Atlas geoquímico dos solos das bacias hidrográficos dos rios Douro e Mondego
Bibliographic record
Abstract
Este trabalho tem como objectivos a caracterização geoquímica e a avaliação da aptidão natural dos solos das bacias hidrográficas dos rios Douro e Mondego, para o cultivo da vinha. Estes dois rios, têm uma importância socioeconómica para Portugal, por integraram duas das mais famosas regiões vitivinícolas que são respectivamente a região demarcada dos Vinhos do Porto e do Douro e a região demarcada do Dão. Estas duas bacias hidrográficas foram escolhidas, em face de duas razões: Pelo facto dos vinhos representarem uma importante área de exportação e tendo em conta a grande diversidade de unidades geológicas, de climas, de fauna e flora, evidenciadas nas duas bacias hidrográficas (Douro e Mondego). Este trabalho constitui um estudo de amostragem para baixa densidade de amostragem, tendo sido os resultados apresentados para um total de 221 amostras colhidas a norte do rio Tejo, sendo 109 amostras pertencentes à bacia hidrográfica do rio Douro e 21 pertencentes à bacia hidrográfica do rio Mondego. Cada amostra foi analisada para um conjunto de 32 elementos: Al, As, Ag, Au, Ba, B, Bi, Ca, Cd, Co, Cr, Cu, Fe, Hg, K, La, W, Mg, Mn, Mo, Na, Ni, P, Pb, Sb, Sr, Th, Ti, Tl, U,V e Zn. Cada amostra de solo foi digerida em água régia a quente (95ºC) e posteriormente analisada por ICP-ES Optima, num laboratório comercial (ACME Analytical Laboratory ISSO-9002 Acredited.Co, Canadá). Para proceder à avaliação da aptidão natural dos solos para o cultivo das vinhas (outro aspecto importante no trabalho), foram escolhidos os elementos químicos com interesse (Cu, Zn, Co, Mn, As, V, Ca, P, Cr, Mg e K), ou sejam, os nutrientes que podem ser potencialmente tóxicos para a planta. Para atingir os objectivos propostos utilizaram-se: 1) Análise de Componentes Principais (ACP) e a Análise de Correspondências Múltiplas (ACM) para se estabelecerem as relações entre as variáveis. 2) A variografia para definir os modelos de distribuição espacial das variáveis 3) A krigagem para a estimação e elaboração dos mapas de factores. ABSTRACT: This study concerns the geochemical characterization of the soils within the Douro catchment-basin and the Mondego catchment-basin.This two rivers, have an essential socio-economic importance for Portugal and a ancient heritage, since it holds two of the most famous wine production regions, namely the Port and Douro Wine Region and Dão Wine Region. Since wines are one of the major exportation products of Portugal and considering the diversity of the geological units, the climates, the fauna and the flora, along these two catchment-basins (Douro and Mondego) these areas seemed suitable for developing this study. This is an low density sampling survey and the results presented here are results concerning a high number of results (From the 221 samples collected at north of Tagus river,109 are from the Douro catchment-basin and 21 from the Mondego catchment-basin),and each soil sample was analysed for 32 elements: Al, As, Ag, Au, Ba, B, Bi, Ca, Cd, Co, Cr, Cu, Fe, Hg, K, La, W, Mg, Mn, Mo, Na, Ni, P, Pb, Sb, Sr, Th, Ti, Tl, U,V e Zn,and submitted with regia water at 95 Celsius, and after this analysed in ICP-ES Optima, on a commercial laboratory (ACME Analytical Laboratory ISSO-9002 Acredited.Co, Canada). For these study the assessment of the natural aptness of the soils for grapes plantation, were selected the chemical elements with relevance for the vineyards( Cu, Zn, Co, Mn, As, V, Ca, P, Cr, Mg e K) , that is elements acting as nutrients or potentially toxic to the plant, because we are interested in study the natural aptness of the soils for grapes plantation. The methodology used to achieve these purposes consist upon: 1) Principal Components Analysis and Multiple Correspondences Analysis to identify relations between variables. 2) Variography to define the spacial distributing models of variables. 3) Kriging to estimate and therefore to make scores maps.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".