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豆腐渣堆肥过程中的多维光谱解析与建模
引用本文:苏云,李卫华.豆腐渣堆肥过程中的多维光谱解析与建模[J].科学技术与工程,2024,24(1):439-446.
作者姓名:苏云  李卫华
作者单位:安徽建筑大学
基金项目:安徽省高校省级自然科学研究重点项目(2022AH050258);国家自然科学(51978003);安徽省教育厅创新团队项目(2022AH010019);安徽省自然科学(2008085QE264);安徽建筑大学引进人才及博士启动(2019QDZ10)
摘    要:以豆腐渣为底物进行混合好氧堆肥,采用三维荧光光谱(3D-EEMs)分析了堆肥产物淋溶上清液DOM的组成,运用傅里叶红外光谱(FTIR)技术解析了堆肥样品中官能团信息。利用三维荧光结合平行因子法研究了堆肥过程中DOM的动态变化过程,分析得出两种组分即可见区类色氨酸(Ex/Em=285 nm/350 nm)与类腐殖酸(Ex/Em=335 nm/415 nm),随着堆肥的不断进行,可见区类色氨酸荧光强度逐渐下降,类腐殖酸荧光强度逐渐上升,表明堆肥进入腐熟阶段。傅里叶红外光谱分析表明堆肥过程中多糖类小分子物质逐渐减少,而腐殖酸类大分子物质逐渐增加。进一步运用近红外光谱(NIRS)和区间偏最小二乘法等化学计量学方法构建了堆肥过程有机质含量分析预测模型,结果表明,优化选择区间5831.95~6086.52 cm-1可以建立稳健的有机质定量分析模型,堆肥有机质实测值与近红外预测值的相关系数(R)为0.9861、交叉验证均方差(RMSECV)为0.8247、偏差(Bias)为0.005,表明堆肥有机质含量与近红外光谱具有较好的相关性。

关 键 词:豆腐渣  堆肥  三维荧光光谱  傅里叶红外光谱  近红外光谱
收稿时间:2023/3/22 0:00:00
修稿时间:2023/12/19 0:00:00

Multidimensional spectral analysis and modeling in the composting process of tofu residue
Su Yun,Li Weihua.Multidimensional spectral analysis and modeling in the composting process of tofu residue[J].Science Technology and Engineering,2024,24(1):439-446.
Authors:Su Yun  Li Weihua
Institution:Anhui Jianzhu University
Abstract:Mixed aerobic composting with tofu residue as substrate, the composition of DOM on the leaching solution of composting products was analyzed, using the 3-D excitation-emission fluorescence spectra (3D-EEMs).Fourier infrared spectroscopy (FTIR) was used to analyze functional group information in compost samples. The dynamic change of DOM in composting process was studied by three-dimensional fluorescence combined with PARAFAC, which showed that visible tryptophan (Ex/Em=285 nm/350 nm) and humic acid (Ex/Em=335 nm/415 nm) were detected. As the composting process continues, the fluorescence intensity of tryptophan gradually decreases, and the fluorescence intensity of humic acid gradually increases, indicating that the compost is in the stage of rot ripening. It shows that the polysaccharide small molecules gradually decrease, while the humus macromolecules increase gradually using Fourier infrared spectroscopy approach. Furthermore, the stoichiometry methods such as near-infrared spectroscopy (NIRS) and interval partial least squares method were used to construct a prediction model for organic matter content analysis in the composting process. The results show that the optimal selection interval is 5831.95~6086.52 cm-1. Robust quantitative organic matter analysis models can be developed. The correlation coefficient (R) is 0.9861 between the measured values of compost organic matter and the predicted value with NIR spectra. The cross-verified mean square deviation (RMSECV) is 0.8247, and the deviation (Bias) is 0.005, which shows a good correlation between the concentration of compost organic matter and NIR spectra.
Keywords:tofu dregs  aerobic composting  3D-EEMs  FTIR  NIRS
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