Neutron-Stimulated Gamma Ray Analysis of Soil

This chapter describes technical aspects of neutron-stimulated gamma ray analysis of soil carbon. The introduction covers general principles, different modifications of neutron-gamma analysis, measurement system configuration, and advantages of this method for soil carbon analysis. Problems with neutron-gamma technology in soil carbon analysis and methods of investigations including Monte-Carlo simulation of neutron interaction with soil elements are discussed further. Based on the investigation results, a method of extracting the “soil carbon net peak” from the raw acquired data was developed. The direct proportional dependency between the carbon net peak area and average carbon weight percent in the upper 10 cm soil layer for any carbon depth profile was shown. Calibration of the measurement system using sand-carbon pits and field measurements of soil carbon are described. Measurement results compared to chemical analysis (dry combustion) data demonstrated good agreement between the two methods. Thus, neutron-stimulated gamma ray analysis can be used for in situ determination of near-surface soil carbon content and is applicable for precision geospatial mapping of soil carbon

Satellite-detected ammonia changes in the United States: Natural or anthropogenic impacts

Ammonia (NH3) is the most abundant alkaline component and can react with atmospheric acidic species to form aerosols that can lead to numerous environmental and health issues. Increasing atmospheric NH3 over agricultural regions in the US has been documented. However, spatiotemporal changes of NH3 concentrations over the entire US are still not thoroughly understood, and the factors that drive these changes remain unknown. Herein, we applied the Atmospheric Infrared Sounder (AIRS) monthly NH3 dataset to explore spatiotemporal changes in atmospheric NH3 and the empirical relationships with synthetic N fertilizer application, livestock manure production, and climate factors across the entire US at both regional and pixel levels from 2002 to 2016. We found that, in addition to the US Midwest, the Mid-South and Western regions also experienced striking increases in NH3 concentrations. NH3 released from livestock manure during warmer winters contributed to increased annual NH3 concentrations in the Western US. The influence of temperature on temporal evolution of NH3 concentrations was associated with synthetic N fertilizer use in the Northern Great Plains. With a strong positive impact of temperature on NH3 concentrations in the US Midwest, this region could possibly become an atmospheric NH3 hotspot in the context of future warming. Our study provides an essential scientific basis for US policy makers in developing mitigation strategies for agricultural NH3 emissions under future climate change scenarios

The mesh is a network of microtubule connectors that stabilizes individual kinetochore fibers of the mitotic spindle

Kinetochore fibers (K-fibers) of the mitotic spindle are force-generating units that power chromosome movement during mitosis. K-fibers are composed of many microtubules that are held together throughout their length. Here we show, using 3D electron microscopy, that K-fiber microtubules are connected by a network of microtubule connectors. We term this network 'the mesh'. The K-fiber mesh is made of linked multipolar connectors. Each connector has up to four struts, so that a single connector can link up to four microtubules. Molecular manipulation of the mesh by overexpression of TACC3 causes disorganization of the K-fiber microtubules. Optimal stabilization of K-fibers by the mesh is required for normal progression through mitosis. We propose that the mesh stabilizes K-fibers by pulling MTs together and thereby maintaining the integrity of the fiber. Our work thus identifies the K-fiber meshwork of linked multipolar connectors as a key integrator and determinant of K-fiber structure and function

Minerals and potentially toxic elements in corn silage from tropical and subtropical Brazil

Copyright: This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Our aim was to assess the mineral composition of corn silages produced in four states of Brazil: Goiás, Minas Gerais, Paraná, and Santa Catarina. In total, seventy-three samples were analyzed. Total element content was extracted by HNO3 and H2O2 microwave-assisted digestion, and inductively coupled plasma-mass spectrometry (ICP-MS) was used to determine concentration. Of the 31 elements analyzed (Ag, Al, As, B, Ba, Be, Ca, Cd, Co, Cr, Cs, Cu, Fe, K, Li, Mg, Mn, Mo, Na, Ni, P, Pb, Rb, S, Se, Sr, Ti, Tl, U, V, and Zn), 21 had concentrations above equipment detection limits. No elements reached the maximum tolerable concentration, but concentrations of Ca (0.14-0.15%), Cu (3.4-5.6 mg kg-1), P (0.13-0.16%), S (0.06-0.08%), and Zn (13-19 mg kg-1) were below the adequate concentration for good nutritional balance. The strong and consistent correlation observed between Fe and Ti in silage samples indicated contamination by soil. Mean concentrations of Cu, Mn, Mo, P, S, and Zn were different among states, and canonic analyses successfully discriminate samples according to their state of origin. Minerals from corn silage should be considered when formulating balanced cattle diets. To ensure silage quality, farmers must adopt strategies that reduce contamination by soil during the ensiling process

