Near-Infrared Reflectance Analysis - Analytical Chemistry (ACS

David L. Wetzel

Report

Department of Grain Science and Industry Kansas State University Manhattan, Kan. 66506

Near-Infrared Reflectance Analysis Sleeper Among Spectroscopic Techniques Near-infrared reflectance analysis (NIRA), which relies effectively upon chemometrics, is a "sleeper" because it is unknown, illogical, or presumed a priori to be illegitimate by spectroscopists and analytical chemists. Examination of the facts concerning near-infrared reflectance in Table I will acquaint the reader with the potential of this technique. Traditionally applied quantitative infrared spectroscopy of mixtures in powder form could hardly be described as a user-friendly technique since extensive sample workup is required. Thus, for such analytical problems, chromatographic methods or in-

Table I.

direct separation are necessary for individual determinations of components. Since the 1978 work of Peter Griffiths (1), diffuse-reflectance infrared Fourier transform (DRIFT) spectroscopy has received considerable attention. This mid-infrared technique uses spectral subtraction to uncover hidden features within mixtures and has been successfully applied to analysis of pharmaceuticals, highly absorbing samples such as coal, and trace quantities such as catalysis studies of adsorbed chemicals. To date over 200 diffuse reflectance attachments have been sold for FT-IR instruments.

Facts Concerning Near-Infrared Reflectance

Industrial applications of NIRA include: • molecular weight of propylene and ethylene glycol polymers • moisture content of coal and hematite • textile blends of cotton-polyester and of rayon-polyester • finishes on textile fibers • amount of cross linkage in chemically modified starch • hydrogénation of unsaturated fatty acid esters • hydrocarbon mixture of n-hexane, benzene, cyclobenzene, and iso-octane • volatiles (loss on drying) and moisture in cosmetics • total alkaloids, nicotine, and reducing sugar in tobacco processing • moisture in pharmaceutical excipients and in detergent powders Agricultural commodities in worldwide commerce are analyzed by NIRA for their content of water, protein, lipid, etc. Pharmaceuticals have been identified by applying previously determined canonical variables resulting from multiwavelength measurements. Rapid and timely analysis for process control in various processing industries is based upon NIRA methods. Sample preparation prior to spectroscopic measurement is minimal even in the case of powders.

0003-2700/83/A351-1165$01.50/0 © 1983 American Chemical Society

Quantitative diffuse reflectance in the near-infrared region has probably not yet received the attention it deserves. In the case where components, present in the amount of 1% or more, of weakly absorbing samples require quantitation, near-infrared (diffuse) reflectance at multiple wavelengths coupled with multivariate statistics might be applied as the method of choice. The convenience of sample handling, computer assistance, and additivity of the near-infrared response makes this possible. Pioneering work in near-infrared transmission spectroscopy was done by Kaye (2, 3) of Beckman Instruments in the 1950s. Classical spectroscopy in this region prior to 1969 has been reviewed by Whetsel (4). Although commercial single-purpose dual-wavelength (near-infrared) diffuse-reflectance production line moisture monitors had existed previously, it was Norris (5) of the Beltsville USDA laboratory who recognized the potential of diffuse-reflectance measurement in the near-infrared for routine quantitative analysis of major components in agricultural commodities. This latter work caused the appearance of commercial multiwavelength filter instruments in the 1970s by Dickey-John, Neotec (Pacific Scientific), and Technicon. European instruments have subsequently appeared in the 1980s. What the Instrument Sees Most filter instruments in routine use generate raw optical data for only a few wavelengths. However, the spec-

ANALYTICAL CHEMISTRY, VOL. 55, NO. 12, OCTOBER 1983 ·

1165 A

Figure 1. (a) Mustard seed; (b) millet; ( c ) durum; (d) soybean Data taken f r o m Reference 6

Table II.

