In this article we will discuss about:- 1. Introduction to Precision Agriculture 2. Definition of Precision Agriculture 3. Models 4. Technology Elements 5. Components and Framework 6. Case Studies 7. Technologies 8. Precision Farming for Small Farms in India 9. Need 10. Some Examples of Adoption.
Contents:
- Introduction to Precision Agriculture
- Definition of Precision Agriculture
- Need for Precision Agriculture
- Technology Elements of Precision Agriculture
- Components and Framework of Precision Agriculture
- Case Studies on Precision Agriculture
- Technologies for Precision Agriculture
- Precision Farming for Small Farms in India
- Models for Precision Agriculture
- Some Examples of Adoption of Precision Farming
1. Introduction to Precision Agriculture:
Precision agriculture, newly emerging agricultural management concept, embodies the convergence of biotechnologies & other agricultural technologies with space and informatics. With a goal to achieve the quantum jump in agricultural productivity, reduced cost of cultivation, diversified and resilient agricultural systems, and the precision agriculture plays catalytic role in order to achieve a common ground between environmental and economic goals.
It is basically designed to optimize agricultural inputs viz., fertilizers, pesticides, water etc., in tune with micro-level/field requirements. Optimization is focused on increased yields, reduced cost of cultivation and to minimized environmental impacts through location-specific management. New technologies, including information technology have been in use in the field of agriculture for the management since many decades.
These technologies have assisted in better management, decision making and in obtaining economic efficiency. In this modern era, expanding dimensions of information technologies have opened the doors for crop production management and decision making. This approach is being reflected in the concept of precision farming.
Agricultural production system is an outcome of a complex interaction of seed, soil, water and agro-chemicals; including fertilizers. Therefore, judicious management of all the inputs is essential for the sustainability of such a complex system. We need to maximize the resource input use efficiency in precision farming.
The time has now come to exploit all the modern tools available by bringing information technology & agricultural sciences together for improved economic and environmentally sustainable crop production. Precision agriculture merges the new technologies borne of the information age with a mature agricultural industry.
It is an integrated crop management system that attempts to match the kind and amount of inputs with the actual crop needs for small areas within a farm field. This goal is not new, but new technologies now available, allow the concept of precision agriculture to be realized in a practical production setting.
2. Definition of Precision Agriculture:
Precision farming means tailoring soil and crop management to fit the different conditions found in each field.
Precision farming is a site-specific crop production management system which fulfills the following objectives:
i. Improvement in crop production & product quality
ii. Reduction in expenditure of crop cultivation
iii. Reduction in environmental pollution
iv. Improvement in documentation of farming technologies
Precision farming is sometimes called as “Prescription Farming”, Site-specific Farming and “Variable Rate Technology”. It focuses in the use of Remote Sensing, Geographic Information Systems (GIS) and Global Positioning Systems (GPS).
Precision farming is generally defined as information and technology based farm management system to identify, analyze and manage variability within fields for optimum profitability, sustainability and protection of the land resource. In this mode of farming, new information technologies can be used to make better decisions about many aspects of crop production.
Precision farming involves looking at the increased efficiencies that can be realized by understanding and dealing with the natural variability found within a field. The goal is not to obtain the same yield everywhere, but rather to manage and distribute inputs on a site specific basis to maximize long term cost/benefit.
Applying the same inputs across the entire field may no longer be the best choice. Precision farming is helping many farmers worldwide to maximize the effectiveness of crop inputs. Precision agriculture often has been defined by the technologies that enable it and is often referred to as GPS (Global Positioning System) agriculture or variable-rate farming.
As important as the devices are, it only takes a little reflection to realize that information is the key ingredient for precise farming. Farmers who effectively use information earn higher returns than those who don’t. Precision farming distinguishes itself from traditional agriculture by its level of management wherein instead of managing whole fields as a single unit; management is customized for small areas within fields.
This increased level of management emphasizes the need for sound agronomic practices. Before shifting to precision agriculture management, it is essential to have a good farm management system in place. Precision agriculture is a systems approach to farming.
To be viable, both economic and environmental benefits must be considered, as well as the practical questions of field-level management and technologies needed. The issues related to precision agriculture include perceived benefits and also barriers to widespread adoption of precision agriculture management.
