Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8879290 | Field Crops Research | 2018 | 11 Pages |
Abstract
Rice is the staple food for almost half of the world population. In South and South East Asia, about 40% of rice production is from deltaic regions that are vulnerable to salt stress. A quantitative approach was developed for characterizing genotypic variability in biomass production, leaf transpiration rate and leaf net photosynthesis responses to salinity during the vegetative stage, with the aim of developing efficient screening protocols to accelerate breeding varieties adapted to salt-affected areas. Three varieties were evaluated in pots under greenhouse conditions and in the field, with average soil salinity ranging from 2 to 12Â dSÂ mâ1. Plant biomass, net photosynthesis rate, leaf transpiration rate and leaf conductance were measured at regular intervals. Crop responses were fitted using a logistic function with three parameters: 1) maximum rate under control conditions (Ymax), 2) salinity level for 50% of reduction (b), and 3) rate of reduction (a). Variation in the three parameters correlated significantly with variation in plant biomass production under increasing salinity. Salt stress levels that caused 50% reduction in net leaf photosynthesis and transpiration rates were higher in the tolerant genotype BRRI Dhan47 (16.5Â dSÂ mâ1 and 14.3Â dSÂ mâ1, respectively) than the sensitive genotype IR29 (11.1Â dSÂ mâ1 and 6.8Â dSÂ mâ1). In BRRI Dhan47, the threshold beyond which growth was significantly reduced was above 5Â dSÂ mâ1 and the rate of growth reduction beyond this threshold was as low as 4% per unit increase in salinity. This quantitative approach to screening for salinity tolerance in rice offers a means to better understand rice growth under salt stress and, using simulation modelling, can provide an improved tool for varietal characterization.
Related Topics
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Agricultural and Biological Sciences
Agronomy and Crop Science
Authors
Ando M. Radanielson, Olivyn Angeles, Tao Li, Abdelbagi M. Ismail, Donald S. Gaydon,