scholarly journals Predicting Profile Soil Properties with Reflectance Spectra via Bayesian Covariate-Assisted External Parameter Orthogonalization

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3869 ◽  
Author(s):  
Kristen S. Veum ◽  
Paul A. Parker ◽  
Kenneth A. Sudduth ◽  
Scott H. Holan
Keyword(s):  
High Resolution ◽  
Environmental Factors ◽  
Soil Properties ◽  
Bayesian Modeling ◽  
Model Performance ◽  
External Parameter ◽  
Soil Cores ◽  
Bayesian Lasso ◽  
Modeling Techniques

In situ, diffuse reflectance spectroscopy (DRS) profile soil sensors have the potential to provide both rapid and high-resolution prediction of multiple soil properties for precision agriculture, soil health assessment, and other applications related to environmental protection and agronomic sustainability. However, the effects of soil moisture, other environmental factors, and artefacts of the in-field spectral data collection process often hamper the utility of in situ DRS data. Various processing and modeling techniques have been developed to overcome these challenges, including external parameter orthogonalization (EPO) transformation of the spectra. In addition, Bayesian modeling approaches may improve prediction over traditional partial least squares (PLS) regression. The objectives of this study were to predict soil organic carbon (SOC), total nitrogen (TN), and texture fractions using a large, regional dataset of in situ profile DRS spectra and compare the performance of (1) traditional PLS analysis, (2) PLS on EPO-transformed spectra (PLS-EPO), (3) PLS-EPO with the Bayesian Lasso (PLS-EPO-BL), and (4) covariate-assisted PLS-EPO-BL models. In this study, soil cores and in situ profile DRS spectrometer scans were obtained to ~1 m depth from 22 fields across Missouri and Indiana, USA. In the laboratory, soil cores were split by horizon, air-dried, and sieved (<2 mm) for a total of 708 samples. Soil properties were measured and DRS spectra were collected on these air-dried soil samples. The data were randomly split into training (n = 308), testing (n = 200), and EPO calibration (n = 200) sets, and soil textural class was used as the categorical covariate in the Bayesian models. Model performance was evaluated using the root mean square error of prediction (RMSEP). For the prediction of soil properties using a model trained on dry spectra and tested on field moist spectra, the PLS-EPO transformation dramatically improved model performance relative to PLS alone, reducing RMSEP by 66% and 53% for SOC and TN, respectively, and by 76%, 91%, and 87% for clay, silt, and sand, respectively. The addition of the Bayesian Lasso further reduced RMSEP by 4–11% across soil properties, and the categorical covariate reduced RMSEP by another 2–9%. Overall, this study illustrates the strength of the combination of EPO spectral transformation paired with Bayesian modeling techniques to overcome environmental factors and in-field data collection artefacts when using in situ DRS data, and highlights the potential for in-field DRS spectroscopy as a tool for rapid, high-resolution prediction of soil properties.

Comparison of Field and Laboratory VNIR Spectroscopy for Profile Soil Property Estimation

2017 ◽  
Vol 60 (5) ◽  
pp. 1503-1510 ◽  
Author(s):  
Yongjin Cho ◽  
Alexander H. Sheridan ◽  
Kenneth A. Sudduth ◽  
Kristen S. Veum
Keyword(s):  
Soil Properties ◽  
Water Content ◽  
Bulk Density ◽  
Precision Agriculture ◽  
Soil Property ◽  
Soil Cores ◽  
Estimation Errors ◽  
Vnir Spectroscopy ◽  
Dry Soil

