Literature DB >> 23226882

Near infrared spectroscopy for determination of various physical, chemical and biochemical properties in Mediterranean soils.

R Zornoza1, C Guerrero, J Mataix-Solera, K M Scow, V Arcenegui, J Mataix-Beneyto.   

Abstract

The potential of near infrared (n class="Chemical">NIR) reflectaclass="Chemical">nce spectroscopy to predict various physical, chemical aclass="Chemical">nd biochemical properties iclass="Chemical">n Mediterraclass="Chemical">neaclass="Chemical">n soils from SE Spaiclass="Chemical">n was evaluated. Soil samples (class="Chemical">n=393) were obtaiclass="Chemical">ned by sampliclass="Chemical">ng thirteeclass="Chemical">n locatioclass="Chemical">ns duriclass="Chemical">ng three years (2003-2005 period). These samples had a wide raclass="Chemical">nge of soil characteristics due to variatioclass="Chemical">ns iclass="Chemical">n laclass="Chemical">nd use, vegetatioclass="Chemical">n cover aclass="Chemical">nd specific climatic coclass="Chemical">nditioclass="Chemical">ns. Biochemical properties also iclass="Chemical">ncluded microbial biomarkers based oclass="Chemical">n class="Chemical">n class="Chemical">phospholipid fatty acids (PLFA). Partial least squares (PLS) regression with cross validation was used to establish relationships between the NIR spectra and the reference data from physical, chemical and biochemical analyses. Based on the values of coefficient of determination (r(2)) and the ratio of standard deviation of validation set to root mean square error of cross validation (RPD), predicted results were evaluated as excellent (r(2)>0.90 and RPD>3) for soil organic carbon, Kjeldahl nitrogen, soil moisture, cation exchange capacity, microbial biomass carbon, basal soil respiration, acid phosphatase activity, β-glucosidase activity and PLFA biomarkers for total bacteria, Gram positive bacteria, actinomycetes, vesicular-arbuscular mycorrhizal fungi and total PLFA biomass. Good predictions (0.81<r(2)<0.90 and 2.5<RPD<3) were obtained for exchangeable calcium and magnesium, water soluble carbon, water holding capacity and urease activity. Resultant models for protozoa and fungi were not accurate enough to satisfactorily estimate these variables, only permitting approximate predictions (0.66<r(2)<0.80 and 2.0<RPD<2.5). Electrical conductivity, pH, exchangeable phosphorus and sodium, metabolic quotient and Gram negative bacteria were poorly predicted (r(2)<0.66 and RPD<2). Thus, the results obtained in this study reflect that NIR reflectance spectroscopy could be used as a rapid, inexpensive and non-destructive technique to predict some physical, chemical and biochemical soil properties for Mediterranean soils, including variables related to the composition of the soil microbial community composition.

Entities:  

Year:  2008        PMID: 23226882      PMCID: PMC3517214          DOI: 10.1016/j.soilbio.2008.04.003

Source DB:  PubMed          Journal:  Soil Biol Biochem        ISSN: 0038-0717            Impact factor:   7.609


  2 in total

1.  Visible-near infrared reflectance spectroscopy for rapid, nondestructive assessment of wetland soil quality.

Authors:  Matthew J Cohen; Joseph P Prenger; William F DeBusk
Journal:  J Environ Qual       Date:  2005-07-05       Impact factor: 2.751

2.  Determinants of Soil Microbial Communities: Effects of Agricultural Management, Season, and Soil Type on Phospholipid Fatty Acid Profiles

Authors: 
Journal:  Microb Ecol       Date:  1998-07       Impact factor: 4.552

  2 in total
  11 in total

1.  Predicting field capacity, wilting point, and the other physical properties of soils using hyperspectral reflectance spectroscopy: two different statistical approaches.

Authors:  Hakan Arslan; Mehmet Tasan; Demet Yildirim; Eyüp Selim Koksal; Bilal Cemek
Journal:  Environ Monit Assess       Date:  2014-04-09       Impact factor: 2.513

2.  Changes in soil microbial community structure following the abandonment of agricultural terraces in mountainous areas of Eastern Spain.

Authors:  R Zornoza; C Guerrero; J Mataix-Solera; K M Scow; V Arcenegui; J Mataix-Beneyto
Journal:  Appl Soil Ecol       Date:  2009-07       Impact factor: 4.046

3.  Concentration estimation of heavy metal in soils from typical sewage irrigation area of Shandong Province, China using reflectance spectroscopy.

Authors:  Fei Wang; Chunfang Li; Jining Wang; Wentao Cao; Quanyuan Wu
Journal:  Environ Sci Pollut Res Int       Date:  2017-06-01       Impact factor: 4.223

4.  Estimation of potentially toxic elements contamination in anthropogenic soils on a brown coal mining dumpsite by reflectance spectroscopy: a case study.

Authors:  Asa Gholizadeh; Luboš Borůvka; Radim Vašát; Mohammadmehdi Saberioon; Aleš Klement; Josef Kratina; Václav Tejnecký; Ondřej Drábek
Journal:  PLoS One       Date:  2015-02-18       Impact factor: 3.240

5.  Determination of Total Polysaccharides and Total Flavonoids in Chrysanthemum morifolium Using Near-Infrared Hyperspectral Imaging and Multivariate Analysis.

Authors:  Juan He; Lidan Chen; Bingquan Chu; Chu Zhang
Journal:  Molecules       Date:  2018-09-19       Impact factor: 4.411

6.  Fast and inexpensive detection of total and extractable element concentrations in aquatic sediments using near-infrared reflectance spectroscopy (NIRS).

Authors:  Till Kleinebecker; Moni D M Poelen; Alfons J P Smolders; Leon P M Lamers; Norbert Hölzel
Journal:  PLoS One       Date:  2013-07-29       Impact factor: 3.240

7.  Effects of Subsetting by Parent Materials on Prediction of Soil Organic Matter Content in a Hilly Area Using Vis-NIR Spectroscopy.

Authors:  Shengxiang Xu; Xuezheng Shi; Meiyan Wang; Yongcun Zhao
Journal:  PLoS One       Date:  2016-03-14       Impact factor: 3.240

8.  Discovery of the Linear Region of Near Infrared Diffuse Reflectance Spectra Using the Kubelka-Munk Theory.

Authors:  Shengyun Dai; Xiaoning Pan; Lijuan Ma; Xingguo Huang; Chenzhao Du; Yanjiang Qiao; Zhisheng Wu
Journal:  Front Chem       Date:  2018-05-07       Impact factor: 5.221

9.  Predicting Key Agronomic Soil Properties with UV-Vis Fluorescence Measurements Combined with Vis-NIR-SWIR Reflectance Spectroscopy: A Farm-Scale Study in a Mediterranean Viticultural Agroecosystem.

Authors:  Emmanuelle Vaudour; Zoran G Cerovic; Dav M Ebengo; Gwendal Latouche
Journal:  Sensors (Basel)       Date:  2018-04-10       Impact factor: 3.576

10.  Machine-learning-based quantitative estimation of soil organic carbon content by VIS/NIR spectroscopy.

Authors:  Jianli Ding; Aixia Yang; Jingzhe Wang; Vasit Sagan; Danlin Yu
Journal:  PeerJ       Date:  2018-10-17       Impact factor: 2.984

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.