鸡粪沼渣好氧堆肥颗粒尺度下氧气渗透深度表征

发布时间：2019-01-08 13:20

【摘要】：利用傅里叶变换显微红外光谱技术对鸡粪沼渣好氧堆肥颗粒尺度下氧气渗透深度进行了量化表征。用于表征鸡粪沼渣颗粒氧气渗透深度的显微红外透射光谱法的光谱采集范围为750~4 000 cm~(-1),光谱分辨率16 cm~(-1),像素点尺寸6.25μm×6.25μm,扫描次数8次。鸡粪沼渣好氧堆肥样品经冷冻干燥处理后,应采用石蜡切片技术制成12μm薄片,选取2 856 cm~(-1)和1 640 cm~(-1)代表脂肪类化合物,1 568 cm~(-1)和3 001 cm~(-1)代表芳香族化合物作为氧气渗透深度边界判定特征波长,且氧气渗透深度终点定义为差分曲线迅速下降处。鸡粪沼渣颗粒氧气渗透深度较小,介于7~20μm范围内动态变化,其符合指数关系式。研究结果表明,采用傅里叶显微红外透射光谱法判定好氧堆肥颗粒氧气渗透深度具有可行性,但应根据不同物料特性,选用适用的方法和技术参数。
[Abstract]:The depth of oxygen permeation in aerobic compost of chicken dung was quantitatively characterized by Fourier transform microinfrared spectroscopy (FTIR). The spectrum acquisition range, spectral resolution of 16 cm~ (-1), pixel size of 6.25 渭 m 脳 6.25 渭 m, scanning times 8 times, were obtained by using micro-infrared transmission spectroscopy method to characterize the oxygen permeation depth of chicken dung biogas residue. The spectral acquisition range was 750m 4 000 cm~ (-1), the spectral resolution was 16 cm~ (-1), and the pixel size was 6.25 渭 m 脳 6.25 渭 m. After freeze-drying, 12 渭 m thin pieces of chicken manure biogas residue compost should be made into 12 渭 m thin slices by paraffin section technique. 2 856 cm~ (-1) and 1 640 cm~ (-1) were selected to represent fatty compounds. 1 568 cm~ (-1) and 3 001 cm~ (-1) represent aromatic compounds as the boundary of oxygen permeation depth to determine the characteristic wavelength, and the end point of oxygen permeation depth is defined as the point where the difference curve drops rapidly. The oxygen permeation depth of chicken dung biogas particles was small, which varied dynamically in the range of 7 ~ 20 渭 m, which was in accordance with the exponential relationship. The results show that it is feasible to determine the oxygen permeation depth of aerobic compost particles by Fourier microinfrared transmission spectroscopy, but suitable methods and technical parameters should be selected according to different material characteristics.
【作者单位】：中国农业大学工学院;青海藏地堂生物科技开发有限公司;
【基金】：欧盟框架计划项目(690142) 国家国际科技合作专项(2015DFA90370) 国家重点研发计划项目(2016YFE0112800)
【分类号】：S141.4

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