Durum Wheat Dough and Pasta
|
Viscoelasticity
|
Ability of solids to have simultaneous viscous and elastic properties
|
The determinantal characteristic of gluten, necessary for pasta-making process
|
Viscosity
|
Resistance of a liquid to flow
|
It determines in which way the dough flows through the press and the dye
|
Elasticity
|
Ability of solids to recover their initial shape after deformation
|
It allows the mass to withstand strong compression (about 10 MPa) during the extrusion phase and to assure regular shrinkage during drying (shape maintenance)
|
Extensibility
|
Maximum degree of deformation reached by solids before breakage
|
Excessive extensibility doesn’t counteract the mechanical stresses during processing
|
Tenacity
|
Resistance of dough to deformation
|
It allows the mass to resist, without breaking, the high/intense mechanical stresses (shear and stretching) occurring during the extrusion phase
|
Strength
|
Ability of solids to resist mechanical stress
|
It allows proteins to form a regular and continuous network that promotes good cooking quality
|
3. Assessing Gluten Quality
Dough is one of the most difficult materials to characterize from a rheological point of view
[20]. In fact, it exhibits viscoelastic behavior defined as plastic by Bushuk
[21], or in other words, its behavior ranges between that of an elastic solid and that of a viscous liquid. Moreover, the characteristics of dough change at each stage of the process (especially due to temperature changes occurring during pasta-making) and it is therefore difficult to predict its behavior during processing. This complexity justifies the development of so-called “empirical” rheological tests, which are widely used in the industry. In any case, as pointed out by Dobraszczyk
[20], it is essential to define, for each processing variable (humidity, temperature, pressure, etc.), the range of values applied in the step/phase that is under investigation.
Since the 1980s, several rheological tests have been proposed to characterize durum wheat semolina and to objectively describe its pasta-making performance, as summarized in Figure 1.
Figure 1. Time sequence of the rheological tests adopted in the durum wheat value chain
[7][22][23][24][25][26].
In general terms, the tests used for the rheological characterization of durum wheat can be classified according to various criteria. Some of them (i.e., Gluten Index and Glutograph® tests) directly evaluate the quality of gluten after its extraction from semolina, while others are carried out on dough (i.e., Alveograph, Mixograph, and Mixolab tests) or slurry (i.e., GlutoPeak test) systems. Some of them provide information mainly about strength (i.e., Mixograph, and Mixolab tests), others also provide details on extensibility (e.g., Alveograph) or elasticity (e.g., Glutograph® test). Some of them (i.e., Alveograph, GlutoPeak) test sample breakage, others do not (i.e., Glutograph®, Mixograph, Mixolab). Some of them are used more in Europe than in the United States or Canada, and vice versa, depending on the country of the company that produced the device. For example, the Alveograph is mostly used in European countries, whereas the Mixograph is widely used in North America
[27]. For further information, readers should see the research of Dick and Youngs
[28], Rath et al.
[29], Finney
[30], Khatkar et al.
[31], Kovacs et al.
[32], and AbuHammad et al.
[33].
The main approaches used for semolina characterization are summarized in
Table 2. From the well-known methods to the most recent, the common goal has been to respond to the needs of the operators of the supply chain who are often asked to provide, as quickly as possible, a reliable prediction of the behavior of the raw material during both the pasta-making process and cooking. In particular, breeders need to analyze in a short time a very large number of new breeding lines and released varieties, for which the quantity of material represents a limiting factor
[34]. The milling industry needs fast, simple, and reliable methods to control the quality of wheat during the reception phase, in terms of milling yield and semolina characteristics that define its commercial value. Finally, the pasta industry also needs rapid and reliable methods that determine the pasta-making ability of the semolina and predict the cooking quality of the finished product. In this context, near infrared (NIR) spectroscopy, a rapid and non-destructive technique widely used in the industry to determine moisture and protein content
[35], is becoming increasingly studied as a technique to predict some of the indices expressed by rheological tests to define the technological quality of semolina
[36][37]. Nevertheless, the NIR prediction of qualitative rheological parameters requires robust calibration models to extract information from the spectral data
[38].
