Accepted Manuscript

Title: Infrared spectroscopy as a tool to characterise starchordered structure- a joint FTIR-ATR, NMR, XRD and DSCstudy

Author: Frederick J. Warren Michael J. Gidley BernadineFlanagan

PII: S0144-8617(15)01156-XDOI: http://dx.doi.org/doi:10.1016/j.carbpol.2015.11.066Reference: CARP 10585

To appear in:

Received date: 12-10-2015Revised date: 25-11-2015Accepted date: 26-11-2015

Please cite this article as: Warren, F. J., Gidley, M. J., and Flanagan,B.,Infrared spectroscopy as a tool to characterise starch ordered structure- ajoint FTIR-ATR, NMR, XRD and DSC study, Carbohydrate Polymers (2015),http://dx.doi.org/10.1016/j.carbpol.2015.11.066

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Highlights

A larger sample set (61) of starches than has been used in previous studies

Full structural characterisation using a range of techniques

A non-linear, hydration dependent response occurs in the infrared spectrum

Complex changes in the infrared spectra of starch with increasing structural order

Highlights (for review)

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Infrared spectroscopy as a tool to characterise starch ordered 1

structure- a joint FTIR-ATR, NMR, XRD and DSC study 2

Frederick J. Warren †, Michael J. Gidley

†, Bernadine Flanagan

†* 3

†Centre for Nutrition and Food Sciences, ARC Centre of Excellence in Plant Cell Walls, 4

Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St. 5

Lucia, Brisbane, Queensland 4072, Australia 6

7 8 9 10

11 12 * Corresponding author. Centre for Nutrition and Food Sciences, ARC Centre of Excellence 13

in Plant Cell Walls, Queensland Alliance for Agriculture and Food Innovation, The 14

University of Queensland, St. Lucia, Brisbane, Queensland 4072, Australia 15

16

17

Title Running Head: Infrared spectroscopy to characterise starch ordered structure 18

Keywords: Starch, crystallinity, polymer structure, FTIR-ATR, NMR, XRD 19

20

*Manuscript

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21

Abstract 22

Starch has a heterogeneous, semi-crystalline granular structure, and the degree of ordered 23

structure can affect its behaviour in foods and bioplastics. A range of methodologies are 24

employed to study starch structure; differential scanning calorimetry, 13

C nuclear magnetic 25

resonance, X-ray diffraction and Fourier transform infrared spectroscopy (FTIR). Despite the 26

appeal of FTIR as a rapid, non-destructive methodology, there is currently no systematically 27

defined quantitative relationship between FTIR spectral features and other starch structural 28

measures. Here, we subject 61 starch samples to structural analysis, and systematically 29

correlate FTIR spectra with other measures of starch structure. A hydration dependent peak 30

position shift in the FTIR spectra of starch is observed, resulting from increased molecular 31

order, but with complex, non-linear behaviour. We demonstrate that FTIR is a tool that can 32

quantitatively probe short range interactions in starch structure. However, the assumptions of 33

linear relationships between starch ordered structure and peak ratios are overly simplistic. 34

Graphical abstract 35

36

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37

1. Introduction 38

Starch is one of the most important biopolymers in the world. It is the main source of energy, 39

in the form of exogenous glucose supply, in the human diet, and is a key feedstock for a 40

number of industries such as bioethanol production and biodegradable plastics manufacture 41

(Butterworth, Warren & Ellis, 2011; John, Anisha, Nampoothiri & Pandey, 2011; Shen, 42

Worrell & Patel, 2010). Starch granules are made up of two glucose polymers, amylose (an 43

essentially linear polymer composed of α-1→4 linked anhydro-glucose residues, typically 44

reported to have a molar mass ∼ 105–10

6 g mol

−1) and amylopectin (a highly branched 45

polymer consisting of short chains of α-1→4 linked anhydro-glucose residues, interspersed 46

with 5-6% branch points of α-1→6 linkages, with a molecular weight perhaps as high as 107–47

109 g mol

−1) (Gidley et al., 2010). These two polymers are arranged into a complex semi-48

crystalline granular arrangement, based on aggregates of double helices formed primarily 49

from adjacent branches of amylopectin molecules. 50

The ratio of crystalline to amorphous material in the native starch granule varies greatly, from 51

