Abstract
The calibration transfer between instruments is mainly aimed at the calibration transfer between normal spectrometers. There are few studies on the calibration transfer of soil nutrient concentration from a hyperspectral camera to a normal spectrometer. In this paper, 164 soil samples from three regions in Qingdao, China, were collected. The spectral data of normal spectrometer and hyperspectral camera and the concentration of total carbon and nitrogen were obtained. And then, the models of soil total carbon and nitrogen content were established by using the spectral data of a normal spectrometer. The hyperspectral data were transferred by a variety of methods, such as single conventional calibration transfer algorithm, combination of multiple calibration transfer algorithms, and calibration transfer algorithm after spectral pretreatment. The transferred hyperspectral data were predicted by the total carbon and total nitrogen concentration model established by using a normal spectrometer. The absolute coefficients Rt2 and root mean square error of prediction (RMSEP) were used to evaluate the prediction performance after calibration transfer. After trying many calibration transfer methods, the prediction performance of calibration transfer by the Repfile-PDS and Repfile-SNV methods was the best. In the calibration transfer of the Repfile-PDS method, when the number of PDS windows was 27 and the number of standard data was 40, the Rt2 and the RMSEP of TC concentration were 0.627 and 2.351. When the number of PDS windows was 25 and the number of standard data was 100, the Rt2 and the RMSEP of TN concentration were 0.666 and 0.297. In the calibration transfer of the Repfile-SNV method, when the number of TC and TN standard data was 120, the Rt2 was the largest, 0.701 and 0.722, respectively, and the RMSEP was 2.880 and 0.399, respectively. After the hyperspectral data were calibration transferred by the above algorithms, they could be predicted by the soil TC and TN concentration model established by using a normal spectrometer, and better prediction results can be obtained. The solution of the calibration transfer of soil nutrient concentration from the hyperspectral camera to the normal spectrometer provides a powerful basis for rapid prediction of a large number of image information data collected by using a hyperspectral camera. It greatly reduces the workload and promotes the application of hyperspectral camera in quantitative analysis and rapid measurement technology.
Highlights
The models of soil total carbon and nitrogen content were established by using the spectral data of a normal spectrometer. e hyperspectral data were transferred by a variety of methods, such as single conventional calibration transfer algorithm, combination of multiple calibration transfer algorithms, and calibration transfer algorithm after spectral pretreatment. e transferred hyperspectral data were predicted by the total carbon and total nitrogen concentration model established by using a normal spectrometer. e absolute coefficients R2t and root mean square error of prediction (RMSEP) were used to evaluate the prediction performance after calibration transfer
After the hyperspectral data were calibration transferred by the above algorithms, they could be predicted by the soil TC and TN concentration model established by using a normal spectrometer, and better prediction results can be obtained. e solution of the calibration transfer of soil nutrient concentration from the hyperspectral camera to the normal spectrometer provides a powerful basis for rapid prediction of a large number of image information data collected by using a hyperspectral camera
The models of soil total carbon and total nitrogen concentration were established by using the spectral data of a normal spectrometer. e hyperspectral data were transferred by a variety of methods, such as single conventional calibration transfer algorithm, combination of multiple calibration transfer algorithms, and calibration transfer algorithm after spectral pretreatment. e transferred hyperspectral data were predicted by the total carbon and total nitrogen concentration model established by using the normal spectrometer. e absolute coefficients R2t and root mean square error of prediction (RMSEP) were used to evaluate the prediction performance after calibration transfer
Summary
Soil (3–5 g) was gently flattened in a homemade sample box, whose size was the same as the optical fiber probe bracket. E spectral reflectance of each soil sample was measured five times, and the average value was obtained. E hyperspectral camera was placed on a tripod, and soil samples were taken vertically (Figure 1(b)). E image of soil sample was collected by using the hyperspectral camera, and the region of interest (ROI) of the image was extracted by a rectangular figure of 100 ∗ 100 pixels size. Common spectral bands were obtained between the normal spectrometer and hyperspectral camera, a total of 169 wavelength points. Common spectral bands were obtained between the normal spectrometer and hyperspectral camera, a total of 169 wavelength points. e average spectra of all soil samples under the two instruments were plotted, and the difference was significant (Figure 2(c))
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