Examining plant uptake and translocation of emerging contaminants using machine learning: Implications to food security

Bagheri, Majid; Al-jabery, Khalid K.; Wunsch, Donald C.; Burken, Joel G.

doi:10.1016/j.scitotenv.2019.133999

Cited by 46 publications

(25 citation statements)

References 36 publications

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“…Thereafter, these concentrations cause the normally effective antibiotics to fail completely in curing illnesses (Bhandari et al 2008;Diwan et al 2010;Homem and Santos 2011). Furthermore, the irrigation of plants with antibiotic-contaminated water leads to the uptake of antibiotics by plants and then antibiotics exposure to the food chain (Bagheri et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Characterization of activated bentonite clay mineral and the mechanisms underlying its sorption for ciprofloxacin from aqueous solution

Maged

Kharbish

Ismael

et al. 2020

Environ Sci Pollut Res

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The presence of emerging pollutants such as hazardous chemicals, pharmaceuticals, pesticides, and endocrine-disrupting chemicals in water sources is a serious concern to the environment and human health. Thus, this study focused on exploring the interaction mechanisms between ciprofloxacin (CIP) (antibiotic) and clay (a low-cost adsorbent) during sorption process. Acid activation technique was opted for modifying natural bentonite (NB) to enhance the adsorptive removal of CIP from water. The BET surface area analysis revealed that acid-activated bentonite (AAB) possessed more than two fold higher surface area as compared to NB. Combining pH zpc measurements, effect of solution pH and CIP speciation revealed that CIP sorption onto bentonite is highly dependent on solution pH. Kinetic studies confirmed that CIP sorption mechanism was chemisorption which included ion-exchange and surface complexation mechanisms. The mechanism of CIP sorption onto AAB was successfully explored with the assistance of characterization techniques. Maximal monolayer sorption capacity of AAB was found to be 305.20 mg/g, compared to 126.56 mg/g for NB. Reusability studies demonstrated that AAB could be reused successfully up to 5 cycles. Furthermore, column studies showed satisfactory results confirming that AAB can be successfully used in continuous mode for practical applications. Electronic supplementary material The online version of this article (10.1007/s11356-020-09267-1) contains supplementary material, which is available to authorized users.

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Section: Introductionmentioning

confidence: 99%

Characterization of activated bentonite clay mineral and the mechanisms underlying its sorption for ciprofloxacin from aqueous solution

Maged

Kharbish

Ismael

et al. 2020

Environ Sci Pollut Res

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“…A recent major endeavor is the development of multilayer perceptron neural networks to predict the translocation of ECs including benzo[ a ]anthracene, chrysene, perfluorobutanesulfonate (PFBS), and PFOA, in which fuzzy logic was used to determine the physiochemical cutoffs and eliminate the partition effect. 247 With key water parameters being digitalized and visualized through data acquired from LTCM, a modern water system can be decomposed into different dimensional layers connected through data flow ( Figure 4 b).…”

Section: Current State and Challenge Of Data Processing For Ltcmmentioning

confidence: 99%

Forward-Looking Roadmaps for Long-Term Continuous Water Quality Monitoring: Bottlenecks, Innovations, and Prospects in a Critical Review

Huang

Wang

Xiang

et al. 2022

Environ. Sci. Technol.

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Long-term continuous monitoring (LTCM) of water quality can bring far-reaching influences on water ecosystems by providing spatiotemporal data sets of diverse parameters and enabling operation of water and wastewater treatment processes in an energy-saving and cost-effective manner. However, current water monitoring technologies are deficient for long-term accuracy in data collection and processing capability. Inadequate LTCM data impedes water quality assessment and hinders the stakeholders and decision makers from foreseeing emerging problems and executing efficient control methodologies. To tackle this challenge, this review provides a forward-looking roadmap highlighting vital innovations toward LTCM, and elaborates on the impacts of LTCM through a three-hierarchy perspective: data, parameters, and systems. First, we demonstrate the critical needs and challenges of LTCM in natural resource water, drinking water, and wastewater systems, and differentiate LTCM from existing short-term and discrete monitoring techniques. We then elucidate three steps to achieve LTCM in water systems, consisting of data acquisition (water sensors), data processing (machine learning algorithms), and data application (with modeling and process control as two examples). Finally, we explore future opportunities of LTCM in four key domains, water, energy, sensing, and data, and underscore strategies to transfer scientific discoveries to general end-users.

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“…TOMRA industry sorts the good quality tomatoes from defected tomatoes during harvesting or/and during the postharvesting phase, as shown in Figure 2. e goal of this article is to assist farmers with postharvest processing by determining whether modern AI approaches may assist in distinguishing healthy tomatoes from tomatoes with flaws [57][58][59][60].…”

Section: Synthesis and Way Forwardmentioning

confidence: 99%

Modelling Techniques to Improve the Quality of Food Using Artificial Intelligence

Sahni¹,

Srivastava²,

Khan³

2021

Journal of Food Quality

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Artificial intelligence (AI), or AI/machine vision, is assuming an overwhelming part in the realm of food handling and quality affirmation. As indicated by Mordor Intelligence, AI in the food and refreshments market is required to enlist a CAGR of 28.64%, during the conjecture time frame 2018–2023. Artificial intelligence makes it workable for PCs to gain as a matter of fact, investigate information from the two data sources and yields, and perform most human assignments with an improved level of accuracy and proficiency. Here is a concise gander at how AI is expanding sanitation and quality activities. This exploration has along these lines tried to furnish policymakers with a way to assess new and existing strategies, while likewise offering a reasonable premise through which food chains orders can be made stronger through the thought of the executive’s practices and strategy choices. This survey centers on the AI applications according to four mainstays of food security that is food accessibility, food availability, food use, and strength.

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Examining plant uptake and translocation of emerging contaminants using machine learning: Implications to food security

Cited by 46 publications

References 36 publications

Characterization of activated bentonite clay mineral and the mechanisms underlying its sorption for ciprofloxacin from aqueous solution

Characterization of activated bentonite clay mineral and the mechanisms underlying its sorption for ciprofloxacin from aqueous solution

Forward-Looking Roadmaps for Long-Term Continuous Water Quality Monitoring: Bottlenecks, Innovations, and Prospects in a Critical Review

Modelling Techniques to Improve the Quality of Food Using Artificial Intelligence

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