Non-invasive prediction of maca powder adulteration using a pocket-sized spectrophotometer and machine learning techniques

Paper information is provided by public research databases. Summaries are generated to aid understanding and may not reflect the complete scope of the work. For the authoritative version, please refer to the original publication.