Roots model calibration to describe root length density for rainfed rice using soil profile root impacts : [Abstract, Poster].

International audienc

Towards a simple generic model for upland rice root lengthdensity estimation from root intersections on soil profile

International audienceRoot length density (RLD), a key factor for water and nutrient uptake, varies as a function of space and time, and is laborious to measure by root washing. In order to estimate RLD from root intersection density (RID), taking root orientation into account, RID was determined on three perpen-dicular soil planes of cubic samples and RLD was measured for the enclosed volume at different dates and positions in the soil. Results showed that the root system had a very slight preferential orientation whatever the depth, age, and tillage. This mainly isotropic root system led us to parameterise for rice a theoretical geometric model. The ratio between measured and theoretical RLD was stable and introduced as an empirical coefficient. The model was validated in two different countries (Madagascar and Ivory Coast) and accurately predicted RLD

Modeling salinity effect on rice growth and grain yield with ORYZA v3 and APSIM-Oryza

Development and testing of reliable tools for simulating rice production in salt-affected areas are presented in this paper. New functions were implemented in existing crop models ORYZA v3 and the cropping systems modelling framework APSIM. Field experiments covering two years, two different sites, and three varieties were used to validate both improved models. We used the salt balance module in the systems model APSIM to simulate the observed daily soil salinity with acceptable accuracy (RMSE

Varietal improvement options for higher rice productivity in salt affected areas using crop modelling

The rice model ORYZA v3 has been recently improved to account for salt stress effect on rice crop growth and yield. This paper details subsequent studies using the improved model to explore opportunities for improving salinity tolerance in rice. The objective was to identify combinations of plant traits influencing rice responses to salinity and to quantify yield gains by improving these traits. The ORYZA v3 model was calibrated and validated with field experimental data collected between 2012 and 2014 in Satkhira, Bangladesh and Infanta, Quezon, Philippines, then used for simulations scenario considering virtual varieties possessing different combinations of crop model parameter values related to crop salinity response and the soil salinity dynamic observed at Satkhira site. Simulation results showed that (i) short duration varieties could escape end of season increase in salinity, while long duration varieties could benefit from an irrigated desalinization period occurring during the later stages of crop growth in the Satkhira situation; (ii) combining short duration growth with salt tolerance (bTR and bPN) above 12 dS m(-1) and a resilience trait (aSalt) of 0.11 in a variety, allows maintenance of 65-70% of rice yield under increasing salinity levels of up to 16 dS m(-1); and (iii) increasing the value of the tolerance parameter b by 1% results in 0.3-0.4% increase in yield. These results are relevant for defining directions to increase rice productivity in saline environments, based on improvements in phenology and quantifiable salt tolerance traits

Integrating fish into irrigation infrastructure projects in Myanmar: rice-fish what if…?

With rapidly increasing investment in water control infrastructure (WCI) and a recently ratified agriculture development strategy that promotes integrated farming of high-value products such as fish, agricultural production, already fundamental to Myanmar’s economy, will be central to driving the countries’ socioeconomic transformation. Water planners and managers have a unique opportunity to design and manage WCI to incorporate fish and, in so doing, reduce conflicts and optimise the benefits to both people and the ecosystem services upon which they depend. Results from rice–fish culture experimental trials in Myanmar’s Ayeyarwady Delta are providing an evidence base for the importance of integrating fish into WCI, highlighting a range of both environmental and social benefits. By using less than 13% of paddy land area and through best management practices, existing rice productivity is sustained, alongside a 25% increase in economic returns for the same land area from fish. In addition, there are considerably more protein and micronutrients available from the fish produced in the system. Should these farming system innovations be adopted at scale, Myanmar stands to benefit from increased employment, incomes and nutritional value of farm plots (alongside associated reductions in pesticide pollution) and water use benefits

Evaluation of the APSIM model in cropping systems of Asia

Resource shortages, driven by climatic, institutional and social changes in many regions of Asia, combined with growing imperatives to increase food production whilst ensuring environmental sustainability, are driving research into modified agricultural practices. Well-tested cropping systems models that capture interactions between soil water and nutrient dynamics, crop growth, climate and farmer management can assist in the evaluation of such new agricultural practices. One such cropping systems model is the Agricultural Production Systems Simulator (APSIM). We evaluated APSIM's ability to simulate the performance of cropping systems in Asia from several perspectives: crop phenology, production, water use, soil dynamics (water and organic carbon) and crop CO response, as well as its ability to simulate cropping sequences without reset of soil variables. The evaluation was conducted over a diverse range of environments (12 countries, numerous soils), crops and management practices throughout the region. APSIM's performance was statistically assessed against assembled replicated experimental datasets. Once properly parameterised, the model performed well in simulating the diversity of cropping systems to which it was applied with RMSEs generally less than observed experimental standard deviations (indicating robust model performance), and with particular strength in simulation of multi-crop sequences. Input parameter estimation challenges were encountered, and although ‘work-arounds’ were developed and described, in some cases these actually represent model deficiencies which need to be addressed. Desirable future improvements have been identified to better position APSIM as a useful tool for Asian cropping systems research into the future. These include aspects related to harsh environments (high temperatures, diffuse light conditions, salinity, and submergence), conservation agriculture, greenhouse gas emissions, as well as aspects more specific to Southern Asia and low input systems (such as deficiencies in soil micro-nutrients)