ANALYTICAL TECHNIQUES FOR DIFFERENTIATING HUACAYA AND SURI ALPACA FIBERS
DISSERTATION
Presented in Partial Fulfillment of the Requirements for
the Degree Doctor of Philosophy in the Graduate School of
The Ohio State University
By
Sohie Shim, M.S.
*****
The Ohio State University 2003
Dissertation Committee: Approved by Professor Kathryn A. Jakes, Adviser
Professor Terry L. Gustafson
Professor Matthew S. Platz Adviser Textiles and Clothing Graduate Program Professor Susan L. Zavotka ABSTRACT
The alpaca industry is burgeoning in North America. The two breeds of alpacas,
i.e. huacaya and suri, are very different in appearance despite the close genetic
relationship. The most apparent difference is in the crimp characteristics of the fibers in
these animals. Because ortho- and para-cortical cell structure is believed to be associated
with crimp in sheep’s wool, differential scanning calorimetry (DSC) and scanning
electron microscopy (SEM) were used for the investigation of the cortical cell structure of alpaca fibers. Energy dispersive spectrometry (EDS) and IR spectroscopy were also conducted to elucidate the sulfur distribution, cystine oxidation content and α-helical
content related to the cortical cell compositions.
DSC results determined that huacaya have an ortho and para bicortical structure
whereas suri fibers mostly consist of paracortical cells. Similar results were observed in
SEM imaging experiments with plasma etched fiber cross-sections. SEM images
illustrate that huacaya fibers have smaller cortical cells assigned to the orthocortex, and
larger cortical cells to the paracortex. Localization of cortical cells was observed in
huacaya fibers. However, suri fibers only show randomly mixed cells that are likely to be
paracortex. The composition of bicomponent cortical cells obtained using DSC or the cortical cell size distribution observed by SEM can be used for discrimination of huacaya and suri fibers. Sulfur analysis performed by EDS was unable to discriminate huacaya
ii and suri fibers readily. The use of Igor Pro software enhanced the presentation of sulfur
distribution by means of a three dimensional rotation. IR spectra of huacaya and suri fibers distinguish neither cystine oxidation content nor helical structures.
iii
Dedicated to my beloved husband
Whatever I called you by while I was writing this
you are not it, honey.
iv ACKNOWLEDGEMENTS
I wish to thank my adviser, Professor Kathryn A. Jakes for her constant support, encouragement and intellectual nourishment.
I would like to give special thanks to Professor Terry Gustafson, Professor
Matthew Platz, and Professor Susan Zavotka for the commitment to this dissertation.
I also would like to thank Dr. John Mitchell and Dr. Sreenivas Bhattiprolu for technical advice and guidance.
I acknowledge Magical Farms, Inc., Litchfield, Ohio and Alpaca Jack's Suri
Farm, Findlay, Ohio who generously donated alpaca fibers for the research.
Partial support for this research was provided with funds from the Lois Dickey-
Ester Meacham Endowment, and by the Cynthia Ann Spafford Fellowship.
v VITA
January 19, 1973 ...... Born – Taejon, Korea
1995...... B.S. Clothing and Textiles, Seoul National University
1997...... M.S. Clothing and Textiles, Seoul National University
1998 – Present...... Graduate Teaching and Research Associate, The Ohio State University
PUBLICATIONS
Shim, S. & Park. C. (1997). Interface properties and detergency of the mixed surfactant solution. Journal of Korean Society of Clothing & Textiles, 21(3), pp 623-640.
FIELDS OF STUDY
Major Field: Textiles and Clothing Minor Field: Chemistry
vi TABLE OF CONTENTS
Abstract...... ii
Dedication...... iv
Acknowledgements...... v
Vita...... vi
List of Tables ...... ix
List of Figures...... x
1. Introduction...... 1 1.1. History of the South American Camelid and the Current Economics of Alpaca Fiber...... 1 1.2. Hair Fibers...... 4 1.2.1. The chemistry of wool fiber...... 5 1.2.2. The morphology of wool fiber...... 6 1.2.3. Alpaca fiber fleece types...... 8 1.2.4. Fiber evaluation...... 8 1.3. Research Problem Statement ...... 9 1.3.1. Research...... 10
2. Differentiating Alpaca Fibers by Thermal Analysis...... 16 2.1. Introduction...... 16 2.2. Thermal Analysis of Wool...... 17 2.3. Method ...... 19 2.3.1. Materials ...... 19 2.3.2. Experimental...... 19 2.4. Results...... 20 2.5. Discussion...... 22 2.6. Conclusion ...... 24
3. Differentiating Alpaca Fibers by Scanning Electron Microscopy and Energy Dispersive Spectrometry ...... 37
vii 3.1. Introduction...... 37 3.2. Method ...... 42 3.3. Results...... 43 3.4. Discussion...... 46 3.5. Conclusions...... 49
4. Infrared Spectroscopy of Alpaca Fibers ...... 78 4.1. Introduction...... 78 4.2. Experimental...... 82 4.3. Results...... 83 4.4. Discussion...... 85 4.5. Conclusions...... 87
5. Conclusions...... 97
Bibliography ...... 102
viii LIST OF TABLES
1.1. Alpaca fleece prices according to AAC as of December 2000...... 12
1.2. Common amino acids in wool fiber...... 12
1.3. Classification for alpaca fibers...... 13
2.1. DSC peak temperatures of alpaca fibers derived by using TA instruments Universal Analysis software ...... 26
2.2. DSC peak temperatures of alpaca fibers derived by using Grams/AI software...... 27
2.3. DSC peak temperatures of suri alpaca fibers with two peak assumption derived by using Grams/AI software...... 28
2.4. Ortho- and para-cortical cell compositions based on the enthalpy reported by Wortmann and Deutz (1998)...... 29
4.1. Some IR absorbance frequencies of keratin fibers ...... 89
4.2. Relative IR peak heights of alpaca fibers standardized with the peak height at 1236 cm-1 and obtained using Spectrum for Windows...... 90
4.3. Second derivative IR peaks of alpaca fibers obtained using Spectrum for Windows ...... 91
4.4. IR peaks of alpaca fibers obtained using PeakFit ...... 93
ix LIST OF FIGURES
1.1. Alpaca population in North America...... 14
1.2. Fine structure of wool fibers...... 15
1.3. The relationship between crimp and cortex...... 15
2.1. Deconvolution of DSC curves for huacaya fibers ...... 31
2.2. Deconvolution of DSC curves for suri fibers ...... 33
2.3. Deconvolution of DSC curves of suri fibers, assuming two peaks...... 35
3.1. SEM images of plasma etched huacaya fibers...... 51
3.2. Trend of cortical cell sizes in plasma etched huacaya fibers...... 56
3.3. SEM images of plasma etched suri fibers...... 61
3.4. Destruction of alpaca fiber from an X-ray line scan...... 65
3.5. Sulfur distribution in huacaya fibers...... 66
3.6. Sulfur distribution in suri fibers...... 69
3.7. Three-dimensional plot of sulfur distribution in huacaya fibers...... 72
3.8. Three-dimensional plot of sulfur distribution in suri fibers...... 75
4.1. IR spectrum of an alpaca fiber obtained using Spectrum for Windows ...... 95
4.2. Deconvolution of IR spectrum performed by PeakFit...... 96
x CHAPTER 1
INTRODUCTION
1.1. History of the South American Camelid and
the Current Economics of Alpaca Fiber
The camelidae, i.e. llamas, alpacas, vicuñas, and guanacos, have been the source of textile fibers for thousands of years in South America. Today vicuñas and guanacos are protected as wild animals, while llamas and alpacas, domesticated since 4000 B.C., provide meat and fine fibers to the commercial market place. Llama fiber is used regionally and has seen little commercial development worldwide. Alpaca fiber, which was used by the Incan royalty, is a high prestige hair fiber. Alpaca fiber attracts worldwide interest due to its soft hand, fine diameter, lack of allergenic properties, and strength as well as its beautiful colors. It is also environmentally friendly, because (1) alpacas require small acreage due to their efficient digestion and because their hoof structure causes little pasture damage, (2) they are a renewable resource of fiber, and (3) the various natural colors of the fibers preclude dyeing (Alpaca Company, 2001; Alpaca
Owners and Breeders Association, 2001).
In spite of the desirable qualities of alpaca fibers, the price fluctuations of alpaca fibers have been a serious problem (Russel, 1994; Walsh, 1994). The result has been the 1 inability to provide stable profits. The South American alpaca industry still lacks a formal
promotion strategy for these fibers, and relies on the demand of western fashion trends
for marketing (Gabriel, 1998; Walsh, 1994), although alpaca fiber production in Peru,
which still commands the majority of the world’s alpaca fiber trade, reaches into the
millions of dollars (Hoffman & Fowler, 1995).
Price fluctuations remain a major concern of breeders outside South America as
well. The Australian Alpaca Co-operative (AAC)’s alpaca fiber prices are shown in Table
1.1. Considering the fleece yield of an alpaca, the fiber of a single animal, approximately
2.5kg, is worth about AU$ 18.85 per kilogram, which corresponds to US$ 10.10 (ACIL,
2001). However, the price of US$ 30~40 per kilogram was advertised to breeders (Barns,
2001). Fleeces achieve higher prices when they are sold individually to special markets such as home spinners. Some fiber producers advertise their alpaca yarns at over $10 per
100g online. One requirement for stabilizing prices is the establishment of systemized mass production rather than depending on unpredictable, individual fiber producers. The obstacle for mass production in developed countries is the shortage of usable fibers
(ACIL, 2001; Barns, 2001). Although the number of alpacas in Australia was about
35,000 as of May 7, 2001, similar to the number of alpacas in the U.S. in 2001, ACIL
(2001) and Barns (2001) recognized that more fiber production was needed to establish integrated mass production of alpaca fiber, yarns and textiles.
In the past, the government of Peru provided little help to the camelid specialty fiber industry (Gabriel, 1998; Hoffman & Fowler, 1995). However, as Peru has accomplished significant industrial development with political stabilization in the mid
1990’s, the government has placed increased attention on the importance of fiber
2 industries to its economic system (Cortazar, 1997; Gabriel, 1998). Peru’s Commission for
Export Promotion (PROMPEX) and the Peruvian Exporters’ Association (ADEX) assist
the textile industries, including alpaca, vicuña, and cotton (Cortazar, 1997; Gabriel,
1998). The Matsushita Foundation of Japan and the International Alpaca Association
(IAA) also started a program in 1995 to assist and educate small alpaca growers in Peru
(Gamero, 1997). Alpaca fiber consumption extends worldwide. The IAA reported China
as the largest importer of alpaca fibers and fabrics from Peru between January and
August, 1999 (IAA, 1999). The ACIL (2001) report also shows China, Italy, Britain,
Japan, and Germany are chief importers of alpaca fiber products.
In the 1980’s, countries outside of South America started to import llamas and
alpacas. The United States and Canada have imported alpacas since 1984, and Australia
and New Zealand began to import alpacas in 1989 (IAA, 2000). According to the Alpaca
Registry, Inc. (2003) over 47,000 head of alpacas are registered in the United States as of
September 1, 2003. The growth of the alpaca populations in North America is expected to
continue to increase, as breeders work to improve the North American herds (Figure 1.1).
Although the amount of fiber produced in the United States has been steadily
increasing, it is predominantly used by individual handcrafters and artisans. Hoffman and
Fowler (Hoffman & Fowler, 1995) pointed out the need for the establishment of a
domestic mill industry in North America. However, after considerable work trying to find
mills to process North American alpaca fiber, the Alpaca Fiber Cooperative of North
America, Inc. (AFCNA, 1999) decided to send fiber to Peru for processing because of the
lower cost. Most products sold by the AFCNA today are produced from Peruvian fiber,
3 while a lesser number are made from North American fibers and produced in a North
American mill.
Justification of the study
While the alpaca population in North America grows rapidly, little has been done
to study the specialty fibers they produce. Instead, emphasis in the U.S. and Canada has
been on animal breeding. Although the potential economic value of these specialty fibers
is large, camelid fiber is still collected and processed unsystematically in North America.
Fibers are classed in a sorting process by human evaluators with no objective standards
(Hoffman & Fowler, 1995; Walsh, 1994).
Since alpaca fibers have not been studied extensively, and particularly little is
known about fibers grown in the United States, this study was focused on the
examination and comparison of the microstructure and composition of huacaya and suri
alpaca fibers. The study provides fundamental data that will be useful in the development
of quality assessments of alpaca fiber in a commercial setting, and provides baseline
information useful in research, such as in studies of animal nutrition and fiber productivity. Elucidating different characteristics of huacaya and suri fibers also provides a fundamental understanding of how to differentiate alpaca fiber for industry processing.
The research, therefore, provides both a foundation for the future textile industry and an avenue to evaluate animal improvement. Not limited to alpaca fibers, the different characteristics of huacaya and suri fibers, and the methods of analysis employed in this research may provide new guidelines for the identification and the characterization of other specialty hair fibers.
4 1.2. Hair Fibers
1.2.1. The chemistry of wool fiber
Wool and mammalian fibers are made of keratin, which is a natural protein.
Keratin, such as horn, nail and hair, is classified into hard keratin and soft keratin
according to cystine content.
Wool fiber consists of amino acids (Table 1.2). Amino acids contain an amino
group, –NH2 and a carboxyl group, –COOH, and they are connected with polypeptide
chains, -CONH- (McFadden, 1967). Wool fiber is a bulk network of polypeptide chains.
Molecular chains in wool fiber are cross-linked by the strong disulfide bonds, -S-S- of
cystine. Another molecular association of polypeptide chains is the salt linkage, which
forms through association of terminal amino and carboxyl groups.
Cystine constitutes about 10% of the total mass of wool, and provides the strong
primary valence cross-links between the molecular chains (Alexander, Hudson, &
Earland, 1963; McFadden, 1967). Thus, cystine plays an important role in the chemical
and physical properties of wool fiber. The oxidation of cystine yields cystine-S-
monoxide, cystine-S-dioxide, and cysteic acid (Carr & Lewis, 1993; Fredline, Kokot, &
Gilbert, 1997; Millington & Church, 1997). The sulfur content of wool primarily
corresponds to the amount of cystine and its oxidation products. Also, each
morphological part consists of a different chemical composition. For example, scales on the surface of the cuticle cells contain more sulfur than do the cortical cells (McFadden,
1967). In addition, cortical cells are classified into ortho- and para-cortex depending on
relative sulfur content (Jones, Rivett, & Tucker, 1998b; McFadden, 1967).
