玉米粮堆霉变发热过程中的温湿度场变化规律研究

    Research on temperature and humidity field change during corn bulk microbiological heating

    • 摘要: 为模拟储粮粮堆局部含水率偏高引起的霉变发热现象,进而研究此现象中温、湿度场的变化规律,该文在试验仓内湿基含水率14.0%的玉米粮堆中心加入湿基含水率18.2%的玉米,在30 ℃室内储藏40 d。试验粮堆由于霉变引起自发热。试验过程中,通过计算玉米粮堆中垂面内高温区和高湿区的面积变化,从而揭示玉米粮堆霉变发热过程中温、湿度场的变化规律。试验结果表明,粮堆中垂面高湿区面积缓慢扩大,高温区面积开始扩大缓慢,但在与周围粮温最高温差升至3.7 ℃后,面积扩大速率加快,且高温区与高湿区面积的当量半径r与温度差(T成正比,此正比关系经过了粮库浅圆仓的验证。这为进一步定量分析粮食仓储过程中的高温区和高湿区扩散提供了依据。

       

      Abstract: Abstract: Corn is widely planted in China with high yield. It is a major source of foods and materials for industrial processing. Microbiological heating occurs easily during corn bulk storage, which seriously affects grain safety. The problem has also attracted much attention. Stored grain is mostly infected by Penicillium spp. and Aspergillus spp.. Fungal growth in maize is facilitated by hot and humid conditions. Warm pockets initiated by microorganisms are mainly induced by pockets of wet grain because microorganisms need larger than 0.65 water activity to multiply and develop. It has been reported by many researchers that the relationship between temperature, moisture and fungi growth. Moisture diffusion and migration from a hotspot to its surrounding was recorded by some researchers. They also found that as a hotspot develops, the grain moisture at the top of the hotspot increases while the grain moisture below decreases. Since it is difficult to estimate the production rate of heat without using mathematical models, there are a few models developed to understand the development of hotspot. These models was used to calculate the heat production rate of stored grain. However, there is little research on the quantitative change of temperature and humidity field in space. The objective of this study was to develop a method to measure changes of high temperature and high humidity zones in space during grain microbiological heating. To explore quantitative variation of temperature and relative humidity fields in space in corn heating, different moisture corn (14.0% and 18.2%, w.b.) was stored in a simulated silo in 40 d at 30 ℃ non-airtight. The simulated silo was a cylindrical iron silo with 0.54 m in internal diameter, 0.70 m in height and 0.01 m in thickness, respectively. And its inner wall was provided with insulation layer (0.02 m thickness). Two air pipes (0.08 m internal diameter) on the top and bottom of the silo were applied to exchange the gas inside and outside the silo and ensure adequate oxygen supply. In the experiment, the high moisture corn (cylinder, diameter, 0.30 m; height, 0.30 m; 18.2%, w.b.) in the silo was surrounded by low moisture corn (14.0%, w.b.). After 4 days storage, the growth of Aspergillus candidus and Aspergillus flavus caused a hot spot appears in corn bulk. In the paper, high temperature areas were temperature higher than 30 ℃, and high humidity areas were relative humidity higher than 75% due to Aspergillus candidus and Aspergillus flavus increasing greatly. During the storage, temperature and relative humidity cloud maps of the min-vertical plane were drawn. These cloud maps indicate that areas of high temperature and high humidity expanded under heat conduction. Areas of high temperature zone and high humidity zone were calculated. Then, treated these areas as circles and calculated equivalent radii (r) of high temperature zone and high humidity zone. Besides temperature difference ((T) were equal to the highest temperature in high temperature zone minus 30 ℃. During (T increasing from 3.7 to 8 ℃, equivalent radii (r) had a significant linear correlation with temperature difference ((T). However, no noticeable change was observed when (T ranged from 0 to 3.7 ℃. The corn temperature data of a squat silo during microbiological heating proved the linear relationship between the equivalent radius of high temperature area and temperature difference. But the diffusion rate of heating area in squat silo was higher than the simulated silo due to height and span of grain bulk. Height and span of grain bulk in squat silo increased heat convection which was weak in simulated silo. This study lays a foundation for the further quantitative research on the prediction of microbiological heating in grain storage.

       

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