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The following results are related to Rural Digital Europe. Are you interested to view more results? Visit OpenAIRE - Explore.

  • Rural Digital Europe
  • 2023-2023

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Mokgolo , M.J.; Mzezewa , J.;

    An assessment of soil nutrient status based on farmers’ samples was carried out in the Capricorn, Sekhukhune, and Waterberg Districts of the Limpopo Province of South Africa. A total of 336 soil samples were collected and analysed for pH, phosphorus (P), potassium (K), calcium (Ca) and magnesium (Mg). The results showed that the pH of more than 80% of the submitted soil samples was suitable for the production of most field crops ,while less than 20% required liming to make them productive. Phosphorus levels were very low (<8 mg kg-1), with most soils (≥95%) needing P fertilisation to improve crop yields. Potassium was adequate (>250 mg kg-1) for most districts' crops. Between 70% and 74% of soils from Sekhukhune and Waterberg Districts were deficient in Ca (<200 mg kg-1). Magnesium was adequate (>300 mg kg-1) in more than 60% of the analysed samples. Apart from soil pH, all soil properties showed a high degree of variability across all districts. Further studies are needed to investigate the role of field management, crop rotation, field position in the landscape, lithology, and socioeconomic conditions of the farmer on the observed trends of soil nutrients.

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    Authors: Tagliabue, G.; Masseroli, A.; Mattia, M.; Sala, C.; +5 Authors
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Sanderman, Jonathan; Smith, Colleen; Safanelli, José L.; Mitu, Sadia Mannan; +3 Authors

    Up-to-date information on soil properties and the ability to track changes in soil properties over time are critical for improving multiple decisions on soil security at various scales, ranging from global climate change modeling and policy to national level environmental and development planning, to farm and field level resource management. Diffuse reflectance infrared spectroscopy has become an indispensable laboratory tool for the rapid estimation of numerous soil properties to support various soil mapping, soil monitoring, and soil testing applications. Recent advances in hardware technology have enabled the development of handheld sensors with similar performance specifications as laboratory-grade near-infrared (NIR) spectrometers. Here, we've compiled a hand-held NIR spectral library (1350-2550 nm) using the NeoSpectra Handheld NIR Analyzer developed by Si-Ware. Each scanner is fitted with Fourier-Transform technology based on the semiconductor Micro Electromechanical Systems (MEMS) manufacturing technique, promising accuracy, and consistency between devices. This library includes 2,106 distinct mineral soil samples scanned across 9 of these portable low-cost NIR spectrometers (indicated by serial no). 2,016 of these soil samples were selected to represent the diversity of mineral soils found in the United States, and 90 samples were selected across Ghana, Kenya, and Nigeria. 519 of the US samples were selected and scanned by Woodwell Climate Research Center. These samples were queried from the USDA NRCS NSSC-KSSL Soil Archives as having a complete set of eight measured properties (TC, OC, TN, CEC, pH, clay, sand, and silt). They were stratified based on the major horizon and taxonomic order, omitting the categories with less than 500 samples. Three percent of each stratum (i.e., a combination of major horizon and taxonomic order) was then randomly selected as the final subset retrieved from KSSL's physical soil archive as 2-mm sieved samples. The remaining 1,604 US samples were queried from the USDA NRCS NSSC-KSSL Soil Archives by the University of Nebraska - Lincoln to meet the following criteria: Lower depth <= 30 cm, pH range 4.0 to 9.5, Organic carbon <10%, Greater than lower detection limits, Actual physical samples available in the archive, Samples collected and analyzed from 2001 onwards, Samples having complete analyses for high-priority properties (Sand, Silt, Clay, CEC, Exchangeable Ca, Exchangeable Mg, Exchangeable K, Exchangeable Na, CaCO3, OC, TN), & MIR scanned. All samples were scanned dry 2mm sieved. ~20g of sample was added to a plastic weighing boat where the NeoSpectra scanner would be placed down to make direct contact with the soil surface. The scanner was gently moved across the surface of the sample as 6 replicate scans were taken. These replicates were then averaged so that there is one spectra per sample per scanner in the resulting database. The repository contains: Neospectra_database_column_names.csv: describes the variables (columns) of site and soil data, and the range of NIR and MIR spectra. Both Neospectra_WoodwellKSSL_avg and Neospectra_WoodwellKSSL_reps share the same columns. The CSV is composed of the file name, column name, type, example, and description with measurement unit. Neospectra_project_summary.txt: the summary of the project with purpose, the origin of soil samples, instrumentation, and brief SOP. Neospectra_WoodwellKSSL_avg_MIR.csv: the equivalent MIR spectra of neospectra samples' list that was fetched from the KSSL database and formatted to the OSSL specifications. Neospectra_WoodwellKSSL_avg_soil+site+NIR.csv: soil, site, and Neospectra's NIR. Each row contains the averaged spectra for a given scanner and soil sample (1 spectra per scanner per soil sample). Soil and site info is filled within the same soil sample. Neospectra_WoodwellKSSL_reps_soil+site+NIR.csv: soil, site, and Neospectra's NIR. Each row contains one replicated spectra of a given scanner (6 repeats per scanner per soil sample). Soil and site info is filled within the same soil sample. We thank the USDA NRCS National Soil Survey Center for providing access to their soil archives and for continuing to promote the use of soil spectroscopy. This project was funded by USDA National Institute of Food and Agriculture Award # 2020-67021-32467; USDA National Institute of Food and Agriculture Award # 2018-67007-28529; Woodwell Fund for Climate Solutions; and Foodshot Global.