Abstract. In-field, in-situ data collection with soil sensors has potential to improve the efficiency and accuracy of soil property estimates. Optical diffuse reflectance spectroscopy (DRS) has been used to estimate important soil properties, such as soil carbon, nitrogen, water content, and texture. Most previous work has focused on laboratory-based visible and near-infrared (VNIR) spectroscopy using dried soil. The objective of this research was to compare estimates of laboratory-measured soil properties from a laboratory DRS spectrometer and an in-situ profile DRS spectrometer. Soil cores were obtained to approximately 1 m depth from treatment blocks representing variability in topsoil depth located at the South Farm Research Center of the University of Missouri. Soil cores were split by horizon, and samples were scanned with the laboratory DRS spectrometer in both field-moist and oven-dried conditions. In-situ profile DRS spectrometer scans were obtained at the same sampling locations. Soil properties measured in the laboratory from the cores were bulk density, total organic carbon (TOC), total nitrogen (TN), particulate organic matter carbon and nitrogen (POM-C and POM-N), water content, and texture fractions. The best estimates of TOC, TN, and bulk density were from the laboratory DRS spectra on dry soil (R2 = 0.94, 0.91, and 0.71, respectively). Estimation errors with the field DRS system were at most 25% higher for these soil properties. For POM-C and POM-N, the field system provided estimates of similar accuracy to the best (dry soil) laboratory measurements. Clay and silt texture fraction estimates were most accurate from laboratory DRS spectra on field-moist soil (R2 = 0.91 and 0.93, respectively). Estimation errors for clay and silt were almost doubled with the field DRS system. Considering the efficiency advantages, in-field, in-situ DRS appears to be a viable alternative to laboratory DRS for TOC, TN, POM-C, POM-N, and bulk density estimates, but perhaps not for soil texture estimates. Keywords: In-situ sensing, Precision agriculture, Reflectance spectra, Soil properties, Soil spectroscopy.

scholarly journals Comparison of high resolution hydrodynamic model outputs with in-situ Argo profiles in the Ionian Sea

2017 ◽  
Vol 18 (1) ◽  
pp. 22 ◽  
Author(s):  
D. KASSIS ◽  
G. KORRES ◽  
A. KONSTANTINIDOU ◽  
L. PERIVOLIOTIS
Keyword(s):  
High Resolution ◽  
Hydrodynamic Model ◽  
Numerical Models ◽  
Regional Scale ◽  
Model Performance ◽  
Temporal Analysis ◽  
In Situ Monitoring ◽  
Ionian Sea ◽  
Nested Models

In-situ monitoring is an essential component for the development of hydrodynamic numerical models. Argo expansion into marginal seas has enabled the advancement of high resolution regional nested models through initialization, assimilation and validation processes. The SANI (Southern Adriatic-Northern Ionian) hydrodynamic model is a regional nested model producing high resolution outputs for the period 2008-2012. For the corresponding time period, 21 free drifting Argo floats recorded Temperature –Salinity (T/S) profiles throughout the region. This study presents the inter-comparison of the two data sets whilst noting interesting aspects of the model performance regarding the representation of the major water masses characteristics of the SANI area. Aside from the inter-comparison in a basin’s scale, a spatio-temporal analysis is also performed. The results indicate an adequate response of the model simulations regarding the basic hydrographic features of the region. Nevertheless, important differences are highlighted mainly in the upper and deep layers of the study area. At a regional scale, inter-annual variability of the model’s performance is observed reflecting the hydrographic changes occurred in the wider area during the study period. Overall, the results present the strong points but also highlight the weaknesses of the model. They also confirm the challenging task of producing high resolution numerical simulations in transitional areas such as the Ionian Sea.

mRNA localization by Electron microscopic in situ hybridization

1991 ◽  
Vol 49 ◽  
pp. 430-431
Author(s):  
J. A. Pollock ◽  
M. Martone ◽  
T. Deerinck ◽  
M. H. Ellisman
Keyword(s):  
Electron Microscopy ◽  
High Resolution ◽  
Nucleic Acids ◽  
Recombinant Dna ◽  
Light And Electron Microscopy ◽  
Electron Microscopic ◽  
High Voltage Electron Microscopy ◽  
Functional Sites ◽  
Voltage Electron

Localization of specific proteins in cells by both light and electron microscopy has been facilitate by the availability of antibodies that recognize unique features of these proteins. High resolution localization studies conducted over the last 25 years have allowed biologists to study the synthesis, translocation and ultimate functional sites for many important classes of proteins. Recently, recombinant DNA techniques in molecular biology have allowed the production of specific probes for localization of nucleic acids by “in situ” hybridization. The availability of these probes potentially opens a new set of questions to experimental investigation regarding the subcellular distribution of specific DNA's and RNA's. Nucleic acids have a much lower “copy number” per cell than a typical protein, ranging from one copy to perhaps several thousand. Therefore, sensitive, high resolution techniques are required. There are several reasons why Intermediate Voltage Electron Microscopy (IVEM) and High Voltage Electron Microscopy (HVEM) are most useful for localization of nucleic acids in situ.

