Smartphone measuring chlorophyll content from plant leaves

Ojun Kwon, Tusan Park

Research output: Contribution to conferencePaperpeer-review

1 Scopus citations

Abstract

Chlorophyll quantification is vital in monitoring the growth of crops. There were many studies to measure chlorophyll from plant leaves. These includes fluorescence or absorbance analysis of chlorophyll extract or high performance liquid chromatography. However, these methods are destructive, time consuming and expensive for complicated and tedious extraction protocol of chlorophyll from leaves, and the use of high-cost instruments. The SPAD (Soil Plant Analysis Development) meter is an alternative of non-destructive and quick measuring tool for chlorophyll content in the field. However, it measures small area of a leaf which cannot represent the overall amount but still expensive. In this study, we developed a smartphone system which measures the chlorophyll from large area of crop leaves. A common smartphone was combined with an optical module to acquire images of crop leaf under a constant condition at all time without surrounded noise. The optical module consist of a side emitting optical fiber to illuminate the leaf from smartphone flash-light, confocal lens, leaf holder and cover. Crop leaf images were acquired using the optical module attached smartphone. The obtained RGB (Red-Green-Blue) image was converted into HSI (Hue-Saturation-Intensity) image. The result of image process and the SPAD value measured with SPAD meter was analyzed. Based on the linear model, we developed a Smartphone application to implement these processes. The performance of the developed smartphone system to measure the chlorophyll content was comparable with SPAD meter.

Original languageEnglish
DOIs
StatePublished - 2018
EventASABE 2018 Annual International Meeting - Detroit, United States
Duration: 29 Jul 20181 Aug 2018

Conference

ConferenceASABE 2018 Annual International Meeting
Country/TerritoryUnited States
CityDetroit
Period29/07/181/08/18

Keywords

  • Chlorophyll
  • Image analysis
  • Plant
  • Smartphone

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