[advances in food research] advances in food research volume 5 volume 5 || the color problem in...

The Color Problem in Foods

BY G. MACKINNEY AND C. 0. CHICHESTER

Department of Food Technology, University of California, Berkeley

CONTENTS Page

I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11. Color in Selected Commodities.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1. Sugar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311 . . . . . . . . . . . . . . . . . . . . . . . . . . .

4. Tomatoes and Tomato Products.. . . . . . . . . . . . . . . . . . 5. Peas, Spinach, and Similar Chlorophyll-Containing V 6. Strawberry Preserves

111. Some Theoretical Considerations 1. Discrimination.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 331 2. The Uniform Chromaticity Scale (U.C.S.), . . . . . . . . . . . . . . . . . . . . . . . . 332 3. The N.B.S. Unit.. . . . . . . . . . . . . . . . . . . . . . . . . . 4. MacAdam Ellipsoids. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 . Alternative Spaces.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

IV. General Considerations. . . . . . . . . . . . . . . . . . . . . . . . . . V. Instrumentation . . . . . . . . . . . . . . . . . . . . . . .

2. Subtractive Colorimeters . . . . . . . . . . . . . . . . . . . . . . . . . 340

4. Spectrophotometers

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

FOREWORD

“Most color measurements are made for the purpose of specifying a particular color, frequently to ensure a color match. Unlike a dyestuff, manufactured under controlled conditions, a foodstuff is subject to the vagaries of the weather and other variables which affect the natural coloring matters. Consequently the color of a food becomes an important criterion of quality. Is the color characteristic of what we expect from good quality raw material, ie., is the color natural? Has it undergone changes suggestive of deterioration in the foodstuff itself? How much may the color vary before we feel the product to be of inferior quality? Answers

301

302 G. MACKINNEY AND C. 0. CHICHESTER

to these questions of course depend on how strongly we are conditioned to show color preferences. This in turn depends on the product. Butter must be yellow, although considerable latitude in the degree of yellowness is tolerated. A greenish discoloration sometimes observed in eggs, on the other hand, is never acceptable.”’

I. INTRODUCTION

The science of color is hampered in its development by the fact that we are all color-conscious, scientists, artists, and laymen alike. We resist attempts to restrict the use of everyday terms in describing our experiences, even though our description would thereby gain exactness. We are equally unwilling to reject familiar terminology in favor of an entirely new one, defined so as to be free from ambiguity.

As estimated by the Committee on Colorimetry of the Optical Society of America (1953, p. 129), the “volume of the discrimination solid for reflected’ color is about 7,500,000 threshold elements.” (For a discussion of discrimination steps, thresholds or limens, see Section 111, “Some Theoretical Considerations.”)

We must therefore accept the view that a trained eye can differentiate between a vast number of different shades of color. This can be achieved only by direct comparison of series of colored samples, and even then the number of distinguishable shades is limited by the illuminants used and the background conditions under which the comparisons are made. Also, the level of illumination is of critical importance, since different sensitive elements in the retina, the rods and cones, are responsible for vision a t low and high levels, and the type of response, i.e., the color perception, is different in the two cases.

The overriding color problem is to obtain an objective, precise, and reproducible procedure for measuring quantitatively the differences which can be perceived. To do this, we must impose certain restrictions on our concept of color and its attributes. “Color consists of t’he characteristics of light other than spatial or temporal inhomogeneities,” light itself then being defined as the aspect of radiant energy responsible for human vision. The Committee on Colorimetry (1953) can thus concentrate on what Troland (1929) has called “opaque surface character,” which can be determined by reflecting objects with highly diffusing (matt) surfaces. These surfaces, according to Troland, “carry most of the typical color phenomena of everyday experience.” As we depart from the diffuse opaque surface, we become increasingly concerned with gloss (specular

1 From a talk by G. Mackinney on “Color Measurement of Different Commodities,” Quartermaster Food and Container Institute Symposium, November 3-4, 1953, Chicago, Illinois.

THE COLOR PROBLEM IN FOODS 303

or mirrorlike reflection), transparency, and turbidity. The specular component of reflection is eliminated instrumentally in most cases, and corrections can be made for turbidity. When we come to the transparent colored body, further restrictions are necessary if we are to specify its color successfully. If we have two portions of a given transparent object and view them under identical conditions, except that the light paths differ in length in the two cases, we shall find two colors differing not only in the brightness factor but in chromaticity2 as well. The color of a transparent bulk commodity is thus uniquely defined only when the length of the light path is included in our conditions of measurement.

In our presentation, we omit discussion of many charts and dic- tionaries of color ( e g., Ridgway, Maerz and Paui) which may be familiar t o many. We justify the omission on the ground that more precise or more convenient systems exist for measurement of color in foods. This is not to argue that these charts have outlived their usefulness or that they will necessarily be abandoned. We shall emphasize, in our discussion, the usefulness of the C.I.E.3 system (and the 2, y, chromaticity diagram) and also the Munsell color space. Because one instrument (Hunter Color- Difference Meter) discussed here measures quantities in a transformed color space, we cannot safely ignore the problems arising from nonuniformity of color spaces, and procedures for effecting transformations.

In this introduction, we shall attempt, for the reader unfamiliar with these concepts, an elementary discussion of the problems of color space and specifically of the C.I.E. color space. We shall begin by considering the colors, R, G , and B of any convenient red, green, and blue light sources a t the apexes of a Maxwell triangle (Fig. la). We can mix these primaries in any proportions we wish, and the resulting colors must lie within the confines of this triangle. In the center, we shall have white. We cannot, however, reproduce any color which is redder than our selected red primary, and the same limitation applies to green and blue colors. To represent all possible colors in a plane, resort is made to imaginary or unreal primaries. This is purely a mathematical device, somewhat analo- gous to asserting one’s net worth not merely in terms of an outstanding bank balance, but in addition, whatever overdraft the bank might be induced to carry, and whatever credit one might secure. The base line for calculations is simply changed.

Extending the corners of our Maxwell triangle, to locate our new

2 By chromaticity, we refer to attributes equivalent to hue and saturation, independent of photometric brightnes!, lightness, or value. Commission internationale de 1’Eclairage formerly I.C.I., the Internationa1,;Com- mission on Illumination. Reports of this Commission are to be found in the Journal of the Optical Society of America.


primaries wherever we decide, we may again make mixtures, and in this space there will be a line of demarcation (the plot of the pure spectral colors) between what is real and what is imaginary. The line joining the extremes of this plot delimits the purples. We thus create a chromaticity diagram, Fig. lb. This, however, does not completely define the color, which may be dark or light. Reverting to the original Maxwell triangle for a moment, we may visualize our central spot varying through an infinite series of grays from white to black. We complete our definition

4 S p e c t r u m locur

\

‘pu r p I c s

FIG. la. Maxwell triangles (triangular co-ordinates). The color triangle obtained by use of primaries red, blue, and green (R, G, and B) chosen for convenience or availa- bility. They do not have to form an equilateral triangle, nor is white necessarily a t the precise center. Even if pure spectral colors had been selected, the plot of the spectrum locus shows that no three real primaries can be selected which will match all possible colors.

of a color, therefore, by erecting a perpendicular to the chromaticity plane along which the apparent brightness may be plotted. We have thus created a volume which can be referred to rectangular co-ordinates, and which constitutes a “color solid” or “color space,” as in Fig. 2. The International Commission on Illumination provided in 1931 a standard observer, standard (though unreal) primaries, and standard illuminants and the basis for a standard system of co-ordinates.

In matching colors by reference to three primaries, we are dealing in a trichromatic system. The X Y 2 tristimulus values of C.I.E. space are created by simple linear transformation of the color space of R G B . Given any second system, R1, GI, B’, the two may be related thus:4

In Figure la, we locate a color by the proportions of R, G, and B required for a match. In a transformation, the absolute amounts of R, G, and B must be used.


R' = alR + blG + clB G' = azR + b& + czB B1 = arR + b& + c3B

With nine parameters, a1 to c3, and eight degrees of freedom, we have considerable flexibility and some choice as to the properties of a new space

G'

FIG. lb. The same spectrum locus is traced. The primaries R1, GI, and B1 are no longer real but the area enclosed by the broken line contains all possible real colors, and they are all reproducible by appropriate mixtures of R1, GI, and B1. This is not possible in all cases where R, G, and B are used, unless we are willing to adopt other artificial devices, such as negative colors. Thus R might be made equivalent to R 1 by adding to it negative amounts of primaries B and G, represented by the blueness and greenness differences inherent in (R1 - R). The enclosed area constitutes a chromaticity diagram.

in any transformation we may propose. The X , Y , and 2 tristimulus values thus enable us to locate a color in the color space, but they are in- convenient for direct comparison. Trichromatic coefficients (x,y,z) were therefore derived, such that

X Y x = X + Y + Z ) y = x + Y + z '

etc., and consequently x + y + z = 1. Hence a color is fully defined by z, y, and Y . It is unfortunate that the C.I.E. color space is nonuniform

306 0. MACKINNEY AND C. 0. CHICHESTER

with respect to perceptibility differences. Thus if we examine two colors separated by a given distance in the red with two separated by the same distance in the green, the differences in color perceived by the eye will be smaller for the latter.

As we approach the extremes of black and white, our ability to distinguish the colors becomes increasingly uncertain. The color solid is

X

FIG. 2. The C.I.E. Chromaticity Diagram (rectangular co-ordinates). This diagram constitutes a transformation of Fig. l b with rectangular co-ordinates in terms of 2, y, the C.I.E. trichromatic coefficients derived from the original X Y 2 tristimulus values,

The lines OD, ODI, OD11, are lines of constant dominant wave length. The inner figure indicates a locus of constant purity.

therefore highly irregular in shape, and this is true of any color space including the Munsell.

From the foregoing, it should be clear that three measurements are needed to determine color. It is not essential that we use a trichromatic system. A color match may be achieved by mixing white with a spectral color (except in the case of purples, where the complementary green must be subtracted). The spectral color required for a given match is termed the dominant wave length. The degree of saturation is given by the per

307 THE COLOR PROBLEM IN FOODS

cent purity (100% white = 0% purity, and 100% spectral color = 100% purity) , and a measure of photometric brightness completes the specification. In the C.I.E. space, we may designate them by 2, y, and Y or, alternatively, by conversion to the quantities termed dominant wave length, purity, and lightness. In the Munsell space, the appropriate terms are hue, chroma, and value.

It is disconcerting that, while the mind can readily grasp these distinctions and recognize these three attributes of color, they are not so

Purity. per cent

FIQ. 3. Whiteness diagram. For dominant wave length 575 mp. This diagram was suggested to us by Professor A. C. Hardy. Original data may be found in articles by Judd, Paper Trade Journal, 1935, 1936.

clearly differentiated by the eye. The whiteness diagram, Fig. 3, illustrates this point. If we follow the parabola passing through the point-purity 0.4, brightness 7&to the point represented by purity, 2.0, brightness 76, the same perceived whiteness is observed. In other words, the eye will accept as equivalent in whiteness, specimens with different purities, provided the brightness (lightness, in present terminology) is suitably adjusted. Similar adjustments are made by the eye with respect to hue- chroma or dominant wave length-purity changes. This has been observed in tomatoes, where perceived redness is not solely an attribute of hue. To some extent, this may be helpful, in forcing us to recognize that all three


attributes of color determine the perceived color, that the lightness scale is not, outside the central gray point, a purely neutral component.

The historically earlier Munsell color space was developed as a result of an entirely different concept. The C.I.E. system permits a unique specification of a particular color in a reference framework that, regardless of certain conveniences, is highly artificial; whereas the Munsell system is an attempt at systematic sampling of the color solid, by use of permanent reproducible standards. The hues are arranged on a 100-point circular scale from 1R (red) to 10R, then 1YR (yellow red) to lOYR, and similarly through Y to YG, G (green), BG, B (blue), BP, P (purple) and from lORP (red purple) back to 1R. The 10-point value (lightness) scale normal to the plane of the circle ranges from 0 / , black to value lo/, white. The chroma or saturation is arranged radially from the central achromatic gray, chroma / 0 , to that of the fully saturated hue. The numerical value depends on the saturation attainable for a given hue and value, As an example, for hue 5R, attainable chromas at values 1/ and 7/ are approximately /11 and /16 respectively. As Judd (1952) observed, a collection of color chips based on the radial organization favors a closer sampling near the achromatic gray, and a correspondingly poorer sampling of the saturated colors. Judd’s discussion of systematic sampling of the color solid is particularly interesting in its suggestion of a collection of chips organized on a three-layer packing principle.

Because the Munsell collection has now been evaluated in terms of C.I.E. space, accurate interpolations are possible. The most accurate Munsell specifications are now based on C.I.E. data, and it may well be that the greatest value of the Munsell space in the future will be in enabling us to see how a specified color is perceived under standardized conditions. The Munsell quantities are uniformly reported in terms of hue, value, and chroma, in this order. Thus the designation 7.5YR/4.1/5 signifies a hue of 7.5YR, a value of 4.1, and a chroma of 5.

Five important treatises on color have appeared in recent years. “Handbook of Colorimetry” (Hardy, 1936) is a direct outcome of the eighth session of the International Commission on Illumination in 1931. It enables us to compute psychophysical values for brightness (later termed luminous reflectance and now, lightness) and chromaticity (dominant wave length and purity) from the raw spectrophotometric data. In these psychophysical terms, a colored sample may be uniquely defined with respect to its color, provided that we follow a standard procedure for determining the spectral reflectance or transmittance of the sample. The perceived color, however, is not defined, and we enter here into psychological considerations as distinct from those of psychophysics. The C.I.E. quantities z and y (the trichromatic coefficients which


define the chromaticity) and Y (the tristimulus quantity which defines the lightness) are directly computed by aid of a standard observer, standard illurninants, and standard primaries from the spectrophotometric curve, by use of tables compiled by Hardy and his associates. The nontechnical reader for whom this presents difficulty is advised to begin with three Tintometer pamphlets (G. J. Chamberlin, 1951; A. J. Fawcett, 1952; Tintometer Ltd., 1950; or with General Electric Bulletin LD-2 by Sturrock and Staley, 1950).

