藻类增殖过程中关键因子的提取与应用研究
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摘要
目前,对水体富营养化的监测多为在赤潮及水华异常暴发后,通过水域水色深度及面积进行监视,难以预报、预警,寻求一种简便易行、准确性高、成本低廉的预测预警技术,是当前水体富营养化监测技术的研发方向。本课题研究将传统的显微观测手段与计算机图像识别及分析技术相结合,用于有害藻类的识别和数量预测,为藻类水华的预测预警新技术开发提供基础参考。即通过对铜绿微囊藻增殖过程中形态、数量、光合产氧速率等关键因子的研究,提取藻类增殖过程中关键形态学和光合特征,根据已提取的特征对比藻类显微图像进行验证性试验;同时利用神经网络技术对藻类增殖情况进行拟合仿真,对其生长状况进行初步预测;并在人工围隔中诱发水华,监测水华前后藻类的增殖情况、生理生态和种群结构变化,结合现场实验结果探讨已有方法的可行性。
所得主要结论如下:
(1)铜绿微囊藻的比增殖速率和分裂率随培养时间变化,迟缓期(1-3d)、对数期(4-20d)、稳定期(21-25d)、衰老期(26-29d)的比增殖速率μ的变化规律分别为:从0.4d~(-1)猛增至1.0d~(-1)左右、在0.2到1.0d~(-1)之间波动变化、从0.1d~(-1)缓慢下降至0.0d~(-1)、稳定于0d~(-1)以下;分裂率变化也有一定规律,从30%快速上升至50%,在30%-50%之间上下浮动,在10%-15%之间波动,从15%缓慢上升到30%;藻细胞面积的变化随培养时间的增加由小→大→小→大,分别为:从35pixels迅速增大至120pixels,在80-160pixels之间波动,从60pixels逐渐上升到120pixels,均>120pixels且呈上升趋势;铜绿微囊藻处于稳定生长期时的叶绿素a含量最高9.06×10~(-8)μg/cell,其次是对数期7.89×10~(-8)μg /cell,衰老期最低为4.90×10~(-8)μg /cell。
(2)处于不同生长期的铜绿微囊藻在不同培养温度条件下具有不同的呼吸速率和光补偿点;对数期的铜绿微囊藻具有更强的低光适应性,处于同一生长期的铜绿微囊藻呼吸速率受温度影响,温度越高,呼吸速率越强;同一温度下,衰老期藻的呼吸速率显著大于其它生长期;当环境温度为20℃,处于对数期、稳定期、衰老期的铜绿微囊藻,光补偿点分别250lx、900lx、780lx,其呼吸速率分别为45、37、55μmolO2·mg~(-1)·Chl a·h~(-1),当环境温度为25℃时,光补偿点分别为380lx、720lx、480lx,呼吸速率分别为67、57、117μmolO2·mg-1·Chl a·h-1。
(3)在低光照度下,藻类消亡符合内源呼吸-藻细胞衰减模型Ma= Ma0 e-kt ;25℃时,斜生栅藻在不同低光照度0lx、200lx、500lx下的内源代谢系数K值分别为0.20、0.17、0.11d~(-1),30℃时分别为0.24、0.21、0.23d~(-1),可见,随着温度的升高K值增大,随着光照度的提高K值减小;不同藻种的K值不同,在25℃时,铜绿微囊藻、斜生栅藻和水华鱼腥藻的K值分别为0.37、0.20、0.30d~(-1)。
(4)在人工围隔内诱发铜绿微囊藻水华时若进行光限制处理,围隔内叶绿素a、DO、pH值均会发生显著变化,铜绿微囊藻群体也会显著减小。光限制前水中叶绿素a浓度、DO、pH值分别为107.1μg/L、9.7mg/L、9.1,光限制7d后显著下降为44.5μg/L、2.6 mg/L、8.0;在群体形态方面,光限制前约71.4%群体直径大于50μm,光限制7d后几乎都在50μm以下。光限制初期铜绿微囊藻群体存在逐渐上浮聚集的趋势,这与其自身的浮力调控机制有关。
(5)利用多种人工神经网络对实验室条件下的铜绿微囊藻形态特征、数量特征进行拟合仿真,并通过前4d的藻密度预测此后的铜绿微囊藻生长趋势。
Traditional eutrofication monitoring systems can not predict or previously warn harmful algal bloom (HAB) because they were based on measuring the color and area of destroyed water body, thus can only mornitoring HAB after it has occoured. Therefore, exploiting a simple, high-accuracy, low-cost prediction and warning system is a major direction of eutrophication research. In order to provide basic references for previous warning technologies, in this thesis, harmful algae identification and quantitative prediction were stutied through traditional means of microscopic observation plus computer image analysis.
