Shelf-life management and ripening assessment of ‘hass’ avocado (persea americana) using deep learning approaches

Pedro Xavier, Pedro Miguel Rodrigues, Cristina L. M. Silva*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)
8 Downloads

Abstract

Avocado production is mostly confined to tropical and subtropical regions, leading to lengthy distribution channels that, coupled with their unpredictable post-harvest behavior, render avocados susceptible to significant loss and waste. To enhance the monitoring of ‘Hass’ avocado ripening, a data-driven tool was developed using a deep learning approach. This study involved monitoring 478 avocados stored in three distinct storage environments, using a 5-stage Ripening Index to classify each fruit’s ripening phase based on their shared characteristics. These categories were paired with daily photographic records of the avocados, resulting in a database of labeled images. Two convolutional neural network models, AlexNet and ResNet-18, were trained using transfer learning techniques to identify distinct ripening indicators, enabling the prediction of ripening stages and shelf-life estimations for new unseen data. The approach achieved a final prediction accuracy of 88.8% for the ripening assessment, with 96.7% of predictions deviating by no more than half a stage from their actual classifications when considering the best side of the samples. The average shelf-life estimates based on the attributed classifications were within 0.92 days of the actual shelf-life, whereas the predictions made by the models had an average deviation of 0.96 days from the actual shelf-life.

Original languageEnglish
Article number1150
Number of pages22
JournalFoods
Volume13
Issue number8
DOIs
Publication statusPublished - 10 Apr 2024

Keywords

  • Convolutional neural network
  • Fruit ripening
  • Shelf-life tracking
  • Post-harvest handling
  • Supply chain management

Fingerprint

Dive into the research topics of 'Shelf-life management and ripening assessment of ‘hass’ avocado (persea americana) using deep learning approaches'. Together they form a unique fingerprint.

Cite this