On June 28, 2024, Dr. CHENG Hong from the Fruit and Vegetable Storage, Transportation and Processing Laboratory of the Institute of Biotechnology and Food Science published a research paper titled "Potential of hyperspectral imaging for nondestructive determination of α-farnesene and conjugated trienol content in 'Yali' pear" online in the international top chemical spectroscopy journal Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy.
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This study used a combination of visible and near-infrared hyperspectral imaging technology and machine learning models to predict the content of biomarkers α-farnesene and CTols for superficial scald in pear. A nondestructive prediction method of α-farnesene and CTols in 'Yali' pear based on hyperspectral imaging was established, which could predict the contents of α-farnesene and CTols quickly and nondestructively, track the real-time status of pear, and prevent superficial scald. This study provided technical support for nondestructive detection of 'Yali' pear superficial scald.
Link of paper: https://doi.org/10.1016/j.saa.2024.124688
(Source from www.rmlmgmt.com)