5 The main chains of wool fiber possess two different structural configurations
according to how the chains are arranged in the stretched and unstretched states; these
secondary structural configurations are α-keratin (or α-helix) and β-keratin (or β-sheet).
Alpha-keratin is a helically coiled structure, which is the structure of the relaxed state of
wool, while β-keratin refers to the planar structure of the stretched state (Fraser, MacRae,
& Rogers, 1972). The secondary structural conformations are transformable, that is, α-
keratin is changed to β-keratin by stretching, and returns to the α-keratin when stress is removed (Astbury & Street, 1931).
1.2.2. The morphology of wool fiber
Since little research has been conducted on the South American camelid fibers,
sheep’s wool will be used as a model of the typical structure of a hair fiber. Figure 1.2
shows the fine structure of a wool fiber.
Each fiber is surrounded by an outer layer of flattened cuticle cells that provide protection of inner cortical cells. Cuticle cells consist of a sulfur-rich exocuticle, a lower
sulfur-containing endocuticle, and a membrane of epicuticle. The medulla is vacuolated
tissue in the center of the fiber, and is categorized as unbroken or interrupted (Wildman,
1954). It has large nuclei. Fine wools don’t display medullae; medullae typically are a
part of relatively coarse fibers. The presence and shape of medullae and the surface
characteristics of the cuticle cells, such as scale shape, scale height, and scale
distribution, are considered unique to each hair fiber. These microscopic features have been used to identify different kinds of hair fibers using light microscopy and electron microscopy (Kadikis, 1987; Langley & Kennedy, Jr., 1981; Wortmann & Arns, 1986).
6 Cortical cells are important in the fiber’s mechanical properties because the disulfide bond linking protein chains within these cortical cells plays a main role in the physical properties of hair fibers. These cells are packed with microfibrils as shown in stained sections (Birbeck & Mercer, 1957). Based on the difference in dye uptake, cortical cells are classified as ortho and para. Paracortical cells, which take less dye, contain more cystine than orthocortical cells (Jones et al., 1998b; Kulkarni, Robson, &
Robson, 1971). However, intermediate cells between ortho- and para-cortical cells have also been found in wool (Jones et al., 1998b).
Bilateral cortexes containing dichotomously distributed ortho-cells and para-cells are believed to be related to the crimp of wool fibers (Hoffman & Fowler, 1995; Jones et al., 1998b; Safley, 1997), because the orthocortex is always found on the outside of the fiber’s crimp (Horio & Kondo, 1953; Mercer, 1953; Mercer, 1954) as shown in Figure
1.3. Villarroel (1959) reported that fine huacaya fiber with crimp has a distinctive ortho- and para-cortical cell differentiation while suri fiber does not. In his research, the imported Peruvian fibers were examined using light microscopy at a relatively low magnification of 200× to 500×. However, Jones et al.’s review (1998b) provides contradictory statements. One reference is cited stating that alpaca fiber does not have a distinct distribution of ortho- and para-cortical cells while another states that alpaca fiber has a particular ortho- and para-cortical cell distribution. This contradiction might be due to the fact that neither of the sources distinguished which breed of fiber was examined for the study.
7 1.2.3. Alpaca fiber fleece types
There are two breeds of alpacas that may be distinguished by difference in their coat type: the huacaya and the suri, each animal provides fiber that has a very different
appearance. The huacaya fiber has a fluffy and curly appearance, whereas the suri fiber is
more straight with only a slight wave and is lustrous (Hoffman & Fowler, 1995; IAA,
2000). Through thousands of years of genetically selective reproduction, today’s alpaca
has few guard hairs; these are fibers with large diameters that need to be removed if a
fine quality product is desired. The other three camelidae, the vicuña, the guanaco and the
llama yield both downy fleece undercoat fibers and guard hairs. Consequently, it is
necessary to separate and discard these types of guard hair from the fleece prior to textile
production in many textile applications. Whereas sheep’s wool has been studied
extensively, other specialty hair fibers have been less well studied. In addition, despite
the obvious differences between the breeds, huacaya and suri, the distinctive
characteristics of two alpaca breeds have not always been noted; in many textile
references alpaca fiber is not identified as huacaya or suri.
1.2.4. Fiber evaluation
In evaluating fiber on the animal or immediately after shearing, the quality of
alpaca fiber is evaluated by fleece judges according to a set of subjective assessments.
These include contamination, luster, crimp, elasticity, density, strength, and diameter
(Hoffman, 1997). However, the only quantitative measure that is consistently employed in the alpaca industry is the diameter, including average diameter and the diameter
distribution. The IAA (2000) provides Alpaca and Huarizo marks to guarantee the
8 proportion of these fibers in products. The Alpaca mark indicates products containing fine alpaca or "unbristled llama" fiber of less than 28 micrometers, whereas the Huarizo mark distinguishes rustic, handcrafted products with coarse South American camelidae fiber of more than 30 micrometers fineness (IAA, 2000).
Table 1.3(a) shows ASTM standards for alpaca fibers which are based on the average diameter (ASTM D2252-85). Hoffman and Fowler (1995) report the South
American camelid fiber classification system which is somewhat different (Table 1.3).
However, they mention that the classification is not consistently applied in fiber evaluation.
The factors that determine the performance of fibers and textiles are more complicated than diameter alone, although fineness is related to hand and softness.
Objective measurements of many fiber properties such as crimp, strength, luster, and dyeability, will be necessary to develop in order to assure fiber quality to the yarn and textile manufacturer. The investigation of fiber structure and chemical composition contained in this research provides fundamental data in the development of quality assessments of alpaca fiber, as well as contributing to an understanding of fiber performance. This information will aid the animal breeder in producing fiber of increasing quality and the textile manufacturer in producing quality fabric.
1.3. Research Problem Statement
In spite of the distinctive difference in appearance between huacaya and suri fiber, little has been done to discriminate the fiber from these two breeds of alpaca. Moreover, no research is reported that describes how chemical composition is related to cortical cell
9 structure, yet it is known in sheep’s wool that these features are correlated with fiber
properties including strength and crimp. Little information on the microstructure or
amino acid composition is reported on alpaca fiber.
The research questions were formulated as follows,
1. Is there a difference in the ortho- and para-cortical cell composition and
distribution between huacaya and suri alpaca fibers?
2. Is there a difference in the cystine composition and the secondary structure
between huacaya and suri alpaca fibers?
3. Is the cortical cell structure related to the cystine composition and the secondary
structure?
To study these problems, differential scanning calorimetry (DSC), scanning
electron microscopy (SEM) with energy dispersive spectrometry (EDS), and infrared (IR)
spectroscopy were conducted.
1.3.1. Research
To answer the research questions, two objectives were formulated:
(a) Determine cortical cell structure of alpaca fibers
One difference between huacaya and suri may be the ortho- and para-cortical cell
composition and distribution. DSC is examined with huacaya and suri alpaca fibers to
investigate the relative composition of ortho- and para-cortical cells. Also, a chemical
composition map can be obtained on the cortical cell microscopic images using EDS
attached to the SEM while SEM is used for investigating cortical cell structure. In the
experiment alpaca fiber was examined to explore the hypotheses,
10 1. Huacaya and suri alpaca fibers have different cortical cell structures.
2. Huacaya and suri alpaca fibers have different sulfur distributions.
(b) Determine the differences in cystine composition and secondary structure between huacaya and suri alpaca fibers
The study investigates the relationship between cortical cell distribution and chemical composition of the alpaca fibers. The possibility that IR spectroscopy may be used to indicate the relative cystine composition in hair fibers by examining cystine oxidation products was examined in this research. The secondary structure of α-helix and
β-sheet was also examined using IR spectroscopy. The correlation between the content of cystine oxidation products and the cortical cell structure, and the composition of helical structure and the cortical cell structure was considered. The hypotheses set forth are:
3. There is a difference in the content of cystine oxidation products between huacaya
and suri alpaca fibers.
4. There is a difference in the content of α-helix and β-sheet between huacaya and
suri alpaca fibers.
5. There is a relationship between the cortical cell distribution and the relative
quantity of cystine oxidation products over huacaya and suri alpaca fibers.
6. There is a relationship between the cortical cell distribution and the relative
quantity of α-helix and β-sheet over huacaya and suri alpaca fibers.
11
Member Price* (US$/kg)** (AU$/kg) <20 µm “Royal Baby” $45.00 $24.11 20.1~23 µm “Baby” $35.00 $18.75 23.1~27 µm “Fine Adult” $25.00 $13.40 27.1~32 µm “Adult” $5.00 $2.68 >32 µm “Strong” $1.00 $0.54 *Price for the Australian Alpaca Co-operative members ** Applying the currency AU$ 0.5358 for US$1.00
Table 1.1. Alpaca fleece prices according to AAC as of December 2000 (ACIL, 2001).
Alanine Histidine Proline Arginine Isoleucine Serine Aspartic acid Leucine Threonine Cystine Lysine Tryptophane Glycine Methionine Tyrosine Glutamic acid Phenylalanine Valine
Table 1.2. Common amino acids in wool fiber (Fletcher & Buchana, 1977; Fraser, MacRae, & Rogers, 1972; McFadden, 1967).
12 (a) ASTM standards (ASTM D2252-85). Type Average Diameter (µm) Description T Extra Under 22.00 T 22.00-24.99 Tui, 12 months age X 22.00-24.99 Extra fine adult AA 25.00-29.99 Medium adult Ac 30.00-39.99 Coarse SK Over 30.00 Skirtings LP Over 30.00 Locks and pieces *TSK: Tui skirtings, expected to range from 24-28µm
(b) Inca Group classification (Hoffman & Fowler, 1995). Grade or Classification Diameter (µm) Baby 20-22 Super fine (also fine spinning) 25.5 Suri 27 Adult 27.5 Huarizo* 32 Llama** 34 Coarse 34-36 * Huarizo indicates the fiber with certain diameter, instead of hybrids of alpaca and llama **Llama also indicates coarse fiber by its diameter.
Table 1.3. Classification for alpaca fibers.
13
50000
40000
30000
20000 Alpaca populationAlpaca 10000
0 1991 1993 1995 1997 1999 2001
Figure 1.1. Alpaca population in North America. (The data was provided by Alpaca Registry, Inc.)
14
Figure 1.2. Fine structure of wool fibers (Ryder & Stephenson, 1968).
Figure 1.3. The relationship between crimp and cortex (Mercer, 1954).
15 CHAPTER 2
DIFFERENTIATING ALPACA FIBERS BY THERMAL ANALYSIS
2.1. Introduction
Alpacas are South American camelid animals that were domesticated 6000 years ago for the purpose of obtaining high quality textile fibers. Within the Lama pacos group, there are two breeds that are visually distinguishable by the appearance of their fleece.
While fibers from huacaya alpacas are very crimped and look similar to sheep’s wool fibers, fibers from suri alpacas are straight with little or no wave in them (Hoffman &
Fowler, 1995).
Although commercial production of alpaca fiber is centered in Peru, the import of animals to North America and Australia has brought new interest in alternative sources of this fiber. North American populations of alpacas are burgeoning (Alpaca Registry Inc.,
2003) with concomitant interest in fiber they produce, yet little has been reported in the literature concerning the chemical and physical structural differences between huacaya and suri fiber.
Villarroel (1959) reported that crimped huacaya fiber has a distinctive ortho- and para-cortical cell differentiation while suri fiber does not. However, he was not conclusive about a cortical cell structure of suri fiber since he used light microscopy with 16 comparably low magnification. The numbers of fibers examined were not mentioned.
Moreover, his research examined imported alpaca fibers from Peru to Australia, and they
were sterilized at 100°C for one hour and disinfected using formaldehyde. On the other
hand, Jones et al.'s review (1998b) provides contradictory statements on the cortical cell distribution in alpaca fibers. This contradiction might be due to the fact that neither of the
sources distinguish which breed of fiber was examined.
In sheep’s wool, bilateral cortexes containing dichotomously distributed ortho-
and para-cortical cells (Jones et al., 1998b; McFadden, 1967) are believed to be related to
the crimp of the fibers because the orthocortex is always found on the outside of the
fiber’s crimp (Horio & Kondo, 1953; Mercer, 1953; Mercer, 1954).
In this research, the thermal behavior of the fibers from two breeds of alpaca was
studied in an effort to discern the composition of cortical cells and to elucidate
similarities or differences in these fibers in comparison to sheep’s wool.
2.2. Thermal Analysis of Wool
Differential scanning calorimetry (DSC) has been widely used quantitatively and
qualitatively for various hair fibers, especially in determining the α-helical content in
cortical cells. Endotherms of wool have been observed at different temperatures
depending on the experimental environments, such as DSC cell types, heating rates, and
thermal media. A comparison of DSC peaks with those reported in the literature, hence,
should consider the experimental conditions. The study of Cao, Joko and Cook (1997)
showed that different heating rates caused the endotherm peak to shift, although the relative difference was small. The melting endotherms appear at lower temperature when
17 water, a thermal medium, is added to fibers in the sample pan. The Flory theory shows
that the interaction between water and the polypeptide backbone decreases the melting
temperature with an increase in melting entropy (Cao, 1997; Haly & Snaith, 1967).
Previous studies (Crighton, 1990; Haly & Snaith, 1967) reported that the endotherm of a
helical polypeptide structure was located at 230-250°C when the wool was dry but was
located at 130-150°C when the fibers were wet and under positive pressure.
Haly and Snaith (1967) first reported the observation of a bimodal endotherm in
DSC studies of wool. Two peaks were observed in the range near the degradation
temperature of the α-helix in cortical cells.
