Journal of Biosystems Engineering

Korean Society for Agricultural Machinery (한국농업기계학회)
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Detecting Drought Stress in Soybean Plants Using Hyperspectral Fluorescence Imaging

  • Mo, Changyeun (National Institute of Agricultural Sciences, Rural Development Administration) ;
  • Kim, Moon S. (Environmental Microbiology and Food Safety Laboratory, Agricultural Research Service, US Department of Agriculture) ;
  • Kim, Giyoung (National Institute of Agricultural Sciences, Rural Development Administration) ;
  • Cheong, Eun Ju (Division of Forest Sciences, College of Forest and Environment Sciences, Kangwon National University) ;
  • Yang, Jinyoung (Crop Systems and Global Change Laboratory, Agricultural Research Service, US Department of Agriculture) ;
  • Lim, Jongguk (National Institute of Agricultural Sciences, Rural Development Administration)
  • Received : 2015.11.05
  • Accepted : 2015.11.19
  • Published : 2015.12.01
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Abstract

Purpose: Soybean growth is adversely affected by environmental stresses such as drought, extreme temperatures, and nutrient deficiency. The objective of this study was to develop a method for rapid measurement of drought stress in soybean plants using a hyperspectral fluorescence imaging technique. Methods: Hyperspectral fluorescence images were obtained using UV-A light with 365 nm excitation. Two soybean cultivars under drought stress were analyzed. A partial least square regression (PLSR) model was used to predict drought stress in soybeans. Results: Partial least square (PLS) images were obtained for the two soybean cultivars using the results of the developed model during the period of drought stress treatment. Analysis of the PLS images showed that the accuracy of drought stress discrimination in the two cultivars was 0.973 for an 8-day treatment group and 0.969 for a 6-day treatment group. Conclusions: These results validate the use of hyperspectral fluorescence images for assessing drought stress in soybeans.

Keywords

References

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