Comparative study and characterization of starches ...

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chains are localized every 15 – 25 linear units of glucose. [1, 2] . After cellulose .... reported by Mali et al., Alvis et al. and Nwokocha and. Williams [33 – 35] .
DOI 10.1515/polyeng-2012-0092      J Polym Eng 2012; 32: 531–537

Germán Ayala Valencia, Ana Cecilia Agudelo Henao* and Rubén Antonio Vargas Zapata

Comparative study and characterization of starches isolated from unconventional tuber sources Abstract: Some properties of canna (Canna indica L.) and bore (Alocasia macrorrhiza) starches were evaluated and compared using cassava starch (Manihot esculenta Crantz) as a reference. Proximate analysis, differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) and viscosity measurements were performed. Canna and bore starches showed a similar degree of purity as that of the cassava starch. Canna starch exhibited higher thermal stability and viscosity of solution values than those of bore and cassava starches. XRD spectra showed that canna starch crystallizes as a B-type structure; however, bore and cassava starches crystallize as an A-type structure. Results proved that canna and bore starches are promising bio(materials), obtained from unconventional sources, to be used for industrial applications, as their physicochemical properties are similar to those of cassava starch, which it is known has potential applications in this area. Keywords: Alocasia macrorrhiza; Canna indica L.; nonfood industrial applications; physicochemical properties.

*Corresponding author: Ana Cecilia Agudelo Henao, Facultad de Ingeniería y Administración, Universidad Nacional de Colombia, sede Palmira. A.A. 237, Palmira, Colombia, e-mail: [email protected] Germán Ayala Valencia: Basic Sciences Department ZAB/FZEA, University of São Paulo, Av. Duque de Caxias Norte 225, 13635-000, Pirassununga, SP, Brazil Rubén Antonio Vargas Zapata: Facultad de Ciencias Naturales y Exactas, Universidad del Valle. A.A. 25360, Cali, Colombia

1 Introduction Starch is a biopolymer composed of amylose and amylopectin, in which amylose has a linear polymer structure of essentially α-1,4 d-glucopyranosyl units. Amylopectin is a polysaccharide composed of linear α-1,4 d-glucopyranosyl chains and a large number of short chains linked together

at their reducing end side by an α-1,6 linkage; these short chains are localized every 15–25 linear units of glucose [1, 2]. After cellulose, starch is the most abundant carbohydrate in nature, and it is found in specialized tissues of plants as an energy reserve. It is currently used in industrial applications, due to its easy and economic extraction process, being the basic source of energy provided to humans with food (50–65%) and extensively applied in food industry [3, 4]. In addition, starch is used in textiles, adhesives, and thermoplastic applications, due to its flexibility and strength when it is mixed with plasticizers [5–7]. It is also used in pharmacy, hygiene products, environmental management, agriculture, biomedical engineering and biofuel production [8–10]. Recently, starch was used for the synthesis and stabilization of metal nanoparticles as gold, silver and palladium, for different applications in nanobiomedicine, food conservation and the development of biosensors [11–14]. The main sources of starch are corn (Zea mays), cassava (Manihot esculenta Crantz), wheat (Triticum aestivum L.), rice (Oryza sativa L.) and barley (Hordeum vulgare L.). Among these, cassava starch is known for its physical and chemical characteristics, since it presents a low gelatinization temperature (T ∼71°C), low tendency to retrogradation, low content of residual materials as proteins and fats, resistance to cycles of freezing/thawing, high viscosity and water retention, translucency of paste and good gels stability [15, 16]. Due to these characteristics, the marketing of the main sources of starch does not keep a permanent balance between offer and demand in different countries [17], therefore, it is necessary to evaluate new sources of starch that can have industrial applications [18–21]. Some tuber and root starches are not widely used in food applications in different countries, due to their poor functional properties. Some regions in Colombia use canna starch in human feed, and it is basically oriented to the artisanal production of bread and its derivatives; bore starch is not used for human feed. Bore leaves are used mainly for animal feed. In this study, we characterized native canna and bore starches that do not have industrial applications; they could be applied in the non-nutritious