There have been two hypotheses proposed to explain the cause of the bimodal
endotherm observed in wool (Huson, Church, & Heintze, 2001; Tonin, Bianchetto,
Vineis, & Bianchet, 2002). One group of researchers proposed that the melting of α-helix in orthocortical cells and paracortical cells resulted in separate peaks. This is called the ortho/para hypothesis (Huson et al., 2001; Tonin et al., 2002; Wortmann & Deutz, 1993).
Wortmann and Deutz (1998) conducted DSC on separated ortho- and para-cortical cells and reported the enthalpies of 17.4 J/g and 20.6 J/g, respectively. However, when whole fibers were examined, the enthalpy was only 15.0 J/g. They commented that the difference occurred due to the removal of other histological components in the cortical cell separation process. However, these bimodal curves are observed in other keratin fibers which do not display the classical bilateral ortho/para cortical cell distinction (Spei
& Holzem, 1987; Wortmann & Deutz , 1993). This inconsistency lead to another hypothesis for this thermal characteristic of keratin fibers: the two peaks in wool fibers are due to the melting of the crystallite form and to a relatively broad peak from the
18 thermal degradation of fiber. This is called the helix/matrix hypothesis (Cao, 1997; Cao
et al., 1997; Spei & Holzem, 1987; Spei & Holzem, 1989; Spei & Thomas, 1983).
2.3. Method
2.3.1. Materials
White fleeces from nine huacaya alpacas and eight suri alpacas were used in the
study. The alpaca fibers were collected from 2 year old males in a good health, and fed a
consistent diet. All huacaya alpacas came from a single farm, as did all of the suri
alpacas. These farms are located within 75 miles of each other in Ohio. Thus the animals
experienced similar environments in the season in which the fiber was collected. Fleeces
from the blanket area of each animal were collected. Locks from each fleece were
distributed individually on a grid to facilitate random selection. A lock of fibers was selected from 150 locks from each fleece. After the selection, each lock was washed in
ethanol twice. To avoid a weathered tip or a root close to follicle, the middle part of the
fibers were taken and chopped into snippets using surgical scissors.
2.3.2. Experimental
After conditioning at 65% relative humidity and 20°C for at least 12 hours,
snippets between 3 to 5 mg were weighed into an aluminum sample pan, and were sealed with a lid using the Sample Encapsulating Press. A TA Instruments 2910 Modulated DSC thermal analyzer equipped with a Refrigerated Cooling System was used at a heating rate of 10°C/min rate. Because "pan bursting" (Cao et al., 1997), where the decomposed contents erupt from the pan, occurred around 280°C, heating was stopped at 270°C. A
19 sealed empty pan was used as a reference. The calorimeter was calibrated with indium for temperature and cell constants. To verify the reliability of results, all experiments were duplicated.
The data collected were analyzed using the TA Instruments Universal Analysis
Program, version 2.3C. Grams/AI software, version 7 was also used for peak deconvolution. The peaks, which were separated by Grams/AI software, matched the original spectrum with over 99% accuracy. Paired t-tests of peak temperatures in huacaya fibers and t-tests of peak temperatures between huacaya and suri fibers were obtained using Minitab software, version 13.1.
2.4. Results
DSC results of alpaca fibers show endotherm peaks in the range between 230 and
235°C (Table 2.1). These peaks correspond to those reported in the previous studies of wool and other hair fibers when no thermal medium was used (Crighton, 1990; Haly &
Snaith, 1967; Spei & Holzem, 1987; Spei & Holzem, 1989; Tonin et al., 2002). Also, there is a broad endotherm, which overlaps with these endotherms, and the peak of this endotherm is located between 245 and 250°C. This broad curve is believed to be due to thermal degradation of the fiber.
Huacaya fibers displayed bimodal thermal characteristics. Separate peaks were located at 231 and 235°C (Table 2.1) and a paired t-test supports the statement that the peaks are two separate sets (t-value = 32.57, p-value = 0.000). Unlike huacaya fibers, suri fibers displayed only one peak at 235°C. T-test results indicate that the single peak
20 temperatures of suri fibers are not different from the second peak temperature of the huacaya fibers at an α-level of 0.10.
Wortmann and Deutz (1993; 1998) state that assignment of peak temperatures became more accurate as peak analysis software has improved. In addition, peak separation has improved quantitative analyses using DSC. The deconvolution of peaks performed by Grams/AI is illustrated in Figure 2.1 and Figure 2.2. The results in Table
2.2 show that the peak temperatures separated by Grams/AI software were slightly different from those obtained by means of TA Instruments Universal Analysis (Table
2.1). The deconvolution performed by Grams/AI indicated that the huacaya fibers contained two peaks at 230 and 235°C, and suri fibers showed a single peak at 233°C
(Table 2.2).
The source of the differences between the two sets of data can be explained by the asymmetry of the DSC curve. DSC curves are commonly skewed to the right side, and show an irregular baseline. This is due to inevitable effects, such as the thermal resistance of the sample, which changes in the phase transition, and thermal lag from the difference between the true temperature and the measured temperature as well as miscellaneous causes such as uneven contact of samples with the heat (Höhne, Hemminger, &
Flammersheim, 1996). Since the software cannot correct the asymmetry, the peak temperature tends to skew to the lower temperature especially in the case of broad single peaks of suri fibers. All deconvolution results show a coefficient of correlation, R2, over
0.99.
However, the results have the possibility for bias since the manual deconvolution process entails subjective peak determination. To explore the possibility that suri fibers
21 may have two peaks similar to those observed in huacaya fibers, a deconvolution was conducted using Grams/AI and assuming two peaks even though there was no apparent sign of bimodal peaks in the suri fibers (Figure 2.3). The results obtained from the deconvolution with a two peak assumption in suri fibers are summarized in Table 2.3.
Although two peaks are assumed, Figure 2.3 shows that the integrated areas of the peaks found at 230°C are clearly very much smaller than those at 234°C.
In order to compare ortho- and para-cortical cell compositions in a fiber, the amounts of cortical cells were calculated based on the enthalpy that Wortmann and Deutz
(1998) reported using separated cortical cells (Table 2.4). It explains that huacaya fibers can have a much higher orthocortex composition than suri fibers, even when a bicortical structure is assumed for suri fibers. Suri fibers show more paracortical cells than huacaya fibers. Moreover, it shows that huacaya fibers possess a higher percentage of cortical cells as a whole fiber than suri fibers do. However, these results are limited because the enthalpy for separated cortical cells is not obtained from alpaca fibers but from sheep’s wool fibers. Furthermore, the thermodynamics of cortical cells derived from whole fiber are different from separated cells.
2.5. Discussion
The results show the promising potential of the use of the DSC technique for differentiating huacaya and suri alpaca fibers since huacaya fibers display bimodal endotherms but suri fibers show only a single peak in the temperature range of 230 and
235°C.
22 Between the two hypotheses of the cause of the bimodal curve, the helix/matrix
hypothesis leads to suspicion that one might ignore a second peak or a shoulder due to
melting of the paracortex, and interpret the result as an overlapping of alpha helix melting
and thermal degradation of the fiber. For example, the shape of a curve reported in the study of Cao (1997) is more reasonably explained by three peaks, orthocortex melting, paracortex melting, and thermal degradation rather than by two peaks and their overlap.
The major confusion in the interpretation of bimodal curves in previous studies seems to
be due to the overlapping of large thermal degradation endotherms with relatively small
cortex melting peaks.
Thus, the interpretation of DSC endotherms in this study follows the ortho/para
hypothesis. According to the ortho/para hypothesis the first peaks at 230°C correspond to an orthocortex and the second peaks at 235°C are designated as paracortex. The result indicates that suri is composed of only paracortical cells, or the paracortex is primarily
dominant, while huacaya displays a bicomponent ortho-/para-cortical structure. This is
supported by the major visible difference in crimp between the two fiber groups. As in
crimped wool where the orthocortex is always associated with the outside curve of the
crimp, the crimped huacaya shows both ortho- and para- cortical cells. Since paracortical
cells are predominant in suri fibers, the fibers are straight.
The relative compositions of cortical cell types and the overlap of cortical cell
peaks with the broad peak of fiber degradation make the observation of the bimodal
peaks difficult. Since peaks in the range of interest are not separated from each other, and
overlap with another broad peak, peak deconvolution is a necessary process for accurate
thermal analysis.
23 The separation of peaks by Grams/AI produces similar results for huacaya fibers
indicating two peaks at 230 and 235°C. But, for suri fibers, the results indicate a single
peak at 233°C which is lower than the finding of 235°C obtained by Universal Analysis.
Although there are reports of a third cortical cell type in the literature (Orwin, Woods, &
Elliott, 1980; Orwin, Woods, & Ranford, 1984), these may not indicate a new type of cortical cell but the asymmetric nature of peaks, which cannot be corrected by the
Grams/AI program as mentioned earlier in this paper.
Even when two peaks are assumed, the integrated areas of first peaks at 230°C, which are designated as orthocortex, are insignificant compared to those at 234°C, which are designated as paracortex. Consequently, this exercise reinforced the concept that there is only one peak in suri fiber, and there is no sign of a shoulder, but just an asymmetrically broader left half of the peak which is common in DSC curves (Figure
2.2). Compared to suri fiber, huacaya fiber (Figure 2.1) shows two peaks or at least an obvious shoulder on the right side of the first peak, which is not a common asymmetry in
DSC.
2.6. Conclusion
Thermal analysis of alpaca fibers using DSC proved that huacaya and suri alpaca fibers have different cortical cell compositions. Huacaya fibers examined in this research have both ortho- and para-cortical cells while suri fibers display only paracortex. This difference in cortical cell composition can be used to distinguish huacaya and suri alpaca fibers, and may prove useful in future developments in the specialty hair industry or even in the study of archaeological textiles that are composed of alpaca fibers.
24 Ongoing research will provide more information regarding the differences between huacaya and suri alpaca fibers. To verify distribution of cortical cells within these fibers scanning electron microscopy and energy dispersive spectrometry are employed. IR spectroscopic study is conducted to elucidate the content of cystine oxidants and the secondary structure of these fibers.
25
Sample First peak(°C) Second peak(°C) Degradation(°C) Huacaya1 230.5 235.6 258.9 Huacaya2 230.1 234.2 251.0 Huacaya3 231.7 235.9 254.5 Huacaya4 230.5 234.2 251.2 Huacaya5 231.4 235.2 252.0 Huacaya6 231.0 234.3 250.3 Huacaya7 229.8 233.6 252.5 Huacaya8 231.9 235.1 253.4 Huacaya9 230.7 234.5 250.5 average 230.8 234.7 252.7
Suri1 235.1 251.0 Suri2 233.4 252.4 Suri3 233.8 253.5 Suri4 234.3 251.1 Suri5 233.7 247.6 Suri6 234.3 249.4 Suri7 234.6 252.0 Suri8 234.3 249.5 average 234.2 250.8
Table 2.1. DSC peak temperatures of alpaca fibers derived by using TA instruments Universal Analysis software.
26
Sample First peak(°C) Second peak(°C) Degradation(°C) Huacaya1 230.2 235.1 249.7 Huacaya2 229.8 234.1 245.7 Huacaya3 231.0 235.6 249.5 Huacaya4 230.2 234.4 246.9 Huacaya5 230.7 235.0 247.3 Huacaya6 230.3 234.3 245.6 Huacaya7 229.2 233.6 248.5 Huacaya8 231.1 235.7 248.1 Huacaya9 229.9 234.1 245.8 average 230.3 234.7 247.5
Suri1 234.3 245.8 Suri2 232.0 246.7 Suri3 232.6 245.5 Suri4 233.4 246.5 Suri5 232.8 242.5 Suri6 233.7 245.1 Suri7 234.2 245.8 Suri8 233.7 245.4 average 233.3 245.4
Table 2.2. DSC peak temperatures of alpaca fibers derived by using Grams/AI software.
27
Sample First peak(°C) Second peak(°C) Degradation(°C) Suri1 230.5 234.8 245.9 Suri2 229.0 233.4 246.7 Suri3 228.8 233.5 245.5 Suri4 230.5 234.3 246.5 Suri5 229.6 233.6 242.9 Suri6 230.5 234.2 245.1 Suri7 230.8 234.6 245.4 Suri8 230.0 234.1 245.5 average 230.0 234.1 245.4
Table 2.3. DSC peak temperatures of suri alpaca fibers with two peak assumption derived by using Grams/AI software.
28
(a) Calculated from peak areas obtained using Grams/AI software
Orthocortex Paracortex Ortho/Para Orthocortex Paracortex Total cortex (mg) (mg) Ratio (%wt) (%wt) (%wt) Huacaya1 0.914 0.335 2.73 34.25 12.55 46.80 Huacaya2 0.682 0.218 3.13 20.86 6.67 27.53 Huacaya3 0.602 0.353 1.70 22.88 13.43 36.30 Huacaya4 0.606 0.132 4.60 22.28 4.85 27.13 Huacaya5 0.496 0.310 1.60 13.32 8.34 21.66 Huacaya6 0.476 0.285 1.67 14.35 8.59 22.94 Huacaya7 0.649 0.176 3.68 22.46 6.11 28.56 Huacaya8 0.515 0.277 1.86 17.33 9.33 26.66 Huacaya9 0.358 0.247 1.45 10.62 7.32 17.93 average 0.589 0.259 2.49 19.81 8.58 28.39
Suri1 – 0.377 – – 13.42 13.42 Suri2 – 0.583 – – 20.73 20.73 Suri3 – 0.480 – – 15.93 15.93 Suri4 – 0.533 – – 17.18 17.18 Suri5 – 0.395 – – 12.71 12.71 Suri6 – 0.511 – – 18.46 18.46 Suri7 – 0.477 – – 13.90 13.90 Suri8 – 0.441 – – 15.87 15.87 average 0.475 16.02 16.02 (continued)
Table 2.4. Ortho- and para-cortical cell compositions based on the enthalpy reported by Wortmann and Deutz (1998).
