Using mid‐infrared spectroscopy combined with chemometrics to determine digested starch and maltose concentration during in‐vitro digestion of starches [PDF]
R. Visnupriyan +3 more
openalex +1 more source
Infrared Spectroscopy as a Promising Tool for Diagnosing and Typing Human Pathogenic Fungi
ABSTRACT Fungal infections are increasingly recognised as a global health challenge, responsible for millions of cases annually and substantial mortality, especially in immunocompromised individuals. Yet, the diagnosis of these infections remains notoriously difficult, often delayed by slow culture‐based methods or hindered by the high cost and ...
Anthony G. J. Medeiros +8 more
wiley +1 more source
Furdu, a traditional sorghum beer, is prized for both its cultural and nutritional value. However, its production lacks standardization, leading to variations in quality and safety. This study presents a comprehensive characterization of furdu, integrating production practices with physicochemical, bioactive, microbial, sensory, and chemometric ...
James Ronald Bayoï +2 more
wiley +1 more source
AI-Powered Advances in Data Handling for Enhanced Food Analysis: From Chemometrics to Machine Learning. [PDF]
Kharbach M.
europepmc +1 more source
The aroma of Phoenix Dancong tea is central to its sensory quality and market value, yet its molecular basis remains insufficiently understood. In this study, we employed GC–IMS to systematically characterize the volatile profiles of Dancong teas across five tree‐age stages (10–400 years) and 11 traditional aroma types.
Yanjun Wang +3 more
wiley +1 more source
A Comprehensive Review on Minimally Destructive Quality and Safety Assessment of Agri-Food Products: Chemometrics-Coupled Mid-Infrared Spectroscopy. [PDF]
Keithellakpam LB +4 more
europepmc +1 more source
Novel chemometric proposals for advanced multivariate data analysis, processing and interpretation [PDF]
Raffaele Vitale
openalex +1 more source
Honey Botanical Origin Authentication Using HS-SPME-GC-MS Volatile Profiling and Advanced Machine Learning Models (Random Forest, XGBoost, and Neural Network). [PDF]
Pourmoradian A +3 more
europepmc +1 more source