However, the conventional definition of precision farming is suitable when the land holdings are large and enough variability exists between the fields. In India, the average land holdings are very small even with large and progressive farmers. It is necessary to define revised definition of Precision Farming in the context of Indian farming while retaining the basic concept of Precision farming.
The more suitable definition for Precision Farming in the context of Indian farming scenario could be: Precise application of agricultural inputs based on soil, weather and crop requirement to maximize sustainable productivity, quality and profitability. Today because of increasing input costs and decreasing commodity prices, the farmers are looking for new ways to increase efficiency and cut costs. Precision farming technology would be a viable alternate to improve profitability and productivity.
Precision farming has literally taken agriculture in to the space age. This is centralized on the use of remote sensing, geographic information system and global positioning system. Farmers have services available to them that involve; satellite collecting data, transmitting location information or providing data from variety of sources. Farmers can analyze this satellite data/information or they can rely on companies to do this service for them for a fee.
The real value for the farmer is that, he can increase profits by utilizing more precise information about agricultural resources such as; adjustment of seeding rates, planning more accurate crop protection programmes, performing more timely tillage operations, knowing the yield variation within a field etc. The technology has now been developed so that field information (such as yield and application rates) can be controlled and monitored about every 3 feet in the field at a reasonable cost to the farmer.
Pesticides can be applied in areas of pest infestation; reducing the cost of pesticide applied and reducing the amount of pesticide which may potentially impact the environment. Similarly, fertilizers and lime also can be applied where needed.
3. Need for Precision Agriculture:
The potential of precision farming for economical and environmental benefits could be visualized through reduced use of water, fertilizers, herbicides and pesticides besides the farm equipment. Instead of managing an entire field based upon some hypothetical average condition, which may not exist anywhere in the field, a precision farming approach recognizes site-specific differences within fields and adjusts management actions accordingly.
Farmers usually are aware that their fields have variable yields across the landscape. These variations can be traced to management practices, soil properties and/or environmental characteristics. Soil characteristics that affect yields include texture, structure, moisture, organic matter, nutrient status and landscape position. Environmental characteristics include weather, weeds, insects and diseases.
In some fields, within-field variability can be substantial. In one field, the best crop growth was observed near waterways and level areas of the field. Side slopes where erosion depleted topsoil showed moisture stress and reduced plant stands. In another farm, it is being observed that the variation in yield levels of crops is much variable.
Seeing this magnitude of variation prompts most farmers to ask how the problem that is causing the low yields can be fixed. There is no economically feasible method of “fixing” the depleted topsoil areas in this field, so the management challenge is to optimally manage the areas within the field that have different production capacities.
This does not necessarily mean having the same yield level in all areas of the field. A farmer’s mental information database about how to treat different areas in a field required years of observation and implementation through trial-and error.
Today, that level of knowledge of field conditions is difficult to maintain because of the larger farm sizes and changes in areas farmed due to annual shifts in leasing arrangements. Precision agriculture offers the potential to automate and simplify the collection and analysis of information. It allows management decisions to be made and quickly implemented on small areas within larger fields.
4. Technology Elements
of Precision Agriculture:
Recent advances in technology for variable rate technology (VRT), with concurrent advances in remote sensing, GIS & GPS, and the developments taken place in crop simulation modeling, have provided enough opportunities and scope to take-up proto-type Precision Agriculture experiments. The VRT applies production inputs at rates appropriate to soil and crop conditions within micro-level field conditions. The VRT systems have been demonstrated for several materials, including herbicides, fertilizers, insecticides and seeds.
Role of space technologies becomes more crucial in order to address the spatial variability of soils and crops across the various scales of mapping. The space technology inputs also capture the vulnerability and dynamism of agricultural systems. The developments in space- borne imaging sensors, particularly their spatial, spectral and temporal resolutions are well characterized to capture these features.
While high spatial resolution images enable mapping and monitoring the structural attributes of agro-ecosystems, high spectral resolution or hyper- spectral imaging addresses their functionalities. The high temporal resolution captures the dynamisms of agro-ecosystems.
