Non-destructively Determining Blueberry (Vaccinium corymbosum L.) Leaf Area Using DPI-Based Software

Mehmet Serhat ODABAS; Gökhan KAYHAN; Hüseyin ÇELİK; Recai OKTAŞ

doi:https://doi.org/10.47115/bsagriculture.1090017

Makale detayları

Non-destructively Determining Blueberry (Vaccinium corymbosum L.) Leaf Area Using DPI-Based Software

Yazarlar:

Mehmet Serhat ODABAS | Gökhan KAYHAN | Hüseyin ÇELİK | Recai OKTAŞ

Yayıncı:

Hasan ÖNDER

Ana Başlıklar:

Tarım

Dergi:

Black Sea Journal of Agriculture 2022 Vol.5 Issue 3, pp.195-199

Belge Tipi:

Makale

Yayın Tarihi:

6/2022

Belge Dili:

İngilizce

Document ID (Org No.):

2000894438

Sıklık:

Üç Aylık

eISSN:

2618-6578

DOI:

https://doi.org/10.47115/bsagriculture.1090017

Özet:

 

Blueberries (Vaccinium spp.) are a popular crop all throughout the world. Blueberry (Vaccinium corymbosum L.) leaves were randomly selected from the experimental area of Ondokuz Mayis University, Faculty of Agriculture as a research material. Blueberries are high in polyphenolic chemicals, particularly anthocyanins, which are antioxidants and anti-inflammatory. A total of 1500 leaves were collected, with 100 for each cultivar, to represent the variety of sizes found on 15 plants of each cultivar. Manual leaf area measurement was made with a digital planimeter. The area was measured using a 300dpi resolution image read from the relevant file in such a way that every one of them is defined by 8bits in RGB color space. A weighted sum of the RGB components of the image is used to convert RGB values to grayscale values. This three-dimensional gray image generates a binary image. The Otsu method was used to determine the threshold value required to minimize the in-class variation of the threshold black and white pixels. Simulink was used for easy use of the end-user with the developed software. This software can be used for the area measurement of all plant leaves.

Makale detayları

Non-destructively Determining Blueberry (Vaccinium corymbosum L.) Leaf Area Using DPI-Based Software

Yazarlar: Mehmet Serhat ODABAS | Gökhan KAYHAN | Hüseyin ÇELİK | Recai OKTAŞ

Yayıncı: Hasan ÖNDER

Ana Başlıklar: Tarım

Dergi: Black Sea Journal of Agriculture 2022 Vol.5 Issue 3, pp.195-199

Belge Tipi: Makale

Yayın Tarihi: 6/2022

Belge Dili: İngilizce

Document ID (Org No.): 2000894438

Sıklık: Üç Aylık

eISSN: 2618-6578

DOI: https://doi.org/10.47115/bsagriculture.1090017

Sayı

Yazarlar:

Mehmet Serhat ODABAS | Gökhan KAYHAN | Hüseyin ÇELİK | Recai OKTAŞ

Yayıncı:

Hasan ÖNDER

Ana Başlıklar:

Tarım

Dergi:

Black Sea Journal of Agriculture 2022 Vol.5 Issue 3, pp.195-199

Belge Tipi:

Makale

Yayın Tarihi:

6/2022

Belge Dili:

İngilizce

Document ID (Org No.):

2000894438

Sıklık:

Üç Aylık

eISSN:

2618-6578

DOI:

https://doi.org/10.47115/bsagriculture.1090017