Effect of particle size and spectral sub-range within the UV-VIS-NIR range using diffuse reflectance spectra on multivariate models in evaluating the severity of fusariosis in ground wheat.

Control (crops grown in natural conditions) and Fusarium head blight (FHB) damaged (crops inoculated with Fusarium culmorum conidia) grain of four wheat cultivars was ground and sieved into three fractions of different particle size. A series of blended samples differing in content of damaged material were prepared within fractions and cultivars, and diffuse reflectance spectra recorded within the 200-2500 nm wavelength range. Partial least-squares (PLS) models for the percentage of damaged material in blended samples were built for each of twelve series within different spectral ranges, and the root-mean-squared error of cross-validation (RMSECV) was used for the assessment of model performance. Errors using the models were lowest for the finest fraction independent of spectral range; however, their values depended on the cultivar. RMSECV for the finest fraction averaged over cultivars ranged from a little below 3.0 (when the ultraviolet light sub-range was used or participated with another one) to 8.1% (when only the near infrared (NIR) sub-range was used). For the medium and coarse fractions, averaged errors showed the same tendency of dependence on the sub-range(s); however, with higher values that increased with an increase in particle size. In conclusion, within the different fractions of particle size and spectral ranges, the most sensitive to the presence of damaged material were models developed for the finest fraction and when the ultraviolet light sub-range was used in modelling.

Comparison of the usability of different spectral ranges within the near ultraviolet, visible and near infrared ranges (UV-VIS-NIR) region for the determination of the content of scab-damaged component in blended samples of ground wheat.

Soft wheat grain samples of the same variety were obtained from a plot where the crop grew under natural conditions (control material) and from a plot where the crop was inoculated with Fusarium culmorum. The grain was ground and sieved with the finest fraction (a particle size less than 0.18 mm) of both materials being used for the preparation of samples in which the content of damaged constituent varied from zero to approximately 84%. Diffuse reflectance spectra of the absorbance from the blended samples were recorded in the 200-2500 nm spectral range and multivariate calibration PLS (Partial Least Squares) models were built within three spectral ranges: 200-2500, 200-1400 and 1400-2500 nm. Before modelling, several variants for spectra pre-processing were tried: multiple scatter correction, single and double differentiation, in all cases with and without centring. Single differentiation followed by centring was found to be the best method for spectra pre-processing in all spectral ranges. Very good calibration models were obtained for the whole and shorter wavelengths spectral ranges, allowing the detection of 1.50 and 0.76% of the content of scab-damaged constituent, respectively. Two-dimensional correlation spectroscopy applied to the set of spectra enabled the assignment of spectral bands and an analysis of changes in the chemical composition caused by scab damage. It was found that the content of protein and lipids increased with an increase of the scab-damaged constituent, whereas the content of moisture and starch decreased.