Machine learning-assisted carbon dot sensing for iron speciation in Auricularia auricula soaking solutions under
Jing Mao1, Fenghua Li2, Yang Ma2
1College of Chemistry and Material Science, Sichuan Provincial Engineering Research Center of Livestock Manure Treatment and Recycling, Sichuan Normal University, Chengdu, Sichuan 610068, China.
Food Chemistry
|May 25, 2026
Summary
Accurate iron speciation in Auricularia auricula soaking solutions was achieved using bamboo-derived carbon quantum dots (CQDs) and machine learning. This method quantifies iron valence states, crucial for assessing nutritional quality and bioavailability.
Area of Science:
- Analytical Chemistry
- Materials Science
- Biochemistry
Background:
- Accurate iron speciation (Fe2+/Fe3+) in Auricularia auricula (wood ear mushroom) soaking solutions is vital for assessing nutritional value and iron bioavailability.
- Existing methods for iron speciation can be complex and may not be suitable for direct application to food matrices.
Purpose of the Study:
- To develop a novel, machine learning-assisted fluorescent sensing strategy for rapid and accurate iron speciation in Auricularia auricula soaking solutions.
- To investigate the influence of temperature and origin on iron leaching behavior in Auricularia auricula.
Main Methods:
- Synthesis of bamboo-derived carbon quantum dots (CQDs) via a one-pot hydrothermal method.
- Development of a fluorescent sensing assay utilizing CQDs as selective probes for Fe3+ detection (static fluorescence quenching).
- Indirect quantification of Fe2+ through oxidation to Fe3+ followed by CQD-based detection.
- Application of a random forest model to analyze iron leaching behavior and predict iron speciation.
Main Results:
- The developed CQD-based fluorescent sensor exhibited a wide linear range (1-500 μM) and a low limit of detection (0.30 μM) for iron.
- Iron in Auricularia auricula soaking solutions predominantly exists as Fe3+.
- The bioaccessible Fe2+ fraction decreased significantly (<1%) after 30 min at 100 °C.
- The random forest model accurately predicted iron leaching behavior (R2 = 0.99), highlighting temperature and origin dependence.
Conclusions:
- A sensitive and selective machine learning-assisted fluorescent sensing method using CQDs was successfully established for iron speciation in Auricularia auricula soaking solutions.
- The study provides insights into the iron speciation dynamics and leaching behavior in Auricularia auricula under varying conditions, relevant for food quality assessment.
- This approach offers a promising tool for evaluating the nutritional quality and bioavailability of iron in edible mushrooms.
Related Concept Videos
01:21Atomic Absorption Spectroscopy: Lab
For AAS measurements, samples must be introduced as clear solutions, often requiring extensive preliminary treatment to dissolve materials like soils, animal tissues, and minerals. Common methods for sample preparation include treatment with hot mineral acids, wet ashing, combustion in closed containers, high-temperature ashing, or fusion with reagents.
Solutions containing organic solvents, such as low-molecular-mass alcohols, esters, or ketones, enhance absorbances by increasing nebulizer...
Solutions containing organic solvents, such as low-molecular-mass alcohols, esters, or ketones, enhance absorbances by increasing nebulizer...
01:17Precipitation and Co-precipitation
Precipitation and coprecipitation methods can be used to separate a mixture of ions in a solution. In qualitative inorganic analysis, ions that form sparingly soluble precipitates with the same reagent are separated based on the differences in solubility products. For example, consider the separation of Cu(II) and Fe(II) ions by precipitation as insoluble sulfides. First, copper(II) sulfide is precipitated by the addition of acidic H2S, where the dissociation of H2S is suppressed. Adding H2S...
01:27Microbial Leaching
Microbial leaching, also known as bioleaching, is an environmentally favorable method for extracting metals from low-grade ores using specific microorganisms. This biotechnological approach is particularly valuable for mining operations targeting copper, gold, and uranium, where traditional extraction methods may be economically or environmentally impractical.Copper Leaching and Microbial CatalysisIn copper bioleaching, crushed ore is arranged into heaps and irrigated with a dilute sulfuric...