“An Introduction to Color” (Evans, 1948), presented in nonmathe- matical terms, is especially useful in its discussion of color perception and of the distinction between color as calculated in psychophysical terms and color as perceived by the mind. This author points out that a colored object or scene may yield knowledge, create an illusion, or even involve hallucination. Such experiences are explained simply by Evans as follows : when we think we know the color of an object, we do not look to verify the assumption. Consequently, we can be victims of a genuine hallucination. The observer does not look at the stimulus but relies on his memory.6 It is important to realize that the definition of color psychophysically is in essence a definition of what a carefully standardized eye receptor is presumed to record in response to a given stimulus, under prescribed conditions, and has nothing to do with how it may be interpreted by the brain.

The Dutch edition of “Physical Aspects of Colour” was completed by the late P. J. Bouma in 1945. It has been translated into English with some additions by de Groot (Bouma, 1947). The concept of color space is extremely well developed, together with the problem of transformation from one system to another, as, for example, the U.C.S. system (uniform chromaticity scale), in which ideally the colors would be uniformly dis- tributed over the color plane, as judged by the eye. The historical development of color science is also thoroughly treated.

The National Bureau of Standards has been in the forefront of research in color measurement and in the development of lightness and chromatic

6 The psychologist is unlikely to agree with the interpretation that hallucinations are involved. As Professor D. Kresch has observed: “The relation between stimulus and sensation is not simple, but it is systematic.” The example frequently cited is the result achieved by the experimenter who uses spinning discs to match the color of a purple banana. The disc is invariably too yellow, apparently because of the experimenter’s knowledge that the ripe banana skin ought to be yellow. There are those who would analyze problems of color preferences in terms of the Gestalt, i .e., in con- tezt, and a t the other extreme, in purely subjective terms. Granger (1952) seems to steer a middle course, concluding that “color preferences are objective in the sense that: (a) they are to a considerable extent independent of personal taste, and (b) they are dependent to some degree on inherent stimulus properties.”

310 Q. MACKINNEY AND C. 0. CHICHESTER

scales. “Color in Business, Science and Industry” (Judd, 1952), written by a member of the Bureau of Standards, is therefore especially valuable for its analysis of the problems; the worker with color measurements to make will find detailed appraisals of methods and available instruments, and assistance in the procedures for computation.

The latest of the five treatises discussed here is entitled “The Science of Color” by the Committee on Colorimetry of the Optical Society of America (1953). A slight letdown is possibly inevitable, which a rereading does not entirely banish. The report is designed to include an elementary discussion to attract and hold the attention of casual readers, with a gradual transition to more advanced exposition. The food technologist tackling the psychophysics of color is apt to be impatient when confronted with distinctions between operational and relational definitions. He learns that “the use of quantitative concepts would specialize the relational definitions in an undesirable manner” (loc. cit., p. 220). Con- tinued study makes the reader more aware of the problems facing the Committee. Is color to be defined as a sensation or in terms of perception? How many attributes of color are to be admitted?

The five treatises necessarily cover much common ground. “Hand- book of Colorimetry” will remain a standard so long as color is specified in terms of the 1931 C.I.E. conventions. The other books cover a wider field, and collectively they provide a balanced perspective which an individual viewpoint can rarely achieve, and all five have proved their worth to the present writers.

To some extent, the food technologist is today at a crossroads, and decisions which are made in the next few years will govern our whole approach to the problem of color measurement and color specification. Shall we, for example, specify color in terms of the C.I.E. quantities, or shall we proceed by measurement of color differences? How do the Mun- sell, Lovibond, and other systems fit into such a plan?

In a book devoted to advances in a field, we cannot write a treatise on color, even if it lay within our competence to do so. We must therefore presuppose that the reader will acquaint himself with the concepts discussed in the above-mentioned monographs. Additional background is furnished by the following National Bureau of Standards publications : Spectrophotometry (Circular 484) , Photoelectric Tristimulus Colorimetry with Three Filters (Circular C429) , Colorimetry (Circular 478). We shall refer to these and to research articles in the Journal of the Optical Society of America, when necessary, and proceed to discuss their application to foods, emphasizing those problems with which we have had direct, if limited, experience.

As the first reviewers on color for Advances in Food Research, we feel justified in making an individual selection. That subsequent reviewers


will supplement our choice and modify our interpretations should be obvious. " Colour, in Theory and Practice "by Murray (1952) for example, has just come to our attention via a review in Nature, and numerous other monographs and papers might well have been cited, but i t has not seemed necessary to our purpose to attempt completeness at this stage.

In the last analysis, we are interested in color in foods because the consumer of foods has certain color preferences. He will buy and eat primarily according to those preferences. It is surprising how revolting an egg can appear, particularly when poached, if the hen has been fed a diet adequate in vitamin A but devoid of carotenoid. The yolk is an unnatural ivory-white, though perfectly normal from a nutritional standpoint. It has frequently been stated that color involves problems in physics, psychology, philosophy, and aesthetics. It is not unfair to caution the reader that in the opinion of some of our colleagues in psychology and philosophy, only the physical aspects have been adequately treated.

We have arbitrarily chosen seven commodities around which to build our discussion. The selection is governed by the fact that work has been done on these commodities which serves to illustrate the problems in determining color in different regions of the color plane: whiteness in sugars and flours; yellowness in oils; greenness in certain vegetables; redness in tomatoes and tomato products; darkening of strawberry preserves; the color of grape juices, jellies, and wines. Three of these commodities are standard articles of international commerce : sugar, flour (more correctly, wheat), and oils, and the price is determined by the condition of the respective world markets for sugar, grain, and oils. This cannot be said of wines, and certainly not of canned fruits or vegetables.

Consequently for the first three, we may expect to find professional groups keenly aware of the necessity for describing an offering in terms that can be understood in the world market. Thus in this country there is established the New York Sugar Trade Laboratory and a United States National Committee on Sugar Analysis, an affiliate of the International Commission for Uniform Methods of Sugar Analysis. This is probably the most organized of the three.

By contrast, we have a series of local markets for canned fruits and vegetables. Even though standards prevail on a nationwide basis, these are not always adequately defined. A concerted attempt is being made, therefore, to improve color specifications. This is especially true for tomato products.

11. COLOR IN SELECTED COMMODITIES

1. Sugar

The individual sugar crystal is transparent. The whiteness of the mass is due to reflection of light from surface and subsurface layers. The light

3 12 G. MACKINNEY A N D C. 0. CHICHESTER

from subsurface layers undergoes refraction as it passes through the crystals, and the quality of the light transmitted is affected by selective absorption to the extent that colored impurities may be present.

Measurement of color of sugar products has been discussed by Browne and Zerban (1941). We shall omit consideration of Stammer’s colorimeter and the Stammer degree scale, even though this has been extensively used in the past by the European beet-sugar industry. The modern approach requires transmittancy determinations on colored sugar solutions and on “liquid sugars,” while reflectance measurements may be made on solid sugars. I n 1952 neither the Association of Official Agricultural Chemists nor the International Commission for Uniform Methods of Sugar Analysis and its affiliated United States National Committee on Sugar Analysis had adopted standard methods for determining the color of sugars and sugar products, although there was general agreement that for a standard method of color determination, precise photoelectric spectrophotometers would have to be used. There was still a controversy about the proper method for preparing the solutions the transmittancies of which were to be measured.

According to Zerban et al. (1951), Peters and Phelps of the National Bureau of Standards first devised a procedure for determination of the color of sugar and sugar products based on an “absorbancy index” (a5~0) at 560 mp. This index is the negative logarithm of the transmittancy for a solution of concentration of 1 g. of dry substance in 1 ml. of solution for a thickness of 1 cm. The value at 560 mp (‘ . . . is equivalent colori- metrically to the sum total absorption over the visible range.” Zerban et al. (1951) provided experimental verification by measurements of transmittancies a t various wave lengths of 60 ’% solutions filtered through Celite filteraid, of seventy-six different refined sugars. The dominant wave length varied from extremes of 578.2 to 572.0 mp, and the purity from 4 to 63.1.

A similar study on raw cane sugars by Zerban et al. (1952) leaves no doubt that the index a660 is equally useful as a single-value function to describe the color of a sugar solution whether refined or raw.

Two questions arise in connection with these studies: how was it possible to develop a single value function for expressing the color of a sugar, and why should a single measurement a t 560 mp be a practical solution to the problem?

As noted above, Zerban et al. (1952) determined the tristimulus values by use of ten selected ordinates and Illuminant C (Hardy, 1936), and dominant wave length, purity, and brightness were recorded. Corre- lating asBO (or T 6 6 0 ) with these three components determining the color, they obtained a multiple regression equation in which the influence of

T H E COLOR PROBLEM IN FOODS 313

each on a680 (or Taco) is determined. Separate expressions are needed for raw and refined solutions, but the conclusions are identical, that a t 560 mp, the influence of purity and dominant wave length is small compared with the effect of the brightness component. The following facts are to be noted: first that the dominant wave for the solutions, centering around 575 mp, is not far removed from the peak (555 mp) for the visibility function, on which the brightness is based. The dominant wave length is in essence a spectral center of gravity. Small variations at high transmittancies in this region should not have any marked influence. The purity is a measure of the distribution on either side of this spectral center. Here we observe differences. As one may deduce from the published transmittancy curves for the refined sugars, on the long wave length side, ie., above 575, the distribution is essentially uniform, while below 575 mp divergencies are increasingly apparent with increase in yellowness. The yellowness of the raw sugars differs significantly from that of the refined, and the transmittaricy ratios at 420 mp relative to 560 mp are substantially higher for the latter. Thus a420 bears a less direct relation to the brightness. “The refined sugars have throughout a higher purity at equal brightness than the raw.”

It is to be expected, therefore, for this type of problem, where the dominant wave length is reasonably close to 555 mp and where the photometric brightness is high, that a single-value determination around 555 or 560 mp should be obtained which can be correlated with the visually observed color. An accurate absorbancy index requires a nonturbid solution. Provided such solutions have the same purities and the same dominant wave length, a single measurement a t any arbitrarily chosen wave length below 575 mp would be satisfactory. Selection of 560 mp has the advantage of minimal differences in slope, or purity, in the event that the purities are not strictly equivalent in the solutions under examination.

Gillett et al. (1949) approached the whole problem in a different manner. They did not attempt to obtain a clear solution but corrected for turbidity by a measurement in the near infrared (using a Wratten No. 88A filter which does not transmit below 720 mp). Turbid matter was then added to 50% sugar solutions and straight-line plots were obtained for a series of filters for concentration of turbid matter as a function of - log T. They then determined the color by a measurement with a Corning No. 554 filter, maximum transmittance a t 420 mp. This choice emphasizes yellowness in the solution. The turbidity is then determined from the infrared reading, and the 420 mp reading is corrected for this degree of turbidity as i t affects the No. 554 filter. It is not clear to us that this precise procedure has been used on products varying from

. . . light-colored washed raw sugar liquor . . . to dark-colored < <

314 G . MACRINNEY AND C. 0. CHICHESTER

affination green sirup . . . ” (Meads and Gillett, 1949), but the crux of the problem is now clear.

As already stated, a definitive answer is possible in terms of an absorbancy index (or transmittancy) which can be correlated with the color in terms of the C.I.E., provided always that we are dealing with nonturbid solutions. Regardless of the practical difficulties in achieving a clear solution without loss of color, this tying-in with the C.I.E. system is an enormous asset to the value of the absorbancy index. With regard to the procedure of Gillett et al. (1949) its successful application is predi- cated upon two assumptions: (1) that the turbidities of the tested products are due t o turbid matter with essentially the same properties (including the light-scattering power) as the turbid matter used (ben- tonite) in calibrating; and (2) that the corrected second reading at 420 mp is a direct measure of the concentration of coloring matter of reasonably uniform composition. The latter requirement means that the ratios of - log T at any two wave lengths we may care to choose shall be constant throughout the series of samples under testsE The method is attractive because of its speed and simplicity, and it works undoubtedly because the assumptions are valid the majority of the time. Zerban et al. (1952), however, have demonstrated exceptions to the procedure. Furthermore it is tacitly implied that color and turbidity are separable. If it be argued that the turbid matter cannot be removed without modification of the color of the resultant clear solution, we are immediately confronted with the dilemma that the color (corrected for turbidity) describes a system we cannot hope to see in practice. This is not to minimiee the practical usefulness of the method in routine control.

Wiklund (1950) in his report to the International Commission for Uniform Methods of Sugar Analysis analyzed the difficulties yet un- resolved. He pointed out that a source of error in transmittance measurements lies in polarization differences between standards and unknowns. He cites Evans (1948, p. 213): “ . . . A system of material standards having the same energy distribution over the range expected in the sample may be made to give very high precision results . . . Such systems, of course, may be correlated satisfactorily with another system such as the I.C.I. because, in effect these eliminate the observer as a variable.” We shall revert later to the question of material standards. Whalley (see Wiklund, 1950) remarked that the infrared and 420 mp measurements by the method of Gillett et al. (1949) apply only to high-grade refined sugars, and even then are dependent on particle size of the turbid matter.

Since the impurities are yellow, we shall stipulate that the choice shall be between 400 and 550 mp.


In March 1953, the United States National Committee adopted the following procedure: the Tsao measurement is now limited to raw cane sugars, the solutions being prepared and filtered according to specific instructions. Because the solutions still contain fine particles, the Taao reading is converted to an “attenuation index,” the term “specific absorptive index” being abandoned. In the case of white sugars, the recommendation is that the color be determined by measurements at 420 and 720 mp. Since the white sugar solutions cannot be easily filtered, a correction is applied for turbidity to the 420 mp reading. Experimentally some variation is found in the relationship between turbidities at 420 and 720 mp, respectively, though it is approximately twice the attenuation index a t 720 mp. The factor 2 is therefore chosen, and the color of the sample is given by the measured index a t 420 minus twice the index a t 720. It may be further added that Gillett (1953) has reviewed the whole subject of color measurement in sugars and sugar products.

