análisis del espectro infrarrojo por componentes principales

English translation: Principal component analysis of infrared spectra

21:42 Oct 10, 2019
Spanish to English translations [PRO]
Science - Chemistry; Chem Sci/Eng
Spanish term or phrase: análisis del espectro infrarrojo por componentes principales
El análisis del espectro infrarrojo por componentes principales mostró que al realizar la normalización por área de la información se obtuvo la discriminación de las muestras con una explicación del 84% de la varianza; los defectos de café con las muestras de café comercial molido se separaron del café de alta calidad y el café instantáneo. Mediante los descriptores químicos obtenidos del espectro infrarrojo se logró diferenciar las muestras de café de alta calidad, comercial e instantáneo
pistacho
Colombia
English translation:Principal component analysis of infrared spectra
Explanation:
As an abstract, functional description; Principal component analysis (PCA) is a statistical technique which aims to minimise the number of variables to describe the data set by taking advantage of correlations in the data. Eg if you have intensities for A, B and C, but A+B are correlated, you will get (A+B) as one of your principal components (PCs). This means you can now describe the data with two variables (PCs); (A+B) and C.

The idea is then to use these to separate different classes of sample (e.g. the different types of coffee). Say, group 1 is high in (A+B) and low in C, group 2 has high (A+B) and high C, and group 3 has low (A+B) and high C

By finding a minimum number of variables to describe as much of the data as possible, it becomes easier to spot the trends.

I’m not sure how easily you will understand the Wikipedia page, it is a little heavy on the maths, but I’m not convinced it (or I) explain the conceptul background well enough.

https://en.m.wikipedia.org/wiki/Principal_component_analysis
Selected response from:

John Druce
Spain
Local time: 19:47
Grading comment
thank you!
4 KudoZ points were awarded for this answer



Summary of answers provided
4 +3Principal component analysis of infrared spectra
John Druce
3 -1main components of infrared spectral analysis
Juan Arturo Blackmore Zerón


  

Answers


24 mins   confidence: Answerer confidence 3/5Answerer confidence 3/5 peer agreement (net): -1
main components of infrared spectral analysis


Explanation:
https://en.wikipedia.org/wiki/Infrared_spectroscopy

Juan Arturo Blackmore Zerón
Mexico
Local time: 13:47
Native speaker of: Spanish

Peer comments on this answer (and responses from the answerer)
disagree  Neil Ashby: It's "infrared spectroscopy", not "infrared spectral analysis". Secondly, the word order is wrong, giving the wrong meaning.
11 hrs
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1 hr   confidence: Answerer confidence 4/5Answerer confidence 4/5 peer agreement (net): +3
Principal component analysis of infrared spectra


Explanation:
As an abstract, functional description; Principal component analysis (PCA) is a statistical technique which aims to minimise the number of variables to describe the data set by taking advantage of correlations in the data. Eg if you have intensities for A, B and C, but A+B are correlated, you will get (A+B) as one of your principal components (PCs). This means you can now describe the data with two variables (PCs); (A+B) and C.

The idea is then to use these to separate different classes of sample (e.g. the different types of coffee). Say, group 1 is high in (A+B) and low in C, group 2 has high (A+B) and high C, and group 3 has low (A+B) and high C

By finding a minimum number of variables to describe as much of the data as possible, it becomes easier to spot the trends.

I’m not sure how easily you will understand the Wikipedia page, it is a little heavy on the maths, but I’m not convinced it (or I) explain the conceptul background well enough.

https://en.m.wikipedia.org/wiki/Principal_component_analysis

John Druce
Spain
Local time: 19:47
Specializes in field
Native speaker of: English
PRO pts in category: 8
Grading comment
thank you!

Peer comments on this answer (and responses from the answerer)
agree  Thomas Walker
7 hrs
  -> Thanks, Tom

agree  Neil Ashby
10 hrs
  -> Thanks, Neil

agree  neilmac: I was thinking "...BY infrared spectra" ...but hey!... no biggie... :)
16 hrs
  -> Thanks for the suggestion, Neil. I would still go with "OF", because PCA determines the (statistical) PCs that describe the data set of IR spectra, not, say the principal (chemical) components of the samples
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