CAJ | 학술논문

目的：建立起近红外光谱技术关于甜菜糖度的最佳预测模型。方法研究了Savitzky-Golay平滑处理、Savitzky-Golay导数、均值中心化、差分求导、净分析信号、去趋势校正、标准正态变量变换和多元散射校正等8种预处理方法的多方法联用处理进行光谱数据的预处理，结合光谱波段优选，建立甜菜糖度与近红外光谱的预测模型。结果在进行模型的评价时，以误差均方根(SEP)、校正标准误差(SEC)与交叉检验误差(SECV)作为评价指标。结论发现经过光谱波段优选之后，结合 Savitzky-Golay 平滑、Savitzky-Golay 导数、去趋势校正及均值中心化进行光谱数据的预处理得到的模型效果最佳。
목적：건립기근홍외광보기술관우첨채당도적최가예측모형。방법연구료Savitzky-Golay평활처리、Savitzky-Golay도수、균치중심화、차분구도、정분석신호、거추세교정、표준정태변량변환화다원산사교정등8충예처리방법적다방법련용처리진행광보수거적예처리，결합광보파단우선，건립첨채당도여근홍외광보적예측모형。결과재진행모형적평개시，이오차균방근(SEP)、교정표준오차(SEC)여교차검험오차(SECV)작위평개지표。결론발현경과광보파단우선지후，결합 Savitzky-Golay 평활、Savitzky-Golay 도수、거추세교정급균치중심화진행광보수거적예처리득도적모형효과최가。
Objective To establish the optimal forecast model of beet sugar content based on near-infrared spectroscopy. Methods Eight kinds of methods as Savitzky-Golay smoothing, Savitzky-Golay derivative, mean centering, differential derivative, net analytic signal, to the tendency calibration, standard normal variable transformations and multiplicative scatter correction were associated and combined with preferable spectral bands choice to build the beet sugar content and the near-infrared spectrum prediction model. Results SEP, SEC and SECV were set as the evaluation index when evaluating the models. Conclusion The results show after the preferred spectrum bands choice, the preprocessing that combines Savitzky-Golay smoothing, Savitzky-Golay derivative, to the trend correction and mean centering can obtain the optimal model.