![apsim video apsim video](https://acsess.onlinelibrary.wiley.com/cms/asset/142d013e-08ec-4fb3-9d8a-47872c7e1525/agj2agronj20130421-fig-0009-m.jpg)
The NPI team includes field agronomists, crop physiologists, geneticists, modellers, and software engineers. The NPI is a collaborative, cross-disciplinary project led by La Trobe University with project partners from CSIRO, Plant & Food Research NZ, South Australian Research and Development Institute, NSW Department of Primary Industries, Department of Primary Industries and Regional Development WA, and Statistics for the Australian Grains Industry (SAGI) West. A mock-up of the APSIM Next Gen model output that would be available at point of cultivar release.
![apsim video apsim video](https://www.apsim.info/wp-content/uploads/2020/07/Rotili.png)
In addition to the improved APSIM Next Gen model, the NPI is also developing an improved cultivar phenology classification scheme and a new scale of cereal development.įigure 1. It will also help to quantify the consequences of non-optimal sowing dates. This tool will allow growers to make informed decisions about cultivar selection and time of sowing in their specific environment. The NPI will deliver a tool for growers and advisers to more accurately predict optimal sowing date that will be available in 2022 (Figure 1). The improved APSIM Next Gen model will be able to be rapidly parameterised with controlled environment phenotypic data, molecular markers and/or other genomic data, removing the need for time of sowing field experiments. 2018) of wheat and barley development so it is possible to accurately predict cultivar classification and optimal sowing dates across Australia at the time at which cultivars are released to the market. The NPI is improving the APSIM Next Gen model (Holzworth et al. 2003) perform poorly outside a narrow range of validated scenarios. In addition, flowering time models like APSIM (Keating et al. These experiments are costly, time consuming and environment specific. Instead, a cultivar’s development speed or classification is determined using time of sowing experiments over multiple sites and years. To ensure crops flower in the optimal period, accurate information on a cultivar’s development speed is needed, but this information is currently not available when new cultivars are released to the market. Flowering time is determined by interactions between genetics, environment and management: the development speed of the cultivar, the environment in which it is grown, and the time of sowing. When crops flower in the optimal period, yields are maximised by minimising losses due to frost, heat, drought and insufficient radiation (Flohr et al. In addition, the NPI is working to develop a new cultivar phenology classification scheme and new scale of cereal development.įlowering time is a critical determinant of grain yield in wheat and barley.Work on the improved model is ongoing and it will be available to growers and advisers in 2022.The improved APSIM Next Gen model, parameterised and validated using NPI data, is more accurate at simulating phenology than APSIM Classic or the baseline APSIM Next Gen model.
![apsim video apsim video](https://pbs.twimg.com/media/EIQjVhCXkAEUYQi.jpg)
Apsim video simulator#
The National Phenology Initiative (NPI) is improving Agricultural Production Systems sIMulator (APSIM) Next Gen so that it can accurately predict cultivar phenology classification and optimal sowing dates across Australia at point of release.Optimising flowering time of wheat and barley cultivars is one of the most cost-effective ways for growers to maximise yield.Business development and commercialisation