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Record W2994257685 · doi:10.15414/afz.2016.19.02.68-73

Application of various methodological approaches for assessment of soil micromorphology due to VESTA program applicable to prediction of the soil structures formation

2016· article· en· W2994257685 on OpenAlexaboutno aff
Marek Kolenčík, Vladimí­r Šimanský

Bibliographic record

VenueActa fytotechnica et zootechnica/Acta fytotechnica et zootechnica · 2016
Typearticle
Languageen
FieldMaterials Science
TopicClay minerals and soil interactions
Canadian institutionsnot available
Fundersnot available
KeywordsAggregate (composite)ExtrapolationSoil waterWeatheringComputer scienceSoil scienceEnvironmental scienceMineralogyBiological systemGeologyMathematicsStatisticsMaterials scienceGeochemistry

Abstract

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Received: 2015-07-22  |  Accepted: 2016-03-11  |  Available online: 2016-05-30 dx.doi.org/10.15414/afz.2016.19.02.68-73 This work introduces concepts of methodological approach (theoretical investigation) in terms of soil structure analysis. The aim of this work is using VESTA program application as appropriate alternative to quantification of micromorphological analysis. This evaluation mainly with regarded to effects for soils structure at the interactions/ predictions with many aspects of aggregate destruction-stability-reactivity in soil system. This work elucidates different kind of methodological approaches such as implementation 2D micromorphological model, X-ray analysis and their extrapolation in VESTA program. There is some evidence that construct data and parameters gained from this program are suitable for other considerations. For these points is possible to assign of reaction kinetic, established minerals phase and genetic relationships in soil system, detect of potential transformation, mobilization and immobilization activity, distribution of elements species even by general and specific properties of aggregate forms. Detailed characterization (modeled design) of rocks and minerals inorganic particles of soil aggregate forms on the atomic level has significant importance due to detailed data examinations input. In the case of operation module could eliminate of influence various undetected (non-identify) factors and in additionally refine on standardize appropriate fitted the more realistic model. Keywords: methodological approach, micromorphology, X-ray analysis, VESTA design References BARKER, W. et al. (1998) Experimental observations of the effects of bacteria on aluminosilicate weathering. Am Mineral ., vol. 83, pp. 1551-1563. BRONICK, C.J. and LAL, R. (2005) The soil structure and land management: a review. Geoderma, vol. 124, no. 1-2, pp. 3-22. doi: http://dx.doi.org/10.1016/j.geoderma.2004.03.005 CARTER, M.R. and STEWART, B.A. (1996) Structure and organic matter storage in agricultural soils. Boca Raton: CRC/Lewis Publisher. Chenu, C. and Cosentino, D. (2011) Microbial regulation of Soil Structural Dynamics. In: RITZ, K. and Young, I. (eds.) The Architectural and Biology of Soils: Life in Inner Space. London: CAB International, pp. 259-272. ČURLÍK, J. (2011) Potentially toxic trace elements and their distribution in Slovakian soils . Bratislava: Suma print (in Slovak). ČURLÍK, J. and KOLESÁR, M. (2014) Inorganic carbon sequestration in autigenic carbonates and their distribution in soils on loess: micromorphological aspects. AGEOS , vol. 6, pp. 191-202 (in Slovak). Edwards, A.P. and Bremner, J.M. (1967) Microaggregates in soils. J Soil Sci. , vol. 18, pp. 64-73. GADD, G.M. (2007) Geomycology: biogeochemical transformations of rocks, minerals, metals and radionuclides by fungi, bioweathering and bioremediation. Mycol Res ., vol. 111, pp. 3-49. GONZÁLEZ, C. et al. (2007) Applying multivariate methods to soil–solution interactions in carbonate media. In. Geoderma , vol. 137, pp 352-359. Grosbellet, G. et al. (2011) Improvement of soil structure formation by degradation of coarse organic matter. Geoderma , vol. 162, pp. 27–38. doi: http://dx.doi.org/10.1016/j.geoderma.2011.01.003 Hu, F. et al. (2015) Particles interaction forces and their effects on soil aggregates