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Determination of calcium and magnesium in the Solanaceae plant by near infrared spectroscopy combined with interval combination optimization algorithm

Abstract Determination of the content of inorganic nutrients was done as part of a project to improve crop yield by use of fertilizers. Near-infrared spectroscopy coupled with interval combination optimization was used to determine the inorganic nutrients of calcium and magnesium in the Solanaceae plant. Interval combination optimization was employed to choose effective intervals with the merit of assigning smaller weights to less significant variables. Compared with full spectrum partial least squares regression, interval combination optimization improved the predictive accuracy and precision for both calcium and magnesium. The result was a high predictive ability for calcium, with a root mean squared error prediction of 0.159%, and for magnesium, with a root mean squared error prediction of 0.064%. In this study, the superiority of interval combination optimization over full spectrum partial least squares was shown in the aspects of effective variables and accurate results. Near-infrared spectroscopy combined with interval combination optimization was efficient for the determination of inorganic nutrients, calcium and magnesium, in the Solanaceae plant.