Prince Kumar Gupta presented on the role of phenomics in plant pathology. Phenomics refers to quantifying the total phenotypes of an organism across different levels, from molecules to organs. It is useful for functional gene analysis, screening mutants, detecting disease epidemics, and facilitating germplasm screening. Various tools of phenomics were discussed, including digital imaging, multispectral/hyperspectral imaging, ultrasound, X-ray, MRI, thermal imaging, and chlorophyll fluorescence imaging. Platforms for phenomics include controlled environment, ground-based, and aerial-based systems. Research networks and software companies were also mentioned. Improving early disease detection and developing more precise sensing tools were discussed as areas for future focus.

1. Doctoral seminar 2
Role of Phenomics in Plant Pathology
Presented by:
Prince Kumar Gupta
ID. No. 54157
Deptt. of Plant Pathology,
GBPUAT

2. introduction
Introduction
Relevence
Applications
Phenomic data management
Tools of phenomics
Phenomics Platform
Research Coordinating Organisation
Software Companies
Conclusion And Future Prospect
Case Studies

3. The Challenge ….
In the next 50 years, we’re
going to have to produce more
food than we have in the last
10,000 years. We need to find
ways to employ technology
and science to increase
production to feed a hungry
planet.
Norman Borlaug
Nobel Peace Prize Laureate April 7, 2009

4. Phenomics
• Phenomics term given by Gerlai,
2002.
• The term phenomic refers to sum total of
phenotypes at various levels ranging
from molecules to organs and the whole
organism.
• Phenotyping is essential for – functional analysis of
specific genes forward and reverse genetic analysis
production of plants

5. Forward phenomics vs Reverse phenomics

6. • Identification of stress.
• Rapid and efficient screening for mutants.
• Detection and monitoring of disease epidemics in field.
• Detection of root attack by pathogens.
• Facilitate screening of germplasm.
• Study of various physiological processes.
Relevance…….

7. Phenomics
Functional
Genomics
Agricultural
Research
Metabolic
Engineering

8. Agriculture
Agriculture
biotechnology
Entomology
Soil Science
Agronomy
Plant
Breeding
Plant
Pathology

10. In short……….

11. Phenomics Data Management
Phenomic data management involves three critical components
Sensory data
Model
Development
Genotype and
Phenotype
Interactions
Understand
Resource
Development
and Sharing
Networking
Algorithm and
Program
Phenotypic
Information
Management
Databases

12. Digital Imaging In Visible Electromagnetic Spectrum
Digital cameras are designed to sensing light in the visible range of
electromagnetic spectrum. Devices working with these wavelengths are also called
RGB devices because they use the red, green, and blue light color model to
estimate the true color of each pixel. The optical properties of plants are a complex
phenomenon that depends on transmission of light through the plant tissue,
absorption of light by plant chemicals (e.g., pigments, water, and sugars), and
reflection of light by plant surface or internal structures. Reflectance at the visible
range of electromagnetic spectrum is predominantly influenced by plant pigments,
while plant internal structures, water content, and chemical composition affect
primarily reflectance.
Analysis of digital images on the microscopic, organ, plant, or field level is an important
tool used in plant pathology. RGB-based sensors detect changes on plants occurring due
to pathogen infections such as appearance of pathogen structures (e.g., presence of
hyphae) or reaction of plants to pathogens (e.g., degradation of tissue leading to
chlorosis, necrosis, or changes in organ structure).
This nondestructive analysis can be performed with freely available, web-based
software on images taken in the laboratory, greenhouse, or field.

14. Multispectral and Hyperspectral Imaging
• Typical RGB image (eg. “normal” image in formats such
as .jpeg) is made up of 3 bands:
• Multispectral images and hyperspectral images have many more than this (our
images have 240 bands ranging from ~ 400 nm to 1000 nm).
• Average image size: 800 MB

18. Ultrasound
The ultrasound analyzer. a
multicomponent system includes a
piezoelectric transducer, a Kiethly 194 high-
speed voltage digitizer, a personal computer,
an IEEE-488 interface board, and an ASSYST
engineering package. Sample are dropped
approximately 10 cm onto a piezoelectric
transducer tilted at a 30° angle. The sample
is then released, undamaged, into a
collecting pan. A low-frequency sound wave
is generated by the transducer on impact
and is converted into an electrical impulse
signal, amplified, and passed on to a voltage
digitizer. The digitizer converts the
electrical signal from analog to digital form,
which is transferred to a personal computer
where the data acquisition program
measures the magnitude of the electrical
impulse signal at time intervals.

19. Objective of this study was to investigate the ability of ultrasound analysis to detect
asymptomatic infection of soybean seed infection by these pathogens and thus to
determine its potential as a means of removing asymptomatic seeds from seed lots
during conditioning.

20. INCIDENCE %

22. X-ray
Electromagnetic radiation with
wavelength from 10 to 100 pm
called hard X- ray and the radiation
with wavelength between 100 to 10
nm called soft X- ray.
Technology that uses computer
processes x- rays to produced
tomographic images of specific areas
of scanned object and can generate a
3D image of inside of object from
large series of 2D image.

