Relationship between vegetation indices and SPAD values of waxy corn using an unmanned aerial vehicle

Panath Jermthaisong, Sununtha Kingpaiboon, Petchporn Chawakitchareon, Yasushi Kiyoki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The amount of chlorophyll in a plant can indicate leaf N concentration, as chlorophyll is a major component of nitrogen. Identifying chlorophyll levels in plants, therefore, leads to appropriate nitrogen fertilizer recommendations for the plants and to their fertilization at the proper time, optimizing efficiency of agricultural production and helping to preserve the environment by reducing excess use of nitrogen fertilizer. Measuring leaf N concentration in a high accuracy laboratory is expensive and time consuming, whereas a SPAD chlorophyll handheld meter can be carried conveniently in the field and can assess rapidly. However, the handheld meter's capacity is limited, especially in large areas, where samples must be taken to represent an area. The use of vegetation indices calculated from UAV imagery and correlated with SPAD values enables better estimations of N leaf concentrations over large areas. The result showed that relationship between NDVI and SPAD value (chlorophyll contents) of waxy corn (Zea mays L. var. ceratina) at V6 and R1 stage in R2 were 0.594 and 0.632, respectively. The results of this study are beneficial for knowing the amount of chlorophyll in plants, which can result in accurate nitrogen fertilizer requirements and better administration of management zones in precision agriculture.

Original languageEnglish
Title of host publicationInformation Modelling and Knowledge Bases XXX
EditorsTatiana Endrjukaite, Hannu Jaakkola, Alexander Dudko, Yasushi Kiyoki, Bernhard Thalheim, Naofumi Yoshida
PublisherIOS Press
Pages312-318
Number of pages7
ISBN (Electronic)9781614999324
DOIs
Publication statusPublished - 2019 Jan 1

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume312
ISSN (Print)0922-6389

Keywords

  • SPAD Chlorophyll Meter
  • UAV
  • Vegetation Indices
  • Waxy Corn

ASJC Scopus subject areas

  • Artificial Intelligence

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