Dear Colleagues,
Because this is not exactly a technical question I decided to open this issue as a discussion to comply with the Research Gate rules. The purpose of this discussion is quite personal - I would like to get in touch with the researchers who work with the Biolog EcoPlate technique. I have several years of experience with the technique but still encounter difficulties analysing and interpreting the data so I need to exchange my current knowledge and to expand it further.
Sometimes not all the collected data are suitable for publication but they are important for the perception about the preciseness of the method, its advantages and disadvantages, and such information can be exchanged rather in personal communication than in the formal one. If you are interested in the topic you can send me also a personal message at [email protected]
Kind regards,
Katya Dimitrova
The Biolog Eco Plate technique is a powerful tool used for assessing the metabolic diversity and activity of microbial communities in various environmental samples. Data collection involves inoculating the Eco Plates with a sample, incubating them, and then measuring the color changes in each well to determine substrate utilization patterns. Analysis of the data typically involves calculating indices such as Shannon diversity or Simpson's evenness to quantify the overall metabolic diversity present in a sample. Additionally, principal component analysis (PCA) can be used to visualize similarities and differences between samples based on their substrate utilization profiles. Interpreting the results requires an understanding of microbial ecology principles, as changes in substrate utilization patterns may indicate shifts in community composition or ecosystem function. Overall, the Biolog Eco Plate technique provides valuable insights into the functional potential of microbial communities and allows for comprehensive ecological assessments.
Dear Mr. Manickam,
I agree with the information regarding Biolog EcoPlate. However, some of the optical density readings either as raw data or as transformed ones do not allow conducting PCA since the matrice is non-positive definite. I use SPSS and I encounter this problem very often. Since such an issue violates the rules of statistical analysis the program stops doing it and principal components cannt be extracted