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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: Datacite
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Dataset . 2023
      License: CC BY
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: Datacite
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      ZENODO
      Dataset . 2023
      License: CC BY
      Data sources: ZENODO
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  • Authors: Waichayanee Manatthammakul, Natthapol Chittamart;

    Khon Kaen Agriculture Journal, 51, 4, 634-647

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    Authors: Lã, Otavio R.; Azevedo, Caroline C. de; Barra, Cristina M.; Netto-Ferreira, Julia B.; +2 Authors

    The determination of total organic carbon in soils, fertilizers, sewage sludge, sediments, and humic extracts is widely performed by chemical oxidation methods with K2Cr2O7. The Yeomans-Bremner (YB) method is currently the one that stands out the most. The drawback of these methods is the large amount of concentrated H2SO4 used, which generates a large amount of hazardous waste. This work proposes using KMnO4 as an alternative to K2Cr2O7 for a lower consumption of H2SO4. The method uses the back titration of Fe2+ added to consume both the MnO2 produced and the excess KMnO4 that was not consumed in the OM oxidation. A non-trivial and yet not explored stoichiometry was applied for this purpose, providing a success not yet achieved in using permanganate to determine TOC by titration. The ideal condition for the oxidation of OC was determined by the analysis of a potassium hydrogen phthalate standard and involved the use of 0.125 mol L-1 H2SO4 and temperature of 70 °C, obtaining a significant advantage over the YB method (concentrated H2SO4 and 170 °C). The proposed method was applied to the analysis of soil samples, producing conversion factors for soil organic carbon that varied between 0.652 and 1.12.

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  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Authors: Giulia Tagliabue; Cristina Cattaneo; Luca Trombino;

    Many studies have shown how Environmental Sciences can contribute to the forensic and medico-legal investigations on murder and body concealment dynamics. Nonetheless, most of the research is generally limited to botanical, entomological and anthropological fields leaving out the observation of the active interaction between a decomposing body and the surrounding environment, such as soil. Indeed, a clandestine grave can destroy the valuable forensic evidence as well as prevent the identification of the offender or the victim itself and even the determination of the post-mortem interval (PMI), post-burial interval (PBI) and, overall, the dynamics of the crime act. Therefore, the present experiment, built on the basis of a previous pioneer project carried out in the same area between 2009 and 2011, will be based on the re-enactment of real cases of body disposal, consisting in a combination of multiple methods of concealment, all of them including the inhumation of the remains in a woodland setting. It will consist of the excavation of 32 burials, all dug on the same day, at a depth between 40 and 60 cm involving just as many piglet cadavers (Sus scrofa) weighing between 3 and 5 kg. They will be divided into four different groups, each of which will undergo peculiar treatments: eight will be buried naked; eight clothed; eight will be buried in quicklime and the last eight will be previously hurt. The experiment will be conducted for a total of 730 days and the exhumations of the specimens will be performed in eight increasing time intervals, to achieve different PBIs for each group of subjects (15, 30, 60, 120, 240, 365, 545 and 730 days). At the time of each exhumation biological material, commodities and soil will be sampled and investigated from a geochemical, microscopic (polarizing microscope) and ultramicroscopic (SEM-EDS) point of view, aiming to underline any evidence of mutual exchange of material between the different substrates, as well as any symptom of disturbance, both biochemical and mechanical. As focusing on a multidisciplinary approach, not only this study will allow to reach a standardization for the right reading of trace evidence in real cases of clandestine burials inquiry, but it also will contribute to draw up some guidelines for the exploitation of the parameters registered by the geopedological analytical techniques, which have been neglected for years in the forensic and medico-legal context.

