Xin Zhou

Hyperspectral Imaging Combined With a Hybrid Deep Learning Framework for Simultaneous Monitoring of Multiple Quality Indicators in Frozen-thawed Beef

Damage Identification of Cross‐Variety Kiwifruit Based on Hyperspectral Imaging Combined With Transfer Learning and Semi‐Supervised Self‐Training

Kiwifruit is prone to mechanical damage during storage and transportation after harvest, and the early‐stage damage is hidden. Traditional manual detection methods have problems such as low efficiency and strong subjectivity. In response to the problem of decreased generalization ability of models caused by differe...

SERS-Based Detection of Food Contaminants: From Laboratory Sensitivity to Practical Implementation—Bottlenecks and Pathways to Standardization

Ensuring food safety requires the detection of trace-level contaminants such as pesticides, mycotoxins, and heavy metals. Analytical approaches for these analytes should feature high sensitivity, good selectivity, and compatibility with aqueous matrices; surface-enhanced Raman spectroscopy (SERS) satisfies these requir...

Non-destructive prediction of lead content in oilseed rape leaves by fluorescence hyperspectral technology based on neural network.

Based on fluorescence hyperspectral imaging (FHSI), this study targeted rapid, non-destructive quantification of lead (Pb) content in oilseed rape leaves treated with varying silicon (Si) concentrations, acquiring fluorescence spectra over the 484.43-1001.61 nm wavelength range. To optimize spectral data quality, prepr...