Composition of Cereal Grains and Oilseeds Starch

Protein

Lipid

Product

(%)

(%)

(%)

(%)

Mustard seed Millet Durum Soybean

— 60-65 60

35.0 10.5 15.5 40.0

25-40 3.9 2.0 21.0

12.0 2.9 3.5 5.5

tral features of commodities scanned over the entire near-infrared region by use of a grating monochromator permit one to observe the available analytical information. Figure 1 shows the reflectance value expressed as log 1/reflectance in the near-infrared region for four agricultural commodities composed primarily of starch, protein, water, lipid, cellulose, and other fibrous polysaccharides. A look at the region of 2100 nm indicates the presence of structures common to starch and cellulose. Data in Table II indicate high levels of starch in those commodities exhibiting this peak. On either side of the band at 2100 nm are absorptions at 2055 nm and 2180 nm corresponding to amide structures present in protein. In both of the oilseed (soy and mustard) samples the protein peaks are prominent because the band of carbohydrate is essentially absent. Relative prominence of the central carbohydrate peak to the side amide peaks (i.e., shoulders) provides a pattern typical of the other higher starch commodities. Such preliminary qualitative information is useful as an aid in quantitative work, since high-starch samples may require that measurements be made at the 2100-nm wavelength and that this term be included in the quantitation equation to com-

Fiber

pensate for the effect of starch on the background of the analyte (protein) absorption at 2180 nm. In the areas of 2310 nm and 2348 nm prominent peaks appear for the oilseed samples, indicating the presence of lipid. Data in Table II

confirm the high lipid content of these samples. Also, a subtle difference due to CH bands present in cellulose but not in starch allows one to explain the greater absorption in the 2336-nm and 2352-nm regions for low-fat samples containing high fiber. Figure 2 shows how the reflectance value is subject to differences of scattering and sample penetration due to differences in particle size. The data shown are for a coarse wheat-milling fraction (first mids) from the Kansas State University pilot flour mill. Note that the same material reground on a sample mill (UD-Cyclotec with l-mm screen, Boulder, Colo.) and by ball mill for 28 h gave respectively higher reflectance (lower log 1/R), and less contrast between the "absorption" maxima and baseline of the reflectance spectrum. It can also be noted from the absorption peak at 1940 nm that water was partially evaporated during the regrinding. Thus, relative granulation and relative water content of the samples are made obvious by selective near-infrared reflectance measurement. It is readily apparent that a visual look at the spectrum is inadequate to observe many of the spectral features discussed. For this reason, a computer is used to accumulate multiple digitized readings at selected wavelengths. Comparison of time-integrated signals at analyte (indicator) wavelengths with reference wavelength readings allows dual-wavelength spectrometry techniques to be applied. The resulting dual-wavelength measurements are then related to differences in chemical composition. Differences

Figure 2. Kansas State University pilot mill first mids wheat flour (a) Coarse; (b) reground on Cyclotec mill (1-mm screen); (c) reground on ball mill for 28 h. Data taken from Reference 7

1166 A · ANALYTICAL CHEMISTRY, VOL. 55, NO. 12, OCTOBER 1983

in near-infrared optical response of samples with different compositions are very small compared to typical ul traviolet, visible, or mid-infrared ana lytical curves. However, they are reproducibly measurable and are the basis of the success of NIRA as a quantitative technique. Overcoming Apparent Shortcomings It is the nature of absorptions in the near-infrared to be weak since they consist of overtones or combinations of fundamentals. The subtle differ ences among samples previously re ferred to require a careful measure ment of the signal. NIRA is concerned with observing differences between two samples in milliabsorbance units. For differences in this range to be meaningful, the noise levels must be kept to only a few microabsorbance units. Such instrumental require ments are more stringent than those for most other routine spectroscopic quantitation. The character of diffuse reflectance requires special consider ation in the areas of optical design, op eration sequence, sample handling, data accumulation, and statistical treatment. Near-Infrared. A few simple fun damental vibrational bands in the mid-infrared region of the spectrum of a particular compound will produce multiple overtones yielding many higher frequency bands in the nearinfrared region that overlap and that are difficult to interpret. Unlike the mid-infrared region, which is valuable as a tool for obtaining structural infor mation, in the near-infrared region such structural information is ob scured. When working in the near-in frared region there is a lack of refer ence spectra to help one predict what one will see. Knowledge of the midinfrared absorption wavelengths of certain functional groups is of some help in knowing where to look in the near-infrared for overtones. Analytical information may also be obtained by observing a shift in the frequency of the bands due to influence of neigh boring molecules. A salt that does not absorb in the near-infrared may be de tected and quantitated by its effect on the water absorption. Such shifts often explain the success of determin ing nonabsorbing materials because these materials do affect the absorp tion spectra of other molecules present. Weak absorptions in the near-in frared have been cited as a shortcom ing. Instrumentally this is true, but relative absorption strength also serves as a convenient self-limiting factor to restrict which vibrations are observed. For example, a fundamental vibration occurring at 15 yum, with over-

