In order to dynamically analyze the content of organic matter during the composting process in real time,tofu residue was used as the substrate supplemented with fully fermented kitchen waste powder for mixed aerobic composting.The near-infrared spectral data for composting samples were collected at different treatment stages.The original spectra were pretreated by a normalization method,a first-order differential method and a second-order differential method.Backward interval partial least squares(biPLS),synergy interval partial least squares(siPLS)and interval partial least squares(iPLS)were used to construct quantitative analysis models of the near-infrared spectral absorbance and organic matter content.The results show that the model established using the second-order differential pretreatment method combined with iPLS has the best performance.The best characteris-tic band corresponding to the 23rd sub-interval was 5 832-6 086 cm-1,the correlation coefficient of the calibration set(Rc)was 0.986 1,the root mean square error of cross-validation(RMSECV)was 0.824 7,the correlation coef-ficient of the prediction set(Rp)was 0.964 7,the root mean square error(RMSEP)was 0.445 7,and the relative predictive deviation(RPD)was 3.8.The results show that the established model has good stability and reliability.The second-order differential pretreatment method combined with iPLS can effectively optimize the spectral model-ing area,improve the prediction ability of the model,and realize the rapid determination of the organic matter con-tent in compost samples.
关键词
豆腐渣/堆肥有机质/近红外光谱/偏最小二乘法/定量分析模型
Key words
tofu residue/compost organic matter/near-infrared spectroscopy/partial least squares method/quan-titative analysis model
维普
万方数据