The key morphological and photosynthetic characteristics were extracted through the study on the variation of morphology, number, photosynthetic oxygen production rate during proliferation of algal taxa Microcystis aeruginosa. The result was verified by comparing with algae microscopic images. Correspongdinly, neural network technology was utilized to stimulate the algal proliferation. In addition, in order to verify the feasibility of this method, the proliferation of algae as well as the changes of algae spicies and physiological ecology characteristics before and after the water bloom were monitored in artificial enclosure with M. aeruginosa bloom. The main conclusions are shown as follows:
(1) There are four phases during M. aeruginosa proliferation: lag period (1-3d), logarithmic growth period (4-20d), stabilization period (21-25d), aging period (26-29d). Specific growth rateμof the four proliferation phases were increasing rapidly in 0.4-1.0d~(-1), stability changes in 0.2-1.0d~(-1), a declining trend in 0.0-0.1d~(-1), little change in almost <0d~(-1), respectively. Division rates of the four proliferation phases were increasing rapidly in 30%-50%, changes unsteadily in 30%-50%, stability changes in 10%-15%, increased trend slightly in 15%-30%, respectively. Cells areas were increasing rapidly in 35-120 pixels, stability changes in 80-160pixels, increasing slightly in 60-120pixels, increased trend in almost >120pixels, respectively. Chla concentration of M. aeruginosa at logarithmic growth period, stabilization period and aging period were 7.89×10-8, 9.06×10-8 and 4.90×10-8μg/cell, respectively.
(2) Different respiration rates and light compensation point in different proliferation phases. M. aeruginosa at logarithmic growth period has stronger low-light adaptability than others. At the same period, the higher temperature, respiration rates are stronger. At the same temperature, respiration rates are highest at aging period. The respiration rates at logarithmic growth period, stabilization period and aging period were 45、37、55μmolO_2·mg~(-1)·Chl a·h~(-1) respectively under 20℃and 67、57、117μmolO_2·mg~(-1)·Chl a·h~(-1) respectively under 25℃.The light compensation point were 250、900、780lx respectively under 20℃and 380、720、480lx respectively under 25℃.
(3) Endogenous metabolic factor K of Scenedesmus obliquus are different under different temperature: temperature increases, K-value increases and light intensity increase, K-value decreases. The K-value at 0、200、500lx is 0.20、0.17、0.11d~(-1) respectively under 20℃and 0.24、0.21、 0.23d~(-1) respectively under 25℃. Different K-value in different algae species. The K-value of Microcystis aeruginosa, Scenedesmus obliquus and Auabaena Flosaquae were respectively 0.37、0.20、0.30d~(-1).
(4) After Microcystis aeruginosa bloom was induced in artificial enclosure, the light shading material was covered on the surface and the variation of chlorophyll a contents, pH and DO were analyzed. Chlorophyll a, DO and pH declined from 107.1μg/L, 9.7mg/L and 9.1 to 44.5μg/L, 2.6 mg/L and 8.0 respectively. Meanwhile, microcystis colony's radius decreased obviously, from 70% larger than 50μm to less than 50μm. It was shown that microcystis colonies floated upward to the water surface in light shading by means of monitoring Chlorophyll a contents at different water depths,. The buoyancy control mechanism of Microcystis aeruginosa may explain this phenomenon.
(5) Succeed in predicting the growth trend of Microcystis aeruginosa proliferation by simulating morphological characteristics and growth curve using kinds of neural network models.
所得主要结论如下:
(1)铜绿微囊藻的比增殖速率和分裂率随培养时间变化,迟缓期(1-3d)、对数期(4-20d)、稳定期(21-25d)、衰老期(26-29d)的比增殖速率μ的变化规律分别为:从0.4d~(-1)猛增至1.0d~(-1)左右、在0.2到1.0d~(-1)之间波动变化、从0.1d~(-1)缓慢下降至0.0d~(-1)、稳定于0d~(-1)以下;分裂率变化也有一定规律,从30%快速上升至50%,在30%-50%之间上下浮动,在10%-15%之间波动,从15%缓慢上升到30%;藻细胞面积的变化随培养时间的增加由小→大→小→大,分别为:从35pixels迅速增大至120pixels,在80-160pixels之间波动,从60pixels逐渐上升到120pixels,均>120pixels且呈上升趋势;铜绿微囊藻处于稳定生长期时的叶绿素a含量最高9.06×10~(-8)μg/cell,其次是对数期7.89×10~(-8)μg /cell,衰老期最低为4.90×10~(-8)μg /cell。
(2)处于不同生长期的铜绿微囊藻在不同培养温度条件下具有不同的呼吸速率和光补偿点;对数期的铜绿微囊藻具有更强的低光适应性,处于同一生长期的铜绿微囊藻呼吸速率受温度影响,温度越高,呼吸速率越强;同一温度下,衰老期藻的呼吸速率显著大于其它生长期;当环境温度为20℃,处于对数期、稳定期、衰老期的铜绿微囊藻,光补偿点分别250lx、900lx、780lx,其呼吸速率分别为45、37、55μmolO2·mg~(-1)·Chl a·h~(-1),当环境温度为25℃时,光补偿点分别为380lx、720lx、480lx,呼吸速率分别为67、57、117μmolO2·mg-1·Chl a·h-1。
(3)在低光照度下,藻类消亡符合内源呼吸-藻细胞衰减模型Ma= Ma0 e-kt ;25℃时,斜生栅藻在不同低光照度0lx、200lx、500lx下的内源代谢系数K值分别为0.20、0.17、0.11d~(-1),30℃时分别为0.24、0.21、0.23d~(-1),可见,随着温度的升高K值增大,随着光照度的提高K值减小;不同藻种的K值不同,在25℃时,铜绿微囊藻、斜生栅藻和水华鱼腥藻的K值分别为0.37、0.20、0.30d~(-1)。
