Discussion on scatter plot having discontinuous data

"Due to the randomized data split process for calibration and prediction sets, some
graphs show discontinuity (e.g. the TA between 0.14 and 0.18 g/kg). However, the lake of
data observed in the prediction results (Fig. 5) may affect in the calibration results (Table 8)."

(Liu, Y., & Ying, Y. (2007). Noninvasive method for internal quality evaluation of pear fruit using fiber-optic FT-NIR spectrometry. International Journal of Food Properties, 10(4), 877-886.)

SDR = SD/RMSEP: SDR = 2 would mean two group sorting but with much larger error overlap

"A further statistic, SDR, was also used and defined as:
SDR = SD/RMSEP
where SD was the data set standard deviation. In theory (for large normally distributed data set) it is equal to, and indicates more directly than either R2 and RMSEP separately can, the relative predictive performance of a model: the higher the value, the greater the power. We consider a value of three the minimum for sorting/grading purposes, enabling the data set to be split into three groups (of width equivalent to RMSEP) with the extreme two groups not overlapping appreciably. A value of two would mean two groups but with much larger error overlap"

(McGlone, V.A. and Kawano, S., (1998) Firmness, dry-matter and soluble-solids assessment of postharvest kiwifruit by NIR spectroscopy, Postharvest Biology and Technology, 13, 131-141.)

Wavelength of 914 nm was sensitive to the SSC of satsuma mandarins

"However, it is likely that the wavelengths 650-680 nm for SSC mainly attributed to the color of bayberry juice. It is same to the sensitive wavelengths to acidity of 685-695 nm, because there is nonexistent of organic acids in this region of the spectrum. So in our research, to SSC, wavelengths 970-990 nm might be of particular importance, and to acidity, 910-925 nm were better. This found was similar to the earlier literature, such as He (1998) found a wavelength of 914 nm was sensitive to the SSC of satsuma mandarins. And near 900 nm were sensitive wavelengths corresponding to organic acid of oranges."

(Shao, Y. and He. Yong (2007) Nondestructive measurement of the internal quality of bayberry juice using Vis/NIR spectroscopy, Journal of Food Engineering, 79, 1015-1019.)

Important wavelengths can be determined from PLS regression coefficients and difference in spectra

"The wavelengths important in classifying the species of interest were determined based on PLS regression coefficients and differences in spectra."

"The regression coefficients indicating important wavelengths in the calibration model are shown in Fig. 1."

(Fengyou, J., Maghirang, E., Dowell, F. Abel, C. and Ramaswamy, S., 2007. Differentating tobacco budworm and corn earworm using near-infrared spectroscopy, Journal of Economic Entomology, Vol. 100, No. 3, 759-763.)

SDR > 2.5 allows for sorting into two grades

"The SDR_P statistic for approximately 100 samples was typically above 2.5, which allows for sorting into two grades of sweetness."

(Golic, M.; Walsh, K.B. Robustness of calibration models based on near infrared spectroscopy for the in-line grading of stonefruit for total soluble solids content. Analytica Chimica Acta 2006, 555, 286-291.)

In transmission spectra of milk, low scattering gave rise to low absorbance.

"The original NIR spectra of the milk samples having high, medium and low fat contents are shown in Figure 3. The spectrum of milk shifted upward with an increase of fat content. In raw milk, the fat exists in the form of globules from 1 mm to 12 mm in diameter, which act as a scattering material. As fat content increases, the number of fat globules increases, and the scattering effect becomes more severe.”

(Chen, J.Y., Iyo, C., Terada, F. and Kawano, S. 2002. Effect of multiplicative scatter correction on wavelength selection for near infrared calibration to determine fat content in raw milk, Journal of Near Infrared Spectroscopy. 10, 301-307.)

High resolution: is it useful for broad band NIR?

"I have to add something to what David Hopkins said: in the early days of NIR (say, from the mid-1970s to the mid-1980s) the major applications were in the agricultural areas. The absorbance bands corresponding to the key materials in those types of samples were in fact, inherently broad: moisture, starch, and protein all have absorbances that are intrinsically broad due to the effects Dave mentioned. Therefore there was little or no incentive for the instrument manufacturers to design instruments with high spectral resolution, because the applications of them, at that time, did not justify expending the engineering time and resources to improve the resolution. Nowadays, of course, many more different types of applications exist, some of which include measurements of materials with the sharp bands that Dave also described. It is the change in the measurement requirements that drove the technologies in the direction of high spectral resolution devices." (Howard Mark, http://www.impublications.com/discus/messages/5/2147.html?1163283835)