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Mathematical models for the estimation of leaf chlorophyll content based on RGB colours of contact imaging with smartphones: A pomegranate example Cover

Mathematical models for the estimation of leaf chlorophyll content based on RGB colours of contact imaging with smartphones: A pomegranate example

Folia Horticulturae
Volume 32 (2020): Issue 1 (June 2020)
By: Nurdan Özreçberoğlu and  İbrahim Kahramanoğlu  
Open Access
|Apr 2020

Figures & Tables

Figure 1

Experimental methodology and image acquisition: (A) selection of the leaf samples, (B): determination of the mid-point of the leaves, (C) a view of the red LED light from the closed box, (D) insertion of the leaf onto the closed box’s hole, (E) capturing of the contact image with a smartphone and (F) reading the RGB values of the images by using the histogram function of the Photoshop ME 7.0.
Experimental methodology and image acquisition: (A) selection of the leaf samples, (B): determination of the mid-point of the leaves, (C) a view of the red LED light from the closed box, (D) insertion of the leaf onto the closed box’s hole, (E) capturing of the contact image with a smartphone and (F) reading the RGB values of the images by using the histogram function of the Photoshop ME 7.0.

Figure 2

Captured leaf images with a smartphone when red LED passed (three red images from the left side) and when white LED passed (three green images from the right side).
Captured leaf images with a smartphone when red LED passed (three red images from the left side) and when white LED passed (three green images from the right side).

Figure 3

Stepwise linear regression analysis for leaf Chl content measured analytically in laboratory and the RGB values based on contact imaging with smartphone.
Stepwise linear regression analysis for leaf Chl content measured analytically in laboratory and the RGB values based on contact imaging with smartphone.

Correlation between the RGB colours and combination indices and leaf chlorophyll contents (for both mg ∙ g−1 and mg ∙ MW−1) of a pomegranate tree

RGB colours and combination indicesRed LED passedWhite LED passed
Chl (mg ∙ g−1)Chl (mg ∙ MW−1)Chl (mg ∙ g−1)Chl (mg ∙ MW−1)
R value−0.282−0.552**−0.225−0.257
G value0.1130.914**0.2100.460**
B value0.1460.893**−0.382*−0.364*
NRI−0.154−0.914**−0.195−0.424**
NGI0.1480.918**0.344*0.476**
NBI0.1720.897**−0.384*−0.371*
GMR0.2800.571**0.2790.484**
GMB0.0000.756**0.2870.456**
GRRI0.1460.917**0.2330.450**
GRVI0.1440.916**0.3020.475**
DGCI0.2800.574**−0.0140.009

Summary results for multiple regression analysis among G value, B value and Chl (Y)

CoefficientsStandard errort Statp-value
Intercept−0.09140.017741−5.15181.18E-05
G0.15370.0553222.77820.008948
B−0.00190.071268−0.02710.978541
DOI: https://doi.org/10.2478/fhort-2020-0006 | Journal eISSN: 2083-5965 | Journal ISSN: 0867-1761
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Language: English
Page range: 57 - 67
Submitted on: Jan 15, 2020
Accepted on: Feb 13, 2020
Published on: Apr 22, 2020
Published by: Polish Society for Horticultural Sciences (PSHS)
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year
Keywords:
colour index,
computer programs,
fast estimation,
multiple regression analysis,
plant health,
sustainable farming
Related subjects:
Life sciences,
Plant science,
Zoology,
Ecology,
Life sciences, other

© 2020 Nurdan Özreçberoğlu, İbrahim Kahramanoğlu, published by Polish Society for Horticultural Sciences (PSHS)
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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