Home
  • English
  • ÄŒeÅ¡tina
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • LatvieÅ¡u
  • Magyar
  • Nederlands
  • Português
  • Português do Brasil
  • Suomi
  • Log In
    New user? Click here to register. Have you forgotten your password?
Home
  • Browse Our Collections
  • Publications
  • Researchers
  • Research Data
  • Institutions
  • Statistics
    • English
    • ÄŒeÅ¡tina
    • Deutsch
    • Español
    • Français
    • Gàidhlig
    • LatvieÅ¡u
    • Magyar
    • Nederlands
    • Português
    • Português do Brasil
    • Suomi
    • Log In
      New user? Click here to register. Have you forgotten your password?
  1. Home
  2. Resources
  3. UniMAP Index Publications
  4. Publications 2023
  5. Development of Harumanis Mango Insidious Fruit Rot (IFR) Detection by Utilising Vibration-Based Sensors and PCA with Random Forest
 
Options

Development of Harumanis Mango Insidious Fruit Rot (IFR) Detection by Utilising Vibration-Based Sensors and PCA with Random Forest

Journal
Journal of Physics: Conference Series
ISSN
17426588
Date Issued
2023-01-01
Author(s)
Salleh N.M.
Abu Hassan Abdullah
Universiti Malaysia Perlis
Sukhairi Sudin
Universiti Malaysia Perlis
Noor Shazliza Zakaria
Universiti Malaysia Perlis
DOI
10.1088/1742-6596/2641/1/012013
Abstract
Utilising single or multiple modalities systems, non-destructive techniques have been used to assess and determine the quality of mango (magnifera indica L.). It is challenging to anticipate and varies by cultivar at what harvest maturity stage will result in the optimum postharvest quality. Insidious Fruit Rot (IFR) is a disease that affects mangoes. When infected with Insidious Fruit Rot (IFR), the mango variety Harumanis does not exhibit exterior mutilation at the time of harvest or during the mature stage. However, a lack of density in the sinus area can occasionally be detected. Traditional ways of locating the diseases or pests living in the mango are useless for the commercialization of the product. This research presents the investigation done on IFR infection detection using piezoelectric vibration sensors and electret microphones. Data derived by the sensors were processed using the PCA and Random Forest methods to determine the non-IFR and the mango afflicted with IFR. The proposed approach achieved correct classification and is expected to be useful for planters in detecting IFR correctly before Harumanis mangoes were marketed.
Subjects
  • Harumanis Mango | IFR...

File(s)
research repository notification.pdf (4.4 MB)
Views
1
Acquisition Date
Nov 19, 2024
View Details
google-scholar
Downloads
  • About Us
  • Contact Us
  • Policies