Indirect prediction method may need to check for robustness

"While good calibration models were obtained for dry matter, it seems more difficult to predict acidity based on the NIR spectrum. The concentration of acids in most fruit and vegetables is typically considerably smaller than that of sugars, and probably too small to affect the NIR spectrum significantly. The water absorption bands dominate the spectrum of fruit and vegetables, and it is not likely that minor constituents can be measured well. Obviously, when the concentration of such a minor constituent is correlated to, e.g., sugar content, the calibration results may seem reasonable but then the method is indirect and robustness issues are to be expected when applied to a different batch."

(Nicolaï, B.M., Beullens, K., Bobelyn, E., Peirs, A., Saeys, W., Theron, K.I., Lammertyn, J.

Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review (2007) Postharvest Biology and Technology, 46 (2), pp. 99-118. )

Non-linearity can be accounted for by extra latent variables of PLS

"So far there does not seem to be convincing evidence that nonlinear techniques, such as ANNs or kernel- ased methods can really offer advantages with respect to the classical linear algorithms. This is due to the fact that NIR spectroscopy is essentially a very linear technique. Further, Li et al. (1999) stated that both PCR and PLS can provide linear approximations to subtle deviations from ideal linear behaviour by using extra latent variables to account for the nonlinearity."

(Nicolaï, B.M., Beullens, K., Bobelyn, E., Peirs, A., Saeys, W., Theron, K.I., Lammertyn, J.

Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review (2007) Postharvest Biology and Technology, 46 (2), pp. 99-118. )

Definition of Robustness of Calibration Model

"Calibration models are called robust when the prediction accuracy is relatively insensitive towards unknown changes of external factors. The main factors which may affect model performance are (Wang et al., 1991): (i) the calibration model developed on one instrument is transported to another instrument that produces instrumental responses that differ from the responses obtained on the first instrument; (ii) the instrumental responses measured on a single instrument drift because of temperature fluctuations, electronic drift, and changes in wavelength or detector stability over time; and (iii) the samples belong to different batches."

(Nicolaï, B.M., Beullens, K., Bobelyn, E., Peirs, A., Saeys, W., Theron, K.I., Lammertyn, J.

Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: A review (2007) Postharvest Biology and Technology, 46 (2), pp. 99-118. )

A sucrose absorption band in the 900–930 nm range

"A number of researchers have shown that the SSC and:or DM of a number of fruits can be
predicted by NIR spectroscopy (e.g. Birth et al., 1985; Dull et al., 1989; Kawano et al., 1992;
Slaughter, 1995). Generally, NIR light from 800 to 1000 nm has been used and success attributed to a sucrose absorption band in the 900–930 nm range."

(V.Andrew McGlone, Sumio Kawano, Firmness, dry-matter and soluble-solids assessment of postharvest kiwifruit by NIR spectroscopy, Postharvest Biology and Technology, Volume 13, Issue 2, April 1998, Pages 131-141, ISSN 0925-5214)

Second-derivative absorbances at 874 and 902 nm had a high correlation with the sugar content of melons

"Abstract
A method for visualizing the sugar content in the flesh of melons was developed. This method was based on the sugar absorption band in the near-infrared (NIR) region to avoid bias caused by the color information of a sample. NIR spectroscopic analysis revealed that each of the two second-derivative absorbances at 874 and 902 nm had a high correlation with the sugar content of melons. A high-resolution cooled charged couple device camera with band-pass filters, which included the above two wavelengths, was used to capture the spectral absorption image of a half-cut melon. A color distribution map of the sugar content on the surface of the melon was constructed by applying the NIR spectroscopy theory to each pixel of the acquired images."

(J Agric Food Chem. 2002 Jan 2;50(1):48-52.

Near-infrared imaging spectroscopy based on sugar absorption band for melons.

Tsuta M, Sugiyama J, Sagara Y.)