Yield gap analysis in major wheat growing areas of Khorasan province, Iran, through crop modelling
Tài liệu tham khảo
Anonymous, 2010. Agriculture Statistics: Crops and Horticulture Plants. Vol. 1. Iran Ministry of Jihad-e-Agriculture. Available online at: http://www.maj.ir/
Chalmers, 2003, 12
Donatelli, M., Acutis, M., Laruccia, N., 1996. Pedotransfer functions: evaluation of methods to estimate soil water content at field capacity and wilting point. Available on: www.isci.it/mdon/research/bottom_modeling_cs.htm
FAOSTAT, 2013. Crop production Statistics. Food and Agriculture Organization, Rome. Available online at: www.faostat.fao.org
Fischer, R.A., Byerlee D., Edmeades G.O., 2014. Crop yields and global food security: will yield increase continue to feed the world? ACIAR Monograph No. 158. The Australian Centre for International Agricultural Research: Canberra. Available online at http://aciar.gov.au/publication/mn158 0;
Goudriaan, 1993
Lobell, 2002, Soil, climate, and management impacts on regional wheat productivity in Mexico from remote sensing, Agric. For. Meteo., 114, 31, 10.1016/S0168-1923(02)00138-7
Mokhtassi- Bidgoli, 2013, Quantifying the population dynamics of flixweed (Descurainia sophia) in bread wheat under different water and nitrogen regimes, 184 pp
Sadras, 2003, Measuring and modeling yield and water budget components of wheat crops in coarse-textured soils with chemical constrains, Field Crops Res., 84, 241, 10.1016/S0378-4290(03)00093-5
Shahsawari, 2005, The effect of different levels of nitrogen on yield and yield components of wheat varieties in Kerman, J. Res. Dev., 66, 82
Soltani, 2015, Simulation of nitrogen losses in sugar beet production in various production systems in Khorasan, J. Soil Manag. Sustain. Prod., 4, 149
Tatari, 2008, Dryland wheat yield prediction using climatic and edaphic data by applying neural networks