Acoustic Emission and Near-Infra Red Imaging Methods for Nondestructive Apple Quality Detection and Classification

Akinbode A. Adedeji, Nader Ekramirad, Alfadhl Y. khalecl, Chadwick Parrish

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

2 Scopus citations

Abstract

The need to develop nondestructive techniques in the Agrifood industry is becoming more apparent because of the increasing difficulty of securing labor, the increased innovation around artificial intelligence (AI), sensor technology and machine learning, the efficiency of the system, less risk, reduced cost on the long term, and the reliability of the system among others. Apple is one of the most important and highly valued products and its most devastating pest is the codling moth that often defies the manual random method of sorting especially in organic apple farming. The industry is wary of organisms of quarantine concerns like CM being transferred across borders. The application of nondestructive detection and classification methods has the potential to address some of the inadequacies in conventional random manual methods of sorting for pests. This chapter reviewed two important nondestructive methods, acoustic sensing and hyperspectral imaging that are complementary, and present some of the challenges that need to be addressed.

Original languageEnglish
Title of host publicationNondestructive Quality Assessment Techniques for Fresh Fruits and Vegetables
Pages301-329
Number of pages29
ISBN (Electronic)9789811954221
DOIs
StatePublished - Jan 1 2022

Bibliographical note

Publisher Copyright:
© The Editor(s)(if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022.

Keywords

  • Acoustic emission
  • Apple
  • Near-infrared imaging
  • Nondestructive testing

ASJC Scopus subject areas

  • General Engineering
  • General Agricultural and Biological Sciences

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