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    https://doi.org/10.5194/egusph...
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  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Authors: Tagliabue, G.; Masseroli, A.; Mattia, M.; Sala, C.; +6 Authors
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    Authors: Yost, Matt; Cardon, Grant; Baker, Megan; Gale, Jody; +6 Authors

    This fact sheet provides updated guidelines for soil sampling of various soil properties and includes why, how, what, and where to sample. It is a part of a series of updated sampling guidelines. Water, forage, plant tissue, and manure/compost will be forthcoming.

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    DigitalCommons@USU
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    Authors: Mano*,Raquel; Rebelo,Fernanda;

    The main objective of this work was to obtain updated data from soil fertility laboratories located in Portugal. A survey was sent to the Heads of 32 laboratories and a reply was received from 25 of them. 14 of these labs belong to the Ministry of Education, 7 are private and 4 to the Ministry of Agriculture. In addition to soil they also analyse plant material and, the majority, organic soil improver and irrigation water. In the minimum package of analyses they offer (Summary Analysis) pH, organic matter, extractable phosphorus and potassium are always included and 72 % of them also include field texture. But this package differs greatly between labs with regard to the inclusion of other parameters. 76 % of the labs issue fertilisation recommendations, but only 20 % do so automatically. There is a relative homogeneity of methods for the parameters of the summary analysis, except for organic matter. Only two laboratories have accredited tests. The existence of a national interlaboratory test is felt to be important for internal quality control and harmonisation of methodologies. Revista de Ciências Agrárias, Vol. 45 N.º 4 (2022)

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    Authors: Demattê, José A. M.; Novais, Jean Jesus; Rosin, Nicolas Augusto; Rosas, Jorge T. F.; +3 Authors

