During the year ended September 30, 2011, India exported an all-time-high 3.57 lakh tonnes (lt) of coffee, marking a 33 per cent jump over 2009-10. That, in the normal course, should have been cause for celebration. Instead, it stirred doubts, with the Coffee Board reckoning production for 2010-11 at only 3.02 lt. How could the country ship out more than what it produced, the discrepancy being starker if one were to factor in domestic consumption of one lakh tonnes or more? But coffee is not the only instance where official crop estimates have been questioned over reliability, or been subject to continuous revisions as to make a mockery of the original projections. Take sugar, where the output during the 2008-09 season (October-September) was first pegged at 220 lt and then successively brought down to 205 lt, 150-155 lt and finally to 145.38 lt. It was just the other way round in 2009-10, where the first estimate was 146 lt, which finally ended up at 189.12 lt. In cotton, too, the 2010-11 crop was initially assessed at 325 lakh bales, then raised to 329 lakh bales and suddenly slashed to 312 lakh bales, before finally being restored to 325 lakh bales.
All these wild swings in production estimates would not really matter if they were of purely academic interest. But as it happens, these data also form the basis for policymaking and decisions on regulating exports. On many occasions, onion prices have gone through the roof because of the Government failing to take timely cognisance of a crop failure. This would, then, typically be followed by a knee-jerk export ban and belated recognition of the succeeding bumper crop, leading to a price crash and short-changing of growers. The mess deepens when multiple agencies are involved in collection and compilation of data. This was so till recently in cotton, where the Agriculture Ministry's production estimates sharply diverged from that of the Cotton Advisory Board.
It all comes back to the country's agricultural statistics machinery that even today relies on village accountants (‘patwaris') to compile data on land use and crop-wise area. That this system – which bases itself on ‘eye assessment', rather than any systematic measurement, by poorly trained and inadequately supervised village officials – will not provide comprehensive, reliable and timely crop-related information should be obvious. Despite the advent of high-resolution satellites and the demonstrated technical feasibility of using remote sensing for estimating land use, crop area and yields, the dependence on human agency remains perplexingly high. The A. Vaidyanathan Committee on Improvement of Agricultural Statistics had recommended greater use of remote sensing technology and tools such as hand-held GPS sensors for village-level data collection. There is no reason why these cannot be done.