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Details

Autor(en) / Beteiligte
Titel
Specific Gravity-based of Post-harvest Mangifera indica L. cv. Harumanis for ‘Insidious Fruit Rot’ (IFR) Detection using Image Processing
Ist Teil von
  • Computational Science and Technology, p.33-42
Ort / Verlag
Singapore: Springer Singapore
Link zum Volltext
Quelle
Alma/SFX Local Collection
Beschreibungen/Notizen
  • Bruising and internal defects detection is a huge concern for food safety supplied to the consumers. Similar to many other agricultural products, Harumanis cv. has non-uniform quality at harvesting stage. Traditionally, in adapting the specific gravity approach, farmers and agriculturist will estimate the absence of ‘Insidious Fruit Rot’ (IFR) in Harumanis cv. by using floating techniques based on differences in density concept. However, this method is inconvenient and time consuming. In this research, image processing is explored as a method for non-destructive measurement of specific gravity to predict the absence of ‘Insidious Fruit Rot’ (IFR) in Harumanis cv. The predicted specific gravity of 500 Harumanis cv. samples were used and compared with the actual result where it yielded a high correlation ,R2 at 0.9055 and accuracy is 82.00%. The results showed that image processing can be applied for non-destructive Harumanis cv. quality evaluation in detecting IFR.
Sprache
Englisch
Identifikatoren
ISBN: 9789811500572, 9811500576
ISSN: 1876-1100
eISSN: 1876-1119
DOI: 10.1007/978-981-15-0058-9_4
Titel-ID: cdi_springer_books_10_1007_978_981_15_0058_9_4
Format
Schlagworte
image processing, Specific gravity

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