ArticleFood chemistry: X2022
Polysaccharide prediction in Ganoderma lucidum fruiting body by hyperspectral imaging.
Article in Food chemistry: X, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 44 citations in OpenAlex.
- Research progress of polysaccharide detection methods in traditional Chinese medicine.Chinese herbal medicines · 2026Review
- Evaluation of the pharmacological potential of Ganoderma lucidum against haemorrhagic and anticoagulant activities of Echis ocellatus venom.BMC biotechnology · 2025Article
- Unraveling bioactive potential and production inChinese herbal medicines · 2025Review
- Structure-function insights of natural Ganoderma polysaccharides: advances in biosynthesis and functional food applications.Natural products and bioprospecting · 2025Review
- Integration of Hyperspectral Imaging and Deep Learning for Discrimination of Fumigated Lilies and Prediction of Quality Indicator Contents.Foods (Basel, Switzerland) · 2025Article
- Non-destructive analysis ofFrontiers in chemistry · 2025Article
- Hyperspectral reflectance imaging for visualizing reducing sugar content, moisture, and hollow rate in red ginseng.Heliyon · 2024Article
- A Review ofFoods (Basel, Switzerland) · 2024Review
- Non-destructive assessment of soluble solids content in kiwifruit using hyperspectral imaging coupled with feature engineering.Frontiers in plant science · 2024Article
- Natural Bio-Compounds fromAntioxidants (Basel, Switzerland) · 2023Review
- Regulatory Effects ofFoods (Basel, Switzerland) · 2023Article
- Optimization of chemical conditions for metabolites production byFrontiers in microbiology · 2023Article
- Nutrient content prediction and geographical origin identification of red raspberry fruits by combining hyperspectral imaging with chemometrics.Frontiers in nutrition · 2022Article
- Non-destructive detection of kiwifruit soluble solid content based on hyperspectral and fluorescence spectral imaging.Frontiers in plant science · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ganoderma lucidum is a traditional Chinese healthy food with many kinds of nutritious activities, and polysaccharide is one of its main active components. Ganoderma lucidum polysaccharide plays a vital role in improving human immunity and anti-oxidation. At present, the methods of detecting polysaccharide content of Ganoderma lucidum are destructive, and the steps are complicated and time-consuming. This study aims to explore the possibility of using hyperspectral imaging (HSI) to predict polysaccharide content in a nondestructive way during the growth of Ganoderma lucidum. The partial least square regression (PLSR) model shows good performance for Ganoderma lucidum (
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.