1.   Understanding Soil Health : Comparison of Competing Soil Extraction Techniques 
BIKAS K SINHA
ISI, Kolkata [Retired Professor]
&
Ex-Member, Nat’l Stat. Comm. [GoI] [
RUDS
September 13-14, 2017

2. Quote of the Day….. DISCUSS what you know Today…..
Use what you know Today AND
Figure out the rest……
Don’t wait for when you think ….you will be Ready……

3. What is Data Integration ?
Integration of Multiple Indicators
Existence of several different indicators
Desired to provide an AGGREGATE OR Over-all Measure….in an objective and statistically sound approach
Multiple Criteria Decision Making [MCDM]
Advocated by Hwang & Yoon (1981) : Multiple Attribute Decision Making : Methods & Applications : A State-of-the-Art-Survey. Springer-Verlag, Berlin

4. Reference : American Journal of Molecular Biology 2013…3….215—228
Five collaborators
Pakpour/Olishevska
Prasher/Milani/Chenier
McGill & British Columbia, Canada
Title : DNA extraction method selection
for agri. soil using…….

5. Physical & Chemical Characteristics of soil
Soil Type…Sandy with composition
sandy (92.2.%) silt (4.3%) others (3.5%)
pH…….5.5
Bulk density…… [mg.m-3]
Organic matter…..2.97%
Cation exchange capacity….
4.9 [cmol.kg-1]
Hydraulic conductivity …..
1.67 +/ [cm.d-1]

6. DNA Extraction Techniques
Commercial Kits
PowerSoil Ultraclean FastSPIN E.Z.N.A.
[each using conventional / alternative method]
Physical-Chemical Techniques
Bead-Beating Freeze-Thaw
Altogether….there are 10 different techniques
How do we compare their performances so as to arrive at an over-all ranking for ‘best’ extraction technique of Agri. Soil ? Decision Criteria ?

7. Soil Extraction : Decision Criteria
There are SEVEN (7) Decision Criteria for examining the performance of each soil extraction technique. The techniques are applied to THREE (3) different types of soil preparation…..
S :- Soil [sole]
SM :- Soil : Manure :: 99:1
SMB:- Soil : Manure : Biochar :: 98:1:1
Performance/Decision Criteria
(1) Yield [g DNA/g sample]
(2) A260/280 ratio (3) A260/230 ratio
(4) Degree of DNA Degradation [levels : 1-2-3]
(5) Easiness of Amplification [levels : 1-2-3]
(6)Duration of Extraction (7)Cost per Extraction(C$)

8. Description of experimental data
Ultraclean Conventional Method
Sample Yield A260/280ratio A260/230ratio
C C C3
Soil / / /-0.05
SM / / /-0.20
SMB / / /-0.30
Each test was repeated 5 times and the +/- values refer to the respective standard deviations
Likewise..we have data for other techniques

9. Data Matrix Ultraclean Conventional Method Sample C4 C5 C6 C7
Soil level 2 level [hrs] [CAD]
SM same
SMB same
For Bead-beating and Freeze-Thaw….C4 [Degree of DNA Degradation] could NOT be ascertained since extracted DNA was not visible on the agarose gel stained with ethidium bromide
All others……complete data set….available for all 3 types of soil preparation….

10. Nature of Decision Criteria….
C1, C2 & C3 : Higher the Better
C4, C5, C6 & C7 : Lower the Better
All criteria MUST be in the SAME ORDER
Three ways of correctly using the Data Integration Techniques :
(I) Use of C1, C2, C3; C4*, C5*, C6* & C7*
(II) Use of C1*, C2*, C3*; C4, C5, C6 & C7
(III) Thoughtful use of C’s ….as they are…..
C* : Transformed C….to ensure flow in the same direction…..

11. Step I : Data Matrix separately for 7 Decision Criteria : Sole Soil
Methods C1 C2 C3 C4 C5 C6 C7
UCC
UCA
PSC
PSA
FSC
FSA
EZNAC
EZNAA
BB & FT are left out at this stage.

12. Uniform / Weighted Integration ?
All the 7 Criteria EQUALLY Important?
Possibly NOT !
Assessment of Relative Importance….
Could be based on Expert Opinion…..
Also there are data-driven techniques…
We describe computational algorithms
below.

13. Data-driven Choice of Weights
Two methods are available….
1. Use of CV [=sd/mean] for each C….
Weight …..proportional to CV2
2. Use of Shanon’s Entropy Measure  ….
Define piJ = XiJ / i XiJ = proportion….for each Mi
P=((piJ)) = Normalized Data Matrix for each CJ
Compute for each CJ
(J) = - i piJ ln piJ / ln (m), m=# C’s
Use
w(J) = (1 - (J)) / r(1- (r)) for CJ
This is done for each type of soil preparation.

14. Normalized Decision Matrix P=((piJ)) for Computation of Weights of Criteria
Methods C1 C2 C3 C4 C5 C6 C7
UCC
UCA
PSC
PSA
FSC
FSA
EZNAC
EZNAA
Here we are dealing with Soil [Sole] prep.

15. (J) & w(J) based on –pln(p)…
Methods C1 C2 C3 C4 C5 C6 C7
UCC
UCA
PSC
PSA
FSC
FSA
EZNAC
EZNAA
(J)
w(J)

16. Choice of Weights using Entropy Measure….
Sample C1 C2 C3 C4 C5 C6 C Soil SM SMB Recall : C1: Yield [g DNA/g sample] C2: A260/280 ratio C3: A260/230 ratio C4: Degree of DNA Degradation C5: Easiness of Amplification C6: Duration of Extract. C7: Cost per Extract.