    Abstract: NEW VERSION V.002 (Some Lat Long Coordinates added). Soil spectroscopy has emerged as a solution to the limitations associated with traditional soil surveying and analysis methods, addressing the challenges of time and financial resources. Analyzing the soil's spectral reflectance enables to observe the soil composition and simultaneously evaluate several attributes because the matter, when exposed to electromagnetic energy, leaves a "spectral signature" that makes such evaluations possible. The Soil Spectral Library (SSL) consolidates soil spectral patterns from a specific location, facilitating accurate modeling and reducing time, cost, chemical products, and waste in surveying and mapping processes. Therefore, an open access SSL benefits society by providing a fine collection of free data for multiple applications for both research and commercial use. BSSL Description and Usefulness The Brazilian Soil Spectral Library (BSSL), available at https://bibliotecaespectral.wixsite.com/english, is a comprehensive repository of soil spectral data. Coordinated by JAM Demattê and managed by the GeoCiS research group, the BSSL was initiated in 1995 and published by Demattê and collaborators in 2019. This initiative stands out due to its coverage of diverse soil types, given Brazil's significance in the agricultural and environmental domains and its status as the fifth largest territory in the world (IBGE, 2023). In addition, a Middle Infrared (MIR) dataset has been published (Mendes et al., 2022), part of which is included in this repository. The database covers 16,084 sites and includes harmonized physicochemical and spectral (Vis-NIR-SWIR and MIR range) soil data from various sources at 0-20 cm depth. All soil samples have Vis-NIR-SWIR data, but not all have MIR data. The BSSL provides open and free access to curated data for the scientific community and interested individuals. Unrestricted access to the BSSL supports researchers in validating their results by comparing measured data with predicted values. This initiative also facilitates the development of new models and the improvement of existing ones. Moreover, users can employ the library to test new models and extract information about previously unknown soil properties. With its extensive coverage of tropical soil classes, the BSSL is considered one of the most significant soil spectral libraries worldwide, with 42 institutions and 61 researchers participating. However, 47 collaborators from 29 institutions have authorized the data opening. Other researchers can also provide their data upon request through the coordinator of this initiative. The data from the BSSL project can also help wet labs to improve their analytical capabilities, contributing to developing hybrid wet soil laboratory techniques and digital soil maps while informing decision-makers in formulating conservation and land use policies. The soil's capacity for different land uses promotes soil health and sustainability. Coverage The BSSL data covers all regions of Brazil, including 26 states and the Federal District. It is in a .xlsx format and has a total size of 305 Mb. The table is structured in sheets with rows for observations, and columns, representing various soil attributes in the surface layer, from 0 to 20 cm depth. The database includes environmental and physicochemical properties (22 columns and 16,084 rows), Vis-NIR-SWIR spectral bands (2151 columns and 16,084 rows), and MIR channels (681 columns and 1783 rows). An ID unique column can merge the sheet for each attribute or spectral range. Accessing original data source Using these data requires their reference in any situation under copyright infringement penalty. Three mechanisms are available for users to reach the original and complete data contributors: a) Refer to sheet two for name and code-based searches; b) Visit the website https://bibliotecaespectral.wixsite.com/english/lista-de-cedentes or locate the contributors' list by Brazilian state; c) Visit the website of the Brazilian Soil Spectral Service – Braspecs http://www.besbbr.com.br/, an online platform for soil analysis that uses part of the current SSL (Demattê et al., 2022) - It was developed and managed by GeoCiS. There, owners from all over the country can be found. Proceeding to data analysis We registered and organized the samples at the ESALQ/USP Soil Laboratory. Some samples arrived without preliminary data analyses, so we analyzed them for soil organic matter (SOM), granulometry, cation exchange capacity (CEC), pH in water, and the presence of Ca, Mg, and Na, following the recommendations of Donagemma et al. (2011). The GeoCiS research group performed spectral analyses following the procedures described by Bellinaso et al. (2010). Demattê et al. (2019) provide detailed methods