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532      G.A. Valencia et al.: Comparative study and characterization of starches

industrial sector. As we reported previously, starches can be used as raw materials for the development of solid electrolytes, polymers [22–24] being an interesting field of non-food applications in which to use tubers and root starches. It is known that the possible industrial applications of starch are determined by its physical and chemical properties, such as the amylose/amylopectin relation, molecular weight, long chain, thermal and rheological properties, and these properties can be modified by non carbohydrate impurities [21, 25]. Food and non-food industries require the evaluation of new starch sources. In this field, the use of tubers as canna (Canna indica L.) and bore (Alocasia macrorrhiza), which are composed basically of starch, could be interesting. The aim of this work is to characterize some properties of the native starches of canna and bore, and compare their behavior by using cassava starch HCM-1 as a reference.

2 Materials and methods 2.1 Raw materials Cassava starch HCM-1 was provided by the International Center for Tropical Agriculture (CIAT, Colombia), canna starch was purchased from the Piendamó municipality (Cauca-Colombia), bore starch was obtained from a bore crop in an experimental farm located at the Universidad Nacional de Colombia, Palmira Campus, and starch was isolated following the preparation method reported by Alarcon and Dufour [8].

(4–8 mg), which was hermetically sealed. An empty aluminum pan was used as a reference. Pans were heated from 0°C to 250°C at a rate of 10°C/min. The calibrations of DSC temperature and heat flow were done according to standard ASTM [31], using pure indium (melting point 156.4°C), with the same heating rate used for the DSC measurements (10°C/min). The transition temperatures (onset, To; peak, Tp and conclusion, Tc) of the observed thermal events were determined from the DSC curves by means of Universal Analysis 2000 software provided by the TA Company. Calorimetric enthalpy (ΔH) associated with the thermal events was determined by numerical integration of the area under the peak of thermal transition. All starches were studied at least twice.

2.4 Thermogravimetric analysis (TGA) TGA measurements were made using a thermogravimetric analyzer (TGA 2920, TA Instruments), under a flow of dry N2 (50 ml/min). The samples were weighed directly into an aluminum pan (2–5 mg). Pans were heated from 25 to 325°C at a rate of 10°C/min. The weight loss and weight derivatives were determined from the TGA curves by means of the Universal Analysis 2000 software provided by TA Instruments. All starches were studied at least twice.

2.5 Fourier-transform infrared (FTIR) spectroscopy

Humidity, ash and crude fat were analyzed using the AOAC methods [26–28]; crude protein was examined using the Kjeldahl method [29], and crude fiber was determined using the Van Soest method [30]. Total carbohydrate content was calculated by the difference. These determinations were performed at least twice.

FTIR spectra were obtained using a FTIR spectrometer (Shimadzu Prestige 21, Shimadzu, Kyoto, Japan). Samples were prepared using the standard KBr pellet technique. A previous calibration of the instrument was made by recording the KBr pellet spectrum, which was used to determine the background of the samples spectra. The spectra of the starch samples in the form of tablets with a 1:10 ratio with respect to KBr (using the same amount of material as that of initial pure KBr), were recorded in transmission mode from 4000 to 400 cm-1, with spectral resolution of 4 cm-1 at room temperature. Spectra were averaged over 60 scans.

2.3 Differential scanning calorimetry (DSC)

2.6 X-ray diffraction (XRD)

DSC measurements were made using a modulated differential scanning calorimeter (MDSC 2920, TA Instruments, New Castle, DE, USA), under a flow of dry N2 (50 ml/min). The samples were weighed directly into an aluminum pan

The XRD spectra of starches were obtained with an X-ray diffractometer (Bruker D8 Advance, Bruker AXS, GMBH, Karlsruhe, Baden-Württemberg, Germany), with Bragg-Brentano configuration cpn vertical goniometer,

2.2 Proximate analysis

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G.A. Valencia et al.: Comparative study and characterization of starches      533

operating at 35 kV and 30 mA (CuKα1 λ = 0.1541 nm radiation). The spectra were recorded at 25°C for a dispersion angle between 2.5° to 60° (2θ). The interplanar space d (nm) was determined from the diffraction angle in the X-ray spectra and using the Bragg law: nλ = 2dsinθ, where λ, is the wavelength and n is the reflection order (n = 1). All starches were studied at least twice.

