scholarly journals Comparison of Two Methods for Total Inorganic Carbon Estimation in Three Soil Types in Mediterranean Area

Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 409
Author(s):  
Rita Leogrande ◽  
Carolina Vitti ◽  
Mirko Castellini ◽  
Marcello Mastrangelo ◽  
Francisco Pedrero ◽  
...  
Keyword(s):  
Inorganic Carbon ◽  
Quantitative Estimation ◽  
Mediterranean Area ◽  
Soil Types ◽  
Carbonate Content ◽  
Regression Equations ◽  
Total Inorganic Carbon ◽  
Data Set ◽  
Wide Range ◽  
Dry Combustion

The objective of this study was to compare the results of calcimetric and dry combustion methods for quantitative estimation of soil total inorganic carbon (TIC). To this aim, 117 soil samples from three localities in the Mediterranean area (one in Spain and two in Southern Italy), representing a wide range of total inorganic carbon contents (ranging from 1.9 to 54 g 100g−1), were collected. TIC (expressed as CaCO3) was quantified using the volumetric calcimeter method, as reference, and dry combustion in order to find an accurate and rapid method, suitable for different types of soils. The results revealed a concordance between the two methods compared, as shown by the recovery values close to one, for the whole data set and for data grouped per experimental site. Specifically, the dry combustion method showed slightly greater values of TIC compared to volumetric method, probably due to soil acid pretreatments, in dry combustion, and to an incomplete decomposition of carbonates that would require more time for removal, in a calcimeter method. Linear regression equations between the two methods were not affected by different soil types. Overall, our study demonstrated that the dry combustion was a reliable method and could provide accurate estimates of TIC in soils with different calcium carbonate content.

scholarly journals Estimation of the net energy value of barley for finishing beef steers1

2019 ◽  
Vol 3 (4) ◽  
pp. 1550-1560
Author(s):  
Jan G P Bowman ◽  
Darrin L Boss ◽  
Lisa M M Surber ◽  
Tom K Blake
Keyword(s):  
Particle Size ◽  
Bulk Density ◽  
Barley Grain ◽  
Regression Equations ◽  
Animal Performance ◽  
Data Set ◽  
Wide Range ◽  
Development Data ◽  
Laboratory Procedures ◽  
The Mean

Abstract The objective of this study was to identify barley grain characteristics measured by laboratory procedures that could be used to predict barley energy content for finishing beef steers. Twenty-eight different barley genotypes were evaluated including 18 cultivars and 10 experimental lines. Laboratory analysis of barley samples included bulk density, particle size, N, ADF, starch, and ISDMD (in situ DM disappearance after 3 h of ruminal incubation). Animal performance data (BW, DMI, ADG, steer NEm, and NEg requirements) were collected from 26 feedlot experiments conducted in Montana and Idaho during a 10-yr period and were used to estimate barley NEm and NEg content. A total of 80 experimental units were available with each experimental unit being a diet mean from an individual feedlot experiment. Fifty-eight of the 80 experimental units were randomly selected and used in the development data set and the remaining 22 experimental units were used in the validation data set. Forward, backward, and stepwise selection methods were used to identify variables to be included in regression equations for NEm using PROC REG of SAS. Barley samples in the model development data set represented a wide range in concentrations (DM basis): N (1.6% to 2.8%), ISDMD (25.7% to 58.7%), ADF (3.6% to 8.0%), starch (44.1% to 62.4%), particle size (1,100 to 2,814 µm), and bulk density (50.8 to 69.4 kg/hL). The barley grain characteristics of particle size, ISDMD, starch, and ADF were the most important variables in six successful models (R2 = 0.48 to 0.60; P = 0.001). The six prediction equations gave mean predicted values for NEm ranging from 1.99 to 2.05 Mcal/kg (average 2.04 Mcal/kg; 0.45% CV). The mean actual NEm values from animal performance trials ranged from 1.75 to 2.48 Mcal/kg (average 2.03 Mcal/kg; 6.5% CV). The mean bias or difference in predicted vs. actual values ranged from −0.001 to 0.005 Mcal/kg. Barley NEg values calculated from animal performance ranged from 1.13 to 1.78 Mcal/kg (average 1.39 Mcal/kg; 8.4% CV). Average predicted barley NEm and NEg were 0.02 and 0.01 Mcal/kg less, respectively, than the 2.06 Mcal/kg NEm and 1.40 Mcal/kg NEg reported by NRC. Barley NE can be predicted from simple laboratory procedures which will aid plant breeders developing new feed varieties and nutritionists formulating finishing rations for beef cattle.

