A brief introduction to the difference between pc and pl plotting of electronic nose data graph

This article will talk about the difference between pc and pl graphics for electronic nose data maps. Scatter slots online slots online philippines,BAY888.com The world's leading slot game platform, providing exciting gaming experience and great rewards. Join now and start your journey to victory! Don't forget to collect this site.

List of contents for this article:

• 1、How to view the electronic nose pca diagram
• 2、Can electronic nose sensor analysis not be a radar map?

How to view the electronic nose pca diagram

When observing the PCA chart, we should first review its trends and distributions as a whole to identify key components and characteristics. At the same time, PCA plots of different samples were compared to reveal differences and similarities between them. In the PCA plot, data points represent the odor characteristics of each sample. By observing the distribution of these points in the graph, we can judge the similarity and differences between different samples.

The pca diagram displays multiple data points, which represent the odor characteristics of different samples. By observing the distribution of data points in the diagram, you can understand the similarities and differences between samples. In a pca diagram, there will be components or features that dominate the diagram, and these components or features correspond to important odor characteristics.

Figure: Principal component analysis (PCA) based on electronic nose data. The blue vector is the sensor, and the dot spacing represents the gas relationship.

PCA, principal component analysis, is the most commonly used basic method in Baosheng ENOSE electronic nose software. It extracts key information by simplifying a large number of data tables. It helps us understand and analyze complex data through smaller "summary index" collections, such as production sample characteristic measurements.

Can electronic nose sensor analysis not be a radar map?

Electronic nose sensor analysis can not use radar charts at all. Histograms, line charts, principal component analysis charts and cluster analysis charts are all very mainstream and effective alternatives. After understanding the background, it is natural to turn to specific methods, which can more clearly present the inherent laws of the data and information in different dimensions.

The electronic nose can generate response data radar maps, score maps, and principal component analysis (PCA) load maps to reveal the differences in odor between different varieties of eggs.

Methanol was determined to be the best solvent for subsequent experiments. The overall aroma profile of the electronic nose analysis results: The electronic nose radar profile of the three peppers (Vietnam pepper VP, Kampot pepper KP, and Dapo pepper DP) under different extraction methods were similar, but the response intensity was significantly different. Variety differences: KP had the highest overall response value, followed by VP, and DP had the lowest. Differences in extraction methods: UE response value is the highest, SE is the second, and SD is the lowest.

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