Quantitative prediction and visualization of matcha color physicochemical indicators using hyperspectral microscope imaging technology
Authors:
- Dengshan LiDLDengshan Li
- Bosoon ParkBPBosoon Park
- Rui KangRKRui Kang
- Quansheng ChenQCQuansheng Chen
- Qin OuyangQOQin Ouyang
- 18 April 2024
- journal article
- research article
- Published by Elsevier in Food Control
- Vol. 163
Abstract
No abstract availableKeywords
Funding Information
- National Natural Science Foundation of China
This publication has 36 references indexed in Scilit:
- Monitoring chlorophyll changes during Tencha processing using portable near-infrared spectroscopyFood Chemistry, 2023
- A deep learning method for predicting lead content in oilseed rape leaves using fluorescence hyperspectral imagingFood Chemistry, 2022
- Estimating the distribution of chlorophyll content in CYVCV infected lemon leaf using hyperspectral imagingComputers and Electronics in Agriculture, 2022
- Non-destructive and in-site estimation of apple quality and maturity by hyperspectral imagingComputers and Electronics in Agriculture, 2022
- Accurate prediction of soluble solid content in dried Hami jujube using SWIR hyperspectral imaging with comparative analysis of modelsComputers and Electronics in Agriculture, 2022
- Hyperspectral imaging in combination with data fusion for rapid evaluation of tilapia fillet freshnessFood Chemistry, 2021
- Color stability and pH-indicator ability of curcumin, anthocyanin and betanin containing colorants under different storage conditions for intelligent packaging developmentFood Control, 2021
- Utilising near-infrared hyperspectral imaging to detect low-level peanut powder contamination of whole wheat flourBiosystems Engineering, 2019
- Simultaneous determination of six main types of lipid-soluble pigments in green tea by visible and near-infrared spectroscopyFood Chemistry, 2019
- Key wavelengths screening using competitive adaptive reweighted sampling method for multivariate calibrationAnalytica Chimica Acta, 2009