Visualizing the structural and chemical heterogeneity of fruit and vegetables using advanced imaging techniques: fundamentals, instrumental aspects, applications and future perspectives

Abstract

Fruit and vegetables (F&V) are vastly complicated products with highly diverse chemical and structural characteristics. Advanced imaging techniques either combine imaging with spectral information or can provide excellent tissue penetration, and enable the possibility to target, visualize and even qualify the chemical and physical (structural) heterogeneity within F&V. In this review, visible and/or near infrared hyperspectral imaging, Fourier transform infrared microspectroscopic imaging, Raman imaging, X-ray and magnetic resonance imaging to reveal chemical and structural information in a spatial context of F&V at the macro- (entire products), meso- (tissues), and micro- (individual cells) scales are comprehensively summarized. In addition, their basic concepts and operational procedures, particularly sample preparation and instrumental parameter adjustments, are addressed. Finally, future challenges and perspectives of these techniques are put forward. These imaging techniques are powerful tools to assess the biochemical and structural heterogeneity of F&V. Cost reduction, sensor fusion and data sharing platforms are future trends. More emphasis on aspects of knowledge and extension at the level of academia and research, especially on how to select techniques, choose operational parameters and prepare samples, are important to overcome barriers for the wider adoption of these techniques to improve the evaluation of F&V quality.

HIGHLIGHTS

• Hyperspectral imaging reveals chemical heterogeneity of fruit and vegetables.

• Imaging techniques provide spatial insights in fruit and vegetables at multiple scales.

• Future trends are cost reduction, sensor fusion and data sharing.

• Instrumental adjustment and sample preparation should receive more attention.

Keywords:

• Fruit and vegetables
• heterogeneity
• hyperspectral imaging
• 3D phenotyping
• X-ray computed tomography

Acknowledgement

This work has been financially supported by the National Natural Science Foundation of China (32302204), and the “Interfaces” project funded through the ANR (French Research Agency) under “Investissements d’Avenir” programme (ANR-10-LABX-01-001 Labex Agro, coordinated by Agropolis Fondation). Authors PV, HX and BN acknowledge financial support from KU Leuven (project C14/22/076) and FWO Flanders (project S003421N “FoodPhase”).

Author contributions

Weijie Lan: Conceptualization; Methodology; Resources Validation; Data curation; Formal analysis; Writing – Original draft preparation, review and editing;

Hui Xiao: Conceptualization; Methodology; Resources Validation; Data curation; Formal analysis; Writing – Original draft preparation review and editing;

Bart Nicolaï: Conceptualization, Writing – review & editing;

Pieter Verboven: Methodology; Resources Validation; Writing – review & editing on X-ray imaging and magnetic resonance imaging techniques;

Jianwei Qin: Methodology; Resources Validation, writing – review & editing on Raman imaging technique;

Catherine M. G. C. Renard: Funding and Supervision; Writing – review & editing;

Benoit Jaillais: Methodology; Resources Validation; Writing – review & editing on NIR hyperspectral imaging technique;

Kang Tu: Funding and Supervision;

Sylvie Bureau: Methodology; Resources Validation, writing – review & editing on FT-IR microspectroscopic techniques;

Leiqing Pan: Funding and Supervision;

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Additional information

Funding

This work was funded by the Agence Nationale de la Recherche; National Social Science Fund of China.