10% to 50% crystallinity, depending on the botanical origin of the starch (Lopez‐Rubio, 52

Flanagan, Gilbert & Gidley, 2008). Further alterations in structure can occur as a result of 53

subsequent processing of the starch. For example, the most common processing step is 54

gelatinisation, where the starch is heated in excess water at a temperature between 50 and 55

70°C. The starch undergoes a cooperative transition whereby water enters the amorphous 56

regions of granules, causing them to swell and destabilise the crystalline regions. This results 57

in rapid swelling of the granule, melting of the crystallites and a complete loss of ordered 58

structure (Bogracheva, Wang, Wang & Hedley, 2002; Cooke & Gidley, 1992; Perry & 59

Donald, 2002; Waigh, Gidley, Komanshek & Donald, 2000). Other processing steps which 60

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may increase or decrease starch molecular order include annealing (Tester & Debon, 2000), 61

extrusion (Brümmer, Meuser, van Lengerich & Niemann, 2002) and enzymatic digestion 62

(Lopez-Rubio, Flanagan, Shrestha, Gidley & Gilbert, 2008). For all processing applications 63

involving starch, measuring the degree of ordered structure is important, but doing so is far 64

from facile. As different analytical methods measure ordered structure in different ways, and 65

may measure subtly different aspects of starch structure, it is informative to compare and 66

contrast analytical methods. In the present paper, four of the most common analysis methods 67

are used; x-diffraction (XRD), differential scanning calorimetry (DSC), 13

C cross-68

polarization magic angle spinning nuclear magnetic resonance spectroscopy (13

C CP-MAS 69

NMR) and Fourier transform infrared spectroscopy with attenuated total internal reflectance 70

(FTIR-ATR). 71

Diffraction based methods, such as XRD, are the only methods available for the assessment 72

and quantification of long-range crystalline order in starch. Crystalline order in starch is 73

conventionally determined using a two-phase model, introduced by Sterling (Sterling, 1960) 74

and Nara (Nara, Mori & Komiya, 1978), where an amorphous halo is subtracted from the 75

ordered parts of the scattering pattern, and the ratio of the two phases is used as an estimate 76

of long range crystalline order. A more nuanced peak fitting approach has recently been 77

suggested (Lopez‐Rubio, Flanagan, Gilbert & Gidley, 2008), taking into account incoherent 78

scattering from crystalline regions, but due to its simplicity and robustness, the two-phase 79

model is still commonly employed. 80

While XRD is the only method that can measure long-range crystalline order, there are a 81

number of methods available to measure short-range double helical order in starch. DSC 82

measures the enthalpy change associated with gelatinisation of starch, as gelatinisation 83

involves the disruption of ordered regions in the granule, and therefore the magnitude of the 84

enthalpy change is proportional to the amount of ordered structure. Early work assumed that 85

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the enthalpy change was predominantly the result of crystallite melting, and was in essence a 86

direct measure of long-range crystalline order (Biliaderis, Page, Maurice & Juliano, 1986; 87

Donovan, 1979; Liu, Lelievre & Ayoung-Chee, 1991). More recent studies, however, have 88

indicated a more complex picture, in which the contribution from disruption of crystalline 89

order is only one small component, with contributions to the overall enthalpy change also 90

coming from swelling, hydration and disruption of short-range double helical structure, and 91

that gelatinisation is a kinetic event that is dependent on both heating rate and water content 92

(Bogracheva, Meares & Hedley, 2006; Cooke & Gidley, 1992; Gidley, 1992). The enthalpy 93

change associated with starch gelatinisation, under standard conditions, can therefore be used 94

as an indicator of ordered structure, but any further inferences regarding long-range 95

crystallinity should be drawn with caution. 96

In the mid-1980’s Gidley and Bociek (Gidley & Bociek, 1985) noted that the 13

C CP-MAS 97

NMR spectra of starch shows differences in chemical shift displacements due to changes in 98

the conformation of the glucan chain. These changes were particularly pronounced at the C1 99

and C4 positions, and were observed between amorphous starch polymers and double helices, 100

and between A and B type crystalline starch. This observation was subsequently exploited to 101

allow direct quantification of the proportion of double-helices in starch, giving a direct 102

measure of short-range order (Cooke & Gidley, 1992). This method has subsequently been 103

refined through use of peak fitting procedures and, more recently, chemometric approaches to 104

give a reliable estimate of ordered structure (Flanagan, Gidley & Warren, 2015; Tan, 105

