Dataset Information

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

ABSTRACT: 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 (RMSEn <35%), whereas ORYZA v3 used measured soil salinity at a given interval of days as a model input. Both models presented similarly good accuracy in simulating aboveground biomass, leaf area index, and grain yield for IR64 over a gradient of salinity conditions. The model index of agreement ranged from 0.86 to 0.99. Variability of yield under stressed and non-stressed conditions was simulated with a RMSE, of 191?kg?ha^-1 and 222?kg?ha^-1 _, respectively, for ORYZA v3 and APSIM-Oryza, corresponding to an RMSE_n of 14.8% and 17.3%. These values are within the bounds of experimental error, therefore indicating acceptable model performance. The model test simulating genotypic variability of rice crop responses resulted in similar levels of acceptable model performance with RMSE_n ranging from 11.3 to 39.9% for observed total above ground biomass for IR64 and panicle biomass for IR29, respectively. With the improved models, more reliable tools are now available for use in risk assessment and evaluation of suitable management options for rice production in salt-affected areas. The approach presented may also be applied in improving other non-rice crop models to integrate a response to soil salinity - particularly in process-based models which capture stage-related stress tolerance variability and resource use efficiency.

SUBMITTER: Radanielson AM

PROVIDER: S-EPMC7729823 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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

Radanielson A M AM Gaydon D S DS Li T T Angeles O O Roth C H CH

European journal of agronomy : the journal of the European Society for Agronomy 20181001

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 (RMSEn ...[more]

PMID: 33343194

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Project description:Introduction Approximately 50% of irrigation water is saved during drip-irrigation of rice, which has tremendous potential for water-saving agriculture, particularly in areas where water resources are scarce. However, the grain yield and quality of drip-irrigated rice are adversely affected. Methods In this study, we investigated the effects of different irrigation strategies on the grain yield and quality of drip-irrigated rice using field experiments. Four irrigation treatments were studied: whole growing season flooding (FI), whole growing season normal drip irrigation (DI, soil relative moisture (RSM) was maintained in the range of 90-100%), pre-anthesis drip irrigation and post-anthesis water stress (SAF, the RSM was maintained in the range of 80-90% after anthesis), pre-anthesis drip irrigation, and post-anthesis flooding (FAF). Results The results showed that grain yield, harvest index, seed setting rate and 1000 grain weight in DI and SAF were significantly lower than in FI and FAF. These parameters were not significantly different between FI and FAF but were significantly greater in DI than in SAF. Compared with FI and FAF, the source capacity, source activity time, and sink activity of DI and SAF decreased, and the sink-source difference increased. The sink-source difference had a significant negative correlation with rice yield and 1000 grain weight. The activities of ADP-glucose pyrophosphorylase, starch branching enzyme, and amylopectin content in grains in the middle panicles of FAF were significantly higher than those of DI and SAF. SAF resulted in increased amylose/amylopectin ratio and total protein content in grains but decreased proportion of glutenin in total protein. Irrigation after anthesis of drip-irrigated rice narrowed the difference between sink sources in rice plants, increased the grain yield and harvest index by 29.2% and 11%, respectively, compared to DI, increased water productivity by 19% compared to FI, and improved the grain quality of drip-irrigated rice. Discussion This study highlights that post-anthesis sufficient irrigation of drip-irrigated rice plays a positive role in maintaining the source-sink balance. This study serves as a foundation for the development of more effective rice farming methods that conserve water, while increasing the grain yield and quality of drip-irrigated rice.

Project description:BACKGROUND: Selection for grain yield under drought is an efficient criterion for improving the drought tolerance of rice. Recently, some drought-tolerant rice varieties have been developed using this selection criterion and successfully released for cultivation in drought-prone target environments. The process can be made more efficient and rapid through marker-assisted breeding, a well-known fast-track approach in crop improvement. QTLs have been identified for grain yield under drought with large effects against drought-susceptible varieties. Most of the identified QTLs show large QTL?×?environment or QTL?×?genetic background interactions. The development of mapping populations in the background of popular high-yielding varieties, screening across environments, including the target environments, and the identification of QTLs with a consistent effect across environments can be a suitable alternative marker-assisted breeding strategy. An IR74371-46-1-1?×?Sabitri backcross inbred line population was screened for reproductive-stage drought stress at the International Rice Research Institute, Philippines, and Regional Agricultural Research Station, Nepalgunj, Nepal, in the dry and wet seasons of 2011, respectively. A bulk segregant analysis approach was used to identify markers associated with high grain yield under drought. RESULTS: A QTL, qDTY12.1, significantly associated with grain yield under reproductive-stage drought stress was identified on chromosome 12 with a consistent effect in two environments: IRRI, Philippines, and RARS, Nepalgunj, Nepal. This QTL explained phenotypic variance of 23.8% and contributed an additive effect of 45.3% for grain yield under drought. The positive QTL allele for qDTY12.1 was contributed by tolerant parent IR74371-46-1-1. CONCLUSIONS: In this study, qDTY12.1 showed a consistent effect across environments for high grain yield under lowland reproductive-stage drought stress in the background of popular high-yielding but drought-susceptible recipient variety Sabitri. qDTY12.1 was also reported previously [Crop Sci 47:507-516, 2007] to increase grain yield under upland reproductive-stage drought stress situations. qDTY12.1 is the only QTL reported so far in rice to have shown a large effect against multiple recipient genetic backgrounds as well as under highly diverse upland and lowland rice ecosystems. qDTY12.1 can be successfully introgressed to improve grain yield under drought of popular high-yielding but drought-susceptible lowland as well as upland adapted varieties following marker-assisted breeding.

Dataset Information

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

Publications

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

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