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Space inputs for precision agriculture: scope for proto-type experiments in the diverse Indian agro-ecosystems

Sanjay Srivastava
Scientist, National Natural Resource Management System
Indian Space Research Organization, Bangalore, India
[email protected]

Concept
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, 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.

The success stories pertaining to Precision Agriculture have mainly drawn from the developed countries; wherein Agriculture is characterized by highly mechanized and automated systems, and is driven by market forces and has been professionally managed enterprise. Taking into account the predominance of fragmented land holdings, heterogeneity of crops and livestock and concept of farm families in the rural conditions, the model of Precision Agriculture representing the typical Indian Agricultural scenario is yet to evolve. While the ecological integrity of farming systems is an imperative need, it is equally important to extend the access of information and market to the small and marginalized farmers. The Precision Agriculture model for India while addressing these issues should provides an innovative route for sustainable agriculture in globalize and liberalized economy.

Technology Elements
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. Space technology elements relevant to Precision Agriculture are depicted in Fig. 1.1.

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.

Components and Framework
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) (Fig. 1.2). 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.


Fig.1.1: Developments in space technologies relevant to precision agriculture


Fig.1.2:
Components of Precision Agriculture

Case Studies
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, is depicted in Figure 2.1. At the core of the system is a GIS database, which are knowledge based and form the part of decision-making. The GIS databases include the following layers: field topography, soil types, surface drainage, sub-surface drainage, 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.


Fig 2.1. Precision Farming Overview
The main components, which make up a variable rate application system, are shown in Figure 2.2. 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.


Fig 2.2: Components of VTR systems
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.

Space Applications to Agriculture in India: A Brief Profile
Agriculture has been at the top of our priorities for space applications. The road map of agricultural applications started with the first remote sensing experiment on identification of coconut root-wilt diseases in Kerala using Infrared aerial photography- way back in 1969-70. Since then, space applications to agriculture sector have touched almost all the segments of agricultural ecosystems. These include the mapping and monitoring of major crops, soils/degraded lands, command areas, wastelands, surface & ground water, floods & drought, and watersheds.

Agricultural statistics that provides the vital informatics base to agriculture sector originates from age-old village level Patwari system. It often moves upward with its inherent subjectivity and bias. There are hundreds of crucial decisions at different levels, which are taken purely based on this. In order to strengthen the foundations of agricultural statistics in the country, a remote sensing based the nationwide mission called pre-harvest Crop Acreage and Production Estimation (CAPE) was launched in late 80s. Covering all the major cereals, pulses and oilseeds, CAPE provides in-season crop statistics with 90/90 accuracy at state level. The CAPE could thus provide the scientific basis of agricultural statistics and is transitioning further to yet another institutional destination entitled Forecasting Agricultural Output using Space Agro-meteorology and Land-based Observations (FASAL) within Ministry of Agriculture itself. Synthesizing the state-of-the-art in econometrics, agricultural meteorology and remote sensing based modeling, FASAL envisages the multiple productions forecasting of the major crops with improved accuracy to the extent of 95/95 criteria, timeliness and scope in terms of covering the whole country. The FASAL could be used to provide scientific solutions facilitating crop insurance, bridging the gaps between crop production and post-harvest technology, pricing and policy decisions.

Extensions of irrigation, genetically improved crops and use of inorganic fertilizers have been the harbingers of Green Revolution in the country. Those multi-purpose irrigation commands, which accelerated the irrigation networks in 70s & 80s, are now characterized by depleted irrigation efficiency, water logging and salinity. At the behest of Ministry of Water Resources, remote sensing based command areas inventory has been taken up in the priority irrigation commands to enhance the water use efficiency. In the similar line, a coarse scale land degradation mapping was carried out at behest of Ministry of Agriculture. It is important to mention here that in some of critically affected areas of Gangetic plains of Uttar Pradesh, land degradation to the extent of village level has been mapped out. Based on this, several land reclamation efforts- including the World Bank supported programmes, have been taken up to restore the health of soils. In coming years, with the support from Ministry of Agriculture, ISRO/DOS is planning to launch Nationwide Land Degradation Mapping Mission at the scale 1: 50,000, so as to delineate land degradation at Village level.

