Application Of Precision Agriculture Strategies For Management Of Plant Diseases
Agriculture is the backbone of India with more than 60 percent of the population depending on it directly or indirectly for sustainability however, higher return in agriculture is a seldom. The reasons for low returns can be ascribed to lack of awareness of recent advanced technologies, irrational use of inputs, improper management practices, invasion by alien pest and pathogen. Among the constrains hindering the higher returns improper management practices and invasion by alien pest and pathogen are of prime concern. Crop yields are influenced by several factors viz. , quality of seeds, fertility status of soil, availability of irrigation, climatic conditions, incidence of pest and disease and fertilizer application. Incidence of pest and disease are very devastating which has accounted for more than 40 per cent yield loss globally. Any technology which can scale back the cost incurred on inputs and improve the yield or maximize the return is the actual need of the hour. Twenty first century agriculture is all about technology in general and sensors, internet of things and artificial intelligence in particular. This technology when made available to the grower will simplify the task of decision making based on the data provided by the information systems. Precision agriculture is a pro-active approach for management of risk at field level that has changed the perspective of agriculture from survival to sustainability has it allows efficient use of the input based on information technology which facilitates farm operations like sowing, weeding, crop protection and harvesting to be taken up at the right time. Precision agriculture is the art of managing the farm, based on the observations, calculation and responses to inter and intra field variability with the aim of developing the decision support system to attain higher returns per unit input. Precision agriculture approaches mostly utilize the global positioning system (GPS), geographic information system (GIS), hyperspectral imaging and sensors tools are employed to spot the differences and adjust management actions or input accordingly.
Internet of things (IoT) based moniotiring system for early disease forcasting
The present era has witnessed the wrath of climate change leading to increased global temperature, melting of north and south pole and most importantly the ununiform rain which has facilitated the devasting spread of key pathogen and brought down the yield. Growers are not aware of such spread of disease as result they tend to loss a portion of there income. In recent days the internet of things (IoT) are gaining importance agriculture and various application-based areas. IoT basically deals with the wireless sensor network (WSN) technology and it can be accessed through internet. Several diseases are assessed and information regarding the disease their symptoms and architecture of the plant and disease spot are feed to the software. The software is equipped with the ability to develop a plant disease models. In addition, the software will be attached with the sensor that are flexible to use even on different crop if grown in different season or is the same season as in case of multiple cropping system. Usually the monitoring system for disease forecast consists of three modules viz. , hardware, software and agriculture module. Hardware is used basically for the collection of data on desired as parameters using various sensors (weather conditions), software (artificial intelligence based) collects, process and stores the data. Finally, it provides the accurate solution to the possible occurrence of pathogen problem based on the already stored model. Agriculture model will be helpful for the development of disease model in various weather conditions and also validate the solutions provided by the software. Most importantly all this is done through wireless communication network and artificial intelligence is the heart of the system.
Remote sensing and sensor-based detection for management of plant disease
The production of food crops is limited as a result there is an enormous demand for quality and quantity of food. In order to meet the demand of the society we need to produce more that what is required and this is impossible without the use of technology. Pest and disease besides abiotic stress (drought, salinity and alkalinity) are primary reason for loss of yield not only in terms of quantity but also in terms of quantity also. Remote sensing and sensor-based detection and management of disease is an innovative approach to optimize the agriculture production. The fungicides used in agriculture are costly and harmful to a certain level hence care must be taken to get a better control of disease with a minimal quantity of fungicides. Plants or seed under the stress (biotic or abiotic) show physical symptoms like reduced growth, mosaic leaves, albinism, yellowing of leaves, reduced tillers and yield. Besides the physical symptoms they also produce some volatiles (ethanol, propanol, 2-methyl propanol and hexene) during the biotic stress and these volatile compounds released by plants depends on the pathogen attacking it. The produced volatile compounds are mainly from the fermentation of sugars to alcohol, lipid peroxidation and maillard reaction. However, these volatile compounds can be analysed by gas chromatography – mass spectrometry (GC-MS) or by micro sensors. As the system receive the signal from the sensor it commands the sprayer to spray as a result of which we can have a site-specific application of fungicide and disease control. There are two method of management of plant diseases a) indirect decision making by assessing crop growth stage and b) direct detection of disease. The direct detection of plant disease is the conventional method usually followed by most farmers. Indirect decision making is depending on the mechanical sensor which measures the incidence of disease and spray the required quantity of fungicide to the targeted spot. This system is mounted on the automated tractor or a drone feed with GPS of the field. Most research in recent days are focusing on the integration of sensor techniques and image analysis along with the GPS for complete automation of crop protection.