for sampling, preparation, and soil analyses, including reflectance spectroscopy. Latitude and longitude data can be requested directly from the data owner. In summary, the following steps are involved in data acquisition. a) We subjected the soil samples to a preliminary treatment, which involved drying them in an oven at 45°C for 48 hours, grinding them, and sieving them through a 2mm mesh; b) We placed the samples in Petri dishes with a diameter of 9 cm and a height of 1.5 cm; c) We homogenized and flattened the surface of the samples to reduce the shading caused by larger particles or foreign bodies, making them ready for spectral readings; d) The spectral analyses took place in a darkened room to avoid interference from natural light. We used a computer to record the electromagnetic pulses through an optical fiber connected to the sensor, capturing the spectral response of the soil sample; e) We obtained reflectance data in the Visible-Near Infrared-Shortwave Infrared (Vis-NIR-SWIR) range using a FieldSpec 3 spectroradiometer (Analytical Spectral Devices, ASD, Boulder, CO), which operates in the spectral range from 350 to 2500 nm; f) The sensor had a spectral resolution of 3 nm from 350-700 nm and 10 nm from 700-2500 nm, automatically interpolated to 1 nm spectral resolution in the output data, resulting in 2151 channels (or bands); and g) We positioned the lamps at 90° from each other and 35 cm away from the sample, with a zenith angle of 30°. The sensor captured the light reflected through the fiber optic cable, which was positioned 8 cm from the sample's surface. We used two 50W halogen lamps as the power source for the artificial light. It's important to note that we took three readings for each sample at different positions by rotating the Petri dish by 90°. Each reading represents the average of 100 scans taken by the sensor. From these three readings, we calculated the final spectrum of the samples. Notably, the laboratory's equipment and procedures for soil sample spectral analyses followed the ASD's recommendations, particularly about sensor calibration using a white spectralon plate as a 100% reflectance standard. For the analysis in the Middle Infrared (MIR) spectral region, we followed the procedures outlined by Mendes et al. (2022). We milled the soil fraction smaller than 2 mm, sieved it to 0.149 mm, and scanned it using a Fourier Transform Infrared (FT-IR) alpha spectroradiometer (Bruker Optics Corporation, Billerica, MA 01821, USA) equipped with a DRIFT accessory. The spectroradiometer measured the diffuse reflectance using Fourier transformation in the spectral range from 4000 cm-1 to 600 cm-1, with a resolution of 2 cm-1. We conducted these measurements in the Geotechnology Laboratory of the Department of Soil Science at Esalq-USP. We took the average of 32 successive readings to obtain a soil spectrum. Sensor calibration took place before each spectral acquisition of the sample set by standardizing it against the maximum reflectance of a gold plate. Dataset characterization The database, named BSSL_DB_Key_Soils, has five sheets containing the key soil attributes, Vis-NIR-SWIR and MIR datasets, descriptions of the contributors and the proximal sensing methods used for spectral soil analysis. The sheets can be linked by "ID_Unique" columns, which bring the corresponding rows according to the data type. Some cells are empty because collaborators have already provided data in this way. However, we have decided to keep them in the database because they have other soil key attributes. Every Column in the data sheets is described as follows: Sheet 1. BSSL_Soil_Attributes_Dataset Column 1. ID_unique: Sequential code assigned to every record; Column 2. Owner code: Acronym assigned to each contributor who allowed access to their proprietary data; Column 3. Vis_NIR_SWIR_availability: availability of spectral data in visible, near-infrared, and shortwave infrared ranges; Column 4. MIR_availability: availability of spectral data in the middle infrared range; Column 5. Sampling: type of soil sampling; Column 6. Depth_cm: soil surface layer depth in centimeters; Column 7. Lat: Latitude; Column 8. Lat: Longitude; Column 9. Region: Brazilian geographical region of samples' source; Column 10. Municipality: Brazilian municipality of samples' source; Column 11. State: Brazilian Federation Unit of samples' source; Column 12. Vegetation: type of vegetal covering; Column 13. Biome: groupings of ecosystems that share similar characteristics and span different regions; Column 14. Geology: type of rock matter from local soil sampling; Column 15. Sand_gkg: Content of the soil fraction with grain size between 2 and 0.053 mm, expressed in grams per kilogram; Column 16. Clay_gkg: Content of soil fraction with grain size smaller than 0.002 mm, expressed