Flanagan, Halley, Whittaker & Gidley, 2007). It has been consistently noted that the 106

proportion of double-helices in starch is greater than the amount of crystallinity, suggesting 107

that there are a significant proportion of double helices not in crystalline register (Cooke & 108

Gidley, 1992; Lopez‐Rubio, Flanagan, Gilbert & Gidley, 2008). 109

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More recently, FTIR-ATR has been suggested as a method to measure short range order in 110

starch, and even as an “infrared crystalline phase index” (Capron, Robert, Colonna, Brogly & 111

Planchot, 2007; Sevenou, Hill, Farhat & Mitchell, 2002; Van Soest & Vliegenthart, 1997). 112

FTIR-ATR has some notable advantages over other commonly used methods for measuring 113

starch structure- the equipment is relatively cheap, simple to use and maintain, and offers 114

highly flexible sample presentation. The ATR accessory gives the flexibility to analyse starch 115

samples in a range of physical forms, particularly in the hydrated state, making it possible to 116

observe spectral differences due to the level of hydration. Using microspectroscopy, these 117

advantages can also be applied to microscopically-localised regions within samples, in 118

contrast to the other methods which give bulk average data. The FTIR spectra of starch 119

typically shows bands at 2900-3000 cm-1

(C-H stretching), 1100-1150 cm-1

(C-O, C-C and C-120

O-H stretching) and 1100-900 cm-1

(C-O-H bending). It is not possible to assign bands in the 121

spectra of starch unambiguously, as the absorbance bands are overlapping and poorly 122

resolved (Van Soest & Vliegenthart, 1997). The bands in the region 1100-900 cm-1

have been 123

shown to be sensitive to changes in starch structure, in particular bands at 1000, 1022 and 124

1047 cm-1

have been widely studied, using a range of samples including retrograded starches 125

(Wilson, Kalichevsky, Ring & Belton, 1987), mixtures of starch and amorphous maltodextrin 126

(Van Soest & Vliegenthart, 1997), enzyme hydrolysed starches (Sevenou, Hill, Farhat & 127

Mitchell, 2002) and acid hydrolysis residues (‘lintners’) (Capron, Robert, Colonna, Brogly & 128

Planchot, 2007). From these studies, the band at 1022 cm-1

seems to increase in more 129

amorphous samples, while the bands at 1000 and 1047 cm-1

become more defined in more 130

crystalline samples. This has led to the adoption of the band ratios at 1022:1000 cm-1

and 131

1047:1022 cm-1

as measures of short-range ordered molecular structure in a range of different 132

studies (Bello-Pérez, Ottenhof, Agama-Acevedo & Farhat, 2005; Brümmer, Meuser, van 133

Lengerich & Niemann, 2002; Iizuka & Aishima, 1999; Rubens, Snauwaert, Heremans & 134

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Stute, 1999; Smits, Ruhnau, Vliegenthart & van Soest, 1998). Using chemometric 135

approaches, this procedure has been taken further, demonstrating the hydration sensitivity of 136

the 1022:1000 cm-1

intensity ratio and the possible relationship between crystallinity 137

measured by XRD and FTIR band ratio (Capron, Robert, Colonna, Brogly & Planchot, 2007). 138

Capron and co-workers (Capron, Robert, Colonna, Brogly & Planchot, 2007) found the 139

absorbance at 1047 cm-1

to be essentially independent of the degree of structure in the starch. 140

They linked the hydration sensitivity of the 1022:1000 cm-1

band ratio to the model liquid-141

crystalline polymeric model of starch structure proposed by Waigh and co-workers (Waigh, 142

Kato, Donald, Gidley, Clarke & Riekel, 2000; Waigh, Perry, Riekel, Gidley & Donald, 143

