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Keywords:

  • flavor;
  • food structure;
  • mastication;
  • sensory perception;
  • texture

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Overview of Human Mastication
  5. Influence of Physical and Chemical Properties of Food on Oral Processing and Flavor Release
  6. Influence of Physical and Chemical Properties of Food and Oral Processing on Sensory Perception
  7. Conclusions
  8. Acknowledgments
  9. References

Abstract:  Food oral processing is not only important for the ingestion and digestion of food, but also plays an important role in the perception of texture and flavor. This overall sensory perception is dynamic and occurs during all stages of oral processing. However, the relationships between oral operations and sensory perception are not yet fully understood. This article reviews recent progress and research findings on oral food processing, with a focus on the dynamic character of sensory perception of solid foods. The reviewed studies are discussed in terms of both physiology and food properties, and cover first bite, mastication, and swallowing. Little is known about the dynamics of texture and flavor perception during mastication and the importance on overall perception. Novel approaches use time intensity and temporal dominance techniques, and these will be valuable tools for future research on the dynamics of texture and flavor perception.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Overview of Human Mastication
  5. Influence of Physical and Chemical Properties of Food on Oral Processing and Flavor Release
  6. Influence of Physical and Chemical Properties of Food and Oral Processing on Sensory Perception
  7. Conclusions
  8. Acknowledgments
  9. References

The food industry has relied mostly on incremental innovtion for its new product launches, but is becoming increasingly aware that breakthrough, “new to the world” innovations are needed to remain competitive (Business Insights 2009). The incorporation of bioactive ingredients and modification of food structure to generate novel flavor and texture sensations in products that provide consumers with unique eating experiences is increasing the importance of understanding the relationships among food structure, mastication, and sensory perception.

It is generally considered that the way food is broken down intraorally influences the perception of that food and that these perceptions vary between individuals for many reasons, including age, physiological state, and eating occasion (Braxton and others 1996; Agrawal and others 1998; Szczesniak 2002). For example, Braxton and others (1996) found tenderness perception to be related to chewing efficiency and patterns (chewing time, number of chews, and muscle activities), processes that are known to differ from person to person and among foods. Sensory perception occurs during the full duration of mastication and must therefore be understood in relation to time-dependent processes during mastication.

Some time ago, there was a call for an integrated approach to this research (for example, Lucas and others 2004; Nishinari 2004). Since then, only little progress has been made, most likely because of the complex nature of foods and the difficulty of investigating the effect of single structural attributes on mastication and sensory perception. Texture and flavor (olfaction, gustation, and trigeminal responses) are considered the 2 most important attributes in the palatability of foods (Szczesniak 1963). They are complex perceptions that require dynamic sensory methods for evaluation. This review focuses on the role of human oral processing in dynamic sensory perception, with particular emphasis on the structural properties and breakdown of solid foods.

Overview of Human Mastication

  1. Top of page
  2. Abstract
  3. Introduction
  4. Overview of Human Mastication
  5. Influence of Physical and Chemical Properties of Food on Oral Processing and Flavor Release
  6. Influence of Physical and Chemical Properties of Food and Oral Processing on Sensory Perception
  7. Conclusions
  8. Acknowledgments
  9. References

Mastication is a complex process involving rhythmical jaw movements whereby the sizes of particles in the bolus are reduced and lubrication is provided to produce a bolus suitable for swallowing. Oral processing mostly involves the upper (maxilla) and lower (mandible) jaw, the tongue and to a lesser extent the cheeks and lips (Hiiemae and others 1996). The brain stem central pattern generator (CPG) activates the motor programme, which coordinates the activities of the jaw, tongue, and facial muscles (Dellow and Lund 1971; Yamada and others 2005). Sensory feedback from different types of receptors (for example, muscle spindles of the elevator muscles, the periodontal receptors, the receptors within the temporomandibular joints, skin receptors, and taste receptors) allows the motor programme to adapt continuously throughout a chewing sequence to the properties of the bolus (Woda and others 2006).

Transport in the mouth has been divided into 3 stages (stages I to III), which are later followed by a clearance stage. Stage I transport is the preparatory phase, representing the transport from the front of the mouth to the (pre) molars and involves low amplitude simple jaw movements in which the teeth do not come into occlusion (Hiiemae and Palmer 1999). Stage II transport is the reduction phase, representing the reduction of particle size by chewing in cycles. The cycles include a closing phase, a phase when the teeth are close to full occlusion and an opening phase. In some cycles, food is only transported, involving opening and closing strokes, without occlusion (Wilkinson and others 2000). The number of chewing cycles required to prepare a bolus for swallowing is related to the bite volume and consistency of the food (Thexton and others 1980; Peyron and others 1997; Thexton and Hiiemae 1997). The tongue plays an important role during this stage, deciding whether particles are sufficiently small and moistened for swallowing or require more reduction between the molars or lubrication. The reduction in food particle sizes during mastication can be considered as the result of a selection and breakage process (Lucas and others 2002). Selection is defined as the chance of a food particle being contacted by the teeth and it depends on factors such as the total occlusal area of the postcanine teeth, tooth morphology, the relationship between antagonistic teeth, movement of the jaw, the action of the tongue and cheeks, and particle size and number. Breakage is defined as the degree of size reduction produced by the teeth when a selected particle breaks. Breakage depends on tooth morphology, the amount of co-ordination of the jaw-muscle activity (controlling the bite force and its direction), fracture characteristics of the food and particle size and shape (Olthoff and others 2007).

Stage III transport is a preswallowing phase during which the bolus is transported to the back of the tongue in preparation for swallowing (Heath and Prinz 1999). It generally lacks distinct jaw movements and the transport is mainly performed by tongue–palate interactions (Hiiemae and others 1996). Clearance or swallowing involves a pattern of tongue and highly irregular jaw movements to remove the remaining material after a mastication sequence (Hiiemae and others 1996; Heath and Prinz 1999). Once food is pressed backwards into the pharynx by the tongue, swallowing occurs by reflex (Tortora and Grabowski 1999). Swallowing is a sequential process of aggregation of food particles to form a bolus suitable for swallowing and likely depends on adhesion, friction, salivary viscosity, and surface tension (Lucas and others 2004). Prior to swallowing, a level of bolus lubrication and particle-size threshold (Feldman and others 1980) must be reached to prevent discomfort from distension of the soft tissue of the pharynx and esophagus (Prinz and Lucas 1995; Bellisle and others 2000). Yet, the conditions for the optimal state of the bolus, in terms of particle size and cohesiveness at swallowing, are not fully known (Mishellany and others 2006). In general, particle sizes of less than 2 mm are accepted for swallowing unless larger food particles are soft enough to be swallowed (Peyron and others 2004b; Jalabert-Malbos and others 2007).