By virtue of the unique combinations of IRS satellites with varied resolutions and capabilities, the space segment in the country is in a position to monitor agricultural drought and recurrent floods more efficiently. Capturing the flood events with the damages to the Villages and crops has formed the scientific basis for damage assessment and thereby relief operations at various levels. This year, for example, flood inundation maps in Orissa were generated depicting the marooned areas during the different flood waves and disseminated to the user community within hours through the Internet. Space inputs to agricultural drought monitoring is yet another aspect to target the districts and taluks on the basis of severity of drought.

Department of Space at the behest of Ministry of Rural Development has carried out nation-wide wasteland mapping on 1: 50,000 scale using the IRS data. The Wasteland Atlas of India covering the wasteland statistics of entire country has been brought out. These maps would help in retrieving the information at village/watershed (500 ha) levels, for implementation of wastelands/watershed development programmes. The uniqueness of wasteland mapping has also been the creation of digital database with village as well as watershed boundaries.

With the hydro-geomorphological maps prepared under the National Drinking Water Mission, and subsequently to the Rajiv Gandhi National Drinking Water Mission, satellite remote sensing has really made a dent in reaching its potentials down the line to grassroots. Search for groundwater, particularly in areas with consolidated and semi-consolidated rock formations, considered more difficult from the point of view of exploration as well as recharging of groundwater, is considerably aided by the use of the hydro-geomorphological maps. These maps are extensively used for locating prospective groundwater sites around problem habitations in the country, as a part of the ‘scientific-source finding’.

At the behest of the Planning Commission, scientific inputs were generated from remote sensing on land use/land cover of entire country to evolve agro-climatic zonation based planning. These applications have moved further to large scale mapping across the problem regions of the country (especially the rain-fed regions), towards micro-level decision making for sustainable development. Under remote sensing based Integrated Mission for Sustainable Development Mission (IMSD), land and water resources development plans were carried out for about 80 mha. in 175 districts of the country. Implementation of these plans in certain areas has enriched the ground water potential, increased the cropping intensity along with the net returns from the fields. It is important to note that these experiments were conducted in the terrain of low productivity, mainly dry lands/rain-fed areas, predominantly wastelands, where the scope of doubling food production is the main issue. Emphasis is being laid in operational utilization of this vast database for ground level implementation by concerned user agencies.

The success of these experiments lies not only due to the applications of space inputs alone, but largely due to the synergistic interfaces among grass root level farmers, administrators/policy makers and multi-disciplinary scientific communities. With operationalisation of the National Natural Resources Management System (NNRMS) in the country, with DOS as the nodal agency, the space, ground and user segments have been properly tuned to respond to the challenges of sustainable crop production in the country.

The INSAT-VHRR observations on clouds, cyclone depressions, surface radiance and monsoon parameters in the Indian Ocean have really strengthened the agro-meteorological services in the country. To disseminate the appropriate locale-specific agricultural packages, there are several programmes such as ‘Krishi Darshan’ being beamed through all the regional channels. An operational system of public instruction has been established since 1995, using the INSAT based Training and Development Communication Channel (TDCC) for disseminating the improved agricultural practices, training primary school teachers, Panchayat Raj, elected representatives, Anganwadi workers, wasteland development functionaries etc. The Jhabua Development Communication Project (JDCP), undertaken by ISRO in Jhabua district of MP, has been providing communication support to the developmental activities and also interactive training to the development functionaries, besides empowering the poor and marginalised tribal.

A pilot project sponsored by the Planning Commission, a single window information service provider concept – called Agro-climatic Planning and Information Bank (APIB) has been developed for the farmers of drought prone areas of Karnataka. The APIB is an effort to empower the farmers and reduce their vulnerability to crop failures. Moving to the farmer’s cooperatives, ISRO has taken up jointly with IFFCO – a major initiative on developing remote sensing and GIS based decision support system for fertilizer movements in the priority areas. Finally, space applications over last three decades in agriculture have made this sector information rich and have addressed the various issues encompassing the different sectors of agriculture.

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 (Fig.4.1).


Fig.4.1: Precision Agriculture: Phase transitions
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.