23. Magnetic Resonance Imaging (MRI)
Also known as nuclear magnetic resonance imaging. It is a scanning technique for create
detail images of object.

24. The objective of these experiments was to examine the potential of MRI for
detection of biotic changes in sugar beet plants due to pathogen influence with
special reference to the following aspects: (i) investigation of changes of root
geometry due to H. schachtii presence; (ii) visualization of rotting symptoms
caused by R. solani; (iii) detection of cysts and syncytia of H. schachtii on or in the
roots; and (iv) examination of the inter-relationships between R. solani and H.
schachtii in a soil environment

25. Nuclear magnetic resonance image of healthy sugar beet plant (A) and plants inoculated
with Heterodera schachtii (B); Rhizoctonia solani (C), and Rhizoctonia solani with
Heterodera schachtii (D) 28 d after inoculation.

26. Control Inoculated with
Heterodera schachtii
Rhizoctonia solani with
Heterodera schachtii

27. Thermal imaging
Thermal imaging allows for the visualization of infrared radiation of wavelength 9 to 14µm,
indicating an object as the temperature across the object surface. Thermal imaging (fluke
thermal imager Ti32)is used to measure the leaf temperature to study the plant water
relation, and specifically for stomatal conductance. Abiotic or biotic stresses often result
decreased rates of photosynthesis and transpiration. Susceptible interaction between plant
and pathogen usually lead to early decreased in temperature

28. The objectives of this study were to: Assess the potential of thermal imagery to detect
powdery mildew disease; evaluate the disease severity of wheat leaves infected by powdery
mildew, and assess the impact of environmental conditions during measurement of wheat
for the assessment and quantification of powdery mildew

30. Chlorophyll Fluorescence Imaging
Change in photosynthetic responses of infected tissue can be detection by this method
based on CFI. It is well established, nondestructive method for investigation effect of
pathogens on photosynthetic metabolism of host plant at whole-plant or detached leaf.
The analysis based on principle that the energy of light absorbed by chlorophyll molecules
is either used in photosynthesis, dissipated as heat, or re-emitted as chlorophyll
fluorescence. The data provide information about the efficiency of photosynthesis and
heat dissipation.
So several parameters (fv/fm) derive from measurement of chlorophyll fluorescence can
investigate the relationship with change in photosynthesis occurring during plant
pathogen-interaction.

33. Phenomics Platform
Controlled
Environment Ground based
Platform
Aerial based
platform
Controlled Environment

34. Phonospex
https://phenospex.com/products/plant-phenotyping/science-planteye-3d-laser-scanner/ planteye-f500-multispectral-3d-laser-
scanner/

35. Ground Based Plant Phenomics Platform
Field Scanalyzer (LemnaTec)
http://www.lemnatec.com/products/

36. sonar proximity sensor/
infrared radiometer sensor
multi-spectral crop canopy sensor
GPS-RTK receiver-antenna
Andrade-Sanchez P et al (2014) Funct Plant Biol 41: 68-79

37. Purpose Built Crop Monitoring Buggy
Rebetzke G J et al (2013) Funct Plant Biol 40:1-13

38. Aerial Plant Phenotyping Platfprm
Watanabe K et al (2017) Front Plant Sci 8
Unmanned aerial vehicle (UAV)

39. Chapman S C et al (2014) Agronomy 4(2):279-301
Phenocopter

40. Root Phenotyping
Minirhizotrons
Rhizolysimeters

41. Software packages for imaging roots and
extracting quantitative data from captured root
images
•RootScan
•RootNav, DART
•GiARoots
•IJ Rhizo,
•RootSystemAnalyzer
•RootReader
•RootReader3D
Root Image Analysis

43. Research Coordinating Organisations
International Plant
Phenotyping Network
European Plant Phenomics
Network
North American Plant
Phenomics Network
Nordic Plant Phenomics
Network
Latin American Plant Phenomics
Network

44. PHENOME- The French Plant
Phenomics Network
Austrian Plant Phenomics
Network
Germany Plant Phenomics
Network
China plant phenomics
network
National Coordinating Organisations

45. Indian Plant Phenomics Facilities
CRIDA, Hyderabad
NIASM, Baramati

46. Enable exchange of knowledge, information and expertise across
many diciplines involved in plant phenomics by providing a
network linking member, developers
National Plant
phenomics facility at
ICAR- Indian instiitute of
Horticultural research
National Plant
phenomics facility at
IARI, New Delhi

47. Software Companies……..
Some of these companies encourage co- development (system
customization, software development for computation) as a
process of improving their current product and product
utilization such as Lemnashare and Lemna launcher etc.

48. Use of phenomics technologies - detecting specific
phenotypic reactions- plant- pathogen interaction
become more frequent in recent year.
Phenotyping Sensing techniques in combination
with weather monitoring system, diagnostic assay
provide tools for early detection of disease.
Sensor based phenomics tools for accurate
detection of plant disease, also have impact on
postharvest quality.

49. In order to increase the ability of real-time
detection of wide range of fungal diseases, our
focused should on developing early warning
system for disease detection.
Further need to increase the resolution in
order to identify the giant cells in the roots
bythe non-destructive system
UAV system provided a basis to develop site-
specific precision fungicide application
technology for control of this important
disease in the future.