29 (Table 2.4 continued)
(b) When two peaks are assumed for suri fibers
Orthocortex Paracortex Ortho/Para Orthocortex Paracortex Total cortex (mg) (mg) Ratio (%wt) (%wt) (%wt) Suri1 0.088 0.320 0.28 3.15 11.38 14.53 Suri2 0.294 0.329 0.90 10.48 11.69 22.17 Suri3 0.182 0.343 0.53 6.03 11.39 17.43 Suri4 0.200 0.345 0.58 6.47 11.12 17.59 Suri5 0.194 0.251 0.77 6.25 8.07 14.32 Suri6 0.158 0.381 0.41 5.69 13.76 19.45 Suri7 0.142 0.349 0.41 4.14 10.16 14.30 Suri8 0.102 0.369 0.28 3.68 13.27 16.95 average 0.170 0.336 0.52 5.73 11.36 17.09
30
Original Trace + Fitted Trace + Residual + Original Trace + Fitted Trace + Residual + Peaks + Baseline + 2nd Derivative Peaks + Baseline + 2nd Derivative Arbitrary .8 Arbitrary
.4
.6
.3
.4 Heat Flow (mW) Flow Heat (mW) Flow Heat .2
.2 .1
0 0
220 230 240 250 220 230 240 250 260 Temperature (°C) Temperature (°C)
Original Trace + Fitted Trace + Residual + Original Trace + Fitted Trace + Residual + Peaks + Baseline + 2nd Derivative Peaks + Baseline + 2nd Derivative Arbitrary .6
.6
.4
.4 Heat Flow (mW) Flow Heat Heat Flow (mW) Flow Heat
.2 .2
0 0 220 230 240 250 260 220 230 240 250 Temperature (°C) Temperature (°C)
Original Trace + Fitted Trace + Residual + Original Trace + Fitted Trace + Residual + Peaks + Baseline + 2nd Derivative Peaks + BaselineArbitrary + 2nd Derivative
.6
.6
.4 .4 Heat Flow (mW) Flow Heat Heat Flow (mW) Flow Heat
.2 .2
0 0
220 230 240 250 260 220 230 240 250 Temperature (°C) Temperature (°C)
(continued)
Figure 2.1. Deconvolution of DSC curves for huacaya fibers.
31 (Figure 2.1 continued)
Original Trace + Fitted Trace + Residual + Peaks + Baseline + 2nd Derivative
Arbitrary
.4 Heat Flow (mW) Flow Heat
.2
0 220 230 240 250 260 Temperature (°C)
Original Trace + Fitted Trace + Residual + Peaks + Baseline + 2nd Derivative .6
.4 Heat Flow (mW)Heat Flow
.2
0
220 230 240 250 260 Temperature (°C)
Original Trace+ Fitted Trace + Residual + Peaks + Baseline + 2nd Derivative
.4
Heat Flow (mW) Flow Heat .2
0
210 220 230 240 250 260 Temperature (°C)
32
Original Trace + Fitted Trace + Residual + Original Trace + Fitted Trace + Residual + Peaks + Baseline + 2nd Derivative Peaks + Baseline + 2nd Derivative
.5 Arbitrary .5 Arbitrary
.4 .4
.3 .3 Heat Flow (mW) Flow Heat (mW) Flow Heat .2 .2
.1 .1
0 0 220 230 240 250 260 220 230 240 250 260 Temperature (°C) Temperature (°C)
Original Trace + Fitted Trace + Residual + Original Trace + Fitted Trace + Residual + Peaks + Baseline + 2nd Derivative Peaks + Baseline + 2nd Derivative
Arbitrary .4
.4 .3
Heat Flow (mW)Heat Flow .2 (mW)Heat Flow
.2
.1
0 0 220 230 240 250 260 220 230 240 Temperature (°C) Temperature (°C)
Original Trace + Fitted Trace + Residual + Original Trace + Fitted Trace + Residual + Peaks + Baseline + 2nd Derivative Peaks + Baseline + 2nd Derivative
Arbitrary .6 .5
.4
.4 .3 Heat Flow (mW) Flow Heat Heat Flow (mW) Flow Heat
.2 .2
.1
0 0 220 230 240 250 220 230 240 250 Temperature (°C) Temperature (°C)
(continued)
Figure 2.2. Deconvolution of DSC curves for suri fibers.
33 (Figure 2.2 continued)
Original Trace + Fitted Trace + Residual + Peaks + Baseline + 2nd Derivative
.6
Arbitrary
.4 Heat Flow (mW) Flow Heat
.2
0 220 230 240 250 Temperature (°C)
Original Trace + Fitted Trace + Residual + Peaks + Baseline + 2nd Derivative
.4 Heat Flow (mW)Heat Flow
.2
0
220 230 240 250 260 Temperature (°C)
34
Original Trace + Fitted Trace + Residual + Original Trace + Fitted Trace + Residual + Peaks + Baseline + 2nd Derivative Peaks + Baseline + 2nd Derivative .5 Arbitrary .5
.4 .4
.3 .3 Heat Flow (mW) Flow Heat (mW) Flow Heat .2 .2
.1 .1
0 0 220 230 240 250 260 220 230 240 250 260 Temperature (°C) Temperature (°C)
Original Trace + Fitted Trace + Residual + Original Trace + Fitted Trace + Residual + Peaks + Baseline + 2nd Derivative Peaks + Baseline + 2nd Derivative
.4 Arbitrary
.4 .3
Heat Flow (mW)Heat Flow .2 (mW)Heat Flow
.2
.1
0 0 220 230 240 250 260 220 230 240 Temperature (°C) Temperature (°C)
Original Trace + Fitted Trace + Residual + Original Trace+ Fitted Trace + Residual+ Peaks + Baseline + 2nd Derivative Peaks + Baseline + 2nd Derivative
.6 .5 Arbitrary
.4
.4 .3 Heat Flow (mW) Flow Heat Heat Flow (mW) Flow Heat
.2 .2
.1
0 0 220 230 240 250 220 230 240 250 Temperature (°C) Temperature (°C)
(continued)
Figure 2.3. Deconvolution of DSC curves of suri fibers, assuming two peaks.
35 (Figure 2.3 continued)
Original Trace + Fitted Trace + Residual + Peaks + Baseline + 2nd Derivative
.6
Arbitrary
.4 Heat Flow (mW) Flow Heat
.2
0 220 230 240 250 Temperature (°C)
Original Trace + Fitted Trace + Residual + Peaks + Baseline + 2nd Derivative
.4 Heat Flow (mW)Heat Flow
.2
0
220 230 240 250 260 Temperature (°C)
36 CHAPTER 3
DIFFERENTIATING ALPACA FIBERS BY
SCANNING ELECTRON MICROSCOPY AND
ENERGY DISPERSIVE SPECTROMETRY
3.1. Introduction
The fine structure of sheep’s wool (Birbeck & Mercer, 1957; Jones et al., 1998b;
Swift, 1977) is generally used as a model for other hair fibers. A wool fiber contains
cortical cells surrounded by the protective layers of flattened cells, called the cuticle.
Some hair fibers contain a medulla that is a vacuolated tissue in the middle of the fiber.
Typically, coarse wool fibers display medullae, but a medulla is rarely found in fine wool fibers. The presence and shape of medullae and the surface characteristics of the cuticle
cells, such as scale shape, height, and distribution, are considered unique to each hair
fiber. These microscopic features have been used to identify different kinds of hair fibers
(Kadikis, 1987; Langley & Kennedy, 1981; Wortmann & Arns, 1986).
The outermost layer of the cuticle cells is composed of a lipid and proteinaceous
surface membrane, called the epicuticle. Inside the epicuticle, there are layers of lamellar
cuticle cells which fall into one of two major components; the sulfur-rich exocuticle and
lower sulfur endocuticle. 37 The cystine composition of the cortical cells enclosed by the cuticle cells is
closely related to the fiber’s mechanical properties because the disulfide cross-links
between the protein chains in these cells are the predominant intermolecular bonding
force (Jones et al., 1998b; Kulkarni et al., 1971). Based on the differences in their characteristics, cortical cells are classified as orthocortex and paracortex. The orthocortex has lower sulfur content and is stained darker while the paracortex has higher sulfur content and exhibits lower dye take-up. Though wool fiber is known as a natural bicomponent fiber with paracortex and orthocortex, the existence of an intermediate cortex between para- and orthocortex has been reported as a third cell type, labeled mesocortex (Kaplin & Whiteley, 1985; Orwin et al., 1980; Whiteley & Kaplin, 1977).
Each cortical cell is closely packed with macrofibrils that are 0.05-0.2 µm in diameter. Macrofibrils are aggregates of intermacrofibrillar matrix and microfibrils. The intermacrofibrillar matrix is densely stained and consists of high-sulfur, high-tyrosine
proteinaceous material. Microfibrils are 7-8 nm diameter filaments embedded in the
matrix. The paracortex is more densely packed with macrofibrils and has a more parallel
arrangement of microfibrils yet contains a greater matrix content compared to
orthocortex. In the protofibril model, a microfibril consists of eleven protofibrils, and
each protofibril is composed of α-helical coils of two or three protein molecules (Crick,
1952; Filshie & Rogers, 1961).
Each cortical cell and cuticle cell is surrounded by a cell membrane complex
(CMC) that composes the intercellular phase. The CMC does not only define each cell
but also cements cells together. Although the composition of the CMC is not clearly
known, it is believed that there are two major components to the CMC; a lipid membrane
38 (β-layer) and proteinaceous intercellular material (δ-layer). The outer β-layer does not stain well while the inner δ-layer is densely stained.
The cortical cell structure is also believed to play an important role in the crimp property of a wool fiber. The bicortical structure of sheep’s wool fiber is considered to cause the fiber crimp along the length because orthocortex is always found outside the curve of the fiber crimp (Horio & Kondo, 1953; Mercer, 1953; Mercer, 1954). However, a comprehensive mechanism that explains how the bicomponent cortical structure of wool fiber contributes to the crimp has not yet been proven (Jones et al., 1998b; Kaplin &
Whiteley, 1985).
Many studies attest that observing fiber morphology by optical microscopy can provide information about a fiber’s identity with some certainty because hair fibers, including wool, have characteristic internal structures and unique surface characteristics, i.e. scales. Furthermore, because of the much enhanced resolution and depth of field of scanning electron microscopy (SEM) and transmission electron microscopy (TEM) compared to light microscopy, several researchers have suggested that electron microscopy may provide more information than light microscopy. SEM is used to measure scale heights at the scale edge and to identify fibers in a blend (Wortmann &
Arns, 1986). The scale height, which is difficult to measure by light microscopy, seems to be a very unique feature of each hair fiber. Light microscopy has an advantage over electron microscopy, however, in that it can be used for observing internal structures, i.e. medullae and pigmentation, which are also very unique features of hair fibers (Kadikis,
1987; Palenik, 1983; Sich, 1990). In addition, light microscopy is simple, low cost, and available in most analytical laboratories. Hence, Sich (1990) concluded that electron
39 microscopy and light microscopy could be used in a complementary manner for the study
of, respectively, topographical features and internal structures of hair fibers.
However, without treatment the cortical cells in wool fibers are not readily visible using either light microscopes or electron microscopes. Nevertheless, there are a few ways to make cortical cells visible. When wool fibers are dyed with methylene blue, the orthocortex is dyed darker than paracortex (Horio & Kondo, 1953; Mercer, 1953; Mercer,
1954). Differentiating para- and ortho-cortical cells by their heavy-metal stain uptake, such as osmium tetroxide, silver nitrate, silver methanamine and potassium permanganate
(Jones et al., 1998b) has been widely used with scanning electron microscopy (SEM) and transmission electron microscopy (TEM) to examine these fine detailed structures to a higher level of magnification (Bergen, 1954). But, it is limited by the complication of chemical reactions and the possible destruction of the fiber structure in the dyeing process. The method requires subjective judgment to define ortho- and para-cortical cells according to the relative amounts of stain take-up.
In another approach, cortical cells can be studied through the destruction of the
CMC surrounding the cells. In particular, enzymes (Mercer, 1953) or acid hydrolysis
(Leach, Rogers, & Filshie, 1964; Leeder & Rippon, 1982) are used to separate cells. The etching of fiber is a relatively new method used to display cortical cells on the cross- sections of fibers by etching the cell boundary. It incurs minimal structural changes since it does not contaminate the fiber with chemicals, and the method still preserves the fiber as a whole if the proper control of an etching level is achieved.
A “cold plasma” etching technique of embedded fiber cross-sections was developed for the fiber research (Jakes & Mitchell, 1996), while a similar approach was
40 taken by Swift (1980). It does not require high temperatures for materials to be etched and prevents the thermal degradation of the fiber. The etching is caused by plasma generated in an oxygen atmosphere. In the plasma, the β-layer of the CMC, composed of lipids, will be readily destroyed compared to other proteinaceous parts of the fiber. As a result of destruction of the CMC, the boundaries between cortical cells that were not visible can now be seen under an electron microscope. However, the plasma can also destroy the cell structures if the etching is not limited to an appropriate etching time. By minimizing the structural changes incurred by the plasma, the technique enables the observation of the cortex structure of alpaca fibers close to the original condition.
Moreover, electron microscopy can be readily used in combination with an X-ray microanalysis technique, in order to differentiate the ortho and para-cortical cells by their sulfur content. Jones, Cholewa, Kaplin, Legge and Ollerhead (1990) used TEM with microprobes and a proton beam accelerator for sulfur X-ray mapping of cortical cells. In this study, an energy dispersive spectrometer (EDS) attached to SEM was useful to create an elemental map of the cross-section of individual fibers. Although the X-ray elemental analysis by EDS results in a relative comparison, rather than yielding absolute values, it adds a semi-quantitative means to discern ortho- and para-cortical cells based on relative differences in sulfur content.
In the textile industry, alpaca fiber is a highly prestigious specialty hair fiber. The animals have also been imported into North America and Australia by entrepreneurs (see
Chapter 1). The alpaca animals are classified into two breeds, the huacaya alpaca and the suri alpaca. The major apparent difference between huacaya alpaca fiber and suri alpaca fiber is the differences in crimp. Hence, the examination of the cortical cells may provide
41 a key to differentiating these two groups of alpaca fiber. In the research, the techniques of
SEM with EDS were used to explain cortical cell structures and sulfur compositions.
3.2. Method
The fibers from white alpacas were used in this study to avoid the effects of color.