2.7 Rheological properties Rheological properties were measured using a viscometer (DV-E Brookfield, Middleboro, MA, USA). Starch solutions were prepared from the gelatinization of 3 g of each starch in 100 ml of distilled water. The solutions were thermally treated at 95 ± 1°C, during 30 min, in sealed containers to prevent moisture loss. After this treatment, the solutions were filtered using a filter with a pore size of 250 μm, and then cooled to 25°C (∼30 min). The rheological study was performed using specific spindles S-61, S-62 and S-63, with a rotational speed between 0.3 and 100 rpm. All analyses were studied at least twice using the Brookfield viscometer between 20% and 80% full torque scale.

3 Results and discussions 3.1 Proximate analysis The proximate analysis results of canna, bore and cassava starches are shown in Table 1; they are expressed on a dry basis. The moisture content values in starches are in a range between 10.61 to 13.60%. Ahmad et al. [32] reported values of moisture content around 12% for starches at environmental conditions. The content of ash, crude protein, crude fat and crude fiber of original starch were determined. Cassava starch shows a similar composition reported by Mali et al., Alvis et al. and Nwokocha and Williams [33–35]. The proximate analysis for canna starch shows different values of crude protein, crude fat and crude fiber reported in the literature for roots, flour and starch [36, 37]. Proximate analysis shows high values of total carbohydrates for all starches. Information Starch Canna Bore Cassava

about proximate analysis of Alocasia macrorrhiza is not available.

3.2 Differential scanning calorimetry (DSC) Figure 1 shows a representative plot of heat flow vs. temperature between 0°C and 260°C obtained by a differential scanning calorimeter (DSC), for the starches hydrated under room conditions (humidity ∼12%). The thermal characteristics of canna, bore and cassava starches show a range of gelatinization temperature between 17°C and 165°C (Table 2); all DSC curves show a broad endothermic peak on heating, which is associated with this thermal event at low water content [38]. Table 2 summarizes the enthalpy change (ΔH) and the corresponding peak’s temperature for all starches; high enthalpy values are due to a low presence of water in the starches, which acts as a plasticizer [39]. The enthalpies are given in J/g, by dividing the enthalpy obtained from the DSC data by the total mass of the sample. It should be emphasized that the measured enthalpy corresponds to the total energetic of molecular interactions of starch-water, i.e., of the amylose + amylopectin + water constituents, and not for the starch component only. Table 2 shows the enthalpy and transition temperatures of native canna, bore and cassava starches. The peak temperature, TP, of cassava starch was similar to that reported in literature [21, 33, 35, 40, 41]. The TP of canna starch was higher than the value reported by Hung and Morita [42] and Puncha-Arnon et al. [43]. The TP values reported for Canna edulis in those references are between 70 and 74°C. Canna, bore and cassava starches showed a glass transition temperature (Tg) at 18.01, 10.74 and 8.25°C, respectively.

3.3 Thermogravimetric analysis (TGA) Figure 2 shows the TGA spectra of canna, bore and cassava starches hydrated under room conditions (humidity ∼12%). All starches reveal three main weight loss regions. The first region in the 25–105°C temperature range is due to the evaporation of physically weakly and chemically

Moisture (%)

Ash (%)

Crude protein (%)

Crude fat (%)

Crude fiber (%)

Total carbohydrates (%)

12.07 ± 0.32 10.91 ± 0.02 13.60 ± 0.35

0.24 ± 0.01 0.40 ± 0.01 0.42 ± 0.10

0.60 ± 0.11 0.81 ± 0.17 0.61 ± 0.10

0.38 ± 0.05 0.50 ± 0.03 0.73 ± 0.36

0.39 ± 0.10 0.30 ± 0.05 0.60 ± 0.15

98.38 ± 0.27 97.99 ± 0.26 97.64 ± 0.71

Table 1 Proximate analysis of canna, bore and cassava starches.

