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Precision farming in Indian context - Role of Remote Sensing 4. Prospects of Precision Farming in Indian Agricultural Situation Precision farming, though in many cases a proven technology, is still mostly restricted to developed (American and European) countries. The reasons for limited implementation of PF in Asian countries are following:
In India more than 57.8 per cent of operational holdings has size less than 1 ha. With this field size, and the farming being mostly subsistent farming, it is difficult task to adopt the techniques PF at individual field level. However, for adoption of PF, one can consider, instead of individual fields, contiguous fields, with same crop, under similar management practices. Since, management practices, like seed rate, fertilizer rate etc. are mostly based upon the agro-ecological units, they remain similar for a large area. In these cases the PF can be adopted as Information based agricultural system, i.e. at least the farmer has the information about the soil type of his field before adopting the fertilizer practices. Currently, testing of a large number of soil samples may be time-consuming and costly and it may not catch the variability if sampling is not proper. A remote sensing based soil classification will be able to target the samplings towards the variability pattern and thus overcome the above problems. The figure 2 shows the soil spectral variability map of Srirampuram village of Dindigul district, Tamil Nadu. Even at the first level of classification of merged data IRS LISS III (23 m resolution) and Pan (5.8 m resolution) shows that there are at least four types of soil in this village. However the whole village used to apply a similar fertilizer dose for the only crop grown in the Rabi season, i.e. Bengal gram. Presently, this village has been adopted by MS Swaminathan Research Foundation for implementing variable rate application technology.  Figure 2. Soil spectral variability map of Srirampuram village, Dindigul district, Tamil Nadu, generated using merged data of IRS LISS III and Pan. Cost is the other major hurdle in implementing PF techniques. The cost of the full-fledged technology was as high as 21050 UK Pounds as on 1997, out of which 13000 pound is for mapping devices alone. This cost is too high considering the economic status of Indian farmers. In this context, remote sensing data provides a cheaper mapping alternative. IKONOS data (1 m resolution) cost is Rs. 1600 per sq. km. IRS Pan (5.6 m resolution) data is available at a cost of Rs. 15 per sq. km, which is much cheaper than IKONOS. With the launching of Resourcesat -1, one can expect to get 6 m multi-spectral data at less than Rs. 100/sq km. Even after adding up the analysis and the ground truth data cost, the remote sensing based mapping will be far less than the on-field mapping devices and thus can be affordable under Indian condition. The implementation of precision farming in India should have two different strategies - one for the low input subsistent agriculture and the other for input intensive profit making agriculture. In case of the former the increase in productivity is the prime concern. Here, the system has to be converted to information based agriculture, where farmer has spatial information about the soil and crop. This information can be used for efficient input application. Since the field sizes are small in this situation, individually bunded field or a group of fields can be considered as a unit for variable rate application. However, for the later case, such as rice and wheat of Indo-Gangetic belt and the horticultural crops like grape (Mahrashtra), potato (Punjab), tea (Assam), the field sizes are large and the farmers are rich. Already input for farming is high and thereby causing ecological imbalances in many places. Thus the input use efficiency is the prime concern here, apart from enhancing the productivity. Here, remote-sensing data can be used to identify the spatial and temporal variability and necessary actions can be adopted using sophisticated instruments like variable rate applicators. This situation will also benefit from GIS based Decision Support Systems for better management of agriculture. 5. Conclusion Precision farming is essential for serving dual purpose of enhancing productivity and reducing ecological degradation. Though it is widely practiced for commercial crops in developed countries, it is still at a nascent stage in most of the developing countries. Remote sensing can provide a key input (variability map) for the implementation of precision farming at a lower cost. The study on precision agriculture has already been initiated in India, in many research institutes, such as Space Applications Centre (ISRO), MS Swmainathan Research Foundation, Chennai, Indian Agricultural Research Institute, New Delhi, Project Directorate of Cropping Systems Research, Modipuram. In coming few years PF may help the Indian farmers to harvest the fruits of frontier technologies without compromising the quality of land and thereby turning the green revolution into an evergreen revolution. References
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