Soil quality estimation using environmental covariates and predictive models: an example from tropical soils of Nigeria

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41210%2F22%3A92307" target="_blank" >RIV/60460709:41210/22:92307 - isvavai.cz</a>

Výsledek na webu

<a href="https://ecologicalprocesses.springeropen.com/articles/10.1186/s13717-022-00411-y" target="_blank" >https://ecologicalprocesses.springeropen.com/articles/10.1186/s13717-022-00411-y</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1186/s13717-022-00411-y" target="_blank" >10.1186/s13717-022-00411-y</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Soil quality estimation using environmental covariates and predictive models: an example from tropical soils of Nigeria

Popis výsledku v původním jazyce

Information addressing soil quality in developing counries often depends on results from small experimental plots, which are later extrapolated to vast areas of agricultural land. This approach often results in misinformation to en users of land for sustainable soil nutrient management. The objective of this study was to estimate the spatial variability of soil quality index (SQI) at regional scale with predictive models using soil environmental covariates. Structural stability index, sand content, soil oganic carbon content, and mean weight diameter of aggregates were the parameters used in establishing regional soil quality indices, while land surface water index, Sentinel 2 near-infrared band, plane curvature, and clay index were the most important variables affecting soil quality variability. The MDS-L and GWR are effective and useful models to identify the key soil properties for assessing soil quality, which can provide guidance for site-specific management of soils developed on diverse parent

Název v anglickém jazyce

Soil quality estimation using environmental covariates and predictive models: an example from tropical soils of Nigeria

Popis výsledku anglicky

Information addressing soil quality in developing counries often depends on results from small experimental plots, which are later extrapolated to vast areas of agricultural land. This approach often results in misinformation to en users of land for sustainable soil nutrient management. The objective of this study was to estimate the spatial variability of soil quality index (SQI) at regional scale with predictive models using soil environmental covariates. Structural stability index, sand content, soil oganic carbon content, and mean weight diameter of aggregates were the parameters used in establishing regional soil quality indices, while land surface water index, Sentinel 2 near-infrared band, plane curvature, and clay index were the most important variables affecting soil quality variability. The MDS-L and GWR are effective and useful models to identify the key soil properties for assessing soil quality, which can provide guidance for site-specific management of soils developed on diverse parent

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

40104 - Soil science

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

ECOLOGICAL PROCESSES

ISSN

2192-1709

e-ISSN

2192-1709

Svazek periodika

11

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

22

Strana od-do

0-0

Kód UT WoS článku

000888732200001

EID výsledku v databázi Scopus

2-s2.0-85142470009