Ramamurthy V.,National Bureau of Soil Survey and Land Use Planning NBSS and LUP |
Ramamurthy V.,Regional Center |
Venugopalan M.V.,National Bureau of Soil Survey and Land Use Planning NBSS and LUP |
Parhad V.N.,National Bureau of Soil Survey and Land Use Planning NBSS and LUP |
Prasad J.,National Bureau of Soil Survey and Land Use Planning NBSS and LUP
Indian Journal of Agricultural Research | Year: 2015
Participatory Rural Appraisal techniques were employed to identify reasons for low yield in wheat. Due to late sowing of wheat after cotton, poor crop establishment was identified as a major deterrent to high yield. Seed priming could be an attractive approach to obtain better crop stand and higher wheat yield. The present study was conducted to explore the possibility of improving the performance of late sown wheat cultivars through seed priming. The effect of on-farm seed priming on wheat emergence and yield was studied in the farmer's fields during rabi 2005-06 to 2006-07. Seed priming improved the emergence and vigour of the wheat crop which helped to establish a good plant stand, and in turn led to significantly higher grain yield (17 %) over non-primed. Cultivars differ significantly in their performance. Raj-3765 recorded 14 % higher grain yield over HD-2189 and 25 % higher to Lok-1. Farmers' opinioned that seed priming helped in hastening germination, maturity and harvest and reduced the adverse effect of dry spell in wheat.
Patil N.G.,National Bureau of Soil Survey and Land Use Planning NBSS and LUP |
Pal D.K.,National Bureau of Soil Survey and Land Use Planning NBSS and LUP |
Mandal C.,National Bureau of Soil Survey and Land Use Planning NBSS and LUP |
Mandal D.K.,National Bureau of Soil Survey and Land Use Planning NBSS and LUP
Journal of Irrigation and Drainage Engineering | Year: 2011
Irrigation management in vertisols is one of the major challenges to increase agricultural productivity in India and many developing countries. Unfortunately, information on hydraulic properties of these soils is very sparse. In an attempt to understand these soils for better management, 10 different functions were evaluated for their efficacy to describe soil-water retention characteristics (SWRC) of vertisols of India, and point pedotransfer functions (PTFs) were developed by using a nearest neighbor (K-NN) algorithm as an alternative to widely used artificial neural networks (ANN) for prediction of available water capacity (AWC). Soil profile information of 26 representative sites comprising 157 soil samples was used for analysis. The Campbell model fit to measured SWRC data better than any other model, with relatively lower root mean square error (RMSE) (0.0199), higher degree of agreement (0.9867), and lower absolute error on an average (0.0134). Three other functions, namely, modified Cass-Hutson, Brooks-Corey, and van Genuchten, also described the SWRC data with acceptable accuracy. Four levels of input information were used for point pedotransfer function (PTF) development: (1) textural data [data on sand, silt, and clay fraction (SSC)]; (2) Level 1 + bulk density data (SSCBD); (3) Level 2 + organic matter (SSCBDOM); and (4) Level 1 + organic matter (SSCOM). The RMSE in predictions by K-NN PTFs ranged from 0.0339 to to 0.0450 m 3 m -3 with an average of 0.0403 m 3 m -3. The ANN PTFs performed with average RMSE 0.0426 m 3 m -3 and a range of 0.0395 to 0.0474 m 3 m -3. The K-NN algorithm provided a viable alternative to neural regression with marginally better performance and the benefit of flexibility in the appending reference database. The results are significant because SWRC data are still in the development stage in India, and K-NN PTFs would have a greater value because of the flexibility. © 2012 American Society of Civil Engineers.