Difference between revisions of "Team:FAFU-CHINA/Model"

Revision as of 08:15, 1 November 2017

Model

Overview

In soil environment, heavy metal pollution is the most common, which directly affects the health and safety of soil, and can be harmful to human body when serious. To solve the soil problem of heavy metal pollution, our team constructed a combination of heavy metal plants to repair soil. The environment of the soil is complex and changeable, and the control is weak. The influence of the treatment of heavy metal in soil and the influence of the growth condition and the external environment. Therefore, we will analyze the factors influencing the phosphorous bacteria in soil, and use the response surface optimization method to explore the optimal combination, optimal conditions and optimal results.

Design

Mainly through software Design-Expert to realize optimization. The Box-Behnken experiment not only has a better effect. And the number of trials required is limited. Therefore, we adopt Box-Behnken experiment to optimize the adsorption process of heavy metal lead soil for PSB. Select the adsorption efficiency as the response value. The temperature, water and pH were selected as the influencing factors. The influence factors of PSB adsorption process are further discussed and studied. Get the best solution.

Analysis of data

In this paper, the factors that affect the lead pollution in soil are studied and discussed in order to obtain the best solution. The influence factors of single factor test design were determined and the adsorption efficiency of lead in soil was selected. The following is a comparison of the actual value and the predicted value. It can be seen from the figure. The result is a good prediction of the actual soil conditions.

Results

In order to improve the fixed efficiency of lead pollution, the response surface design method was adopted to optimize the fixed efficiency of soil. Firstly, the influences of several major factors in the environment, namely temperature, moisture content and pH. The three factors influencing single factor test were determined, and the optimal value of the interval was determined. The temperature, water and pH were selected as the influencing factors. Then the test scheme of the design of the software was designed. The temperature, water and pH were selected as the influencing factors. We use A as Temperature: B as pH: and C as Wet. The multivariate quadratic regression equation is obtained by experimental results.

Y=64.60940-0.15806*A-19.32045*B-1.01190C-0.022775AB-0.033681AC+0.14524BC+0.010591*A^2+1.65465*B^2+0.082157*C^2

In the optimal conditions:

RSM 3D surface figure(The values of C is 3.07)

Analyze the results. The optimal soil conditions are: the water content is 3.07g/kg , the temperature is 23.88 degrees Celsius, and The pH is 6.98.The maximum Adsorption efficiency can be achieved.55.09 %

We hope that this model can guide the control of soil conditions in phosphate-solubilizing bacteria(psb). Let the phosphate-solubilizing bacteria(psb) grow better and promote Phytoremediation process. To achieve the best effect of soil heavy metal treatment.

The growth curve model of PSB

The pollution of heavy metals in soil is a major problem of environmental sanitation in the world. The governance process faces many difficulties. Phytoremediation is a promising technology because it does not cause secondary pollution and low cost. However, the growth process of these plants are typically inhibited by high concentrations of heavy metals, It causes slow growth of plants and decelerates the phytoextraction process. Therefore, our team engineer a class of phosphate-solubilizing bacteria (PSB) to reduce the concentration of heavy metal ions in the soil. It also accelerates the growth of plants and repairs soil. Faced with severe heavy metal pollution, the environment of soil is complex and diverse. Be familiar with the growth condition of the PSB. It becomes very important. In order to better understand the growth condition of phosphate-solubilizing bacteria (PSB), we adopted the classic Gompertz model. The following is the fitting effect diagram of growth curve

The growth curve model of PSB

y: the absorance in the OD ₆₀₀

t: time/hour

A; B; k; : undetermined coefficient

A model of the growth curve of phosphorus was developed by using the classic Gompertz model. In the chart, it can be seen that there is a delay in 5 hours, and a logarithmic growth phase from 10 to 35 hours, This stage’s bacterial strains is used as the experimental materialsthen stable period occur from 30 to 85 hours, after 85 hours is a degenerating period. In this point, the spores are ripe .Begin the preservation of the fungus seeds.

Master the growth rule of PSB. It has important guiding significance to study PSB physiology and production practice. In order to facilitate the future cooperation with fertilizers and other ways to repair soil environment

Refernce

[1]Cao T J. Least Square Estimation of Parameters in Few Growth Model and Its Application[J]. Journal of Civil Aviation University of China, 2011.

[2]朱珉仁. Gompertz模型和Logistic模型的拟合[J]. 数学的实践与认识, 2002, 32(5):705-709.

[3]叶常明. 农药在土壤中归趋模型的研究进展[J]. 环境化学, 2005, 24(1):1-6.

[4]王新武. 植物生长的微分方程模型[J]. 兰州工业学院学报, 2012, 19(6):59-62.

[5]董立萍. 解磷菌修复土壤铅污染效应优化及机理探索[D]. 西北大学, 2014.

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+		<p style="font-size: 9px ;"><b>Refernce</b></p>
+		<p style="font-size: 9px ;">[1]Cao T J. Least Square Estimation of Parameters in Few Growth Model and Its Application[J]. Journal of Civil Aviation University of China, 2011.</p>
+<p style="font-size: 9px ;"> [2]朱珉仁. Gompertz模型和Logistic模型的拟合[J]. 数学的实践与认识, 2002, 32(5):705-709. </p>
+<p style="font-size: 9px ;"> [3]叶常明. 农药在土壤中归趋模型的研究进展[J]. 环境化学, 2005, 24(1):1-6. </p>
+<p style="font-size: 9px ;"> [4]王新武. 植物生长的微分方程模型[J]. 兰州工业学院学报, 2012, 19(6):59-62. </p>
+<p style="font-size: 9px ;"> [5]董立萍. 解磷菌修复土壤铅污染效应优化及机理探索[D]. 西北大学, 2014. </p>
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