- Title
- Advancing Soil Health: Challenges and Opportunities in Integrating Digital Imaging, Spectroscopy, and Machine Learning for Bioindicator Analysis
- Creator
- Wang, Liang; Cheng, Ying; Meftaul, Islam Md; Luo, Fang; Kabir, Muhammad Ashad; Doyle, Richard; Lin, Zhenyu; Naidu, Ravi
- Relation
- Analytical Chemistry Vol. 96, Issue 20, p. 8109-8123
- Publisher Link
- http://dx.doi.org/10.1021/acs.analchem.3c05311
- Publisher
- American Chemical Society (ACS)
- Resource Type
- journal article
- Date
- 2024
- Description
- The assessment of soil health is of paramount importance for promoting sustainable agriculture and enhancing ecosystem resilience. (1) Healthy soils play a vital role in facilitating vital processes such as nutrient cycling, water filtration, and carbon sequestration, which are essential for maintaining the overall health and functioning of ecosystems. Bioindicators, encompassing the living components in soil, offer valuable insights into the functionality and condition of soils across diverse ecological contexts. (2) These indicators furnish quantifiable data that aid in evaluating soil quality and health. Researchers have identified an array of biological indicators for monitoring soil health, including microbial taxa and community structure, soil respiration and carbon cycling, multienzyme profiling, nematodes, microarthropods, and microbial biomass. (1,2) These indicators reflect important aspects of soil health, such as microbial activity, nutrient availability, and overall soil functionality.
- Subject
- fluorescence; machine learning; quantum mechanics; Raman spectroscopy; soils
- Identifier
- http://hdl.handle.net/1959.13/1504454
- Identifier
- uon:55521
- Identifier
- ISSN:0003-2700
- Language
- eng
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