demonstrations of new tools for spectral data analysis ... · •foss xds •transmittance,...
TRANSCRIPT
Demonstrations of new tools for spectral data analysis & NIRS of Waters
(treated with Magnetic Fields) Bernhard Pollner, Zoltan Kovacs
Aquaphotomics: Understanding Water in the Biological Worldat the 5th Kobe University Brussels European Center Symposium
14th October 2014, Brussels, Belgium
Outline & Resume
R-Package „Aquaphotomics“
•Experiment-design, Data-Import, Data-Analysis
• Prelim. Results:• distinguish between different water species
• show effect of different magnetic treatments of water
Online „Aquagram-Maker“
•upload data to make Aquagram
•easy and fast
R-Package „Aquaphotomics“
a very brief introduction
•high level programming language•open source - freeware !• cross-platform•powerful - extendable•possible: something really new•widely used in academia
Why R-Project ?
Experiment Design
• randomize samples
• facilitates time resolved experimentsData Import
• e.g. straight from binary (.da) file
• controlled source and structure for class- and numerical variables
Data Analysis
• easy splitting and grouping of data
•parallelization of different data pre-treatments
• tools to compare those parallel results
R-Package „Aquaphotomics“
• standardized data structure
•encapsulated and „transportable“ color-coding
•nice to look at: view of NIR-data is minimized (but of course still possible)
• (regress on absTime)
Data Import
• splitting / slicing / grouping of data
• recyclable, separate data-analysis procedure file
• strict separation of calculations and plotting
• customizable parallel processing (if applicable; on UNIX)
• various methods implemented• and much more already on the „list“
Data Analysis
Data Pre-Treatment
• smoothing & derivatives, SNV, MSC, EMSC
•special Aquaphotomics data pretreatments (parallelized)
Evaluation / Analysis:
• subtractions in raw-spectra
•PCA, PLSR
•SIMCA
• (SVM, bootstrap, ...)
•Aquagram !
Data Analysis - Implemented Methods
• fully scriptable analysis routines• consisting of (user´s) custom
code, and
• easy-to-use analysis modules
• same analysis of an exact repetition of a previous experiment can so be done in a few seconds - just by plugging new data into the old (copied) analysis routine
R-Package „Aquaphotomics“
Think - Copy&Paste - Enjoy
Analysis ResultA
Analysis
ResultA
Dataset
Dataset
Preliminary Results
Spectrometer:
• FOSS XDS
• transmittance, pathlength = 1mm
•400nm - 2500nm; Δ=0.5nm
•T = 28.6ºC
•up to 5 different water species
•MilliQ as standard
•Abbreviations showing origin of water• StU: St. Ulrich
• Ob: Oberndorf
• MQ: MilliQ
•Analysis in 1st overtone of OH/water (1300-1600nm)
Different Water Species
1300 1350 1400 1450 1500 1550 1600
0.2
0.4
0.6
0.8
1.0
1.2
1.4
Fusion−AllWaters no Treatment, ProxCuv@1300−to−1600
Aquagram Spectra no treatment (not N corr.)Wavelength
avg
Abso
rban
ce
MQStUObMQs
N= 2
16, 2
54, 1
90, 4
0
3(4) Different Water Species - no Treatment
•raw spectra
no treatment
PC 1
no treatment
−0.005 0.000 0.005
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−0.0015 −0.0005 0.0005
−0.0
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000
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PC 3
no treatment
−0.0
02−0
.001
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001
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no treatment
−0.06 −0.02 0.02
−0.0
015
−0.0
005
0.00
05
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−0.002 −0.001 0.000 0.001 0.002
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PC 4
C_ConSNr ProxCuv@1300−to−1600
3(4) Different Water Species - no Treatment
PCA:
•biggest effect: consecutive scans (98.7%)
no treatment
PC 1
no treatment
−0.005 0.000 0.005
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−0.0015 −0.0005 0.0005
−0.0
6−0
.02
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no treatment
PC 4
C_waterNames ProxCuv@1300−to−1600
3(4) Different Water Species - no Treatment
PCA:
• single water species PC3: 0.127%PC4: 0.030%
1300 1350 1400 1450 1500 1550 1600
−0.1
0−0
.05
0.00
0.05
ProxCuv@1300−to−1600
no treatment PCA , bw=25 ,2 PCs for 99% var.wavelengths
Coe
ffici
ent
PC 1 (98.7022%)PC 2 (1.1061%)PC 3 (0.1269%)PC 4 (0.0303%)
1412
1362