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534      G.A. Valencia et al.: Comparative study and characterization of starches

(1) Canna starch (2) Bore starch (3) Cassava starch

16

Bore starch Humidity ~11%

8

4 Canna starch Humidity ~14%

0

-4 0

50

100

150

200

(3)

(1) Spanded scale

Heat flow (W/g)

Transmittance (%)

Cassava starch Humidity ~12%

12

(2)

4000

250

3500

T0 (°C)

TP (°C)

TC (°C)

ΔH (J/g)

Canna 34.98 ± 3.62 92.13 ± 0.22 164.55 ± 1.56 432.01 ± 3.80 Bore 26.30 ± 3.62 81.53 ± 2.13 162.35 ± 2.34 381.40 ± 6.40 Cassava 16.71 ± 0.14 63.01 ± 0.10 164.98 ± 1.99 338.02 ± 13.01 Table 2 Enthalpy (ΔH) and transition temperatures of native canna, bore and cassava starch.

strongly bound water [44]. The total weight loss of the starches is about 9–10 wt% at 105°C; however, the weight loss due to water evaporation is slightly less than that reported in section 3.1, indicating that a strongly bound water fraction of the starch structure still exists and it is not evaporated, probably due to the rapid rate of heating in the process (10°C/min). The second transition region between 105°C and 275°C shows an increasing degradation rate of the starches; similar results are reported [45]. The total weight loss in the second region is about

FTIR spectra are shown in Figure 3. All samples presented seven absorption bands characteristic of starches:

18°

Intensity (arbitrary units)

(1) Canna starch (2) Bore starch (3) Cassava starch (1) (3)

20 150

200

250

300

350

Cassava starch

Bore starch

5.9°

19.8° 22° 24° Canna starch

0

Temperature (°C)

Figure 2 Thermogravimetric analysis (TGA) curves for the native canna, bore and cassava starches.

23°

15.1°

Spanded scale

Weight (%)

60

100

500

3.4 Fourier-transform infrared (FTIR) spectroscopy

17°

80

50

1000

12–18 wt%, up to 275°C. The third weight loss region was observed above 275°C, and the maximum degradation rate of the starches is about ∼290°C. At the end of the heating process, the residual mass content for each starch (Mres) was calculated as a percentage of the original starch mass, i.e., canna, bore and cassava starch show a Mres of ∼30 wt%, ∼75 wt% and ∼20 wt%, respectively. For bore starch, a slight weight increase above 300°C was observed and attributed to the reaction of the residual mass starch with the dry N2 flowing through the DSC sample holder.

(2)

0

1500

Figure 3 Fourier-transform infrared (FTIR) spectra of native canna, bore and cassava starches.

100

40

2000

Wavelength (cm-1)

Figure 1 Differential scanning calorimetry (DSC) curves for the native canna, bore and cassava starches at low humidity content. Starch

2500

3000

Temperature (°C)

10

20

30 40 2θ (degree)

50

Figure 4 X-ray diffraction patterns of native canna, bore and cassava starches.

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60

G.A. Valencia et al.: Comparative study and characterization of starches      535

A

103

Shear stress (Pa)

Viscosity (cP)

104

103

102 0.01

Canna starch Bore starch Cassava starch 0.1

1

B

102 Canna starch Bore starch Cassava starch 101 0.01

0.1 Shear rate (1/s)

Shear rate (1/s)

1

Figure 5 Pseudoplastic behavior (A) and shear rate vs. shear stress relation in canna, bore and cassava starch solution, both in double logarithmic scale.

3.5 XRD XRD patterns of the native starches are shown in Figure 4. Bore and cassava starches showed a diffraction pattern of an A-type crystal, characterized by diffraction peaks at angles of 2θ = 15.1°, 17°, 18° and 23° [50], with interplanar spacing (d) of 0.59, 0.52, 0.49 and 0.39 nm, respectively. These results are similar to those reported by Jenkins and Donald [40] and Guratnane and Hoover [51]. Canna starch exhibits a diffraction pattern of a B-type crystal, characterized by diffraction peaks at angles of 2θ = 5.9°, 15.1°, 17°, 22° and 24° with interplanar spacing d = 0.15, 0.59, 0.52, 0.40 and 0.37 nm, respectively [50]. A B-type crystal has been previously reported by Hung and Morita [42] for starch from Canna edulis. For canna starch, a low intensity peak at angle 2θ = 19.8° (d = 0.45 nm) was observed, which is characteristic of starches with an amylose-lipids complex [52].

