Abstract
Near Infrared (NIR) Spectroscopy technique combined with chemometrics methods were used to group and identify samples of different soy cultivars. Spectral data, collected in the range of 714 to 2500 nm (14000 to 4000 cm-1), were obtained from whole grains of four different soybean cultivars and were submitted to different types of pre-treatments. Chemometrics algorithms were applied to extract relevant information from the spectral data, to remove the anomalous samples and to group the samples. The best results were obtained considering the spectral range from 1900.6 to 2187.7 nm (5261.4 cm-1 to 4570.9 cm-1) and with spectral treatment using Multiplicative Signal Correction (MSC) + Baseline Correct (linear fit), what made it possible to the exploratory techniques Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) to separate the cultivars. Thus, the results demonstrate that NIR spectroscopy allied with de chemometrics techniques can provide a rapid, nondestructive and reliable method to distinguish different cultivars of soybeans.
Highlights
It is of significant value to the seed industry the development and adaptation of new technologies that improve the system of identification and evaluation of seed lot purity
Considering spectral data from the Near Infrared (NIR) region can carry information about the composition of the samples and these compositions may vary as cultivar varies, these associations suggest the possibility of using chemometric tools to extract and relate such information
NIR spectroscopy can detect the main structural changes related to composition, coming about as consequence of the changes in the DNA structure, since that the phenotypic changes reflect the changes on the genotypic structure (Alishahi, Farahmand, Prieto, & Cozzollino, 2010; Munck, Møller, Jacobsen, & Søndergaard, 2004)
Summary
It is of significant value to the seed industry the development and adaptation of new technologies that improve the system of identification and evaluation of seed lot purity. Soybean is widely desired for its nutritional value. Identification of the soybean variety may be necessary, among other reasons, to avoid fraud, checking the purity of a lot, since the grains/seeds may be difficult to distinguish visually, with the possibility of mixing different soybean varieties, where a cultivar of high productivity and low nutritional value may be giving volume to a lot of variety of greater importance, it becomes necessary a technique to make the identification of quickly and without destruction of the sample. Considering spectral data from the NIR region can carry information about the composition (qualitatively and quantitatively) of the samples and these compositions may vary as cultivar varies, these associations suggest the possibility of using chemometric tools to extract and relate such information.
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