Influence of C02 enrichment and nitrogen fertilization on tissue chemistry and carbon allocation in longleaf pine seedlings

One-year old, nursery-grown longleaf pine (Pinus palustris Mill.) seedlings were grown in 45-L pots containing a coarse sandy medium and were exposed to two concentrations of atmospheric CO2 (365 or 720 µmol?1) and two levels of nitrogen (N) fertility (40 or 400 kg N ha?1 yr?1) within open top chambers for 20 months. At harvest, needles, stems, coarse roots, and fine roots were separated and weighed. Subsamples of each tissue were frozen in liquid N, lyophilized at ?50 ?C, and ground to pass a 0.2 mm sieve. Tissue samples were analyzed for carbon (C), N, nonpolar extractives (fats, waxes, and oils = FWO), nonstructural carbohydrates (total sugars and starch), and structural carbohydrates (cellulose, lignin, and tannins). Increased dry weights of each tissue were observed under elevated CO2 and with high N; however, main effects of CO2 were significant only on belowground tissues. The high N fertility tended to result in increased partitioning of biomass aboveground, resulting in significantly lower root to shoot ratios. Elevated CO2 did not affect biomass allocation among tissues. Both atmospheric CO2 and N fertility tended to affect concentration of C compounds in belowground, more than aboveground, tissues. Elevated CO2 resulted in lower concentrations of starch, cellulose, and lignin, but increased concentrations of FWO in root tissues. High N fertility increased the concentration of starch, cellulose, and tannins, but resulted in lower concentrations of lignin and FWO in roots. Differences between CO2 concentrations tended to occur only with high N fertility. Atmospheric CO2 did not affect allocation patterns for any compound; however the high N treatment tended to result in a lower percentage of sugars, cellulose, and lignin belowgroun

Cryoegg: development and field trials of a wireless subglacial probe for deep, fast-moving ice

nnovative technological solutions are required to access and observe subglacial hydrological systems beneath glaciers and ice sheets. Wireless sensing systems can be used to collect and return data without the risk of losing data from cable breakage, which is a major obstacle when studying fast flowing glaciers and other high-strain environments. However, the performance of wireless sensors in deep and fast-moving ice has yet to be evaluated formally. We report experimental results from Cryoegg: a spherical probe that can be deployed along an ice borehole and either remain fixed in place or potentially travel through the subglacial hydrological system. The probe makes measurements in-situ and sends them back to the surface via a wireless link. Cryoegg uses very high frequency (VHF) radio to transmit data through up to 1.3 km of cold ice to a surface receiving array. It measures temperature, pressure and electrical conductivity, returning all data in real time. This transmission uses Wireless M-Bus on 169 MHz; we present a simple “radio link budget” model for its performance in cold ice and confirm its validity experimentally. Power is supplied by an internal battery with sufficient capacity for two measurements per day for up to a year, although higher reporting rates are available at the expense of battery life. Field trials were conducted in 2019 at two locations in Greenland (the EastGRIP borehole and the RESPONDER project site on Sermeq Kujalleq/Store Glacier) and on the Rhone Glacier in Switzerland. Our results from the field demonstrate Cryoegg’s utility in studying englacial channels and moulins, including estimating moulin discharge through salt dilution gauging with the instrument deployed deep within the moulin. Future iterations of the radio system will allow Cryoegg to transmit through up to 2.5 km of ice

Estimating peanut and soybean photosynthetic traits using leaf spectral reflectance and advance regression models