nature of the viscosity for canna, bore and cassava starch solutions. All solutions present a pseudoplastic behavior, where the hydrodynamic forces of spindle speed lead to a decrease in viscosity, due to a breakdown of amylose and amylopectin fragments in the solutions [54]. This behavior is characterized by the non-linear relation between shear rate and shear stress, such that an increase of shear rate leads to a slight increase of shear stress [55]. Canna solutions exhibited a higher viscosity and shear stress than those of bore and cassava solutions. The non-Newtonian behavior of starch solutions was reported by other researches [56–58]. Apparent viscosities, μa (Pa*s), of starch solutions were fitted to a power law: ln(μa) = (n - 1)ln(4πN)+ln(K)-nln(n)

(1)

where N is the spindle speed (rps), K is the consistency coefficient (Pa*sn), and n is the flow behavior index 10.0 Canna starch

9.5

Bore starch 9.0

Cassava starch

8.5 8.0 Ln (μa)

elongation of –OH groups between 3600 and 3200 cm-1; elongation of –CH groups between 2939 and 2919 cm-1; vibration of –OH groups of water present in the sample between 1653 and 1645 cm-1; torsion of –CH2 groups between 1465 and 1459 cm-1; flexion of –OH groups present in the starch between 1251 and 1239 cm-1; asymmetric elongation of C–O–C groups between 1082 and 1070 cm-1 and symmetric between 922 and 857 cm-1 [46–49].

7.5 7.0 6.5 6.0 5.5

3.6 Rheological properties

5.0 -2

Starch solution viscosity is the intermolecular force that restricts the molecular motion by applied external forces [53]. Figure 5 shows the non-Newtonian/shear thinning

-1

0

1 Ln(4πN)

2

3

Figure 6 Linear fitting to a power law model of the apparent viscosity [Eq. (1)] of native canna, bore and cassava starch solutions.

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536      G.A. Valencia et al.: Comparative study and characterization of starches

Parameters

n K

Starch solution Canna

Bore

Cassava

0.57 5150.01

0.51 557.13

0.38 302.70

Table 3 Flow behavior index (n) and consistency coefficient (K) values of native canna, bore and cassava starch solutions as obtained from the fitting to Eq. (1).

(dimensionless). For each starch, the flow behavior index and the consistency coefficient were determined from the slope and the intercept of the straight line, respectively; the results are presented in Figure 6 and Table 3. Canna solutions showed the highest flow behavior index and consistency coefficient values, which were followed by those presented by bore and cassava solutions, respectively. It is important to emphasize that our statistical analysis of the collected data by testing both the linear fitting to Eq. (1) and the standard deviation (σ), with respect to the mean value of each data point, showed that the data dispersion was not significant and fitted to the functional relation [Eq.(1)].

4 Conclusions The main feature of this study is the characterization of starches extracted from unconventional tuber sources, which in Colombia are abundant and they do not have many applications. Our physicochemical analysis of bore

and canna starch suggested that they have similar behaviors and structures to those of cassava starch (used as a reference). The results showed that canna, bore and cassava starches have a high purity and similar thermal behavior between 25 and 300°C, observed by TGA and DSC measurements that allowed observation of an endothermic thermal event associated to starch gelatinization at a low water content. Starches presented similar functional groups to those of A- and B-type crystal structures, which were verified by FTIR and X-ray spectra. By contrast, measurements of the rheological properties of solutions from the starches showed a pseudoplastic behavior. In summary, our results show that canna and bore starches are promising bio(materials) obtained from unconventional sources and can be used for industrial applications, owing to similar physicochemical properties to those of the cassava starch, which has been proved to have excellent properties for a wide range of applications. Acknowledgements: The authors gratefully acknowledge financial support from “Universidad Nacional de Colombia’’ “DIPAL’’ code number “QUIPU 2010100729 and 2020100626’’, and the “Laboratorio de Nutrición Animal, Universidad Nacional de Colombia-Palmira’’ for the use of installations. They are also grateful to Jefferson Paz N. Received August 10, 2012; accepted October 15, 2012; previously published online November 21, 2012

