Improvement of the model capacity and assessment traits related with water use efficiency for wheat in Australia

Abstract

Traits related with water productivity in dryland cropping interact in multiple ways to influence final grain yield, with traits being of different value across environments. In recent years, crop models have been demonstrated as a useful tool to address the challenge of determining how to best combine traits for region-specific and management-specific adaptation of new genotypes. The APSIM-Wheat model has been developed and widely-used for diverse applications in scientific research and decision support. However, the model requires further effort to accurately simulate important candidate traits associated with improving water productivity. Wheat experiments were conducted in the field and glasshouse to assess traits related with water productivity, e.g. early vigour, tillering, leaf area development, water soluble carbohydrate (WSC) and transpiration efficiency. Contrasting cultivars were selected to study intrinsic mechanisms affecting these traits. Data were collected through field observation, destructive samplings and high-throughput technologies. In glasshouse experiments, multi-view images were taken to reconstruct 3D point clouds, and to then extract accurate 3D phenotype information for early vigour contrasting cultivars. In field experiments, an unmanned aerial vehicle and hand-held camera were used to monitor development of ground cover and the Normalized Difference Vegetation Index (NDVI). These measurements were complemented by manual measurement of wheat phenology, tiller development, biomass partitioning, and leaf area development during the growing season. An improved wheat model is being developed by using the Plant Model framework in the next generation prototype of APSIM. Experiments described above and previously collected datasets are being used to develop new algorithms to model early vigour, tillering, WSC dynamics and transpiration efficiency. The new model will be used to assess wheat traits related to water productivity across the Australian wheatbelt.

Publication
7th International Crop Science Congress
Bangyou Zheng
Bangyou Zheng
Data Scientist / Digital Agronomist

a research scientist of digital agriculture at the CSIRO.

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