Most of the tests were proposed for the common wheat sector, so they do not simulate, either by type or intensity, the stresses that arise during pasta extrusion and drying. In some cases, the method has been adapted to measure the quality of durum wheat by making some modest/small changes (e.g., resting time of the dough in the Alveograph). It follows that the information gathered from the current tests is mainly useful for classifying semolina in broad classes (excellent, good, or poor gluten quality), whereas the screening of samples within each class is still challenging. Although the limitations of such tests are well known, most of them are widely used, as a reference in the industry, to predict the pasta-making quality of durum wheat semolina
[7][10][34][39][40][41][42].
Basically, the procedures have not changed over the years, but additional data integration systems have been developed for directly processing the values of the parameters provided by the instruments. A brief description of each test will be provided in the following sections, whereas the main indices provided by each test are reported in Table 3.
Table 2. Rheological approaches used for semolina characterization.
Test
|
Principle
|
Hydration Level
|
Features
|
Standard Method
for Durum Wheat Semolina
|
Gluten Index
|
Gluten ability to pass through a sieve after centrifugation
|
not required
|
- Short time for analysis (10 min)
- Small amount of sample (10 g)
- Need to extract gluten
- Overestimation of the value in case of
low protein content samples
- Low capacity of discriminating semolina of medium quality
|
Yes [43][44]
|
Glutograph®
|
Gluten resistance to stretching
|
not required
|
- Short time for analysis (20 min, including
extraction and resting time)
- Small amount of sample (10 g)
- Need to extract gluten
- High variability
|
No
|
Alveograph
|
Dough resistance to tridimensional extension
|
≈52 g water/100 g semolina (14% moisture basis)
|
- Long time for analysis (50 min)
- Large amount of sample (250 g)
- High influence of the analyst
- Widely used in the field, especially in Europe
|
Yes [45]
|
GlutoPeak®
|
Aggregation kinetics of gluten proteins
|
≈100 g water/100 g semolina (14% moisture basis)
|
- Short time for analysis (5-10 min)
- Small amount of sample (9 or 10 g)
- Low influence of the analyst
- Few available studies
|
No
|
Mixolab
|
Dough resistance to both mechanical and thermal stress
|
≈60 g water/100 g semolina
(14% moisture basis)
|
- Long time for analysis (45 min)
- Large amount of sample (50 g)
- Low influence of the analyst
- Difficulty in following the set temperature profile
|
No
|
Table 3. Main indices provided by the rheological approaches used for semolina characterization.
Test
|
Index
|
Description
|
Type of Information
|
Gluten Index
|
Value from 0 to 100
|
Percentage of wet gluten retained in the sieve
|
Gluten strength
|
Glutograph®
|
Stretching time
|
Time to reach deflection or value after time threshold
(shear/stretch angle)
|
Gluten extensibility
|
Relaxation
|
Recovery angle after 10 s of stress removal
|
Gluten elasticity
|
Alveograph
|
P
|
Maximum pressure (mmH2O) needed to deform
the dough till breakage
|
Dough tenacity
|
L
|
Length of the curve (mm)
|
Dough extensibility
|
P/L
|
Ratio between P and L
|
Balance between dough tenacity and extensibility
|
W
|
Energy (in 10−4 J) required for dough deformation
till breakage; area under the curve
|
Dough strength
|
Ie
|
Ratio between P200 (i.e., the pressure 4 cm
from the beginning of the curve) and the value of P
|
Dough elasticity
|
GlutoPeak®
|
Maximum consistency (BEM)
|
Maximum height of the peak
|
Consistency of gluten upon aggregation
|
Peak maximum time (PMT)
|
Time required to reach the maximum height
|
Time for gluten aggregation
|
Aggregation energy
|
Area from 15 s before to 15 s after the maximum peak
|
Gluten strength
|
Total energy
|
Area from 0 s before to 15 s after the maximum peak
|
Gluten strength
|
Mixolab
|
Water absorption
|
Amount of water to add to semolina to reach
an optimal consistency of 1.10 Nm (C1)
|
The higher the value, the higher protein quantity/quality
|
Development time
|
Time needed to reach C1
|
The higher the value, the higher protein quantity/quality
|
Stability
|
Time around C1 where the torque is higher
or equal to the real value of C1–C1*11%
|
Dough resistance to mixing
|
Torque C2
|
The lowest point of the curve when the device
starts heating the dough
|
Weakening of protein
|
C1–C2
|
Difference between Torque C1 and C2
|
Gluten strength
|
Torque C3
|
The maximum torque obtained after C2 during the heating phase.
