Non destructive growth measurement of selected vegetable seedlings using machine vision
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NON-DESTRUCTIVE GROWTH MEASUREMENT OF SELECTED VEGETABLE SEEDLINGS USING MACHINE VISION PowerPoint PPT Presentation


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NON-DESTRUCTIVE GROWTH MEASUREMENT OF SELECTED VEGETABLE SEEDLINGS USING MACHINE VISION. Ta-Te Lin, Sheng-Fu Cheng, Tzu-Hsiu Lin, Meng-Ru Tsai Department of Agricultural Machinery Engineering, National Taiwan University, Taipei, Taiwan, ROC. INTRODUCTION.

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NON-DESTRUCTIVE GROWTH MEASUREMENT OF SELECTED VEGETABLE SEEDLINGS USING MACHINE VISION

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Non destructive growth measurement of selected vegetable seedlings using machine vision

NON-DESTRUCTIVE GROWTH MEASUREMENT OF SELECTED VEGETABLE SEEDLINGS USING MACHINE VISION

Ta-Te Lin, Sheng-Fu Cheng, Tzu-Hsiu Lin, Meng-Ru Tsai

Department of Agricultural Machinery Engineering,

National Taiwan University,

Taipei, Taiwan, ROC


Introduction

INTRODUCTION

  • Plant growth measurement and modeling

  • Machine vision technique

  • Seedling characteristics

  • Applications in production management


Objectives

OBJECTIVES

  • Image processing algorithm development

  • Growth measurements of selected vegetable seedlings

  • Model parameter determination and simulations


System implementation

SYSTEM IMPLEMENTATION


Non destructive growth measurement of selected vegetable seedlings using machine vision

SEEDLING CHARACTERISTICS

  • Stem length

  • Height

  • Span

  • Total leaf area

  • Top fresh weight

  • Top dry weight

  • Number of leaves


Image processing algorithm

IMAGE PROCESSING ALGORITHM


Result of node tracing

RESULT OF NODE TRACING


Result of node tracing1

RESULT OF NODE TRACING


Non destructive growth measurement of selected vegetable seedlings using machine vision

Calibration of cabbage top fresh weight from seedling projection area.


Non destructive growth measurement of selected vegetable seedlings using machine vision

Calibration of cabbage top dry weight from seedling projection area.


Non destructive growth measurement of selected vegetable seedlings using machine vision

Calibration of cabbage total leaf area from seedling projection area.


Non destructive growth measurement of selected vegetable seedlings using machine vision

Calibration of amaranth top fresh weight from seedling projection area.


Non destructive growth measurement of selected vegetable seedlings using machine vision

Calibration of amaranth top dry weight from seedling projection area.


Non destructive growth measurement of selected vegetable seedlings using machine vision

Calibration of amaranth total leaf area from seedling projection area.


Non destructive growth measurement of selected vegetable seedlings using machine vision

Calibration of kale top fresh weight from seedling projection area.


Non destructive growth measurement of selected vegetable seedlings using machine vision

Calibration of kale top dry weight from seedling projection area.


Non destructive growth measurement of selected vegetable seedlings using machine vision

Calibration of kale total leaf area from seedling projection area.


Non destructive growth measurement of selected vegetable seedlings using machine vision

Comparison between manually measured top fresh weight and that determined by the automatic measurement system.


Non destructive growth measurement of selected vegetable seedlings using machine vision

Comparison between manually measured total leaf area and that determined by the automatic measurement system.


Non destructive growth measurement of selected vegetable seedlings using machine vision

Comparison between manually measured top fresh weight and that determined by the automatic measurement system.


Non destructive growth measurement of selected vegetable seedlings using machine vision

Serial images of kale seedlings at various growth stages. (images are not of the same scale)


Non destructive growth measurement of selected vegetable seedlings using machine vision

Kale seedlings images from different angles


Non destructive growth measurement of selected vegetable seedlings using machine vision

Top fresh weight of kale seedlings growing under 25/20C. Each curve indicates individual seedling.


Non destructive growth measurement of selected vegetable seedlings using machine vision

Average plant height of kale seedlings grown under five different day/night temperatures.


Non destructive growth measurement of selected vegetable seedlings using machine vision

Average plant top fresh weight of kale seedlings grown under five different day/night temperatures.


Non destructive growth measurement of selected vegetable seedlings using machine vision

Average top dry weight of kale seedlings grown under five different day/night temperatures.


Non destructive growth measurement of selected vegetable seedlings using machine vision

Average total leaf area of kale seedlings growing under five different day/night temperatures.


Non destructive growth measurement of selected vegetable seedlings using machine vision

PLANT GROWTH MODELS

  • LOGISTIC MODEL

Y = Y0 / [ Y0 + ( 1 -  Y0 ) e-m t]

t : Time

Y : Plant characteristics

 : Growth constant

 : Reciprocal of Y when t = 

Y0 : Y at time = 0


Non destructive growth measurement of selected vegetable seedlings using machine vision

PLANT GROWTH MODELS

  • RICHARDS MODEL

Y = Y0 / { ( Y0) + [ 1 - ( Y0 )] e-m t }1/

t : Time

Y : Plant characteristics

 : Growth constant

 : Reciprocal of Y when t = 

Y0 : Y at time = 0

 : For logistic model,  =1


Non destructive growth measurement of selected vegetable seedlings using machine vision

Comparison of regression curves to the experimental data. Top fresh weight of cabbage seedlings growing under various day/night temperatures was used as an example.


Non destructive growth measurement of selected vegetable seedlings using machine vision

GROWTH MODEL PARAMETERS


Growth model parameters

GROWTH MODEL PARAMETERS


Non destructive growth measurement of selected vegetable seedlings using machine vision

RELATIVE GROWTH RATE, RGR

  • LOGISTIC MODEL

  • RICHARDS MODEL


Non destructive growth measurement of selected vegetable seedlings using machine vision

Predicted relative growth rate of cabbage seedling growing under 5 different day/night temperatures using the logistic model.


Non destructive growth measurement of selected vegetable seedlings using machine vision

Comparison of calculated top fresh weight of cabbage, amaranth and kale seedlings growing at 25/200C.


Non destructive growth measurement of selected vegetable seedlings using machine vision

Comparison of calculated relative growth rate (RGR) of cabbage, amaranth and kale seedlings growing at 25/200C.


Non destructive growth measurement of selected vegetable seedlings using machine vision

SEEDLING 3-D RECONSTRUCTION

  • ARTIFICIAL WIRE MODEL


Non destructive growth measurement of selected vegetable seedlings using machine vision

SEEDLING 3-D RECONSTRUCTION

  • CABBAGE SEEDLING


Conclusions

CONCLUSIONS

  • A non-destructive machine vision system was successfully developed for the measurement of vegetable seedling characteristics. A new algorithm for the determination of seedling nodes was implemented.

  • 3-dimension reconstruction of seedling architecture can be achieved with the nodal coordinates determined with the machine vision system.

  • Growth responses of cabbage, kale and amaranth seedlings under various temperature conditions were measured and compared.

  • The dynamic growth responses of selected vegetable seedlings were analyzed with logistic and Richards growth model and the relative growth rates of the seedlings under various conditions were calculated.


Non destructive growth measurement of selected vegetable seedlings using machine vision

FUTURE DEVELOPMENT

  • Measurement under natural lighting

  • Leaf area index (LAI) determination

  • Extraction of information from serial images

  • Modification of the current growth model

  • Application of geometrical modeling in seedling 3D reconstruction


Non destructive growth measurement of selected vegetable seedlings using machine vision

THANK YOU

謝 謝


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