Robotics & Machine Learning Daily News2024,Issue(Oct.4) :230-231.

Accurate non-invasive quantification of astaxanthin content using hyperspectral images and machine learning

Robotics & Machine Learning Daily News2024,Issue(Oct.4) :230-231.

Accurate non-invasive quantification of astaxanthin content using hyperspectral images and machine learning

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-According to news reporting based on a preprint abstract, our journalists obtained the following quote sourced from bi orxiv.org: "Commercial cultivation of the microalgae Haematococcus pluvialis to produce nat ural astaxanthin has gained significant traction due to the high antioxidant cap acity of this pigment and its application in foods, feed, cosmetics and nutraceu ticals. "However, monitoring of astaxanthin content in cultures remains challenging and relies on invasive, time consuming and expensive approaches. "In this study, we employed reflectance hyperspectral imaging (HSI) of H. pluvia lis suspensions within the visible spectrum, combined with a1-dimensional convo lutional neural network (CNN) to predict the astaxanthin content (ug mg-1) as qu antified by high-performance liquid chromatography (HPLC). This approach had low average prediction error (5.9%) across a gradient of astaxanthin contents and was only unreliable at very low contents (<0.6 micrograms mg-1).

Key words

Bioinformatics/Biotechnology/Biotechno logy-Bioinformatics/Cyborgs/Emerging Technologies/Information Technology/M achine Learning

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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