Difference between revisions of "Team:ZJU-China/Model/Coculture"
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| + | <h1 id="coculture" class="page-header ArticleHead GreenAH">Model: Coculture</h1> | ||
| − | + | <h2 id="bg" class="H2Head">Background</h2> | |
| + | <p class="PP">In our project, <em>Phytophthora nicotianae</em> and <em>Trichoderma</em> played important roles, and confrontation is a widely used method. To better understanding the system behind it, we modeled the growth of <em>Phytophthora nicotianae</em> and <em>Trichoderma</em>.</p> | ||
| + | <p class="PP">There are some candidates for the indicator of growth: the biomass and area.</p> | ||
| + | <p class="PP">Measure the biomass- it’s hard to weigh the <em>Trichoderma</em> without taking the water into count, and the <em>Trichoderma</em> would die when being taken out to weigh, so considering these effects, we analyzed the area instead.</p> | ||
| + | <p class="PP">Calculating the area- taking picture is a good choice since it won’t harm the microorganism in the culture dish. To deal with the large amount of pictures, we involved image processing.</p> | ||
| + | <h2 id="hypothesis" class="H2Head">Hypothesis </h2> | ||
| + | <p class="PP">The circumstance may influence the result of area, so there are some irrelevant variables to control, like the distance from camera to culture dish, the light intense around when the photos were taken. We set the measure equipment under a stable condition, so that the influence of irrelevant factors were lowered as much as possible.</p> | ||
| − | < | + | <h2 id="methond" class="H2Head">Method</h2> |
| − | < | + | <p class="PP">We used the MATLAB to deal with the image processing.</p> |
| − | < | + | <p class="PP">The camera was set to take one picture every 30 minutes. Successive differential method was used to narrow the error.</p> |
| − | < | + | <div class="imgdiv"><img class="textimg" src="https://static.igem.org/mediawiki/2017/a/a9/ZJU_China_Coculture_f1.png"></div> |
| + | <br/><br/> | ||
| − | < | + | <div class="imgdiv col-md-4 col-sm-4"><img class="textimg" style="height: 35% !important; width: auto !important;" src="https://static.igem.org/mediawiki/2017/4/4f/ZJU_China_Coculture_1.1.jpg"></div> |
| − | + | <div class="imgdiv col-md-4 col-sm-4"><img class="textimg" style="height: 35% !important; width: auto !important;" src="https://static.igem.org/mediawiki/2017/7/70/ZJU_China_Coculture_1.2.jpg"></div> | |
| − | + | <div class="imgdiv col-md-4 col-sm-4"><img class="textimg" style="height: 35% !important; width: auto !important;" src="https://static.igem.org/mediawiki/2017/0/0b/ZJU_China_Coculture_1.3.jpg"></div> | |
| − | + | <p class="capture">Fig.1 One of the "subtracted" photo of the culture dish, the white area shows new grown <em>Trichoderma</em>.</p> | |
| − | + | ||
| − | + | ||
| − | + | ||
| − | </p> | + | |
| − | + | <p class="">The process is as follows:</p> | |
| − | + | <br/><br/> | |
| − | + | <div class="imgdiv"><img style="width: 100% !important;" class="textimg" src="https://static.igem.org/mediawiki/2017/4/40/ZJU_China_Coculture_f2.png"></div> | |
| − | + | <br/><br/> | |
| − | < | + | <p class="PP">So from the pictures we got the growth curve.</p> |
| − | < | + | |
| − | </ | + | |
| − | < | + | <h2 id="result" class="H2Head">Result</h2> |
| − | + | <div class="imgdiv"><img class="textimg" src="https://static.igem.org/mediawiki/2017/8/8a/ZJU_China_Coculture_2.png"></div> | |
| − | < | + | <p class="capture">As it's shown above, the <em>Trichoderma</em> showed an almost steady growing speed when under plenty nutrition.</p> |
| − | < | + | |
| − | </ | + | |
| − | < | + | <h2 id="summary" class="H2Head">Summary</h2> |
| − | + | <p class="">We involved image processing in our model and successfully got the growth curve of <em>Trichoderma</em>. For further study, better algorithm should be applied to deal with the changing light dense and other disturbance.</p> | |
| − | < | + | |
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| − | <li><a href="#"> | + | <li><a href="#introduction">Introduction</a></li> |
| − | <li> | + | <li><a href="#bg">Background</a></li> |
| − | + | <li><a href="#hypothesis">Hypothesis</a></li> | |
| − | + | <li><a href="#methon">Methond</a></li> | |
| − | + | <li><a href="#result">Result</a></li> | |
| − | + | <li><a href="#summary">Summary</a></li> | |
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Revision as of 11:39, 30 October 2017
Model: Coculture
Background
In our project, Phytophthora nicotianae and Trichoderma played important roles, and confrontation is a widely used method. To better understanding the system behind it, we modeled the growth of Phytophthora nicotianae and Trichoderma.
There are some candidates for the indicator of growth: the biomass and area.
Measure the biomass- it’s hard to weigh the Trichoderma without taking the water into count, and the Trichoderma would die when being taken out to weigh, so considering these effects, we analyzed the area instead.
Calculating the area- taking picture is a good choice since it won’t harm the microorganism in the culture dish. To deal with the large amount of pictures, we involved image processing.
Hypothesis
The circumstance may influence the result of area, so there are some irrelevant variables to control, like the distance from camera to culture dish, the light intense around when the photos were taken. We set the measure equipment under a stable condition, so that the influence of irrelevant factors were lowered as much as possible.
Method
We used the MATLAB to deal with the image processing.
The camera was set to take one picture every 30 minutes. Successive differential method was used to narrow the error.
Fig.1 One of the "subtracted" photo of the culture dish, the white area shows new grown Trichoderma.
The process is as follows:
So from the pictures we got the growth curve.
Result
As it's shown above, the Trichoderma showed an almost steady growing speed when under plenty nutrition.
Summary
We involved image processing in our model and successfully got the growth curve of Trichoderma. For further study, better algorithm should be applied to deal with the changing light dense and other disturbance.