The use of remote sensing, GIS and GPS for crop monitoring, condition assessment and yield modeling has already been well established. Crop simulation models (CSMs) provide potential production under the different scenario of constraints, including weather, soils, crops, cultural practices etc. The conjunctive use of VTR, remote sensing, GIS, GPS and CSMs provides technological framework for Precision Agriculture.
5. Components and Framework
of Precision Agriculture:
Precision agriculture, basically, is characterized by reduced cost of cultivation (through optimization of inputs), improved control and increased resource use efficiency, through appropriate applications of Management Information System (MIS). While the reduced cost of cultivation is achieved through optimization of agricultural inputs taking into account economic push and environmental pull related factors, the control mechanisms are introduced by the help of VRT systems, model outputs and conjunctive use of remote sensing, GIS and GPS.
The MIS comprises Decision Support Systems (DSS), collateral inputs and associated GIS databases on crops, soils & weather. Dynamic remote sensing inputs on in-season crop conditions, crop simulation model outputs on the potential production under the different constraining scenario, and the networks of labs and farms, form the essential ingredients of MIS.
Increased efficiency does not employ only efficient resource use but also reflects in terms of less waste generation, improved gross margin and reduced environmental impact. Precision Agriculture thus calls for the use of appropriate tools and techniques, within a set of the framework as mentioned, to address the micro-level variations between crop requirements and applications of agricultural inputs.
Inevitably, it integrates a significant amount of data from different sources; information and knowledge about the crops, soils, ecology and economy but higher levels of control require a more sophisticated systems approach. It is not simply the ability to apply treatments that are varied at the local level but the ability to precisely monitor and assess the agricultural systems at a local and farm level.
This is essentially to have sufficient understanding of the processes involved to be able to apply the inputs in such a way as to be able to achieve a particular goal not necessarily maximum yield but to maximize financial advantage while operating within environmental constraints.
6. Case Studies on Precision Agriculture:
Most of the case studies, as reported, are mainly from US and European countries representing the agricultural systems, quite different from that of the India’s typical agricultural scenario. Unless few success stories are produced taking into account the different farming practices and cropping systems available in India, Precision Agriculture practices cannot be replicated.
Models of Precision Agriculture drawn from US & UK A framework of the precision agriculture system, being followed in US & UK. At the core of the system is a GIS database, which is knowledge based and forms the part of decision-making.
The GIS databases include the following layers- field topography, soil types, surface drainage, sub-surface drainage, and soil testing results, rainfall, irrigation, actual chemical application rates, and or even more frequently. The GIS enables a study of the relationship between these layers of information to determine cause and effect and to base decisions upon this knowledge.
The main components, which make up a variable rate application system. Not all systems will necessarily contain all of the components shown. As variable rate technology develops, other system components may be included. The central component of variable rate application equipment is the computer/controller.
This device receives information from several sources, which will in turn be used to control the application equipment. The controller may receive information from the application equipment and other sensors to maintain a database on the actual application rate as a function of field position.
Each field operations are governed by VRT systems. Tillage depth varies according to field location; for example, sub-soiling depth is dependent on field location. Seeding rates varies according to field location, which depends on factors such as topography and soil type.
Fertilizer application rates vary in relationship to factors such as soil type and the results from either real time or pre-application testing. Application of insecticides is dependent on insect location from either scouting reports or from aerial imaging. In like manner, the application of all inputs to the crop production process varies with field location.
There are two methodologies for implementing precision, or site-specific, farming.
Each method has unique benefits and can even be used in a complementary, or combined, fashion:
The first method, Map-based, includes the following steps- grid sampling a field, performing laboratory analyses of the soil samples, generating a site-specific map of the properties and finally using this map to control a variable-rate applicator. During the sampling and application steps, a positioning system, usually DGPS (Differential Global Positioning System) is used to identify the current location in the field.
The second method, Sensor-based, utilizes real-time sensors and feedback control to measure the desired properties on-the-go, usually soil properties or crop characteristics, and immediately use this signal to control the variable-rate applicator.
Remote Sensing technologies are used for in-season crop condition assessment including the crop moisture or nutrient stress and other conditions-indicating the need for irrigation and fertilizers or insecticides. All of these data give farmers more opportunities to tailor their management decisions to their farm’s needs. These inputs help the farmers to locate and analyze the stressed part of the field with reduced sampling in map-based technique.
