Abstract
To reduce the influence of moisture content variation on the spectral detection of soluble solid content (SSC) and achieve rapid, non-destructive detection of SSC, as well as optimize the processing parameters of apricot products, improve detection efficiency and quality control, this study, based on spectral detection technology, combined with the multiple scatter correction (MSC) preprocessing method, concentration residual method for outlier removal, competitive adaptive reweighted sampling method for feature band selection and partial least squares (PLS) method, constructed SSC detection models for apricots at different moisture contents, and explored the impact of moisture content on the detection model effect of SSC in apricot. This study showed that as moisture content decreased, both the values of the valley depth and valley area in the first-derivative spectrum near 970 nm, as well as the peak height and peak area of the reflection peak, gradually diminished, reflecting the progressive weakening of moisture-related spectral characteristics. Furthermore, within the 450–1450 nm wavelength range, SSC prediction accuracy significantly improved with decreasing moisture content. Among the four moisture intervals, the optimal moisture range for apricot SSC detection is 30%-48%. The model exhibits an Rp² of 0.9690, an RMSEP of 0.5712°Brix, and an RPD of 5.7989, meeting the requirements for high-precision quantitative analysis. This study reveals variations in the hyperspectral SSC prediction performance across different moisture content ranges during the apricot drying process, providing a theoretical basis and technical reference for subsequent offline quality assessment and process monitoring of dried apricots.
Data availability
The data that support the findings of this study shall be made available from the corresponding author upon reasonable request.
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Acknowledgements
We extend our gratitude to the expert reviewers for their constructive feedback.
Funding
This research was supported by the National Natural Science Foundation of China (11964030), Xinjiang Production and Construction Corps Special Fund (524408001), Sponsored by Natural Scicnce Support Program of Xinjang Production and Construction Corps(2024DB040), and Tianchi Talented Young Doctoral Fund Project and Tarim University President’s Fund Project (TDZKBS202560).
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L.K. and H.L.(Huaping Luo) conceived the study and designed the methodology; L.K. and J.Y. developed the software and performed formal analysis; H.L.(Hongyang Liu), Y.T. and X.M. conducted the investigation and validation; L.K. curated the data and prepared the original draft; X.M. and L.K. created the visualizations; H.L.(Huaping Luo) supervised the project and acquired funding; X.M., J.Y., H.L.(Huaiyu Liu) and H.L.(Hongyang Liu) reviewed and edited the manuscript. All authors reviewed and approved the final version.
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Kang, L., Luo, H., Ma, X. et al. Study on the effect of moisture content on the spectral detection of soluble solids in apricot. Sci Rep (2026). https://doi.org/10.1038/s41598-026-39890-w
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DOI: https://doi.org/10.1038/s41598-026-39890-w