breakdown. Soil Till. Res., vol. 147, pp. 1–9. doi: http://dx.doi.org/10.1016/j.still.2014.11.006 IUSS Working Group WRB (2006) World reference base for soil resources. World Soil Resources Reports no. 103 . Rome: FAO. Jozefaciuk, G. and Czachor, H. (2014) Impact of organic matter, iron oxides, alumina, silica and drying on mechanical and water stability of artificial soil aggregates. Assessment of new method to study water stability. Geoderma, vol. 221–222, pp. 1–10. doi: http://dx.doi.org/10.1016/j.geoderma.2014.01.020 JUMA, N.G. (1999) Pedosphere and its dynamics . Edmonton (Canada): Salman Productions Ins. KAY, B.D. (1998) Soil structure and organic carbon: a review. In: LAL, R. et al. (eds.) Soil Processes and the Carbon Cycle . Boca Raton: CRC Press, pp. 169-197. Kögel-Knabner, I. et al. (2008) An intergrative approach of organic matter stabilization in temperate soils: Linking chemistry, physics and biology. J Plant Nutr Soil Sci. , vol. 171, pp. 5-13. KOLENČÍK, M. et al. (2011) Biological and chemical leaching of arsenic and zinc from adamite. Chem Listy ., vol. 105, pp. 961-965. KUO, Y-M., et al. (2009) Apatite control of phosphorus release to runoff from soils of phosphate mine reclamation areas. Water Air Soil Pollut. , vol. 202, pp.189-198. Lal, R. and Shukla, M.K. (2004) Principles of soil physics . New York: Marcel Dekker. LI, G.Y. and FAN, H.M. (2014) Effect of Freeze-Thaw on Water Stability of Aggregates in a Black Soil of Northeast China . Pedosphere, vol. 24, pp. 285-290. doi: http://dx.doi.org/10.1016/S1002-0160(14)60015-1 MARKGRAF, S.A. and REEDER, R.J. (1985) High-temperature structure refinements of calcite and magnesite. Am Mineral ., vol. 70, pp. 590-600. MOMMA, K. and IZUMI, F. (2011) VESTA 3 for three-dimensional visualization of crystal, volumetric and morphology data. J Appl Crystallogr ., vol. 44, pp. 1272-1276. Morphogenetic Soil Classification System of Slovakia (2014) The basal reference taxonomy (in Slovak). Bratislava: Societa pedologica Slovaca, SSCRI. Paradelo R. et al. (2013) Water-dispersible clay in bare fallow soils after 80 years of continuous fertilizer addition. Geoderma , vol. 200-201, pp. 40-44. http://dx.doi.org/10.1016/j.geoderma.2013.01.014 PRINCE, E. et al. (1999) International tables for crystallography: International Union of Crystallography . Birmingham: Kynoch Press. Roger-Estrade, J. et al. (2010) Tillage and soil ecology: partners for sustainable agriculture. Soil Till Res., vol. 111, no. 1, pp. 33–40. doi: http://dx.doi.org/10.1016/j.still.2010.08.010 Santos, D. et al. (1997) Uniform separation of concentric surface layers from soil aggregates. Soil Sci Soc Am J ., vol. 61, pp. 720-724. doi: http://dx.doi.org/10.2136/sssaj1997.03615995006100030003x ŠIMANSKÝ, V. (2012) Assessment of soil structure under monoculture of vine. Roczniki Gleboznawce , vol. 63, no. 2, p. 42–45. doi: http://dx.doi.org/10.2478/v10239-012-0023-2 Šimanský, V. and Bajčan, D. (2014) The stability of soil aggregates and their ability of carbon sequestration. Soil & Water Res., vol. 9, no. 3, pp. 111-118. ŠIMANSKÝ, V. et al. (2013) The effect of organic matter on aggregation under different soil management practices in a vineyard in an extremely humid year. Catena, vol. 101, pp. 108-113. doi: http://dx.doi.org/10.1016/j.catena.2012.10.011 SOMASUNDARAN, J. et al. (1985) Mineral-solution equilibria in sparingly soluble mineral systems. Colloids Surf., vol. 15, pp. 309-333. ŠUCHA, V., et al. (1993) Smectite to illite conversion in bentonites and shales of the East Slovak Basin. Clay Miner. , vol. 28, pp. 243-243. TINDSAll, J.m. and OADES, j.m. (1982) Organic matter and water-stable aggregates in soils. Soil Sci ., vol. 33, pp. 141-163. WILSON, R. (1999) Rietveld refinement of the crystallographic structure of human dental enamel apatites. Am Mineral ., vol. 84, pp. 1406-1414.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.558
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0040.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.097
GPT teacher head0.363
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations2
Published2016
Admission routes1
Has abstractyes

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