Are you "odor-blind"? - Journal of Chemical Education (ACS

Abstract. Discusses the phenomenon of odor-blindness and requests information regarding personal experiences with this condition...
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LETTERS Are You "Odor-Blind"?

To the Editor: It is well known that human color-vision is based on a system of three primary colors; red, green, and blue. This makes possible the reproduction of any color by means of three inks in color printing, three emulsions in color photography, or three phosphors in color television. Corresponding defects in components of the human visual system result in three main types of color-blindness; red-blindness which afflicts about 2% of men; green-blindness, also affecting 2% of men; and a rare blue-blindness (1 in 50,000). However, it is a very little known fact that a similar situation applies to odor. Some persons, while having an apparently normal sense of smell, find that they are unable to detect one particular odor. About 10% of people cannot smell the poisonous hydrogen cyanide. Two per cent cannot smell the sweaty odor of isovaleric acid. One person in a thousand cannot smell the mercaptan odor of the skunk. This phenomenon has been called "odor-blindness.'' It is known scientifically as "specific anosmia," or specific loss of one component of the sense of smell. It had been suspected for centuries that color-vision works on just three primaries, because of the common knowledge among artists that three pigments sufficeto mix any color. But no such practical rule has ever been found for odor, which leads to the suspicion that odor, if indeed it is based on primaries, must be far more complex than color. This is where odor-blindness comes in. It is a very reasonable hypothesis that each type of odor-blindness is due to a malfunction of one primary odor of the sense of smell. Hence if we knew just how many different types of odor-blindness exist, we would have a clear indication of how many primary odors there are. This idea was put forward twenty years ago by Marcel Guillot, who listed 8 types of odor-blmdness as a beginning. My own recent investigation of the newly discovered isovaleric acid anosmia has firmly established the corresponding "sweaty" primary odor [Nature, 214, 1095 (1967)l. But these observations and others have made it obvious that the list of known specific mosmias is far from complete. The scientific community can contribute quite effortlessly toward clarifying an ancient problem. Many readers must be able to recall personal experiences which, on lookmg back, may have been due to an odor-blindness. You know that you have a perfectly good sense of smell, that faithfully registers the aroma of food, the scent of flowers, the allure of perfume, the stench of decay, or the warning of fire. Yet inexplicably you encounter some particular odor which is obvious to your colleagues or family, but which is a complete blank for you. It might be a perfume, a

flower, a foodstuff, or a specific chemical compound. Or you may perceive some unconventional reaction, like a fruity smell in isobutyric acid, or a sulfury smell in pineapple. You probably dismissed your discovery with a joke, and thought no moreof it. But the chances are that you happen to be specifically ansomic to that one particular odor, or class of odors. If so, do please write and tell me about it, because the information you provide may furnish one more missing piece in the jig-saw puzzle of the sense of smell. JOHNE. AMOORE WESTERN REGIONAL RESEARCH LABOR.~TORY, US.DEPARTMENT OF AGRICULTURE, 94710 ALBANY,CALIF.

Curve Fining

To the Xditor: Three articles in the December issue [J. CHEM. EDUC.,44,756,757, and 759 (1967)l deal with practical problems of curvefitting of experimental data. Since many chemists do not have easy access to the literature on curve-fitting, I would like to suggest some additional references for those who would pursue the subject further. I n my opinion the first reference should be J. Mandel's "The Statistical Analysis of Experimental Data" [Interscience Publishers (a division of John Wiley & Sons, Inc.), New York, 19641. Chapter 7 emphasizes the importance of weighting factors, correlated errors, and the mathematical model. (These concepts of least squares are central to the three articles cited above.) Chapter 12 illustrates the fitting of straight lines using several types of data taken from chemical examples. IGneticists should he particularly interested in the author's analysis of rate data having cumulative errors. The review by L. S. Nelson [J. CHEM.EDUC., 42, A326 (1965) ] summed it up as follows: . . . Any practicing scientist can learn a great deal from this book. The first thing he will l e a n is that there can be no isolation from an understanding of the behavior of measurements.

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E. D. Smith and D. M. Matthews [J. CHEM.EDUC., 44, 757 (1967) 1 are overzealous on this point where they state that:

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in the typical chemical application, the experimental conditions are controlled so as to make the percentage error a. constant.

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Volume 45, Number 3, Morch 1968

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