In the grading of sugar cane sirup and edible sugar cane molasses, Broeg and Walton (1952) discussed the use of inorganic salt solutions developed by the American Molasses Company. These are used for grading products according to the permissive grades of the United States Department of Agriculture for sirup and molasses from sugar cane. This of course is recognized as a temporary expedient.

Bruce and Turner (1952) developed polished glass standards, now in use, for determining color specifications and tolerances for maple syrup and honey, based on the C.I.E. system. They can be used for both clear and cloudy liquids.

Reflectance measurements of white sugars have been made by Gillett and Meads (1952). They observe that the amount of color is extremely small, that 94% or more of the incident light is reflected by high-quality white sugars of normal granulated grain size. Even lower quality sugars will reflect 90% of the incident light. They further remark that “more finely divided particles appear whiter than coarse particles, both to the eye and to photoelectric devices. Furthermore differences in luster influence results, and differences in apparent grayness sometimes confuse the detection of yellowness in the sugar.”

The single-value reflectance measurement made by Gillett and Meads (1952) is not immediately convertible to C.I.E. values. A light blue Corning Daylight type No. 590 filter with a 200-w. projection lamp simulates daylight from the north. The photogenerative type of cell used (Gillett and Holven, 1943) is presumably a selenium cell with characteristics given in Fig. 22 of the bulletin by Sturrock and Staley (1950). This requires special filters if it is to be corrected to approximate the spectral sensitivity of the human eye. Otherwise, it is somewhat more sensitive

316 G . MACKINNEY A N D C. 0. CHICHESTER

in the red and substantially more so in the blue. For detecting traces of yellowness, the unmodified sensitivity would seem more desirable.

2. Flour

Flour is opaque and its whiteness is due to nonselective diffuse surface reflectance. There has not been such interest, internationally, since the world market is for the whole grain, rather than flour. Thus the professional group in the United States (American Association of Cereal Chemists) has no committee on the measurement of flour color, although collaborative studies have been made on methods for determining the yellow pigment content-chiefly carotenoid in nature-of wheat flour. This lies outside the realm of the present review. Four main factors determine flour color, according to Kent-Jones (1952) :

1. The grade of the flour (contamination of endosperm with bran). 2. The yellowness (carotenoid pigments not completely removed by

3. The granularity-(the larger the granules, the darker and duller the

4. Dirt, smut, etc.

The yellowness of flours is caused by selective absorption of blue by yellow-colored naturally occurring pigments or impurities. The problem is strictly twofold: measurement of the total reflectance (a brightness or lightness value) and an independent measurement in the blue. If a flour is gray owing to inclusion of dark particles, the total reflectance or luminosity is decreased by nonselective absorption so that only one measurement, that of diffuse reflectance, is needed. It is interesting to note that the flour technologists appear to ignore yellowness in reflectance measurements, presumably because this can be controlled by the bleach. If not, the yellow is determined indirectly by extraction of the yellow coloring matter, which is then estimated as such. Thus Irvine and Anderson (1952) deliberately choose to make reflection measurements a t 600 mp to ensure that the carotenoids will not affect the answer. Kent- Jones (1952) uses a filter with maximum transmittance at 530 mp where the pigments still do not have too much effect. Investigations are far less advanced here than in the sugar industry. While the single-value measurement for color may be justified, results to date consist of photometric brightnesses a t some particular wave length which may or may not correlate with visual brightness, depending upon the nature of the im- purity. The empirical nature of the work does not impair its usefulness, though the terminology may cause confusion. The usefulness is shown in relating this measure of “brightness” in the flour with the crumb color

bleaching).

flour).


of the loaf. Irvine and Anderson (1952) have set up an arbitrary score to demonstrate such a relationship.

It may be pertinent here to review briefly the development of the Flour Color Grader (Kent-Jones and Martin, 1950; Kent-Jones, Amos, and Martin, 1950). Prior to the development of this instrument, solvent extraction of the bran pigments was used. This is time-consuming and is not an accurate measure of the flour grade. An ash test was also much used. It depended on the low ash content of the endosperm, 0.3%, con- trasted with 8.0% for the outer coverings. The Color Grader with its speed and accuracy was therefore certain of favorable reception. We may properly inquire, however, whether this method should not evolve in the direction taken by the sugar industry. The Gillett-Meads instrument with filters to approximate the spectral sensitivity of the eye would yield a single-value determination essentially equivalent to photometric brightness; the industry is interested primarily in grayness, since measurements have been made at 600 and 530 mp with apparently equally satisfactory results. Finally, the measure taken must be related to some desideratum, e.g., crumb color. Consequently either the C.I.E. brightness or an absorbancy index ax (where the most favorable X has still to be determined) must be correlated with a corresponding quantity of industrial value (presumably crumb color).

3. Oils

The American Oil Chemists’ Society (1946) has published a loose-leaf book of methods which are subject to continuous scrutiny and revision. The following methods for determining oil color are given:

1. Official Method Cc 13a-43, applicable to animal fats and to all fats and oils too dark to be read by the Wesson method.

2. Official Method Cc 13b-45 (Wesson method) corrected November, 1947, applicable to all normal fats provided the samples are not turbid.

3. Tentative Method Cc 13c-50, revised October, 1951, applicable to cottonseed, soybean, and peanut oils.

4. Tentative Method Cc 8d-48 (formerly Cc 8d-47), revised January, 1948, refined and bleached color, applicable to tallows and greases for soap. This deals with samples requiring special treatment prior to application of the Wesson method. Since it is a special case of the latter, involving no differences in principle in the color determination, it will not be considered further.

5. Tentative Method Ka 3-47. This method utilizes a series of eighteen Gardner Standard Colors and is applicable to natural and synthetic drying oils of the same hue as the Standards. These consist of inorganic salt solutions, and a simple direct comparison is made, so that the sample


receives a numerical rating from 1 to 18, or “darker than 18,” according to its position on the Gardner Scale.

The first method employs F.A.C.’ Standard Colors. These consist of inorganic salt solutions also. Unlike method (5), applicable to oils of constant hue, this series of solutions makes provision for changes in hue. The fats are classified in five groups as follows: light-colored, predominantly yellow, dark (red cast), very dark (predominantly green), and very dark (predominantly red).

The second method employs Lovibond glasses. These glasses have been evaluated in terms of C.I.E. quantities; this is of great importance because it represents the first case in this discussion where such a possi- bility is embedded in an official method.

For comparison, a standard white block of magnesia is required, and specifications for a (‘ Wesson-type” colorimeter are approved, together with provisions for the illuminant and for viewing by visual means. The conditions are very carefully specified. Thus in the viewing booth, the level of external illumination at the top of the colorimeter box shall be not less than 1 nor more than 5 foot-candles. This obviates errors due to the Purkinje effect involving too low a light intensity (rod vision), yet extraneous light is held to a relatively low level.

The Lovibond grading of vegetable oils is discussed in some detail by Judd (1952, pp. 209-212). It was shown by McNicholas (1935) and is obvious from the classification of oils in method Cc 13a-43 that there are two groups of pigments, green (chlorophyll-containing) and yellow (frequently due to considerable quantities of carotenoid, but probably also at times to brownish pigments in varying amount). As Judd points out, these vary independently.

Let us now take a specific example of the procedure. The official method is as follows: “a. Refined Oil. Use only 1 yellow glass, 35 yellow for refined cottonseed oil and refined peanut oil, 70 yellow for refined soybean oil. Use not more than 2 red glasses up to and including 13.0 red, and not more than 3 red glasses above 13.0 red. ”

To digress for a moment, color matches are of two kinds. Thus an unknown carotene solution may be matched against a standard carotene solution or against selected Lovibond glasses. I n the former, the spectral composition of the transmitted light is identical in the two cases. They can differ only in brightness, and when a match is achieved, the colors will appear identical regardless of the illuminant. In the second, the spectral composition of the transmitted light is not identical, although the match may be readily achieved. It is valid only under specified conditions of illumination and viewing. This type of match is said to be 7 Fats Analysis Committee, A.O.C.S. and A.C.S.


metameric. Furthermore, since the match involves judgment on the part of the observer with respect both to hue and to brightness, it is more dependent on the observer than the former (non-metameric), where only one variable, brightness, is involved.

Matches following the official method just cited are clearly metameric. As Judd correctly points out, no one-dimensional grading system can yield perfect color matches, because of variability in the two pigment groups which determine the color of an oil. The official method is one- dimensional, as it prescribes a single yellow, e.g., 35Y, 70Y, etc., with a variable red, for this particular category of oils. This has probably been an inevitable development, since a two-dimensional system would have led to uncertainties in interpretation. Furthermore, the difficulties are not too great in practice, or the method would not enjoy the confidence of the industry.

Method Cc 13c-50, a photometric method, is designed to obviate some of the difficulties mentioned under use of the Lovibond. The measurements are made a t selected wave lengths, for which empirical constants are developed to correlate the reading with the Lovibond. This reading, the so-called “photometric color ” D, a modified optical density, is defined thus:

D = 1.29D4~0 + 69.70560 + 41.2Dazo - 56.4Dmo.

The method is based on collaborative work by the Color Committee of the Oil Chemists’ Society. Thomson (1947) related the thinking which led to the selection of specific wave lengths for the measurement. The spectral transmittances of three groups of oils are given, light, medium, and dark. Work at Swift and Company apparently led originally to the selection of 400, 540, and 670 mp to cover a wide range of oil colors. Dark tallows do not transmit appreciably below 600 mp. Light oils, on the other hand, may transmit from 5 to as much as 50% at 420 mp (5-cm. cells). In the absence of chlorophyll, the corrections at 670 and 620 mp will be negligible, except possibly for a dark tallow, where the contribution a t 620 mp may be appreciable.

An interesting extension of the photometric color method of the A.O.C.S. is found in the work of Moster and Prater (1952) on their measurement of color of Capsicum spices. The common method used at present (according to these authors) involves matching an alcohol extract of the spice against combinations of red and yellow Lovibond glasses. “Variations (in the yellow) have only a slight effect upon matching the red glasses, and it has become a widespread practice to use a 20-yellow glass and express the Lovibond value as the number of additional red units needed to obtain a match . . . the widespread experience


of the industry indicates that this color does correlate with the tinctorial value of these spices.” It appears from further observations that the same problem arises with Capsicum when the experimental variability is limited to one dimension. Moster and Prater therefore developed a spectrophotometric procedure which they call the Gentry method. They prepare alcohol extracts which transmit insignificant amounts of blue. Therefore the 2 tristimulus value, and hence z, the trichromatic coefficient, are both zero. Under these circumstances x defines the chromaticity, since z + y + 0 = 1. Thus, from the properties inherent in the extract, they have a one-dimensional chromaticity scale which can be compared directly with the one-dimensional red scale of the Lovibond. Because, as before, two pigment groups are involved, carotenoids and chlorophyll or chlorophyll derivatives, they required measurements a t a minimum of two wave lengths. For chlorophyll, 663 mp is a natural choice, the point of maximum absorption in the red for chlorophyll a in the solvent used. The transmittances of chili and paprika extracts below 540 mp are so low, except a t high dilution, that choice of the second wave length is limited to the yellow and orange regions. Several wave lengths were considered, and because the color range for the samples was great, from 11 to 36 red units on the Lovibond, it was necessary to place the samples in two groups. The wave length 569 mp was selected for low Lovibond red numbers, and 577.5 mp for the high. The authors showed that for a substantial overlap, either wave length might be chosen. Two equations were then formulated:

1. Gentry (color) units = T669 + 0.2(100 - T 6 8 3 ) .

2. Gentry (color) units = T6,7.6 + 0.2(100 - T663) - 14.2.

The first term on the right is the principal factor in determining the size of the Gentry unit. The higher the chlorophyll concentration, the lower will be the value of T 6 6 3 , and the greater therefore the numerical value of 0.2(100 - T 6 6 B ) ; a low Gentry number is indicative of a high red color, and therefore the T 6 6 3 correction factor gives a higher Gentry number with correspondingly less “redness.”

The Gentry unit was expressly designed to correlate with the x trichromatic coefficient, and there is an almost exact inverse proportionality between it and x over the range 1: = 0.67 to 1: = 0.59. (Recall that in these samples x + y = 1, so that Moster and Prater have developed a one- dimensional scale on the basis of their two measurements.)

Over this range of Lovibond reds, x (and the Gentry Units necessarily also) shows deviation from linearity with the Lovibond reading below x = 0.64. Below a Lovibond reading of 22 red, the limitations imposed by insisting on using the Lovibond one-dimensionally (ie., with

T H E COLOR PROBLEM IN FOODS 32 1

a fixed yellow) become apparent, because a two color-component system is now involved.

The oil chemists have avoided the more serious of these difficulties by alternative methods, using F.A.C. Standards, for example, for different hues. Melvin, et al. (1953) have studied the spectral characteristics of green soybean oil and have suggested optical density values at selected wave lengths which would delimit Grade 2 for crude, refined, refined and bleached oils. Thomson (1953) has further discussed single-number systems with particular reference to the measurement of color of cottonseed and soybean oils.

4. Tomatoes and Tomato Products

The Production and Marketing Administration of the United States Department of Agriculture promulgated standards of identity, including color specifications based on the Munsell system for tomato pulp (pur6e) , juice, paste, and catsup. We shall consider the specifications for pulp, the grade of which is determined by a numerical point score, 60 for color and 40 for absence of defects. (The color score for catsup is only 25% and for juice, 30% of the total score.) The appropriate section of the specification is quoted below:

“I. COLOR-The score for the factor of color is determined by comparing the color of the product with that produced by spinning a combination of the following Munsell color discs:

Disc l-Red (5R 2.6/13)-(Glossy finish) Disc 2-Yellow (2.5YR 5/12)-(Glossy finish) Disc 3-Black (N1)-(Glossy finish) Disc 4-Grey (N4)-(Mat finish)

(A) Canned tomato puree (tomato pulp) that possesses a good red, ripe tomato color may be given a score of 51 to 60 points. “Good red, ripe tomato color ” means the typical color of well-ripened tomatoes. This color contains as much or more red than that produced by spinning the specified Munsell color discs in the following combinations: 65 percent of the area Disc 1; 21 percent of the area Disc 2; 14 percent of the area either Disc 3 or Disc 4, or any combination of the two.

