Chemometric soil analysis
from north of Sweden
*UPDATED 2018-12-07*

TABLE OF CONTENTS
Introduction
Data-set
Plant nutrition series
Explaination of Rxy vs pKs
Formulas related to theory
Hydroxides
Sulfides
Sulfates
Carbonates
Chromates
Phosphates
Silica
Distribution phenomena
Nutrition along height-curve
Secondary nutrition-effect
Secondary mobilizing ions
Practical experiment QED
VIDEO summary
e-mail author



I have through chemometric analysis of soil samples from north of Sweden found several interesting phenomena where elements that form less soluble compunds outcompete more soluble compounds. This cause a characteristic gain in plant-nutrition and transport of ions down the height-curve.

Dear Reader !

In the late summer of year 2000 I travelled along the coastline of northern Sweden and along six rivers inlands, measuring pH in river-water and plant-nutrition in soil at 20 km intervals. This resulted in 28 test-spots and I complemented with data of 20 elements analysed by SLU "MarkInfo" for each test-spot. The data early in statistical analysis divided into two groups, one that had tendency to increase downhill and the other staying uphill, by further analysis it shows that these effects can be explained by the theory of Competitive Solving and Crystallization, where the ions compete in forming hard to solve compounds in deficiency of an-ions as Sulfide, Sulfate and Carbonate. Hard to solve compounds also seems to be inhibiting Sulfide oxidation to Sulfate (affects river pH) and cause an interesting secondary release of plant nutrition by elements as Lead, Zinc, Zirconium, Titanium, Barium and Silica which form hard to solve compounds with a selection of Sulfide, Sulfate, Carbonate and Phosphate causing deficiency of an-ions for easy to solve plant-nutritious ions and thus cause release of nutrients and transport of ions downhill. The project is now in progress to optimize the proportions between solving and crystallization in order to maintain long term plant nutrition.

This first diagram shows how easily dissolved compounds maintain available and mobile, and how hard to dissolve compounds rarely interact in solution. The white field represents the time of the compound in water solution, and the black field represents time of the compound as solid.



If You find this theory interesting so please contact Me !

Best regards
Joakim Forssman

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Data-set parameters



The database consists of 28 measure-spots with 23 variables each.
The program used for comparing the data, I developed myself and is called "pHgraf" and it has functions for linear regression and overview of the dataset.

Parameters that I collected the summer of year 2000, travelling along six rivers in the north of Sweden.

PictureImage of every measure-spot
pHAcidity in river-water at every measure-spot
NutritionPlant nutrition at every measure-spot
Distance [km]Distance from river outlet in kilometers

The nutrition parameter is botanically defined in four classes (depending what plants grow at measure-spot)
Concentration of substances in soil collected from SLU (Swedish agricultural university) "MarkInfo" service.
Al2O3 [%]Ba [ppm]
P2O5 [%]Pb [ppm]
Fe2O3 [%]Cu [ppm]
CaO [%]Cr [ppm]
K2O [%]Mo [ppm]
SiO2 [%]Ni [ppm]
MgO [%]Sr [ppm]
MnO [%]V [ppm]
Na2O [%]Zn [ppm]
TiO2 [%]Zr [ppm]

The solubility products are fetched from Gunnar Hägg Allmän och oorganisk kemi and CRC Handbook and are defined at room temperature.

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Explaination of Rxy vs pKs

The theory of competitive solving and crystallization is based on variations between soil components in the dynamic range of free ions (nutrients and toxic).

The statistical parameter Rxy is computed for linear regression and yield a measure of how strong the correlation is between two database components in the range of -1 for strong negative correlation, 0 for no correlation and is +1 for strong positive correlation.

The Rxy parameter is not depending on various ranges of the compared components, and is in the database "pHgraf" also completed with a linear equation.

The solubility product pKs is a measure of how the solid state of a compound balances to solution, and as there are many alternative solid states concerning positive and negative ions the diagrams sometimes interfere with each other depending on how strong the most competitive correlation is.


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Formulas related to the theory

In this diagram with Rxy on the Y-axis and pKs on the X-axis:
With increasing solubility from A to B

Point 1: The studied compound is competitivly dissolved
Point 2: An equal optima at similar pKs
Point 3: The studied compound is competitivly crystallizing

These phenomena cause redistribution along the height-curve
and regulate the availability of plant nutrients.




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Mathematic formulas related to the theory of competitive dissolving.

By statistically comparing 28 measure spots with 23 parameters each, significant covariance in distribution along the height-curve, pH in river-water and plant-nutrition in soil was noted.