Table III.

Assumptions for Analytical Diffuse Reflectance

• Light incident on a powder or granular material changes directions as it encounters each individual boundary of powder granule. Reflection, refraction, and diffraction take place. • Diffuse reflection occurs when a portion of the light entering the sample is scattered by boundaries within the sample and exits the body of the sample from the surface of entry. • In the absence of absorption and with sufficient (effectively Infinite) thickness and multiple scattering-induced direction changes, a maximum of light is scattered back out of the powder. • Absorption may occur as the scattered light is transmitted between the scattering boundaries within the sample before being scattered back. • The amount of transmittance back and forth between the scattering boundaries affects the opportunity for absorption or the effective thickness (cell path length) of the sample. • The size and shape of the sample particles, the voids between them, and the amount of compacting affects the amount (concentration) of material through which the scattered light must be transmitted between individual scattering boundaries. • Some of the preceding factors also affect the mean free path between scattering boundaries. • The transmission path length (thickness) is shorter for strong scattering (opaque) materials and longer for translucent materials. • Reduction of particle size increases the scattering of transparent materials. • Specular reflection, though geometrically well defined, comes off individual grains with surfaces of random slope in any direction and is a factor in the measurement of diffuse reflectance. • Weakly absorbing samples allow a simple specular reflectance correction (the constant background primarily dependent on refractive index effect can be subtracted out to move the specular component) handled by regression. • A constant specular background results at any wavelength when the refractive index does not change and the effect of absorption is negligible.

tones at 7.5, 5.0, 3.75, and 3.0 μηι is not likely to be observed in the nearinfrared because the fifth or sixth over tones lack intensity. Weak absorp tions in the near-infrared provide se lectivity. The commonly used region is from 1000 to 2500 nm where over tones of fundamental vibrations no higher than 5-8 μνη, depending on their intensity, appear. The long wavelength end of the mid-infrared beyond 8 μπι does not contribute to the near-infrared. This means that the overlapping bands in the near-in frared produced by many combina tions and overtones, although spectroscopically complicated, are from only a few molecular groups. In the near-infrared we predomi nantly see the result of vibrations of light atoms that have strong molecular bonds. If the chemical bond is weak, or the atoms are heavy, the vibrational frequency is low and its overtone will not be detectable in the near-infrared. Therefore, we primarily see chemical bonds containing hydrogen attached to atoms such as nitrogen, oxygen, or carbon, thereby limiting the chemical structures that are observable to fairly simple ones that are common in many organic compounds. These weak over tone bands are more subject to their environment than is the fundamental of the same vibration. A slight pertur bation in the bonding scheme causes small changes in the fundamental, but drastic frequency shifts and amplitude


changes in the near-infrared. Since these weak bands are broad and over lapping, resolution is not a problem, but reproduction of the same wave length is essential. The practical result of this is that there are numerous re gions in the near-infrared where if wavelength reproducibility is high, signals maximized, and noise mini mized, then the optical responses are sensitive to the environment of the ab sorbing molecules and the number of the molecules present. Thus quantita tive measurement can be made and successfully correlated to chemical data obtained by other means. From these data and application of a suit able statistical relationship with ap propriate constants, determination of analyte concentrations of unknowns can be made with surprising success. Diffuse Reflectance. Scattering is greater at the shorter wavelengths of the near-infrared than in the mid-in frared region. In diffuse reflectance, scattering is an important factor. Dif fuse reflectance characteristics are summarized in Table III. A volley of photons fired into a nonabsorbing, scattering sample will not interact identically. Not all will be scattered back the same way since some will be transmitted through more of the sample and undergo many more scattering boundaries before exiting the sample. They will have dif ferent penetration depths, a different number of scattering events (encoun-