(C) If the canned tomato puree (tomato pulp) possesses a fairly good red tomato color, with red predominating, a score of 42 to 50 points may be given. Canned tomato puree (tomato pulp) that falls into this classification shall not be graded above U. S. GRADE C or U. S. STANDARD, regardless of the total score for the product. “Fairly good red tomato color” means the typical color of tomatoes which may not be well-ripened. This color contains as much or more red than that produced by spinning the specified Munsell color discs in the following combinations: 53 percent of the area Disc 1 ; 28 percent of the area Disc 2; 19 percent of the area either Disc 3 or Disc 4, or any combination of the two.

“ (D) If the color is definitely off-color for any reason or the product fails to meet the requirements of paragraph (C) above, a score of 0 to 41 points may be


given. Canned tomato puree (tomato pulp) that falls into this classification shall not be graded above U. S. GRADE D or SUBSTANDARD, regardless of the total score for the product.”

We must now consider details of the Munsell system. Two points require consideration-the nature of Munsell color space and the determination of a color match. Munsell notation is in terms of hue, chroma, and value. Hue and chroma are essentially measures of C.I.E. chromaticity-dominant wave length and purity, respectively-and value corresponds with the photometric brightness. However the analogy must not be pushed too far. A constant hue a t different values has different dominant wave lengths. This is shown in plots of constant hue loci on the C.I.E. chromaticity diagram in the final report of the Optical Society of America, Subcommittee on the Spacing of Munsell Colors (1943). This plot, shown in Fig. 4, is of interest also in illustrating the extent to which Munsell color is reproducible, Thus, the point (z = 0.24, y = 0.43) is the limit of the locus for constant hue 5G at value 9, and this is the limit of attainable chroma for 5G a t this value. It should be clear that we cannot have high chromas (or purities) at high brightnesses for surface colors. Only with illuminants is this theoretically possible, and even here the color perceptibility will be a factor a t high brightness levels. Thus Judd (1952) describes the dilemma of the couple who would make their white oleomargarine yellow by viewing it under a sodium vapor lamp. With a white table cloth, the unpigmented margarine still appears white.

There are two common methods of matching colors by the Munsell procedure, by the use of specially prepared chips of known hue, chroma, and value, and by spinning discs made by allocating wedge-shaped percentages of the disc area to specified papers supplied by the Munsell Color Company. This is an important asset to the Munsell system. Not only can the papers be evaluated in terms of C.I.E. quantities, but where color matches have been made, the color can then be reproduced and seen by any observer without reference to the original sample, the color of which was under examination.

There are, necessarily, limitations to the above. Normally, the specular component of the reflected light is eliminated, and since the color matches are metameric, viewing conditions must be specified. Also, the greatest usefulness lies in the measurement of surface colors. The object should be opaque and nonfluorescent. The nature of the surface of tomato puree is far from ideal. Although many difficulties arise in borderline cases, and the result is dependent on the skill and color vision of the observer, the method has served a useful purpose. If however we examine the word- ing of the PMA specification, a sample “shall contain as much or more red than that produced by spinning the specified Munsell discs . . . ,” it


seems reasonable to interpret the phrase “as much or more red” in line with the early work of MacGillivray (1937), who stated that the dominant wave length was a measure of desirable redness, and that the brightness /x, l l I - / /

I / \ ‘. ,’ , I \

FIG. 4. Plots of some Munsell Hues on the C.I.E. chromaticity diagram at two values.

Plots of the loci of ten hues, 5G, 5BG, etc. to 5YG, on the C.I.E. chromaticity diagram are shown as broken lines for value 1, superimposed on plots of the loci of the same hues, solid lines, for value 9. The limits of plots for value 9 are given by the heavy solid line.

Plots of constant chroma have been omitted. They would appear as ovoids around the central gray. Detailed plots for 40 hues were prepared by the sub-committee of the Optical Society of America on the spacing of Munsell colors, J. Opt. SOC. America 83,385 (1943), and by interpolation, data in the two systems are completely in terconvertible.

The simplified diagram presented here shows clearly the distinction between hue and dominant wave length.

and purity were of relatively less significance. We shall revert to this later, but may note again an attempt to reduce the number of variables.

The volume of tomato products is so great that, a concerted attack has been made on tomato color measurement, in part to establish more precisely the determination of the color grade of a sample, and in part, by

324 G . MACKINNEY AND C. 0. CHICHESTER

determining the color of a raw tomato, to predict the color grade of the product. The bulk of the work to be reported makes use of the Hunter Color-Difference Meter, and we shall have occasion to discuss the relation of the aL, bLl and L scales* to the C.I.E. quantities and also in terms of the chromaticity co-ordinates a, 0; the uniform chromaticity scale, U.C.S. ; and AE, the color difference in N.B.S. units. Since aL and bL are determined in relation to a standard red reference tile, they represent differences, al - a2 and bl - b2, respectively.

Younkin (1950a, b) has plotted Munsell renotations for value 3/ in terms of Hunter’s aL and bLl including the portion from Chroma /4 to chroma /8 and from hue 2.5R to 2.5YR, where colors of tomato purees lie. “Colors that plotted near the 2.5YR hue line were undesirable, while colors that plotted near the 7.5R hue line were highly desirable. Thus the hue of a puree was evaluated with respect to its proximity to one of the constant hue lines. If hue differences were equivalent to 0.3 of a unit on the aL scale, observers noted differences in color.” Chromas of / 6 were weaker and less desirable than those of /8, but differences had to be greater than 0.5 to be readily perceptible. Younkin further noted that as L diminished, colors became darker and more attractive, provided L was greater than 23, but that below 23, the puree colors became objectionably dark. An L of 23 represents a lightness of Y tristimulus value equivalent to 5.29%. Younkin (1950b) then evaluated tomato puree colors from fruits selected to represent the upper and lower limits of U.S. No. 1 and No. 2 in terms of aL and bLl from which it appeared that the fruit was graded almost exclusively on hue, with the line represented by 0.5YR separating the two grades. A second test was made with other inspectors and the hue was again shown to be critical. If in the narrow range represented, we assume the 0.5YR hue can be plotted as a straight line in terms of aL and bL then we may obtain for the line of constant hue, 0.5YR1 that aL N 2.5bL - 8.4, at this Munsell value. If aL exceeds this, the grade is fancy. Important contributions have also been made by Robinson et al. (1951) and Robinson et al. (1952). In a comparative study of methods for measuring color of tomato juice, Robinson et al. (1952) point out that two juices of the same lycopene content but of different insoluble solids content present quite different appearances, and consequently a method is to be preferred that does not depend on a quantitative determination of pigment. Because computations based on reflectance data by spectrophotometry are tedious, tristimulus filters have been developed by Hunter (1942). The characteristics of three, amber, green, and blue, respectively, have been adjusted so that from three readings, A , G, and B, the tristimulus values X , Y, and 2 may be readily computed. Like aL/bLl the 8 See Section V, “Instrumentation,” and Section 111.5, “Alternative Spaces.”


ratio ( A - G ) / ( G - B) is directly related to the dominant wave length. Robinson et al. (1952) compared the Maxwell spinning disc, the Beckman DU spectrophotometer, the Photovolt Reflection Meter, and the Hunter Color-Diff erence Meter. The various methods were compared and evaluated on the basis of correlation with PMA grades. The values obtained for the ratio aL/bL in the tomato samples were independent of the brightness (or Munsell value), since the ratio is linearly related to the dominant wave length. The disadvantages of the spinning discs are set forth in some detail.

I n an earlier paper, Robinson et al. (1951) made a detailed study of tomato grades which were correlated with the Hunter aL/bL ratio. They remarked that the correlation between this ratio and the PMA color score fell when the tomato juice samples had widely differing chromaticities. Their general consideration is summed up as follows: “Colors of the same dominant wave length are interpreted as slightly different hues when chroma and value differ. In the tomato color region, according to the Munsell system, higher chroma is interpreted as yellower hue, while higher value is interpreted as a redder hue.” The dilemma is then pointed out that the Munsell system most nearly corresponds to the interpretation of human observers, yet individual observers differ in their interpretations. When samples are similar in value and chroma, then the C.I.E. dominant wave length or some similar measure, such as aL/bL , is not only satisfactory but much easier to use.

Friedman el al. (1952) expressed some concern as to these conclusions. The pressure is great on all workers to find an acceptable industrial solution. We have on the one hand the data of Younkin (1950b) clearly showing that as we approach the 7.5R hue, we have desirable redness, and apparently unequivocally, that the 0.5YR hue delimits standard from fancy grades. If with Robinson et al. (1952) we accept uL/bL as a measure of redness, and recognize further that this is a measure of dominant wave length, this latter quantity is independent of brightness and purity. Now we are entitled to compare New York and New Jersey samples, solely on the basis of aL/bL ratios. Friedman et al. (1952) selected seven such New York samples with the highest aL/bL ratios, 1.59 to 1.62. They then selected three standard and three fancy New Jersey samples, for which aL/bL ranged from 1.29 to 2.32. To present a common basis for comparison, the Y, z, y C.I.E. quantities were calculated so that they in turn could be referred back to PMA grades determined by spinning discs with the appropriate Munsell papers. It makes no difference for this comparison that each batch of Munsell papers must be specially calibrated. An ideal disc 5 R 2.6/13 has precise and ascertainable tristimulus values, as is the case for the other Munsell discs specified by PMA. We are con-

326 G. MACKINNEY AND C. 0. CHICRESTER

cerned solely with the question: Can we grade these samples, regardless of variety, differences in processing treatment, storage conditions, etc., in an objective manner with respect to their degree of desirable redness?

In the simplest terms, an aL/bL ratio of 1.6 for a sample graded fancy in New York, would not necessarily yield a fancy grade in New Jersey, according to the data presented by Younkin (1950a, b, c), though it might if L is 25 or below. Robinson et al. (1952) present convincing evidence that inspectors must have their own prediction equations for satisfactory grading. If, as seems to be established by their work, there is (or may be) a sufficiently large effect of brightness on hue, and if also samples are going to differ substantially in purity (or chroma), then the aL/bL ratio must be used with reserve as a measure of desirable redness in tomato products. Consequently the correlation between PMA grades and the a and b values obtained for a series of samples by Kramer (1950, 1951) necessitates uniform chroma and value. This is perfectly possible but by no means inevitable. The L values for the seven New York samples with a t / b L ratios of 1.59 to 1.62 vary within the narrow range 28.0 to 28.8, corresponding to brightness variations from 7.84 to 8.29%. The New Jersey samples show much greater variation. A nationwide a L / b h standard would be most unfortunate a t this juncture without further definition.

Buck and Sparks (1952) have used the Hunter instrument to correlate the color of heated extracts of whole tomatoes with the color of the finished catsup. We shall have occasion to consider these contributions in Section V, “Instrumentation.”

6. Peas, Spinach, and Similar Chlorophyll-Containing Vegetables

There has been relatively little work evaluating the greenness of vegetables such as peas or spinach, though there has been considerable effort expended to measure chemical changes related to color changes, e.g., the conversion of chlorophyll to pheophytin (Dutton, et al., 1943; Mackinney and Weast, 1940) and also the disappearance of chlorophyll with ma- turity, as, for example, in lemon peel (Eastmond, 1950). Eastmond et ul. (1951) give a series of reflectance curves for fresh, stored, frozen, and dehydrofrozen peas (whole, cooked). In addition they consider the effect of two storage temperatures (- 10’ and + 10” F.) and storage times up to one year. In the former series differences were observed in luminous reflectance and small changes in dominant wave length, ranging from 16.7 to 21 % in Y and from 566.0 to 569.1 mp in A. These changes resulted in a yellowing of the product. In the second series, a graying was observed. A measure of greenness was obtained from the expression ( G / A ) + B where G, A , and B are the green, amber, and blue filter readings. A similar index can be obtained from selected reflectances. Eastmond et al. (1951)


chose a greenness index expressed as R 6 4 0 / R 4 9 0 + RbgO. It will be noted that in most of their curves, the reflectance at 490 mp is fairly constant, and even more so a t 470 mp. R4Q0 is therefore relatively fixed, and the ratio R 6 4 0 / R 4 9 0 depends on the reflectance at 540 mp. The higher the reflectance at 580 mp, the greater the increase in yellowness and consequently the greater the loss in greenness. Like the Gentry unit in relation to the Lovibond (see Section 11.3, “Oils”), the green index is inversely related to greenness.

In view of the limited data on these commodities we deemed it worth- while t o make a few color measurements on extreme cases. Blanched frozen peas and spinach were therefore thawed, portions blended, then centrifuged to remove air bubbles. Other portions were heated in the presence of dilute oxalic acid, and treated as before. Canned peas and

TABLE I Color Data on Peas and Spinach*

Frozen blanched Canned t Thawed, blended With oxalic, blended b h d e d

Peas $ Y , % 20.3 18.8 25.9 X 0.379 0.438 0.405 Y 0.498 0.454 0.445 A, m P 565.5 576.5 573.4

Y, % 5.26 2.81 5.69 X 0.344 0.413 0.413 Y 0.442 0.424 0.429 A, mr 563.5 577 576.2

* Mackinney and Chichester (unpublished data). t Canned eamples, from the local market, do not have comparable total pigment contents, so that no

1: Y is the C.I.E. tristimulus Y, z and II the trichromatic coefficients; method, 10 selected ordinates.