1998). This led to the suggestion that the change in the 1022:1000 cm-1

band ratio upon 144

hydration of crystalline (but not amorphous) starches is the result of a nematic-smectic 145

transition. Warren and co-workers (Warren, Perston, Royall, Butterworth & Ellis, 2013) 146

recently investigated the spectral changes that occur during in situ hydrothermal 147

gelatinisation of starch. Their findings showed that changes in the spectra during 148

gelatinisation can accurately determine the gelatinisation temperature reflecting the loss of 149

ordered structure. The intensity ratio of the bands at 1022:1000 cm-1

proved a useful tool to 150

monitor loss of structure, but a detailed appraisal of the spectra suggested greater complexity, 151

with an apparent peak position shift during gelatinisation. 152

In the present study, we examine a wider range of starches than has previously been used in 153

any single structural study of starch, including native wild type, mutant, amorphous, and 154

extruded starches, both in the dry and hydrated states. Using this extensive sample set, we 155

aim to develop a detailed understanding of the changes that occur in the FTIR spectra of 156

starches with different levels of molecular structure using chemometric analysis tools in 157

addition to peak ratio analysis, to improve the use of FTIR-ATR as a tool to understand 158

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starch ordered structure. The starch samples are also analysed using 13

C CP/MAS NMR, 159

XRD and DSC to explore short-range and long-range molecular order in starch. 160

2. Materials and Methods 161

2.1. Materials 162

Commercially available starches: regular maize, gelose 80 (high amylose) maize and mazaca 163

waxy maize were purchased from National Starch (Australia), waxy maize was bought from 164

Penford (Australia) and potato starch was purchased from National Starch and Chemicals 165

(UK). All commercially obtained starches were used without further treatment. All other 166

starches were gifts from collaborators and were from a range of botanical sources, including 167

native barley and barley mutants (Higgins et al., 2013; Regina et al., 2012) and wild rice and 168

rice mutants (Butardo et al., 2011). Due to the limited amount of mutant rice samples, whole 169

flours were used rather than isolated starches. Additional starch samples were produced under 170

different drying conditions (Zhang et al., 2014), and using extrusion to add variation to the 171

sample set (Zhang, Dhital, Flanagan, Luckman, Halley & Gidley, 2015). Wheat starch 172

(Cerestar, cv. GL04) and pea starches (WT, r and lam (Wang, Bogracheva & Hedley, 1998)) 173

were gifts from Prof. T. Bogracheva and Prof. C. Hedley (formerly of the John Innes Centre, 174

Norwich, UK), waxy rice starch (cv. Remyrise) was a gift from Dr. P. Rayment (Unilever, 175

UK); these starches are described in detail elsewhere (Warren, Royall, Gaisford, Butterworth 176

& Ellis, 2011). Native starch powders from tapioca (Penford, Ausralia), regular maize 177

(Penford, NZ), waxy maize (Tate and Lyle, Decatur, IL), high amylose maize (HylonVII, 178

Penford, Australia), potato, and wheat (both commercial material, supermarket, Sydney, 179

Australia) were gifts from Dr. E.P. Gilbert (ANSTO, Australia) (Doutch & Gilbert, 2013). 180

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Amorphous starches were prepared following the method of Gidley and Bociek (Gidley & 181

Bociek, 1985) with minor adjustments. Briefly, starches were boiled in water (1% w/v) for 30 182

minutes and precipitated with ethanol or rapidly frozen in liquid nitrogen and lyophilised. 183

Moisture contents were measured by weighing approximately 200mg of sample into a 184

crucible, drying the sample for 18 hours in an oven at 105°C. The resultant weight of the 185

sample was recorded and the difference in weight is taken as the moisture content. 186

