Logical thinking, analysis and synthesis

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Multispectral analysis of remote sensing data for
early diagnosis of biotic stress in the potato
crop
Chávez, P. , P. Zorogastúa, C. Chuquillanqui ,
L.F. Salazar, V. Mares and R. Quiroz
CIP Annual Meeting November 2008
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Outline

• Description of the problem

• Principles of multispectral analysis

• The experimental work

• Results

• Conclusions

• Future work

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The problem

• Viruses such as (PYVV) threatens potato
  production in South America.
• Visual field monitoring is used to detect PYVV
  infection but the disease is detected after
  significant damage has occurred to photosynthetic
  tissues.
• A method for early diagnosis before yields are
  severely affected would be useful.
• We suggest that the measurement of canopy
  reflectance at several wavelengths, would allow
  disease patches to be identified earlier and
  thus, properly controlled.

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Principles of multispectral analysis

• The multispectral analysis is based on the
  absorption, reflection and transmission of solar
  radiation by plant tissues
• Reflectivity and absorption of light is
  determined by the biochemical and structural
  components of the plant, such as chlorophyll,
  water, proteins and cell wall materials
• All these components, particularly chlorophyll
  content, are affected by diseases, resulting in
  differences in the spectral signature of healthy
  and stressed plants

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The experimental work

• Three indoors experiments with a split-plot in
  time design with inoculated and control
  treatments in the main plot, and time
  measurements as sub-plots
• Six plants infected with PYVV and 3 virus-free as
  control comprised each repetition.
• The PYVV infection was induced through lateral
  graft in plants about 2 weeks after emergence
• A visual assessment of both PYVV-infected plants
  and virus-free plants was continuously conducted
• Multispectral images of the same plants were
  periodically recorded using an Agricultural
  Digital Camera equipped with visible red and near
  infrared sensors
• The images were analysed to obtain the NDVI, SAVI
  and IPVI
• Light reflectance was recorded by a Li-Cor 1800
  spectroradiometer, covering the 350-850 nm
  wavelength region.
• First and second-order derivatives were
  calculated for the spectroradiometric
  measurements as well as for the vegetation
  indices calculated from the spectral photography
  

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Results

• Vein yellowing symptoms in leaves were visually
  noted in infected plants 39 days after
  inoculation.

• A distinct reflectance pattern from infected
  plants was evident for several wavelengths 23
  days after inoculation

• The vegetation indexes tested also showed that
  from as early as 23 days after inoculation the
  NDVI, SAVI, and IPVI values could differentiate
  healthy from unhealthy plants

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Conclusions

• Changes in reflectance detected by remotely
  sensed spectroradiometry and multispectral
  imagery provided early detection of viral
  infection, long before symptoms were detected by
  the trained eye.

• An earlier observation of symptoms of damage to
  the photosynthetic micro-anatomy of plants will
  allow for an effective control of the viral
  infection and a lesser negative impact on yield.

• Infected plants presented differential
  reflectance from healthy ones in the blue and red
  regions of the electromagnetic spectrum, which
  will permit the design of low cost detection
  devices in the visible range of the spectrum.

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Future work

• Further tests under field conditions where tuber
  yields are measured will be conducted.

• An earlier observation of symptoms of damage to
  the photosynthetic micro-anatomy of plants will
  allow for an effective control of the viral
  infection and a lesser negative impact on yield.

• Infected plants presented differential
  reflectance from healthy ones in the blue and red
  regions of the electromagnetic spectrum, which
  will permit the design of low cost detection
  devices in the visible range of the spectrum.

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Thank you