in grams per kilogram; Column 17. SOM_gkg: Soil organic matter content, expressed in grams per kilogram; Column 18. pH_H2O: Soil hydrogen ion potential measured in water; Column 19. Ca_mmolkg: Exchangeable calcium content in the soil, expressed in millimoles per kilogram; Column 20. Mg_mmolkg: Exchangeable magnesium content in the soil, expressed in millimoles per kilogram; Column 21. Na_mmolkg: Exchangeable sodium content in the soil, expressed in millimoles per kilogram; and Column 22. CEC_Ph7_mmolkg: Cation exchange capacity of the soil at neutral pH, expressed in millimoles per kilogram. Sheet 2. BSSL_Vis_NIR_SWIR_Dataset Column 1. ID_Unique: Sequential code assigned to every record; Column 2. Owner code: Acronym assigned to each contributor who allowed access to their proprietary data; and Column 3 – 2153. 350 – 2500: Reflectance in 2151 spectral bands in nanometers from visible and near-infrared to shortwave infrared range (350 – 2500 nm). Sheet 3. BSSL_MIR_Dataset Column 1. ID_Unique: Sequential code assigned to every record; Column 2. Owner_code: Acronym assigned to each contributor who allowed access to their proprietary data; and Column 3 – 683. 4000 – 600: Reflectance in 681 spectral bands in centimeters in the middle infrared range (4000 – 600 cm-1). Sheet 4. Contributors Column 1. Owner_code: Acronym assigned to each contributor who allowed access to their proprietary data, which identifies and links it to datasets; Column 2. Owner: Name of the collaborator who agreed to the availability of the data; Column 3. E-mail: Contact the e-mail of the owner for more information or a data request; Column 4. Institution: Contributor's affiliation; Column 5. Samples NIR: Number of Vis-NIR-SWIR samples sent to the BSSL collection; Column 6. Samples MIR: Number of MIR samples sent to the BSSL collection; Sheet 5. Metadata Column 1. Material and Methods: Description of procedures performed for soil data analyses Expectation and Social Relevance These data can impact various disciplines such as soil surveying, soil attribute mapping, soil analysis, soil mineralogy, soil management zones, precision agriculture, development of new datasets and scientific groups, and others. We expect this contribution to be valuable and useful to the soil research community in promoting this non-renewable natural resource's conservation and sustainable use. {"references": ["DEMATT\u00ca, J. A. M.; DOTTO, A. C.; PAIVA, A. F. S.; SATO, M. V.; DALMOLIN, R. S. D.; ARA\u00daJO, M. do S. B.; \u2026 NORONHA, N. C. (2019). The Brazilian Soil Spectral Library (BSSL): A general view, application and challenges. Geoderma, 113793. doi:10.1016/j.geoderma.2019.05.043.", "DEMATT\u00ca, J. A. M.; PAIVA, A. F. S.; POPPIEL, R. R.; ROSIN, N. A.; RUIZ, L. F. C.; MELLO, F. A. O.; MINASNY, B. \u2026 SILVERO, N. E. Q. The Brazilian Soil Spectral Service (BraSpecS): A User-Friendly System for Global Soil Spectra Communication. Remote Sensing. 2022, 14, 740. https://doi.org/10.3390/rs14061459", "MENDES, W. S.; DEMATT\u00ca, J.A.M.; ROSIN, N. A.; TERRA, F. S.; POPPIEL, R. R.; URBINA-SALAZAR, D.F.; BOECHAT, C. L.; SILVA, E. B.; CURI, N.; SILVA, S. H. G.; SANTOS, U. J.; VALLADARES, G. S. 2022. The Brazilian soil Mid-infrared Spectral Library: The Power of the Fundamental Range. Geoderma, V. 415, 2022, 115776, doi:10.1016/j.geoderma.2022.115776", "IBGE. Brasil em s\u00edntese: Territ\u00f3rio. Rio de Janeiro: Instituto Brasileiro de Geografia e Estat\u00edstica. 2021. Available in: https://brasilemsintese.ibge.gov.br/territorio/dados-geograficos.html accessed in July 1 2023", "DONAGEMMA, G.K., CAMPOS, D.V.B. DE, CALDERANO, S.B., TEIXEIRA, W.G., VIANA, J.H.M., 2011. Manual de m\u00e9todos de an\u00e1lise de solo, 2 rev. ed, Embrapa Solos.", "BELLINASO, H., DEMATT\u00ca, J.A.M., ROMEIRO, S.A., 2010. Soil spectral library and its use in soil classification. Revista Brasileira de Ci\u00eancia Solo 34, 861\u2013870. https://doi.org/10.1590/S0100-06832010000300027"]} Acknowledgments Geotechnologies in Soil Sciences Research Group - GeoCiS Brazilian Society of Soil Science - SBCS Research Support Foundation of the State of São Paulo - FAPESP grant number #2021/05129-8 Higher Education Personal Improvement Coordination - CAPES National Council for Scientific and Technological Development CNPq Department of Soil Science, Luiz de Queiroz College of Agriculture, University of São Paulo. Grupo de Pesquisa Geotecnologias em Ciências do Solo - GeoCiS Sociedade Brasileira de Ciência do Solo - SBCS Fundação de Amparo à Pesquisa do Estado de São Paulo - FAPESP (#2021/05129-8) Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES Conselho Nacional de Desenvolvimento Científico e Tecnológico CNPq Departamento de Ciência do Solo, Escola Superior de Agricultura Luiz de Queiroz, Universidade de São Paulo.

