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Polysaccharide prediction in Ganoderma lucidum fruiting body by hyperspectral imaging

Summary

Researchers developed a quick, damage-free method to measure the health-promoting polysaccharide content in Ganoderma lucidum mushrooms using special imaging technology that analyzes light reflection. This technology combines visible and near-infrared light imaging with computer learning to predict polysaccharide levels across the entire mushroom cap. The method achieved 92.4% accuracy and could help mushroom farmers determine the best time to harvest for maximum nutritional value.

Background

Ganoderma lucidum is a traditional Chinese medicinal mushroom with polysaccharides as one of its main active components important for immune function. Current methods for detecting polysaccharide content are destructive, complicated, and time-consuming. Hyperspectral imaging (HSI) offers potential for nondestructive detection during mushroom cultivation.

Objective

To explore the feasibility of using hyperspectral imaging to predict polysaccharide content in Ganoderma lucidum fruiting bodies nondestructively throughout their growth cycle. The study aimed to establish calibration models using visible and near-infrared spectroscopy and determine optimal tissue regions for prediction.

Results

The best model used near-infrared spectrum with combined SG and SNV preprocessing, achieving calibration R² of 0.886 and validation R² of 0.924 with RPD of 3.622. Visible spectrum analysis yielded similar results with R² of 0.9. Analysis of different tissue regions (center, edge, entire cap) showed that using the entire cap as region of interest provided the best prediction performance.

Conclusion

Hyperspectral imaging is feasible for rapid, nondestructive determination of polysaccharide content in Ganoderma lucidum fruiting bodies. The method provides growers with growth monitoring capability and helps determine optimal harvesting time, with potential applications in large-scale cultivation and high-throughput detection.
  • Published in:Food Chemistry X,
  • Study Type:Experimental Research,
  • Source: 10.1016/j.fochx.2021.100199, PMC9039882, PMID: 35498961
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