Version 1
: Received: 1 July 2024 / Approved: 2 July 2024 / Online: 4 July 2024 (11:12:32 CEST)
How to cite:
Arolkar, N. M.; Ortiz, C.; Dapurkar, N.; Blanes, C.; Gonzalez-Planells, P. Automated Tenderness Assessment of Okra Using Robotic Non-Destructive Sensing. Preprints2024, 2024070214. https://doi.org/10.20944/preprints202407.0214.v1
Arolkar, N. M.; Ortiz, C.; Dapurkar, N.; Blanes, C.; Gonzalez-Planells, P. Automated Tenderness Assessment of Okra Using Robotic Non-Destructive Sensing. Preprints 2024, 2024070214. https://doi.org/10.20944/preprints202407.0214.v1
Arolkar, N. M.; Ortiz, C.; Dapurkar, N.; Blanes, C.; Gonzalez-Planells, P. Automated Tenderness Assessment of Okra Using Robotic Non-Destructive Sensing. Preprints2024, 2024070214. https://doi.org/10.20944/preprints202407.0214.v1
APA Style
Arolkar, N. M., Ortiz, C., Dapurkar, N., Blanes, C., & Gonzalez-Planells, P. (2024). Automated Tenderness Assessment of Okra Using Robotic Non-Destructive Sensing. Preprints. https://doi.org/10.20944/preprints202407.0214.v1
Chicago/Turabian Style
Arolkar, N. M., Carlos Blanes and Pablo Gonzalez-Planells. 2024 "Automated Tenderness Assessment of Okra Using Robotic Non-Destructive Sensing" Preprints. https://doi.org/10.20944/preprints202407.0214.v1
Abstract
Okra, a widely grown vegetable in many regions, often suffers from freshness loss during transportation, causing significant waste. Factors like variety, environment, maturity, and handling affect its quality. Current methods for checking okra tenderness are slow and prone to mistakes, so we need a better, non-damaging method. This study aims to use a device on a robot arm to assess okra freshness and tenderness. We tested 120 okra pods, storing some in a cold chamber for 24 hours (considered tender) and others at room temperature for two days before moving them to a cold environment for five more days (considered not tender). We used a force sensor on a robot arm to measure okra hardness without damaging it, then did tenderness tests. We found that certain sensor data, like the first slope (S1) and the difference between the maximum value and the first overshoot (Os), were good predictors of tenderness, with an accuracy rate of nearly 80%. We also validated this non-damaging method with weight loss, compression, and puncture tests, achieving a 95.5% accuracy rate in distinguishing between tender and non-tender okra pods.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
