Ali el battay dr yap tsong shiuan kamaruzaman sijam dr mazlan hashim prof dr
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PROACTIVE APPROACH TO USE HYPERSPECTRAL REMOTE SENSING FOR CROP BIOTIC STRESS DETECTION - PowerPoint PPT Presentation


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Ali El Battay (Dr.) Yap Tsong Shiuan Kamaruzaman SIJAM (Dr.) Mazlan HASHIM (Prof. Dr.). PROACTIVE APPROACH TO USE HYPERSPECTRAL REMOTE SENSING FOR CROP BIOTIC STRESS DETECTION. Significance. PROACTIVE APPROACH TO USE HYPERSPECTRAL REMOTE SENSING FOR CROP BIOTIC STRESS DETECTION

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Ali el battay dr yap tsong shiuan kamaruzaman sijam dr mazlan hashim prof dr

Ali El Battay (Dr.)

Yap TsongShiuan

Kamaruzaman SIJAM (Dr.)

Mazlan HASHIM (Prof. Dr.)

PROACTIVE APPROACH TO USE HYPERSPECTRAL REMOTE SENSING FOR CROP BIOTIC STRESS DETECTION


Significance
Significance

PROACTIVE APPROACH TO USE HYPERSPECTRAL REMOTE SENSING FOR CROP BIOTIC STRESS DETECTION

  • “proactive” means controlling a situation by causing something to happen rather than waiting to respond to it after it happens. RS data are the mirror of what happened on Earth surface.

  • Using PRS, the change detected in RS data are deliberately induced and the Earth surface is intentionally modified in such a way that the electromagnetic signal reflects new information inaccessible by conventional RS techniques.


Significance cont d
Significance (cont’d)

  • Early detection and treatment of cash crop diseases can prevent unnecessary losses and significantly increase crop yield

  • The induced spectral response will aid in early detection of cash crop diseases through synchronization of remote sensing data acquisition with the routine farming practices and/or environmental fluctuations


Detection of vegetation biotic stress
Detection of vegetation biotic stress

Conventional methods

Remote sensing

Thermology

Detect transpiration

Passive

Sensitive to environment

Chlorophyll fluorescence imaging

Chlorophyll efficiency

Artificial illumination

Reflectance imaging

Satellite or airborne platform

Expensive

  • Visual Approach

  • Requires years of knowledge and experience

  • Time consuming

  • Labour intensive

  • Difference in perception among individuals


Objectives
Objectives

  • To prove the occurrence of pre-symptom stage (spectral) of ralstonia solanacearum infection in cucumber plant

  • To determine the possibility of inducing a measurable spectral change by using nutrient, light exposure and water stress during the pre-symptom stage


Scope
Scope

  • Crop Type: Cucumber

    (Cucumis sativus L.)

  • Pathogen: Ralstonia solanacearum (Bacterial Wilt)

  • Stimuli: Nutrient content, water content, light exposure


Cucumber cucumis sativus
Cucumber (CucumisSativus)

  • Cucumber (CucumisSativus L.) is one of the most widely produced vegetable in the world.

  • An annual, creeping herb, up to 5 m long

  • It is grown for the immature fruits which are used as a salad vegetable, pickles and sometimes boiled in stews


Ralstonia solanacearum
RalstoniaSolanacearum

  • A gram-negative, plant pathogenic, soil bacterium

  • The cause of bacterial wilt in a very wide range of potential host plants

  • Common crop hosts are:potatoes, tomatoes, aubergine, banana, geranium, ginger, tobacco, sweet peppers, olive, etc.

  • Transmission is through contaminated:tools, machinery, handlers, water, soil and seed


Symptoms
Symptoms

  • Severe rapid wilting of leaves

  • Chlorotic or stunted with adventitious roots on the stem

  • Glistening beads of dark gray slimy ooze from the infected xylem in stem cross sections

  • Bacterial streaming of fine, milky white strands from xylem vessels occurs when stems are cut and placed in water



Flow chart

Inoculated cucumber under normal condition

Non-inoculated cucumber under normal optimal conditions

Inoculated cucumber + manipulated nutrient

Non-inoculated cucumber + manipulated nutrient

Inoculated cucumber + manipulated light exposure

Non-inoculated cucumber + manipulated light exposure

Non-inoculated cucumber + manipulated water content

Inoculated cucumber + manipulated water content

Spectroradiometer measurement

Determination of pre-symptom stage of ralstonia solanacearum in cucumber

Quantitative estimation using vegetation indices

Detection of spectral signature changes in the pre-symptom stage

Flow Chart


Design

Non-inoculated Seed

Inoculated Seed

Water Stress

Backup

Backup

Water Stress

Normal Condition

Normal Condition

Light Stress

Nutrient Stress

Nutrient Stress

Light Stress

Design




Data capture
Data capture

  • ASD FieldSpecPro Spectroradiometer connected to the Panasonic Toughbook.

  • (b) Fiberoptic attached to pistol grip with 8˚ foreoptic.



Data collection
Data Collection

  • White reference

  • Dark current

  • Raw DN (10 times)

  • Constant lighting

  • Constant angle

  • Accompanying image and notes

θ









Objectives reminder
Objectives (reminder)

  • To prove the occurrence of pre-symptom stage (spectral) of ralstonia solanacearum infection in cucumber plant

  • To determine the possibility of inducing a measurable spectral change by using nutrient, light exposure and water stress during the pre-symptom stage









Normal Condition

Nutrient Stress

Non-inoculated

Inoculated

Non-inoculated

Inoculated

Water Stress

Light Stress

Non-inoculated

Inoculated

Inoculated

Non-inoculated


Conclusion
Conclusion

  • The occurrence of pre-symptom spectral stage of ralstoniasolanacearuminfection in cucumber plant has been proven, and last at least 10 days in this experimental conditions.

  • There is a possibility of inducing a measurable spectral change by reducing light exposure (-5 hours) during the spectral pre-symptom stage. MCARI and NRI vegetation indices respond to this induced EM-Spectral change.


Future work
Future Work

  • Understanding!

  • Modeling and Generalization!

  • Implementation feasibility?

  • .

  • .

  • .

  • Monetising!



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