Spinach

significance can be attached to the changes in Y as between canned and fresh.

spinach were also blended and centrifuged. Samples were then placed in special leucite cells and measurements were made using the amber, green, and blue filters with the Photovolt Reflection Meter, and by the 10- selected ordinate method, with the Beckman Spectrophotometer. Results are shown in Table I. The frozen peas thawed and blended exhibit a dominant wave length almost exactly that reported by Eastmond et al. (1951). The canned peas show a shift of almost 8 mp, and the spinach of 12 mp. The difference in Y values between peas and spinach is due primarily to difference in chlorophyll content. The changes observed are thoroughly plausible, as the conversion of chlorophyll to pheophytin causes a marked diminution in the absorption ca 570 mp, and an increase ca 535 mp in solutions of the extracted pigment. It would be of interest to determine whether spinach canned after blanching at 160’ F. (the Thomas


patent) has in fact a significantly lower dominant wave length than that canned after steam-blanching. The Photovolt readings on the pea samples were in reasonable agreement with those obtained from reflectance measurements for the selected ordinate method. Those for the spinach were not, differences of 7-8 mp in dominant wave length being noted. The reason for this is that at the low brightness level, with a high pigment content, the very low blue readings on which tristimulus 2 depends could not be estimated within better than a 50% reading error.

6. Strawberry Preserves

Strawberry preserves and jams were included for two reasons. They contain anthocyanin pigment, the pelargonidin 3-glucoside (Sondheimer and Kertesz, 1947), but in relatively low concentrations, 3 to 10 mg. per 100 g. preserve, and secondly they show a marked tendency to brown a t unfavorable storage temperatures. Strawberry preserves are customarily made in the United States from frozen strawberries. These are drawn from freezing storage as needed, thus obviating unnecessary storage of the final product. Unlike the jam, where no attempt is made to secure whole fruit, the strawberry preserve contains a high proportion of whole fruit and pieces of fruit which have been only partially distintegrated during handling. The preserve therefore consists of opaque berries and portions of berries suspended in a jelly highly translucent to red light.

We have, in consequence, an awkward problem in color measurement, owing to inhomogeneity of the material. If we examine the jelly portion, freed from all turbid matter, there is virtually no light reflected. This may be illustrated very simply, by placing the jelly in a container the inner surfaces of which have been painted black. The jelly appears black. If however a white background is substituted the jelly will have its cus- tomary red color, the red light being reflected from the white surface and transmitted back through the jelly. By using a sample holder of sufficient depth, with a white background, the jelly will have a negligible 2 tristimulus value, and there is furthermore relatively little fluctuation in dominant wave length or purity. The situation is in some respects comparable with that found in Capsicum. However, whereas chlorophyll may modify the color of the spice, this is not true in any normal instance for the strawberry. The dominant wave length, for the jelly, is constant, ca 605 mp, within fairly narrow limits, and a surprising number of samples will have chromaticities represented by x, 0.65 - 0.66; y, 0.34 - 0.33. As Eastmond (1950) has shown with raspberries, if it were solely a matter of securing a measure of anthocyanin, an R S f O or Tala would serve the purpose, the maximum for the anthocyanin absorption appearing at or near


520 mp. We have, however, the browning to contend with at the same time. Measurements 011 a number of samples of industrial origin, both normal and dark, indicate that changes in appearance are governed almost exclusively by changes in the brightness.

The question arises as to why there should be so little change in dominant wave length during browning. The answer lies in the nature of the spectral curves. The brown pigments show a more general absorption, high in the blue, low in the red, than the natural anthocyanin which they replace. Until most of the anthocyanin has disappeared, however, this will not seriously affect the relative proportions of light reflected from different spectral regions. It will result only in a darker red of essentially the same hue. There is, on heating, as in the preparation of the preserve itself, a substantial loss in anthocyanin. When the packer speaks of de- veloping the color during the cooking process, he is redistributing the anthocyanin in the berry-syrup mixture. In spite of the ‘(deepening” of the color, there is in fact a net loss of pigment. This ‘(deepening” is physically not unlike the color change in a green leaf, held under water in an evacuated flask to eliminate air. Substantially less light is reflected from the surface, and the leaf, originally opaque, becomes partially translucent. The lightness, or Y tristimulus value, therefore, should be a useful measure of the changes in a strawberry preserve. Loss in anthocyanin without concomitant browning may result in a slight increase in lightness, though the paling is not likely to be detected visually. Browning would immediately be reflected in lower tristimulus green, or G readings, and in Y computed from reflectance data. As shown by Shah and Worth- ington (1953) for pur6ed frozen strawberries, either the Hunter L value or the Photovolt G reading provided a measure of color differences in their samples.

Unfortunately, for similar results with a strawberry preserve, a procedure must be agreed upon whereby the opaque berries are consistently and uniformly dispersed. Centrifuging will not eliminate air bubbles incorporated as a result of blending. It may prove feasible to force the preserve gently through a coarse mesh screen and secure consistent reproducible results. The values obtained by this procedure differ from those made on the jelly. The 2 value is no longer negligible, as there is substantial surface reflection. Increase in turbid matter has not, in our experience, changed the dominant wave length, but the purity has fallen appreciably from ca 95-98% t o SO-SO%, depending upon the sample. The browning, however, is immediately detected by a decrease in Y .

Possibly enough has been said to indicate that color measurement in a preserve, containing opaque and also highly translucent portions, depends upon carefully standardized procedures.


7. Wines

As with other commodities, suggestions have been made for color specifications in terms leading toward a single-value function. Thus Boutaric et al. (1937) suggest the optical density a t 520 mp (the peak for anthocyanin absorption) and the ratio of the densities a t 480 and 640 mp. There is no a priori reason why some such measure should not provide a uaeful scale for specifying the color of a given wine, though as Winkler and Amerine (1938) point out, its greatest utility would be for red wines possessing similar transmission curves.

With wines, however, it would be much more difficult to correlate the data with the C.I.E. system. Winkler and Amerine distinguish between brightness (lightness on a gray scale) and brilliance, which represents freedom from turbidity. Furthermore the gamut of wine colors from dark red Burgundies to rose wines and to tawny ports or white wines, is such that a photometric color index of the kind developed for oils would be most difficult to interpret. A series of such indices might be set up for each wine type, but this would not assist in identifying types, particularly where blends have been made. Winkler and Amerine therefore computed C.I.E. quantities from transmission data obtained spectrophotometrically. They used light paths from 0.25 cm. in the case of a dark red Petite Sirah, 0.5 to 1.0 cm. for California Ports, to 4.0 for Grenache (light pink), and 3.0 to 4.0 for various white wines.

Dominant wave lengths varied from the complementary of 504 mp (a purple) to 650 mp for the Petite Sirah, 590 to 595 m p for the ports, and 587 to 590 mp for the white wines.

We select in the following table examples of wines from the work of Winkler and Amerine (1938) and of Amerine and Winkler (1941) to indicate the range of variation in color. A cursory inspection of the table indicates some of the difficulties. The Grignolino is “typical” and “light orange pink,” the Port “too brown,” and “light amber red,” the white wines, as is well known, normally light amber. The coefficient z in the three cases is negligible, 0.027, 0.028, and 0.033, but if all were adjusted to standard depth, 1.0 cm., this would not be true. This is because at any given wave length and pigment concentration, the optical density (a logarithmic function of T , the transmittance) is determined by the depth, d, and

T Q: e-d,

the C.I.E. values are determined from T itself. We must therefore consider the wines in one sense to be multicolored or polychroic, insofar as the color perceived with the transmitted light changes with the depth of wine being viewed.

THE COLOR PROBLEM I N FOODS

TABLE 11. Colors of Wines*

Wave length, Pu- 5 2/ mp rity

Petite Sirah 0.649 0.316 655 73 Alicante Bouschet 0.635 0.309 504c 68 Muscat 0.615 0.344 616 71 Mission 0.603 0.380 599.5 86.2 Port 0.572 0.400 596 83 Grignolino 0.565 0.408 593 78 Mixed whites 0.550 0.417 590 72 Grenache 0.520 0.410 592 52 .4 * From Winkler and Amerine (1938) and Amerine and Winkler (1941). t Y ia the C.I.E. triatimulus Y, z and I/ the trichromatic coefficients.

Y t 9 . 6 2 . 4

15.4 24.6 30 .4 34.1 38.8 57.3

33 1

Depth, cm . 0.25 0 . 5 0 . 5 1 .o 1 .o 4 . 0 3 . 0 4 . 0

111. SOME THEORETICAL CONSIDERATIONS

1. Discrimination

In the foregoing sections, we have selected for discussion what we believe to be significant contributions to the color problem in foods. A certain line of development is followed-the selection of a unidimensional color scale or index is attempted, according to the color problem to be evaluated, which wherever possible is related to the C.I.E., possibly via the Lovibond or Munsell systems. This is in actuality an attempt to correlate visual estimation of a color with an instrumentally measured numerical score. Bouma (1947, ch. XII) discusses discrimination by the eye. If a color match has been made, the question is raised as to how far one can modify one of the colors before the eye can perceive the difference. The amount of change to render the difference perceptible is a “discrimination step,” “threshold,” or “limen.” The discrimination may be applied to the brightness, the wave length or hue, and to the purity or chroma. The various thresholds are determined individually, keeping the other two variables constant. If we can just distinguish the spectral color X + AX from the spectral color X, then we can plot AX as a function of X for the visible spectrum, but as Bouma points out, results are in- fluenced by brightness, size (i.e., areas) of the spots under comparison, environment, and other factors.

With respect to purity ( p ) discrimination, it appears that p can fall from p = 1 to p = 0.5 before AX as a function of X changes appreciably. As p approaches zero (white), the number of distinguishable colors becomes much less. In the immediate neighborhood of the white point, hue discrimination is small. This is true also a t low brightness levels, i.e., as we approach black (Y -+ 0).

For a color space to have maximum usefulness, all steps of just distinguishable differences, whether of brightness, hue, or purity, should be


represented by equal distances along the appropriate axis; i.e., each series of thresholds or limens should be equally spaced. This procedure involves the development of a uniform chromaticity scale. This requires construc- tion of the color space in a Euclidean geometry, possessing no ruffled planes as in the index of fading as defined by Nickerson (1936). A second method compensates for the known distortions of C.I.E. space by use of MacAdam ellipsoids.

2. The Uniform Chromaticity Scale (U.C.S.)

Judd (1952) expresses a “ . . . somewhat dismaying suspicion that a strictly uniform tridimensional color scale cannot possibly be developed.” Nevertheless, the success that the Bureau of Standards has achieved is convincing proof that an extremely useful approximation can be made, and for maximal usefulness we must understand some of the limitations involved. The range of brightness over which measurements can be made extend over nearly five orders of magnitude and Bouma (1947, p. 226) plots B/AB as a linear function of log B, where AB is the brightness limen. The ratio is called the sensitivity of the eye to differences of brightness. This sensitivity possesses the characteristics of a logarithmic function and is markedly lower in dark surroundings. The Munsell system has a 10-step series from white to black. In the simplest form, these steps V were based on the following relationship with the reflectance:

v = 1022%

Thus the reflectance for step 5 was 0.25; for step 7, 0.49, etc., step 10 (white) having a value of 1.0.

Judd traces the development of modifications needed to take into account the reflectance of the background as well as of the gray chips representing the various steps. As shown by Bouma, it is only for a light background that B/AB is a linear function of log B. Consequently Munsell value must be determined against such a background. In sum- mary, he accepts the equation given above as a convenient first approximation, and states that i t can be applied to lightness differences perceived among chromatic colors as well as to those among grays.

Judd then considers chromaticness and shows how Munsell hue and chroma scales can be developed, and explains the irregularity of the Munsell Color Solid. The chroma loci are determined with color chips on a middle gray-to-white background and this prevents detection of chroma and hue differences a t low values. The limits in “ideal Munsell space” were plotted by Nickerson and Newhall (1943).

Judd developed a U.C.S. triangle based on a projective transformation of the C.I.E. co-ordinates (z,y) to new co-ordinates (r,g), such that


approximately equal distances were obtained for perceptually equal differences. Results were plotted on a triangular grid in terms of R, B, and G. Of the various other transformations, mention should be made of Hunter’s (a#) co-ordinates (1942). Thkse are defined by the equations:

a = 1.0000~ + 2.2633~ + 1.1054’ 2.42662 - 1.3631~ - p.3214.

0.5710~ + 1.2447y - 0.5708 1.0000~ + 2.2633~ + 1.1054’ a =

They may be approximated from readings made with Hunter’s amber, green, and blue tristimulus filters, in much simpler form:

N ( A - G ) / ( A + 2G + B ) ; p N_ 0.4(G - B ) = ( A + 2G + B ) .

The origin (a = 0, p = 0) represents illuminant C of the C.I.E.

3. The N.B.S. unit

To determine color tolerances, we need ideally an assessment of color differences on a tridimensional color scale. Judd discusses the various attempts to measure the color differences. These include Nickerson’s index of fading I , based on Munsell spacing, the changes in hue, chroma, and value ( A H , AC, AV) being appropriately weighted for perceptibility differences, and his own contribution, AE, the N.B.S. unit. This has been redefined in terms of Hunter’s (a,@ chromatic space. The simplest expression of this quantity is given by Scofield (1943) :

AE = [(L, - L2)2 + (al - a2)2 + (bl - b2)2]f4

where L is a function of the square root of Y , and a and b are proportional to a and ,8, respectively.

In 1945 Bouma summarized limitations of the various U.C.S. systems as’follows: that in the neighborhood of the white point, and also for unsaturated colors, they give a fairly correct measure of the number of steps of just noticeable color differences; that for the spectral locus and for very saturated colors, agreement is much worse; finally, so far as thresholds for colorimetric purity are concerned, the U.C.S. system is useless (Bouma, 1947 p. 241). So far as we know, these views have not been contradicted. This is not to say, as Bouma points out, that the U.C.S. system is not serviceable, and furthermore it is wholly proper that emphasis should be given to the usefulness of the quantity A E to set color tolerances in various industries.