Not only is saliva important in softening and altering the mechanical properties of food (Williams and others 2005) and providing lubrication to aid bolus formation, movement of the bolus within the oral cavity and swallowing (Mackie and Pangborn 1990; Van Der Reijden and others 1993), it also plays a key role in taste perception. Taste perception requires tastants to first dissolve in the saliva and then ascend to the taste receptors via the taste pore located at the top of the taste bud. The structural characteristics of the food, therefore, play a key role along with interindividual differences in chewing behavior, saliva flow, and bolus formation. Olfactory, visual, auditory, touch, taste, and thought of food are potent stimulators of saliva secretions (Fischer and others 1994; Tortora and Grabowski 1999). Chemicals in the food stimulate receptors in taste buds, and impulses are conveyed from the taste buds to the brain stem/autonomic nervous system to determine volume (Mackie and Pangborn 1990; Van der Reijden and others 1993), flow rate (Sarosiek and McCallum 2000), and composition of saliva (Bender and Bender 1997) to be secreted. Saliva is mainly composed of water (99.5 wt%), which acts as a medium for dissolving food, facilitates taste perception of the ingested foods, and initiates enzymatic digestion via α-amylase and lingual lipase. Saliva contains mucins, which are large extracellular glycoproteins that are important in the lubrication of food particles (Bourne 2002). Dilution by the secretion of saliva plays an important role in aroma release; however, the change in overall composition of the saliva–food mixture and mastication also influence aroma release (Van Ruth and Roozen 2000). Further saliva production is also important in mediating the trigeminal response known as astringency (a dry puckering feeling in the oral cavity) (Nayak and Carpenter 2008).

As discussed by Mioche and others (1999), the rhythmic activity of jaw opening and closing during chewing is adaptively modulated by sensory inputs in accordance with the physical and textural demands of the bolus. The sensory inputs influence mandibular movements and forces (Gibbs and others 1981) and the duration and number of chewing cycles (Hiiemae and others 1996). This requires information on the position and velocity of the jaw, the forces acting on the teeth and jaw, and the activity of muscles involved in chewing (Lucas and others 2004). The time taken from intake until swallowing will vary among individuals and with food properties (Van der Bilt and others 2006). It has also been demonstrated that oral processing varies with the type of sensory judgment being made (de Wijk and others 2008a).

Influence of Physical and Chemical Properties of Food on Oral Processing and Flavor Release

  1. Top of page
  2. Abstract
  3. Introduction
  4. Overview of Human Mastication
  5. Influence of Physical and Chemical Properties of Food on Oral Processing and Flavor Release
  6. Influence of Physical and Chemical Properties of Food and Oral Processing on Sensory Perception
  7. Conclusions
  8. Acknowledgments
  9. References

Food properties such as structure, composition, appearance, size, and shape influence the masticatory function (Figure 1) (Togashi and others 2000; Foster and others 2006; Woda and others 2006; Lenfant and others 2009). Mastication provides sensory feedback from which texture and flavor perceptions are derived (Brown and others 1998).

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Figure 1–. Overview of interactions among food properties, oral processing, and sensory perception.

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Textural terms are often used to describe the physical properties of the various foods used in mastication research. The terms used to describe foods are extensive, and definitions of common terms are not always consistent. As an example, Foegeding and Drake (2007) provide a list of texture terms used for describing cheese. These include terms that are evaluated by hand, first bite, and multiple bites (chewdown and residual at the point of swallowing) and include firmness, springiness, rate of recovery, fracturability, degree of breakdown, cohesiveness, adhesiveness, and smoothness. There is some discrepancy between the definitions of these terms and those used in materials science, for example, hardness and firmness (Foegeding 2007). For solid foods these are generally measured using compression or cutting tests on an Instron Universal Testing Machine (Foster and others 2006) or Texture Analyzer (Stable Microsystems) (Hutchings and others 2009), which measure force and deformation over time. A portable tester has also been developed and is commonly used for measuring the modulus of elasticity (E) and toughness (R) of test foods (Lucas 2004). Instrumental texture profile analysis (TPA), which is commonly used to measure food texture, returns values for fracturability, hardness, cohesiveness, adhesiveness, springiness, gumminess, and chewiness (Bourne 2002). Rheometers are commonly used to study stress/strain relationships in liquids, semisolids and soft solid foods (Foegeding 2007).

The influence of food properties on oral processing and flavor release are considered during the first bite, masticatory sequence, and swallowing.

The first bite

The first bite may include the acquisition of a sample from a food product or may be the 1st chewing cycle where subjects are given a constant sized sample in an experimental situation. Acquisition requires external assessment by sensory organs. Although there is limited literature available, it is clear that bite sizes vary among individuals and among foods, for example, males are known to have larger bite sizes than females (Medicis and Hiiemae 1998). With liquid foods, the size of the first bite is relatively small compared with that of semisolid and solid foods. However, successive bites become gradually bigger, whereas for semisolid and solid foods, the opposite has been found (de Wijk and others 2008b). Hutchings and others (2009) compared the natural bite sizes (weight, volume, and length) for 45 subjects from 6 manufactured food bars. Bite length was more consistent among all bars than bite volume. This work indicated that constant bite volume might represent normal feeding behavior better and be more appropriate than offering constant mass samples. Increases in the thickness of the food and the volume of the initial mouthful also increase most masticatory parameters (Woda and others 2006).

Masticatory sequence

Due to the large amount of literature available, this section has been divided into the influence of food properties on mastication and, subsequently, flavor release.

Physical and chemical properties of the food matrix and masticatory behavior Jaw movements and masticatory muscles activities are modulated throughout the entire masticatory sequence with respect to the changing physical and chemical properties of the foods. During a masticatory sequence, it has often been observed that the amplitude of vertical jaw movements tends to decline gradually. This is attributed to the bolus being softened and the food particles being reduced in size (Watt 1976; Jemt and others 1979; Wickwire and others 1981). Horizontal jaw movements also reduce with an increasing number of chewing cycles (Lucas and others 1986; Foster and others 2006). Jaw movements also vary with food type, for example, Brown and others (1998) found apple and carrot to be principally broken down using vertical compression, whereas, this was initially the case for biscuit but transferred to shearing action over the course of the masticatory sequence. In general, foods with a firm texture are chewed between the molars with slower jaw-closing velocities (Plesh and others 1986; Takada and others 1994) and more lateral movement of the trajectory compared with foods with a soft texture, which are ruptured between the tongue and the palate (Foegeding 2007). Chew work also declines over time, however, the rate of decline differs per food although Brown and others (1998) found biscuit to be unusual in that it required more work from 6 to 10 chews than it required initially. The most commonly studied physical property is hardness; however, masticatory behavior is also related to other physical and chemical properties. These are discussed below.

Hardness An increase in food hardness has been shown to increase the number of chewing cycles, duration of a masticatory sequence, and electromyographic (EMG) activity of the masseter and temporalis per sequence and per cycle (Hiiemae and Palmer 1999; Mioche 2004; Peyron and others 2004b; Foster and others 2006; Pereira and others 2006; Woda and others 2006; de Wijk and others 2008b). The effect of initial food hardness of gel and caramel model foods on EMG activities and jaw movements at various stages of a masticatory sequence has been studied (Foster and others 2006). EMG parameters appeared to be mostly related to initial food hardness for all stages of a masticatory sequence, whereas the effect of hardness on masticatory frequency was only important during the initial stage. Previously, there was some discrepancy with regard to the effect of food hardness on masticatory parameters, largely due to the use of natural foods (Sakamoto and others 1989; Agrawal and others 1998). Although these natural foods were chosen to have a range of hardness, variation in other textural parameters would have had an effect on the masticatory response. Elastomers and waxes have also been used (for example, Buschang and others 1997) although there is some doubt about the validity of this approach since they cannot be swallowed and therefore limit natural chewing.