scholarly journals Methodology for Studying Oxidation of Organic Species in Solution

2000 ◽  
Vol 83 (3) ◽  
pp. 584-587 ◽  
Author(s):  
Susan M Grimes ◽  
Helen C Ngwang
Keyword(s):  
Mass Spectrometry ◽  
Gas Chromatography ◽  
Inorganic Carbon ◽  
Photochemical Oxidation ◽  
Photocatalytic Decomposition ◽  
Gas Chromatography Mass Spectrometry ◽  
Uv Spectrophotometry ◽  
Total Inorganic Carbon ◽  
Organic Species ◽  
Wide Range

Abstract A photoreactor was developed to study products of photochemical oxidation in a wide range of organic compounds. Analysis of the products from the reactor were used to determine the extent of mineralization of the organic material, to characterize any intermediate compounds formed, and to obtain information on the decomposition mechanism. Appropriate methods for separation and characterization include LC, UV spectrophotometry, gas chromatography/mass spectrometry, total organic carbon, and total inorganic carbon. The uses of the reactor are described for the photocatalytic decomposition of phenol and of its major decomposition intermediates 1,2- and 1,4-dihydroxybenzene.

ANALYSIS OF EMPIRICAL COMPRESSION INDEX EQUATIONS USING THE VOID RATIO

2017 ◽  
Vol 4 (1) ◽  
Author(s):  
Amir Al-Khafaji ◽  
Krishnanand Maillacheruvu ◽  
Robert Jacobs
Keyword(s):  
Void Ratio ◽  
New Technique ◽  
Soil Types ◽  
Regression Equations ◽  
Compression Index ◽  
Data Set ◽  
Data Points ◽  
Compression Data ◽  
A New Technique ◽  
Selection Of

A new technique to assess the reliability of published compression index equations in terms of soil void ratio is presented. Several published equations pertaining to different soil types are examined in terms of accuracy and applicability. The new technique employs regression analysis to examine a substantial number of published compression data objectively. The traditional bias inherent in the selection of the number of data points and the range of void ratios for a given regression equation is eliminated. This was made possible by creating ranges for the compression index irrespective of the data set involved. This technique revealed that a strong correlation exists between the slopes and intercepts of all published equations. The slopes and intercepts of the newly developed regression equations were used to compare several well know published equations to assess accuracy and applicability. The proposed technique permits the examination of the authenticity of any published empirical equations relating to the compression index of clay to void ratio.

ANALYSIS OF EMPIRICAL COMPRESSION INDEX EQUATIONS USING THE WATER CONTENT

2017 ◽  
Vol 4 (1) ◽  
Author(s):  
Amir W. Al-Khafaji ◽  
Krishnanand Y. Maillacheruvu ◽  
Melissa Hoerber
Keyword(s):  
Water Content ◽  
Empirical Models ◽  
Soil Types ◽  
Data Sets ◽  
Regression Equations ◽  
Compression Index ◽  
Empirical Formulas ◽  
Wide Range ◽  
Compression Data ◽  
Water Contents

