The growing demand for beef and dairy products requires technological options to improve
#Apsim site software
Software developers and engineers to develop models/algorithms linking remote sensing data with crop/soil mechanistic models to predict crop phenology/yield, Models, sensors, and scientific knowledge to make decision support tools more efficient and world-wide applicable.
My current role at Regrow Ag is focus on developing digital solutions by linking geospatial data (crop, management, environment and genetics), I am currently mentoringĬollaboration with international researchers and has previously supervised (70% as chief investigator) with a cash value of ~AUD8.13M. I have moreġ5 in high-impact journals (12 as first author)]. I collected (field experimental trials) and analysed data including >18 crop species (annual, perennials). Over 15 years of experience managing large soil-crop-climate datasets (5+ years using Python) and 10 years developing the AgriculturalĪPSIM) and applying data pipelining and optimization towards solving large-scale
Soil conditions how crops obtain water/nutrients from the soil how soil processes contribute to the loss of C, N and How the environment and genetics influences crop growth/development how rainfall, irrigation, and fertilizer influence To better predict crop growth, both yield and quality and environmental indicators. I have a passionate interest in disentangling sources of uncertainties/variability Models at different spatio-temporal scales. My interests are in quantifying theĮffects of crop management, genetics and climate variability on soil-crop processes and integrating data into mechanistic Sensing algorithms to improve crop production and reduce environmental impacts. I apply data analytics, statistics and programming to understand the crop ecophysiology behind crop models and remote
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