1418
1490
13141324
1416
1509 1546 1593
1457
1362
1379
14641474
Loadings
MQ
@5
StU@
5
Ob@
5
MQ
s@5
no Treatment ProxCuv@1300−to−1600
no treatment
Inte
rcla
ss D
istan
ce
0.0
0.5
1.0
1.5
2.0
2.5
MQ StU Ob MQs
SIMCA - Interclass Distances
observe:
•MQs and MQ - same water in different containers
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12
34
5
no Treatment ProxCuv@1300−to−1600
(classic) no treatment class distance (Ob, MQs) = 2.72Ob@5
MQ
s
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SIMCA - Interclass Distances
Ob / MQs:
•nice separation
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12
34
5
no Treatment ProxCuv@1300−to−1600
(classic) no treatment class distance (StU, MQs) = 1.72StU@5
MQ
s
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SIMCA - Interclass Distances
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•nice separation
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12
34
5
no Treatment ProxCuv@1300−to−1600
(classic) no treatment class distance (MQ, MQs) = 0.61MQ@5
MQ
s
●
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MQStUObMQs
SIMCA - Interclass Distances
MQ / MQs:
• same water - different container
SIMCA - ClassificationApparent error rate 0.0371
PredictedActual MQ StU Ob MQsMQ 208 7 0 1StU 1 253 0 0Ob 0 5 185 0
MQs 12 0 0 28
50% new data - Apparent error rate 0.0657Predicted
Actual MQ StU Ob MQsMQ 107 3 0 0StU 1 127 0 0Ob 0 3 89 0
MQs 15 1 0 4
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23
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6
StU@1300−to−1600 − Validation
no treatment color by C_ExpName, N=254measured
pred
icte
d
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DZ1hSeqDZ12hDZ48h1DZ48h2
RMSECV: 0.6442R2CV: 0.856
PLSR (number of consec. scan)
St. Ulrich Water
0 1 2 3 4
0.6
0.8
1.0
1.2
1.4
1.6
StU@1300−to−1600
no treatmentNr of components
erro
r val
ue
RMSECRMSECVRMSECV_adj
1300 1350 1400 1450 1500 1550 1600
−60
−40
−20
020
40
StU@1300−to−1600
no treatment mvr regressed on Y_ConSNr , RMSECV= 0.6442 , R2CV= 0.856 , bw=25wavelengths
Coe
ffici
ent
4 comps13081316 1336
14201434
1470
14841544
155415661586
1364
1386
14521460
1478 149615091517
1530
PLSR (number of consec. scan)
Classic
Fusion−AllWaters no Treatment, ProxCuv@1300−to−1600
no treatment grouping by C_waterNames (not N corr.)
−0.29
−0.15
0
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1342
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Mode: classic
N= 216, 254, 190, 40
Fusion−AllWaters no Treatment, ProxCuv@1300−to−1600
no treatment grouping by C_waterNames (not N corr.)
−0.1
−0.05
−0.01
0.04
0.08
C01
C12
C11
C10
C09
C08
C07
C06
C05
C04
C03
C02
MQStUObMQs
Mode: aucs.dce−diffMinus: MQCalib: 26.6−30.6 deg. C. T Exp.: 28.6 deg. C
N= 216, 254, 190, 40
aucs.dce-diff
Aquagram
Fusion−AllWaters no Treatment, ProxCuv@1300−to−1600
no treatment grouping by C_waterNames (not N corr.)
−0.1
−0.05
−0.01
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0.08
C01
C12
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C10
C09
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MQStUObMQs
Mode: aucs.dce−diffMinus: MQCalib: 26.6−30.6 deg. C. T Exp.: 28.6 deg. C
N= 216, 254, 190, 40
aucs.dce-diff
Aquagram
New Aquagram Algorythm
•completely different mathematics,
• but showing high similarity with results of „classic“ code
• independent, stable scale
•unit: ºC
now possible:
• use fix-scale aquagrams in time-resolved experiments
Spectrometer:
• FOSS XDS
• transmittance, pathlength = 1mm
•400nm - 2500nm; Δ=0.5nm
•T = 28.6ºC
•2 different kinds of magnetic treatment
•MilliQ as standard
•Analysis in 1st overtone of OH/water (1300-1600nm)•Preliminary Results: as this was an industry-financed experiment, I can
not give out hardcopies of even the preliminary results before we published them — I humbly ask for your understanding. Thank you.
Effect of Magnetic Fields on Water
Online Aquagram Makerin development ...
Online Aquagram Maker
•upload own data
• compare with available data
• easy to use
• in development -- coming soon...
• http://aquaphotomics.com
Acknowledgements•Prof. Roumiana Tsenkova & Zoltan Kovacs
•Zoltan Kovacs
•George Bázár & Alexandar Slavchev
•everybody at the Biomeasurement Technology Laboratory
Thank You !