This paper proposes a new method to evaluate the reliability of published empirical formulas in terms of accuracy and applicability to different soil types. Different empirical models are proposed to properly approximate the compression index for a wide range of water contents and soil types. They were developed using a unique technique and a substantial number of published regression equations and compression data. Familiar empirical equations were examined for their reliability in predicting the compression index of clay for any water content. A comparison was made between available and newly-proposed empirical formulas using combined regression data sets compiled independently by several authors. The newly proposed empirical compression index equations are applicable to a wide range of clay soils, and in validating other published relationships. The degree of scatter and variations in the computed compression index values are minimized for any water content.

scholarly journals Two decades of inorganic carbon dynamics along the West Antarctic Peninsula

2015 ◽  
Vol 12 (22) ◽  
pp. 6761-6779 ◽  
Author(s):  
C. Hauri ◽  
S. C. Doney ◽  
T. Takahashi ◽  
M. Erickson ◽  
G. Jiang ◽  
...  
Keyword(s):  
Antarctic Peninsula ◽  
Ocean Circulation ◽  
Inorganic Carbon ◽  
Dissolved Inorganic Carbon ◽  
World Ocean ◽  
Nutrient Utilization ◽  
Total Alkalinity ◽  
Data Set ◽  
Molar Ratios ◽  
Wide Range

Abstract. We present 20 years of seawater inorganic carbon measurements collected along the western shelf and slope of the Antarctic Peninsula. Water column observations from summertime cruises and seasonal surface underway pCO2 measurements provide unique insights into the spatial, seasonal, and interannual variability in this dynamic system. Discrete measurements from depths > 2000 m align well with World Ocean Circulation Experiment observations across the time series and underline the consistency of the data set. Surface total alkalinity and dissolved inorganic carbon data showed large spatial gradients, with a concomitant wide range of Ωarag (< 1 up to 3.9). This spatial variability was mainly driven by increasing influence of biological productivity towards the southern end of the sampling grid and meltwater input along the coast towards the northern end. Large inorganic carbon drawdown through biological production in summer caused high near-shore Ωarag despite glacial and sea-ice meltwater input. In support of previous studies, we observed Redfield behavior of regional C / N nutrient utilization, while the C / P (80.5 ± 2.5) and N / P (11.7 ± 0.3) molar ratios were significantly lower than the Redfield elemental stoichiometric values. Seasonal salinity-based predictions of Ωarag suggest that surface waters remained mostly supersaturated with regard to aragonite throughout the study. However, more than 20 % of the predictions for winters and springs between 1999 and 2013 resulted in Ωarag < 1.2. Such low levels of Ωarag may have implications for important organisms such as pteropods. Even though we did not detect any statistically significant long-term trends, the combination of on\\-going ocean acidification and freshwater input may soon induce more unfavorable conditions than the ecosystem experiences today.

scholarly journals Assessing Non-Photosynthetic Cropland Biomass from Spaceborne Hyperspectral Imagery

2021 ◽  
Vol 13 (22) ◽  
pp. 4711
Author(s):  
Katja Berger ◽  
Tobias Hank ◽  
Andrej Halabuk ◽  
Juan Pablo Rivera-Caicedo ◽  
Matthias Wocher ◽  
...  
Keyword(s):  
Hyperspectral Image ◽  
Quantitative Estimation ◽  
Gaussian Process Regression ◽  
Training Data ◽  
Coefficient Of Determination ◽  
Canopy Reflectance ◽  
Data Set ◽  
Area Index ◽  
Essential Information ◽  
Wide Range

