Estimating impact of puddling, tillage and residue management on wheat ( Triticum aestivum, L.) seedling emergence and growth in a rice–wheat system using nonlinear regression models

Puddling is known to increase the yield of rice due to the creation of suitable physical environment that favours growth of the crop. However, in rice–wheat system, wheat yield has been reported to decrease due to the deterioration of soil structure caused by puddling in rice. This affects seedling emergence in wheat. Seedling emergence model that predicts seedling emergence and early growth of wheat can be used to estimate the major effects of different tillage and residue management practices on seedling shoot and root growth. Output from such a model can be used to initialize crop growth models under diverse soil and climatic conditions in which the variations in crop establishment are often poorly taken into account The information on predicting wheat ( Triticum aestivum, L.) seedling emergence and growth using nonlinear regression models under rice–wheat cropping system is essential as early emergence and growth of seedlings affect the grain yield. A study was undertaken to assess the residual effect of puddling in rice (no puddling i.e. direct seeding, puddling by four passes of 5 hp power tiller and puddling by eight passes of 5 hp power tiller) and direct effect of different tillage (conventional and zero tillage) and residue (residue-retained and removed) management practices on wheat seedling emergence and growth in rice–wheat system on a Vertisol of Central India. Wheat seedling emergence was maximum where rice was direct seeded, and wheat was grown under conventional tillage with residue retained at the surface. Prediction of wheat seedling emergence by the [France, J., Thornley, J.H.M., 1984. Mathematical Models in Agriculture and Related Sciences. Butterworth, London] model, shoot growth by the Logistic and Gompertz models, and root growth by Monomolecular model was attempted. Time to reach 50% emergence as predicted by the [France, J., Thornley, J.H.M., 1984. Mathematical Models in Agriculture and Related Sciences. Butterworth, London] model was closer to the observed emergence data. The nonlinear regression models study indicated that the Logistic model predicted the shoot growth of wheat under different tillage and residue management practices better than the Gompertz model. Whereas, for root growth the Monomolecular model fitted well with the experimental data.