Dry and hard products require more chewing cycles before swallowing. More time is needed to fragment the food and to add enough saliva to form a cohesive bolus suitable for swallowing (Anderson and others 1985). A study by Engelen and others (2005) comparing the mastication of peanuts, carrot, cheese, melba toast, bread, toast, and cake found that the largest number of chewing cycles was observed for the hard and dry foods.

Lubrication: moisture and oil contentsEngelen and others (2005) added extra lubrication (butter) to bread, toast, melba toast, and cake and found that the number of chewing cycles reduced, particularly for the dry products (cake, melba toast, and toast). Pereira and others (2006) followed up this study by looking at the effect of added water on the mastication of melba toast, cake, carrot, peanut, and cheese. Adding fluids reduced the muscle activity for melba toast, cake, and peanuts and the number of chewing cycles for cheese, melba toast, and peanuts. The decrease in muscle activity during chewing was more accentuated for cake and melba toast, which are foods that easily absorb water and are thus softened. de Wijk and others (2008a) found vibromyographic (VMG) throat activities to decrease with a small increase in oil content in semisolid vanilla custard desserts. Overall, an increase in lubrication results in a decrease in oral processing time and muscle activities in order to prepare the food for swallowing.

Elasticity and plasticity The effect of the rheological properties of gel and caramel model foods on EMG activities and jaw movements (measured using an articulograph) at various stages of a masticatory sequence for 15 subjects has been studied (Foster and others 2006). The gelatin gel model foods were mostly elastic in behavior, whereas the caramel model foods were mostly plastic in behavior. In a textural sense, these properties might be considered as the opposite ends of a springiness spectrum. As previously mentioned, masticatory frequency was affected by food hardness during the initial stage, but overall was more related to the rheological properties of the food. Vertical and lateral jaw movements throughout the entire sequence were mostly related to the initial rheological properties of the food and, most likely as a direct consequence of this, the variability of opening and closing velocities and cycle durations were also mostly explained by the rheological properties, particularly from the middle of the sequence onwards. This work proposed that 2 control mechanisms are involved. Firstly, a cortical and brain stem preprogrammed organization of different groups of neurons shapes the jaw movement to adapt to the rheological properties of the food. This would be influenced by existing knowledge of the food and triggered by sensorial cues (Westberg and others 1998; Sessle and others 1999; Yamada and others 2005). Secondly, a brain stem mechanism, depending on ongoing inputs and triggered by the food being processed, automatically sets a load-compensating reaction that adapts the muscle force to the resistance of the food (Hidaka and others 1997; Peyron and others 2002). This would be a fast reaction mechanism that responds to an unplanned food property.

Modulus of elasticity and toughnessAgrawal and others (2000) measured 3-dimensional jaw movements for 10 subjects while chewing standard volumes of 15 food types. The modulus of elasticity (E) and toughness (R) of the test foods were measured and compared with 3 measures from the jaw movement data: maximum lateral amplitude, maximum vertical amplitude, and the closing angle made by the jaw during the late closing phase relative to the vertical axis. The mechanical properties of the foods influenced jaw movements where (R/E)1/2 (also known as a fragmentation index, which is an estimate of the foods resistance to being broken down during mastication) was significantly correlated with both the closing angle and maximum lateral amplitude when all subjects’ data were averaged. Overall, hard, brittle foods, which have low (R/E)1/2 values, were chewed with wider jaw movements than softer, tougher foods, which have higher (R/E)1/2 values. This work demonstrates that the mechanical properties of foods are a source of sensory feedback to the CPG, influencing jaw movements during the late closing phase of a chewing cycle (Agrawal and others 2000). Chen (2009) made a similar conclusion after using the data of Engelen and others (2005) and found a linear relationship between the number of chewing cycles and the yield force for peanuts, carrot, cheese, melba toast, bread, toast, and cake, which also concurred with the findings of Wilson and Brown (1997).

Mioche and others (2003) compared the mastication and bolus properties, after 7 s of chewing and at swallowing, of meat with different textures—tough and dry meat versus tender and juicy meat. The mechanical properties of the meat, shear force, were measured using a cutting test. Greater muscle activities and number of chewing cycles were used for tougher meat and the toughest meat gave the toughest bolus, although this reduced as the bolus became ready to swallow. Yven and others (2005) did not find meat texture to influence bolus texture (shear forces) although dryer meat gave a dryer bolus for dentate subjects.

Heterogeneous food systemsHutchings and others (2010) undertook some unique work investigating the mastication of moist and dry peanuts within chocolate and gelatine gel matrices (4× test foods) for 8 subjects. It was found that matrices type influenced the masticatory frequency, sequence duration and number of chewing cycles required, and the broadness of the resulting peanut particle-size distributions. The moisture content, and likely resulting mechanical properties, of the peanuts affected the median particle size of the peanuts in the bolus ready for swallowing. It was proposed that the physical properties of the food matrices influence the selection function while the physical properties of the peanut particles influence the breakage function and resulting particle size. This work makes a step closer to understanding the dynamics of eating a meal where many different foods may be eaten at once.

Particle size The initial particle sizes in the food sample have been found to influence mastication. Van der Bilt and others (1991) varied the size of Optosil particles (2.4 and 9.6 mm) and measured the horizontal and vertical positions of 2 light-emitting diodes using an opto-electronic system for 8 subjects. Using the large Optosil particles, the jaw gape at first fall in velocity (which likely concurred with the sudden resistance of the particles) was found to correlate well with the size of the largest particle in the bolus for initial chewing cycles. In the later stages of the chewing sequence, the gape was significantly larger than the largest particle and tended to converge to a constant level that varied by subject. Maximum jaw gape was found to depend on the initial particle size.

Kohyama and others (2007) compared the EMG muscle activities when chewing blocks and finely cut samples of raw carrot, cucumber, roast pork, and surimi gels. There was no difference in the number of chewing cycles, chewing time, and EMG activities between block and finely cut (constant mass) samples of roast pork and surimi gels. Raw carrot and cucumber showed greater mastication effort for cut samples compared to block samples indicating that a reduction in particle size does not necessarily reduce mastication effort when the same initial weight of sample is maintained.

de Wijk and others (2008a) added polystyrene particles to vanilla custard desserts and found an increase in VMG temporalis and throat activities with increasing particle size for 10 subjects. These results are expected given that particle-size reduction is a requirement for bolus formation and swallowing.

BitternessNeyraud and others (2005) used viscoelastic gels with varying concentrations of quinine, 0 to 1446 μmol/kg, and measured the EMG activity of the masticatory muscles along with the intensity of several sensory attributes over time. Quinine concentration did not affect the chewing frequency or rate of salivation, however, with increasing quinine concentration, chew time decreased (from 30 to 22 s) and clearance time increased (from 7 to 14 s). Chewing muscle activity was not significantly affected by quinine concentration although it did decrease slightly with increasing quinine concentration.