7. Technologies for Precision Agriculture:
In order to collect and utilize information effectively, it is important for anyone considering precision farming to be familiar with the modern technological tools available. The vast array of tools includes hardware, software and the best management practices. There are mainly five components/elements of precision farming technology; Geographic Information System (GPS), Global Positioning System (GPS), Sensors, Variable Rate Technology (VRT) and Yield Monitoring.
Enhancement in production & reduction in input costs may be achieved by the use of information of these components in farming. There is prime role of information technology and decision planning in precision farming. We can obtain different information through GIS, GPS and sensors for crop production. As a result of the implementation or alteration in agricultural operations based on this information, there is increase in production with reduction in the input costs.
Availability of different relevant information is essential to adopt the precision farming. Precise and timely availability of this information is a prime resource to the today’s farmers. Crop characteristics, hybrid response, soil quality, requirements of fertility, quantity of weeds and insects – diseases, effect of crop growth, achievable yield, post-harvest operations and market prediction etc. should be included in the list of availability of information.
A farmer should essentially obtain, analyze and use this information in every stage of crop production under precision farming. Now-a-days, sufficient relevant data is available in internet. One can access these data easily and new data can also be added quickly.
Farmers, scientists and technicians have to assess that how the new technologies could be used in farming? How these could be implemented? For example, to store these data or technologies, their analysis & management computer is used. Storage of all these is easy in computer. Apart from these, one can quickly access to the relevant information of preceding years.
The computer software is easily available for storage, analysis and use of these data. Such type of computer software includes spread sheets, database, GIS and other software to be used. This software can easily be used by operating it.
Global Positioning System (GPS) Receivers:
Global Positioning System satellites broadcast signals that allow GPS receivers to compute their location. This information is provided in real time, meaning that continuous position information is provided while in motion. Having precise location information at any time allows soil and crop measurements to be mapped. GPS receivers, either carried to the field or mounted on implements allow users to return to specific locations to sample or treat those areas.
Uncorrected GPS signals have an accuracy of about 300 feet. To be useful in agriculture, the uncorrected GPS signals must be compared to a land-based or satellite-based signal that provides a position correction called a differential correction. The corrected position accuracy is typically 63-10 feet. When purchasing a GPS receiver, the type of differential correction and its coverage relative to use area should be considered.
Yield Monitoring and Mapping:
In highly mechanized systems, grain yield monitors continuously measure and record the flow of grain in the clean-grain elevator of a combine. When linked with a GPS receiver, yield monitors can provide data necessary for yield maps. Yield measurements are essential for making sound management decisions.
However, soil, landscape and other environmental factors should also be weighed when interpreting a yield map. Used properly, yield information provides important feedback in determining the effects of managed inputs such as fertilizer amendments, seed, pesticides and cultural practices including tillage and irrigation.
Since yield measurements from a single year may be heavily influenced by weather, it is always advisable to examine yield data of several years including data from extreme weather years that helps in pinpointing whether the observed yields are due to management or climate-induced.
Grid Soil Sampling and Variable-Rate Fertilizer (VRT) Application:
Under normal conditions, the recommended soil sampling procedure is to take samples from portions of fields that are no more than 20 acres in area. Soil cores taken from random locations in the sampling area are combined and sent to a laboratory to be tested. Crop advisors make fertilizer application recommendations from the soil test information for the 20-acre area.
Grid soil sampling uses the same principles of soil sampling but increases the intensity of sampling. For example, a 20-acre sampling area would have 10 samples using a 2-acre grid sampling system (samples are spaced 300 feet from each other) compared to one sample in the traditional recommendations.
Soil samples collected in a systematic grid also have location information that allows the data to be mapped. The goal of grid soil sampling is to generate a map of nutrient requirement, called an application map. Grid soil samples are analyzed in the laboratory, and an interpretation of crop nutrient needs is made for each soil sample.
Then the fertilizer application map is plotted using the entire set of soil samples. The application map is leaded into a computer mounted on a variable-rate fertilizer spreader. The computer uses the application map and a GPS receiver to direct a product-delivery controller that changes the amount and/or kind of fertilizer product, according to the application map.