The amylose contents of the samples were measured according to the iodine binding method 187

of Knutson (Knutson 1986; Knutson and Grove 1994; Knutson 2000). In this analysis starch 188

samples were dissolved overnight by shaking in a 6 mM iodine solution which was made by 189

first dissolving iodine in 9 parts DMSO then adding 1 part water. Once the starch had 190

dissolved, the solution was diluted in 8 parts H2O. After 30 min the iodine-amylose complex 191

formed a stable colour and the absorbance of the starch samples and amylose standards was 192

read spectrophotometrically at 600 nm against the reagent blank. 193

2.2. Fourier transform infrared spectroscopy 194

All spectra were collected using a PerkinElmer Spectrum One FTIR spectrometer fitted with 195

a PerkinElmer UATR single bounce ATR accessory with a diamond crystal. Data were 196

collected by an attached computer running PerkinElmer Spectrum 6 software. Dry starches 197

were equilibrated at laboratory humidity (50 % RH) and clamped directly onto the crystal for 198

analysis. Hydrated starches were made into a slurry by mixing with deionised water (50% 199

w/w), and added to the top of the crystal. Spectra of hydrated starches were obtained without 200

applying pressure. 32 spectra were obtained and co-added for each sample at a resolution of 4 201

cm-1

. A background spectrum was obtained by collecting 32 co-added scans following 202

cleaning of the crystal with a mixture of ethanol and water. The spectra were vector 203

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normalized by dividing each spectrum by the standard deviation of its absorbance values 204

(with mean subtraction), prior to subsequent analysis (SNV normalisation). 205

2.3. Wide Angle X-Ray Diffractometry 206

X-ray diffraction measurements were performed with an X’Pert Pro X-ray diffractometer 207

(XRD) (PANalytical, Almelo, the Netherlands) operating at 40 kV and 40 mA with Cu Kα 208

radiation (λ) at 0.15405 nm. The scanning region was set from 2θ = 3 to 2θ = 40 with a step 209

interval of 0.02 and a scan rate of 0.5/min. The crystalline peak area and amorphous area 210

were separated by PeakFit software (Version 4.12, Systat Software Inc., San Jose, CA, USA) 211

following the method of Lopez-Rubio, Flanagan, Shrestha, Gidley and Gilbert (2008) 212

Relative crystallinity was calculated as the ratio of the crystalline peak area to the total 213

diffraction area. 214

2.4. 13

C CP/MAS Nuclear Magnetic Resonance Spectroscopy 215

All starches were analysed by 13

C cross-polarized magic angle spinning (CP/MAS) nuclear 216

magnetic resonance (NMR) spectroscopy, using a Bruker MSL-300 spectrometer (Bruker, 217

Billerica, MA, USA) at a frequency of 75.46 MHz. Depending on availability, up to 200 mg 218

starch was packed in a 4-mm diameter, cylindrical, PSZ (partially stabilized zirconium oxide) 219

rotor with a Kel-F end cap. When as little as 50 mg of starch was available, the rotor was 220

packed with Teflon tape above and below the sample to maximize signal and ensure correct 221

spinning. The rotor was spun at 5 kHz at the magic angle (54.7°). The 90° pulse width of 5 μs 222

and a contact time of 1 ms were used for all starches with a recycle delay of 3 s. The spectral 223

width was 38 kHz, the acquisition time was 50 ms, 2 k points were recorded, and zero-filled 224

to 4 k before transformation. Exponential adopization resulting in 20 Hz of line broadening 225

was used. At least 1000 scans and up to 2000 scans were accumulated for each spectrum. 226

Spectral acquisition and interpretation methodology as described by Tan, Flanagan, Halley, 227

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Whittaker and Gidley (2007) and Flanagan, Gidley and Warren (2015) were used to quantify 228

the double helices, single helices, and amorphous conformational features. 229

2.5. Differential Scanning Calorimetry 230

All DSC data were obtained using a TA Instruments Q2000 instrument, using Tzero 231

hermetically sealed aluminium pans. The sample chamber was purged with nitrogen gas at a 232

rate of 40 mL/min. The instrument was calibrated for temperature using indium and tin 233

standards. Samples were prepared in triplicate by accurately weighing approximately 5 mg of 234

starch with 40 mg of deionised water into a pan, mixing, sealing and leaving overnight to 235

equilibrate. Samples were heated from 10 to 95°C at a rate of 5°C/min. Subsequent 236

thermograms were analysed using TA Instruments Universal Analysis software to obtain 237

gelatinisation enthalpies, as described elsewhere (Bogracheva, Wang, Wang & Hedley, 238

2002). 239

2.6. Data analysis 240

Preparation of figures, statistical analyses and linear regression fitting was carried out using 241

