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

机译:近红外光谱与间隔组合优化算法结合溶均匀植物中钙和镁的测定

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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.
机译:测定无机营养素的含量作为项目的一部分进行,以通过使用肥料来改善作物产量。近红外光谱与间隔组合优化耦合,用于确定溶均植物中钙和镁的无机营养素。间隔组合优化用于选择有效的间隔,其优点将较小的重量分配给不太重要的变量。与全谱偏重最小二乘回归相比,间隔组合优化提高了钙和镁的预测精度和精确度。结果是钙的高预测能力,具有0.159%的根部平均平方误差预测,镁,具有0.064%的根部平均平方误差预测。在该研究中,在有效变量和准确的结果方面,显示了在全谱偏数最小二乘上过度的间隔组合优化的优越性。结合间隔组合优化的近红外光谱对茄科植物中无机营养素,钙和镁的测定是有效的。

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