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

Producción científica: Chapterrevisión exhaustiva

3 Citas (Scopus)

Resumen

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.

Idioma originalEnglish
Título de la publicación alojadaNondestructive Quality Assessment Techniques for Fresh Fruits and Vegetables
Páginas301-329
Número de páginas29
ISBN (versión digital)9789811954221
DOI
EstadoPublished - ene 1 2022

Nota bibliográfica

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

ASJC Scopus subject areas

  • General Engineering
  • General Agricultural and Biological Sciences

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