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Near-Infrared Hyperspectral Imaging Rapidly Detects the Decay of Postharvest Strawberry Based on Water-Soluble Sugar Analysis

  • Qiang Liu
  • Kangli Wei
  • Hui Xiao
  • Sicong Tu
  • Ke Sun
  • Ye Sun
  • Leiqing Pan
  • Kang Tu
Article
  • 12 Downloads

Abstract

This paper presents a novel strategy to detect the fungal decay in strawberry using reflectance near-infrared hyperspectral imaging (NIR-HSI, 1000–2500 nm). The variation of fructose, glucose, sucrose, and total water-soluble sugar (TWSS) content was analyzed using HPLC with a reference method during fungal infection in strawberry. The feasibility of quantifying sugar constituents relevant to the different stages of decay in strawberry was evaluated using NIR-HSI with key wavelengths selected via successive projection algorithm. The results showed that the predicted performance of TWSS content was acceptable within 0.807 for Rp2 and 2.603 for RPD, respectively. Five to seven key wavelengths were obtained based on sugar constituents, and excellent performance for classification accuracy among the three stages of decay was 89.4 to 95.4% for calibration and 87.0 to 94.4% for prediction, respectively. This rapid approach provides a new strategy for the selection of key wavelengths to detect the decay and sugar constituents in strawberries.

Keywords

Decay Hyperspectral imaging Key wavelength Strawberry Sugar content 

Notes

Funding Information

This study is financially supported by National Natural Science Foundation of China (NSFC 31671926; 31671925), the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD), and 2017 Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX17_0631).

Compliance with Ethical Standards

Conflict of Interest

Qiang Liu declares that he/she has no conflict of interest. Kangli Wei declares that he/she has no conflict of interest. Hui Xiao declares that he/she has no conflict of interest. Sicong Tu declares that he/she has no conflict of interest. Ke Sun declares that he/she has no conflict of interest. Ye Sun declares that he/she has no conflict of interest. Leiqing Pan declares that he/she has no conflict of interest. Kang Tu declares that he/she has no conflict of interest.

Ethical Approval

This article does not contain and studies with human participants or animals performed by any of the authors.

Informed Consent

Informed consent was obtained from all individual participants included in the study.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Qiang Liu
    • 1
  • Kangli Wei
    • 1
  • Hui Xiao
    • 1
  • Sicong Tu
    • 2
    • 3
  • Ke Sun
    • 4
  • Ye Sun
    • 5
  • Leiqing Pan
    • 1
  • Kang Tu
    • 1
  1. 1.College of Food Science and TechnologyNanjing Agricultural UniversityNanjingPeople’s Republic of China
  2. 2.Medical Sciences DivisionUniversity of OxfordOxfordUK
  3. 3.Sydney Medical SchoolThe University of SydneySydneyAustralia
  4. 4.College of Environmental Science and EngineeringAnhui Normal UniversityWuhuChina
  5. 5.College of EngineeringNanjing Agricultural UniversityNanjingChina

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