Hyper specteral imaging for detecting of plant disease
According to IPCC (International Panel on Climate Change) has reported that most disease and pest incidence is a result of climate change resulted due to increased temperature, prolonged and uneven rainfall throughout the year. Over the past decades multispectral imaging and hyperspectral imaging cameras in the visible and near infrared regions have found place in agriculture due its reliability and quick assessment of pathogens. Which is why aerial imaging using the drones and satellite are gaining importance. Several climate models have been developed to map the spread of disease in the crop field on basis of niche concept. Most plant disease have reflectance at the 670nm (red absorption) indicating the health status of the plant. The availability of several sensors has made the hyperspectral imaging a viable option for researchers. With the advancement of remote sensing and drones technology made the hyperspectral imaging for identification of diseased plant and take up necessary action according.
Mechanization for management of disease
Machines paly an important role in the success of the precision agriculture. Since the precision disease management is about the site-specific application of required fungicides at the right amount is a must. In order to move to the specific site we will need help of locomotors. Usually tractors or trucks are used for moving the sensor- based sprayer that is usually mounted behind. Usually there are two approaches to site specific farming are a) map based and b) sensor based. Map based is used when the soil is heterogenous fertility status and varying amount of fertilizer need to be applied then the field is divided into imaginary boxes and amount of fertilizer to be applied is feed and the applicator machine does the same (Siciliano et al. , 2009). In case of sensor-based approach, individual plants are sensed and if found unhealthy the fungicide is sprayed and it’s done at a uniform rate unlike the map based approaches. But in both the cases the system will attached with the GPS coordinates to keep the wheels between the plant and sensor on the plant. The tractor is mounted with a sprayer equipped with an optical sensor. As the tractor moves from one direction the sensor is also move in the same direction but, on the plant as it move it will sense the presence or absence of disease. If the disease is present on the plant then it will send the signal to sprayer. On receiving the signal the spray solution flows from the tank to the nozzle further the spraying takes place and hence the control of disease.
Other approaches of controlling pathogens
Other approaches that can be use for controlling of the plant pathogen by seed treatment with the beneficial micronutrients and fungicides after reducing them to nano size. As these nano sized particles increases the surface area the quantity of the active ingredient can be reduced. In the above conditions the pathogens were above the soil surface so we could have monitored very easily but what if the pathogen is present inside the soil surface. There few antifungal agents like the nanoparticles of zinc oxide, silver and titanium oxide against several soil borne pathogens which when treated on seeds can be made to release slowly are effective control of pathogen can be achieved.
Advantages
Precisions agriculture has several advantages in monitoring the nutrient status of soil, irrigation systems specially drip irrigation, harvesting and reduction post-harvest losses. However, it is highly useful for the management of pest and disease 1. Occurrence of climate change can be predicted and forecasted 2. This is rapid, reliable and most importantly time saving 2. Prediction of pest and disease occurrence can be forecasted to take necessary action accordingly 3. Allows efficient utilization of time and input (pesticide and fungicide) 4. Facilitate the better management of pest and diseases in the filed 4. Precision agriculture is economically feasible besides being environmentally friendly as it directly reduces the amount of harmful pesticide released there by protecting the non-target organism.
Obstacles
Any technology or practice or innovation is bound to have few short falls similarly precision agriculture also has few drawbacks like lack of technical expertise in the field, small and marginal land holdings, lack of success stories, higher cost of implements and machines.
Conclusion
Precision agriculture can be better followed by management of pest and disease besides predicting the occurrence in advance using the above mentioned technologies as they are precise, reliable, reproducible and time saving. With the advancement of tools and technologies like hyperspectral imaging, remote sensing, internet of things and nanotechnology can be applied for the better management of disease and increase the yield as discussed in the chapter.
