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Development of smartphone-based imaging techniques for the estimation of chlorophyll content in lettuce leaves

Leaf color is a good indicator of plant’s health status. In this study, a new image acquisition technique was developed to estimate chlorophyll content of lettuce leaves. The images of lettuce leaves grown under artificial light were acquired using a smartphone. Leaves images was captured by direct...

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Main Authors: Ibrahim, Nur Ul Atikah, Abd Aziz, Samsuzana, Jamaludin, Diyana, Harith, Hazreen Haizi
Format: Article
Language:English
Published: Rynnye Lyan Resources 2021
Online Access:http://psasir.upm.edu.my/id/eprint/96702/1/ABSTRACT.pdf
http://psasir.upm.edu.my/id/eprint/96702/
https://www.myfoodresearch.com/vol-59474supplementary-1.html
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spelling my.upm.eprints.967022022-12-01T08:40:54Z http://psasir.upm.edu.my/id/eprint/96702/ Development of smartphone-based imaging techniques for the estimation of chlorophyll content in lettuce leaves Ibrahim, Nur Ul Atikah Abd Aziz, Samsuzana Jamaludin, Diyana Harith, Hazreen Haizi Leaf color is a good indicator of plant’s health status. In this study, a new image acquisition technique was developed to estimate chlorophyll content of lettuce leaves. The images of lettuce leaves grown under artificial light were acquired using a smartphone. Leaves images was captured by directly attached the leaves to the camera lens with the aid of background illumination from SMD LED. Red, green, blue (RGB) color indices were extracted from leaves color images and some vegetation indices were also calculated. Then, the correlation between these indices and chlorophyll content obtained from SPAD502 chlorophyll meter were evaluated. Significant correlation was found between all the image indices and chlorophyll content with the R2 ranging from 0.63 to 0.85 except for G and B indices from RGB component. Highly significant correlation was found between vegetation indices (VI) and chlorophyll content (R2= 0.85) with the lowest root mean square error (RMSE) of 8.07 g of chlorophyll/100 g fresh tissue. This demonstrated that the chlorophyll content of lettuce leaves can be successfully estimated using regular smartphone with added background light illumination from SMD LED. Rynnye Lyan Resources 2021 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/96702/1/ABSTRACT.pdf Ibrahim, Nur Ul Atikah and Abd Aziz, Samsuzana and Jamaludin, Diyana and Harith, Hazreen Haizi (2021) Development of smartphone-based imaging techniques for the estimation of chlorophyll content in lettuce leaves. Food Research, 5 (suppl.1). 33 - 38. ISSN 2550-2166 https://www.myfoodresearch.com/vol-59474supplementary-1.html 10.26656/fr.2017.5(S1).036
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Leaf color is a good indicator of plant’s health status. In this study, a new image acquisition technique was developed to estimate chlorophyll content of lettuce leaves. The images of lettuce leaves grown under artificial light were acquired using a smartphone. Leaves images was captured by directly attached the leaves to the camera lens with the aid of background illumination from SMD LED. Red, green, blue (RGB) color indices were extracted from leaves color images and some vegetation indices were also calculated. Then, the correlation between these indices and chlorophyll content obtained from SPAD502 chlorophyll meter were evaluated. Significant correlation was found between all the image indices and chlorophyll content with the R2 ranging from 0.63 to 0.85 except for G and B indices from RGB component. Highly significant correlation was found between vegetation indices (VI) and chlorophyll content (R2= 0.85) with the lowest root mean square error (RMSE) of 8.07 g of chlorophyll/100 g fresh tissue. This demonstrated that the chlorophyll content of lettuce leaves can be successfully estimated using regular smartphone with added background light illumination from SMD LED.
format Article
author Ibrahim, Nur Ul Atikah
Abd Aziz, Samsuzana
Jamaludin, Diyana
Harith, Hazreen Haizi
spellingShingle Ibrahim, Nur Ul Atikah
Abd Aziz, Samsuzana
Jamaludin, Diyana
Harith, Hazreen Haizi
Development of smartphone-based imaging techniques for the estimation of chlorophyll content in lettuce leaves
author_facet Ibrahim, Nur Ul Atikah
Abd Aziz, Samsuzana
Jamaludin, Diyana
Harith, Hazreen Haizi
author_sort Ibrahim, Nur Ul Atikah
title Development of smartphone-based imaging techniques for the estimation of chlorophyll content in lettuce leaves
title_short Development of smartphone-based imaging techniques for the estimation of chlorophyll content in lettuce leaves
title_full Development of smartphone-based imaging techniques for the estimation of chlorophyll content in lettuce leaves
title_fullStr Development of smartphone-based imaging techniques for the estimation of chlorophyll content in lettuce leaves
title_full_unstemmed Development of smartphone-based imaging techniques for the estimation of chlorophyll content in lettuce leaves
title_sort development of smartphone-based imaging techniques for the estimation of chlorophyll content in lettuce leaves
publisher Rynnye Lyan Resources
publishDate 2021
url http://psasir.upm.edu.my/id/eprint/96702/1/ABSTRACT.pdf
http://psasir.upm.edu.my/id/eprint/96702/
https://www.myfoodresearch.com/vol-59474supplementary-1.html
_version_ 1752147920339075072
score 13.211869

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