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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 sanjay@isro.org 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
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