Abstract
BackgroundManganese (Mn) is an essential microelement in cottonseeds, which is usually determined by the techniques relied on hazardous reagents and complex pretreatment procedures. Therefore a rapid, low-cost, and reagent-free analytical way is demanded to substitute the traditional analytical method.ResultsThe Mn content in cottonseed meal was investigated by near-infrared spectroscopy (NIRS) and chemometrics techniques. Standard normal variate (SNV) combined with first derivatives (FD) was the optimal spectra pre-treatment method. Monte Carlo uninformative variable elimination (MCUVE) and successive projections algorithm method (SPA) were employed to extract the informative variables from the full NIR spectra. The linear and nonlinear calibration models for cottonseed Mn content were developed. Finally, the optimal model for cottonseed Mn content was obtained by MCUVE-SPA-LSSVM, with root mean squares error of prediction (RMSEP) of 1.994 6, coefficient of determination (R2) of 0.949 3, and the residual predictive deviation (RPD) of 4.370 5, respectively.ConclusionsThe MCUVE-SPA-LSSVM model is accuracy enough to measure the Mn content in cottonseed meal, which can be used as an alternative way to substitute for traditional analytical method.
Highlights
Manganese (Mn) is an essential microelement for plant growth
Seventy-two samples consisted of the validation set for the prediction, and 216 samples formed calibration set for modeling (Table 1)
Compared with full-spectra partial least squares (PLS) model, the values of R2 and residual predictive deviation (RPD) were increased, while the values of RMSEC, RESEP and RMSECV were decreased in full-spectra least-squares support vector machine (LSSVM) model (Table 3), which indicated that nonlinear full-spectra LSSVM model was superior to classical linear full-spectra PLS model to build the calibration model for cottonseed Mn content
Summary
Manganese (Mn) is an essential microelement for plant growth. Mn participated in the watersplitting system of photosystem II (PSII) and provided electrons necessary for photosynthetic electron transport. A group of four Mn atoms (Mn cluster) was associated with the oxygen-evolving complex (OEC) bound to the reaction center protein (D1) of PSII in water photolysis (Goussias et al 2002). Mn intervened in activating enzyme-catalyzed reactions, including phosphorylation, decarboxylation, reduction, and hydrolysis reaction. These reactions could affect the processes such as respiration, amino acid synthesis, lignin biosynthesis and the level of hormones in plants (Millaleo et al 2010). Manganese (Mn) is an essential microelement in cottonseeds, which is usually determined by the techniques relied on hazardous reagents and complex pretreatment procedures. A rapid, low-cost, and reagent-free analytical way is demanded to substitute the traditional analytical method
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