These formulas resulted applied with the program pHgraf and solubility products for some of the compounds in the theory of competitive solving and crystallization in soil.



Cat-ions
(positive)
An-ions
(negative)
Conclusions

Al

Ba

Ca

Cr

Fe

Cu

K

Mo

Mg

Ni

Mn

Pb

Na

Sr

P

V

Si

Zn

Ti

Zr

Carbonate

Chromate

Hydroxide

Phosphate

Sulfate

Sulfide

By comparing distribution-phenomena in parallell along six rivers in the north of Sweden a strong pattern evolves inbetween the cat-ions in the table, they compete in forming hard to solve compounds with the an-ions, this show as coherent curves in diagrams of the solubility products vs the statistical parameter Rxy. Some elements with hard to solve compounds outcompete the bonding to an-ions causing release of several plant nutrients yielding a secondary nutrition effect.



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Hydroxides

The diagram of hydroxide solubility show the difference between Potassium and Magnesium and the coherency of the curves between elements with strong linear correlation.



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Sulfides

The simple coherency of the curves for Barium, Calcium, Sodium and Strontium indicates an easy to solve Sulfide crystallization, and they are outcompeted by the more insoluble compounds.

Zirconium show an inverted curve with positive correlation to Lead and Zinc Sulfide, indicating more insoluble characteristics, Titanium also has a curve-shape that indicates insolubility as Sulfide, interesting that these hard to solve Sulfides have a positive correlation towards pH in river-water though Sulfide oxidation to Sulfate release hydrogen ions. The hard to solve Sulfide compounds seems to inhibit the lowering of pH in river-water in a competitive way.


Formula of the Sulfide oxidation process to Sulfate, here presented with Iron, other metals are assumed to have similar reaction. The solubility of the compounds determine cyclic dissolving and crystallization. As shown in the formula below, the oxidation-process release Hydrogen ions, and hard to dissolve compounds inhibit this process in a competitive way, increasing the pH in close river water and release more easily dissolved compounds (several nutrients).


Formula of acidifying Sulfide oxidation to Sulfate and forming of hydroxides:
4 FeS2 + 15 O2 + 14 H2O → 4 Fe(OH)3 + 8 SO42- + 16 H+

It is the metal that causes acidification, as it bonds hydroxide.

Other elements that acidifies according to the database pHgraf:
Acidifying elements
Aluminium
Barium
Calcium
Chrome
Copper
Iron
Magnesium
Molybdenum
Nickel
Phosphor
Sodium
Strontium
Vanadium


Silicon also has an influence among Sulfides, and rise pH in close river-water, Silicon form polymer as Sulfide, and is to be regarded as hard to dissolve.


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Sulfates


Potassium has a curve-shape that indicates an easy to solve Sulfate.
Copper is easy to solve as Sulfate and follow the height-curve downhill.
The over layer of the ground is called oxidationzone, as oxygen easier access the soil, and causes the Sulfate ion to dominate over Sulfide.

In deficiency of Oxygen a microbial reaction with organic compounds reduces the Sulfate back to Sulfide in the presence of Hydrogen ions.
4 Fe(OH)3 + 4 SO42- + 9 CH2O + 8 H+ → 4 FeS + 9 CO2 + 19 H2O


Barium is one of the strong competitors bonding Sulfate, and according to this theory release nutrients in the surface oxidationzone of the soil, but is easily dissolved as Sulfide and thus washed downhill.



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Carbonates

This diagram is strongly affected by other processes but Potassiumcarbonate (Pearlash) has a mid-range peak at the solubility of Barium Carbonate.

Pearlash (K2CO3) is dissolved to 50 weight% in water and get a simultanous solubility peak with Bariumcarbonate (BaCO3) that is not easily dissolved in water, this perhaps due to reaction with acid. An ammine ion can also form with covalent character.


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Chromates

This vague diagram of Chromates with only three known coordinates still show the coherency along the line of solubility according to linear regression between the elements.



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Phosphates

The Phosphates present in the diagram show that Potassium-Phosphate is easily solved in comparison to Nickel-Phosphate, that has positive synergy towards Chrome-Phosphate.

Phosphor-Oxide has a peak at the solubility of Iron-Phosphate.



