Predicting soil particle density from clay and soil organic matter contents

Geoderma ◽  
2017 ◽  
Vol 286 ◽  
pp. 83-87 ◽  
Author(s):  
P. Schjønning ◽  
R.A. McBride ◽  
T. Keller ◽  
P.B. Obour
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Particle Density ◽  
Soil Particle

Corrigendum to ‘Predicting soil particle density from clay and soil organic matter contents’ [Geoderma 286 (2017) 83–87]

Geoderma ◽  
2017 ◽  
Vol 292 ◽  
pp. 150 ◽  
Author(s):  
P. Schjønning ◽  
R.A. McBride ◽  
T. Keller ◽  
P.B. Obour
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Particle Density ◽  
Soil Particle

Soil organic matter and silt contents determine soil particle surface electrochemical properties across a long-term natural restoration grassland

CATENA ◽  
2020 ◽  
Vol 190 ◽  
pp. 104526 ◽  
Author(s):  
Jingfang Liu ◽  
Zilong Wang ◽  
Feinan Hu ◽  
Chenyang Xu ◽  
Rentian Ma ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Electrochemical Properties ◽  
Particle Surface ◽  
Soil Particle ◽  
Natural Restoration

scholarly journals Hyperspectral Estimation Model of Forest Soil Organic Matter in Northwest Yunnan Province, China

Forests ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 217 ◽  
Author(s):  
Yun Chen ◽  
Jinliang Wang ◽  
Guangjie Liu ◽  
Yanlin Yang ◽  
Zhiyuan Liu ◽  
...  
Keyword(s):  
Particle Size ◽  
Organic Matter ◽  
Soil Organic Matter ◽  
Linear Regression ◽  
Forest Soil ◽  
Spectral Reflectance ◽  
Soil Particle ◽  
Estimation Model ◽  
Soil Particle Size ◽  
First Derivative

Soil organic matter (SOM) is an important index to evaluate soil fertility and soil quality, while playing an important role in the terrestrial carbon cycle. The technology of hyperspectral remote sensing is an important method to estimate SOM content efficiently and accurately. This study researched the best hyperspectral estimation model for SOM content in Shangri-La forest soil. The spectral reflectance of soils with sizes of 2 mm, 1 mm, 0.50 mm, and 0.25 mm were measured indoors. After smoothing and de-noising, the reciprocal reflectance (RR), logarithmic reflectance (LR), first-derivative reflectance (FR), reciprocal first-derivative reflectance (RFR), logarithmic first-derivative reflectance (LFR), and mathematical transformations of the original spectral reflectance (REF) were carried out to analyze the relevance of spectral reflectance and SOM content and extract the characteristic bands. Finally the simple linear regression (SLR), multiple stepwise linear regression (SMLR), and partial least squares regression (PLSR) models for SOM content estimation were established. The results showed that: (1) With the decrease of soil particle size, the spectral reflectance increased. The smaller the soil particle sizes, the more obvious was the increase in spectral reflectance. (2) The sensitive bands of SOM were mainly in the 580–690 nm range (correlation coefficient (R) > 0.6, p-value (p) < 0.01), and the spectral information of SOM could be significantly enhanced by first-order differential transformation. (3) Comparing the three models, PLSR had better estimation ability than SMLR and SLR. The precision of the 0.25 mm soil particle size and the LFR index in the PLSR estimation model of SOM content was the best (coefficient of determination of validation (Rv2) = 0.91, root mean square error of validation (RMSEv) = 13.41, the ratio of percent deviation (RPD) = 3.33). The results provide a basis for monitoring SOM content rapidly in the forests of Northwest Yunnan, and provide a reference for forest SOM estimation in other areas.

Influence of aggregate architecture and minerals on living habitats and soil organic matter

1997 ◽  
Vol 77 (3) ◽  
pp. 367-377 ◽  
Author(s):  
C. M. Monreal ◽  
H. Kodama
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Ammonium Oxalate ◽  
Clay Content ◽  
Integrated Approach ◽  
Soil Particle ◽  
Organic C ◽  
Equivalent Spherical Diameter ◽  
Primary Particles ◽  
Spherical Diameter

We used an integrated approach to determine the effects of soil particle architecture and minerals on living habitats and soil organic matter (SOM). Macroaggregate (> 250 µm), microaggregate 1 (50–250 µm), and microaggregate 2 (< 50 µm) fractions of adjacent forested and cultivated Gleysolic soil were obtained by wet sieving. The forested site was used as a reference to evaluate the effects of cultivation on soil particle architecture. Aggregates and respective clay fractions were characterized using optical, chemical, physical and microbial methods. Microaggregates 1 had primary particles with the largest mean equivalent spherical diameter (ESD) and void volume of all aggregate fractions. These physical characteristics were paralleled by the highest SOM and microbial biomass content, and number of microorganisms. Cultivation increased the weathering of primary particles and SOM loss, and decreased the content of microbial pools, suggesting deteriorated living habitats. Soil organic C content in aggregates correlated significantly with the amount of ammonium oxalate extractable Al, chloritized vermiculite, and vermiculite, and was inversely associated with the total clay content. The mean ESD of primary particles and expandable phyllosilicates of aggregates influenced living habitats by supplying substrates, and providing different void and protective space for soil microorganisms. Key words: Aggregate, mean equivalent spherical diameter, bacteria, fungi, actinomycetes, microbial biomasss, organic carbon, vermiculite, non-crystalline inorganic soil components

Sign in / Sign up

Export Citation Format

Share Document