Physical and chemical properties of the food matrix, mastication, and flavor release To examine the effects of changing the physical properties of the food matrix on flavor release, we need to consider firstly how flavor components are released from the food–saliva matrix and secondly how they are transported to the appropriate receptors (Taylor 2002). This includes the reduced or increased levels of tastants/aroma compounds accessing receptors (Juteau-Vigier and others 2007) or the blocking of taste receptor sites in the oral cavity. A 3rd issue is how signals from different receptors (for example, taste, aroma, and texture) interact on a cognitive level to generate our final sensory perception of the food matrix. The 3rd part of this process requires sensory evaluation measurements and therefore will be discussed in section 4 “Influence of Physical and Chemical Properties of Food and Oral Processing on Sensory Perception” of this review.

Mechanisms and models It is agreed that how flavor compounds are released from the food matrix is affected by the structure of the food matrix, the chemistry of the flavor compounds, their interaction with the components that make up the food matrix, the physiological processes that occur during the processing of the food, and the transport of flavor compounds to the receptor sites. Bylaite and others (2005) commented that 2 main mechanisms affect aroma release in hydrocolloids: (1) during stagnant conditions, mass transport takes place by molecular diffusion, whereas during mastication, the generation of eddies within the food and saliva matrix is likely to speed up the release rate of aroma volatiles; (2) molecular binding between flavor components and the food matrix.

Models for flavor release from food systems have been developed considering factors such as portioning coefficients, mass transport, and diffusion. This is an area that is well covered in a review by Taylor (2002). The conclusion from this comprehensive review was that although these models go some way to being able to predict flavor release in model food systems, there is a need to study more closely the dynamics of eating to obtain more information of the main parameters that are likely to affect the process. In particular, Taylor (2002) commented that in vivo measurements are the way forward to help build viable models.

Instrumentation for in vivo aroma analysisIn vivo aroma release has been examined by using specialized techniques such as atmospheric pressure chemical ionization mass spectrometry (APCI-MS) or proton transfer reaction mass spectrometry (PTR-MS). These techniques have been in use for a number of years to measure retronasal release of aroma compounds during eating. The classic measurements using these techniques are maximum concentration reached by target volatile (Imax), the time taken to reach maximum concentration (Tmax), the slope of the release curves (release rate), and the area under the curve. However, interfering ions can limit the number of compounds that can be successfully identified, and therefore model systems in which aroma compounds are added to the matrix seem to be the most appropriate application of these techniques. The use of solid phase microextraction for sampling breath and its subsequent analysis on conventional gas chromatography-mass spectrometer (GC-MS) equipment might expand the number of compounds that can be identified simultaneously, but the technique requires a cumbersome manual sampling procedure that is likely to limit its usefulness (Musteata and Pawliszyn 2007). Recent technical developments in selected ion flow tube mass spectrometry have enabled it to be used to analyze compounds in breath (Pysanenko and others 2009; Xu and Barringer 2010). This technique, which uses more reagent ions for the ionization of the analyte, might expand the number of compounds that can be identified simultaneously and has potential for analyzing retronasal flavor release. The influence of mastication on flavor release has been studied by examining the residual key odorants remaining in the food material using a methodology called spit-off odorant measurements (SOOMs). The volatiles are analyzed and quantified using multidimensional high resolution GC-MS. The authors using these techniques have concluded that an increase in polarity of an odorant results in a lower retardation in the mouth (Buettner and Schieberle 1999). Combining SOOM, videofluoroscopy, and magnetic resonance imaging (MRI), Buettner and others (2002) considered the possibility that the adsorption of potential aroma compounds by the oral mucosa may be a possible source of prolonged retronasal aroma perception.

In vivo analysis—the effects of “natural breakdown.”In vivo aroma release from a food matrix can be examined by changing the compositional nature of foods, that is, by varying the ingredients (for example, fat) or by changing the structure of the food matrix without varying the ingredients. Variation in the type and rigidity of gels has been examined. Initial investigations (Baek and others 1999) seem to show a decrease (not significant) in Imax as the rigidity of the gel increased, while other researchers show no change in Imax (Weel and others 2002) or the opposite trend (Boland and others 2006). One of the potential reasons for this discrepancy is the sensory instructions that were passed onto panelists. Weel and others (2002) requested participants to chew for 30 s and then swallow the entire bolus. Boland and others (2006) allowed samples to be chewed for as long as they required and reported significant differences between participants and for both types of gels. Chewing time increased with increased gel rigidity that might explain the higher levels of Imax in this work. Interestingly, the air/gel partition coefficients decreased as the rigidity of the gels increased.

There are clear benefits of comparing flavor release using mouth simulators. These techniques are able to minimize interindividual differences and focus solely on the changes of the food structure during this dynamic process. Other parameters such as temperature, air flow, salivation, and volume of food sample analyzed can also be varied (Taylor 2002). Gierczynski and others (2007) examined 3 cheese-like gels using APCI-MS with 14 subjects and compared data with aroma released from a mouth simulator (product breakdown was performed by using a rotor with 6 45-degree angle blades). An increase in hardness resulted in a faster and greater release of flavor during in vivo measurements, which was not observed with the mouth simulator where the hardness of the gel had no effect on the quantity of volatiles released (measured by air/water partition coefficients). The authors concluded that subjects changed their chewing behavior for each type of texture, with a harder gel providing a more intense chewing action that released more volatiles. From this data, it can be seen that subtle changes in the food structure are not enough to affect significantly aroma release under controlled conditions of constant time (16 min), whereas when subjects adapt their oral processing to the different structures of the food, significant differences are observed. Gierczynski and others (2007) reported that “natural breakdown” may be the “key parameter” in explaining in vivo aroma release and the following articles seem to confirm this.

Tarrega and others (2007) examined the relationship between chewing behavior using EMG and aroma release using APCI-MS in 8 model cheeses (with significantly different hardness levels as measured by a texture analyzer) with the same flavor content. Only 4 of the compounds out of the 8 were examined due to the interference of other ions. By asking subjects to complete 20 chewing cycles and then allowing to swallow ad libitum, it was shown that the composition of the cheeses changes the chewing behavior which in turn changed the aroma release profile with aroma release increasing with chewing work. However, it was also observed that the variability in aroma release was mainly related to variability in chewing parameters (in vitro“static” experiments seem to indicate that aroma release depends on the affinity of the compound for the food matrix and therefore partitioning of the compounds into the vapor phase). Two factors affecting physical aroma release were proposed: firstly, the effects of the food matrix; and secondly, the amount of chewing work that is carried out by individuals (Tarrega and others 2007).

Similar results were obtained by investigating flavor release into saliva. Pionnier and others (2004) used the techniques of atmospheric pressure ionization-mass spectrometry and ion chromatography to measure the amounts of 12 flavor compounds in saliva collected over eating time from 8 subjects in a model cheese system. They correlated maximum concentration in saliva and time to reach maximum concentration (Tmax) with mastication parameters measured by EMG. It was concluded that high Tmax values could be related to high chewing time and low saliva flow rate.

