奶牛粪便与秸秆混合发酵过程通风工艺优化

    Optimization of the ventilation technology for the mixed fermentation of cow manure and crop straw

    • 摘要: 通风是影响好氧发酵的重要技术参数,但目前对于奶牛粪便好氧发酵通风缺乏系统研究,导致发酵后物料质量参差不齐,为优化奶牛粪便好氧发酵过程中的通风参数,该研究采用响应曲面法,以通风速率、通停比、通风时间为3因素,通过中心组合试验设计方法(Box-Behnken Design)设计17组试验,以含水率和病原菌去除效率为响应值,建立回归模型并拟合。结果表明,3因素对响应值F1(含水率)的影响显著性排序为:通风速率>通风时间>通停比,对响应值F2(病原菌去除效率)的影响显著性排序为:通停比>通风速率>通风时间。综合考虑,为实现较高的病原菌去除效率,最优的通风工艺条件为通风速率为5.750 L/min,通停比为0.100,通风时间为2.119 min。该研究为奶牛粪便与秸秆混合发酵过程中的通风工艺参数优化提供参考,并为牛粪垫料开发利用提供基础支撑。

       

      Abstract: Abstract: Aerobic fermentation has been widely used to treat cow manure in recent years. The Bedding Material Recovered from Cow Manure (BMRCM) has also been applied to aerobic fermentation at present. The traditional bedding materials (sand, sandy soil, sawdust, and rice husk) are unstably supplied so far, due mainly to the market factors and the high cost. Some materials can also easily damage the fecal sewage treatment equipment in the subsequent process. Therefore, the BMRCM can serve as a low cost, less damage, and is easy to obtain. The manure produced by dairy cows can also reach hundreds of millions of tons every year in China. A large amount of cow manure needs to be treated in time and effectively, particularly for the healthy development of the dairy farming industry, and less pollution to the surrounding environment. The BMRCM can be fully utilized to reduce the economic burden of dairy farms in cow dung treatment. Aerobic fermentation can be one much more effective way to treat cow manure, compared with solid-liquid separation or direct drying in the sun. Among them, the ventilation parameters have been the most important technical indicators during aerobic fermentation. The uneven material quality after fermentation can also result in the limited popularization and application of aerobic fermentation. But, there is still lacking of the systematic research on the ventilation of cow manure in aerobic fermentation. In this study, a Box-Behnken test under the Response Surface Method (RSM) was designed to optimize the ventilation parameters in the aerobic fermentation process of cow manure. 17 experimental groups were set with three factors, including the ventilation rate, on-off time ratio, and ventilation time. The moisture content and degradation efficiency of pathogenic bacteria (Staphylococcus aureus and Klebsiella) were used as the response values to establish the regression model. The programming solution was utilized to predict the moisture content. The lowest moisture content was predicted to be 36.4%, particularly when the ventilation rate, the on-off time ratio, and the ventilation time were 11.626 L/min, 0.518, and 5.651 min, respectively. The significance of three factors on the response value F1 (moisture content) was ranked in the order of the ventilation rate > ventilation time > on-off time ratio. The maximum degradation efficiency of pathogens was predicted to be 90.4%, when the ventilation rate, the on-off time ratio, and the ventilation time were 5.750 L/min, 0.100, and 2.119 min, respectively. The significance of the response value F2 (degradation efficiency of pathogenic bacteria) was ranked in the order of the on-off time ratio > ventilation rate > ventilation time. Consequently, an optimal ventilation condition was achieved for the high degradation efficiency of pathogens, where the ventilation rate was 5.750 L/min, the on-off time ratio was 0.100, the ventilation time was 2.119 min, the maximum degradation efficiency of pathogens was 90.4%, and the moisture content was 49.44%. The material after aerobic fermentation can fully meet the requirements, where the moisture content was less than 50%. This finding can provide a strong reference to the ventilation parameters of cow manure aerobic fermentation in dairy farms, particularly for the stability and biological safety of the aerobic fermentation process. The optimization of fermentation ventilation can also greatly contribute to improving the possible BMRCM (such as cow manure and crop straw) development in dairy farms.

       

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