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

S. Abd Aziz, . and N. U. A. Ibrahim, . and D. Jamaludin, . and H. H. Harith, . Development of smartphone-based imaging techniques for the estimation of chlorophyll content in lettuce leaves. pp. 33-38. ISSN 2550-2166

Leaf color is a good indicator of plants 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 R 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 (R 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.

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Abstract

Leaf color is a good indicator of plants 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 R 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 (R 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.

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Item Type:	Article
AGROVOC Term:	Chlorophylls
AGROVOC Term:	Lettuces
AGROVOC Term:	Nondestructive testing
AGROVOC Term:	Plant physiology
AGROVOC Term:	Experimental design
AGROVOC Term:	Image analysis
AGROVOC Term:	Statistical analysis
AGROVOC Term:	Analysis of variance
AGROVOC Term:	precision agriculture
AGROVOC Term:	Remote sensing
Depositing User:	Mr. AFANDI ABDUL MALEK
Last Modified:	24 Apr 2025 00:55
URI:	http://webagris.upm.edu.my/id/eprint/10547

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