ter a different number of scattering boundaries), and a different length transmission path through the sample. Individual photons of a volley fired into an absorbing, scattering medium will have different probabilities of being absorbed since the effective thickness of the path within the sam ple will vary with multiple scattering events and penetration depth (Figure 3). Consideration of these facts makes it necessary to accumulate and aver age data to develop empirical con stants and to treat the data statisti cally. From the detailed list of assump tions concerning the nature of diffuse reflectance as found in Table III, we see that the following sample treat ments are necessary. In practice, the variable of particle size difference from sample to sample and from sam ple to standards must be minimized. In the development of any NIRA method it is prudent to establish the limits within which one can deviate between mean particle size within an experiment and between different particle size distributions within a given type of sample preparation. Since the wavelength is on the order of 1-2 μτΐί, the lower limit of particle size should be no smaller than a few mi crometers in diameter. The upper limit is based on the need to get a large number of particles in the beam to adequately represent the sample and the need to optimize scatter. This is particularly true in the case of het erogeneous materials. In general, the median diameter is on the order of 100 μτα, and it is desirable to avoid too broad a distribution. The overriding factor on particle size, however, is to reproduce a mean particle size and particle size distribution for each type of material and standards of that ma terial. The nature of diffuse reflectance in volves a change in the direction of the light which comes off randomly in all directions but varies with the angle of observation from the normal. As a de tector is moved away from the angle of incidence, the intensity will decrease. From this consideration, we observe that the instrument design is impor tant. There is radiation coming off 360° around the sample and coming out in a solid angle around the inci dent beam. It is advantageous to col lect a maximum amount of this radia tion for three reasons: first, to maxi mize the signal; second, to average all directions; and third, to represent all desirable angles from the normal. For samples of interest in certain analyses, peculiar circumstances favor a simplification to correct for the specular effect referred to in Table III. The specular contribution involves both refractive index and absorption.

Figure 3. Various pathways of diffuse reflectance from weakly absorbing scatter ing particles

Fortunately, in the near-infrared the refractive index effect is essentially constant. Also, the absorptions are usually weak, and thus constancy of the specular background is common for many organic samples. The right combination of high scatter, weak ab sorption, and nearly constant index of refraction allows scattered back trans mission within the sample to be mea sured in the presence of a steady-state specular reflectance background. Under optimum conditions the re sponse is sufficiently linear over the measurement range. Much of the past success with plant materials, for ex ample, may be due to the constancy found in nature. Consideration of the nature of nearinfrared absorption and diffuse reflec tance measurement allows one to real ize both the quantitation possibilities and practical limitations and the ne cessity for empirical statistical input. Instrumental Considerations. The primary instrumental consider ations are those that provide a high


signal-to-noise ratio. A high-intensity stable source and a low-noise highly sensitive detector are required. Also the ability to capture the maximum amount of the diffuse component of the reflected radiation at multiple an gles and to reject the specular compo nent is needed. The mechanism and frequency of optical referencing may contribute to favorable noise and drift characteristics. Intensity of the light scattered back varies with angle from the normal, di minishing at larger angles. In practice, the angle of observation is fixed by the design of the instrument. Since a slight vertical difference in positioning of the sample would result in a differ ence in the angle observed by the fixed optical components, a mechanism for reproducible positioning of the sample is necessary. Packing a granular sample against a window regiments the orientation of the sample so that the orientation is no longer random. The degree of regi mentation affects the intensity mea-

