The microfibril angle of the S2 layer in the secondary cell wall of the tracheid is important for molecular and microscopic properties that influence collapse resistance, longitudinal modulus of elasticity and other l...
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The microfibril angle of the S2 layer in the secondary cell wall of the tracheid is important for molecular and microscopic properties that influence collapse resistance, longitudinal modulus of elasticity and other lateral properties of conifers at the macroscopic level. This research aimed to investigate the feasibility of using a fruit fly optimization algorithm for visible and near infrared modeling optimization of Dahurian larch wood microfibril angle prediction. Originally, the linear relationship between microfibril angle and their raw spectra and visible and near infrared spectra pretreated by wavelet transform was established. Then, a nonlinear coupledmodel was built by combining the stepwiseregressionanalysis and generalizedregressionneuralnetwork methods. As a final point, fruit fly optimization algorithm was used for optimizing stepwiseregressionanalysis- generalizedregressionneuralnetworkcoupledmodel. It was found that stepwise regression analysis-generalized regression neural network coupled modelcoupledmodel based on the optimization of fruit fly optimization algorithm simplify visible and near infrared spectral data and its prediction results ( r(p)(2) = 0.90, RMSEP = 0.75, mean average percentage error ( MAPE(p)) = 0.05) outperforms original partial least squares model ( r(p)(2) = 0.86, RMSEP = 0.88, MAPE(p) = 0.06). This work demonstrated the feasibility of using improved chemometric techniques for improving the precision of visible and near infrared spectra in the prediction of microfibril angle.
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