A fully automated modified three-step BCR flow-through sequential extraction method was developed for the fractionation of the arsenic (As) content from agricultural soil based on a multi-syringe flow injection analysis (MSFIA) system coupled to hydride generation-atomic fluorescence spectrometry (HG-AFS). Critical parameters that affect the performance of the automated system were optimized by exploiting a multivariate approach using a Doehlert design. The validation of the flow-based modified-BCR method was carried out by comparison with the conventional BCR method. Thus, the total As content was determined in the following three fractions: fraction 1 (F1), the acid-soluble or interchangeable fraction; fraction 2 (F2), the reducible fraction; and fraction 3 (F3), the oxidizable fraction. The limits of detection (LOD) were 4.0, 3.4, and 23.6 μg L(-1) for F1, F2, and F3, respectively. A wide working concentration range was obtained for the analysis of each fraction, i.e., 0.013-0.800, 0.011-0.900 and 0.079-1.400 mg L(-1) for F1, F2, and F3, respectively. The precision of the automated MSFIA-HG-AFS system, expressed as the relative standard deviation (RSD), was evaluated for a 200 μg L(-1) As standard solution, and RSD values between 5 and 8% were achieved for the three BCR fractions. The new modified three-step BCR flow-based sequential extraction method was satisfactorily applied for arsenic fractionation in real agricultural soil samples from an arsenic-contaminated mining zone to evaluate its extractability. The frequency of analysis of the proposed method was eight times higher than that of the conventional BCR method (6 vs 48 h), and the kinetics of lixiviation were established for each fraction.
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http://dx.doi.org/10.1016/j.aca.2015.03.019 | DOI Listing |
World J Microbiol Biotechnol
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Department of Environmental Engineering, Kyungpook National University, 80 Daehak-Ro, Buk-Gu, Daegu, 41566, South Korea.
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College of Resources and Environmental Sciences, National Academy of Agriculture Green Development, Key Laboratory of Plant-Soil Interactions, Ministry of Education, State Key Laboratory of Nutrient Use and Management, China Agricultural University, Beijing, PR China.
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Intelligent Agricultural Machinery Equipment Engineering Laboratory, Harbin Cambridge University, Harbin, Heilongjiang, China.
Improved soil fertility to sustain crop productivity is important to enhance agroecosystem services. To address the low nutrient content, subsoil compaction, and poor root penetration in Planosol, a new machine was designed to improve these conditions. This machine integrates subsoil mixing and fertilizer application.
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January 2025
Department of Environmental Sciences & Engineering, Faculty of Agriculture & Natural Resources, Ardakan University, Ardakan, Iran.
Assessing the impact of climate change on water-related ecosystem services (ES) in Protected Areas (PAs) is essential for developing soil and water conservation strategies that promote sustainability and restore ES. However, the application of ES research in Protected Area (PA) management remains ambiguous and has notable shortcomings. This study primarily aimed to assess the SDR-InVEST (Sediment Delivery Ratio-Integrated Valuation of Ecosystem Services and Tradeoffs) model for estimating ES, including soil loss, sediment export, and sediment retention, under various climate change scenarios from 1997 to 2100 in the data-scarce region of the Bagh-e-Shadi Forest PA.
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January 2025
Agricultural College of Inner Mongolia Minzu University, Tongliao, 028000, Inner Mongolia, China.
Salinity tolerance in brewing sorghum is a very important trait, especially in areas that are affected by soil salinity. In order to elucidate the mechanism underlying salt tolerance, we conducted a comparative analysis of the transcriptome and metabolome in two distinct sweet sorghum genotypes, namely the salt-tolerant line NY1298 and the salt-sensitive line MY1176, following exposure to salt treatment. Our initial findings indicate the presence of genotype-specific responses in brewing sorghum under salt stress conditions.
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