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Silica compounds

Silica has negative correlation towards:
Al,P,Fe,Ca,Mg,Mn,Na,Ti,Ba,Cu,Cr,Mo,Ni,Sr,V

Silica has positive correlation towards:
K,Pb,Zn,Zr and all of them (including Silica) have positive correlation to pH in river-water. This can be explained by the inhibiting of the H+ releasing Sulfide oxidation to Sulfate indicating a possible accessible plant-nutrient increase. Silic acid (H4SiO4) also has an high pKa that rises the pH.


Silica has as the largest soil component a negative correlation towards nutrition, most likely because of long term competitive solving effect on nutrients (causing deficiency), this is a perspective on the other hard to solve competitive compounds as well.

Depletion through Silicon:
Engulfs Sulfides in a cyclic manner.

SiO2 + Al2S3 + H2O → SiS2 + Al2O3 + H2S
or with more water:
SiO2 + Al2S3 + 4 H2O → SiS2 + 2 Al(OH)3 + H2S
and further on:
2 Al(OH)3 + 3 H2SO4 → Al2(SO4)3+ 6 H2O
Al2(SO4)3 + 3 Ba(NO3)2 → 2 Al(NO3)3 + 3 BaSO4
SiS2 + 4 H2O → H4SiO4 + 2 H2S
H4SiO4 ↔ SiO2 + 2 H2O


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Clusters separating along height-curve

Positive correlation is signed with (/)
Negative correlation is signed with (\)


These elements stay uphill the height-curve, except Potassium that is solved and transported downhill.



These elements are transported downhill except Zinc that is remaining uphill.



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Alteration of plant-nutrition along height-curve

The nutrient result of these phenomena along the height-curve evens out with big fluctuations, as both the uphill and the downhill clusters contain poisons and nutrients.

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Secondary plant nutrition effect

Positive correlation is signed with (/)
Negative correlation is signed with (\)


It is to be noted that hard to solve compounds of no nutritious effect cause a secondary release of plant nutrition by competitive bonding of negative ions in deficiency.

Silica has as the largest soil component a negative correlation towards nutrition, most likely because of long term competitive solving effect on nutrients (causing deficiency), this is a perspective on the other hard to solve competitive compounds as well.


This picture shows how the penetration of Oxygen into the soil forms an oxidationzone in which Sulfate dominates over Sulfide, the depth of the oxidationzone can be regulated by plowing thus affecting whether the bonding of nutrients is to be by Sulfate or Sulfide. It also shows how the soil is naturally added with Sulfur by acid rain and also can emit Sulfur as Dihydrogensulfide.


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Secondary nutrition effect by competitive bonding

Sulfides
secondary
mobilising
unbound
nutrition
Cu
Pb
Si
Ti
Zn
Zr
Ca
Fe
Mg
Sulfates
secondary
mobilising
unbound
nutrition
Ba
Pb
Ca
Fe
K
These tables show how plant-nutrition can be released by harder bonding of Sulfide and Sulfate, but as Sulfur is of great nutrition value to humans and plants a dilemma appears. Excessive amounts of Sulfur bonds other plant-nutrition, and excessive plant-nutrition makes the Sulfur less accessable to enrichen the crop. Thus, it is an interesting perspective controling the balance here.


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Practical experiments

In the summer of 2008 I cropped carrots in three large pots, one with an ordinary turf-soil and two with clay-soil, of one was added with a trace amount of Zirconium dioxide (ZrO2).

The growth result was an increase of 3.5 times in the clay soil added with ZrO2 in comparison with the original clay soil, the outmost crop was as expected in the turf-soil.

It is thus very likely the theory of competitive dissolving and crystallization works practically, Zirconium has caused a secondary nutrition release accordingly, bonding Sulfide that would have made nutrients like Calcium, Magnesium and Iron unavailable to plants.

QED

Carrots cropped in three pots
Normal growth in turf-soil Untreated clay-soil Zirconium increase growth 3.5x


The pictures below show how the competitive processes affect plant-nutrition from year 2010 to 2018. The pots containing Zirconium and the untreated Reference were collected in 2008. The pots containing the Fertilized soil and the one with Bound fertilizer were collected in 2010. The bonding of the excessive fertilization is with CaSO4 and K2CO3 to alter the anion-balance, to study the effects on available plant-nutrition.


The results of these tests are: Fast release, availability and nutrient depletion with Zirconium added. Only fertilization lasts longer. With Carbonate and Sulfate added, plant-nutrition becomes unavailable but remains in soil. The completly untreated Reference still has plant-nutrition to grow grass.

A series of total ICP-analyses are planned for 2019, to figure out these phenomena properly.

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Thank You ! Joakim Forssman JSF-KEMI