Method for identifying Dendrobium aphyllum (Roxb.)C. E. Fisch., Dendrobium officinale Kimura et Migo and Dendrobium devonianum Paxt.
A technology of iron maple bucket and purple maple, applied in the field of identification, can solve the problems of deceptive sales, no-seeing, irresponsibility, etc.
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Embodiment 1
[0032] 3. Spectral data preprocessing: Multiple data points are selected for each spectrum. In order to eliminate the spectral baseline drift and spectral bending, as well as the near-infrared absorption spectrum overlap caused by the mutual interference between different components contained in the sample, the derivative formula is used: ① First derivative formula: y=(x(i+Δ)-x(i)) / Δ;
[0033] Where: Δ is the spectral distance, x is the spectral absorbance before derivation, and y is the spectral absorbance after derivation;
[0034] 4. Establish the identification model: first, specify the category values of the water grass maple bucket, the iron maple bucket and the purple maple bucket as 1, 2, and 3 respectively, and use the Matlab software to preprocess the The final spectrum value is the independent variable of the model, and the specified category is the dependent variable to establish the prediction models of water grass maple, iron maple and purple maple, and then pr...
Embodiment 2
[0045] 3. Spectral data preprocessing: Multiple data points are selected for each spectrum. In order to eliminate spectral baseline drift and spectral bending, as well as the near-infrared absorption spectrum overlap caused by the mutual interference between different components contained in the sample, the derivative formula is used: 2 Order derivative formula: y=(x(i+Δ)-2x(i)+x(i-Δ)) / Δ 2
[0046] Where: Δ is the spectral distance, x is the spectral absorbance before derivation, and y is the spectral absorbance after derivation;
[0047] 4. Establish the identification model: first, specify the category values of the water grass maple bucket, the iron maple bucket and the purple maple bucket as 1, 2, and 3 respectively, and use the Matlab software to preprocess the The final spectrum value is the independent variable of the model, and the specified category is the dependent variable to establish the prediction models of water grass maple, iron maple and purple maple, and t...
Embodiment 3
[0056] 3. Spectral data preprocessing: Multiple data points are selected for each spectrum. In order to eliminate spectral baseline drift and spectral bending, as well as the near-infrared absorption spectrum overlap caused by the mutual interference between different components contained in the sample, the derivative formula is used: 1 Order derivative formula: y=(x(i+Δ)-x(i)) / Δ;
[0057] Where: Δ is the spectral distance, x is the spectral absorbance before derivation, and y is the spectral absorbance after derivation;
[0058] 4. Establish the identification model: first, specify the category values of the water grass maple bucket, the iron maple bucket and the purple maple bucket as 1, 2, and 3 respectively, and use the Matlab software to preprocess the The final spectrum value is the independent variable of the model, and the specified category is the dependent variable to establish the prediction models of water grass maple, iron maple and purple maple, and then predic...
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