17. Averaging Technique for DI
Methods C1 C2 C3 C4* C5* C6* C7*
UCC
UCA
PSC
PSA
FSC
FSA
EZNAC
EZNAA
w(J)
Comp. of weighted average for each Meth.

18. Criticism of Averaging Technique……..
Formula uses one method at – a – time
Variation among ‘scores’ across different methods for different assessment criteria are NOT taken into account.
Criteria C1, C2, C3 and C6 show more variation in ‘within criterion scores of different methods’ …though only C1, C3 and C6 have high weights……
Needed a formula which takes account of ‘within criterion variations’…..

19. Less Known Methods…. TOPSIS METHOD ELECTRE METHOD
[computation-intensive…..]
Concepts : TOPSIS Method
Methods versus Criteria Rank Matrix….….
Ideal Method Anti-Ideal Method
Distance from Ideal and from Anti-ideal
Within C Variation …..Composite Index
TOPSIS is based on Original Data Matrix

20. TOPSIS METHOD Technique for Ordering Preferences by Similarity to Ideal Solution
Uses Concepts of
Ideal & Anti-Ideal Methods
Distance from Ideal & Anti-Ideal Methods
Weight of Evaluation Criteria
Sum of Squares for each evaluation criteria
Normalized Decision Matrix

21. Philosophy for TOPSIS
TOPSIS (Technique for Ordering Preferences by Similarity to Ideal Solution)
In the absence of a natural course of action for over-all summary measure and ranking….next best alternative course of action would be to assign top rank to the one which has shortest distance from the ideal and farthest distance from the anti-ideal…..

22. Back to the Original Data Matrix……
Methods C1 C C3 C4 C5 C6 C7
UCC
UCA
PSC
PSA
FSC
FSA
EZNAC
EZNAA
BB ND
F-T ND

23. Normalized Decision Matrix R
Methods C1 C C3 C4 C5 C6 C7
UCC
UCA
PSC
PSA
FSC
FSA
EZNAC
EZNAA
Normalization : riJ = XiJ / [i X2iJ]½
R = ((riJ )) subject to i r2iJ =1 for each J

24. Weighted Normalized Decision Matrix V
Meth. C C2 C C4 C5 C6 C7
UCC
UCA
PSC
PSA
FSC
FSA
EZNC
EZNA
V=((viJ)) where viJ = WJriJ for each (i,J)
Waive-like Pattern of V-scores across all C’s

25. Concepts : Ideal and Anti-Ideal Methods
Ideal : For each Criterion of Evaluation, Ideal Method possesses max/min viJ’s…
Anti-Ideal Method : For each Criterion of Evaluation, Anti-ideal Method possesses minimum/maximum viJ’s ……
Hypothetical Methods !!!
Setting up the Limits for others…..
Closer to Ideal : Distance from Ideal…small
AND ALSO Far from Anti-Ideal :
Distance from Anti-Ideal…Large
Distance Measures from Ideal & Anti-Ideal

26. Concepts : Ideal and Anti-Ideal Methods Soil [Sole] Sample
Ideal Score : V_max/min over all the techniques
Anti-Ideal Score: V_min/max over all the tech.
Methods C1 C2 C3 C4* C5* C6* C7*
Sum V
Vmax/min
Vmin/max
Distance of a Method from the Hyp. Ideal d+
Distance from Anti-Ideal…..d-
Euclidean Distance….Squared Distance…sq root
di+ = [J (viJ – Vmax/min)2]½ ; di- = [J (viJ – Vmin/max)2]½

27. Why Ideal and Anti-Ideal ?
Ideal : Abs. Best Method……
Anti-Ideal : Abs. Worst Method
Hypothetical Methods !!!
Setting up the Limits for others…..
Ranking of the others…..
Better - Placed States ?
Closer to Ideal : Distance from Ideal..small
AND ALSO Far from Anti-Ideal :
Distance from Anti-Ideal…Large
Hypothetical Best/Worst Methods to attain Max /Min.
Distance Measures from Ideal & Anti-Ideal Methods

28. Finally…..Composite Index….
Composite Index for ascertaining over-all Ranks of the methods…..
Ci- = di- / [ di+ + di- ]
Larger the C- - value……better is the rank.
We deduce over-all ranks of each of the methods against each of the three types of soil preparations.

29. TOPSIS Scores & Final Ranks of 8 Methods for DNA Extraction Methods for Soil [Sole Preparation]
Meth. di di Ci- Rank Ci-
UCC
UCA
PSC
PSA
FSC
FSA
EZNC
EZNA

30. TOPSIS Scores & Final Ranks of 8 Methods for DNA Extraction Methods for SM [Soil : Manure : : 99:1]
Meth. di di Ci- Rank Ci-
UCC
UCA
PSC
PSA
FSC
FSA
EZNC
EZNA

31. TOPSIS Scores & Final Ranks for DNA Extraction Methods for SMB [Soil : Manure : Biochar: 98:1:1]
Meth. di di Ci- Rank Ci-
UCC
UCA
PSC
PSA
FSC
FSA
EZNC
EZNA

32. Over-all Performance….
UltraClean Conventional…..
UltraClean Alternative….
PowerSoil Conventional…..
PowerSoil Alternative…..
These are recommended methods for DNA Extraction…..

33. That’s it !!!
The End !
Sept , 2017