One proposed key strategy for increasing potential crop stability and yield centers on exploitation of genotypic variability in photosynthetic capacity through precise high-throughput phenotyping techniques. Photosynthetic parameters, such as the maximum rate of Rubisco catalyzed carboxylation (V-c,V-max) and maximum electron transport rate supporting RuBP regeneration (J(max)), have been identified as key targets for improvement. The primary techniques for measuring these physiological parameters are very time-consuming. However, these parameters could be estimated using rapid and non-destructive leaf spectroscopy techniques. This study compared four different advanced regression models (PLS, BR, ARDR, and LASSO) to estimate V-c,V-max and J(max) based on leaf reflectance spectra measured with an ASD FieldSpec4. Two leguminous species were tested under different controlled environmental conditions: (1) peanut under different water regimes at normal atmospheric conditions and (2) soybean under high [CO2] and high night temperature. Model sensitivities were assessed for each crop and treatment separately and in combination to identify strengths and weaknesses of each modeling approach. Regardless of regression model, robust predictions were achieved for V-c,V-max (R-2 = 0.70) and J(max) (R-2 = 0.50). Field spectroscopy shows promising results for estimating spatial and temporal variations in photosynthetic capacity based on leaf and canopy spectral propertiesThe authors would like to thank the technical help during the experiment of Mr. Robert Icenogle, Barry Dorman (USDA-ARS), Seth Johnston, and Mary Durstock (Crop Physiology Laboratory, Auburn University). The authors also would like to thank to Dr. Jose A. Jimenez Berni for statistical support to analyze the data. This research was supported by the Action CA17134 SENSECO (Optical Synergies for Spatiotemporal Sensing of Scalable Ecophysiological Traits) funded by COST (European Cooperation in Science and Technology, www.cost.eu).This research was also supported by Auburn University and Alabama Agricultural Experimental Station Seed Grant

Estimating peanut and soybean photosynthetic traits using leaf spectral reflectance and advance regression models

One proposed key strategy for increasing potential crop stability and yield centers on exploitation of genotypic variability in photosynthetic capacity through precise high-throughput phenotyping techniques. Photosynthetic parameters, such as the maximum rate of Rubisco catalyzed carboxylation (Vc,max) and maximum electron transport rate supporting RuBP regeneration (Jmax), have been identified as key targets for improvement. The primary techniques for measuring these physiological parameters are very time-consuming. However, these parameters could be estimated using rapid and non-destructive leaf spectroscopy techniques. This study compared four different advanced regression models (PLS, BR, ARDR, and LASSO) to estimate Vc,max and Jmax based on leaf reflectance spectra measured with an ASD FieldSpec4. Two leguminous species were tested under different controlled environmental conditions: (1) peanut under different water regimes at normal atmospheric conditions and (2) soybean under high [CO2] and high night temperature. Model sensitivities were assessed for each crop and treatment separately and in combination to identify strengths and weaknesses of each modeling approach. Regardless of regression model, robust predictions were achieved for Vc,max (R2 = 0.70) and Jmax (R2 = 0.50). Field spectroscopy shows promising results for estimating spatial and temporal variations in photosynthetic capacity based on leaf and canopy spectral properties

Exploring High Aspect Ratio Gold Nanotubes as Cytosolic Agents: Structural Engineering and Uptake into Mesothelioma Cells.

The generation of effective and safe nanoagents for biological applications requires their physicochemical characteristics to be tunable, and their cellular interactions to be well characterized. Here, the controlled synthesis is developed for preparing high-aspect ratio gold nanotubes (AuNTs) with tailorable wall thickness, microstructure, composition, and optical characteristics. The modulation of optical properties generates AuNTs with strong near infrared absorption. Surface modification enhances dispersibility of AuNTs in aqueous media and results in low cytotoxicity. The uptake and trafficking of these AuNTs by primary mesothelioma cells demonstrate their accumulation in a perinuclear distribution where they are confined initially in membrane-bound vesicles from which they ultimately escape to the cytosol. This represents the first study of the cellular interactions of high-aspect ratio 1D metal nanomaterials and will facilitate the rational design of plasmonic nanoconstructs as cytosolic nanoagents for potential diagnosis and therapeutic applications.BLF-Papworth Fellowship from the British Lung Foundation and the Victor Dahdaleh Foundation