(4)在人工围隔内诱发铜绿微囊藻水华时若进行光限制处理,围隔内叶绿素a、DO、pH值均会发生显著变化,铜绿微囊藻群体也会显著减小。光限制前水中叶绿素a浓度、DO、pH值分别为107.1μg/L、9.7mg/L、9.1,光限制7d后显著下降为44.5μg/L、2.6 mg/L、8.0;在群体形态方面,光限制前约71.4%群体直径大于50μm,光限制7d后几乎都在50μm以下。光限制初期铜绿微囊藻群体存在逐渐上浮聚集的趋势,这与其自身的浮力调控机制有关。
(5)利用多种人工神经网络对实验室条件下的铜绿微囊藻形态特征、数量特征进行拟合仿真,并通过前4d的藻密度预测此后的铜绿微囊藻生长趋势。
Traditional eutrofication monitoring systems can not predict or previously warn harmful algal bloom (HAB) because they were based on measuring the color and area of destroyed water body, thus can only mornitoring HAB after it has occoured. Therefore, exploiting a simple, high-accuracy, low-cost prediction and warning system is a major direction of eutrophication research. In order to provide basic references for previous warning technologies, in this thesis, harmful algae identification and quantitative prediction were stutied through traditional means of microscopic observation plus computer image analysis.
The key morphological and photosynthetic characteristics were extracted through the study on the variation of morphology, number, photosynthetic oxygen production rate during proliferation of algal taxa Microcystis aeruginosa. The result was verified by comparing with algae microscopic images. Correspongdinly, neural network technology was utilized to stimulate the algal proliferation. In addition, in order to verify the feasibility of this method, the proliferation of algae as well as the changes of algae spicies and physiological ecology characteristics before and after the water bloom were monitored in artificial enclosure with M. aeruginosa bloom. The main conclusions are shown as follows:
(1) There are four phases during M. aeruginosa proliferation: lag period (1-3d), logarithmic growth period (4-20d), stabilization period (21-25d), aging period (26-29d). Specific growth rateμof the four proliferation phases were increasing rapidly in 0.4-1.0d~(-1), stability changes in 0.2-1.0d~(-1), a declining trend in 0.0-0.1d~(-1), little change in almost <0d~(-1), respectively. Division rates of the four proliferation phases were increasing rapidly in 30%-50%, changes unsteadily in 30%-50%, stability changes in 10%-15%, increased trend slightly in 15%-30%, respectively. Cells areas were increasing rapidly in 35-120 pixels, stability changes in 80-160pixels, increasing slightly in 60-120pixels, increased trend in almost >120pixels, respectively. Chla concentration of M. aeruginosa at logarithmic growth period, stabilization period and aging period were 7.89×10-8, 9.06×10-8 and 4.90×10-8μg/cell, respectively.
(2) Different respiration rates and light compensation point in different proliferation phases. M. aeruginosa at logarithmic growth period has stronger low-light adaptability than others. At the same period, the higher temperature, respiration rates are stronger. At the same temperature, respiration rates are highest at aging period. The respiration rates at logarithmic growth period, stabilization period and aging period were 45、37、55μmolO_2·mg~(-1)·Chl a·h~(-1) respectively under 20℃and 67、57、117μmolO_2·mg~(-1)·Chl a·h~(-1) respectively under 25℃.The light compensation point were 250、900、780lx respectively under 20℃and 380、720、480lx respectively under 25℃.
(3) Endogenous metabolic factor K of Scenedesmus obliquus are different under different temperature: temperature increases, K-value increases and light intensity increase, K-value decreases. The K-value at 0、200、500lx is 0.20、0.17、0.11d~(-1) respectively under 20℃and 0.24、0.21、 0.23d~(-1) respectively under 25℃. Different K-value in different algae species. The K-value of Microcystis aeruginosa, Scenedesmus obliquus and Auabaena Flosaquae were respectively 0.37、0.20、0.30d~(-1).
(4) After Microcystis aeruginosa bloom was induced in artificial enclosure, the light shading material was covered on the surface and the variation of chlorophyll a contents, pH and DO were analyzed. Chlorophyll a, DO and pH declined from 107.1μg/L, 9.7mg/L and 9.1 to 44.5μg/L, 2.6 mg/L and 8.0 respectively. Meanwhile, microcystis colony's radius decreased obviously, from 70% larger than 50μm to less than 50μm. It was shown that microcystis colonies floated upward to the water surface in light shading by means of monitoring Chlorophyll a contents at different water depths,. The buoyancy control mechanism of Microcystis aeruginosa may explain this phenomenon.
(5) Succeed in predicting the growth trend of Microcystis aeruginosa proliferation by simulating morphological characteristics and growth curve using kinds of neural network models.
引文
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