Sigma Plot 13 (Systat, USA). Principal component analysis (PCA) was carried out using 242

Unscrambler X 10.3 (Camo, Norway). 243

3. Results 244

3.1. Analytical data 245

DSC, XRD and 13

C CP/MAS NMR data were obtained for a total of 61 starch samples. The 246

mean DSC enthalpy of the sample set was 9.0 J/g with a range from 0 to 17.6 J/g. 13

C 247

CP/MAS NMR spectra were analysed to calculate total helical order for each of the samples. 248

The mean helical order in the sample set was 30.0 % with range from 4 to 49 % total helical 249

order. XRD data were analysed to obtain relative crystallinity, and the sample set had a mean 250

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of 25.8 % with a range from 0 to 51 % relative crystallinity (see Supporting Information 251

Table S1 for full data sets). 252

3.2. Fourier transform infrared spectra 253

Spectra were collected for the starch sample set used in the present study, and are shown in 254

Figures 1 A and B for the dry and hydrated samples, respectively. The hydrated samples 255

showed much more pronounced peaks at 3000-3700 cm-1

, 2000-2250 cm-1

and 1500-1750 256

cm-1

, as well as a pronounced baseline slope below 900 cm-1

as a result of adsorption by 257

excess water. The dry samples showed a large number of adsorption bands in the region 258

1700-1200 cm-1

presumably arising from minor components (protein, lipid) in the starch, as 259

well as the CH- stretch peaks at approximately 2900 cm-1

, which were masked by the large 260

water adsorption bands in the hydrated samples. The amide I and amide II peaks at 1640 and 261

1530 cm-1

are particularly prominent in the rice flour samples, which have a lower degree of 262

purity, and reflect their slightly elevated protein content. The major adsorption bands arising 263

from starch can be observed in the region 1200-1000 cm-1

, arising from C-O, C-C and C-O-H 264

stretching and C-O-H bending, as discussed in the introduction. A visual inspection of the 265

spectra indicates that there is significant variation between the different spectra in the region 266

1200-1000 cm-1

, and that the hydrated starches showed significantly more variation in this 267

region than the dry samples. Both the hydrated and dry sample sets were subjected to PCA 268

and the loadings for the first and second principal components (PC) are shown in Figure 2. 269

For the hydrated starches, the loadings for the first and second PC’s (Figure 2A and B) show 270

that the majority of the variance in the spectra occurs in the region 1000-1030 cm-1

. The same 271

can be observed for dry samples (Figure 2C and D), although the loadings for PC 2 (Figure 272

2D) also show a number of peaks in the region 1700-1200 cm-1

. This confirms the findings of 273

Capron et al. and Sevenou et al., (Capron, Robert, Colonna, Brogly & Planchot, 2007; 274

Sevenou, Hill, Farhat & Mitchell, 2002) using an extended data set, that the 1000-1022 cm-1

275

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region is the main source of variation in the spectra of starch, and that there is significant 276

water sensitivity in the spectra. 277

278

279

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280

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281

282

283

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3.3. Relationship between peak height ratios and ordered structure from other analytical 284

methods 285

As previously discussed, a number of authors have suggested that the peak ratios 995:1022 286

and 1045:1022 cm-1

may be useful indicators of ordered structure in starch. In the present 287

study, these two peak ratios have been systematically investigated for correlation against data 288

from DSC, XRD and 13

C CP/MAS NMR, to investigate if they can be used as predictors of 289

ordered molecular structure in starch (Table 1 and, Supplementary Information Table S1 and 290

Figure S1). In the dry state, there are correlations between both peak ratios and all three 291

analytical methods, although these are all weak correlations. The root mean square error of 292

calibration (RMSEC) (Table 1 and 2) for all of these models are large, representing errors of 293

greater than 25 % for the average sample in the calibration set. 294

Table 1. Fitting parameters for correlations between selected FTIR peak ratios and measures 295

of starch ordered structure for hydrated starches 296

Analytical

method

Ratio r2

(Calibration) RMSEC P value

DSC 995:1022 0.68 2.83 J/g <0.001

NMR 995:1022 0.48 9.53 % <0.001

XRD 995:1022 0.48 8.61 % <0.001

DSC 1045:1022 0.001 5.02 J/g 0.81

NMR 1045:1022 0.006 13.25 % 0.57

XRD 1045:1022 0.006 11.92 % 0.57

297

Table 2. Fitting parameters for correlations between selected FTIR peak ratios and measures 298

