The staling of processed cereal products such as bread, biscuits, and cakes during storage is associated with the recrystallization (or ‘‘retrogradation’’) of starch or, more precisely, amylopectin chains, into A- or B-type crystalline polymorphs from its initial gelatinized state obtained by baking. The spatial distribution of retrogradation rates can be followed by MRI and related to the changing moisture distribution. Moisture maps (actually maps of the initial water proton magnetiza- tion,M(0), for freshly baked biscuit ‘‘sweetrolls’’ and after 1, 3, and 5 days of storage have been reported by Ruan et al. (48). These showed that staling was associated with an apparent migration of moisture from the inside to the outside of the sweetroll. Surprisingly, the correspondingT2maps showed a longer initial T2 in the drier, outer region of the sweetmeal and a shorter T2 in the middle region, which gradually increased during storage. The reasons for these storage changes is still a matter of speculation. One possibility is that retrogradation proceeds faster in the center because of the higher initial moisture content and results in an increase of more mobile water with a longerT2, which migrates to the outside of the sweetroll. Whatever the correct interpretation, it is clear that MRI has an important role to play in imaging the spatial changes associated with staling cereal products.
At a molecular level, retrogradation corresponds to an increased crystalliza- tion of the amylopectin into either A or B crystallites (depending on the water content and temperature), which causes the textural change associated with stal- ing and results in decreased biopolymer proton mobility. The molecular factors
controlling the retrogradation rates can therefore be studied with high-power NMR relaxometry.
In waxy maize starch extrudate consisting mainly of gelled amylopectin containing 35% water, both the relaxation rate for the solid, nonexchanging pro- ton component of the amylopectin, obtained from a Gaussian analysis of the FID, and the single exponential water proton transverse relaxation rate obtained from the CPMG decay increase with storage time as the amylopectin crystallizes.
These changes, which are shown inFigure 6,can be modeled with the Avrami equation, which has the form
R(t)⫽Rmax⫺(Rmax ⫺R0) exp[⫺(Gt)n] (3)
Here Gis the rate of retrogradation and the index n typically assumes values between 1 and 4.RmaxandR0are the asymptotic relaxation rates at infinite and zero storage times, respectively. The resulting rates of crystallization,G, can be
Figure 6 Effect of storage time on the CPMG water-exchangeable proton transverse relaxation rate (solid wedges); the CH proton relaxation time measured from the FID (pluses); and the crystallinity index measured by X-ray diffraction for an amylopectin extrudate containing 35% water. Only relative increases are shown, and the lines are the fits of the Avrami equation. (From Ref. 49.)
analyzed with glass–rubber transition theory. At, or below, the glass transition temperature,TG,Gis expected to be zero, because the extremely low chain mobil- ity prevents growth of the amylopectin crystallites. The relationship betweenG and (T⫺Tg) is expected to follow a modified version of the empirical Williams–
Landel–Ferry (WLF) equation, which relates kinetic properties to (T⫺Tg). Ap- plied to retrogradation, the modified equation can be written
log10冢GGref冣⫽ ⫺C2C⫹1(∆T(∆T⫺⫺∆T∆Trefref)) (4)
Here∆T⫽ (T⫺Tg) and∆Trefis (T⫺ Tref), whereTrefis an arbitrary reference temperature. The log-linear plot predicted by Eq. (4) has been confirmed by Far- hat et al. (49). Because the glass transition temperature is itself a function of water content and sugar content, the rate of retrogradation,G, will also depend on the system composition, increasing with increasing water content because of the reduction inTg. More quantitatively, the compositional dependence of the glass transition temperature can be estimated by equations such as that of ten Brinke (56) or modifications of it. The ten Brinke equation has the form
Tg⫽ ⌺iWi∆CpiTgi
⌺iWi ∆Cpi
(15) whereWiis the weight fraction of componentiand∆Cpiis the difference in the specific heat capacity between the liquid and glassy states at Tg. Equation (5) shows that the introduction of lower-molecular-weight species, such as water and sugars, with low intrinsicTgvalues results in a lowering of the overallTgfor the mixture. This, in turn, leads to an increased rate of retrogradation via the WLF equation.
