Valuing a Test for Nitrogen Status in Rice

Abstract

Nitrogen is a crucial input for the efficient production of rice and is generally applied in two split treatments. The first treatment is given before flooding the rice paddocks at sowing time ie at the pre-flooding (PF) stage. The second treatment is applied within a week after the beginning of the panicle initiation (PI) stage. There is no pre-sowing test to estimate nitrogen requirements and farmers use cropping history to make this decision. Later in the season further nitrogen can be applied on the basis of existing Near Infra-red Reflectance (NIR) based nitrogen tissue test but yield potential has often been established by this time. A further source of yield risk is temperature prior to flowering and at high rates of nitrogen there is a potential for yield losses at low temperatures. The aim of one of the projects, funded by the Cooperative Research Centre (CRC) for Sustainable Rice Production, is to develop a nitrogen test for soils of rice paddocks. This would help determine the amount of nitrogen available in the soil and how much more nitrogen needs to be applied at the PF stage. The aim of this study is to first value the information that is provided to the rice growers at PF by the soil test on nitrogen availability and then measure returns to investment on research and extension to develop and promote this test. The problem is first presented in a decision tree framework. The Bayesian framework is then applied, where information provided by the test is used to revise perceived probabilities of yield outcomes under different nitrogen regimes. MaNage rice, a bio-economic model, is used to work out payoffs from different rates of nitrogen at PF on different nitrogen status soils. Finally, returns to investment on R&D are measured within a benefit-cost framework. The results reveal that the information provided by the soil test is valuable as the test helps farmers to use nitrogen more profitably. The outcome of the benefit-cost analysis shows that with the current accuracy levels the benefits from the new test are not sufficient to meet the costs involved on research. If the scientists were able to improve the accuracy of the test (ie at par with existing NIR tissue test), the returns to investment on the project would be quite significant.