of starch ordered structure for dry starches 299

Analytical

method

Ratio r2

(Calibration) RMSEC P value

DSC 995:1022 0.42 3.64 J/g <0.001

NMR 995:1022 0.31 11.34 % <0.001

XRD 995:1022 0.39 9.50 % <0.001

DSC 1045:1022 0.44 3.17 J/g <0.001

NMR 1045:1022 0.59 8.32 % <0.001

XRD 1045:1022 0.48 8.53 % <0.001

300

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For the hydrated starch samples, the peak ratio 1045:1022 cm-1

showed no correlation with 301

any of the analytical methods employed in this study. The 1022:995 cm-1

peak ratio showed a 302

correlation with all three analytical methods, and the best correlation (r2 0.69) for any of the 303

peak ratios in either the hydrated or dry states was observed for the relationship between the 304

hydrated starch 1022:995 cm-1

ratio and DSC enthalpy for the same starch samples. To 305

further investigate the relationship between these peak ratios and measures of ordered 306

structure, heat map plots were generated (Figure 3) in which the spectra have been ranked 307

according to DSC enthalpy from high to low, and then plotted in series, with high absorbance 308

values shown as “hot” colours (reds and yellows) and low absorbance values shown as “cold” 309

colours (greens and blues). 310

311

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312

The hydrated starch spectra (Figure 3a) show a pronounced peak position shift, with the most 313

intense peak moving from around 1000 cm-1

in starches with a high order (above 14 J/g) to 314

1020 cm-1

in starches with low order (less than 10 J/g).The bi-plot from the PCA analysis of 315

the hydrated starches (Figure 4) confirms this, showing that the high and low ordered starches 316

divide into two groups. The dry starches show a similar, but much less pronounced, peak 317

position shift. 318

319

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4. Discussion 320

In the present study we have subjected a very wide range of starch samples to a range of 321

commonly used analytical methods (XRD, NMR, DSC and FTIR-ATR). This was carried out 322

with the aim of exploring the use of FTIR-ATR as a general method for the analysis of starch 323

ordered structure, and to build calibrations allowing direct quantification of starch ordered 324

structure. 325

The speed and flexibility in sample presentation of FTIR-ATR make it an attractive 326

alternative to conventional analysis methods, and it has received wide use, but few authors 327

have attempted to validate FTIR-ATR as a quantitative method (Capron, Robert, Colonna, 328

Brogly & Planchot, 2007). The starch samples used in the present study cover the full range 329

of levels of ordered structure that would be commonly encountered in the study of starch 330

structure, from fully amorphous hydrothermally treated or extruded starches through to native 331

tuber starches with levels of crystallinity measured by XRD to be as high as 51%. The 332

samples come from a wide range of botanical origins, including genetic mutants, allowing a 333

thorough assessment of the expected variation in FTIR-ATR spectra. 334

It is clear that large variability exists across FTIR-ATR spectra of different starches, and 335

Figure 3 highlights this variation. A key observation is that in the hydrated state there is a 336

pronounced peak position shift from around 1022 cm-1

to around 1000 cm-1

between the low 337

and high ordered starches, and that this change is far less pronounced for starch in the dry 338

state, where all but the most amorphous samples have a mean absorbance peak at around 339

1000 cm-1

. Thus, for starch in the hydrated state, it is possible to use the 1000:1022 cm-1

peak 340

ratio to indicate (but not to fully quantify) whether a starch has high or low levels of ordered 341

structure. The peak position shift from 1000 to 1022cm-1

is the most dramatic change in the 342

spectra as a result of changes in ordered structure, far more so than those at 1045 and 1080 343

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cm-1

, which have been suggested by some authors to be alternative indices of ordered 344

structure (Rubens, Snauwaert, Heremans & Stute, 1999). This is observation in good 345

agreement with previous work (Warren, Perston, Royall, Butterworth & Ellis, 2013) 346

demonstrating that when native (and therefore ordered) starch in excess water undergoes 347

hydrothermal treatment to an amorphous form there is a distinct peak position change from 348