White fleeces from nine huacaya alpacas and eight suri alpacas obtained from 2-year old healthy males were studied. Fibers were randomly selected from the fleeces and washed with ethanol. Several fibers from each alpaca were arranged parallel and embedded in
Epofix resin, manufactured by Struers. Then, they were cut with a diamond saw into cross-sections and the surfaces were polished with grits of 2500 and then 4000. Samples were dried in a vacuum desiccator overnight. An SPI Plasma Prep II was used to etch the samples by the cold plasma purged with oxygen. The sample chamber was evacuated and
radio frequency power at 13.56MHz was applied. The samples were exposed to plasma for 30 minutes. Mounted on carbon planchettes with carbon tape, the etched samples were sputter-coated with gold using a Pella Pelco sputter coater. For the EDS elemental analysis, fibers were not plasma etched but were sputter-coated with carbon using a
Denton Vacuum Desk II coater. Although the samples for both coatings are obtained from the same lock and the same set of fiber embedments, the SEM observation and EDS elemental analysis were not conducted on the exact same fiber.
Coated samples were observed using a JEOL JSM 820 scanning electron microscope. The instrument is located at the Microscopic and Chemical Analysis
Research Center (MARC) in the Department of Geological Sciences, The Ohio State
University. It was equipped with the Oxford Instruments Analytical Group INCA energy
42 dispersive spectrometer and microanalysis software suite. It was operated at 15kV accelerating voltage for EDS X-ray elemental analysis and at 7kV accelerating voltage for collecting images.
The EDS linked to the SEM provided elemental mapping of the differences in sulfur composition. A Pentafet light element detector was used for this experiment. The data were collected and analyzed with Oxford Instruments Analytical Group INCA software suite. It was calibrated to a NIST traceable standard. Sulfur elemental analyses
were conducted using EDS line scans. Spectra were collected along diametric lines
approximately 45 º apart from each other. Captured images were analyzed to record fiber
diameter using INCA software suite. Igor Pro software, version 4.07 by WaveMetrics,
Inc. was used for the presentation of three-dimensional spectra. Since the trend of relative
sulfur contents was very subtle compared to the large data fluctuation, data were smoothed using the Savitsky-Golay second order algorithm for 25 data points before they
were plotted.
3.3. Results
The images of the etched huacaya fibers are shown in Figure 3.1. In etched huacaya fibers, it is possible to discriminate cortical cells by the relative size and shapes
of the cells, although the difference can be judged only subjectively. It is not feasible to
set a numeric threshold of the size between cortical cells because the difference in sizes is
relative, and moreover small cells are sometimes present among larger cells. Defining a
bisecting line between two sizes of cortical cells is tricky because the cell sizes change
continuously rather than dichotomously with a distinct boundary. Hence, the plasma
43 etching of huacaya fibers displays a trend of changes in the cell size instead of an absolute demarcation between two groups of cortical cells. The topographical trends of the cortical cell distribution by cell sizes in alpaca fibers are illustrated in Figure 3.2.
Compared to huacaya fibers where the cells display a distinct trend of size changes and the cells of similar size are localized (Figure 3.1), suri fibers (Figure 3.3) do not show any localization of the cell sizes. The cell sizes are randomly mixed together. In addition, the sizes of the cortical cells in suri fibers appear more uniform.
Through the etching process, fibers displayed some shrinkage and left behind a void area surrounding the fibers. The void is seen as a dark ring encircling the fiber in the
SEM images (Figure 3.1~Figure 3.3). While the void areas appear on one side of huacaya fibers, those of suri fibers are concentrically located. Furthermore, the size distribution of cortical cells from larger cells to smaller cells in huacaya fibers shows a consistent trend in each cross-section. Larger cells abut the crescent-shaped void and smaller cells appear on the opposite side. This indicates that huacaya fibers exposed to the plasma preferentially shrink on one side while suri fibers shrink evenly.
Figure 3.5 illustrates the sulfur contents of alpaca fibers obtained using EDS. One of the concerns in the X-ray analysis by EDS is destruction of material by the X-ray beam as shown in Figure 3.4. The irregular surface created by this destruction may cause erroneous elemental results. In the research, line scans were applied instead of area scans, in order to minimize fiber surface destruction as well as to reduce overall time for data collection. In order to get an idea of the overall sulfur distribution from the EDS analysis, an X-ray beam scanned each fiber on four different axes, radiating at 45º from each other.
44 The four different X-ray spectra acquired from each cross-section need to be observed together in order to understand overall sulfur distribution. This is a somewhat difficult arrangement. Moreover, when the medulla exists in a fiber, a spectrum displays a
large drop in sulfur content in the vicinity of the medulla, which obstructs detection of
observation of a trend in sulfur content. To illustrate the sulfur content in three-
dimensions, Igor Pro software was used and results are illustrated in Figure 3.7 and
Figure 3.8. The software enables the rotation of the spectra in a three-axial space and
helps in the examination of the sulfur distribution.
In spite of the fluctuation in the spectra, sulfur in huacaya fibers seems more
concentrated in one area of the fiber, and that area with higher sulfur content seems to be
near one edge of a fiber cross-section. Compared to huacaya fibers, most suri fibers
display sulfur distributions which are distributed across the entire fiber cross-section.
These results are relative and it is difficult to identify the boundaries between ortho- and
para-cortical cells by the amount of sulfur content.
The dark colored points, illustrated in Figure 3.7 and Figure 3.8, reflect the
medulla that contains no sulfur. Also, sudden increases at the edges of the sulfur spectra
are sometimes observed because the scanning passed over the cuticle cells which contain
higher amounts of sulfur. In spite of its obstruction, the overall sulfur distribution became
much easier to be perceived by the data presentation performed by Igor Pro software. The
images of each cross-section in Figure 3.7 and Figure 3.8 illustrate how Igor Pro aids
observation of sulfur distribution by rotating of the spectra on the cross-section. By
increasing the number of scans this technique has the potential to describe the elemental
mapping in a more rapid and simple manner compared to the time-consuming area scan.
45 3.4. Discussion
Plasma etching of alpaca fibers provided a view of the internal structure. Cortical
cells of alpaca fibers which became visible by this method indicate that the cortical cell
distribution can be used for the discrimination between huacaya alpaca fibers and suri
alpaca fibers since huacaya fibers display a distinguishable trend of cortical cell sizes while suri fibers display randomly mixed cells in various sizes.
The different cell sizes seem likely to represent the different cortical cell types between ortho and para. From the shrinkage behavior of alpaca fibers in the plasma, huacaya fibers have two components with different shrinkage rates while suri fibers have one type of cortical cells with a uniform shrinkage rate. This difference between the crimped huacaya fibers and the straight suri fibers corresponds to the theory that asserts that the crimp in hair fibers is related to the distribution of these ortho- and para-cortical cells.
Observations are conclusive that suri fibers do not display the traditional bicortical structure of crimped huacaya fibers or of sheep’s wool and it is different
enough to discern suri from huacaya fibers. However, the cortical cell’s uniform
shrinkage in suri fibers does not explain the type of cortical cells in suri fibers. More information is needed to decipher the suri fiber’s internal structure. There are three possible explanations for the suri fiber’s cortical cell type based on the ortho- and para- bicortical structure: all orthocortex, all paracortex, or a random distribution of both cortical cells throughout the fiber. There is also a possibility of the presence of the third type of cortex, mesocortex. However, as discussed in Chapter 2, differential scanning
46 calorimetry (DSC) indicates that there is only one component present in the suri fiber,
and that the paracortex is likely the sole component. Villarroel (1959) mentioned that suri
fibers did not dye well and simply considered it as a difficulty in his study. This observation may reflect the absence of orthocortex in suri fibers. Swift (1977) mentioned that the straight Mongolian hair fibers displayed all paracortex as shown by TEM observation.
Swift (1980) reported the plasma etched keratin fibers revealed the internal structure depending on each component’s oxidation susceptibility. He assigned ortho- and para-cortical cells of Merino wool according to their macrofibrillar structures; orthocortical cells show macrofibrils more clearly than paracortical cells. On the other hand, in an electron microscopic picture of the wool’s cross-section in the paper, paracortex-assigned cortical cells look larger than orthocortex-assigned cells.
It may be related to the fact that the macrofibrils of a paracortical cell in a wool fiber are more closely packed than those of an orthocortical cell (Swift, 1977). Swift
(1980) commented that components with lower sulfur content, such as CMC and intermacrofibrillar matrix, were etched more rapidly than those with higher sulfur content, such as macrofibrils. Hence, the orthocortex which has lower sulfur content would be etched at a greater rate, and shrink more preferentially in comparison to the paracortex. The smaller cells found in huacaya fiber’s etched cross-section would be orthocortex because of higher shrinkage. It also coincides to the image from Swift’s study
(1980). Higher shrinkage on orthocortex side is one possible explanation of the bending of a fiber towards one edge of void area that occurred by plasma etching. Moreover, this
explanation can be supported by the reverse of the crimping mechanism explained by
47 Horio and Kondo (1953) and Mercer (1954). Cells that shrank more would contract the
fiber and be located on the inside of the bending curve near the edge of the void area.
The sulfur analysis does not provide evidence of different cell structures between huacaya and suri fibers as definitive as that obtained from the etched cortical cell observation. Fluctuations in the spectra hinder the data interpretation not only due to
noise but also due to the intricacy of the internal structure composed of several different
components, including the fibril/matrix complex. The interaction volume of the electron beam is not a small spot, but penetrates some distance into the material, thus the sulfur content acquired by EDS reflects a volumetric space with an axial depth, and not just a cross-sectional surface (Goldstein et al., 2003; Slayter & Slayter, 1992). Although the distinction of alpaca fibers between huacaya and suri may not be obtained solely by EDS sulfur analysis, huacaya and suri fibers still can be seen to show some differences in the overall trend of sulfur distribution.
One of the limitations of this study is that the etched surfaces of pictures were not from the exact same fiber from which the EDS results were obtained, due to the different sample preparations. A gold coating is preferred when images of etched cross-sections are to be taken whereas a carbon coat has to be applied to the flat, polished surface of fibers for the EDS analysis. A study linking the visual investigation of cortical cells and the sulfur distribution mapping would be ideal, and further investigation is needed to develop the method to conduct the elemental analysis on the plasma etched surface to collect cortical cell images at once. If the sulfur distribution can be obtained on visible cortical cells by plasma etching, the relationship between an individual cell and sulfur
48 content will be explained, and it will contribute to the understanding of the internal
structure of hair fibers.
3.5. Conclusions
The plasma etching technique produced visible internal structures of huacaya and
suri alpaca fibers. Huacaya fibers displayed the perceptible trend of localized cortical cell
sizes from large to small while the differences in cortical cell sizes of suri fibers are small
and randomly mixed. Based on the DSC study in Chapter 2 and its shrinkage behavior,
there is only paracortex in suri fiber while huacaya fiber is composed of both ortho- and
para-cortex. Since orthocortical cells have a loose arrangement of macrofibrils and
reacted more rapidly in oxygen plasma, they are likely the smaller cells seen in huacaya
fiber’s etched cross-section. The different shrinkage rates of ortho- and para-cortical cells
may explain the huacaya fiber’s asymmetric arrangement of the void area. However, in
order to clarify the relationship between cortical cell sizes and cell types, further studies
using separated ortho- and para-cortical cells are required.
The difference in sulfur content distributions between huacaya and suri alpaca
fibers was not very apparent; however, suri fibers seemed to display a more uniform
distribution throughout the fiber compared to huacaya fibers. For the further investigation
of sulfur content, the use of an electron microprobe analyzer with wavelength dispersive spectrometry (WDS) would be suggested for a better resolution.
The combined study of etched surface observation and sulfur analysis on the same surface will be one approach for the further investigation to elucidate the relationship between cortical cell sizes and cortical cell types. Also, the size of each cortical cell can
49 be measured using the image analysis of cross-sectional views of the etched fibers. The quantitative study of different cortical cell sizes and their relationship with cortical cell types is open for a further study.
The outline of the cross-section is obtained by etching the cell boundary of the
CMC. Swift (1980) insisted that components with lower sulfur content are etched more rapidly. A series of fibers etched for different periods of time can be studied in order to obtain more information about fiber components related to their resistance to plasma degradation which may provide indirect indication of chemical and physical compositions, as well as to visually illustrate a detailed cell structure.
50
(continued)
Figure 3.1. SEM images of plasma etched huacaya fibers. 51 (Figure 3.1 continued)
(continued)
52 (Figure 3.1 continued)
(continued)
53 (Figure 3.1 continued)
(continued)
54 (Figure 3.1 continued)
55 Small
Large
Large
Small
(continued)
Figure 3.2. Trend of cortical cell sizes in plasma etched huacaya fibers.
56
(Figure 3.2 continued)
Small
Large
Large
Small
(continued)
57 (Figure 3.2 continued)
Large
Small
Large
Small
(continued)
58 (Figure 3.2 continued)
Small
Large
Large
Small
(continued)
59 (Figure 3.2 continued)
Large
Small
60
(continued)
Figure 3.3. SEM images of plasma etched suri fibers.
61 (Figure 3.3 continued)
(continued)
62 (Figure 3.3 continued)
(continued)
63 (Figure 3.3 continued)
64 (a) Before scanning
(b) After scanning
Figure 3.4. Destruction of alpaca fiber from an X-ray line scan.
65
Huacaya1 Huacaya2 Huacaya3
(continued)
Figure 3.5. Sulfur distribution in huacaya fibers.
66 (Figure 3.5 continued)
Huacaya4 Huacaya5 Huacaya6
(continued)
67 (Figure 3.5 continued)
Huacaya7 Huacaya8 Huacaya9
68
Suri1 Suri2 Suri3
(continued)
Figure 3.6. Sulfur distribution in suri fibers.