References [1] Badui Dergal, S, Eds., Química de los alimentos, 4th ed., Pearson, México, 2006. [2] Bhupinder K, Fazilah A, Rajeev B, Alias AK. Food Hydrocoll. 2012, 26, 398–404. [3] Cock, JH. Cassava: new potential for a neglected crop, Westview Press: Boulder, 1985, p. 12. [4] Thanh-Blicharz JL, Lewandowicz G, Błaszczak W, Prochaska K. Food Hydrocoll. 2012, 27, 347–354. [5] Sobral PJA, Santos JS, García FT. J. Food Eng. 2005, 70, 93–100. [6] Jongjareonrak A, Benjakul S, Visessanguan W, Prodpran T, Tanaka M. Food Hydrocoll. 2006, 20, 492–501. [7] Teixeira EM, Da Róz AL, Carvalho AJF, Curvelo AAS. Carbohydr. Polym. 2007, 4, 619–624. [8] Alarcon, F, Dufour, D, Eds., Almidón agrio de yuca en Colombia: Producción y recomendaciones. 1st ed., Centro Internacional de agricultura Tropical (CIAT), Colombia, 1998. [9] Villada Castillo, HS, Ed., Influencia de mezclas de almidón agrio, perfil de temperatura y velocidad de tornillo de un extrusor sencillo en la producción de almidón termoplástico,

su caracterización físico-química, mecánica, microestructural y comportamiento frente al almacenamiento, Universidad del Valle: Calí, Colombia, Suramérica, 2005, pp. 14–112. [10] Lawal OS, Lechner MD, Kulicke WM. Polym. Degrad. Stab. 2008, 93, 1520–1528. [11] Raveendran P, Fu J, Wallen SL. J. Am. Chem. Soc. 2003, 125, 13940–13941. [12] Raveendran P, Fu J, Wallen SL. Green Chem. 2006, 8, 34–38. [13] Vigneshwaran N, Nachane RP, Balasubramanya RH, Varadarajan PV. Carbohydr. Res. 2006, 341, 2012–2018. [14] Engelbrekt C, Sorensen KH, Zhang J, Welinder AC, Jensen PS. J. Mater. Chem. 2009, 19, 7839–7847. [15] Mali S, Grossmann MVE. J. Agric. Food Chem. 2003, 51, 7005–7011. [16] Che LM, Li D, Wang LJ, Chen XD, Mao ZH. Int. J. Food Prop. 2007, 10, 527–536. [17] Nweke F. New Challenges in the Cassava Transformation in Nigeria and Ghana. EPTD Discussion Paper No. 118. International Food Policy Research Institute, USA, 2006.

Unauthenticated | 186.86.86.186 Download Date | 1/19/13 1:21 PM

G.A. Valencia et al.: Comparative study and characterization of starches      537