1000 to 1022 cm-1

. 349

It is possible to speculate on the reasons for this peak shift occurring, and as to why it may be 350

more pronounced in hydrated samples as opposed to dry samples. It is well established that 351

hydration of the starch granule leads to significant structural rearrangements (Waigh, Gidley, 352

Komanshek & Donald, 2000; Waigh, Kato, Donald, Gidley, Clarke & Riekel, 2000) at longer 353

length scales (10-100 nm) than are directly probed by infrared spectroscopy. From the data in 354

the present paper, and from previous work (Capron, Robert, Colonna, Brogly & Planchot, 355

2007), these starch structural rearrangements have a significant impact at the scale of 356

individual chemical bonds probed by infrared spectroscopy. It is interesting to note that for 357

FTIR spectra collected from hydrated samples, a considerably better correlation was seen 358

between the infrared spectra and DSC enthalpy, than NMR and XRD data (Table 1 and 3). 359

The DSC enthalpy change associated with starch gelatinisation is dependent, in a complex 360

manner, on a range of short range molecular interactions which are altered upon heating in a 361

hydrated environment (Cooke & Gidley, 1992). It may be speculated that the FTIR spectra of 362

hydrated samples reflects these short range interactions, rather than the longer range 363

associations which result in the formation of helices (detected by NMR), and the arrangement 364

of these helices into crystalline arrays (detected by XRD), although clearly structures 365

detected at all these length scales contribute to the overall structure of the starch granule. 366

5. Conclusions 367

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The present study uses a wider range of starch samples than has been available in previous 368

studies to compare different measures of starch ordered structure, with the aim of probing the 369

relationship between FTIR spectra of starch in the dry and hydrated states, and other 370

measures of starch ordered structure. It has been confirmed that in the spectra of hydrated 371

starch, the main difference between starches with high and low degrees of order is a peak 372

position shift from 1000 to 1022 cm-1

, but using the wide range of starches available in this 373

study it has been shown that there is a more complex relationship between infrared spectra of 374

starches with different degrees of order than has previously been appreciated. There is a clear 375

and distinct shift in the spectra, in particular of hydrated starches, as starch molecular order 376

increases, however this is a non-linear transition. While this complexity means that FTIR 377

spectra cannot be used directly in place of alternative quantitative measures of starch 378

structure, we demonstrate the feasibility of using FTIR to characterise short range molecular 379

interactions in starch, so long as care is taken in the analysis of the spectra. 380

6. Acknowledgements 381

We acknowledge the facilities, and the scientific and technical assistance of the Australian 382

Microscopy & Microanalysis Research Facility at the Centre for Microscopy and 383

Microanalysis for XRD measurements, and the NMR facilities at the Centre for Advanced 384

Imaging at The University of Queensland. We would like to thank Barbara Gorham from the 385

Centre for Nutrition and Food Science at The University of Queensland for her assistance in 386

measuring the starch moisture contents.387

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388

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Figure legends 496

Figure 1. Overlay SNV normalised FTIR-ATR spectra for all the starch samples analysed in 497

dry (A) and hydrated (B) states. The spectra have been zoomed to show the fingerprint region 498

(full spectra inset). 499

Figure 2. Principal component loadings for the PCA analysis of complete sample sets for dry 500

and hydrated starch FTIR-ATR spectra. A and B hydrated starch, PC1 and PC2 respectively; 501

C and D dry starch, PC1 and PC2 respectively. 502

Figure 3. Heat map plots of the SNV normalised FTIR-ATR spectra for the starch samples 503

used in this study. The spectra have been plotted relative to DSC enthalpy (y-axis) and 504

absorbance intensity is shown in colours, with “hot” colours (reds and yellows) indicating 505

high absorbance and “cool” colours (blues and greens) indicating low absorbance. A; 506

hydrated starch samples, B; dry starch samples. 507

Figure 4. Bi-plot showing the first two PC’s for a PLS model of the hydrated FTIR-ATR 508

spectra. Samples with a DSC enthalpy below 10 J/g have been marked with circles. 509