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Statistical and theoretic soil chemistry
from north of Sweden
*UPDATED 2012-01-09*
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 furhter 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.
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.
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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 | ||||||||||||||||||||||||||
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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.Click here for such diagram
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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).
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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: |
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Click here for such diagram
Silicon also has an influence among Sulfides, and rise pH in close river-water, Silicon and Potassium form polymers as Sulfides, and are to be regarded as hard to dissolve.
Click here for such diagram
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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.
Click here for such diagram
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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, but as other alkaline earth metals bind Ammonia as covalent and form an Ammine-ion for example BaNH3+ and in presence of Ammonia yields a solubility equal to Pearl-ash (that is just dissolved in water).
Click here for such diagram
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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.Click here for such diagram
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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.
Click here for such diagram
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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.
Click here for such diagram
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.
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Periodic Table
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 0 |
| H | He | ||||||||||||||||
| Li | Be | B | C | N | O | F | Ne | ||||||||||
| Na | Mg | Al | Si | P | S | Cl | Ar | ||||||||||
| K | Ca | Sc | Ti | V | Cr | Mn | Fe | Co | Ni | Cu | Zn | Ga | Ge | As | Se | Br | Kr |
| Rb | Sr | Y | Zr | Nb | Mo | Tc | Ru | Rh | Pd | Ag | Cd | In | Sn | Sb | Te | I | Xe |
| Cs | Ba | La | Hf | Ta | W | Re | Os | Ir | Pt | Au | Hg | Tl | Pb | Bi | Po | At | Rn |
| Fr | Ra | Ac |
The elements with red background follow the height-curve downhill.
The elements with green background stay uphill the height-curve
The elements with blue background have not negative influence on river pH
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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.TABLE OF CONTENTS
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
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| 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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Microscopy on the plotted soil-samples
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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 Sulfate that would have made nutrients like Calcium, Magnesium and Iron unavailable to plants, strong bonding of Sulfide also rise the pH in soil (inhibiting Sulfide oxidation to Sulfate).
QED
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| Data table |
The summer of 2009 I also cropped carrots, and the results are shown in the pictures below, grassgrowth was most in the pot treated with ZrO2, but the carrots grew better in the untreated soil and the test also shows that the turf-soil and the soil treated with ZrO2 had more mobility of plant-nutrients causing the nutrition to disappear with crop and water.
So the peak of harvest in 2008, with the turf-soil and the treatment with ZrO2 was a short time boost, not enough to maintain long term fertilization. In 2010 I have planned a balanced adding of binding agents to raise the amount of plant-nutrition available long-term. See below !
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Testing of soil 2010
Carrots cropped in the same soil since 2008.One pot prepared with ZrO2 and
One pot with untreated clay soil.
No further additives except water.
In these images, differences show the soils inbetween, the soil treated with ZrO2 has more green sprouts and higher grass-growth, the increased grass-growth depends on more available minerals, as Zirkonium bonds Sulfide that otherwise would have bound nutrients as Calcium and Iron, resulting in modified soil-properties, the bonding of Sulfur can also have affected the result. The test now shows even stronger signs of the possible in affecting the trace-amounts of available plant-nutrition.
2011 will be an interesting year, as I have prepared two new pots soaked with an excess of nutrient, one of them added with Calciumsulfate (gypsum) and Potassiumcarbonate (Pearlash), this in order to study long term effect on binding nutrition to the soil. When adding these chemicals the pH rised dramatically, especially in the soil added with gypsum and Pearlash, then Ammonia was released (use caution) this depending on a bacteriological process that reduces Sulfur from Sulfate to Sulfide rising the pH.
2011 became interesting indeed, with three sample studies:
Two pots with Zirconium enhanced soil + reference
Two pots with excess nutrition, of one treated with Gypsum (CaSO4) and Pearlash (K2CO3)
Two pots with NPK fertilized compost soil
The soil treated with Zirconium, still after three years show increased grass growth, with more seed than the untreated reference, probable that Calcium and Iron freed of Sulfide bonding caused this.
Zirconium enhanced harvest to the left, reference to the right.
The excessivly fertilized pots showed an increased carrot harvest, and the reference gave more carrots than the soil treated with Gypsum and Pearlash (the nutrition bond by Carbonate and Sulfide/Sulfate), the reference showed a greater washout in chystallization-study. Both the pots have normalized at pH 5,9
The NPK fertilized compost-soil of turf character gave the most carrots, but will probably washout until 2012. An realistic objective is to bind fertilizer in turf soil for longterm nutrition and minimum leakage.
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Joakim Forssman JSF-KEMI