In vivo analysis—subject differences in chewingBlissett and others (2006) used EMG, electroglottography, turbine airflow technology, and APCI-MS to examine the effect of chewing and swallowing on volatile release in 2 “chew”-type confectionary products. Chewing and swallowing behavior seemed important in explaining volatile release patterns in product 1 where the increased retention time in the oral cavity due to differences in subjects’ selection efficiencies (slow unenergetic eaters as opposed to energetic fast eaters) may have been the determining factor. Conversely, chewing and swallowing behavior was less influential on volatile release from product 2. It was proposed that the higher fragmentability of product 1 than product 2 (which remained as one bolus) caused chewing to become the significant factor in determining aroma release.

Interindividual differences were the focus of Gierczynski and others (2008) investigation into the in vivo aroma release of different hardness milk gels using APCI-MS and performing hierarchical clustering on the retronasal release curves of 14 subjects (fixed 20-s chewing period). They found that 2 groups were identified with specific aroma release profiles. For one group, retronasal aroma release was continuously detected in the nasal cavity during the chewing phase, while with the other group, retronasal aroma release mainly occurred after the swallowing of the product. The authors consider that the masticatory differences between the 2 groups explain this phenomenon, with group A performing more chewing action, which allows the opening of the velum–tongue barrier and the transfer of aroma compounds to the nasal cavity, while group B performed shearing actions with the food product being pressed with the tongue on the frontal part of the oral cavity. Group A also perceived the aroma to be more intense than group B during the chewing phase. This supports the work by Buettner and others (2002), who commented that during mastication, an alternating series of open and closed stages of the velum–tongue border takes place, which is highly dependent on the movements of the jaw and tongue. It was also observed that the more liquid the food, the more the velum–tongue border would remain closed, thus reducing aroma compounds to the nose (however, more liquid also produces an increased swallowing rate, in turn increasing the velum–tongue border opening). Boland and others (2006), while observing the effect of gelatin and pectin gel textures on the in vivo release of strawberry flavor using PTR-MS, similarly found that the majority of recorded in vivo flavor release for low-rigidity gels occurred after swallowing, while there was significant recorded in vivo flavor release before and after swallowing for high-rigidity gels.

While studying ethyl butanoate release in gels prepared with 4% to 10% whey protein additions, Mestres and others (2006) reported that aroma release as analyzed by PTR-MS had a high concurrence with the perceptual sensory response, as determined by 7 panelists (30 s with closed lips, then swallow and continue chewing for 60 s) using time-resolved sensory evaluation. However, large intraindividual differences were observed. In accordance with Buettner and others (2002), observations with videofluoroscopy of the chewing process showed that chewing techniques affected the way the velum–tongue border opened and closed, thus affecting the retronasal release into the nose. For some panelists, the soft gel was mainly pressed by the tongue in the frontal part of the oral cavity with no velum–tongue border opening and thus no or little volatile release into the nasal cavity similar to viscous liquids (Hansson and others 2002). When these panelists were requested to chew with jaw opening, the velum–tongue border opened, and the volume of odors reaching the nasal passage increased.

In vivo aroma analysis expands the role of the food matrix in affecting aroma release by considering the influence of salivation and breathing rate during eating, mastication, and swallowing (Harrison and Hills 1996; Nahon and others 2000). Further by studying all in vivo approaches including EMG and electroglottography, we are able to extend the conclusions drawn from in vitro work by considering a wide range of important factors such as swallowing mechanisms, mastication, bolus formation, prolonged retronasal aroma perception (via adsorption of potential aroma compounds in the oral cavity), saliva production, and interindividual differences. During mastication, eddy diffusion within the matrix and surface area exposure for release of volatiles are likely to be the main mechanisms affecting release of volatiles from the food matrix. However, by examining structural changes of the food without considering the interindividual differences on how subjects break this food structure down during mastication will lead to different conclusions. Currently, research seems to indicate that participants might be able to be grouped by their mastication characteristics. Increased effort in chewing, product physical properties, and extended time before bolus formation are important factors in flavor release.

Swallowing

Bolus properties at the point of swallowing are commonly investigated by measuring particle-size distribution (Peyron and others 2004b; Mishellany and others 2006), moisture content (Gaviao and others 2004; Engelen and others 2005), and recently the slipperiness of the bolus (Seo and others 2007). Several techniques are used to measure the particle-size distribution of the bolus, including wet and dry sieving (Peyron and others 2004b; Jalabert-Malbos and others 2007), image analysis (Hoebler and others 2000; Mishellany and others 2006; Hutchings and others 2010), and laser diffraction (Hoebler and others 2000; Peyron and others 2004b). In our laboratory, we have used both wet sieving (Flynn and others 2010b) and image analysis (Hutchings and others 2010) techniques. We have found the wet sieving technique to be extremely time consuming as it requires a number of stages: removal of saliva from the bolus by washing with a TRIS buffered saline solution, carefully washing the bolus particles through a stack of sieves (0.125 to 4.0 mm), back washing the particles on each sieve onto predried and weighed filter papers then drying of the filter papers and particles to determine the dry mass of solids on each sieve. We have found the image analysis technique to be much quicker and very reproducible. With this technique, we have washed the bolus over a sieve aperture of 0.355 mm to remove unwanted material (saliva and the matrices when studying heterogeneous foods that influenced the size of the sieve for washing), dispersed in ethanol (which did result in the extraction of some fat from the particles but does not result in a change in the particle size of the peanuts used), and then images taken. We have also compared both techniques and found the same trends to be observed although the image analysis technique did have a tendency to divide large particles during analysis.

Some solids are lost during the mastication process (dissolution and subsequent loss of soluble solids, retained within the oral cavity, intermediary swallows) (Flynn and others 2010a) and sometimes when preparing a bolus sample for subsequent particle-size analysis, that is, washing the bolus to remove saliva (Peyron and others 2004b; Flynn and others 2010b). It has been found that 14% to 61% of the bolus solids are recovered at the point of swallowing, depending on food type (Peyron and others 2004b; Jalabert-Malbos and others 2007; Flynn and others 2010b). Peyron and others (2004b) and Flynn and others (2010b) found that about 40% of the initial weights of nut and vegetable samples were recovered. These losses mean that the resulting particle-size distribution is not truly indicative of a swallowed bolus and inferences made to nutrient release, for example, glycaemic response, may not be valid, particularly when it tends to be the very small particles and dissolved solids that are lost.

The particle-size distribution of the bolus depends largely on food type. Peyron and others (2004b) compared the boluses produced after mastication of raw vegetables (carrot, radish, and cauliflower) and nuts (peanut, almond, and pistachio). Raw vegetables were transformed into similar boluses made up of particles larger than 2 mm, and nuts gave similar boluses containing 90% of particles smaller than 2 mm. While the particle-size distributions of the raw vegetables and nuts were significantly different, no significant differences were seen within each group. Interestingly, although variability among subjects was clearly observed for masticatory parameters such as the number of chew cycles and EMG activity per cycle, such variability was not seen among the particle-size distributions from different subjects. This indicates that subjects may use different strategies to reach a similar end point. In general, the particle-size distributions of ready-to-swallow food boluses display no significant intraindividual variability and only a very small interindividual variability (Woda and others 2006). This shows that a food bolus has to meet precise conditions before swallowing can be triggered, and such conditions may be considered a vital requirement to prevent dysfunctional deglutition (Woda and others 2006).