69 (Figure 3.6 continued) Suri4 Suri5 Suri6
(continued)
70 (Figure 3.6 continued) Suri7 Suri8
71
Huacaya1 Huacaya2 Huacaya3
18 18 16 14 16 16 16 14 14 12 14 14 14 12 12 12 10 12 12 10 10 10 8 10 10 8 8 8 8 6 8 6 6 6 6 4 6 4 4 4 4 4
200 -200 -200 200 -200 200 100 0 0 0 0 0 0 -100 -200 200 200 -200 200 -200
18
16 18 16 14 14 16 16 14 14 12 12 14 14 12 12 10 10 12 12 10 10 8 8 10 8 8 6 10 6 8 6 6 4 8 4 4 6 6 4 4 4 200 -200 200 -200 100 -100 200 -200 0 0 0 0 -100 0 100 0 200 200 200 -200
200 200 -200 100 100 200 -100 -200 0 100 -200 0 0 -100 -100 0 -100 0 -100 100 0 -100 100 100 -200 -200 200 -200 200 200
200 -200 200 -200 0 -100 200 4 4 0 100 0 -200 0 100 -200 4 0 -100 200 4 0 -100 6 100 6 4 -200 200 4 -200 6 200 6 8 8 6 6 8 8 10 10 8 8 10 12 10 12 10 10 14 12 12 14 12 12 16 14 14 16 14 14 18 16 16 18
(continued)
Figure 3.7. Three-dimensional plot of sulfur distribution in huacaya fibers.
72 (Figure 3.7 continued) Huacaya4 Huacaya5 Huacaya6
20 20 20 20 20 20 18 18 18 18 16 15 15 16 16 16
14 14 14 14 10 10 12 12 12 12
10 10 10 10 5 5
-200 -200 -200 -200 -200 -200 0 200 200 0 0 0 0 0 200 200 200 200
20
20 18 20 16
18 14 20 20 15 16 12 18 20 14 10 16 15 10 18 12 14 10 16 12 10 5 14 -200 10 12 -100 -200 5 -200 10 0 -100 -200 -100 0 -200 0 100 -100 -200 0 100 -100 100 0 0 200 100 100 200 200 200
-200 -200 -200 -100 -100 -100
-200 0 0 0 -200 -100 -200 -100 -100 100 100 0 100 0 0 100 100 100 200 200 200 200 200 200
-200 -200 -200 -200 -200 0 0 0 0 -200 -100 0 200 200 200 200 0 100 200 5 200 10 10 5 10 10
12 12 12 10 12 10 14 14 14 14 16 15 16 16 15 16 18 18 18 20 20 18 20 20 20 20
(continued)
73 (Figure 3.7 continued) Huacaya7 Huacaya8 Huacaya9
20 20 16 16 16 18 16 14 14 18 14 14 16 12 12 16 12 12 10 10 14 10 14 10 8 8 12 8 12 8 6 6 10 6 10 6 4 4
-200 200 -200 0 -200 -200 0 -200 0 200 200 -100 0 0 100 200 200 0 200 -200
20 16 18 14 16 16 16 14 12 20 12 14 14 10 10 18 16 12 12 8 14 8 6 16 12 10 10 6 10 14 8 8 4 6 200 6 12 -200 100 4 10 -200 -100 -200 0 -100 0 -100 -200 0 -200 0 -100 -100 -100 100 0 100 0 100 100 100 200 -200 200 200 200 200
10
-200 -200 200 -100 10 -100 100
-200 0 -200 0 -200 0 -100 -100 -100 100 0 100 0 0 -100 100 100 100 200 200 -200 200 200 200
-200 -200 200 -200 -200 0 0 -100 0 -200 0 100 200 200 0 200 200 4 0 4 200 -200 10 6 6 10 6 6 12 8 8 12 8 8 10 14 10 10 10 14 12 12 16 12 12 16 14 14 18 14 14 18 16 16 16 16 20 20
74
Suri1 Suri2 Suri3
26 18 26 20 20 18 24 16 24 16 22 14 22 15 14 20 15 12 20 12 18 10 18 10 10 16 10 8 16 8 14 6 14 6 12 5 12 5
200 -200 0 100 200 0 -100 -200 0 200 -200 -100 0 -200 200 100 0 0 100 200 -200 -100
26 20 24 18 26 18 22 16 24 15 16 20 20 14 14 22 12 18 10 12 20 15 10 16 10 18 8 14 5 8 10 16 6 12 6 14 200 5 -200 12 100 200 -200 -100 -200 0 -100 100 -100 0 200 0 100 -100 0 0 100 0 -100 -100 100 100 200 200 -200
200
-200 100 200 200 -100 -200 100 -200 0 100 -100 -100 0 0 0 -100 0 0 100 -100 100 -100 100 -200 200 200 -200 200 -200
-200 200 200 200 -200 0 0 0 0 -200 200 200 -200 -100 0 12 -200 5 0 5 12 100 6 200 -200 14 6
14 8 16 8 10 16 10 18 10 10 18 20 12 12 20 22 15 15 14 14 22 24 16 24 16 26 20 20 18 26 18
(continued)
Figure 3.8. Three-dimensional plot of sulfur distribution in suri fibers.
75 (Figure 3.8 continued) Suri4 Suri5 Suri6
22 22 24 25 25 24 22 20 20 22 20 20 20 18 18 20 18 15 18 16 16 15 16 16 14 14 10 10 14 14 12 12 12 5 5 12
200 -200 0 0 0 -200 200 0 200 100 0 -100 -200 200 100 0 -100 -200
22 24 22 25 24 20 22 25 22 20 20 18 20 20 18 20 15 18 16 18 16 15 16 14 10 16 14 10 14 12 5 14 12 12 5 12
-200 200 -200 -200 -100 -200 200 -100 100 -100 0 -100 0 0 0 0 0 100 100 -100 100 100 200
20
20
-200 -200 -200 20 -100 -100 20 -100 200 0 -200 0 0 100 200 -100 100 0 100 100 0 100 0 -100 -100 100 200 200 200 -200 -200 200
-200 -200 -200 -200 0 200 200 0 200 200 0 0 0 0 -200 200 -200 200 5 5 12 12 12 12 14 10 14 14 10 14 16 16 16 16 15 15 18 18 18 18 20 20 20 20 20 20 22 22 25 22 22 25 24 24
(continued)
76 (Figure 3.8 continued) Suri7 Suri8
24 24 20 20 22 22
20 20 15 15 18 18
16 16
14 10 10 14
12 12
10 10
200 -200 200 0 -200 200 100 0 -100 -200 0 200 -200 0
24
20 20 24 22 22 20 18 15 15 20 18 16 16 14 10 10 14 12 12 10 10 200 200 -200 100 100 -100 -200 0 0 0 0 -100 100 -100 200
20 20
20 200 -200 20 100 -100 200 -200 0 100 0 -100 0 100 0 -100 -100 100 -200 -200 200 200
-200 200 200 -200 100 0 0 0 -100 -200 200 0 200 -200 10 10 12 12 10 14 10 14 16 16 18 15 18 15 20 20 22 22 20 20 24 24
77 CHAPTER 4
INFRARED SPECTROSCOPY OF ALPACA FIBERS
4.1. Introduction
Infrared and Raman spectroscopy provide information about the chemical
composition of various polymers, including amino acids from proteins. Hence, it has
been widely used in the research of wool and other hair fibers which are natural protein fibers. For instance, the degradation of wool by UV, heat, or chemical processes has been studied using IR spectroscopy since degradation causes the oxidation of amino acids and changes in overall structure (Carr & Lewis, 1993; Fredline et al., 1997; Jones, Carr,
Cooke, & Lewis, 1998a; Joy & Lewis, 1991; Lewis & Yan, 1993; Millington & Church,
1997).
Previous FT-IR spectroscopic studies of wool fibers have reported and assigned several absorbance frequencies to particular component amino acids (Carr & Lewis,
1993; Fredline et al., 1997; Gomez, Julia, Lewis, & Erra, 1995; Jones et al., 1998a; Joy &
Lewis, 1991; Lewis & Yan, 1993; Pielesz, Wkochowicz, & Binias, 2000). Table 4.1 summarizes these peaks.
Among the amino acids in keratin fibers, cystine is very important since the disulfide bonds of this amino acid play a great role in determination of the mechanical 78 and physical properties of the fiber. The orthocortex has less cystine and a lower sulfur content than the paracortex (Fraser et al., 1972; Kulkarni et al., 1971). Although IR spectroscopy does not detect the cystine directly, it has been used to detect the oxidation products of cystine, i.e. cystine monoxide, cystine dioxide, and cysteic acid (Hilterhaus-
Bong & Zahn, 1987).
Moreover, IR spectroscopy has been proven to be useful for the investigation of the secondary structures of proteins, i.e. α-helices, β-sheets, β-turns, and random coils. IR bands in the region of 1620 and 1670 cm-1 are empirically assigned to the secondary structure of proteins. Torii and Tasumi (1996) summarized the following assignments:
1650~1660 cm-1 to α-helices, 1620~1640 cm-1 to β-sheets, 1660~1695 cm-1 to β-sheets and β-turns, and 1640~1650 cm-1 to unordered structures. Huson et al. (2001) and
Church, Corino and Woodhead (1997) reported that the α-helix peaks in wool fibers were found at 1652~1653 cm-1. IR spectroscopy has been used for the study of secondary structural conformations between α-helices and β-sheets for wool and other hair fibers as well as other various forms of protein (Koga et al., 1989; Miyazawa & Blout, 1961).
Dobb (1970) found twice the quantity of α-helix in orthocortical cells than in paracortical cells.
Alpha- and β-keratin structures in hair fibers provide distinctive X-ray diffraction patterns. These structures are known to convert from one to the other. Upon stretching, the α-helix transforms to a β-sheet (Astbury & Street, 1931). Fraser (1953) obtained the birefringence vs. extension curve, and discussed the possible destruction of the crystal structure after initial orientation by stretching. To the contrary, the research of Cao and
79 Billows (1999) showed that total crystallinity of wool fiber bundles was constant
regardless of stretching.
The X-ray technique has been used widely in the investigation of the crystallinity and microfibrillar structures of fibers. However, X-ray diffraction studies about keratin
fibers are still very limited and the crystal structure in keratin fibers is not well defined
despite its long history of research (Briki, Busson, & Doucet, 1998). Recent Raman
spectroscopy studies (Church et al., 1997; Rintoul, Carter, Stewart, & Fredericks, 2000;
Wojciechowska, Wlochowicz, & Weselucha-Birczynska, 1999) show that FT-Raman
spectroscopy can be used for conformation analysis when an efficient deconvolution tool
is available.
In order to compare peaks quantitatively, the ratio of peaks may be used to provide a way to compare samples regardless of the variable size of the specimens.
Gomez et al.(1995) took the ratios of the second derivative spectrum intensity of a 1023 cm-1 band (Bunte salt) against that of 1230 cm-1 band (Amide III) to determine the relative quantity of Bunte salt (-SO4) formed. Jones et al. (1998a) calculated the ratio of
I 830cm-1/ I 854cm-1 to indicate the strength of the hydrogen bond to the phenolic hydroxyl
group of tyrosine. They measured band intensities of the second derivative absorbance spectrum by normalization of the entire spectrum on the amide I band at 1630 cm-1. The
absorbance at 1640 cm-1 is identified as the C=O stretching vibration in polypeptides, and
the ratios of I 914cm-1/I 1640cm-1 and I 1080cm-1/I 1640cm-1 are attributed to the relative
intensity of C-O stretching in -CH2OCH2- and in epoxides, respectively (Ito, Muraoka,
Umehara, Shibata, & Miyamoto, 1994).
80 Peak resolution is a major concern in vibrational spectroscopy. Carr & Lewis
(1993) and Jones et al.(1998a) used second derivative spectra rather than zero order derivative spectra in their research of sheep’s wool because the peaks are better discriminated and interpretation of data becomes easier. However, since the second derivatives do not represent the peak height of the original spectrum, quantitative comparison remains difficult and inaccurate. Moreover, the peaks of the second derivative are not located at exactly the same wavenumber as those of the zero order spectra. After calculating the second derivative, the original peaks in zero-order spectra which displayed the highest absorbency at the point are now the “bases” which show the lowest value (Dong, Huang, & Caughey, 1990). Peaks that overlap are not resolved to their original heights in the second derivative. Other deconvolution methods using software as alternative methods of peak definition have been developed.
The predominant fiber examined in the application of IR and Raman spectroscopy has been sheep’s wool, ranging from the effect of treatments on the chemical composition to degradation in the keratin structure. Such information has been rarely reported for hair fibers other than sheep’s wool though they share a common chemical structure.
Information on molecular stretching and keratin structure discovered in sheep’s wool fibers should be applicable to other hair fibers, too.
In this research, alpaca fibers were explored by IR techniques. Alpacas are classified into two breeds; huacaya alpacas and suri alpacas. The most apparent difference in these alpaca breeds is the crimp characteristics of the fibers. Huacaya fibers have crimped appearance while suri fibers are straight with little or no crimp. Because the crimp of a wool fiber is believed to be associated with its ortho- and para- bicortical cell
81 structure (Horio & Kondo, 1953; Mercer, 1953; Mercer, 1954), this research was focused
on the investigation of the cystine composition and the helical structure of the huacaya
and suri fiber by means of infrared spectroscopy, which were reported to distinguish the
ortho- and para-cortical cells in sheep’s wool (Dobb, 1970; Fraser et al., 1972; Kulkarni
et al., 1971).
4.2. Experimental
A lock of fibers were randomly selected from the white fleece of nine huacaya
alpacas and eight suri alpacas. The fibers were washed with ethanol and chopped into
snippets. The middle parts of fibers were used for experiments thus avoiding weathered
tips. Other aspects of the environment of the fibers were controlled (Chapter 2) so
oxidation of the fibers was assumed to be identical. After storing overnight in a 65%
relative humidity atmosphere at 20°C, 3~5 mg of chopped fibers were measured, and
mixed with 180 mg of spectroscopy grade potassium bromide (KBr). This mixture was
placed under a pellet barrel, and pressed at 90,000 psig for 5 minutes under a vacuum. A
KBr pellet without fibers was used as a reference for the background spectrum.
A Perkin-Elmer Spectrum 2000 FT-IR spectrometer was used. The spectra of
each sample were averaged with 128 scans in order to get an appropriate signal to noise
ratio. The IR spectra were collected in the range of 370 – 4000 cm-1. A Fourier transform was performed at a resolution of 4 cm-1. The frequency was calibrated to a 0.01 cm-1
accuracy with the helium-neon laser.