|
Starch gelatinization
|
Torque C4
|
The minimum torque after the holding period at 90°C
|
Stability during heating and mixing
|
Torque C5
|
Torque at the end of the test
|
Starch retrogradation tendency
|
P, maximum pressure; L, maximum length; P/L, pressure:length ratio; W, area under the curve; Ie, P200/P (P200: pressure at 4 cm from the beginning of the curve).
4. Relation among the Main Rheological Approaches and Relevance for Cooking Quality
Assessing the quality of gluten is an old but still relevant topic. Indeed, the selection of new lines/varieties as well as the impact of climate change on the quality of wheat crops and, consequently, on gluten quality, account for the number of studies evaluating the pasta-making potential of durum wheat samples. At the same time, several studies aimed at correlating the parameters obtained from different rheological approaches. Such studies are certainly not a pure publication exercise, but are driven by various aspects, for example:
(I) Every time a new device appears on the market, it is necessary to verify its reliability by correlating its indices with those obtained by well-established, conventional approaches;
(II) Each rheological approach provides information on a specific gluten attribute (e.g., elasticity, tenacity, extensibility, and strength); hence, the need to evaluate semolina quality by using all the available rheological tests and/or to find one approach that in the shortest possible time provides information that can be correlated to as many attributes/indices as possible.
SDS and GI are widely used among breeders to select durum wheat varieties
[46]. If a positive correlation is found between SDS and protein content, the GI appears to be relatively independent of proteins. Both SDS and GI are significantly correlated to various parameters for evaluating the rheological quality of semolina, but the most interesting correlations were observed with the Alveograph indices
[7][10][32][34]. Some authors
[47][48] pointed out that Alveograph indices do not seem to distinguish the contribution of the amount of protein from its quality. In other words, a high value for Alveograph strength (W) may be related either to the high percentage of protein or to the high quality of the protein network
[49]. This issue seems to be obviated when gluten viscoelasticity is assessed by the Glutograph test. Correlated with SDS, GI, W, and P values, the stretching value is a good indicator of gluten strength. However, analyzing extracted gluten instead of semolina dough might ’hide’ the potential role of other compounds—as well as their interactions with proteins—in defining the technological potential of semolina samples.
Among the GlutoPeak indices, the area under the curve—which takes into consideration both the peak torque and peak time—seems to be the most indicative index, since it is correlated with W index.
Although all operators in the durum wheat supply chain support the use of rheological tests for predicting the quality of cooked pasta, only a few studies showed relationships between semolina and pasta quality. As regards the GI, it is positively correlated with cooked firmness
[33]. According to Alamri et al.
[50] some Glutograph indices are positively correlated with cooking quality (i.e., stretching time versus cooking loss and firmness), whereas others exhibit a negative correlation (i.e., relaxation versus cooking loss). Alveograph indices are the most frequently related to pasta cooking behavior. In particular, the W parameter was significantly correlated with firmness tested by devices for texture analysis
[33] as well as the quality judgment expressed by a trained panel
[7][32]. Among the latest approaches, GlutoPeak test measurements of maximum torque and energy provided information on firmness, stickiness, and bulkiness of cooked pasta
[40][51].
Overall, the number of analyzed samples (generally low), differences in the characteristics of the raw materials (i.e., gluten content and quality, as well as amylose content) differences in pasta-making conditions (e.g., extrusion pressure, and drying temperature), in cooking procedures (ratio pasta:water, optimal or pre-fixed cooking time, etc.) and in methods used for cooked pasta evaluation (sensory evaluation by trained personnel or devices) among the studies might account for the difficulty in determining relationships between semolina and pasta quality.
Although numerous efforts have been made to propose rapid and reliable tests for semolina characterization, the ideal test has yet to be proposed, indicating that researchers and pasta companies need to focus on perfecting the way to assess the quality of durum wheat and pasta.
This entry is adapted from the peer-reviewed paper 10.3390/foods10122947