Non-photosynthetic vegetation (NPV) biomass has been identified as a priority variable for upcoming spaceborne imaging spectroscopy missions, calling for a quantitative estimation of lignocellulosic plant material as opposed to the sole indication of surface coverage. Therefore, we propose a hybrid model for the retrieval of non-photosynthetic cropland biomass. The workflow included coupling the leaf optical model PROSPECT-PRO with the canopy reflectance model 4SAIL, which allowed us to simulate NPV biomass from carbon-based constituents (CBC) and leaf area index (LAI). PROSAIL-PRO provided a training database for a Gaussian process regression (GPR) algorithm, simulating a wide range of non-photosynthetic vegetation states. Active learning was employed to reduce and optimize the training data set. In addition, we applied spectral dimensionality reduction to condense essential information of non-photosynthetic signals. The resulting NPV-GPR model was successfully validated against soybean field data with normalized root mean square error (nRMSE) of 13.4% and a coefficient of determination (R2) of 0.85. To demonstrate mapping capability, the NPV-GPR model was tested on a PRISMA hyperspectral image acquired over agricultural areas in the North of Munich, Germany. Reliable estimates were mainly achieved over senescent vegetation areas as suggested by model uncertainties. The proposed workflow is the first step towards the quantification of non-photosynthetic cropland biomass as a next-generation product from near-term operational missions, such as CHIME.

scholarly journals Two decades of inorganic carbon dynamics along the Western Antarctic Peninsula

2015 ◽  
Vol 12 (9) ◽  
pp. 6929-6969 ◽  
Author(s):  
C. Hauri ◽  
S. C. Doney ◽  
T. Takahashi ◽  
M. Erickson ◽  
G. Jiang ◽  
...  
Keyword(s):  
Ocean Acidification ◽  
Interannual Variability ◽  
Antarctic Peninsula ◽  
Ocean Circulation ◽  
Inorganic Carbon ◽  
Dissolved Inorganic Carbon ◽  
World Ocean ◽  
Data Set ◽  
Wide Range ◽  
Melt Water

Abstract. We present 20 years of seawater inorganic carbon measurements collected along the western shelf and slope of the Antarctic Peninsula. Water column observations from summertime cruises and seasonal surface underway pCO2 measurements provide unique insights into the spatial, seasonal and interannual variability of the dynamic system. The discrete measurements from depths > 2000 m align well with World Ocean Circulation Experiment observations across the time-series and underline the consistency of the data set. Analysis shows large spatial gradients in surface alkalinity and dissolved inorganic carbon content, with a concomitant wide range of Ωarag from values < 1 up to 3.9. This spatial variability was mainly driven by increasing influence of biological productivity towards the southern end of the sampling grid and melt water input along the coast towards the northern end. Large inorganic carbon drawdown through biological production in summer caused high near-shore Ωarag despite glacial and sea-ice melt water input. In support of previous studies, we observed Redfield behavior of regional C / N nutrient utilization, while the C / P (80.5 ± 2.5) and N / P (11.7 ± 0.3) molar ratios were significantly lower than the Redfield elemental stoichiometric values. Seasonal predictions of Ωarag suggest that surface waters remained mostly supersaturated with regard to aragonite throughout the study. However, more than a third of the predictions for winters between 1999 and 2013 resulted in Ωarag < 1.3. Such low levels of Ωarag may have implications for important organisms such as pteropods. Despite large interannual variability, surface pCO2 measurements indicate a statistically significant increasing trend of up to 23 μatm per decade in fall and spring and a concomitant decreasing pH, pointing towards first signs of ocean acidification in the region. The combination of ongoing ocean acidification and freshwater input may soon provoke more unfavorable conditions than what the ecosystem experiences today.

ANALYSIS OF EMPIRICAL COMPRESSION INDEX EQUATIONS USING THE LIQUID LIMIT

2015 ◽  
Vol 2 (1) ◽  
Author(s):  
Amir W. Al-Khafaji ◽  
Krishnanand Y. Maillacheruvu ◽  
Matthew Sainz ◽  
Rebecca Neuman
Keyword(s):  
Soil Property ◽  
Liquid Limit ◽  
Empirical Models ◽  
Soil Types ◽  
Data Sets ◽  
Regression Equations ◽  
Compression Index ◽  
Empirical Formulas ◽  
Wide Range ◽  
Compression Data

This paper proposes a new method to evaluate the reliability of published empirical formulas in terms of accuracy and applicability to different soil types. Different empirical models are proposed to properly approximate the compression index for a wide range of liquid limits and soil types. They were developed using a unique Soil Property Line (SPL) developed using a substantial number of published regression equations and compression data. Familiar empirical equations were examined for their reliability in predicting the compression index of clay for any liquid limit. A comparison was made between available and newly-proposed empirical formulas using combined regression data sets compiled independently by several authors. The newly proposed empirical compression index equations are applicable to wide ranges of clay soils, validating other published relationships. The degree of scatter and variations in the computed compression index values are minimized for any liquid limit.

