scholarly journals Study on hyperspectral estimation model of soil organic carbon content in the wheat field under different water treatments

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chenbo Yang ◽  
Meichen Feng ◽  
Lifang Song ◽  
Chao Wang ◽  
Wude Yang ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Spectral Reflectance ◽  
Growth Stages ◽  
Organic Carbon Content ◽  
Mathematical Transformation ◽  
First Order ◽  
Differential Transformation ◽  
Mode 2 ◽  
Water Treatments

AbstractHyperspectral remote sensing technology can be used to monitor the soil nutrient changes in a rapid, real-time, and non-destructive manner, which is of great significance to promote the development of precision agriculture. In this paper, 225 soil samples were studied. The effects of different water treatments on soil organic carbon (SOC) content, and the relationship between SOC content and spectral reflectance (350–2500 nm) were studied. 17 kinds of preprocessing algorithm were performed on the original spectral (R), and the five allocation ratios of calibration to verification sets were set. Finally, the model was constructed by partial least squares regression (PLSR). The results showed that the effects of water treatment on SOC content were different in different growth stages of winter wheat. Results of correlation analysis showed that the differential transformation can refine the spectral characteristics, and improve the correlation between SOC content and spectral reflectance. Results of model construction showed that the models constructed by second-order differential transformation were not good. But the ratio of standard deviation to the standard prediction error (RPD) values of the models were constructed by simple mathematical transformation (T0–T5) and first-order differential transformation (T6–T11) can reach more than 1.4. The simple mathematical transformation (T0–T2, T4–T5) and the first-order differential transformation (T6–T10) resulted in the highest RPD in mode 5 and mode 2, respectively. Among all the models, the model of T7 in mode 2 reach the highest accuracy with a RPD value of 1.9861. Therefore, it is necessary to consider the data preprocessing algorithm and allocation ratio in the process of constructing the hyperspectral monitoring model of SOC.

scholarly journals Study on hyperspectral estimation model of soil organic carbon content in the wheat field under different water treatments

2021 ◽  
Author(s):  
Chenbo Yang ◽  
Meichen Feng ◽  
Lifang Song ◽  
Chao Wang ◽  
Wude Yang ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Carbon Content ◽  
Spectral Reflectance ◽  
Organic Carbon Content ◽  
Mathematical Transformation ◽  
First Order ◽  
Soil Organic Carbon Content ◽  
Differential Transformation ◽  
Mode 2

Abstract Hyperspectral remote sensing technology can realize the rapid, real-time, and non-destructive monitoring of soil nutrient changes, which is of great significance to promote the development of precision agriculture. In this paper, 225 soil samples were taken as the research object to study the influence of different water treatment on soil organic carbon content, and the relationship between soil organic carbon content and spectral reflectance. After spectral preprocessing, the hyperspectral monitoring models of SOC content were constructed by partial least squares regression(PLSR) with five different sample allocation ratios of calibration to validation sets. The results showed that the effects of drought stress on SOC content were different in different growth stages of winter wheat. Results of correlation analysis showed that the differential transformation can refine the spectral characteristics and improve the correlation between SOC content and spectral reflectance. Results of model construction showed that the models constructed by second-order differential transformation were not effective, but the RPD values of the models were constructed by simple mathematical transformation(T0-T5) and first-order differential transformation(T6-T11) can reach more than 1.4. The simple mathematical transformation(T0-T2, T4-T5) and the first-order differential transformation(T6-T10) resulted in the highest RPD in mode 5 and mode 2, respectively. Among all the models, the model of T7 in mode 2 reach the highest accuracy with a RPD value of 1.9861. Therefore, it is necessary to consider the data preprocessing algorithm and allocation ratio in the construction of SOC hyperspectral monitoring model.

