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Laser-spectroscopic Information on Agricultural Products as Future Resources for Field server

17th APAN Meetings, University of Hawaii 2004.1.28-30. Laser-spectroscopic Information on Agricultural Products as Future Resources for Field server Yasunori Saito *, T. Koga*, T. Matsubara*, Y. Maruyama*, F. Kobayashi*, Nomura*, H. Ishizawa** and K. Komatsu***

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Laser-spectroscopic Information on Agricultural Products as Future Resources for Field server

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  1. 17th APAN Meetings, University of Hawaii 2004.1.28-30 • Laser-spectroscopic Information on • Agricultural Products as Future Resources for Field server • Yasunori Saito*, • T. Koga*, T. Matsubara*, Y. Maruyama*, F. Kobayashi*, • Nomura*, H. Ishizawa** and K. Komatsu*** • *Shinshu University (Engineering), Nagano, Japan • **Shinshu University (Textile Science & Technology), Ueda, Japan • ***Nagano Vegetable and Ornamental Crops Experiment Station, Nagano, Japan

  2. Furture Field Server Motivation Future field server (next generation) will be required more direct information on health and living status of agricultural products. Environment Information Direct Status Information Temperature Humidity Sun Light CO2 Water Content Image .... Physiological Biological Biophysical Photobiological Ecophysiological … + Field Server Purpose Application of laser spectroscopy as a new method to collect the direct status information of agricultural products Discussion on its possibility and usefulness

  3. Abnormal Fluorescence Emission Normal Laser Spectrum Sample Methodology Laser-induced Fluorescence Spectroscopy (LIFS) LIFS for Agriculture Project Molecular Energy Diagram Vegetation Fluorescence as an Index for Photosynthesis, Stress, Disease, Vitality, etc. No-use Chemical Solution Non Destructive Method Remote Sensor toward OPTICUL FARMING

  4. Examples 1) Lettuce : Optimal Harvest Time Decision 2) Coffee : Leaves Vitality (?) Distribution Map 3) Tomato : Seedling’s Remote LIF Imaging

  5. 1.5 1 0.5 2 Relative Intensity 0 300 400 500 600 700 800 Wavelength (nm) 1) Lettuce : Optimal Harvest Time Decision PC Nd:YAG Laser Spectrometor & CCD detector Fluorescence Detection Fiber Laser Transmission Fiber Mobile LIF Monitoring System LIF Spectra of Lettuce Leaf Chlorophyll Ferulic Acid & Others

  6. Outer Leaves Harvest time ‘99 ‘98 ‘97 1.5 ●　‘97 ▲　‘98 ■　‘99 1 Relative Intensity 0.5 0 100 80 ▲‘98 ‘99 ■ Chlorogenic acid Concentration(μg/g) 60 ■ ■ 40 ■ 20 ■ ■ 0 0 10 20 30 40 50 60 Days after Planting

  7. 2） Coffee Tree Leaves : Vitality (?) Distribution Map Image Intensified Cooled CCD Camera CW Violet Diode Laser Controll Units Liquid Crystal Tunable Filter PC LIF Imaging System Coffee Tree

  8. 5 0 Relative Value to660nm Fluorescence Image Intensity Activated ？ 460nm 530nm 740nm 685nm Chlorophyll Ferulic acid derivatives Phenylpropanoids NAD(P)H

  9. Gated ICCD Camera Liquid Crystal Tunable Filter 0.3m Camera Controller 1.5m PC Fluorescence Tomato Seedling Nd:YAG Laser 15m 3) Tomato : Seedling Remote LIF Imaging

  10. 600 700 800 Wavelength (nm) Remote Spectral Imaging of LIF F740/F620 F720/F620 F685/F620 F660/F620

  11. Needs direct comparison to physiological data (evidence) More experimental discussion required Conclusion Proposal : LIF information for a future field server System development and discussion of the usefulness 1) Lettuce : Optimal harvest time decision 2) Coffee tree leaves : Vitality distribution map 3) Tomato : Remote LIF imaging

  12. Needs direct comparison to physiological data (evidence) More experimental discussion required Plan Field Server Conclusion Proposal : LIF information for a future field server System development and discussion of the usefulness 1) Lettuce : Optimal harvest time decision 2) Coffee tree leaves : Vitality distribution map 3) Tomato : Remote LIF imaging

  13. Thank you very much !! Mahalo Nui Loa !!

  14. １）LIFスペクトル情報取得 ex 2） 形態付属情報の取得 　　　　　実験方法 　　　　　　　　ハウス管理栽培トマト葉 移動型LIFスペクトル計測装置

  15. #9 8 9 #7 6 7 5 4 #4 3 2 #1 1 0 #2 #0

  16. #5 #3 #8 #6

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