sured at any angle. The amount of reg imentation varies with the compacting pressure and with particle size and shape. The direction of observation can have an effect on the intensity measured at a given angle depending on whether the observation is against the grain or with the grain of a textured sample. Such is the case with naturally textured samples as in meat. Surfaces may be oriented preferential ly in one direction by polishing, slicing a section of sample, or by striking off as in the case of an uncovered powder or granular surface. Sample observation variables ad dressed by the instrument design, in cluding the median angle of observa tion, angular boundaries of obser vance, and the direction of observa tion, are summed up in the designa tion of solid angle. The observation may be simultaneous for different an gles and directions, or sampling of a particular angular segment may be in one direction continuously or in dif ferent directions intermittently. The signal intensity depends on the fraction of reflected light hitting the detector (solid angle of observation) and on the total flux from the source that strikes the sample. Wavelength selection by interference filters or interferometry does not limit optical throughput; however, in using a grat ing monochromator this is a major consideration and optics with f/2 or less are desirable. The instrument operator is respon sible for sample preparation and must ensure that procedures for unknowns and calibration standards are kept the same. This includes grinding (homogenization of liquid suspensions), stor ing of the sample, and packing and po sitioning of the sample cell. Any change requires experimental verifica tion that analytical results have not been affected. Instrumentation The typical operating sequence of a routine instrument for NIRA involves measurement of reflected intensity off the sample surface at a number of wavelengths and off a standard refer ence reflecting surface at those same wavelengths. The reflectance mea surement in practice is thus a relative measurement to a standard reflector. The term I 0 (incident intensity) does not appear in the practical relation ship. Reflectance = I(sample)/I(reference). Such a relationship exists at every wavelength measured. The tra ditional Kubelka-Munk function with appropriate scattering and absorption constants has generally given way among NIRA practitioners.to logarith mic reflectance terms used with em pirical coefficients that accommodate the scattering effects as part of the

calibration. The general analytical ex pression is of the type: % = ζ + a log 1/Ri + b log 1/R2 + c log 1/R3 + . . . A commonly used term involves a coefficient multiplied by log 1/R as shown above. The equation has been modified in some instances to allow for a transformation of R that may combine data from a number of wave lengths into one term. The result of this is that there are fewer terms in the equation but each of these terms becomes considerably more compli cated. Modern Hardware Features. Commercial instruments commonly use tungsten-quartz-halogen sources and lead sulfide detectors, but the mechanisms for referencing to a stan dard reflector and collecting the dif fusely reflected radiation differ con siderably (8). Intermittent referencing of reflect ed radiation intensity from sample to maximum reflected intensity from a standard reflector allows each mea surement to be expressed as a ratio. In the most elaborate referencing system, this is done at each wavelength read ing before indexing to the next sam ple. In other instances, sample mea surements are made at all selected wavelengths followed by measurement of the standard at those same wave lengths. Multidirectional (360°) reflectance sampling allows simultaneous collec tion of radiation in all directions with an integrating sphere, time-averaging with rotating sample, or use of multi ple detectors. A maximum solid-angle (approximately 2 π steradians) simul taneous reflectance collection is ob tained with an integrating sphere. Available commercial NIRA instru ments include interference filter and grating monochromator systems. Commercial grating monochromator instruments designed specifically for NIRA are specialized systems with ap propriate computer software and high-throughput monochromators. The Technicon InfraAlyzer 500 per forms incremental step scanning. The Pacific Scientific 6350 accumulates rapid scan data. Diffuse reflectance accessories are commercially available for use with existing FT-IR instru ments. In filter instruments two types of mountings are the continuously mov ing type and the turret wavelength se lection of discrete narrow band inter ference filters. In the second type (Figure 4), radiation intensity is mea sured at one wavelength and stored in the computer and, after rotation of the filter mount to the next preselected filter, the process is repeated. In the continuously moving filter mount,