Regional predictions of soil organic carbon content from spectral reflectance measurements

2009 ◽  
Vol 104 (3) ◽  
pp. 442-446 ◽  
Author(s):  
H. Aïchi ◽  
Y. Fouad ◽  
C. Walter ◽  
R.A. Viscarra Rossel ◽  
Zohra Lili Chabaane ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Carbon Content ◽  
Spectral Reflectance ◽  
Organic Carbon Content ◽  
Soil Organic Carbon Content ◽  
Reflectance Measurements

scholarly journals Phytoavailability of Cd, Cr, Cu, Hg, Mn, Mo, Ni, Pb, Tl and Zn in Arable Crop Systems Amended for 13 to 15 Years with Organic Waste Products

Agronomy ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 664
Author(s):  
Aurélia Marcelline Michaud ◽  
Valérie Sappin-Didier ◽  
Philippe Cambier ◽  
Christophe Nguyen ◽  
Noémie Janot ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Carbon Content ◽  
Organic Waste ◽  
Field Experiments ◽  
Chemical Properties ◽  
Growth Stages ◽  
Organic Carbon Content ◽  
Waste Products ◽  
Soil Organic Carbon Content

Repeated applications of organic waste products (OWP) are a source of trace elements (TE) inputs to agricultural topsoils. The present study aimed at (i) assessing the effects of repeated OWP inputs on the chemical properties of topsoils in two long-term field experiments (13 and 15 years; calcareous and non-calcareous soils), (ii) evaluating TE phytoavailability and their transfer to grain (winter wheat and maize) and (iii) identifying the underlying factors causing alterations of TE phytoavailability. In both field experiments, receiving compliant or slightly high doses of OWP in compliance with regulations, OWP and soil physicochemical properties and TE concentrations in soils and grains were determined. In situ phytoavailability of TE was assessed at two juvenile crop growth stages by analyzing TE concentrations in shoot plantlets. Depending on the OWP input amount, results showed that compared to the soil receiving no organic amendment, repeated OWP inputs significantly increased soil organic carbon content, pH, cation exchange capacity, total soil Cu, Mo and Zn concentration and the phytoavailability of Mo, while the phytoavailability of Cd, Mn, Ni and Tl was significantly reduced. No notable effect was observed for Cr, Cu, Hg, Pb and Zn phytoavailability. Statistical approaches suggested that due to the repeated OWP applications, increased soil organic carbon content and pH, were likely responsible for decreased TE phytoavailability (e.g., Cd).

scholarly journals Soil Organic Carbon Content Prediction Using Soil-Reflected Spectra: A Comparison of Two Regression Methods

2021 ◽  
Vol 13 (23) ◽  
pp. 4752
Author(s):  
Sharon Gomes Ribeiro ◽  
Adunias dos Santos Teixeira ◽  
Marcio Regys Rabelo de Oliveira ◽  
Mirian Cristina Gomes Costa ◽  
Isabel Cristina da Silva Araújo ◽  
...  
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Carbon Content ◽  
Spectral Reflectance ◽  
Arid Region ◽  
Principal Component ◽  
Organic Carbon Content ◽  
Least Squares Regression ◽  
Semi Arid Region ◽  
Semi Arid

Quantifying the organic carbon content of soil over large areas is essential for characterising the soil and the effects of its management. However, analytical methods can be laborious and costly. Reflectance spectroscopy is a well-established and widespread method for estimating the chemical-element content of soils. The aim of this study was to estimate the soil organic carbon (SOC) content using hyperspectral remote sensing. The data were from soils from two localities in the semi-arid region of Brazil. The spectral reflectance factors of the collected soil samples were recorded at wavelengths ranging from 350–2500 nm. Pre-processing techniques were employed, including normalisation, Savitzky–Golay smoothing and first-order derivative analysis. The data (n = 65) were examined both jointly and by soil class, and subdivided into calibration and validation to independently assess the performance of the linear methods. Two multivariate models were calibrated using the SOC content estimated in the laboratory by principal component regression (PCR) and partial least squares regression (PLSR). The study showed significant success in predicting the SOC with transformed and untransformed data, yielding acceptable-to-excellent predictions (with the performance-to-deviation ratio ranging from 1.40–3.38). In general, the spectral reflectance factors of the soils decreased with the increasing levels of SOC. PLSR was considered more robust than PCR, whose wavelengths from 354 to 380 nm, 1685, 1718, 1757, 1840, 1876, 1880, 2018, 2037, 2042, and 2057 nm showed outstanding absorption characteristics between the predicted models. The results found here are of significant practical value for estimating SOC in Neosols and Cambisols in the semi-arid region of Brazil using VIS-NIR-SWIR spectroscopy.

