NEAR IR SURFACTANT ANALYSIS 455 ß •50' ß 200' t50' ß too ' ' I ' I ' I 200 1 aO0 1600 1800 2000 HAVELENGTH (nm) ß 050 • ' I ' I ' 2200 2400 Figure 7. Near infrared reflectance spectra of a variety of shampoos with water bands removed by mathe- matical subtraction. and solids can be linked to either water bands or aliphatic C-H bands. Often pairs of wavelengths, one at baseline and the other on the prominent peak, are selected, simu- lating the derivative techniques of Norris (12). Note the choice of the two wavelength pairs chosen for benzoic acid, which coincide with the prominent aromatic C-H stretch at 1685 nm. In addition, it is interesting to note the 1300- 1400 nm bands selected for benzoic acid are those usually assigned to the broad first overtone of water. This could indicate the influence of hydrogen bonding of solvent water and benzoic acid. The benzoic acid spectrum is very featureless in this region due to the infrared inactivity of OH symmetrized by dimerization (13). Also of interest are the bands selected to predict pH, which seem to be entirely due to the broad overtone and combination bands of water, again indicating that pH has some type of hydrogen bonding effect on the solvent water (14). Table VIII Compositional Data for Finished Product Shampoo Brand A Brand X Constituent Mean % SD Range Mean % SD Range Active Detergent 11.32 0.72 10.3-15.35 10.89 0.77 7.27-12.72 Solids 20.65 1.14 19.43-25.21 16.18 1.15 12.86-20.86 Moisture 80.76 2.09 74.68-86.51 83.77 2.27 79.27-87.46 pH 5.71 0.10 5.55-6.0 * , * pH not measured.

456 JOURNAL OF THE SOCIETY OF COSMETIC CHEMISTS Table IX Linear Regression Data for NlRA Prediction of Brand A Shampoo Constituent nm K o . . K n r SEC F Active Detergent - 27.45 0.96 0.35 408 2083 - 384.28 2139 470.83 Solids - 89.16 0.98 0.46 725 1940 - 98.12 2348 292.86 Moisture 253.23 0.93 0.76 154 1680 4258.50 1790 -4634.74 1940 246.78 pH 11.85 0.79 0.06 34 1380 - 87.61 2360 32.25 FINISHED PRODUCT SHAMPOOS The near infrared spectra of finished product shampoos are very similar to those of the raw material surfactants which are the major constituents. Figure 7 shows the spectra of a variety of shampoos with most of the water bands removed by mathematical subtrac- tion. Typical C - H, O - H, and N - H group frequencies according to Table VI can be identified. Table VIII lists the compositional data for Brand A and Brand X varieties. The multiple linear regression statistics at selected wavelengths are listed in Tables IX and X. It should be noted that the ranges listed in Table VIII for shampoo composition contain some samples that were artificially created. Although it is better to use a "real" plant production set to calibrate the near infrared spectrophotometer, it would have taken much longer to obtain out-of-specification samples to include with the majority of in-specification product produced in our plant. Figures 8 and 9 are examples of the linearity achievable by NIRA in the prediction of moisture and pH in Brand A shampoo. In all cases but pH, the SEC are at least as good Table X Linear Regression Data for NIRA Prediction of Brand X Shampoo Varieties Constituent nm K o .. K n r SEC F Active Detergent 121.39 0.92 0.31 215 1710 - 3790.16 1722 3387.62 2139 73.32 Solids - 56.49 0.97 0.27 690 2083 - 476.13 2130 238.21 2270 374.73 Moisture 58.94 0.95 0.71 418 1905 103.83 2139 - 171.33