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    Authors: Mokgolo , M.J.; Mzezewa , J.;

    An assessment of soil nutrient status based on farmers’ samples was carried out in the Capricorn, Sekhukhune, and Waterberg Districts of the Limpopo Province of South Africa. A total of 336 soil samples were collected and analysed for pH, phosphorus (P), potassium (K), calcium (Ca) and magnesium (Mg). The results showed that the pH of more than 80% of the submitted soil samples was suitable for the production of most field crops ,while less than 20% required liming to make them productive. Phosphorus levels were very low (<8 mg kg-1), with most soils (≥95%) needing P fertilisation to improve crop yields. Potassium was adequate (>250 mg kg-1) for most districts' crops. Between 70% and 74% of soils from Sekhukhune and Waterberg Districts were deficient in Ca (<200 mg kg-1). Magnesium was adequate (>300 mg kg-1) in more than 60% of the analysed samples. Apart from soil pH, all soil properties showed a high degree of variability across all districts. Further studies are needed to investigate the role of field management, crop rotation, field position in the landscape, lithology, and socioeconomic conditions of the farmer on the observed trends of soil nutrients.

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    Authors: Tagliabue, G.; Masseroli, A.; Mattia, M.; Sala, C.; +5 Authors
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    Authors: Sanderman, Jonathan; Smith, Colleen; Safanelli, José L.; Mitu, Sadia Mannan; +3 Authors

    Up-to-date information on soil properties and the ability to track changes in soil properties over time are critical for improving multiple decisions on soil security at various scales, ranging from global climate change modeling and policy to national level environmental and development planning, to farm and field level resource management. Diffuse reflectance infrared spectroscopy has become an indispensable laboratory tool for the rapid estimation of numerous soil properties to support various soil mapping, soil monitoring, and soil testing applications. Recent advances in hardware technology have enabled the development of handheld sensors with similar performance specifications as laboratory-grade near-infrared (NIR) spectrometers. Here, we've compiled a hand-held NIR spectral library (1350-2550 nm) using the NeoSpectra Handheld NIR Analyzer developed by Si-Ware. Each scanner is fitted with Fourier-Transform technology based on the semiconductor Micro Electromechanical Systems (MEMS) manufacturing technique, promising accuracy, and consistency between devices. This library includes 2,106 distinct mineral soil samples scanned across 9 of these portable low-cost NIR spectrometers (indicated by serial no). 2,016 of these soil samples were selected to represent the diversity of mineral soils found in the United States, and 90 samples were selected across Ghana, Kenya, and Nigeria. 519 of the US samples were selected and scanned by Woodwell Climate Research Center. These samples were queried from the USDA NRCS NSSC-KSSL Soil Archives as having a complete set of eight measured properties (TC, OC, TN, CEC, pH, clay, sand, and silt). They were stratified based on the major horizon and taxonomic order, omitting the categories with less than 500 samples. Three percent of each stratum (i.e., a combination of major horizon and taxonomic order) was then randomly selected as the final subset retrieved from KSSL's physical soil archive as 2-mm sieved samples. The remaining 1,604 US samples were queried from the USDA NRCS NSSC-KSSL Soil Archives by the University of Nebraska - Lincoln to meet the following criteria: Lower depth <= 30 cm, pH range 4.0 to 9.5, Organic carbon <10%, Greater than lower detection limits, Actual physical samples available in the archive, Samples collected and analyzed from 2001 onwards, Samples having complete analyses for high-priority properties (Sand, Silt, Clay, CEC, Exchangeable Ca, Exchangeable Mg, Exchangeable K, Exchangeable Na, CaCO3, OC, TN), & MIR scanned. All samples were scanned dry 2mm sieved. ~20g of sample was added to a plastic weighing boat where the NeoSpectra scanner would be placed down to make direct contact with the soil surface. The scanner was gently moved across the surface of the sample as 6 replicate scans were taken. These replicates were then averaged so that there is one spectra per sample per scanner in the resulting database. The repository contains: Neospectra_database_column_names.csv: describes the variables (columns) of site and soil data, and the range of NIR and MIR spectra. Both Neospectra_WoodwellKSSL_avg and Neospectra_WoodwellKSSL_reps share the same columns. The CSV is composed of the file name, column name, type, example, and description with measurement unit. Neospectra_project_summary.txt: the summary of the project with purpose, the origin of soil samples, instrumentation, and brief SOP. Neospectra_WoodwellKSSL_avg_MIR.csv: the equivalent MIR spectra of neospectra samples' list that was fetched from the KSSL database and formatted to the OSSL specifications. Neospectra_WoodwellKSSL_avg_soil+site+NIR.csv: soil, site, and Neospectra's NIR. Each row contains the averaged spectra for a given scanner and soil sample (1 spectra per scanner per soil sample). Soil and site info is filled within the same soil sample. Neospectra_WoodwellKSSL_reps_soil+site+NIR.csv: soil, site, and Neospectra's NIR. Each row contains one replicated spectra of a given scanner (6 repeats per scanner per soil sample). Soil and site info is filled within the same soil sample. We thank the USDA NRCS National Soil Survey Center for providing access to their soil archives and for continuing to promote the use of soil spectroscopy. This project was funded by USDA National Institute of Food and Agriculture Award # 2020-67021-32467; USDA National Institute of Food and Agriculture Award # 2018-67007-28529; Woodwell Fund for Climate Solutions; and Foodshot Global.