Perkin-Elmer Spectrum for Windows software, version 1.5 was used for IR data
collection and analysis (Figure 4.1). Each peak was corrected for the baseline and offset,
82 and standardized with the height of a peak in the range of 1230 and 1240 cm-1. Second
derivatives were obtained with the Savitsky-Golay derivative function for a 5 data point
window. The peaks in the zero order spectra were obtained by the same software as well
as those of second derivative spectra.
PeakFit software (Systat Software Inc.) was also used for the deconvolution of
peaks. The deconvolution of peaks using second derivatives was selected as a software
option to define matching peaks. A coefficient of correlation, R2 of over 99% was
obtained. For the deconvolution of the secondary structure, which ranged over
1620~1660 cm-1, the spectrum was narrowed to the range between 1600 and 1700 cm-1
before applying the peak separation to obtain more precise deconvolutions, and examined
by PeakFit (Figure 4.2). The relative peak heights between huacaya and suri fibers were
compared and a t-test was performed using SPSS version 11.5.
4.3. Results
Table 4.2 shows the relative peak heights of IR spectra that were standardized against the peak heights at 1236 cm-1. Because of the standardization, the peak heights of
fibers can be compared to each other. Although the cystine contents of the ortho- and
para-cortex are considered different and the distinguishable crimp characteristics between
the huacaya and suri alpaca fibers indicates a difference in cortical cell composition, there
is no significant difference in the relative peak heights of cystine oxidation products in the two breeds of alpaca fibers. Even when deconvolution by the second derivative
(Table 4.3) and the Peakfit software (Table 4.4) were applied, distinction between huacaya and suri fibers was not clear.
83 The variance of each animal’s relative peak height within each alpaca breed was much greater than the difference between huacaya and suri alpaca fibers, and a t-test failed to prove a significant difference between huacaya and suri fibers at the α-level of
0.10. However, even though the difference was statistically insignificant, the averages of the relative peak heights of each cystine oxidation product consistently appear higher in suri fibers than in huacaya fibers, indicating a possible trend that needs further exploration.
In analyzing the data using a second derivative of a spectrum, some peaks in a spectrum are too subtle, even in the second derivatives, to be detected. Consequently, either a base or a peak of second derivative located reasonably near the known peak wavenumber was considered as a representative peak of the IR spectrum (Table 4.3).
Compared to the second derivatives obtained using Spectrum for Windows, the
PeakFit software decides the peak position based on the second derivative, but the peak fitting is followed for the closest match to the original spectra. Hence, the data obtained by the PeakFit seems to correspond more reliably to each peak.
The secondary structure of α-helix and β-sheet in the fibers was also examined over the range of 1620~1660 cm-1, and the results from these methods are shown in Table
4.2~Table 4.4. Both Spectrum for Windows with the zero-order spectra and PeakFit analysis provide insignificant differences in relative peak heights. The average on the peak heights of suri fibers appear to be higher, but the difference is insignificant. Also, the ratios between the two peak heights for the α-helix and β-sheet were calculated but it was not significantly different for huacaya and suri fibers.
84 In sheep’s wool, the protein fraction with higher cystine content was reported to
have lower α-helix content (Kulkarni et al., 1971). While the differences of cystine
oxidation products between huacaya and suri fibers were insignificant, there was no
significant difference in the amount of α-helix revealed in this study.
4.4. Discussion
IR spectroscopy of suri and huacaya fibers shows no significant difference in the content of cystine oxidation products and the secondary structure of α-helix and β-sheet.
These results contradict those of previous studies of sheep’s wool which found that the
paracortex has a lower α-helix content and a higher cystine content than the orthocortex
(Dobb, 1970; Fraser et al., 1972; Kulkarni et al., 1971). However, in those previous studies the ortho- and para-cortical cells were separated prior to analysis. The separation process of cortical cells may manipulate the composition of fibers and alter the result.
Fraser et al. (1972) pointed out that two amino acid analyses from Bradbury, Chapman, and King (1968) and Kulkarni et al. (1971) did not produce identical results on the difference between ortho- and para-cortical cells.
The results in this study may not only reflect the internal cortical cell structure of alpaca fibers but also other histological components, especially cuticle cells on the surface. The cuticles at the surface of wool fibers contain a higher content of cystine
(Bradbury & Leeder, 1970). It seems that there is no difference in an overall fiber,
including cuticle cells, between huacaya and suri fibers in terms of the cystine content
and the helical structure, but a method that examines the cortical cells alone would be desirable.
85 One of the problems is related to the resolution of IR spectra in the region of 1600
and 1700 cm-1. This is the region that is attributed to the helical structure. It appears that
there are no sharp peaks but a broad band in this region. Although the peaks can be
separated by peak fitting programs, slightly changed parameters provide very different
outputs. The decision of the location of peaks is still somewhat subjective in terms of
choosing parameters for deconvolution.
On the other hand, even though statistically not significant, the mean of the
relative peak height of each cystine oxidation product always appears higher in suri fibers
than in huacaya fibers, and it may suggest that suri fibers have more cystine oxidation products of the two alpaca breeds. However, the relative peak heights are very small and the variation of fleeces within each breed is too large to yield definitive results. In
addition, contradictory results are provided by different data analysis methods. In order to enhance the reliability of the IR data of alpaca fibers, a larger quantity of alpaca fleeces and much more data are needed.
Other techniques, such as Raman spectroscopy (Church et al., 1997; Rintoul et al.,
2000; Wojciechowska et al., 1999), thermal analysis (Spei & Holzem, 1989), and X-ray diffraction (Arai & Arai, 1980; Cao & Billows, 1999) have been used to examine the secondary structural conformation of wool fiber. To obtain the vibrational spectrum corresponding to cystine as well as to gain a better resolution within the range of the helical structure free from any pressure applied in making a pellet (Church et al., 1997),
Raman spectroscopy may be complementarily conducted for the further study.
In addition, IR spectroscopy may prove more useful if a microscopic attachment
was employed. One of the main problems with the KBr pellet method in IR spectroscopy
86 was that the fibers are impossible to arrange in a cross-sectional direction because the
fibers are chopped and randomly mixed with potassium bromide into a pellet. If the
proper sample preparation for the fiber cross-section is developed, IR spectroscopy could
be used to examine specific locations of the fiber’s internal structure. Combining these
techniques, IR spectroscopy has a potential as a simple and economical method to
elucidate the helical structure of the alpaca fiber’s internal structure.
4.5. Conclusions
IR spectroscopy using a KBr pellet method was used for differentiating huacaya
and suri alpaca fibers. The apparent difference in crimp characteristics in huacaya and
suri fibers is believed to be related to internal cortical cell structures, in which ortho- and
para-cortical cells have different amino acid compositions and α-helix contents.
However, the IR results did not show any significant difference in either cystine oxidation product content or α-helix content between huacaya and suri fibers.
The inconclusive results may be due to the fact that fibers were used as a whole instead of separating the ortho- and para-cortex. A further study needs to be conducted on
a cross-sectional sample preparation technique for IR spectroscopy attached with a microscope in order to examine each cortical cell individually.
Also, the possibility of deconvolution of IR spectra was explored using second derivative and PeakFit deconvolution software. The methods improved peak selection
and peak fitting. However, the results depended on values of deconvolution parameters,
and it required exploring to find appropriate parameter values.
87 Combining the IR technique with other analytical techniques, such as X-ray analysis or Raman spectroscopy, can add complementary information to aid understanding of the difference between huacaya and suri fibers.
88
Species Wavenumber (cm-1) Reference Cystine monoxide (-SO-) 1060, 1075 1 1071 2
Cystine dioxide (-SO2-) 1124 1 1121 2
Cysteic acid (-SO3-) 1040, 1170 1 1040 2 S-sulfonate (Bunte salt) 1023 1 1022 2 Inorganic sulfate 1100 1 Inorganic hydrogen sulfate 1048 1 Sulfate ester of serine 1003 1 Inorganic sulfite 922 1 Dehydroalanine 876 1 C=O in –CONH- 1640 3
C-O in –CH2-O-CH2- 1080 3 C-O in epoxides 914 3 Amide I (C=O stretch) 1655, 1627, 1697 4 Amide II (N-H bending) 1545, 1522 4 Amide III (N-H bending/C-N stretch) 1230 4 Amide II of Random coil 1535 5 Amide II of α-helix 1516(//), 1546(⊥) 5 Amide II of β-sheet 1530(//), 1550(⊥) 5 1. Gomez et al. (1995) 2. Joy and Lewis (1991) 3. Ito et al. (1994) 4. Bendit* (1966) 5. Miyazawa and Blout* (1961) (*experiments on keratin films)
Table 4.1. Some IR absorbance frequencies of keratin fibers.
89
cystine cystine cysteic amide I amide I monoxide dioxide acid amide III β-sheet α-helix 1654/ 1078 1124 1173 1236 1624 1654 1624 huacaya1 0.6091 0.5993 0.7244 1 1.3128 1.3195 1.0051 huacaya2 0.6354 0.6284 0.7565 1 1.2551 1.2631 1.0064 huacaya3 0.6407 0.6332 0.7663 1 1.2672 1.2706 1.0027 huacaya4 0.6364 0.6170 0.7428 1 1.2897 1.3001 1.0081 huacaya5 0.6321 0.6151 0.7475 1 1.2817 1.2945 1.0100 huacaya6 0.6060 0.5940 0.7337 1 1.3249 1.3411 1.0122 huacaya7 0.6292 0.6065 0.7259 1 1.3094 1.3562 1.0357 huacaya8 0.5879 0.5753 0.7092 1 1.3653 1.3806 1.0112 huacaya9 0.5909 0.5806 0.7104 1 1.3750 1.3937 1.0136 average 0.6186 0.6055 0.7352 1.3090 1.3244 1.0117
suri1 0.6118 0.5837 0.7177 1 1.4360 1.4572 1.0148 suri2 0.6488 0.6233 0.7511 1 1.3154 1.3387 1.0177 suri3 0.6325 0.6120 0.7340 1 1.3477 1.3953 1.0353 suri4 0.6182 0.5950 0.7266 1 1.3801 1.4004 1.0147 suri5 0.6673 0.6539 0.7784 1 1.2464 1.2920 1.0366 suri6 0.6469 0.6217 0.7364 1 1.3505 1.3963 1.0339 suri7 0.6330 0.6157 0.7466 1 1.3017 1.3602 1.0450 suri8 0.6043 0.5894 0.7208 1 1.3883 1.4074 1.0137 average 0.6328 0.6118 0.7389 1.3458 1.3809 1.0265
Table 4.2. Relative IR peak heights of alpaca fibers standardized with the peak height at 1236 cm-1 and obtained using Spectrum for Windows.
90 (a) Peak assignments of the second derivative of the standardized spectrum cysteic cystine cystine cysteic amide I amide I Bunte salt acid monoxide dioxide acid amide III β-sheet α-helix 1024 1042 1074 1126 1172 1228 1624 1655 huacaya1 0.00080 0.00141 0.00168 0.00116 0.00189 0.00106 0.00238 0.00804 huacaya2 0.00105 0.00160 0.00183 0.00126 0.00219 0.00108 0.00179 0.00887 huacaya3 0.00067 0.00149 0.00162 0.00108 0.00193 0.00090 0.00469 0.01775 huacaya4 0.00064 0.00130 0.00155 0.00124 0.00197 0.00110 0.00283 0.01328 huacaya5 0.00137 0.00194 0.00173 0.00083 0.00168 0.00106 0.00109 0.00620 huacaya6 0.00106 0.00194 0.00169 0.00093 0.00189 0.00093 0.00226 0.00791 huacaya7 0.00045 0.00103 0.00110 0.00094 0.00135 0.00155 0.00630 0.02146 huacaya8 0.00067 0.00142 0.00134 0.00135 0.00177 0.00117 0.00207 0.00537 huacaya9 0.00074 0.00125 0.00178 0.00095 0.00177 0.00119 0.00330 0.01053
suri1 0.00027 0.00128 0.00163 0.00108 0.00201 0.00113 0.00340 0.00907 suri2 0.00071 0.00129 0.00149 0.00116 0.00196 0.00097 0.00188 0.00491 suri3 0.00082 0.00128 0.00125 0.00104 0.00146 0.00083 0.00446 0.01889 suri4 0.00154 0.00166 0.00144 0.00101 0.00206 0.00072 0.00109 0.00182 suri5 0.00126 0.00178 0.00120 0.00113 0.00137 0.00121 0.00586 0.02095 suri6 0.00103 0.00137 0.00176 0.00101 0.00185 0.00143 0.00390 0.01366 suri7 0.00164 0.00203 0.00174 0.00159 0.00143 0.00119 0.00881 0.03264 suri8 0.00104 0.00128 0.00114 0.00096 0.00145 0.00068 0.00130 0.00279 (continued)
Table 4.3. Second derivative IR peaks of alpaca fibers obtained using Spectrum for Windows.
