1 Proximal-sensing of Plant Diseases

Transcript

Hello! Welcome to the 5th week of the course “Detection, Diagnosis and Management of Plant Diseases”. In this week in the first talk will be talking about ‘Proximal sensing of plant diseases’. We all that in the fields situation its the human eye basically who first try to identify any problem associated with the plants particularly, if the plants are being infected by the pathogen or not. But, although it is a common practice this way of diagnosis may be not be full proof as human eye cannot trace the initial infection of plant pathogens and a human eye only identify if a visible change on the plant or plant parts is occurred due to development of symptoms by the particular pathogen that is infecting the plant. So technologies are coming in a big way to help and identify those pre systematic symptoms in the plants so that the disease can be properly diagnosed and proper controlled measure could be adopted.

The common method for diagnosis of plant disease include visual examination, microscopic evaluation, as well as molecular, serological, and microbiological techniques. But the new sensor-based methods assess the optical properties of plants within different regions of the electromagnetic spectrum and are able to utilize information beyond the visible range. They enable the detection of early changes in plant physiology due to biotic stresses, which is a limiting factor for human eye and that is why we normally have to wait till the symptom production stage for management of the particular pathogen.

Currently, the most promising techniques are sensors that measure reflectance, temperature, or fluorescence of the leave. Remote sensing is a method used to obtain information from plants or crops without direct contact or invasive manipulation. The concept has been recently enlarged by proximal, close-range or small-scale sensing of plant material. Proximal sensors may be hand-held, machine-mounted or attached to suitable unmanned aerial vehicles (UAVs).

Proximal Sensing vs. Remote Sensing

So, this a comparative between Proximal and Remote Sensing tools. In case of Proximal sensing normally autonomous systems are that can go very close the plants are used which are ground based as well as certain machine mountain cameras and another tools being used then sometimes even unmanned vehicles can also be used for Proximal sensing but mostly these are used as remote sensing tools. Further, aircraft or satellite are used for remote sensing detection of plant diseases.

Various sensors, like sensors like RGB, Multispectral, Hyperspectral, Thermal, chlorophyll fluorescence and 3D sensors are used for detection of plants symptom at various level at Cell, Leaf, Plant, Plot, Field or even at the Ecosystem level. So depending on the uses of the equipment or depending on the requirement this different sensors are used to detect and diagnose plant diseases.

Systems for Proximal Disease Sensing – First one is Thermography. The thermal imaging is a non-contact technique to determine the temperature distribution of any object in a short period of time. Infrared radiation emitted from plant surfaces may be recorded by detectors sensitive to radiation in the infrared region from 8 to 12 micrometer. Each pixel of image is related to a temperature value of the objects surface and may be illustrated in false color image. The technology can be used from microscope applications to ground-based equipment covering a range from leaf tissues to crop canopies. it is used to detect pathogens like tobacco plants infected with tobacco mosaic virus, sugar beet infected by Cercospora, downy mildew of cucumber caused by Pseudoperonospora, grapevine leaves infected with Plasmoparaviticola, and for apple leave infected by Venturia inaequalis. So we can see that a large number of applications has been used for proximal sensing of certain diseases again seasonal to perennial crop plants.

So, this is an example how Thermographic detection takes place. So this is Fusarium head blight in wheat and this is an infected wheat ear head and this is a healthy ear head and one can see that the thermal reflection or thermography of both infected and healthy shows variations in the different temperature scoring.

Then the next one is Fluorescence Measurements: So, various fluorescence parameters of plants irradiated with ambient excitation light may be recorded for the assessment of photosynthetic activity and the content of chlorophyll and other plant metabolites, e.g. phenols. These methods are very sensitive to detect changes in photosynthesis. Since disease development also affects the crops photosynthetic apparatus like pigments, electron transport chain, enzymes of the CO2 fixing Calvin cycle and the intensity as well as the spectrum of chlorophyll fluorescence are modified in diseased plants, sometimes even before visible symptoms appear. So, fluorescence measurement is again useful tool to detect if the plant leaf or plant is affected by certain pathogens because it causes change in the photosynthesis apparatus. This is an example, the left one is a normal colour image of the plant leaf whereas, the right one is a chlorophyll fluorescence parameter of an apple leaf infected by Venturia inaequalis. So, one can see that the image based on fluorescence parameters are very different from the normal visible range of light and this is how one can see that whether there is any abnormality in the leaf is taking place because of change in the fluorescence pattern.

Then the next one is Spectral Techniques – The reflectance of incoming electromagnetic radiation in the visible, near infrared and short wave infrared depends on multiple interactions like back scattering at the leaf surface and internal cellular structures, radiant energy absorption induced by leaf chemistry, for e.g. content of pigments, leaf water, proteins or carbon. So, all these factors determine how much light will be emitted back through the electromagnetic radiation. The detection of diseased plants, i.e. plants with a spectrum different from that of healthy ones, using spectroscopic techniques has been successfully used for the blast pathogen of rice i.e. Magnaporthe grisea on rice, Phytophthora infestans on tomato, Venturia inaequalis on apple trees, canker lesions on citrus fruits, Blumeria graminis i.e. the pordery mildew fungi on barley, and Rhizoctonia root and crown rot of sugar beet. So, infections of sugar beet by various leaf pathogens could be detected even pre-symptomatically using this technique.

So, these techniques are useful that is why even if the symptoms are not visible by naked eye in the plant hole but they will change in chlorophyll content or there is change in other physiological or molecular markers in the leaf. This technique can have different ability to detect those affected and healthy plants and that’s how they can give us an indication how what are the status of the plants health. So, here we can see that it’s wheat leaf infected by rust and you can see the spectrum or the hyperspectral data that is obtained from the infected leaf, it varies depending on the amount of leaf area covered by the pustules of the rust pathogen. So the Spectral Signature of Disease Symptoms can be similar for a particular disease and it varies from disease to disease. So, in case of healthy plants the spectral range is this whereas, the chlorotic tissues have the spectral range of the, there’s a middle line, it shows the chlorotic tissue from the rust pustules is developed that is the lowest or third line. So, with this type of spectrum we can very easily distinguish that whether the leaf is affected, whether there is any chlorotic area, whether there is any pustule present in the leaf surface. So, by looking at the data one can very well recognize whether the plants are healthy or infected.

So , with this we have seen how Proximal sensing can be done and what are the tools that are been used, how Thermography or Spectral data can help us in identifying or recognizing an infected plant by using Proximal sensing devices. So in the next class or in the next talk we will be talking about the remote sensing technologies that are used for plant disease diagnosis. Till then, have a good time.

Thank you very much.