Sweet lemon mechanical damage detection using image processing technique and UV radiation

被引:13
|
作者
Firouzjaei, Rouhallah Abedi [1 ]
Minaei, Saeid [1 ]
Beheshti, Babak [1 ]
机构
[1] Islamic Azad Univ, Sci & Res Branch, Dept Agr Machinery, Tehran, Iran
关键词
Sweet lemon; Mechanical damage; Non-destructive; Ultraviolet radiation; Image processing; FRUITS;
D O I
10.1007/s11694-018-9766-8
中图分类号
TS2 [食品工业];
学科分类号
0832 ;
摘要
Non-destructive measurement of qualitative parameters of agricultural produce is quite beneficial in the postharvest operations. The consequential effect of mechanical damage in citrus fruits is rarely visible in their appearance compared to other commodities. The purpose of this study was to propose a fast, non-destructive method for sweet lemon mechanical damage detection using image processing technique and UV radiation. For this purpose, 135 sweet lemons were tested based on a completely randomized factorial design. In order to examine mechanical damage, the independent variables included drop height, fruit diameter and tempering period (holding time at room temperature after treatment). Fruits were dropped from heights of 2, 2.5 and 3 m onto the ground. Then images were captured under UV light having a wavelength of 365 nm, 1, 3 and 6 days after treatment. The images were sent to a PC and analyzed using MATLAB software. "Green Spot Index" or GSI was defined to show the extent of mechanical damage. Results of the analysis of variance showed that the percentage of green spots on fruit skin is significant at the 1% level considering the main and double interaction effects of drop height and fruit diameter. Green spot index significantly increases with the level of mechanical damage. Accuracy of the developed method in differentiating the bruised and undamaged fruits was found to be 100%.
引用
收藏
页码:1513 / 1518
页数:6
相关论文
共 50 条
  • [21] Image processing technique (IPT) to determine radiation shielding
    Akkurt, I.
    Comak, B.
    Kilincarslan, S.
    Basyigit, C.
    DIGITAL SIGNAL PROCESSING, 2010, 20 (06) : 1592 - 1596
  • [22] Development of an intelligent drowsiness detection system for drivers using image processing technique
    Suhaiman, Amin Azizi
    May, Zazilah
    Rahman, Noor A'in A.
    2020 18TH IEEE STUDENT CONFERENCE ON RESEARCH AND DEVELOPMENT (SCORED), 2020, : 233 - 236
  • [23] Prediction of UV spectra and UV-radiation damage in actual plasma etching processes using on-wafer monitoring technique
    Jinnai, Butsurin
    Fukuda, Seiichi
    Ohtake, Hiroto
    Samukawa, Seiji
    JOURNAL OF APPLIED PHYSICS, 2010, 107 (04)
  • [24] Detection of External Damage of Apple by Hyperspectral Image Technique
    Liu J.
    Liu F.
    Shi T.
    Sun C.
    Zhang J.
    Men H.
    Journal of Chinese Institute of Food Science and Technology, 2018, 18 (01) : 278 - 284
  • [25] Automated Impact Damage Detection Technique for Composites Based on Thermographic Image Processing and Machine Learning Classification
    Alhammad, Muflih
    Avdelidis, Nicolas P. P.
    Ibarra-Castanedo, Clemente
    Torbali, Muhammet E. E.
    Genest, Marc
    Zhang, Hai
    Zolotas, Argyrios
    Maldgue, Xavier P. V.
    SENSORS, 2022, 22 (23)
  • [26] Automated Detection of Corrosion Damage in Power Transmission Lattice Towers Using Image Processing
    Valeti, Bhavana
    Pakzad, Shamim
    STRUCTURES CONGRESS 2017: BUSINESS, PROFESSIONAL PRACTICE, EDUCATION, RESEARCH, AND DISASTER MANAGEMENT, 2017, : 474 - 482
  • [27] Mechanical Damage Detection in Polymer Tiles by THz Radiation
    Rahani, Ehsan Kabiri
    Kundu, Tribikram
    Wu, Ziran
    Xin, Hao
    IEEE SENSORS JOURNAL, 2011, 11 (08) : 1720 - 1725
  • [28] Autonomous lemon grading system by using machine learning and traditional image processing
    Hanh, Le Duc
    Bao, Danh Nguyen The
    INTERNATIONAL JOURNAL OF INTERACTIVE DESIGN AND MANUFACTURING - IJIDEM, 2023, 17 (01): : 445 - 452
  • [29] Autonomous lemon grading system by using machine learning and traditional image processing
    Le Duc Hanh
    Danh Nguyen The Bao
    International Journal on Interactive Design and Manufacturing (IJIDeM), 2023, 17 : 445 - 452
  • [30] Damage index: Assessment of mould growth on building materials using digital image processing technique
    Bamgbopa, I. A.
    Aibinu, A. M.
    Salami, M. J. E.
    Shafie, A.
    Ali, M.
    Kassim, P. S. Jahn
    2008 INTERNATIONAL CONFERENCE ON COMPUTER AND COMMUNICATION ENGINEERING, VOLS 1-3, 2008, : 584 - +