A new method for pedicel/peduncle detection and size assessment of grapevine berries and other fruits by image analysis

  1. Cubero, S. 12
  2. Diago, M.P. 24
  3. Blasco, J. 1
  4. Tardáguila, J. 2
  5. Millán, B. 2
  6. Aleixos, N. 3
  1. 1 Instituto Valenciano de Investigaciones Agrarias
    info

    Instituto Valenciano de Investigaciones Agrarias

    Moncada i Reixac, España

    GRID grid.419276.f

  2. 2 Instituto de Ciencias de la Vid y del Vino
    info

    Instituto de Ciencias de la Vid y del Vino

    Logroño, España

    GRID grid.481584.4

  3. 3 Universidad Politécnica de Valencia
    info

    Universidad Politécnica de Valencia

    Valencia, España

    GRID grid.157927.f

  4. 4 Catholic University of the Sacred Heart
    info

    Catholic University of the Sacred Heart

    Milán, Italia

    GRID grid.8142.f

Journal:
Biosystems Engineering

ISSN: 1537-5110

Year of publication: 2014

Volume: 117

Issue: C

Pages: 62-72

Type: Article

Export: RIS
DOI: 10.1016/j.biosystemseng.2013.06.007 SCOPUS: 2-s2.0-84890815380 WoS: 000330157000008 GOOGLE SCHOLAR

Metrics

Cited by

  • Scopus Cited by: 39 (14-07-2021)

Journal Citation Reports

  • Year 2014
  • Journal Impact Factor: 1.619
  • Best Quartile: Q1
  • Area: AGRICULTURE, MULTIDISCIPLINARY Quartile: Q1 Rank in area: 9/56 (Ranking edition: SCIE)
  • Area: AGRICULTURAL ENGINEERING Quartile: Q2 Rank in area: 4/12 (Ranking edition: SCIE)

SCImago Journal Rank

  • Year 2014
  • SJR Journal Impact: 0.881
  • Best Quartile: Q1
  • Area: Agronomy and Crop Science Quartile: Q1 Rank in area: 46/346
  • Area: Animal Science and Zoology Quartile: Q1 Rank in area: 64/409
  • Area: Control and Systems Engineering Quartile: Q1 Rank in area: 55/851
  • Area: Food Science Quartile: Q1 Rank in area: 44/308
  • Area: Soil Science Quartile: Q2 Rank in area: 29/127

CiteScore

  • Year 2014
  • CiteScore of the Journal : 3.2
  • Area: Animal Science and Zoology Percentile: 86
  • Area: Agronomy and Crop Science Percentile: 82
  • Area: Food Science Percentile: 80
  • Area: Soil Science Percentile: 76
  • Area: Control and Systems Engineering Percentile: 75

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Abstract

The berry size of wine-grapes has often been considered to influence wine composition and quality, as it is related to the skin-to-pulp ratio of the berry and the concentration of skin-located compounds that play a key role in the wine quality. The size and weight of wine-grapes are usually measured by hand, making it a slow, tedious and inaccurate process. This paper focuses on two main objectives aimed at automating this process using image analysis: (1) to develop a fast and accurate method for detecting and removing the pedicel in images of berries, and (2) to accurately determine the size and weight of the berry. A method to detect the peduncle of fruits is presented based on a novel signature of the contour. This method has been developed specifically for grapevine berries, and was later extended and tested with an independent set of other fruits with different shapes and sizes such as peppers, pears, apples or mandarins. Using this approach, the system has been capable of correctly estimating the berry weight (R2 > 0.96) and size (R2 > 0.97) of wine-grapes and of assessing the size of other fruits like mandarins, apples, pears and red peppers (R2 > 0.93). The proven performance of the image analysis methodology developed may be easily implemented in automated inspection systems to accurately estimate the weight of a wide range of fruits including wine-grapes. In this case, the implementation of this system on sorting tables after de-stemming may provide the winemaker with very useful information about the potential quality of the wine. © 2013 IAgrE.