Structure Guided Molecular Docking Assisted Alignment Dependent 3DQSAR Study on Steroidal Aromatase Inhibitors (SAIs) as Anti-breast Cancer Agents

2019 ◽  
Vol 16 (7) ◽  
pp. 808-817 ◽  
Author(s):  
Laxmi Banjare ◽  
Sant Kumar Verma ◽  
Akhlesh Kumar Jain ◽  
Suresh Thareja
Keyword(s):  
Breast Cancer ◽  
Molecular Docking ◽  
Aromatase Inhibitors ◽  
Direct Synthesis ◽  
3D Qsar ◽  
Chemotherapeutic Agents ◽  
Modeling Tools ◽  
Data Set ◽  
Wide Range ◽  
Steroidal Aromatase Inhibitors

Background: In spite of the availability of various treatment approaches including surgery, radiotherapy, and hormonal therapy, the steroidal aromatase inhibitors (SAIs) play a significant role as chemotherapeutic agents for the treatment of estrogen-dependent breast cancer with the benefit of reduced risk of recurrence. However, due to greater toxicity and side effects associated with currently available anti-breast cancer agents, there is emergent requirement to develop target-specific AIs with safer anti-breast cancer profile. Methods: It is challenging task to design target-specific and less toxic SAIs, though the molecular modeling tools viz. molecular docking simulations and QSAR have been continuing for more than two decades for the fast and efficient designing of novel, selective, potent and safe molecules against various biological targets to fight the number of dreaded diseases/disorders. In order to design novel and selective SAIs, structure guided molecular docking assisted alignment dependent 3D-QSAR studies was performed on a data set comprises of 22 molecules bearing steroidal scaffold with wide range of aromatase inhibitory activity. Results: 3D-QSAR model developed using molecular weighted (MW) extent alignment approach showed good statistical quality and predictive ability when compared to model developed using moments of inertia (MI) alignment approach. Conclusion: The explored binding interactions and generated pharmacophoric features (steric and electrostatic) of steroidal molecules could be exploited for further design, direct synthesis and development of new potential safer SAIs, that can be effective to reduce the mortality and morbidity associated with breast cancer.

Integrative Data Analysis from a Unifying Research Synthesis Perspective

2018 ◽  
Author(s):  
Eun-Young Mun ◽  
Anne E. Ray
Keyword(s):  
Data Analysis ◽  
Large Scale ◽  
Research Synthesis ◽  
Alcohol Intervention ◽  
Data Set ◽  
Integrative Data Analysis ◽  
Level Data ◽  
Model Complex ◽  
Wide Range ◽  
Individual Participant

Integrative data analysis (IDA) is a promising new approach in psychological research and has been well received in the field of alcohol research. This chapter provides a larger unifying research synthesis framework for IDA. Major advantages of IDA of individual participant-level data include better and more flexible ways to examine subgroups, model complex relationships, deal with methodological and clinical heterogeneity, and examine infrequently occurring behaviors. However, between-study heterogeneity in measures, designs, and samples and systematic study-level missing data are significant barriers to IDA and, more broadly, to large-scale research synthesis. Based on the authors’ experience working on the Project INTEGRATE data set, which combined individual participant-level data from 24 independent college brief alcohol intervention studies, it is also recognized that IDA investigations require a wide range of expertise and considerable resources and that some minimum standards for reporting IDA studies may be needed to improve transparency and quality of evidence.

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