Hutchings and others (2010) embedded wet and dry peanut particles in chocolate and gelatin gel matrices and measured the particle-size distribution of the peanut particles in the ready-to-swallow bolus. The physical properties of the peanut particles influenced the resulting mean particle size at swallowing although chewing behavior (for example, number of chewing cycles) remained unchanged within a particular matrix. The type of matrices that the peanuts were embedded influenced the chew number and broadness of the distributions as analyzed by a Rosin–Rammler function. This work demonstrates the possibility of influencing both chewing behavior and the properties of the ready-to-swallow food bolus by manipulating a particular food system, which in turn will influence sensory perceptions and nutrient release.

The food bolus particle size does not take into account other determinants for triggering deglutition such as optimal lubrication, plasticity, or the perception of cohesive forces unifying the bolus (Hutchings and Lillford 1988; Lillford 1991; Prinz and Lucas 1995, 1997). Bolus texture acts as a source of sensory information controlling the masticatory processes (Mishellany and others 2006). This occurs through activation of the CPG of mastication located in the brain stem (Mishellany and others 2006). The information conveyed by the same afferents is able to trigger, at least indirectly, the CPG that controls deglutition because the 2 functions are very similar, not only in their time features but also in their outcome (Mishellany and others 2006). These 2 CPG are not located in the same areas of the brain stem (Lund 1991) and their close functional relationship suggests the presence of feedback loops by which the activity of one CPG is controlled by the activity state of the other (Mishellany and others 2006).

Real-time MRI and videofluoroscopy have been used to understand the role of swallowing in the process of retronasal aroma release (Buettner and others 2001; Buettner and others 2002). It was observed that barriers in the retronasal cavity allow access of aroma compounds to the nasal epithelium only at certain times during the eating process. It was generally concluded that the most compliant textures are swallowed first, for example, liquids before solids. This would mean that aromas associated with the liquid are likely to be perceived first and the aromas from the more solid part of the food later. Buettner and others (2001) proposed that time intensity (TI) measurements should be considered in light of these findings with heterogeneous food systems having several intensity measurements over time related to the individual matrix component.

Influence of Physical and Chemical Properties of Food and Oral Processing on Sensory Perception

  1. Top of page
  2. Abstract
  3. Introduction
  4. Overview of Human Mastication
  5. Influence of Physical and Chemical Properties of Food on Oral Processing and Flavor Release
  6. Influence of Physical and Chemical Properties of Food and Oral Processing on Sensory Perception
  7. Conclusions
  8. Acknowledgments
  9. References

The overall acceptability of food is largely based on sensory factors such as appearance, flavor, and texture, which are perceived by the senses directly (Bourne 2002). To advance the area of dynamic sensory perception, we need to consider the current dynamic sensory techniques available, the interplay between oral physiology and sensory perception, and the relationships between physical characteristics and sensory perception. These are discussed further below.

The selection of appropriate dynamic sensory methods

Examining flavor and textural changes during a masticatory sequence requires sensory techniques that can assess perception considering the additional dimension of time. The main techniques that have been applied for this purpose can be categorized into 2 quite different approaches: temporal dominance of sensation (TDS) and TI measurements (such as discrete point TI, continuous TI). TI has been around for some 40 y (the evolution of time-intensity methodology for sensory evaluation was reviewed comprehensively by Cliff and Heymann (1993), whereas TDS is a relatively new method developed by “Centre European des Sciences du Guot” in the year 1999 (Pineau and others 2009). A good description of these techniques can be found in Kemp and others (2009).

Lenfant and others (2009) used TDS to evaluate the dynamics of texture perceptions during oral processing of different breakfast cereals. TDS allows the subject to record their dominant sensation (in this case hardness, crackliness, crispness, brittleness, lightness, stickiness, grittiness, or dryness) for each product at different points throughout a masticatory sequence. Twenty-five untrained subjects were used to create a vocabulary for the breakfast cereals of interest, which were later reduced to the 8 most frequently used terms. A glossary for these terms was created and the subjects practiced the use of these terms using different commercially available (nonbreakfast cereal) products. After training on the use of the TDS method and the protocol used, 3 g samples were assessed and the dominant attribute, which changed with time, was selected on a computer screen throughout the chewing process. Due to the masticatory process being highly variable among subjects, each TDS curve was standardized by reducing the x-axis was reduced from x= 0 (1st scoring) to x= 1 (swallowing). The aim here was to standardize the data according to individual mastication time; however, differences between the time taken from ingestion to 1st scoring were unaccounted for. Overall, hardness and crackliness attributes were dominant in the early stages of mastication (and registered ≤5 s after ingestion), which then gave way to the perception of crispness. Brittleness was dominant in the middle of a masticatory sequence and stickiness was highly dominant at the end. Stickiness referred to sticking to the palate and teeth during oral processing, but it is possible that subjects also assessed this as cohesiveness, which is thought to be critical for the initiation of swallowing (Prinz and Lucas 1995; Lillford 2001; Woda and others 2006).

To date, TI method is defined as one of the most frequently used descriptive sensory analyses to determine intensity of a specific attribute(s) over a period of time (Cliff and Heymann 1993; Peyvieux and Dijksterhuis 2001; Sprunt and others 2002; McGowan and Lee 2006; Ross 2009). However, TI has several limitations as discussed by Ledauphin and others (2006). In particular, it is very time consuming when more than one attribute is of interest. Dual-attribute TI was developed with the intention to reduce the time used for sensory evaluation by requiring panelists to score simultaneously 2 attributes by moving a cursor on a xy axis (each axis refers to one attribute) (Pineau and others 2009). Nevertheless, this method cannot be extended to more than 2 attributes at one time. Continuous TI has also been reported as producing inconsistent data with Saint-Eve and others (2006) selecting 3 discrete points for intensity ratings of aroma in flavored yoghurt complexes rather than using continuous TI. Therefore, when multiple attributes need to be assessed during the same run, the newer TDS method warrants further investigation.

Despite this noteworthy introduction of a new dynamic process for assessing sensory evaluation, there is currently little data comparing these 2 approaches formally, particularly in solid foods. This possibly is due to the newness of the technique. However, there is a need for us to understand more fully how subjects interact with these techniques. The decision processes that subjects are using for TDS where dominant attributes are being selected can be viewed as a series of ranking assessments over a period of time as opposed to TI where one or two attributes are being assessed for their intensity. Pineau and others (2009) compared TI and TDS for assessing 5 dairy products. Although both methodologies gave similar patterns of sensations, it was concluded that TDS demonstrated more clearly the sequence of the sensations over time. Labbe and others (2009) compared TDS with sensory profiling for gels containing different levels of odorants, citric acid, cooling agent, and xanthan gum. They found differences between dynamic perceptions and those gained immediately postconsumption, in particular for bitterness and coldness sensations, and concluded that TDS may be more relevant for understanding complex perceptions such as refreshing. TDS and TI methods are compared in Table 1.