Remote Sensing:
Remote sensing is collection of data from a distance. Data sensors can simply be hand-held devices, mounted on aircraft or satellite-based. Remotely-sensed data provide a tool for evaluating crop health. Plant stress related to moisture, nutrients, compaction, crop diseases and other plant health concerns are often easily detected in overhead images.
Electronic cameras can also record near infrared images that are highly correlated with healthy plant tissue. New image sensors with high spectral resolution are increasing the information collected from satellites. Remote sensing can reveal in-season variability that affects crop yield, and can be timely enough to make management decisions that improve profitability for the current crop.
Remotely-sensed images can help determine the location and extent of crop stress. Analysis of such images used in tandem with scouting can help determine the cause of certain components of crop stress. The images can then be used to develop and implement a spot treatment plan that optimizes the use of agricultural chemicals.
Crop Scouting:
In-season observations of crop conditions may include- Weed patches (weed type and intensity); Insect or fungal infestation (species and intensity); Crop tissue nutrient status; Flooded and eroded areas using a GPS receiver on an all-terrain vehicle or in a backpack, a location can be associated with observations, making it easier to return to the same location for treatment. These observations also can be helpful later when explaining variations in yield maps.
Geographic Information Systems (GIS):
Geographic information systems (GIS) are computer hardware and software that use feature attributes and location data to produce maps. An important function of an agricultural GIS is to store layers of information, such as yields, soil survey maps, remotely sensed data, crop scouting reports and soil nutrient levels.
Geographically referenced data can be displayed in the GIS, adding a visual perspective for interpretation. In addition to data storage and display, the GIS can be used to evaluate present and alternative management by combining and manipulating data layers to produce an analysis of management scenarios.
Information Management:
There are four levels or stages in the quality of information. The lowest level is data, followed by information, knowledge, and finally wisdom. The “data-stage” means a mass of signals and numerical values, which have no practical value in themselves.
The “information-stage” provides some meaning from a set of data, such as levels of excessive, appropriate or deficient fertilizer use. The “knowledge-stage” implies that the information is individualized in some logical way, which can enable someone to make a decision, such as application guidelines. Information technology tends to be powerful in levels up to the knowledge-stage.
The wisdom-stage requires the intellectual and creative activities of fanners and researchers, if there is to be a break-through in accumulated knowledge. Precision farming needs all stages of information in the agricultural production system, and also requires good linkage between the stages. In particular, information technology should be closely linked to farmers.
The adoption of precision agriculture requires the joint development of management skills and pertinent information databases. Effectively using information requires a farmer to have a clear idea of the business objectives and crucial information necessary to make decisions. Effective information management requires more than record-keeping analysis tools or a GIS. It requires an entrepreneurial attitude toward education and experimentation.
Identifying a Precision Agriculture Service Provider:
It is also advisable for farmers to consider the availability of custom services when making decisions about adopting site-specific crop management. Agricultural service providers or property trained extension workers may offer a variety of precision agriculture services to farmers.
By distributing capital costs for specialized equipment over more land and by using the skills of precision agriculture specialists, custom services can decrease the cost and increase the efficiency of precision agriculture activities. The most common custom services that precision agriculture service providers offer are intensive soil sampling, mapping and variable rate applications of fertilizer and lime.
Equipment required for these operations include a vehicle equipped with a GPS receiver and a field computer for soil sampling, a computer with mapping software and a variable rate applicator for fertilizers and lime. Purchasing this equipment and learning the necessary skills is a significant up-front cost that can be prohibitive for many farmers.
Agricultural service providers must identify a group of committed customers (Self Help Groups or Co-operatives) to justify purchasing the equipment and allocating human resources to offer these services. Once a service provider is established, precision agriculture activities in that region tend to center around the service providers. For this reason, adopters of precision farming practices often are found in clusters surrounding the service provider.
Scenario:
Developing system technology for precision farming. First of all, it is necessary to describe and understand the variability within and between fields. Field sensors with GPS and monitors for machine application make this easier. The next stage is to develop machines, which can be operated by remote control. There are three steps in technology development, and three strategies for precision farming.
