Determination of pectin content in orange peels by near infrared hyperspectral imaging

FOOD CHEMISTRY(2020)

引用 45|浏览9
暂无评分
摘要
Pectin has several purposes in the food and pharmaceutical industry making its quantification important for further extraction. Current techniques for pectin quantification require its extraction using chemicals and producing residues. Determination of pectin content in orange peels was investigated using near infrared hyperspectral imaging (NIR-HSI). Hyperspectral images from orange peel (140 samples) with different amounts of pectin were acquired in the range of 900-2500 nm, and the spectra was used for calibration models using multivariate statistical analyses. Principal component analysis (PCA) and linear discriminant analysis (LDA) showed better results considering three groups: low (0-5%), intermediate (10-40%) and high (50-100%) pectin content. Partial least squares regression (PLSR) models based on full spectra showed higher precision (R-2 > 0.93) than those based on few selected wavelengths (R-2 between 0.92 and 0.94). The results demonstrate the potential of NIR-HSI to quantify pectin content in orange peels, providing a valuable technique for orange producers and processing industries.
更多
查看译文
关键词
Principal component analysis,Linear discriminant analysis,Partial least squares regression, near infrared spectra,Agriculture
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要