Ultrastructural analysis of the spatial distribution of MRNA

1992 ◽  
Vol 50 (1) ◽  
pp. 552-553
Author(s):  
Gary Bassell ◽  
Robert H. Singer
Keyword(s):  
Electron Microscopy ◽  
Spatial Distribution ◽  
In Situ Hybridization ◽  
High Resolution ◽  
Nucleic Acids ◽  
Colloidal Gold ◽  
Dna Probe ◽  
Nucleotide Analogs ◽  
Gold Particles

We have been investigating the spatial distribution of nucleic acids intracellularly using in situ hybridization. The use of non-isotopic nucleotide analogs incorporated into the DNA probe allows the detection of the probe at its site of hybridization within the cell. This approach therefore is compatible with the high resolution available by electron microscopy. Biotinated or digoxigenated probe can be detected by antibodies conjugated to colloidal gold. Because mRNA serves as a template for the probe fragments, the colloidal gold particles are detected as arrays which allow it to be unequivocally distinguished from background.

High-Resolution Resistance Mapping in SEM

2018 ◽  
Author(s):  
Grigore Moldovan ◽  
Wolfgang Joachimi ◽  
Guillaume Boetsch ◽  
Jörg Jatzkowski ◽  
Frank Altman
Keyword(s):  
Electron Microscopy ◽  
Scanning Electron Microscopy ◽  
High Resolution ◽  
Reference Structure ◽  
Total Resistance ◽  
Embedded Electronics ◽  
Improved Performance ◽  
Mapping Techniques ◽  
Scanning Electron

Abstract This work presents advanced resistance mapping techniques based on Scanning Electron Microscopy (SEM) with nanoprobing systems and the related embedded electronics. Focus is placed on recent advances to reduce noise and increase speed, such as integration of dedicated in situ electronics into the nanoprobing platform, as well as an important transition from current-sensitive to voltagesensitive amplification. We show that it is now possible to record resistance maps with a resistance sensitivity in the 10W range, even when the total resistance of the mapped structures is in the range of 100W. A reference structure is used to illustrate the improved performance, and a lowresistance failure case is presented as an example of analysis made possible by these developments.

scholarly journals Venus: key to understanding the evolution of terrestrial planets

2021 ◽  
Author(s):  
Colin F. Wilson ◽  
Thomas Widemann ◽  
Richard Ghail
Keyword(s):  
High Temperature ◽  
High Resolution ◽  
Radar Imaging ◽  
Space Science ◽  
Interior Surface ◽  
Extended Surface ◽  
Earth Like Planets ◽  
Orbital Mission

AbstractIn this paper, originally submitted in answer to ESA’s “Voyage 2050” call to shape the agency’s space science missions in the 2035–2050 timeframe, we emphasize the importance of a Venus exploration programme for the wider goal of understanding the diversity and evolution of habitable planets. Comparing the interior, surface, and atmosphere evolution of Earth, Mars, and Venus is essential to understanding what processes determined habitability of our own planet and Earth-like planets everywhere. This is particularly true in an era where we expect thousands, and then millions, of terrestrial exoplanets to be discovered. Earth and Mars have already dedicated exploration programmes, but our understanding of Venus, particularly of its geology and its history, lags behind. Multiple exploration vehicles will be needed to characterize Venus’ richly varied interior, surface, atmosphere and magnetosphere environments. Between now and 2050 we recommend that ESA launch at least two M-class missions to Venus (in order of priority): a geophysics-focussed orbiter (the currently proposed M5 EnVision orbiter – [1] – or equivalent); and an in situ atmospheric mission (such as the M3 EVE balloon mission – [2]). An in situ and orbital mission could be combined in a single L-class mission, as was argued in responses to the call for L2/L3 themes [3–5]. After these two missions, further priorities include a surface lander demonstrating the high-temperature technologies needed for extended surface missions; and/or a further orbiter with follow-up high-resolution surface radar imaging, and atmospheric and/or ionospheric investigations.

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