Summary
Two case studies were conducted to verify calibration model transfer methods without standards by multi-step wavelength selection, using 3–7 near infrared spectrometers to predict ingredients in corn and total plant alkaloids (TPA) in tobacco leaves. Based on the characteristic wavelengths of Uc, which are selected using the scale-invariant feature transform (SIFT), this study advances two multistep wavelength selection methods by selecting wavelengths with high independence and a high standard deviation of the sample spectra (SDSS). The first method, SIFT-SDSS-CORX, selects important characteristic wavelengths Uc-i from Uc whose SDSS is greater than a threshold SDSSacrit. Subsequently, rx, the correlation coefficient matrix between spectral signals of Uc-i, is calculated, and only one wa
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