Root

Summary

In vascular plants, the roots are the organs of a plant that are modified to provide anchorage for the plant and take in water and nutrients into the plant body, which allows plants to grow taller and faster. They are most often below the surface of the soil, but roots can also be aerial or aerating, that is, growing up above the ground or especially above water. Function The major functions of roots are absorption of water, plant nutrition and anchoring of the plant body to the ground. Anatomy Root morphology is divided into four zones: the root cap, the apical meristem, the elongation zone, and the hair. The root cap of new roots helps the root penetrate the soil. These root caps are sloughed off as the root goes deeper creating a slimy surface that provides lubrication. The apical meristem behind the root cap produces new root cells that elongate. Then, root hairs form that absorb water and mineral nutrients from the soil. The first root in seed producing plan

Official source

https://en.wikipedia.org/wiki/Root

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Root development and heavy metal phytoextraction efficiency: comparison of different plant species in the field

Catherine Keller

Springer, Kluwer Academic Publishers2003

Phytoextraction is a non-invasive remediation method using plants. Phytotech Foundation and AGB in Berne are performing phytoextraction on an old landfill of a former hot dip galvanization plant, using sunflowers and tobaccos as extractors. Every year since 2007, total and soluble zinc concentrations in soil as well as zinc concentrations in shoot of the plants have been measured. To study the role of roots in phytoextraction, 14 root samples were harvested in autumn 2010 and their zinc concentration was measured. The results show that sunflowers were more efficient in fast transfer of zinc from root to shoot. They were also compared with the 4-year measurements and a mass balance was performed. This has shown that phytoextraction was so efficient that even the decrease in soluble zinc did not explain itself the concentrations in the plant. The roots may mobilize total zinc, which might re-load the soluble zinc pool in soil. In parallel, a pot experiment was performed at laboratory scale with young tobacco plants growing on polluted soils, monitoring root, stem, leaves, leachates and soil zinc concentrations. A mass balance was also performed, which confirmed the previous statement, even at young stage and for detailed values. Finally thanks to both experiments, it was suggested that there should be a potential concentration for each part of plants. Once this concentration reached, transfer of zinc could occur from the root to the stem, and then from the stem to the leaves where it is accumulated.

2011

Partitioning soil organic carbon into its centennially stable and active fractions with machine-learning models based on Rock-Eval (R) thermal analysis (PARTY(SOC)v2.0 and PARTY(SOC)v2.0 (EU))

Juan Carlos Quezada Rivera

Partitioning soil organic carbon (SOC) into two kinetically different fractions that are stable or active on a century scale is key for an improved monitoring of soil health and for more accurate models of the carbon cycle. However, all existing SOC fractionation methods isolate SOC fractions that are mixtures of centennially stable and active SOC. If the stable SOC fraction cannot be isolated, it has specific chemical and thermal characteristics that are quickly (ca. 1 h per sample) measurable using Rock-Eval (R) thermal analysis. An alternative would thus be to (1) train a machine-learning model on the Rock-Eval (R) thermal analysis data for soil samples from long-term experiments for which the size of the centennially stable and active SOC fractions can be estimated and (2) apply this model to the Rock-Eval (R) data for unknown soils to partition SOC into its centennially stable and active fractions. Here, we significantly extend the validity range of a previously published machine-learning model (Cecillon et al., 2018) that is built upon this strategy. The second version of this model, which we propose to name PARTYsoc, uses six European long-term agricultural sites including a bare fallow treatment and one South American vegetation change (C4 to C3 plants) site as reference sites. The European version of the model (PARTY(SOC)v2.0(EU)) predicts the proportion of the centennially stable SOC fraction with a root mean square error of 0.15 (relative root mean square error of 0.27) at six independent validation sites. More specifically, our results show that PARTY(SOC)v2.0(EU) reliably partitions SOC kinetic fractions at its northwestern European validation sites on Cambisols and Luvisols, which are the two dominant soil groups in this region. We plan future developments of the PARTY(SOC) global model using additional reference soils developed under diverse pedoclimates and ecosystems to further expand its domain of application while reducing its prediction error.

COPERNICUS GESELLSCHAFT MBH2021

Partitioning soil organic carbon into its centennially stable and active fractions with machine-learning models based on Rock-Eval (R) thermal analysis (PARTY(SOC)v2.0 and PARTY(SOC)v2.0 (EU))

Juan Carlos Quezada Rivera

COPERNICUS GESELLSCHAFT MBH2021