Rice-based diet faces an important public health concern due to arsenic (As) accumulation in rice grain, which is toxic to humans. Rice crops are prone to assimilate As due to continuously flooded cultivation. In this study, the objective was to determine how water regimes (flooded and aerobic) in rice cultivation impact total As and inorganic As speciation in rice on the basis of a field-scale trial in the post-monsoon season. Iron and silicon with NPK/organic manure were amended in each regime. We hypothesised that aerobic practice receiving amendments would reduce As uptake in rice grain with a subsequent decrease in accumulation of inorganic As species relative to flooded conditions (control). Continuously flooded conditions enhanced soil As availability by 32% compared to aerobic conditions. Under aerobic conditions, total As concentrations in rice decreased by 62% compared to flooded conditions. Speciation analyses revealed that aerobic conditions significantly reduced ( < 0.05) arsenite (68%) and arsenate (61%) accumulation in rice grains. Iron and silicon exhibited significant impact on reducing arsenate and arsenite uptake in rice, respectively. The study indicates that aerobic rice cultivation with minimum use of irrigation water can lead to lower risk of inorganic As exposure to rice relative to flooded practice.
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http://dx.doi.org/10.3390/ijerph18094643 | DOI Listing |
J Environ Manage
December 2024
Department of Infrastructure and Water Management, Faculty of Civil and Environmental Engineering and Architecture, Rzeszow University of Technology, Ave Powstańców Warszawy 6, 35-959, Rzeszów, Poland. Electronic address:
Current urban challenges related to local urban flooding require effective preventive measures. This applies particularly to various methods of stormwater retention, including forced retention, and solutions that enable cooperation between small individual retention systems and drainage systems. Therefore, this study presents the results of research on the hydraulic efficiency of controllable systems, which combine the features of an on-site tank with the solutions of network tanks to increase the retention of stormwater in drainage systems.
View Article and Find Full Text PDFCognition
December 2024
Department of Psychology & Neuroscience, Duke University 417 Chapel Drive, Box 90086, Durham, NC 27708, USA. Electronic address:
Acting for the greater good often involves paying a personal cost to benefit the collective. In two studies, we investigate how children (N = 184, M = 8.02 years, SD = 1.
View Article and Find Full Text PDFSci Rep
December 2024
College of Energy Engineering, Xi'an University of Science and Technology, Xi'an, 710054, China.
Affected by weakening effect of water in the goaf, the bearing capacity of coal pillar reduced, and coal pillar rock burst is prone to occur, which is a serious threat to mine safety in production. In order to study the equivalent width and stability of coal pillar in water-rich coal seam, taking the section coal pillar of a working face as the research object, combined with laboratory test, theoretical analysis, simulation and engineering practice, the stress, elastic core area width, damage degree and energy accumulation of 36 m water-immersed coal pillar and 26 m, 28 m, 30 m, 32 m, 36 m unimmersed coal pillars are analyzed. The research results show that: (1) The reasonable width of coal pillar under flooded and unflooded conditions is 36.
View Article and Find Full Text PDFJ Environ Manage
December 2024
Key Laboratory of the Three Gorges Reservoir Region's Eco-Environment, Ministry of Education, Chongqing University, Chongqing, 400045, China; Department of Ecological Sciences and Engineering, Chongqing University, Chongqing, 400045, China. Electronic address:
In wetlands, hydrological conditions drive plant community distribution, forming vegetation zones with plant species and material cycling. This mediates nitrogen migration and NO emissions within wetlands. Five vegetation zones in a large wetland were studied during flooding and drought periods.
View Article and Find Full Text PDFSci Rep
December 2024
Department of Civil, Construction and Environmental Engineering (Dept 2470), North Dakota State University, PO Box 6050, Fargo, ND, 58108-6050, USA.
A precise streamflow forecast is crucial in hydrology for flood alerts, water quantity and quality management, and disaster preparedness. Machine learning (ML) techniques are commonly employed for hydrological prediction; however, they still face certain drawbacks, such as the need to optimize the appropriate predictors, the ability of the models to generalize across different time horizons, and the analysis of high-dimensional time series. This research aims to address these specific drawbacks by developing a novel framework for streamflow forecasting.
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