HighlightsHigher cereal productivity can be achieved with lower environmental footprint through conservation agriculture.Wheat productivity and profitability can be increased by zero-tillage and early sowing.Kharif maize appears to be a suitable and profitable alternative to rice in northwest India.Productivity and resource efficiency of transplanted rice can be improved by BMPs.Directly sown rice has potential to save water, energy and global warming potential compared to transplanted rice.

Lack of suitable machinery is a major constraint to direct drilling into combine-harvested rice residues due to the heavy straw load, and the presence of loose tough straw deposited by the harvester. Therefore, most rice stubbles are burnt in the mechanised rice–wheat systems of south Asia and Australia, as this is a rapid and cheap option, and allows for quick turn around between crops. As well as loss of organic matter and nutrients, rice stubble burning causes very serious and widespread air pollution in the north-west Indo-Gangetic Plains, where rice–wheat systems predominate. A novel approach with much promise is the Happy Seeder, which combines the stubble mulching and seed drilling functions in the one machine. The stubble is cut and picked up in front of the sowing tynes, which engage bare soil, and deposited behind the seed drill as mulch. Evaluation of the technology over 3 years in replicated experiments and farmers’ fields in Punjab, India, showed that establishment of wheat sown into rice residues with the Happy Seeder was comparable with establishment using conventional methods (straw burnt followed by direct drilling or cultivation before sowing) for sowings around the optimum time into stubbles up to 7.5 t/ha. For late sowings, plant density declined significantly at straw loads above 5 t/ha. The mulch also reduced weed biomass by ~60%, and reduced soil evaporation. Yield of wheat sown around the optimum time into rice residues, using the Happy Seeder, was comparable with or higher than yield after straw removal or burning, in replicated experiments and farmers’ fields, for straw loads up to 9 t/ha. In farmers’ fields there was an average yield increase of 9 and 11% in 2004–05 and 2005–06, respectively, compared with farmer practice. For sowings after the optimum time, yield declined significantly at straw loads greater than 7.5 t/ha. The Happy Seeder offers the means of drilling wheat into rice stubble without burning, eliminating air pollution and loss of nutrients and organic carbon due to burning, at the same time as maintaining or increasing yield.

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Abstract:Remote sensing offers a low-cost method for developing spatially continuous crop production statistics across large areas and through time. Nevertheless, it has been difficult to characterize the production of individual smallholder farms, given that the land-holding size in most areas of South Asia (<2 ha) is smaller than the spatial resolution of most freely available satellite imagery, like Landsat and MODIS. In addition, existing methods to map yield require field-level data to develop and parameterize predictive algorithms that translate satellite vegetation indices to yield, yet these data are costly or difficult to obtain in many smallholder systems. To overcome these challenges, this study explores two issues. First, we employ new high spatial (2 m) and temporal (bi-weekly) resolution micro-satellite SkySat data to map sowing dates and yields of smallholder wheat fields in Bihar, India in the 2014-2015 and 2015-2016 growing seasons. Second, we compare how well we predict sowing date and yield when using ground data, like crop cuts and self-reports, versus using crop models, which require no on-the-ground data, to develop and parameterize prediction models. Overall, sow dates were predicted well (R 2 = 0.41 in 2014-2015 and R 2 = 0.62 in 2015-2016), particularly when using models that were parameterized using self-report sow dates collected close to the time of planting and when using imagery that spanned the entire growing season. We were also able to map yields fairly well (R 2 = 0.27 in 2014-2015 and R 2 = 0.33 in 2015-2016), with crop cut parameterized models resulting in the highest accuracies. While less accurate, we were able to capture the large range in sow dates and yields across farms when using models parameterized with crop model data and these estimates were able to detect known relationships between management factors (e.g., sow date, fertilizer, and irrigation) and yield. While these results are specific to our study site in India, it is likely that the methods employed and the lessons learned are applicable to smallholder systems more generally across the globe. This is of particular interest given that similar high spatio-temporal resolution micro-satellite data will become increasingly available in the coming years.