Use of biostimulators impacts the entire microbiota. The final resulting bacterial distribution depends on interactions between bacteria and can be illustrated through correlation. From our initial NGS data we can determine the nature of the relationships between bacteria and use these properties to accurately predict how soil microbiota changes with addition of biostimulators using machine learning.
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<div class="title_2"><p>Eveness--Shannon index</p></div> | <div class="title_2"><p>Eveness--Shannon index</p></div> | ||
− | <div class="text"> Evenness is defined as how close, in numbers, each genera of bacteria is in soil. Maintaining evenness ensures no type of bacteria grow to be too dominant, occupying niches of other potentially important bacteria. </div> | + | <div class="text"><p> Evenness is defined as how close, in numbers, each genera of bacteria is in soil. Maintaining evenness ensures no type of bacteria grow to be too dominant, occupying niches of other potentially important bacteria.</p></div> |
− | <div class="text">One way to measure evenness is by calculating the Shannon Index of a sample, as shown below: </div> | + | <div class="text"><p>One way to measure evenness is by calculating the Shannon Index of a sample, as shown below:</p></div> |
<div class="equation">$$H'=-\sum_{i=1}^{S}p_{i}lnp_i$$</div> | <div class="equation">$$H'=-\sum_{i=1}^{S}p_{i}lnp_i$$</div> | ||
<div class="table"> | <div class="table"> |
Revision as of 12:09, 28 September 2018
Overview
Original OTU Table
16s NGS uses the 16 small subunit of bacterial ribosomes to differentiate bacteria of different genera. Through this technology we obtain the bacterial distribution of our soil, summarized in the operational taxonomical unit table (OTU Table) below:
Ratio Analysis
NGS data includes several unclassified entries consisting of incomplete genomic segments that don’t represent functional bacteria. We first delete these entries, then calculate the ratios of the remaining entries to produce the following bar chart:
Spearman's Rank Correlation
To predict the final microbial distribution of soil as a result of adding biostimulators, we need to understand the interbacterial relationships that exist within the microbiome. Said relationships can be summarized by calculating a Spearman correlation coefficient using the following formula:
Symbol |
Unit |
Explanation |
---|---|---|
$\rho_s$ | - | Spearman's correlation value |
$d_i$ | - | The difference in the ranked observations from each group |
$n$ | - | The sample size |
The Spearman correlation coefficient is a value ranging from -1 to 1… [ ]
A computer program can then visualize the results in a heat map. A map of the 20 most abundant bacteria of our soil is shown below:
α Diversity Analysis
Use of biostimulators to manipulate soil factors requires careful consideration of the microbiota. Certain stimulators may cause specific genera of bacteria to become overly dominant, damaging soil integrity. As a method of monitoring the balance of the microbial ecosystem, we investigate the evenness of the soil.
Eveness--Shannon index
Evenness is defined as how close, in numbers, each genera of bacteria is in soil. Maintaining evenness ensures no type of bacteria grow to be too dominant, occupying niches of other potentially important bacteria.
One way to measure evenness is by calculating the Shannon Index of a sample, as shown below:
Symbol |
Unit |
Explanation |
---|---|---|
$H'$ | - | Shannon index |
$S$ | - | The total number of genuses in samples |
$p_i$ | - | The ratio of bacteria amount of the ith genus in the sample |
Triplicate Analysis