Space-time monitoring of soil organic carbon content across a semi-arid region of Australia

2021 ◽  
Vol 24 ◽  
pp. e00367
Author(s):  
Patrick Filippi ◽  
Stephen R. Cattle ◽  
Matthew J. Pringle ◽  
Thomas F.A. Bishop
Keyword(s):  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Carbon Content ◽  
Arid Region ◽  
Space Time ◽  
Organic Carbon Content ◽  
Soil Organic Carbon Content ◽  
Semi Arid Region ◽  
Semi Arid

scholarly journals Influence of Slope Gradient and Aspect on Soil Organic Carbon Content in the Region of Niš, Serbia

2021 ◽  
Vol 13 (15) ◽  
pp. 8332
Author(s):  
Snežana Jakšić ◽  
Jordana Ninkov ◽  
Stanko Milić ◽  
Jovica Vasin ◽  
Milorad Živanov ◽  
...  
Keyword(s):  
Land Use ◽  
Spatial Distribution ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Slope Aspect ◽  
Available Phosphorus ◽  
Organic Carbon Content ◽  
Slope Gradient ◽  
Phosphorus And Potassium ◽  
Uncultivated Land

Topography-induced microclimate differences determine the local spatial variation of soil characteristics as topographic factors may play the most essential role in changing the climatic pattern. The aim of this study was to investigate the spatial distribution of soil organic carbon (SOC) with respect to the slope gradient and aspect, and to quantify their influence on SOC within different land use/cover classes. The study area is the Region of Niš in Serbia, which is characterized by complex topography with large variability in the spatial distribution of SOC. Soil samples at 0–30 cm and 30–60 cm were collected from different slope gradients and aspects in each of the three land use/cover classes. The results showed that the slope aspect significantly influenced the spatial distribution of SOC in the forest and vineyard soils, where N- and NW-facing soils had the highest level of organic carbon in the topsoil. There were no similar patterns in the uncultivated land. No significant differences were found in the subsoil. Organic carbon content was higher in the topsoil, regardless of the slope of the terrain. The mean SOC content in forest land decreased with increasing slope, but the difference was not statistically significant. In vineyards and uncultivated land, the SOC content was not predominantly determined by the slope gradient. No significant variations across slope gradients were found for all observed soil properties, except for available phosphorus and potassium. A positive correlation was observed between SOC and total nitrogen, clay, silt, and available phosphorus and potassium, while a negative correlation with coarse sand was detected. The slope aspect in relation to different land use/cover classes could provide an important reference for land management strategies in light of sustainable development.

scholarly journals Soil age and soil organic carbon content shape biochemical responses to multiple freeze–thaw events in soils along a postmining agricultural chronosequence

2021 ◽  
Author(s):  
Christoph Rosinger ◽  
Michael Bonkowski
Keyword(s):  
Microbial Biomass ◽  
Organic Carbon ◽  
Soil Organic Carbon ◽  
Carbon Content ◽  
Organic Carbon Content ◽  
Freeze Thaw ◽  
Biochemical Responses ◽  
Microbial Responses ◽  
Soil Age ◽  
Carbon Losses

AbstractFreeze–thaw (FT) events exert a great physiological stress on the soil microbial community and thus significantly impact soil biogeochemical processes. Studies often show ambiguous and contradicting results, because a multitude of environmental factors affect biogeochemical responses to FT. Thus, a better understanding of the factors driving and regulating microbial responses to FT events is required. Soil chronosequences allow more focused comparisons among soils with initially similar start conditions. We therefore exposed four soils with contrasting organic carbon contents and opposing soil age (i.e., years after restoration) from a postmining agricultural chronosequence to three consecutive FT events and evaluated soil biochgeoemical responses after thawing. The major microbial biomass carbon losses occurred after the first FT event, while microbial biomass N decreased more steadily with subsequent FT cycles. This led to an immediate and lasting decoupling of microbial biomass carbon:nitrogen stoichiometry. After the first FT event, basal respiration and the metabolic quotient (i.e., respiration per microbial biomass unit) were above pre-freezing values and thereafter decreased with subsequent FT cycles, demonstrating initially high dissimilatory carbon losses and less and less microbial metabolic activity with each iterative FT cycle. As a consequence, dissolved organic carbon and total dissolved nitrogen increased in soil solution after the first FT event, while a substantial part of the liberated nitrogen was likely lost through gaseous emissions. Overall, high-carbon soils were more vulnerable to microbial biomass losses than low-carbon soils. Surprisingly, soil age explained more variation in soil chemical and microbial responses than soil organic carbon content. Further studies are needed to dissect the factors associated with soil age and its influence on soil biochemical responses to FT events.

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