Spectral reflectance characteristics of citrus canker and other peel conditions of grapefruit

被引:41
作者
Balasundaram, D. [1 ]
Burks, T. F. [1 ]
Bulanon, D. M. [1 ]
Schubert, T. [2 ]
Lee, W. S. [1 ]
机构
[1] Univ Florida, Dept Agr & Biol Engn, Gainesville, FL 32611 USA
[2] Florida Dept Agr & Consumer Serv, Gainesville, FL USA
关键词
Citrus canker; Discriminant analysis; Spectral reflectance; DEFECTS; IDENTIFICATION; INSPECTION; QUALITY; VISION; APPLES;
D O I
10.1016/j.postharvbio.2008.07.014
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
The presence of one fruit infected with citrus canker in a shipment may render the whole shipment unmarketable. Therefore it is important to classify fruit infected with citrus canker in the packinghouse before shipping the produce. The purpose of this research was to determine the significant wavelengths that could be used to classify canker among other peel conditions using grapefruit, a variety susceptible to canker. A spectrophotometer, with a wavelength range of 200-2500 nm, was used to measure the spectral reflectance data of peels from market quality fruit and fruits that were infected with cake melanose, wind scar, copper burn, greasy spot and canker. Statistical data analysis was performed on the spectral reflectance data to identify the wavelengths that had maximum discriminatory potential among the different peel conditions and to derive a discriminant function from the identified wavelengths. The discriminatory wavelengths were identified in the visible and the visible near infrared range. In addition, the classification based on the derived discriminant function resulted in 100% classification of canker. These results provide fundamental and practical use in the development of an automatic fruit sorter for canker classification based on spectral reflectance. Future research would involve the development of a vision-based classification system using the significant wavelengths identified in this study. (C) 2008 Elsevier B.V. All rights reserved.
引用
收藏
页码:220 / 226
页数:7
相关论文
共 13 条
  • [1] Multispectral inspection of citrus in real-time using machine vision and digital signal processors
    Aleixos, N
    Blasco, J
    Navarrón, F
    Moltó, E
    [J]. COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2002, 33 (02) : 121 - 137
  • [2] Citrus sorting by identification of the most common defects using multispectral computer vision
    Blasco, J.
    Aleixos, N.
    Gomez, J.
    Molto, E.
    [J]. JOURNAL OF FOOD ENGINEERING, 2007, 83 (03) : 384 - 393
  • [3] CANTEROS BI, 2004, P INT SOC CITR
  • [4] *FL DEP AGR CONS S, 2008, CITR CANK FACT SHEET
  • [5] GAFFNEY JJ, 1973, T ASAE, V16, P310
  • [6] Gottwald T. R., 2002, Plant Health Progress, P1
  • [7] KANE KE, 2006, THESIS U FLORIDA
  • [8] Development of a multi-spectral vision system for the detection of defects on apples
    Kleynen, O
    Leemans, V
    Destain, MF
    [J]. JOURNAL OF FOOD ENGINEERING, 2005, 69 (01) : 41 - 49
  • [9] Mehl PM, 2002, APPL ENG AGRIC, V18, P219
  • [10] Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy:: A review
    Nicolai, Bart M.
    Beullens, Katrien
    Bobelyn, Els
    Peirs, Ann
    Saeys, Wouter
    Theron, Karen I.
    Lammertyn, Jeroen
    [J]. POSTHARVEST BIOLOGY AND TECHNOLOGY, 2007, 46 (02) : 99 - 118