Home
KeyWords
Skills
Experience
Media
Education
Work History
Prizes
Grants
Research Exchange
Partners
Research Projects
Crop Modelling and Uncertainty
Linking Crop Models with Remote Sensing
Coding
Bestiapop Python package
Data Science
APSIM Applications
Communication
Research Papers
Conference & Poster Presentations
Talks List
Mentoring
PhD Supervision
Honours Supervision
CV
Contact
APSIM
Niche - Optimising Crop Variety Placement in Sub-Saharan Africa
2021-ongoing
Niche - A scalable modelling tool to assess G×E×M interactions at continental scales (oral presentation)
Modelling approaches to select best genotypes by environment
Quantifying the effects of varietal types × management on the spatial variability of sorghum biomass across US environments
Main drivers of sorghum biomass in the USA.
Assessing errors during simulation configuration in crop models – A global case study using APSIM-Potato
We assessed the errors during simulation configuration in APSIM-Potato using GxExM experiments worldwide.
Radiation use efficiency and its use for a better characterization of ecosystem change syndromes in grasslands
2021-ongoing
The role of biological nitrogen fixation on crop productivity, nitrogen use efficiency and nitrous oxide emissions in reconfigured crop rotations. Quantification at different spatio-temporal scales
Daian Francia Laurenzo
Quantifying the effects of G×E×M on the spatial variability of crop biomass in the US
2020-ongoing
Linking remote sensing and crop models to estimate the aboveground biomass of annual and perennial forage crops
Facundo Della Nave
Modelling inter-annual variation in dry matter yield and precipitation use efficiency of perennial pastures and annual forage crops sequences
We compared two forage landcovers, the sequence oats-maize and pure alfalfa across a mean annual precipitation gradient.
Evaluation of the agricultural production systems simulator simulating Lucerne and annual ryegrass dry matter yield in the Argentine Pampas and south-eastern Australia
We evaluated the capacity of APSIM to simulate the growth rates and predict the dry matter yield of Lucerne (_Medicago sativa_ L.) and annual ryegrass (_Lolium multiflorum_ Lam.) in contrasting climatic regions of Argentina and Australia.
Cite
×