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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Rynnye Lyan Resources
2021
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| Online Access: | http://psasir.upm.edu.my/id/eprint/96702/ http://psasir.upm.edu.my/id/eprint/96702/1/ABSTRACT.pdf |
| _version_ | 1848862425120505856 |
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| author | Ibrahim, Nur Ul Atikah Abd Aziz, Samsuzana Jamaludin, Diyana Harith, Hazreen Haizi |
| author_facet | Ibrahim, Nur Ul Atikah Abd Aziz, Samsuzana Jamaludin, Diyana Harith, Hazreen Haizi |
| author_sort | Ibrahim, Nur Ul Atikah |
| building | UPM Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T13:16:49Z |
| format | Article |
| id | upm-96702 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T13:16:49Z |
| publishDate | 2021 |
| publisher | Rynnye Lyan Resources |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-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 |
| 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 |
| title | 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_short | 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 |
| url | http://psasir.upm.edu.my/id/eprint/96702/ http://psasir.upm.edu.my/id/eprint/96702/ http://psasir.upm.edu.my/id/eprint/96702/ http://psasir.upm.edu.my/id/eprint/96702/1/ABSTRACT.pdf |