4. MacAdam Ellipsoids

Hitherto we have discussed measurement of the distance separating two colors plotted in a visually uniform color space. Instead of transforming the C.I.E. space into a uniform color space, its known distortions can be compensated by MacAdam ellipsoids (MacAdam, 1942). Davidson (1951)

Fro. 5. MacAdam ellipsoids. Any point in the color plane may be surrounded by an ellipse, and in the color solid by an ellipsoidal volume, the boundary of which represents a finite number of perceptual color differences. For any fixed number of differences, the size of the ellipsoid depends upon its position in the color space. By courtesy Dr. D. L. MacAdam by permission of the Optical Society.

calculates the color differences by a simple graphical method, assuming that any point on the surface of the ellipsoidal volume represents aunit color difference from a focal point of the ellipsoid. As he points out, MacAdam ellipsoids are theref ore a means of specifying color tolerances. In Fig. 5 are shown a series of ellipses within the chromaticity diagram which illustrate the nonuniformity of C.I.E. color space. The distances from any marked point to points on the boundary of the ellipse enclosing it all represent equal chromaticity differences. Since we must take into


account the lightness, we have an ellipsoidal volume. “We may plot two colors, A and B , of nearly equal chromaticities A, and B, on the conven- tional 2, y chromaticity diagram, but an ellipsoid surrounding either point A , or B, will be of little value in determining the number of just perceptible differences between them, unless plots of the two colors on an 2, Y diagram also fall near each other.” Davidson’s solution is graphical:-

A and B represent the loci of two colors differing slightly in z, y and Y . We plot their chromaticities A,, B,. We then erect plane Y perpendicular to the x, y plane and plot A and B such that A A , and BB, are proportional t o YA and YB respectively. We may next visualize A as a point in color space which we shall enclose by a surface not unlike an egg shell. The volume contained within this shell is ellipsoidal, and every point on the shell surface represents an equal perceptual difference from I)oint A . We join A B which must pass through the shell at some point P . Thus A P represents a vector along the line joining the two colors. It constitutes a stated unit perceptual difference along A B . The quantity ,4 B / A P then gives us the number of such differences.

6. Alternative Spaces

Whereas Hunter derived his alpha, beta chromaticity directly from C.I.E. quantities, Adams (1942, 1943) developed a chromatic value space and subsequently derived from it a chromatic valence space. He first modified the tristimulus values so that for illuminant C

x, = Y c ( = Y ) = 2,

where the subscript c indicates the values have been corrected for the illuminant, the corrections being X , = X/0.9804,2, = 2/1.180. He then applied the Munsell value function to Y,, deriving V,, calculated from reflectance ratio, using the Y primary and a magnesium oxide standard white, from the expression

R,/R,M,o = 1.2219Vg - 0.2311Vv2 + O.2345Vv3 - 0.021009V~4 + 0.0008404V,6.

The other two quantities required to define the valence space are W, and 0.4W2, where

W , = V,(X, - Y ) and W, = V,(Z, - Y ) .

In the chromatic value space, Adams (1942) applied the Munsell value functions by the substitution of X , and 2, in the original value function. We see that substitution of X , and 2, in the same formula yields two new quantities, Vz and V, which with V, uniquely define any color. This then will give slightly better spacing, since we apply the value function to each

336 G. MACKINNEY A N D C. 0. CHICHESTER

tristimulus quantity separately. This is a difficult problem in which to have a direct reading instrument. The differences (V, - V,) and (V, - V,) determine the chromatic value. They will be zero for a neutral gray. If the Munsell hues for a given value are plotted in the Adams value space, lines of constant chroma describe a concentric series of ovoids about the neutral gray. An instrument could not be developed to measure all the quantities in the Adams value space, but the quantities of a modified valence could be incorporated in a direct reading instrument, the Hunter Color-Difference Meter (Hunter, 1948a, b, Gardner Laboratory, 1950).

Using the tristimulus filter Y G and X E (0.80A + 0.20B) we may (0.80' + 0.2'' - G), o r ~ , ( 1 . 0 2 ~ - y) .

0.9804 substitute and obtain W , = V,

To approximate V , without recourse to involved circuits, Hunter h w

which has proved evolved the function V, g f, = 0.51

quite satisfactory. Multiplying the whole expression by a constant, we arrive at Hunter a, = Kl(fg)(1.02X - Y ) , and

(21 4- 2oy) 1 + 2 0 Y '

br = -[0.4Klf,(Oa847Z - Y ) ] .

These give quite a good visual spacing and together with V , = K2Y(f,) give a good measure of visual differences, AE.

AE = [(AK2Y(fU)2 + ( A U , ) ~ = (Ab,)']%.

Hunter, however, has not been able to incorporate Y(f,,), i.e.,

= L,

so it is necessary to compute L from R or to accept as a compromise L = K ( Y ) n . This conversion to L scales unfortunately means that the rest of the scales are also changed by the same factor, which slightly decreases their usefulness in estimating color differences. The instrument can be used with both scales so it merely involves a switching operation (Gardner Laboratory, 1950).

Saunderson and Milner (1946) developed a zeta space, which like an omega space of Moon and Spencer (1943) is based upon the Munsell renotation. The omega space is not as useful a representation and therefore will not be discussed. The zeta space is a modification of the Adams chromatic diagram. Chroma is represented by the expression

Chroma = Ic[(V, - V,)' + 0.16(V. - V , ) 2 ] s

in which Ic represents the proportionality factor between radial distance on Adams chromatic value co-ordinates (ie., V, - V , and V, - V,) and

THE COLOR PROBLEM I N FOODS 337

the chroma itself. The k is remarkably constant for different Munsell values and consequently the zeta space transformation is not a function of Munsell value. This follows from the fact that the radius for constant chroma is the same for all values. The zeta space is therefore defined by (ll, {z, lb), where l.2 is proportional to Munsell value and lI and la define the color plane.

IV. GENERAL CONSIDERATIONS

In considering the developments within the food industry, a pattern may be discerned. Frequently, ad hoc material standards may be set up, to be replaced by more precise measurements based on one or more attributes of the C.I.E. color system. A trend toward simplification then commences, in order to specify the color for grading purposes. The method has been described as abridged spectophotometry. As Hardy and Young (1949) point out, the abridged method may serve a dual purpose, in production control and where necessary, as an estimate of tristimulus values. Before this method can be successfully applied, three sets of data are required:

1. The nature of the pigments involved, and reflection or transmission measurements, determined spectrophotometrically.

2. The basis for a visual color preference, e.g., desired redness in tomatoes, or whiteness in sugar.

3. Some objective measure which locates the color preferences in color space. This is best determined by reference to the C.I.E. or related systems.

Given the foregoing, it becomes possible to determine whether a more restricted set of data can replace the cumbersome C.I.E. evaluation and simplify interpretation of the color preference. Where this is practicable, an instrument can be designed for a given commodity which will assign a grade on the basis of the color tolerances permitted in the grade specification. Where this procedure has not been followed, difficulties have been encountered.

These difficulties usually involve the assignment of different values for the color difference between two samples when judged visually and by the instrument in question. This is best illustrated in the near-white region, where even the basic C.I.E. system gives incorrect values owing to incomplete evaluation of the 1931 standard observer. This was first noted by Jacobsen (1948), though Wald (1945) had already indicated that the eye was more sensitive to the blue than is shown by the standard observer. These findings were corroborated by Judd (1949), who modified the characteristics of the standard observer to account for differences observed visually in titanium paints but not indicated by reference to the C.I.E.

338 C. MACKINNEY AND C. 0. CHICHESTER

The pattern we have been describing, beginning with simple material standards, is capable of an additional step, the development of new material standards duplicating with high fidelity the reflectance curve of the commodity. We are in no position to offer a critical appraisal of the possibilities here. We may remark however that the printed color varies slightly between batches, even with the care exercised by the Munsell Color Company. Similar difficulties may be encountered with ceramic tiles. We have been interested therefore to learn of the development of plastic standards which rather remarkably duplicate the reflectance curves of tomatoes, obtained in the General Electric Recording Spectro- photometer. These and similar discs for peaches have been developed by Monsanto for use with the Agtron instrument of Ma,gnuson Engineers (Smith and Huggins, 1952).

Matches are thus nonmetameric and are independent of the observer and the illuminant, since comparisons are confined to the brightness.

Two additional procedures may be mentioned here, to be described possibly as abridged photometry or abridged colorimetry. Eolkin (1952) evaluated the “relative color” of purees by black and white photography. This would obviously be of greatest use, when ordinary film is employed, in light-colored products subject to browning. Eolkin used the procedure to measure discoloration in apple sauces. Livingston and Vilece (1953) substituted a photoelectric method for a similar type of problem.

V. INSTRUMENTATION With respect to the majority of procedures discussed for the different

commodities, and the instruments used, it is necessary to accumulate data from widely different sources to evaluate the natural variability of the commodity, the usefulness of the procedure selected as a criterion for delimiting a color grade, and finally the instrumental reliability under operating conditions, whether it be in the laboratory or in the inspection service in the field.

Work of this type has been initiated by Worthington, Cain, and Wiegand (1949) on a variety of juices, by Shah and Worthington (1953) on strawberries, and by Sastry and Tischer (1952) on the anthocyanins of grapes. Kramer and El-Kattan (1953) have worked out detailed correla- tions between visual score and Hunter quantities for tomatoes.

1 . Additive Colorimeters

Some of the oldest color-determining instruments are the additive visual colorimeters. They establish the basis for all color measurements which fundamentally assign a unique numerical value to a particular color. When the spinning disc technique is applied to the Munsell color


collection, it is in principle an additive colorimeter. In order to obtain values for an unknown color, it is necessary to use a minimum of four segments to secure the necessary three degrees of freedom for a successful match. Munsell color can be converted to C.I.E. quantities so that data can be transformed into other standard systems of color specifications. The Munsell system despite its simplicity and low cost appears less in favor than it was at one time, although many specifications are still based upon it. Aside from the labor involved in the measurement and the fact that a personal judgment is involved, the method has many advantages. It is the only standard system which will allow a specified color to be inspected by the eye. Thus one can reproduce the color from a numerical specification as a color plaque which can be held in hand. Deviations from these standards may be interpolated with surprising accuracy. The placement of the color chips a t constant hue is uniform with respect to value and chroma. Munsell colorimetry has some disadvantages. If chips are not chosen which closely match the color being evaluated, the match is likely to be metameric, in which case the value assigned is not unambiguous. The lighting conditions for making the comparison and the surroundings must be standardized, if the maximum accuracy is to be obtained. The colors to be specified must be of moderate saturation, since the discs are limited in saturation, owing to the inherent nature of the dyes and the lack of a wide enough range of dyes. The chips represent only a narrow range of surfaces, making comparison difficult with unusual surfaces or other modes of appearance.

The additive colorimeter in which a sample is matched by the addition or negative addition of three or more primary lights has fallen into disuse. The number of colors which can be matched with practical primaries (practical in the sense that they must be a compromise between saturation and the loss of the major part of the incident light flux owing to high selectivity) is limited. With moderately saturated primaries the match becomes metameric, and the match thus made will not stand up under other illurninants. These instruments are usually constructed with a single eyepiece so that the field is restricted to two degrees or less. This in turn reduces drastically the accuracy in matching. Some matches will neces- sitate the use of negative amounts of one of the primaries further com- plicating the transformation of the data to other specifications. By adding more primaries some of these disadvantages may be overcome. Donaldson (1947) has developed a six-color additive colorimeter in which an initial approximate match is made with three primaries and the final match is secured with three more. The instrument is calibrated in terms of C.I.E. quantities, and since the spectral distribution of the final light flux is dependent on six filters the matches are essentially nonmetameric, and


the color gamut covered is quite large, owing to the placement of the six primaries.

2. Subtractive Colorimeters

The visual subtractive colorimeter avoids some of the troubles of the three-primary additive colorimeters. By using primary filters between the standard field and the eye, or between a light source and the field, the emergent beam can be varied with respect to both hue and saturation, thus assuring a more nearly physical or nonmetameric match. I n the case of additive mixtures the intensity of impinging flux is varied, which in turn varies only the intensity of the field, leaving hue and saturation substantially unchanged. By the use of two primaries and a method of controlling the illumination, a subtractive instrument becomes easier to use and interpret. The ability to transform any readings obtained on a subtractive colorimeter into other specifications is dependent upon the calibration of the filters in some other system. The permanence of the filters is vital to success; gelatin filters in particular may not retain their initial calibration.

The Lovibond Tintometer is probably the most widely used subtractive colorimeter today. The filters are not continuously variable as in some of the wedge instruments but are interchanged to vary the color in discrete steps. The individual filters bear standard specifications allowing readings obtained to be convertible-at the expense of some labor. The Schofield-Lovibond modification (Schofield, 1939), using a controllable light source and two filters at a time, makes the conversion extremely simple. Since the wedges are made of glass, they are in general permanent. The instrument, however, suffers the usual disadvantages of a monocular system in that the field is of necessity restricted to a small angle. In addition, the yellow and blue transmit in the far red and this in turn restricts the producible colors to the lower part of the chromaticity diagram. The instrument has found wide usage in the specification of oils, which generally have dominant wave lengths in the red, orange, and yellow portions of the chromaticity diagram.

The subtractive colorimeter and the additive colorimeters possess one characteristic which none of the available photoelectric instruments possess, that is, the ability to give a reproducible specification to a fluorescent material.

3. Comparators

There are also instruments used to compare a standard color with the color of an unknown, i .e., the comparators. These are of little use in the specification of color as such, since they are restricted essentially to the matching of a particular color to that of a standard by adjustment in the


amount of luminous flux transmitted by, or reflected from, the specimen to be standardized. They may also be used to place a sample within a color grade. When used in this manner, the answer obtained is unequivo- cal as to whether the specimen falls within a given tolerance. The dis- advantage is that this answer does not give any information as to what causes the mismatch.

