A new in situ method showed greater persistence of added soil organic matter in natural than restored wetlands

2021 ◽  
Author(s):  
Amr E. Keshta ◽  
Stephanie A. Yarwood ◽  
Andrew H. Baldwin
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Restored Wetlands ◽  
In Situ Method

scholarly journals In vitro estimation of rumen fermentable organic matter using enzymes

1996 ◽  
Vol 44 (2) ◽  
pp. 103-110 ◽  
Author(s):  
J.W. Cone ◽  
A.H. Van Gelder ◽  
A.M. Van Vuuren
Keyword(s):  
Organic Matter ◽  
Crude Fibre ◽  
Fermentation Products ◽  
In Situ Method ◽  
Degradation Rates ◽  
Digestible Organic Matter ◽  
Similar Accuracy ◽  
The Relationship

The amount of rumen fermentable organic matter (FOM) can be calculated using tables, taking into account the amount of digestible organic matter, the content of fat and fermentation products, and the amount of starch and protein escaping rumen fermentation, or FOM can be calculated using in situ incubations. An in vitro method is described to predict FOM using amylase and other carbohydrate degrading enzymes. FOM estimated by the enzymic method showed a moderate correlation (Rsuperscript 2 = 0.71) with FOM estimated by the in situ method. The relationship could be improved by separating the high crude fibre samples (Rsuperscript 2 = 0.88) from the other samples (Rsuperscript 2 = 0.77). Because degradation rates with the enzymic method were high compared with the assumed rumen passage rates, it proved that FOM could be predicted with a similar accuracy (Rsuperscript 2 = 0.76 - 0.80) by the undegraded fraction after 24 h.

In situ photo-polymerization of soil organic matter by heterogeneous nano-TiO2 and biomimetic metal-porphyrin catalysts

2016 ◽  
Vol 52 (4) ◽  
pp. 585-593 ◽  
Author(s):  
Assunta Nuzzo ◽  
Elisa Madonna ◽  
Pierluigi Mazzei ◽  
Riccardo Spaccini ◽  
Alessandro Piccolo
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Metal Porphyrin ◽  
Nano Tio2 ◽  
Photo Polymerization

Effective carbon sequestration in Italian agricultural soils by in situ polymerization of soil organic matter under biomimetic photocatalysis

2018 ◽  
Vol 29 (3) ◽  
pp. 485-494 ◽  
Author(s):  
Alessandro Piccolo ◽  
Riccardo Spaccini ◽  
Vincenza Cozzolino ◽  
Assunta Nuzzo ◽  
Marios Drosos ◽  
...  
Keyword(s):  
Organic Matter ◽  
Carbon Sequestration ◽  
Soil Organic Matter ◽  
In Situ Polymerization ◽  
Agricultural Soils

Quantifying in situ and modeling net nitrogen mineralization from soil organic matter in arable cropping systems

2017 ◽  
Vol 111 ◽  
pp. 44-59 ◽  
Author(s):  
Hugues Clivot ◽  
Bruno Mary ◽  
Matthieu Valé ◽  
Jean-Pierre Cohan ◽  
Luc Champolivier ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Nitrogen Mineralization ◽  
Cropping Systems ◽  
Net Nitrogen Mineralization ◽  
Quantifying In

Investigating the impact of in situ soil organic matter degradation through porewater spectroscopic analyses on marsh edge erosion

Chemosphere ◽  
2021 ◽  
Vol 268 ◽  
pp. 129266
Author(s):  
Michael P. Hayes ◽  
Yadav Sapkota ◽  
John R. White ◽  
Robert L. Cook
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Organic Matter Degradation ◽  
Marsh Edge ◽  
Spectroscopic Analyses ◽  
The Impact

Soil Organic Matter and Phosphate Sorption on Natural and Synthetic Fe Oxides under in Situ Conditions

2019 ◽  
Vol 53 (22) ◽  
pp. 13081-13087 ◽  
Author(s):  
Kristof Dorau ◽  
Lydia Pohl ◽  
Christopher Just ◽  
Carmen Höschen ◽  
Kristian Ufer ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Phosphate Sorption ◽  
Fe Oxides ◽  
In Situ Conditions ◽  
Natural And Synthetic

scholarly journals In situ near-infrared spectroscopy for soil organic matter prediction in paddy soil, Pasak watershed, Thailand

2018 ◽  
Vol 64 (No. 2) ◽  
pp. 70-75 ◽  
Author(s):  
Romsonthi Chutipong ◽  
Tawornpruek Saowanuch ◽  
Watana Sumitra
Keyword(s):  
Organic Matter ◽  
Infrared Spectroscopy ◽  
Soil Organic Matter ◽  
Soil Properties ◽  
Soil Quality ◽  
Near Infrared Spectroscopy ◽  
Spectral Reflectance ◽  
Near Infrared ◽  
Partial Least Square

Soil organic matter (SOM) is a major index of soil quality assessment because it is one of the key soil properties controlling nutrient budgets in agricultural production systems. The aim of the in situ near-infrared spectroscopy (NIRS) for SOM prediction in paddy area is evaluation of the potential of SOM and prediction of other soil properties. There are keys for soil fertility and soil quality assessments. A spectral reflectance of 130 soil samples was collected by field spectroradiometer in a region of near-infrared. Spectral reflectance collections were processed by the first derivative transformation with the Savitsky-Golay algorithms. Partial least square regression method was used to develop a calibration model between soil properties and spectral reflectance, which was used for prediction and validation processes. Finally, the results of this study demonstrate that NIRS is an effective method that can be used to predict SOM (R<sup>2</sup> = 0.73, RPD (ratio of performance to deviation) = 1.82) and total nitrogen (R<sup>2</sup> = 0.72, RPD = 1.78). Therefore, NIRS is a potential tool for soil properties predictions. The use of these techniques will facilitate the implementation of soil management with a decreasing cost and time of soil study in a large scale. However, further works are necessary to develop more accurate soil properties prediction and to apply this method to other areas.

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