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    ZENODO
    Dataset . 2023
    License: CC BY
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    ZENODO
    Dataset . 2023
    License: CC BY
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    ZENODO
    Dataset . 2023
    License: CC BY
    Data sources: ZENODO
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      ZENODO
      Dataset . 2023
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      Dataset . 2023
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  • Authors: Waichayanee Manatthammakul, Natthapol Chittamart;

    Khon Kaen Agriculture Journal, 51, 4, 634-647

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    Authors: Lã, Otavio R.; Azevedo, Caroline C. de; Barra, Cristina M.; Netto-Ferreira, Julia B.; +2 Authors

    The determination of total organic carbon in soils, fertilizers, sewage sludge, sediments, and humic extracts is widely performed by chemical oxidation methods with K2Cr2O7. The Yeomans-Bremner (YB) method is currently the one that stands out the most. The drawback of these methods is the large amount of concentrated H2SO4 used, which generates a large amount of hazardous waste. This work proposes using KMnO4 as an alternative to K2Cr2O7 for a lower consumption of H2SO4. The method uses the back titration of Fe2+ added to consume both the MnO2 produced and the excess KMnO4 that was not consumed in the OM oxidation. A non-trivial and yet not explored stoichiometry was applied for this purpose, providing a success not yet achieved in using permanganate to determine TOC by titration. The ideal condition for the oxidation of OC was determined by the analysis of a potassium hydrogen phthalate standard and involved the use of 0.125 mol L-1 H2SO4 and temperature of 70 °C, obtaining a significant advantage over the YB method (concentrated H2SO4 and 170 °C). The proposed method was applied to the analysis of soil samples, producing conversion factors for soil organic carbon that varied between 0.652 and 1.12.

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    Authors: Giulia Tagliabue; Cristina Cattaneo; Luca Trombino;

    Many studies have shown how Environmental Sciences can contribute to the forensic and medico-legal investigations on murder and body concealment dynamics. Nonetheless, most of the research is generally limited to botanical, entomological and anthropological fields leaving out the observation of the active interaction between a decomposing body and the surrounding environment, such as soil. Indeed, a clandestine grave can destroy the valuable forensic evidence as well as prevent the identification of the offender or the victim itself and even the determination of the post-mortem interval (PMI), post-burial interval (PBI) and, overall, the dynamics of the crime act. Therefore, the present experiment, built on the basis of a previous pioneer project carried out in the same area between 2009 and 2011, will be based on the re-enactment of real cases of body disposal, consisting in a combination of multiple methods of concealment, all of them including the inhumation of the remains in a woodland setting. It will consist of the excavation of 32 burials, all dug on the same day, at a depth between 40 and 60 cm involving just as many piglet cadavers (Sus scrofa) weighing between 3 and 5 kg. They will be divided into four different groups, each of which will undergo peculiar treatments: eight will be buried naked; eight clothed; eight will be buried in quicklime and the last eight will be previously hurt. The experiment will be conducted for a total of 730 days and the exhumations of the specimens will be performed in eight increasing time intervals, to achieve different PBIs for each group of subjects (15, 30, 60, 120, 240, 365, 545 and 730 days). At the time of each exhumation biological material, commodities and soil will be sampled and investigated from a geochemical, microscopic (polarizing microscope) and ultramicroscopic (SEM-EDS) point of view, aiming to underline any evidence of mutual exchange of material between the different substrates, as well as any symptom of disturbance, both biochemical and mechanical. As focusing on a multidisciplinary approach, not only this study will allow to reach a standardization for the right reading of trace evidence in real cases of clandestine burials inquiry, but it also will contribute to draw up some guidelines for the exploitation of the parameters registered by the geopedological analytical techniques, which have been neglected for years in the forensic and medico-legal context.

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    https://doi.org/10.5194/egusph...
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