The ten Brinke equation is only a first approximation in most food systems, because it assumes that there is no selective partitioning of water between bio- polymer or sugar molecules. In fact, the sorption isotherm for the amylopectin and sugar shows that this assumption is not strictly valid, with water preferably hydrating the biopolymer at low water contents and the sugar at high water con- tents. The foregoing analysis also assumes that the rate-limiting step in retrogra- dation is the growth of amylopectin crystalline regions within the biopolymer network and not the rate of crystal nucleation, which decreases up to the amylo- pectin melting point. If nucleation is rate limiting, the rate of retrogradation will be expected to decrease with increasing temperature, which is sometimes ob- served in cake products. Despite these complexities it is clear that glass–rubber transition theory offers exciting possibilities for the prediction of the effect of water content, sugar content, and temperature on the rate of staling of baked products and also clear that NMR and MRI provide the means for a detailed
investigation of the space and time changes in molecular mobility associated with the staling process.
The application of1H,2H, and17O NMR to the even more complex problem of the staling of bread has been reviewed by Chinachoti (52). Both the amplitude and the relaxation rate of the rigid component in the proton free induction decay of white bread increased over a 10-day storage period, consistent with starch retrogradation and an increase in rigidity of the gluten network, though these contributions have yet to be distinguished. Somewhat surprisingly, the broadband deuterium spectrum of aging bread containing about 50% moisture showed no developing solid-state spectrum (a Pake pattern), indicative of oriented ‘‘icelike’’
water. This negative observation shows the high mobility of the water even when it is known that the biopolymer components are becoming more rigid. Clearly much remains to be understood about the molecular mechanisms of bread staling, and this remains an outstanding challenge for the future.
VIII. CONCLUSION
It is clear that NMR and MRI have important roles to play in optimizing all stages of cereal production, from the field to the processed food product, and that, with a few exceptions, the information emerging from NMR is of a fundamental, nonroutine nature. The fundamental nature of the information is not a disadvan- tage, because understanding structure–function relationships in foods over all distance scales, from the molecular to the macroscopic, is surely one of the out- standing challenges in food science. An example serves to illustrate this point.
It is now possible to genetically engineer wheat, corn, and potato to modify starch granule structure at the molecular level by altering the activities of the enzymes responsible for starch granule synthesis. Yet our understanding of starch structure–function relationships is still too primitive to predict the effect of this molecular-level engineering on the subsequent response of the granule to pro- cessing operations, such as thermal gelatinization. It is also too primitive to pre- dict the properties of the resulting starch system, such as the rheology of the genetically modified starch gel, and it is here that the true power of NMR tech- niques is apparent. As we have seen, the changing dynamic state of the starch chains in the granules during processing can be monitored with techniques such as proton relaxometry and high-resolution solid-state spectroscopy (CPMAS).
The changing microscopic distribution of water inside the granule can also be monitored with multinuclear relaxometry and diffusometry. Water migration dur- ing the starch processing stage can be monitored with NMR microimaging, while MRI rheology can also be used to characterize the rheological state of the starch–
water system. In addition, storage changes, such as starch retrogradation, can be characterized with relaxation-weighted imaging.
Even this impressive array of NMR techniques hardly serves to scratch the surface of the large number of NMR techniques and pulse sequences that can be brought to bear on the problem of starch and starch processing. In addition it should be remembered that it is not always the NMR data themselves that are of greatest value, but rather the mathematical models of structure–function and heat and mass processing that are developed from the data and that can subse- quently be used to optimize the production stages. The development and testing of these models must therefore be added to the list of outstanding future chal- lenges in cereal science.
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14
Phosphorescence Spectroscopy as a Probe of the Glassy State in
Amorphous Solids
Richard D. Ludescher
Rutgers University, New Brunswick, New Jersey, U.S.A.
I. INTRODUCTION