91 (Table 4.3 continued)
(b) Peak assignments once again standardized with the peak height at 1228 cm-1 cysteic cystine cystine cysteic amide I amide I Bunte salt acid monoxide dioxide acid amide III β-sheet α-helix 1655/ 1024 1042 1074 1126 1172 1228 1624 1655 1624 huacaya1 0.754 1.334 1.583 1.092 1.782 1 2.251 7.589 3.371 huacaya2 0.969 1.473 1.692 1.163 2.024 1 1.654 8.182 4.947 huacaya3 0.750 1.658 1.812 1.207 2.149 1 5.236 19.815 3.784 huacaya4 0.576 1.174 1.405 1.124 1.783 1 2.563 12.034 4.695 huacaya5 1.295 1.835 1.636 0.786 1.591 1 1.032 5.856 5.676 huacaya6 1.149 2.090 1.828 1.003 2.041 1 2.438 8.540 3.504 huacaya7 0.289 0.662 0.708 0.607 0.872 1 4.071 13.864 3.405 huacaya8 0.570 1.209 1.141 1.151 1.511 1 1.769 4.577 2.588 huacaya9 0.623 1.052 1.495 0.797 1.492 1 2.778 8.860 3.190 average 0.775 1.388 1.478 0.992 1.694 2.644 9.924 3.907
suri1 0.242 1.134 1.437 0.949 1.773 1 2.999 8.008 2.670 suri2 0.731 1.325 1.533 1.198 2.020 1 1.935 5.057 2.613 suri3 0.988 1.542 1.502 1.254 1.762 1 5.372 22.759 4.237 suri4 2.145 2.310 2.008 1.409 2.864 1 1.518 2.527 1.664 suri5 1.045 1.473 0.995 0.936 1.138 1 4.851 17.345 3.576 suri6 0.721 0.956 1.231 0.704 1.295 1 2.724 9.551 3.507 suri7 1.384 1.710 1.467 1.338 1.211 1 7.435 27.540 3.704 suri8 1.538 1.884 1.684 1.418 2.141 1 1.926 4.125 2.141 average 1.099 1.542 1.482 1.151 1.775 3.595 12.114 3.014
92 (a) Peak assignments before standardized cystine cystine amide I amide I Bunte salt cysteic acid monoxide dioxide cysteic acid amide III β-sheet α-helix 1024 1042 1074 1126 1172 1228 1624 1655 huacaya1 0.2889 0.3946 0.5580 0.5330 0.6531 0.8325 0.6325 0.5085 huacaya2 0.2782 0.3405 0.4573 0.4863 0.6098 0.7392 0.5074 0.5110 huacaya3 0.3329 0.4243 0.5005 0.4921 0.6004 0.7066 0.4859 0.5330 huacaya4 0.2390 0.4006 0.4236 0.4714 0.5781 0.6909 0.5540 0.5712 huacaya5 0.2835 0.3660 0.5103 0.5279 0.6543 0.7898 0.6476 0.6741 huacaya6 0.2984 0.3880 0.4941 0.4603 0.5863 0.7117 0.5002 0.4620 huacaya7 0.2408 0.4333 0.4646 0.5000 0.6104 0.7311 0.5322 0.4979 huacaya8 0.1995 0.3752 0.3902 0.4179 0.5505 0.6762 0.8241 0.5005 huacaya9 0.2009 0.3914 0.4165 0.4622 0.5851 0.7176 0.5296 0.5060
suri1 0.2339 0.4269 0.4626 0.5052 0.6212 0.7644 0.6030 0.5716 suri2 0.3274 0.4209 0.5485 0.5092 0.6121 0.7252 0.5643 0.4034 suri3 0.2268 0.4152 0.4476 0.4884 0.6127 0.7799 0.5064 0.5571 suri4 0.3007 0.4026 0.5848 0.5380 0.6277 0.7513 1.0031 0.7574 suri5 0.2865 0.3415 0.4829 0.5224 0.6272 0.7248 0.4985 0.4849 suri6 0.2832 0.3505 0.4843 0.5289 0.6294 0.7390 0.5834 0.5218 suri7 0.2724 0.4512 0.4813 0.5153 0.6277 0.7462 0.5798 0.5938 suri8 0.1973 0.3879 0.3995 0.4277 0.5603 0.6951 0.6909 0.4287 (continued)
Table 4.4. IR peaks of alpaca fibers obtained using PeakFit.
93 (Table 4.4 continued)
(b) Peak assignments standardized with the peak height at 1237 cm-1 cysteic cystine cystine cysteic amide I amide I Bunte salt acid monoxide dioxide acid amide III β-sheet α-helix 1655/ 1024 1042 1074 1126 1172 1228 1624 1655 1624 huacaya1 0.347 0.474 0.670 0.640 0.784 1 0.760 0.611 0.804 huacaya2 0.376 0.461 0.619 0.658 0.825 1 0.686 0.691 1.007 huacaya3 0.471 0.600 0.708 0.696 0.850 1 0.688 0.754 1.097 huacaya4 0.346 0.580 0.613 0.682 0.837 1 0.802 0.827 1.031 huacaya5 0.359 0.463 0.646 0.668 0.828 1 0.820 0.854 1.041 huacaya6 0.419 0.545 0.694 0.647 0.824 1 0.703 0.649 0.924 huacaya7 0.329 0.593 0.636 0.684 0.835 1 0.728 0.681 0.936 huacaya8 0.295 0.555 0.577 0.618 0.814 1 1.219 0.740 0.607 huacaya9 0.280 0.545 0.580 0.644 0.815 1 0.738 0.705 0.955 average 0.358 0.535 0.638 0.660 0.824 0.794 0.724 0.934 suri1 0.306 0.558 0.605 0.661 0.813 1 0.789 0.748 0.948 suri2 0.452 0.580 0.756 0.702 0.844 1 0.778 0.556 0.715 suri3 0.291 0.532 0.574 0.626 0.786 1 0.649 0.714 1.100 suri4 0.400 0.536 0.778 0.716 0.836 1 1.335 1.008 0.755 suri5 0.395 0.471 0.666 0.721 0.865 1 0.688 0.669 0.973 suri6 0.383 0.474 0.655 0.716 0.852 1 0.789 0.706 0.894 suri7 0.365 0.605 0.645 0.691 0.841 1 0.777 0.796 1.024 suri8 0.284 0.558 0.575 0.615 0.806 1 0.994 0.617 0.621 average 0.359 0.539 0.657 0.681 0.830 0.850 0.727 0.879
94 (a) Original spectrum of alpaca fiber 0.517 0.50
0.45
0.40
A
0.35
0.30
0.254 4000.0 3000 2000 1500 1000 500 370.0 cm-1
(b) Offset correction and standardization 1.35
1.2 12341234 1.0
0.8
A 0.6
0.4
0.2
0.0 -0.08 4000.0 3000 2000 1500 1000 500 370.0 cm-1
(c) Second derivative 0.0100
0.008
0.006
0.004 12341234 0.002
0.000 A -0.002 12311231 -0.004
-0.006
-0.008
-0.0100 2000.0 1900 1800 1700 1600 1500 1400 1300 1200 1100 1000 950.0 cm-1
Figure 4.1. IR spectrum of an alpaca fiber obtained using Spectrum for Windows.
95 (a) Deconvolution in the range of 950~2000 cm-1 Huacaya1 Pk=Gauss Amp 81 Peaks r2=0.999531 SE=0.00992326 F=11683.2 1.5 1.5
1.25 1.25
1617 1 1260.6 1 1572.8 1721.1 1171.81243.5 1688.4 1437.5 1523.1 1602.8 1152.9 1226.4 1422.9 1675.6 1748.7 1329.4 1511.1 1133.1 1409.6 1587.5 1664.5 0.75 1208.6 1314.9 1493.3 1734.8 0.75 1114.7 1398.51468.6 1543.3 1638.5 1190.6 1276.6 1709.3 1095.8 1356.5 1482.3 1560.21628.71700.3 1076.8 1301.1 1380.9 1500.6 1647.9 1289.8 1456.2 1762.3 1058.1 1533.6 0.5 1343.3 1449.5 1655.9 0.5 1793.4 1040.3 1550.6 1368.7 1774.4 1858.9 1022.3 1390 17841845.8 1934.1 0.25 1803 1922.2 0.25 1004.1 1811.91881.4 1970.2 984.73 1820.1 1891 1958.7 964.21 0 1832.1 1910.7 0 750 1000 1250 1500 1750 2000
(b) Deconvolution in the range of 1600~1700 cm-1 Huacaya1 Pk=Gauss Amp 18 Peaks r2=0.994725 SE=0.00264004 F=335.216 1.5 1.5
1.25 1.25
1 1698.9 1 1611.8 1618.4 1655.8 1685.8 1605.3 1624.8 1649.3 1679.2 1692.2 1631 1637.2 1643.1 1667.2 1673 1661.8 0.75 0.75
0.5 0.5
0.25 0.25
0 0 1600 1620 1640 1660 1680 1700
Figure 4.2. Deconvolution of IR spectrum performed by PeakFit.
96 CHAPTER 5
CONCLUSIONS
While there has been considerable interest in promoting an alpaca breeding
industry in North America and Australia, little work has been conducted on the
characteristics of the fibers produced by the two breeds of alpacas. The fleeces can be
readily distinguished by the differences in their crimp characteristics, with huacaya being highly crimped and suri being straight. Huacaya fiber, then, is suitable for lofty woolen yarns while suri fiber is suitable for lustrous fine worsted yarns. They each require different methods of processing in yarn formation. Crimp in sheep’s wool has been related to the presence of a bicomponent structure of the cortical cells. These ortho- and para-cortical cells also differ in sulfur and cystine content, and are therefore related to dyeability. Studies conducted on alpaca fiber to aid in discrimination between the two breeds are limited.
The research questions were formulated as:
1. Is there a difference in the ortho- and para-cortical cell composition and
distribution between huacaya and suri alpaca fibers?
2. Is there a difference in the cystine composition and the secondary structure
between huacaya and suri alpaca fibers?
97 3. Is the cortical cell structure related to the cystine composition and the secondary
structure?
To investigate the chemical and structural differences between huacaya and suri alpaca fibers, three analytical techniques were employed: DSC, SEM with EDS and IR spectroscopy. Since the two breeds of alpacas have differences in their crimp characteristics, the internal structure of ortho- and para-cortical cells, which is believed to be associated with crimping, was a central focus.
DSC is a thermal analysis technique. The first research question, “Is there a difference in the ortho- and para-cortical cell composition and distribution between huacaya and suri alpaca fibers?” was examined using DSC. Ortho- and para- cortical cells can be discriminated by their degradation points (230 and 235 °C, respectively). The endotherm for huacaya fibers showed bimodal behavior similar to sheep’s wool. This is consistent with the presence of both ortho- and para- cortical cells as concluded from
SEM imaging. The endotherms for suri fibers displayed a single peak. From the peak temperature of this single peak, it was believed to be the paracortex.
SEM allows for direct observation of the internal structure with minimal chemical manipulation of fibers. The first research question, “Is there a difference in the ortho- and para-cortical cell composition and distribution between huacaya and suri alpaca fibers?” was examined using SEM. The plasma etching technique enabled visualization of cortical cells. Huacaya fibers possessed an ordered array of cell sizes while suri fibers tended to be randomly distributed. The cells arrayed such that ortho- and para-cortical cells could be distinguished. In addition, based on observations in the shrinkage behavior of sheep’s
98 wool, the asymmetrical shift observed in SEM images of huacaya fiber indicates a
bicortical structure. Smaller cortical cells are assumed to be orthocortex due to its higher
shrinkage rate, while the larger cells are assumed to be the paracortex. This assumption is
also supported by its bending behavior, in which smaller cells are found to be contracted
towards the edge of a void area. The randomly mixed cortical cells found in suri fibers
are one type of cortex because the fiber is located concentrically to the void area. The
DSC results reinforce the assignments put forth by SEM that the cortical cells of suri
fibers are paracortex.
Further investigation may be done with separated ortho- and para-cortical cells to elucidate the shrinkage behavior of each cortex in oxygen plasma environment.
Quantitative image analysis studies may elucidate the relationship between cortical cell sizes and cortical cell types to expand the study to other hair fibers.
The results from SEM and DSC support the presence of an ortho- and para- bicortical cell structure in huacaya fibers while suri fibers have only paracortex. Both are reliable techniques to distinguish huacaya and suri alpaca fibers. With a rapidly growing number of alpacas in North America, the techniques may contribute to the development of the alpaca fiber industry as well as the other applications, such as archaeological
textile research.
The sulfur content that is related to the amount of cystine was obtained using EDS
to examine the second research question, “Is there a difference in the cystine composition
and the secondary structure between huacaya and suri alpaca fibers?” The sulfur content
obtained by EDS was very difficult to distinguish between huacaya and suri alpaca fibers.
Advanced data presentation in three-dimensions was obtained using Igor Pro software. It
99 improved understanding of sulfur content distribution. While the difference is very small,
most suri fibers seemed to display a more uniform distribution throughout the fiber
compared to huacaya fibers. To improve the sulfur detection on the surface, another
technique to scan the sulfur contents on the cross-section, such as wavelength dispersive
spectrometry (WDS), could be considered.
It has been reported that ortho- and para-cortical cells have different amino acid compositions and α-helix contents. The KBr pellet method of IR spectroscopy was used in an attempt to correlate and assign the two properties to huacaya or suri fibers. First,
cystine oxidation products are indicative of cystine concentration in fibers. Second, α-
helix content is related to the composition of ortho- and para- cortical cells. IR
spectroscopy was used to see if any vibrations due to cystine oxidation products
(1000~1200 cm-1) or the secondary structure of α-helix and β-sheet (1620~1660 cm-1)
would correlate with huacaya or suri fibers. The second research question, “Is there a
difference in the cystine composition and the secondary structure between huacaya and suri alpaca fibers?” was examined using IR spectroscopy. No conclusive evidence was
found that would allow unambiguous assignment of absorptions unique to huacaya or suri fibers. It is believed that IR spectroscopy was limited because it examines whole fibers
rather than individual ortho- and para- cortical cells. There was a significant difference in
neither the content of cystine oxidation products nor the secondary structure between
huacaya and suri fibers by IR spectroscopy. While, DSC (chapter 2) and SEM (chapter 3)
provided the evidence of different cortical cell structures between the fiber of the two
breeds, therefore, the third research question, “Is the cortical cell structure related to the
cystine composition and the secondary structure?” was not resolved by IR spectroscopy.
100 Hence, the use of IR spectroscopy to distinguish huacaya and suri alpaca fibers
requires further investigation with the goal of removing the interference of other
histological components, such as the cuticle. A cross-sectional study of fibers with IR spectroscopy attached with an optical microscope may enable the examination of individual cortical cells without destruction of the fiber. Other analytical techniques, such as X-ray analysis or Raman spectroscopy, can be conducted to obtain complementary information on helical structure and cystine composition of huacaya and suri fibers.
Nondestructive techniques to elucidate cystine content, helical structure, and sulfur contents as signature characteristics of ortho- and para-cortical cells, which were attempted using IR spectroscopy and SEM/EDS, require further exploration.
The research provides information that clarifies the differences between huacaya and suri fibers. This information is useful for the animal breeder, the textile manufacturer, and the fiber scientist.
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