Abstract
Blackheart and soluble solids content (SSC) are critical parameters of pear for quality assessment and export trade guarantee. A non-destructive detection method was developed for measuring blackheart pear and SSC. Three discriminate analysis models, such as principal component analysis (PCA), correlation analysis and partial least square discriminate analysis (PLS-DA), were developed to identify black heart samples. Compared with PCA and correlation analysis, PLS-DA achieved the highest classification accuracy of 100% for identifying blackheart pears. Three sample sets of healthy samples, black heart ones, and their combination were applied to assess the performance of PLS model, and PLS model calibrated with healthy pears yielded better with root-mean-square errors of prediction 0.45°Brix. The overall results suggested that it was feasible to detect blackheart and SSC of pears simultaneously by online visible–NIR spectroscopy.
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Acknowledgements
The authors gratefully acknowledge the financial support provided by Jiangxi Outstanding Youth Talent Program (20171BCB23060) and Jiangxi Provincial Education Department Project (GJJ160478).
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Sun, X., Zhu, K., Jiang, X. et al. Non-destructive detection of blackheart and soluble solids content of intact pear by online NIR spectroscopy. J Supercomput 76, 3173–3187 (2020). https://doi.org/10.1007/s11227-018-2537-9
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DOI: https://doi.org/10.1007/s11227-018-2537-9