Step 1 is based on conventional farming technology, with intensive mechanization to reduce the labour input. Step 2 involves the development of mapping techniques, VRT machines, and introductory DSS on the basis of information technology. Step 3 implies the maturity of wisdom-oriented technologies.
Scenario 1 is based on a “high-input and high-output” conventional strategy. Scenario 2 has a strategy for “low-input but constant-output”, and Scenario 3 aims at “optimized input-output” as the goal of precision farming. Advanced technology levels allow us to choose freely between these three scenarios. Effective regulations will encourage progress in precision farming.
8. Precision Farming for Small Farms in India:
Whether precision farming is feasible for small-scale farms is a leading issue for agricultural scientists and politicians. It should be noted that precision farming is characterized by variable management. A key point in precision farming is understanding variability in the field.
There are at least two types of variability. One is within-field variability; the other is between-field or regional variability. Within-field variability focuses on a single field, and the one plant variety being cultivated. Between-field variability considers each field as a unit on a map.
There is a need to consider the kind of variability required when considering precision farming for small farms. Whether farms are large or small, precision farming should mean improved farm management. It should give a higher economic return with a reduced environmental impact. On a single small farm, the farmer can understand fairly well what is going on in each field.
This makes possible variable-rate applications to meet site-specific requirements, using the farmer’s knowledge and skills. When it comes to an area of a few dozen hectares, containing many small fields, precision farming has to coordinate diverse types of land use and many farmers with different motivations.
The terms precision agriculture and site-specific farming often trigger thoughts of expensive equipment such as satellite based global positioning systems, yield monitors, and variable rate applicators. This notion leads people to conclude that precision agriculture is for larger farms only. This is simply not true.
Site-specific farming refers to an approach, not the technologies that make it easier. Fortunately there are some very low-tech, inexpensive methods that may make site-specific management possible and profitable on small farms. The key to maximizing farm profits is to increase the quantity or quality of a given product, all while minimizing inputs and environmental costs.
These adjustments are often made at the enterprise level; however, there are opportunities for even greater profits if they are made site-specifically. A site may be a stick-row of tobacco, an area of a soybean field that drowns out most years, or even a particular cow and her calf. Good decisions cannot be made without good information.
The key to site-specific management decisions is tracking what happens on the site, particularly inputs and outputs. Relatively high-tech solutions (e.g., yield mapping) may be necessary for large farms. For smaller farms, technology as simple as pencil and paper may be adequate for site-specific records.
For example, a producer might have a half-acre field of peppers where they have simply tracked the yields throughout the field. In doing so, they identify particular zones in their field that produce more than other areas. Taking it a step further, the producer may take separate soil samples in those zones.
Often the results will come back that the high producing zones are relatively low in fertility, while the low yielding zones are relatively high in fertility. This may seem opposite. However, the high yielding areas have been removing more nutrients than the low yielding areas, all while receiving the same amount of fertilizer based on a field average. The producer may take this and change the rate of fertilizer that they apply in those particular zones.
This may save fertilizer costs and perhaps increase yields further in those high producing zones. This may seem like an oversimplification, but using site-specific farming methods allows a farmer to be more precise by employing techniques and technologies that are as simple or as complex as they deem workable.
9. Models for Precision Agriculture: Is really needed in India’s Context?
Agriculture in India, as we see today, is at the crossroads.
1. On the one hand there are depletions of ecological foundations of the agro-ecosystems, as reflected in terms of increasing land degradation, depletion of water resources and rising trends of floods, drought and crop pests and diseases. On the other hand, there is imperative socio-economic need to have enhanced productivity per units of land, water and time.
2. At present, 3 ha of rain fed areas produce cereal grain equivalent to that produced in 1 ha. of irrigated. Out of 142 million ha. Net sown areas, 92 million ha. are under rain-fed agriculture in the county.
3. From equity point of view, even the record agricultural production of more than 200 Mt is unable to address food security issue. A close to 60 Mt food grains in the storehouses of Food Corporation of India (FCI) is beyond the affordability and access to the poor and marginalized in many pockets of the country.
4. Globally, there are challenges arising from the Globalization especially the impact of WTO regime on small and marginalized farmers.
