Spectral Data Analysis. The spectroscopic (NIR and mid-IR)detectors receive light from the sample in the form of diffuse reflectance after absorption, specular reflectance, and scattered light.Only the diffuse reflectance contains chemical information, whereas the latter two carry no useful information as there is no large variation in particle size between starch and onion powder (based on the result from Cilas 1090 particle size analyzer). The collected spectra might be affected by systemic noise due to light scattering, variation in particle size, and instrumental drift. Thus, to determine an accurate chemical composition from spectroscopic measurements, the raw spectra must be corrected at different levels by applying preprocessing methods.18 In this study, both FT-NIR and FT-IR spectral data were treated with five preprocessing methods: three data normalization methods (minimum, maximum, and range), standard normal variate transformation (SNV), and multiple-scatter correlation (MSC). The original FT-NIR spectra of all the samples and the original spectra preprocessed by the SNV method are depicted in Figure 1, panels a and b, respectively. The raw FT-IR spectra for each sample and SNV-preprocessed spectra are shown in Figure 2, panels a and b,respectively.