[18] Shiraishi K, Lauzon RD, Yamazaki M, Sawayama S, Sugiyama N, Kawabata A. Food Hydrocoll. 1995, 9, 69–75. [19] Sefa-Dedeh S, Kofi-Agyir Sackey E. Food Chem. 2002, 79, 435–444. [20] Lu T-J, Chen J-C, Lin C-L, Chang Y-H. Food Chem. 2005, 91, 69–77. [21] Nwokocha LM, Aviara NA, Senan C, Williams PA. Carbohydr. Polym. 2009, 76, 362–367. [22] Caicedo CH, Ayala G, Agudelo AC, Vargas RA. Rev. Colomb. Fís. 2010, 42, 439–448. [23] Ayala G, Agudelo CH, Paz J, Vargas RA. Ionics 2011, 17, 647–652. [24] Ayala G, Agudelo A, Vargas R. DYNA 2012, 79, 138–147. [25] Leach, HW, In Gelatinization of Starch. Starch: Chemistry and Technology, Whistler, RL, Paschall Eugene, F, Eds., Academic Press: New York, London, 1965, pp. 289–307. [26] Association of Official Analytical Chemists, Eds., Official Methods of Analysis, AOAC Method number: 920.39. 15th ed., Arlington, Virginia, USA, 1990. [27] Association of Official Analytical Chemists, Eds., Official Methods of Analysis, AOAC Method number: 934.01. 15th ed., Arlington, Virginia, USA, 1990. [28] Association of Official Analytical Chemists, Eds., Official Methods of Analysis, AOAC Method number: 942.05. 15th ed., Arlington, Virginia, USA, 1990. [29] Kjeldahl J. Z. Anal Chem. 1883, 22, 366–382. [30] Van Soest PJ, Wine RH. J. Ass. Official Agr. Chem. 1967, 50, 50–55. [31] Standard test method for transition temperatures of polymers by differential scanning calorimetry, Eds., Annual book of ASTM. V. 08.02, ASTM Method number: D3418. Philadelphia: ASTM, 2005. [32] Ahmad FB, Williams PA, Doublier JL, Durand S, Buleon A. Carbohydr. Polym. 1999, 38, 361–370. [33] Mali S, Grossmann MVE, García MA, Martino MM, Zaritzky NE. J. Food Eng. 2006, 75, 453–460. [34] Alvis A, Vélez CA, Villada HS, Mendoza MR. Inf. Tecnol. 2008, 19, 19–28. [35] Nwokocha LM, Williams PA. Carbohydr. Polym. 2009, 78, 462–468.

[36] Thitipraphunkul K, Uttapap D, Piyachomkwan K, Takeda Y. Carbohydr. Polym. 2003, 53, 317–324. [37] Andrade-Mahecha MM, Tapia-Blácido DR, Menegalli FC. Carbohydr. Polym. 2012, 88, 449–458. [38] Liu H, Xie F, Yu L, Chen L, Li L. Prog. Polym. Sci. 2009, 34, 1348–1368. [39] Blazek J, Salman H, Lopez AR, Elliot G, Hanley T, Copeland L. Carbohydr. Polym. 2009, 75, 705–711. [40] Jenkins PJ, Donald AM. Carbohydr. Res. 1998, 308, 133–147. [41] Ren G-Y, Li D, Wang L-J, Özkan N, Mao Z-H. Carbohydr. Polym. 2010, 79, 101–105. [42] Hung PV, Morita N. Carbohydr. Polym. 2005, 61, 314–321. [43] Puncha-Arnon S, Puttanlek C, Rungsardthong V, Pathipanawat W. Carbohydr. Polym. 2007, 70, 206–217. [44] Ruiz GA. Ing. Cienc. 2006, 2, 5–28. [45] Liu X, Yu L, Liu H, Chen L, Li L. Polym. Degrad. Stab. 2008, 93, 260–262. [46] Campbell, D, Pethrick, RA, White, IR, Eds., Polymer Characterization, 2nd ed., Stanley Thornes, England, 2000. [47] Huang ZQ, Lu JP, Li XH, Tong ZF. Carbohydr. Polym. 2007, 68, 128–135. [48] Kaewtatip K, Tanrattanakul V. Carbohydr. Polym. 2008, 73, 647–655. [49] Yuping W, Cheng F, Zheng H. Carbohydr. Polym. 2008, 74, 673–679. [50] Spence KE, Jane J. Carbohydr. Polym. 1999, 40, 261–269. [51] Guratnane A, Hoover R. Carbohydr. Polym. 2002, 49, 425–437. [52] Zobel HF. Starch-Stärke 1988, 40, 1–7. [53] Che L-M, Li D, Wang LJ, Özkan N, Chen XD, Mao Z-H. Carbohydr. Polym. 2008, 74, 385–389. [54] Rao MA, Tattiyakul J. Carbohydr. Polym. 1999, 38, 123–132. [55] Rodríguez SE, Fernandez QA, Alonso AL, Ospina PB. Ing. Desarrollo 2006, 19, 17–30. [56] Evans ID, Haisman DR. J. Texture Stud. 1980, 10, 347–370. [57] Nurul IM, Mohn Azemi BMN, Manan DMA. Food Chem. 1999, 64, 501–505. [58] Rao MA, Okechukwu PE, Da Silva PMS, Oliveira JC. Carbohydr. Polym. 1997, 33, 273–283.

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