5. Some other unforeseen challenges could be anticipated global warming scenario and its possible impact on diverse agro-ecosystems in terms of alterations in traditional crop belts, micro-level perturbations in hydrologic cycle and more uncertain crop- weather interactions etc.
At this stage, agriculture needs new paradigms to deal with the present situation. The strategy lies in integration of the dynamic information and scientific knowledge into the management of agro-ecosystems, and thereby optimizing the radiation, water and nutrient usages.
Agriculture has to transition from high inputs material inputs to the optimum level, through the appropriate use of information, knowledge and strategies for efficient resource usages. In such case, productivity of agricultural may not be the function of the quantum of agricultural input use alone, but will include information, knowledge and efficiency while managing the agricultural practices.
With the fragmentations of land holdings and predominance of small and marginal farmers, our agricultural systems are basically dis-aggregated farm families. Fundamentally, Precision Agriculture aims at a dis-aggregated micro-level farm management strategy with intense information inputs addressing the variations of soils, crops, water, chemicals, market access etc.
Taking into the present state of Agriculture in the country, Precision Agriculture is absolutely essential in order to address poverty alleviation and food security to a very large cross-section of the population. For example, at present, the average Orissa farmer produces slightly more than one ton of rice per hectare, and keeps little below one tone for his family. But if he can produce four tons, then he has three tons to sell and more cash in hand. The smaller the farm, the greater the need for a marketable surplus.
Defining Precision Agriculture in Indian Context Taking into account the typical characteristics of Indian Agriculture, the definition of Precision Agriculture, therefore, must encompass the strategy and framework to achieve higher productivity, reduced cost of cultivation by optimization of inputs, and diversified & resilient agricultural systems. All these goals are to be achieved within the typical constraints of India’s agro-ecosystems.
While the depletion of ecological foundations of farming systems needs to be arrested, the access of information, credit, agricultural inputs and market to the small and marginal farmers are equally crucial. The Precision Agriculture model for must be derive encompassing all these issues, within a broad framework of addressing the negatives of globalization and achieving sustainable agriculture in the long run.
The definition of Precision Agriculture has to be micro-level contextual and should capture the local variabilities, vulnerabilities and dynamisms of agro-ecosystems. For example, Agriculture in Punjab, Haryana & Western UP is characterized by higher productivity (about 4 t/ha), higher use of inputs (irrigation ~ 96%; fertilizer consumption 0.158 t/ha), higher cropping intensities and predominance of medium and large farmers.
Sustainability of such agro-ecosystems has been a cause of concern in the recent times. The model for Precision Agriculture for such ecosystems may focus on sustainability through the optimization of agricultural inputs and thereby reduction of cost of cultivation, and cropping system analysis.
Agriculture in Southern part of the country-especially Andhra and Tamilnadu is moderate yield (around 2 t/ha), inputs (irrigation ~ 55%; fertilizer consumption 0.12 t/ha) and cropping system based, with predominance of small and marginal farmers. Precision Agriculture for such system should aim at enhancing the productivity based on in situ soil & water conservation.
The Eastern India especially Orissa, though high potential agricultural system is unfortunately characterized by low inputs (irrigation ~ 25%, fertilizer use 0.025 t/ha), low yield (~1.2t/ha) and low cropping intensity, with predominance of marginal and small farmers.
A model for Precision Agriculture for Orissa could focus more on poverty alleviation and food security through enhanced productivity and low cost of cultivation. The models for Precision Agriculture in Indian context could therefore be the micro-level and contextual – addressing the empirical issues in the diverse agro-ecosystems of the country.
The access and outreach of best practices in Precision Agriculture – as demonstrated by contextual models, to the large cross-sections of the farming community would then help in cultivating the new paradigms in age-old agriculture enterprise in the country.
Precision Agriculture models are not complete, unless the parameters related to empowerment of the farmers; especially small and marginal farmers are integrated. In this context, ISRO has also initiated Gramsat project in Orissa. In the line of JDCP, the Gramsat project aims at empowering the people especially the poor and marginalized, by awareness building and access to information and services.
Towards this, a network of one-way video and two-way audio Village Information Kiosks is being developed in the selected blocks of Orissa. The same networks are also planned to facilitate e-governance in the region. Precision Agriculture model should present a synergy that could lead to a holistic mission, focused on agricultural development with the backdrop of present issues and challenges.