Table 1–.  Comparison between temporal dominance of sensations (TDSs) and time intensity (TI) methods.Thumbnail image of

An important consideration in comparing masticatory behavior with sensory perception is the influence of training on oral processing. It is well known that there are large variations among individuals for all parameters of mastication, even when potentially influencing variables (for example, age, gender, dental status) are controlled for (Lassauzay and others 2000). Training on sensory attributes could be another potential source of variation. Mioche and Martin (1998) found significant differences between trained and untrained panelists for EMG muscular work and insignificant differences for the number of chews and chewing time. González and others (2002) found trained subjects to use longer chewing times, smaller chewing frequencies, and larger muscular work than untrained subjects. Intraindividual variability was also greater for trained subjects, and this was thought to be related to these subjects having too much knowledge of the products and them receiving samples slightly different from what they were expecting. González and others (2002) found gender not to be an influencing variable. This is in contrast to other studies, which have found males to display higher EMG activities, higher vertical amplitudes, and slightly higher frequencies although no difference between the total number of cycles used compared with females (Peyron and others 2004a).

The decision of which dynamic sensory technique is most suited to investigate the effects of food properties and/or oral processing on sensory evaluation requires some consideration. Currently, our understanding of which techniques are most suitable is at a general level based on numbers of attributes that need to be assessed and the complexity of the food system. Until we can develop model food products where only 1 sensory attribute changes over time, TDS is a technique worthy of further investigation for this area of research. However, there is now a need for more studies to investigate this technique further, for example, looking at factors such as effects of training panelists, attribute selection, and how panelist's sensory data is standardized across the whole eating process. From this research a more standardized approach to using the techniques may be formulated.

Interplay between oral physiology and sensory perception

It is believed that many assessments are made during the first bite and that the 1st chewing cycle is often exploratory and is generally different from subsequent chewing cycles, for example, the frequency of a chewing cycle is usually slower for the 1st cycle (Foster and others 2006; Peyron and others 2002). Duizer and others (1996) compared instrumental TPA with sensory tenderness measured over an entire masticatory sequence using TI sensory evaluation and masseter activity measured by surface EMG for 5 different beef samples. It was found that maximum tenderness perception occurred anywhere between the 1st and 4th chew, illustrating that more than just the first bite is required to measure tenderness, as previously proposed by Boyar and Kilcast (1986). It was also found that age differences among the 5 meat samples relating to tenderness were best detected during late mastication.

Unfortunately, only a few studies have looked at sensory adaptations throughout a masticatory sequence, and very different foods were used. While Duizer and others (1996) focused on meat tenderness, de Wijk and others (2008a) investigated sensory attributes in vanilla custard desserts. Here, the authors compared VMG activities from the throat and temporalis with the assessments of thick, creamy, melting, fatty, rough, and liking attributes using 11 starch-based vanilla custard desserts (with different fat contents, viscosities, and polystyrene particle sizes) from 10 subjects. A 5 mL sample of each custard was tested orally for 5 s while 1 of the 6 attributes was assessed using a 10-cm line scale. Activities measured from the temporalis muscles were mostly affected by jaw movements whereas those measured from the throat were mostly affected by tongue movements. As seen by de Wijk and others (2003 and 2006b), increasing thickness ratings related to reduced up and down movements of the tongue. High melting ratings were associated with higher throat VMG activities and hence increased up and down tongue movements. Both VMG activities were related to creaminess ratings, indicating more complex movements are required to assess creaminess, which is believed to be a complex sensation relating to the food's viscosity, lubrication, and flavor (de Wijk and others 2006a). Although creaminess is typically correlated with liking, different oral behaviors were used to assess creaminess and liking. Both were associated with low VMG activities at the temporalis, whereas liking was associated with low throat VMG activities, and creaminess was associated with high throat VMG activities. The point during the 5 s of oral processing at which these attributes were related to oral movements differed: 1 to 2 s after ingestion for liking compared with 4 to 5 s after ingestion for creaminess. de Wijk and others (2008a) stated that liking (hedonic) and creaminess (analytical) sensations activate different pathways and motor programmes in the brain that determine oral movements.

Although, in theory it is possible to minimize the effects of aroma when studying the interplay between sensory perception and oral processing by allowing subjects to wear nose clips that inhibits retronasal aroma release, the taste modality (sweet, sour, bitter, salt, umami, and possibly fatty taste), trigeminal responses (for example, astringency), and effects of saliva cannot be minimized as easily. Further, a model system that minimizes these effects may be a step too far away from a real eating situation. Neyraud and others (2005) used viscoelastic gels with varying concentrations of quinine, 0 to 1446 μmol/kg, and measured the activity of the masticatory muscles and intensity of several sensory attributes (bitterness, sourness, sweetness, firmness, and acceptability) over time. With increasing quinine concentration, bitterness perception increased while acceptability and sweetness decreased, chew time decreased (from 30 to 22 s), and clearance time increased (from 7 to 14 s). Neyraud and others (2005) also found correlations between chewing and sensory perceptions. Subjects who chewed for longer reported higher bitterness and lower acceptability ratings. Subjects who used more muscle effort found the gels to be sweeter, and subjects who had higher levels of quinine in their saliva rated the gels as more bitter. This study indicates clearly that acceptability correlated with taste will decrease chew time regardless of the textural characteristics of the products. Saliva, which is known to be important during the breakdown of food in the mouth, also affects sensory perception in custard and mayonnaise. Engelen and others (2007) found that subjects with high total protein concentrations in their saliva reported low flavor ratings, low slippery lip-tooth feelings, and fatty after-feel. High α-amylase activity correlated with a reduced vanilla flavor sensation in custard and decreased creamy after-feel. This is thought to be due to the enzyme breaking down the starch in the custard to give a less viscous product, resulting is less surface area and reduced flavor release. Subjects with low α-amylase activity also had stronger slippery lip-tooth sensations. Pionnier and others (2004) used a modified TI methodology to study the relationships between perception, flavor release, and oral parameters during mastication of one type of cheese. Interindividual differences in aroma and taste compounds were related to interindividual differences in flavor release, masticatory measurements, and salivation.

The relationship between physical characteristics and sensory perception

Texture perceptionSzczesniak (2002) defined texture as being “the sensory and functional manifestation of the structural, mechanical and surface properties of foods detected through the sense of vision, hearing, touch and kinesthetics.” This definition conveys many important concepts including that texture is a sensory property that only humans can truly perceive and describe as well as being a multiparameter attribute that consists of numerous characteristics derived from the structure of the food. Finally, it conveys the sense that texture is a property that is detected by several senses (Szczesniak 2002). There are numerous studies which have found or sought to correlate sensory and instrumental texture terms where better correlations are generally seen when instrumental measures more closely mimic intraoral processes (for example, see Duizer and Winger 2006; Kim and others 2009). There are, however, some quite distinct differences in how sensory and instrumental terms are evaluated, for example, instrumental measures cannot usually replicate the temperatures and compression rates used in the mouth. Also, Foegeding and Drake (2007) discuss how correlations can be found in the absence of any mechanistic links. A further complication is that static instrumental methods ignore the incorporation of saliva into the bolus, the reduction in particle size, and changing bolus texture over time. It is likely that robotic mouths are more appropriate texture measurement devices as they can account for some of the shortfalls of current instrumental methods.