multiple wavelengths are obtained from the same filter depending on the angle of tilt at the instant of transmis sion through this filter. There are three levels of filter instruments (min imal, basic, enhanced) from which to choose for analysis by multichannel discrete wavelength measurement and computer data treatment. Enhanced systems have auxiliary computer hardware and software to allow rapid in-house custom calibra tion and method development. Other channels or wavelengths may be added to, or substituted for, those commonly used on the basic system. The system may allow direct raw data transfer to a computer equipped with statistical software suitable for identi fying the channels best correlated to the quantity of analyte of interest by the " t " test or other statistical func tions. Statistical terms as well as cali bration coefficients typically result from multiple linear regression of data from a suitable training set. Such a set is selected to include a suitable range of analyte concentration in a matrix that contains other constituents in a typical variation cross section for that product. Good reference classical labo ratory analytical data are a prerequi site for success. Developing a Method In NIRA the principle of multiplewavelength spectroscopy is used. At least one wavelength is responding to the amount of a particular analyte in the sample matrix. The measurement of at least one other wavelength is used as a reference of the overall re flectivity of that particular sample matrix. In some instances a third, fourth, fifth, etc., wavelength may be used. These may also perform a refer ence function or may give either a neg ative or positive correlation to the an alyte. To obtain the most transferable (robust) calibration, one should mini mize the use of data at wavelengths that are not essential to the calibra tion. When simultaneous analyses are performed, data are collected at the wavelengths required for each of the analyses, and a different equation is solved for each different analyte. In each equation the corresponding cor rect wavelengths appear, and their ap propriate coefficients are used. We have thus the capability for simulta neous multicomponent analysis. For example, one set of reflectance mea surements for milk could be used to determine protein, fat, total solids, and lactose by the solution of four dif ferent equations using the reflectance data at the appropriate wavelength in each equation, and the proper regres sion coefficients for each wavelength. Experimental. To perform a cali bration, it is necessary to assemble a

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r a t i o n i n t o t h e p r e d i c t i o n (analytical) e q u a t i o n , 2) assigning empirical coefficients, a n d 3) t e s t i n g t h e applicability ( r o b u s t n e s s ) t o t h e r a n g e of s a m p l e s . Even though the absorption bands are b r o a d , for q u a n t i t a t i o n , w a v e l e n g t h r e p r o d u c t i o n is essential. Also, for ins t r u m e n t s using c o m p o s i t e d reflect a n c e t e r m calculations, t h e increm e n t s b e t w e e n close p a i r s or t r i o s of w a v e l e n g t h s a r e a p a r t of t h e calibrat i o n a n d m u s t n o t vary. In p r a c t i c e , if available, s p e c t r o scopic i n f o r m a t i o n on t h e a n a l y t e a n d o t h e r major c o n s t i t u e n t s of t h e s a m p l e is u s e d along with t h e m u l t i v a r i a t e statistical m e t h o d s t o choose t h e w a v e l e n g t h s t o be used. P r i o r work w i t h t h e s a m e a n a l y t e in similar m a trices can serve as a s t a r t i n g p o i n t in t h i s selection. However, t h e r e a r e also cases w h e r e t h e c h e m i c a l basis of a s a m p l e ' s i m p o r t a n t c h a r a c t e r i s t i c s is n o t defined b u t t h a t t h e n e a r - i n f r a r e d reflectance analyzer can still b e used. F o r such cases, we m u s t rely entirely u p o n correlation t r a n s f o r m a t i o n s t a tistics. O t h e r calculation m e t h o d s h a v e i n c l u d e d l e a s t - s q u a r e s curve fitting, p r i n c i p l e c o m p o n e n t , l a t e n t variables, a n d row r e d u c t i o n (9-13).