10. Some Examples of Adoption of Precision Farming:
i. Weed Control:
In the process of crop production under precision farming, weed control can be done in effective manner. Under traditional system of weed control, herbicides are being sprayed uniformly in the entire field. However, there is no need to spray the herbicides where weeds are not present.
Application of herbicides through variable rate technology i.e. according to the presence of weeds in the field; not only requires less herbicide quantity but, unnecessary release of herbicides to the environment could also be stopped. An automatic technology has been developed to identify the weeds in field.
On the other hand, CCD cameras are used in image analysis system. Computer software is also used in the system to identify the composition of various species of weeds. It identifies the weeds out of the crop plants in the field. The identification of weeds is being done on the basis of their characteristics like; colour, shape, texture etc.
On the other hand, optoelectronic sensors measure the reflection of length of light waves under a certain limit. Site-specific based weed control technology for beet root, maize, wheat and barley has been developed in Germany. In this system, online identification facility is available through digital image analysis.
Computer-based decision making and GPS- controlled herbicide spray facilities in patches are also available in this system. There have been economic gains by the use of this system in all the crops. Herbicides are being sprayed in this system according to the number of weeds at different places.
Different special methods have been developed in other fields of crop production under precision farming. In some of the methods, electromagnetic waves are used for identifying the soil characteristics, remote sensing and simulation-based site-specific nitrogen use; mechanical sensors (pendulum)-based crop weight determination and site-specific seed rates of cereals for sowing are included as the part of the technologies.
ii. Use of Nitrogen:
The use of nitrogen under precision farming is done by measuring chlorophyll florescence. In this method, machines do not come in to the direct contact of crop plants but, the identification of laser-induced chlorophyll florescent is used.
It is considered that, the image of chlorophyll florescent of plants can be used for quick calculation of nitrogen present in crop plants. This is an indicator of nitrogen concentration present in the plants. This method can be used in wheat & maize. Several studies revealed that nitrogen absorption by plants can be determined reliably by measuring the chlorophyll florescence.
Conclusion:
Precision farming implies a management strategy to increase productivity and economic returns with a reduced impact on the environment, by taking into account the variability within and between fields.
Variability description, variable-rate technology and decision support systems are the key technologies for precision farming. Precision farming on a regional level is one way to apply this approach to small-farm agriculture, but may also promote the development of rural areas.
Precision Farming provides farmers with a tool to apply fertilizer according to the need of a particular sub-field. The savings made with this variable can be fairly large.
This technology is certainty exciting and is bound to change the face of agriculture in the near future.
Precision agriculture gives farmers the ability to use crop inputs more effectively including fertilizers, pesticides, tillage and irrigation water. More effective use of inputs means greater crop yield and/or quality, without polluting the environment. However, it has proven difficult to determine the cost benefits of precision agriculture management.
At present, many of the technologies used are in their infancy, and pricing of equipment and services is hard to pin down. This can make our current economic statements about a particular technology dated. Precision agriculture can address both economic and environmental issues that surround production agriculture today.
Questions remain about cost-effectiveness and the most effective ways to use the technological tools we now have, but the concept of “doing the right thing in the light place at the right time” has a strong intuitive appeal. Ultimately, the success of precision agriculture depends largely on how well and how quickly the knowledge needed to guide the new technologies can be found.
The approach required to be adopted by the policy makers to promote Precision farming at farm level:
a. Promote the precision farming technology for the specific progressive farmers who have sufficient risk bearing capacity as this technology may require capital investment.
b. Identification of niche areas for the promotion of crop specific organic farming.
c. Encourage the farmers to adopt water accounting protocols at farm level.
d. Promote use of micro level irrigation systems and water saving techniques.
e. Encourage study of spatial and temporal variability of the input parameters using primary data at field level.
f. Evolve a policy for efficient transfer of technology to the farmers.
g. Provide complete technical backup support to the farmers to develop pilots or models, which can be replicated on a large scale.
h. Policy support on procurement prices, in formulation of cooperative groups or self-help groups.
i. Designation of export promotion zones with necessary infrastructure such as cold storage, processing and grading facilities.