ReviewJournal of agricultural and food chemistry2026
Unlocking Soil Health and Surface Water Quality Management: A Review on Fluorescent Dissolved Organic Matter (fDOM) in Agricultural Systems.
Review in Journal of agricultural and food chemistry, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Agricultural runoff is a major source of water quality impairments and is prevalent in areas where agricultural operations focus on maintaining global food security. To alleviate downstream impacts, best management practices are used to cultivate food systems and enhance soil nutrient cycling. When runoff events do occur, tracing the impairments often involves complex and costly methods to determine analyte concentrations and forecast mitigation techniques. Fluorescent dissolved organic matter (fDOM) is an innovative approach to understanding parent source materials and carbon signatures from runoff. Fluorescence and absorbance indices can distinguish intensities of the carbon molecular weight, biological activity, and humification that can trace the environmental availability of carbon sources. Comprehensive data sets can be combined using parallel factor analysis (PARAFAC) to determine parent source components. Integrating these analyses can provide real-time high-frequency data to empower policymakers and land managers to make informed decisions aimed at reducing the environmental degradation associated with modern intensive agriculture.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.