4 . Spectrophotometers The basis of much instrumentation and methodology lies in the

requirement of the American Standards Association that “the spectrophotometer shall be recognized as the basic instrument in the funda- mental standardization of color.” The Bureau of Standards concurs in this statement. Basically a spectrophotometric curve, that is, a plot of intensity versus wave length, is certainly the most unambiguous specification of color that can be obtained. In one sense this is not color, and data are open to many interpretations. For instance, we can have two dis- similar curves which will give the same apparent color sensation under certain conditions, thus our metameric match. Extremely small variations in spectrophotometric curves may lead to large variations in individual appearance. In order to interpret such curves, careful study is required. If specifications are to be based on the curves by reference to some standard color system, the conversion must be performed with extreme care to prevent errors of considerable magnitude. With reference to the C.I.E. system the eye has the ability to detect a difference in color samples in some parts of the chromaticity diagram differing by only 0.001 in 2 or y. This may in many cases be smaller than the uncertainty of the measurement. A study by Nickerson (1935) of various specimens, using the weighted ordinate method for intervals of 10 mp, gave x and y with an average uncertainty of 0.004 while the 10 selected ordinate method gave an average uncertainty in the same samples of 0.0035, which is more than three times the minimum detectable difference.

The determination of reflectance curves on a large number of samples, particularly from nonrecording spectrophotometers, is extremely labori- ous with instruments such as the Beckman, where the specimen holder has room for only the standard and a single specimen. The subsequent reduction of the data can be simplified somewhat by the use of automatic integrating devices on the recording machines and the use of punch card calculators (Peterson et al., 1944; MacAdam, 1950; Davidson and Imm, 1949; Kaye and Devaney, 1952). Most spectrophotometers are designed to avoid the inclusion of the specular component in reflection measurements. In some cases it would be highly desirable to include this but unfortunately only one of the present spectrophotometers, that is the General Electric, has any provision for doing this.

342 a. MACKINNEY AND C. 0. CHICHESTER

There is an unfortunate tendency to regard a spectrophotometric reading as definitive, and this unavoidably is perpetuated by making the spectrophotometer the ultimate reference instrument in color work. Ayres (1949) evaluated the operational accuracy in photometric analysis and instrumental performance under differing conditions. Color measurements are hampered in that the sample itself may not be altered. This differs from “ chemical photometry,” where concentrations can be altered to give maximum reading accuracy. One is limited therefore in the color work to changes in the reference standard, which may add appreciably to the labor. Ewing and Parson (1948) show that any absolute assay undertaken with a number of Beckman spectrophotometers is subject to uncertainty greater than that indicated by the limits of precision of each individual instrument. We have no reason to doubt that this applies to all spectrophotometers. Caster (1951) studied variability on a single instrument and found that although duplicates checked within 0.1 to 0.5%, consistent errors of 3 to 5% were observable, depending upon the phototube, slit width, lamp intensity, aging, and similar factors.

Cannon and Butterworth (1953) demonstrated that a linear plot of Beer’s law is no proof of linearity of spectrophotometer response, and erroneous absorbancy values may be obtained. They suggest an instrumental check by use of independently calibrated neutral filters. Their findings apply particularly to the barrier-layer photocells, used in such instruments as the Unicam, the smaller Coleman, the Evelyn, Hunter, Klett-Summerson, and Photovolt, and are less applicable to the gas- filled photocells used in the General Electric Recording and Beckman instruments. Errors in standards for spectrophotometry as well as errors concerned with the General Electric instrument are discussed by Gibson (1949).

Goldring et al. (1953) have examined anomalies in spectrophotometric measurements. These have been classified on the basis of chemical factors, instrument factors, operational techniques, and mathematical considerations. Of particular concern are errors of which the operator may remain unaware. The case of mechanically insecure elements in the input elec- trometer tube is cited. As the photocell compartment shutter is opened or closed, there can be a substantial shift in the zero of the photometer system. This is unsuspected when the change in zero is reproducible, the new position being metastable.

Spectrophotometers do not suffer from the limitations of visual colorimeters in that the data obtained may be considered objective, but the time involved in interpretation of the data and the skill needed for


this interpretation prevent their use in routine day-to-day checks on products except under unusual circumstances.

The uses and limitations of spectrophotometers, such as the General Electric Recording and the Beckman DU Spectrophotometers, are discussed in detail by Gibson (1949) and by Judd (1952).

5. Tristimulus Filter Colorimeters

The tristimulus filter colorimeter was apparently developed in order to retain some of the advantages of the spectrophotometer and a t the same time to decrease the labor needed to calculate the numerical specifications of color. They are generally more portable than the spectrophotometers, cost less, and require much less interpretation of the results. All of the data of the tristimulus colorimeters can be interconverted to any of the standard systems of color measurement. Their accuracy depends upon the fit between the theoretical response of the C.I.E. primaries and the response achieved by the combination of light source, filter, and photocell. The fit is in no case perfect, and is usually worst in the small lobe of the X primary.

Some of the instruments originally developed for use with a set of tristimulus filters attempted to use a white reference point as their standard. This usage means that there is a large color difference between most of the samples measured and the reference point, and it can be shown that the larger the difference between the standard and the observed color, the larger the uncertainty in the measurement. With the Hunter filters and a magnesium oxide white plaque the discrepancy between the spectrophotometrically determined x or y and the colori- metrically determined x or y is frequently larger than 0.02, that is, more than ten times a reasonable chromaticity tolerance for most colorimeter work. Since these discrepancies are proportional to t,he difference between the standard and the measured color, this difficulty can be obviated by the use of specimens of similar spectral composition. Another difficulty inherent in the measurement by the use of tristimulus filters is that the more metameric the match between specimens, the larger the discrepancy in the measurement.

The Hunter tristimulus colorimeter represents a departure from the usual colorimeters, as it presents its data in a form closely akin in spacing to the Munsell system. By resistance networks between a series of barrier- layer photocells which view the reflected light from a specimen through tristimulus filters and a compensating cell which views the light source, a reading is obtained which is related to perceptible differences.

The degree of fit between Munsell spacing and that of Hunter’s ar, br


is discussed by Nickerson (1950). She compared the color space of Hunter and Adams’s chromatic value space, in terms of Munsell renotation. For constant Munsell value, the constant chroma lines should fall on concentric circles around a neutral gray, if uniform perceptibility spacing is to be achieved. It was found that the Adams value space gave better over-all results in terms of uniform chromaticity. The Hunter ovoid is flattened on the side of the yellow hues, and expanded in the blues and purples, while the Adams ovoid is flat on the blue side.

The use of barrier-layer photocells in some of these instruments intro- duces other difficulties. As the radiant energy impinging upon the photocell decreases, the current likewise decreases to such an extent that i t is impossible to obtain accurate readings at low intensities. In most instruments this occurs at approximately 2 % reflection.

In order to achieve, higher sensitivity a t low intensities, recourse is made to the high-impedance outputs afforded by vacuum photocells, which allow their output to be more easily measured by vacuum tubes. The Differential Colorimeter of Glasser and Troy (1952) is such an instrument. In order to achieve direct reading, stability with respect to slight changes in light intensity during measurement, and balance of dark currents, two vacuum photocells are used in a balanced bridge. Their unbalance is measured with a vacuum voltmeter, in a cathode-follower circuit. In order to avoid phototube fatigue and dependence upon light source intensity or gain consistency of the voltmeter, optical null balance is used, causing the phototubes to operate a t equal response at balance. With this arrangement, however, new tristimulus filters had to be devised for the source, filter, photocell combination. This instrument can beused to as low a reflectance as 0.02%.

The Differential Colorimeter reads in terms of per cent reflectance of the tristimulus filter, which may be converted to X Y 2 tristimulus values, or directly to Adams’s chromatic value system. As with other tristimulus colorimeters this instrument performs best if i t is used as a difference meter, i .e . , to compare colors which are close together in color space.

All of the current instruments of this type use the recommended angles of incidences or reflection, either R46-o or RO--45, and exclude the directional reflectance. These instruments in general greatly simplify the specification of nonfluorescent colors, if used within their limitations.

6. Other Instruments

To simplify further the specification of colors there have been developed a series of instruments dependent essentially on the reduction of the selected ordinate method as used in spectrophotometry. If one attempts to measure a series of color specimens whose reflection or trans-


mission curves differ only in extremely small details one can obtain considerable accuracy and still decrease the number of selected ordinates used. Essentially we enter abridged spectrophotometry. The observer decides where the characteristic absorption of the average sample occurs (usually as the result of spectrophotometric measurements) and uses a few measurements to express the effect of small variations in the curves. By this method it is intended to reveal very small differences between like-colored samples rather than to measure the actual color. The reason for this simplification is obvious-it is capable of differentiating between an acceptable or nonacceptable product without recourse to any involved or lengthy calculations and may yield a single-valued function which then may be used to characterize a grade. Naturally any of the instruments used to specify color may in some cases be used in an abridged method.

Several instruments have been developed such as the Agtron and the Purdue Colorimeter that are specifically used for abridged spectrophotometry of particular products. These instruments can be operated quite satisfactorily by unskilled operators and the results obtained require no interpretation. The drawbacks are many. They cannot be used with any degree of success on colored objects differing materially from those they were designed for. They must be standardized with nonmetameric matches. If they are used to compare even moderately metameric specimens the data obtained may be so far from correct as to be completely meaningless. The data obtained even with nonmetameric colors are generally nonconvertible and therefore valid only for the particular instrument used, requiring separate specifications to be introduced for each product and for each instrument.

It would seem appropriate to consider the instrumentation problem in a specific industrial case, the grading of tomatoes, where two substantially different approaches have been made, the one developed on the Atlantic seaboard, the other in California. Two separate problems are involved: first, the assignment of the correct color grade to a given lot of tomatoes, determined prior to acceptance by the canner. The second is the ability to predict the final color grade of the tomato product from the first set of measurements. This necessitates further data on the processed material in order to establish a correlation. In the East, the Hunter Color-Difference Meter has been used for both sets of data. For both measurements, the tomatoes must be pulped and the pulp deaerated. The aL/bL ratio is then calculated, and the resulting value checked for the grade. As noted earlier, Robinson et al. (1952) correlated the ratio with dominant wave length.

In California, the Agtron has been developed specifically for the pur-

346 a. MACKINNEY AND C. 0. CHICHESTER

pose of assigning a grade to the raw tomato, and is described by Smith and Huggins (1952). It embodies an abridged spectrophotometric procedure but differs from those previously discussed in that one measures directly the ratio of the reflectances at the 546 mp mercury line and at the neon 640-651 mp lines. Two filters are used (Corning 4-64 and 2-61) which effectively isolate the two spectral regions from their respective low-pressure discharge tubes. There are two circuits with different and adjustable sensitivities for the red and green. Moving the filters switches the circuits, each of which is adjusted to a “standard level” by means of plastic discs of controlled color. The 546 and 640 mp regions were selected partly for convenience and simplicity, and because measurements a t 640 are reasonable sensitive to chlorophyll characteristic of unripe tomatoes and at 546 they are sensitive to lycopene in the well-ripened fruit. Measurements are not made on pulped tomatoes, but upon both cut halves. Field inspection procedure has been outlined by Whipple (1952) of the Bureau of Fruit and Vegetable Standardization, State of Cali- fornia. Since both grower and canner representatives may be present, the cut fruit may be returned to the former to aid picking by relating external to internal color, or given to the canner to relate the color grades of raw and finished product.

Since the Agtron as now used makes no measurement of the brightness, results cannot be converted to any of the standard color systems. It is primarily a field instrument, while the Hunter is primarily a laboratory instrument designed for wider applicability. The Agtron type is an attempt a t reducing the complexities of color aystems to a single meamre- ment upon which grades of one specific commodity can be determined.

The “Purdue Color Ratio Meter” developed by Desrosier et al. (1952) has certain features in common with the Agtron and involves essentially the same considerations in operation, though skin color instead of flesh color is measured. The Purdue instrument uses two banks of three photocells and a single light source. A ratio is obtained which is indicated as a single-value function. I n order to obtain an average reading the latest machine rotates the tomato. The choice of filters would seem somewhat less advantageous, the 560 mp region being chosen for the carotenoid and evaluation of good color development.

Where dependence is placed upon less than three attributes (whether 2, y, and Y , aL, bL, or any equivalent set) the findings of Younkin (1950b) should be borne in mind. Examining a large number of tomato purdes, he observed that the majority could be evaluated for appearance from hue and brightness, but for precise classification of all samples, all three attributes needed to be considered. Experience in the present authors’ laboratory fully substantiates this conservative view. Genetic strains of


tomatoes light pink in color will be completely devoid of chlorophyll when fully ripe. It may be surmised that they have the correct dominant wave length owing to the presence of small amounts of lycopene. The chroma or purity is so low that no inspector could accept them, yet they might be acceptable by instrumental check. Instrumentation and current activity in the color field show that it is in a state of flux, and nothing better than a guess can be hazarded as to future developments. The extent to which the Agtron is used depends upon developments both in the general thinking on the subject and in specific changes that may be projectedin theinstrument itself. The original blue filter to isolate the 436 mp line (note the article by Smith and Huggins, 1952) has already been superseded by the Corning green filter to isolate the 546 mp mercury line. The basicidea, however, has found acceptance in the State of California, Bureau of Fruit and Vegetable Standardization, as an acceptable and practical one for easy reference in field inspection work.

A similar situation exists for the Hunter instrument, where both circuit changes and filter modifications are in progress. Some thought is also being given to changing the characteristics of the 1931 standard observer to conform with Judd’s findings (Hunter, 1952). Matches based on material standards differing solely in brightness (nonmetameric matches) are clearly worth exploring. Abridged spectrophotometry may save an inordinate amount of labor. Color space transformations for perceived difference evaluation would seem less useful in foods than elsewhere, since differences must be expected in the perceived colors within a grade, and it is only the line of demarcation between two grades that need be determined.

It is of course possible to pick a single standard and to set grades so that samples within a grade shall not differ by more than a certain number of N.B.S. units, or by some other measure of AE.

It becomes increasingly apparent that color in foods will be measured in one of two ways: by abridged spectrophotometry, or by direct color measurement, preferably in terms of the 1931 C.I.E. conventions in either the original C.I.E. color space or one of its more useful transformations. One may also anticipate increased use (when applicable) of carefully prepared plastic material standards which can be cleaned and polished as often as necessary, for nonmetameric matches delimiting tolerances acceptable in a given color grade for a food.