Kim and others (2009) measured the textural attributes of 20 cereal snack bars by both a trained sensory panel and various instrumental methods (3-point bending test, cut (shear) test, puncture test, TPA, and modified TPA using a probe size smaller than the sample size). It was found that TPA and modified TPA could be used to predict sensory attributes of firmness, chewiness, and crumbliness; however, the 2nd compression from the modified TPA gave the best prediction of these attributes. This was due to it minimizing the effect of variation in the sample test area and more closely imitating mastication where both shear (cutting) and compression occur.

The following work is interesting as an attempt has been made to link perception with instrumental measures that more closely mimic oral processing. Seo and others (2007) evaluated the sensory attributes of the food bolus during swallowing using 10 trained panelists and commercially available food products. Two sensory attributes were derived: slipperiness, which was defined as the degree of slide of the food bolus through the mucosal surface of the oro-pharynx; and compliance, which was defined as how easily the shape of the food bolus could be transformed for comfortable swallowing. Water, tomato juice, plain yoghurt, Thousand Island dressing, yellow mustard, and tomato ketchup were used to assess slipperiness; water, sweet pumpkin gruel, plain yoghurt, soft tofu, pudding, and canned pork were used to assess compliance. Slipperiness was also measured instrumentally by placing the food sample on a sliding bar and measuring the angle from horizontal required for the food to move along the sliding bar, much like a Bostwick consistometer. Compliance was measured using a texture analyzer. This consisted of a vessel containing the sample and a probe with a hexahedron-shaped internal cavity. The force required to transform the sample from its initial shape to completely fill the internal cavity of the probe was measured. Both instrumental measurements used initial food samples in their analysis although they did attempt to mimic some oral conditions during the instrumental testing, particularly for the measurement of compliance. The sensory slipperiness attribute differed significantly among the samples, with the least viscous sample having the highest slipperiness rating and the most viscous sample having the lowest slipperiness rating. Significant differences were also seen among the samples for the sensory compliance attribute where liquid samples were perceived as being more compliant than semisolid and solid samples. Sensory and instrumental measures were also highly correlated.

Flavor perception.  For retronasal aroma analysis with techniques such as PTR-MS, APCI-MS, and SYFT-MS, we are able to examine in real time the concentrations of aroma compounds reaching the olfactory cavity (as discussed earlier). With carefully controlled experiments using dynamic sensory methods, we have a technique that uniquely investigates sensory perception of aroma in relation to the concentrations of those compounds that are interacting with the olfactory epithelium. Already some interesting observations have been made.

Most reports in the literature note that aroma perception is reduced with increasing viscosity of foods (Pangborn and Szczesniak 1974; Baines and Morris 1987). A similar effect with gel strength is also observed (Weel and others 2002; Boland and others 2006). However, in vivo studies have shown that in-nose aroma concentrations are independent of thickener concentration (Cook and others 2005) or gel strength (Weel and others 2002).These authors proposed that the perceived changes in flavor were due to congruent perceptual interactions between tactile, taste, and aroma signals. Boland and others (2006) also explained an increase in retronasal aroma concentrations of ethyl butyrate with a decrease in perceived strawberry flavor with increased perceived thickness with firmer gelatin and pectin gels as a possible cross modality interaction. Hollowood and others 2002 with very carefully designed experiments were able to demonstrate eloquently that in viscous solutions, congruent interactions were occurring between texture (thickness), taste (sweetness), and aroma. More experiments of this type need to be designed for solid food systems to investigate this effect more closely.

Cook and others (2005) correlated continuous TI analysis with retronasal breath-by-breath aroma release data (collected using APCI-MS) of 3 solid products requiring mastication. The products were prepared in 3 different forms but with the same concentration of flavoring added. TI measurements focused on 1 attribute only—rosemary flavor intensity. Results showed that both techniques similarly differentiated the product matrices. However, there was a lag in perception compared with the retronasal aroma release data.

The speed that aroma compounds are released from the food matrix seems to play a critical role. A rapid release of volatile compounds will produce a delay in perception. However, a slower release of aroma compounds may cause maximum perception being reached first due to adaption (Baek and others 1999). Mestres and others (2005) measured maximum overall perceived retronasal aroma intensity of ethyl butanoate (defined as a fruity attribute) in a series of model gel systems during mastication. These results were compared with PTR-MS in vivo retronasal volatile (ethyl butanoate) release. The authors reported that soft gels were perceived as more flavor intense than the hard gels during mastication, even though the total release of volatiles did not significantly differ as measured by PTR-MS. However, the matrix did have a time-dependent effect on the way ethyl butanoate was released, with the soft gels giving a high initial liberation of aroma, (with the harder gels the aroma gradually built up) which might indicate the psychological importance of first impression. In a follow-up article, the authors report the results of a more dynamic approach to the way sensory perception was measured that allowed for more observations of “first impression” (Mestres and others 2006). They used a time resolved sensory evaluation measurement where panelists indicate the moments of intense aroma perception by raising the hand.

Therefore, rate of release as well as intensity are important factors in aroma perception that can only be studied appropriately using dynamic sensory techniques. These studies also indicate the importance of combining retronasal aroma release studies with dynamic sensory methods to investigate adaptive processes and multimodal interactions that are occurring during oral processing (Bult and others 2007; Kremer and others 2007; Zampino and others 2008). This area is particularly well covered in a review by Auvray and Spence (2008). There is space to extend these experiments where oral processing measurements such as EMG, articulography, and retronasal aroma release measurements (PTR-MS, APCI-MS, SYFT-MS) are combined with TDS.

Conclusions

  1. Top of page
  2. Abstract
  3. Introduction
  4. Overview of Human Mastication
  5. Influence of Physical and Chemical Properties of Food on Oral Processing and Flavor Release
  6. Influence of Physical and Chemical Properties of Food and Oral Processing on Sensory Perception
  7. Conclusions
  8. Acknowledgments
  9. References

The relationships between food properties, mastication, and sensory perception are complicated by the dynamic nature of mastication and sensory perception, which varies among individuals. Although there are numerous studies investigating the mastication of various food products, only a few of these have convincingly demonstrated the effect of different textural properties (hardness, springiness) using controlled model food systems. Further research in this area will need to use model food systems where other textural attributes are varied; this is quite a challenge in itself. There is little information about the dynamics of texture perception during mastication (where the physical properties of the food bolus are constantly changing over time) and how this relates to overall texture perceptions for a food product. Two quite different dynamic sensory methods have been used, TI and TDS, particularly in flavor research. Several studies have shown that aroma release profiles can be grouped based on differing oral behaviors. This highlights the need to consider differing oral behaviors between individuals when investigating dynamic texture and flavor perception. Some thought is needed when determining the most appropriate sensory techniques to use given the overall perception of the food product and the possible congruent interactions that might be taking place during the analysis.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Overview of Human Mastication
  5. Influence of Physical and Chemical Properties of Food on Oral Processing and Flavor Release
  6. Influence of Physical and Chemical Properties of Food and Oral Processing on Sensory Perception
  7. Conclusions
  8. Acknowledgments
  9. References