Advancing digital depth: AI-enhanced 3D reconstruction for post-harvest food supply chain quality management

Traditional computer vision-based quality perception lacks depth information, limiting its application to reliable food quality management in the post-harvest supply chain. Three-dimensional (3D) reconstruction technology captures detailed surface geometry and internal structural information for reliable non-destructive quality inspection. Combined with emerging artificial intelligence (AI) technologies, 3D data-driven adaptive management brings potential for next-generation post-harvest quality management. This review analyzed 90 major related studies during 2015–2025, covering high-throughput 3D in-line inspection, high-resolution tomography, portable 3D sensing, and AI-driven 3D reconstruction technologies. Post-harvest supply chain application scenarios are mainly distributed in post-harvest processing (33 studies), manufacturing (29 studies), distribution (15 studies), and consumption (13 studies). Among them, fruit and vegetable products are the most intensively researched, highlighting the suitability and potential benefits of 3D reconstruction for these types of products. Besides, multiple 3D reconstruction technologies have been validated for postharvest evaluation, with X-ray CT dominating postharvest processing, manufacturing, and distribution, and portable RGB imaging devices dominating application in consumption. Besides, relevant 3D reconstruction analysis is evolving from geometry-driven to AI-enhanced analysis and management, highlighting the growing role of 3D reconstruction technology in intelligent, traceable, and sustainable post-harvest supply chain quality management. In the future, by integrating digital twins, IoT, and blockchain technologies, it is expected to build a transparent, tamper-proof quality traceability and control system across the global food supply chain. • 3D reconstruction significantly improves non-destructive food quality inspection. • AI integration expands 3D reconstruction applications in food supply chains. • Applications span post-harvest, processing, logistics, and consumer evaluation. • Enables automation in grading, manufacturing, cold chain, and dietary assessment. • Future trends include sensor fusion, XR, and digital twin for food quality control.

Publication Details

Journal
Postharvest Biology and Technology
Published
2026-03-24
DOI
https://doi.org/10.1016/j.postharvbio.2026.114329
Primary Topic
Spectroscopy and Chemometric Analyses
Type
article
Field-Weighted Citation Impact
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article

Advancing digital depth: AI-enhanced 3D reconstruction for post-harvest food supply chain quality management

Postharvest Biology and Technology
Spectroscopy and Chemometric Analyses
article

Advancing digital depth: AI-enhanced 3D reconstruction for post-harvest food supply chain quality management

article en

Abstract

Traditional computer vision-based quality perception lacks depth information, limiting its application to reliable food quality management in the post-harvest supply chain. Three-dimensional (3D) reconstruction technology captures detailed surface geometry and internal structural information for reliable non-destructive quality inspection. Combined with emerging artificial intelligence (AI) technologies, 3D data-driven adaptive management brings potential for next-generation post-harvest quality management. This review analyzed 90 major related studies during 2015–2025, covering high-throughput 3D in-line inspection, high-resolution tomography, portable 3D sensing, and AI-driven 3D reconstruction technologies. Post-harvest supply chain application scenarios are mainly distributed in post-harvest processing (33 studies), manufacturing (29 studies), distribution (15 studies), and consumption (13 studies). Among them, fruit and vegetable products are the most intensively researched, highlighting the suitability and potential benefits of 3D reconstruction for these types of products. Besides, multiple 3D reconstruction technologies have been validated for postharvest evaluation, with X-ray CT dominating postharvest processing, manufacturing, and distribution, and portable RGB imaging devices dominating application in consumption. Besides, relevant 3D reconstruction analysis is evolving from geometry-driven to AI-enhanced analysis and management, highlighting the growing role of 3D reconstruction technology in intelligent, traceable, and sustainable post-harvest supply chain quality management. In the future, by integrating digital twins, IoT, and blockchain technologies, it is expected to build a transparent, tamper-proof quality traceability and control system across the global food supply chain. • 3D reconstruction significantly improves non-destructive food quality inspection. • AI integration expands 3D reconstruction applications in food supply chains. • Applications span post-harvest, processing, logistics, and consumer evaluation. • Enables automation in grading, manufacturing, cold chain, and dietary assessment. • Future trends include sensor fusion, XR, and digital twin for food quality control.

Postharvest Biology and TechnologyVol. 237
Zero hunger
Openalex Percentile: Top 10%
Spectroscopy and Chemometric Analyses
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