REFERENCES Adams, E. Q. 1942, X - Z planes in the 1931 I.C.I. system of colorimetry. J . O p t .

Adams, E. Q. 1943. Chromatic valence as a correlate of Munsell chroma. J . Opt . SOC. SOC. Amer. 83, 168.

Amer. 88, 683.

348 0. MACKINNEY A N D C. 0. CHICHESTER

American Oil Chemists’ Society. 1946. Official and tentative methods of 2nd ed.

Amerine, M. A., and Winkler, A. J . 1941. Color in California Wines. Food Research 6 , l . Ayres, G. H. 1949. Evaluation of accuracy in photometric analysis. Anal. Chem. 21,

652. Bouma, P. J. 1947. “Physical Aspects of Colour,” trans. by de Groot. Elsevier Press,

New York. Boutaric, A., Ferre, L., and Roy, M. 1937. Recherches spectrophotometriques sur la

couleur des vins. Ann. fals. et fraudes 30, 196. Broeg, C. B., and Walton, C. F., Jr. 1952. Color standards for sugar cane sirup and

edible sugar cane molasses. Anal. Chem. 24, 832. Browne, C. A., and Zerban, F. W. 1941. “Handbook of Sugar Analysis,” 3rd ed.

John Wiley & Sons, Inc., New York. Bruce, B. A., and Turner, A. 1952. Permanent glass color standards for maple sirup

and honey. J . Opt. SOC. Amer. 42, 881. Buck, R. E., and Sparks, R. A. 1952. Relation of ketchup color to tomato color as

determined by the Hunter instrument. Food Technol. 6, 122. Cannon, C. G., and Butterworth, I. S. C. 1953. Beer’s and spectrophotometer linearity.

Anal. Chem. 26, 168. Caster, W. 0. 1951. Variability in the Beckman spectrophotometer. Anal. Chem.

23, 1229. Chamberlin, G. J. 1951. The C.I.E. colour system explained. Tintometer Ltd., Salis-

bury, England. Davidson, H. R. 1951. Calculation of color differences from visual sensitivity ellipsoids.

J . Opt . SOC. Amer. 41, 1052. Davidson, H. R., and Imm, L. W. 1949. A continuous automatic tristimulus integrater

for use with the recording spectrophotometer. J . Opt. SOC. Amer. 39, 942. Desrosier, N. W., Gaylord, F. C., Kellie, W. F., and Ellis, N. K. 1952. Meter simplifies

color grading of fruits and vegetables. Food Eng. 24(5), 92. Donaldson, R. 1947. A colorimeter with six matching stimuli. Proc. Phys. SOC. (Lon-

don) 69, 554 Dutton, H. J., Bailey, G. F., and Kohake, E. 1943. Dehydrated spinach: changes in

color and pigments during processing and storage. Ind. Eng. Chem. 86, 1173. Eastmond, E. J. 1950. Measurement of color changes in foods. Advances in Chem. Ser.

h e r . Chem. SOC. number 3, pp. 3-12. Eastmond, E. J., Peterson, J. E., and Stumpf, R. R. 1951. Observation of color

changes in some processed and stored foods. Food Technol. 6 , 121. Eolkin, D. 1952. Relative color evaluation of purees using black and white photog-

raphy. Food Technol. 6, 214-217. Evans, R. M. 1948. “An Introduction to Color.” John Wiley & Sons, Inc., New York. Ewing, G. W., and Parson, T., Jr., 1948. Intercomparison of Beckman spectro-

photometers. Anal. Chem. 20, 423. Fawcett, A. J. 1951. Colour and the visual measurement of colour. Tintometer Ltd.,

Salisbury, England. Friedman, M. E., Marsh, G. L., and Mackinney, G. 1952. On color in tomato prod-

ucts. Food Technol. 6, 395. Gardner Laboratory, Inc. 1950. Description and instructions for Hunter color and

color-difference meter (Brochure). Henry A. Gardner Lab., Inc., Bethesda, Maryland.

Chicago, Illinois.

Gibson, K. S. 1949. Spectrophotometry. Nat’l Bur. Standards. Circ. 484.


Gillett, T. R. 1953. “ Chemical-Physical Principles of Sugar Technology ”. (Pieter Honig, ed.). Elsevier Press, New York.

Gillett, T. R., and Holven, A. L. 1943. Grading of soft sugars. Znd. Eng. Chem. 36, 210.

Gillett, T. R., and Meads, P. F. 1952. Measurement of reflectance of white sugar. Anal. Chem. 24, 829.

Gillett, T. R., Meads, P. F., and Holven, A. L. 1949. Measuring color and turbidity of white sugar solutions. Anal. Chem. 21, 1228.

Glasser, L. G., and Troy, D. J. 1952. A new high sensitivity differential colorimeter. J . Opt. SOC. Amer. 42, 652.

Goldring, L. S., Hawes, R. C., Hare, G. H., Beckman, A. O., and Stickney, M. E. 1953. Anomalies in extinction coefficient measurements. Anal. Chem. 26,869-878.

Granger, G. W. 1952. Objectivity of colour preference. Nature 179, 778. Hardy, A. C. 1936. “Handbook of Colorimetry.” Technology Press, Cambridge,

Hardy, A. C., and Young, F. M. 1949. Colorimetry by abridged spectrophotometry.

Hunter, R. S. 1952. Improvement of the Color-Difference Meter. J . Opt. SOC. Amer.

Hunter, R. S. 1942. Photoelectric trietimulus colorimetry with three filters. Nat’l Bur.

Hunter, R. S. 1948a. Photoelectric Color-Difference Meter. J . Opt. SOC. Amer. 38,661. Hunter, R. S. 1948b. Accuracy precision and stability of a new photoelectric Color-

Difference Meter. J . Opt. Soc. Amer. 38, 1094. Irvine, G. N., and Anderson, J. A. 1952. A note on the determination of brightness in

flour. Trans. Am. Assoc. Cereal Chemists. 10, 59. Jacobsen, A. E. 1948. Non-adaptability of the ICI system to some near whites which

show absorption in the far blue region of the spectrum. J . Opt. SOC. Amer. 38, 442. Judd, D. B. 1949. A comparison of direct colorimetry of titanium pigments with their

indirect colorimetry based upon spectrophotometry and a standard observer. J . Opt. SOC. Amer. 39, 945.

Judd, D. B. 1952. “Color in Business, Science, and Industry.” John Wiley & Sons, Inc., New York.

Judd, D. B. 1950. Colorimetry. Nat’l Bur. Standards Circ. 478. Kaye, W., and Devaney, R. G. 1952. An automatic relative transmission attachment

for the Beckman Model DV Spectrophotometer. J . Opt. SOC. Amer. 42, 567. Kent-Jones, D. W. 1952. Measurement of flour color as affected by grade. Trans. Am.

Assoc. Cereal Chemists 10, 61. Kent-Jones, D. W., Amos, A. J., and Martin, W. 1950. Experiments in the photo-

electric recording of flour grade by measurement of reflecting power. Analyst 76, 133.

Kent-Jones, D. W., and Martin, W. 1950. A photoelectric method of determining the colour of flour as affected by grade, by measurements of .reflecting power. Analyst 76, 127.

Massachusetts.

J . Opt. SOC. Amer. 39, 460.

43,289.

Standards Circ. C429.

Kramer, A. 1950. This meter gives better color evaluations. Food Znds. 22, 1987. Kramer, A. 1951. Objective testing of vegetable quality. Food Technol. 6, 265. Kramer, A., and El-Kattan, A. A. 1953. Effect of application of heat on tomato juice

Livingston, G. E., and Vilece, R. J. 1953. Measuring discoloration of food purees in color. Food Technol. 7 , 400-404.

glass tubes. Food Technol. 7 , 272-275.


MacAdam, D. L. 1942. Visual sensitivities to color differences in daylight. J. Opt. SOC. A ~ T . 32, 247.

MacAdam, D. L. 1950, Method of colorimetric integration using punch-card account- ing machines. J. Opt. SOC. Amer. 40, 138.

MacGillivray, J. H. 1937. Spectrophotometric and colorimetric analyses of tomato pulp. Proc. Am. SOC. Hort. Sci. 36, 630.

Mackinney, G., and Weaat, C. A. 1940. Color changes in green vegetables. Znd. Eng. Chem. 32,392.

McNicholas, H. J. 1935. The color and spectral transmittance of vegetable oils. J. Research Nat’l Bur. Standards 16, 99.

Meads, P. F., and Gillett, T. R. 1949. Preparation of sugar liquors sirups for color determination. Anal. Chem. 21, 1495.

Melvin, E. H., MacMillan, D., and Senti, F. R. 1953. Suggested spectrophotometric methods for grading green soybean oil. J. Am. Oil Chemists SOC. 30, 255-259.

Moon, P., and Spencer, D. E. 1943. A metric for color space. J. Opt. Soc. Amer. 33, 260, 270.

Moster, J. B., and Prater, A. N. 1952. Color of capsicum spices. I. Measurement of extractable color. Food Technol. 6, 459.

Murray, H. D. 1952. “Color in Theory and Practice.” Chapman & Hall, Ltd., London. Nickerson, D. J. 1935. Disk colorimetry including a comparison of methods for com-

Nickerson, D. 1936. The specification of color tolerances. Teztile Research 6 , 509. Nickerson, D. 1950. Munsell renotation used to study the color space of Hunter and

Adams. J. Opt. Soe. Amer. 40, 85. Nickerson, D., and Newhall, S. M. 1943. A psychological color solid. J. Opt. SOC.

Amer. 33, 419. Optical Society of America, 1943. Sub-committee on the Spacing of the Munsell

Color. J. Opt. SOC. Amer. 33, 385. Optical Society of America Committee on Colorimetry. 1953. “Science of Color.”

Thomas Y. Crowell Company, New York. Peterson, E. W., Grossman, H. H., Saunderson, J. L., and Caldecourt, V. J. 1944. An

electrical tristimulus integrater. J. Opt. SOC. Amer. 39, 1055. Production and Marketing Administration. 1945. U. S. Standards for Grades of

Canned Tomato Puree. Jan. 1, 1945. United States Department of Agriculture, Waahington, D.C.

Robinson, W. B., Ransford, J. R., and Hand, D. B. 1951. Measurement and control of color in the canning of tomato juice. Food Technol. 6, 314.

Robinson, W. B., Wishnetsky, T., Ransford, J. R., Clark, W. L., and Hand, D. B. 1952. A study of methods for the measurement of tomato juice color. Food Technol. 6 , 269.

Sastry, L. V. L., and Tischer, R. G. 1952. Stability of the anthocyanin grapes in con- cord grape juice. Food Technol. 6, 264.

Saunderson, J. L., and Milner, B. I. 1946. Modified chromatic value color space. J . Opt. Soc. Amer. 36, 36.

Schofield, R. K. 1939. The Lovibond Tintometer adapted by means of the Rotham- sted device to measure colours on the C.I.E. system. J. Sci. Instr. l6,74.

Scofield, F. A method for determination of color differences. Nat’l Paint, Varnish and Lacquer Assoc., Sci. Section Circ. 664 (1943).

Shah, J. N., and Worthington, 0. J. 1953. Comparison of several methods for specifying the color of frozen strawberries. Paper 28, 13th, Annual Meeting, I.F.T., Boston, Massachusetts, p. 14 of Technical Program and Abstracts.

puting tristimulus values for certain disks. J. Opt. Soc. Amer. 26, 253.


Smith, T. J., and Huggings, R. A. 1952. Tomato classification by spectrophotometry.

Sondheiner, E., and Kertesz, Z. L. 1947. The anthocyanin of strawberries. J. Am.

Sturrock, W., and Staley, K. A. 1950. Fundamentals of light and lighting. Gen. Elect.

Thomson, P. 1953. Single number systems for the color of transparent objects. J. Am.

Thomson, P. 1947. Methods of reading color without Lovibond. J. Am. Oil Chemists

Tintometer Ltd. 1950. Colorimetry, Part I. Tintometer Ltd. Salisbury, Eng. Lovibond

Troland, L. T. 1929. “Psychophysiology.” D. Van Nostrand Company, Inc., New

Wald, G. 1945. Human vision and the spectrum. Science 101, 653. Whipple, S. R. 1951. Problems in grading canning tomatoes to color standards by

visual methods: and an electronic means of objectively grading color to these standards. Department of Agriculture Bureau of Fruit and Vegetable Standard- ization, Sacramento, California.

Wiklund, 0. 1950. Colorimetry, nephelometry, reflectometry and fluorescence in the sugar industry. Socker 6, 225.

Winkler, A. J., and Amerine, M. A. 1938. Color in California Wines. Food Research 3, 429.

Worthington, 0. J., Cain, R. F., and Wiegand, E. H. 1949. Determination of color of unclarified juices by reflectometer. Food Technol. 3, 274.

Younkin, S. G. 1950a. Application of Hunter Color-Difference Meter to a tomato color measurement problem. J. Opt. Soc. Amer. 40, 265.

Younkin, S. G. 1950b. Measurement of small color differences in tomato purees. J. Opt. SOC. Amer. 40, 596.

Younkin, 5. G. 1950c. Color measurement of tomato purees. Food Technol. 4, 350. Zerban, &’. W., Martin, J., Erb, C., and Sattler, L. 1952. Spectrophotometric studies

Zerban, F. W., Sattler, L., and Martin, J. 1951. Spectrophotometric studies on refined

Elect Tonics.

Chem. SOC. 70, 3476.

Bull. LD-2, Cleveland, Ohio.

Oil Chemists Soc. 30, 259-262.

SOC. 24, 387.

System. Part 11. Lovibond-Schofield System.

York.

on raw cane sugar in solution. Anal. Chem. 24, 168.

sugar in solution. Anal. Chem. 23, 308.

[advances in food research] advances in food research volume 5 volume 5 || the color problem in...

Documents