Role of analytical chemists in NIRA Since correlation t r a n s f o r m a t i o n m a y uncover a useful r e l a t i o n s h i p t h a t m a y n o t be obvious from k n o w n t h e o ry, it m a y be necessary t o p u t aside one's pride and try this approach. H e r e is w h e r e c o n t r i b u t i o n s can be m a d e . G o o d solid analytical sense a n d m e t h o d o l o g y a r e also n e e d e d t o o b t a i n highly reliable a n d a p p r o p r i a t e reference d a t a from which specific N I R A m e t h o d s e m e r g e for r a p i d a n d r o u t i n e a p p l i c a t i o n . T h e analytical reference m e t h o d d e v e l o p e d for t h i s p u r p o s e n e e d n o t be r a p i d a n d practical b u t j u s t a c c u r a t e . T h i s is a d e p a r t u r e from t h e u s u a l criteria a n d m o t i v a t i o n for analytical method development. One of t h e m o s t e x t r e m e e x a m p l e s of such a n a p p r o a c h is t h e use of solid s t a t e c a r b o n 13 N M R d a t a by B a r t o n a n d coworkers (14) t o o b t a i n s t r u c t u r a l information concerning natural produ c t s . N e a r - i n f r a r e d reflectance d a t a correlated to the quantitative expression of s t r u c t u r e allows s u b s e q u e n t r a p i d a n a l y s e s of large n u m b e r s of similar n a t u r a l p r o d u c t s a m p l e s , a p propriate quality assessment, and sorting for p a r t i c u l a r e n d use. As p r o b l e m solvers we n e e d every available tool a n d c a n n o t afford t o overlook a p o t e n t i a l l y v a l u a b l e one such as N I R A . G r e a t e r chemical i n p u t a n d ins i g h t will u n d o u b t e d l y aid in t h e recognition of its legitimacy.

References (1) Fuller, M. P.; Griffiths, P. R. Anal. Chem. 1978,50,1906.


(2) Kaye, W. Spectrochim. Acta 1954,6, 257. (3) Kaye, W. Spectrochim. Acta 1955,7, 181. (4) Whetsel, K. B. Appl. Spectrosc. Rev. 1968,2(1), 1. (5) Ben-Gera, L; Norris, K. H. Israel J. Agr. Res. 1968,18,125. (6) Wetzel, D. L.; Mark, H. "Scanning NIR of Grains, Oilseeds, and Their Components"; ICC Symposium: Use of NearInfrared Techniques, 6th World Bread Congress, Winnipeg, 1978; Paper No. S2.1. (7) Wetzel, D. L. "Particle Size as a Variable in Near-Infrared Reflectance Analysis," American Association of Cereal Chemists, 62nd Annual Meeting, San Francisco, Calif., 1977; Paper No. 44. (8) Stark, E. W. "State of the Art of NIRA Instruments"; Research Conference on Diffuse Reflectance Spectroscopy, Chambersberg, Pa., August 1982. (9) Hamid, Α.; McClure, W. F.; Whitaker, T. B. Am. Lab. 1981,13 (3), 108. (10) Hruschka, W. R.; Norris, Κ. Η. Appl. Spectra. 1982 36 (3), 261. (11) Hruschka, W. R.; Martens, H. "Prin cipal Component Analysis Predicts Pro tein and Moisture Content from Near In frared Spectra of Ground Wheat," Pitts burgh Conference on Analytical Chemis try and Applied Spectroscopy, Atlantic City, N.J., 1982; Paper No. 375. (12) Martens, H.; Jensen, S. A. "Proceed ings of the 7th World Cereal and Bread Congress," Prague Czechoslovakia, 1982, Paper No. S.45; Elsevier: Amsterdam, in press. (13) Honigs, D. E.; Hieftje, G. M.; Hirschfeld, T. "Near Infrared Reflectance Analysis (NIRA) Correlation Methods and Performance," Pittsburgh Confer ence on Analytical Chemistry and Ap plied Spectroscopy, Atlantic City, N.J. 1982; Paper No. 380. (14) Barton, F. E., Ill; Akin, D. E., Himmelsbach, D. S.; Windham, W. R. "Ab stracts of Papers"; 186th National Meet ing of the American Chemical Society, Washington, D.C, Aug. 28-Sept. 2,1983; American Chemical Society: Washing ton, D.C, 1983; CELL 11.

David L. Wetzel, professor at Kansas State University, joined the grain science department there in 1973 to develop analytical methods for ce real-based foods and the grain pro cessing industry. His research inter ests include HPLC, laser diffractometry, and NIRA. His PhD graduate work was in analytical chemistry, and he held a number of teaching and re search positions prior to joining KSU. He currently writes a column on instrumentation for Cereal F o o d s World.

Near-Infrared Reflectance Analysis - Analytical Chemistry (ACS

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