Articles
Image processing to assess repeated impact damage in banana fruit
Article number
1396_26
Pages
193 – 200
Language
English
Abstract
Bananas are one of the highly perishable produce that requires an advanced inspection during the postharvest supply chain.
Applying new non-destructive methods like image processing in identifying bruise intensity in bananas and other fresh produce is necessary.
To emphasize the effect of mechanical damage on the quality attributes of bananas, a computer vision system was used.
This study presents an approach for determining bruise damage of fresh bananas resulting from repeated impacts using the simulated handling experiment (the drop impact test). An impact energy of 0.32 J with three repeated series (1, 3, and 6) and two storage temperatures (13 and 22°C) were used on banana fruit.
Image process technique was used to determine bruise area (BA), color (lightness (L*), yellowness (b*)), and surface area (AS). Bruise volume (BV) and bruise susceptibility (BS) were also calculated.
Bruise magnitude and the studied quality attributes were perfectly presented in this study due to the application of a computer vision system.
The results demonstrated that the repeated impacts series could significantly influence the BV and BS of banana fruit.
Increasing the repetition of impact showed a higher deterioration of the fruit.
Statistical analysis showed that the effect of storage temperature was statistically significant on AS (P<0.05). More repeated impacts and storage at 22°C were more likely to increase the transpiration rate of the fruit after the storage period.
The top surface zone of the banana showed higher bruise susceptibility followed by the middle and bottom surface zones, respectively.
Besides, the data obtained by converting the RGB values to L*a*b* color space showed an alternation of L* and b* after 72 h of storage.
Using image processing can facilitate the measurements of bruising and other quality attributes in the actual locations of damage occurrence like farms and markets.
Also, knowledge regarding mechanical bruise damage from fresh banana fruit under repeated series of impacts is essential for developing strategies for decreasing or even avoiding this problem.
Applying new non-destructive methods like image processing in identifying bruise intensity in bananas and other fresh produce is necessary.
To emphasize the effect of mechanical damage on the quality attributes of bananas, a computer vision system was used.
This study presents an approach for determining bruise damage of fresh bananas resulting from repeated impacts using the simulated handling experiment (the drop impact test). An impact energy of 0.32 J with three repeated series (1, 3, and 6) and two storage temperatures (13 and 22°C) were used on banana fruit.
Image process technique was used to determine bruise area (BA), color (lightness (L*), yellowness (b*)), and surface area (AS). Bruise volume (BV) and bruise susceptibility (BS) were also calculated.
Bruise magnitude and the studied quality attributes were perfectly presented in this study due to the application of a computer vision system.
The results demonstrated that the repeated impacts series could significantly influence the BV and BS of banana fruit.
Increasing the repetition of impact showed a higher deterioration of the fruit.
Statistical analysis showed that the effect of storage temperature was statistically significant on AS (P<0.05). More repeated impacts and storage at 22°C were more likely to increase the transpiration rate of the fruit after the storage period.
The top surface zone of the banana showed higher bruise susceptibility followed by the middle and bottom surface zones, respectively.
Besides, the data obtained by converting the RGB values to L*a*b* color space showed an alternation of L* and b* after 72 h of storage.
Using image processing can facilitate the measurements of bruising and other quality attributes in the actual locations of damage occurrence like farms and markets.
Also, knowledge regarding mechanical bruise damage from fresh banana fruit under repeated series of impacts is essential for developing strategies for decreasing or even avoiding this problem.
Authors
M. Al-Dairi, P.B. Pathare, R. Al-Yahyai, H. Jayasuriya, Z. Al-Attabi
Keywords
image processing, banana, repeated impact, surface area, color
Online Articles (82)