Remote Sensing Based Yield Forecasting in Australian Horticultural Tree Crops
Avocado, mango and macadamia are all important horticultural tree crops to the Australian economy. However the ability to accurately forecast and map yield at multiple scales (tree, farm, state and national) is somewhat lacking. Accurate forecasting of yield supports improved on-farm decision making in terms of labour, storage and transport requirements, as well as for deriving estimates of annual production required for the forward selling of produce. The latter is also of great importance at the national scale. The recently completed ‘Rural R&D for Profit Project – Managing Tree Crops’ led by the University of New England, identified remote sensing as an accurate technology for forecasting and mapping yield when compared to currently adopted methods. The further development of the Australian Tree Crop Rapid Response Map also provided the industry with a more accurate understanding of production area and orchard distribution. Although encouraging further development of these algorithms and methodologies is needed to better compensate for seasonal and locational variability and to produce adoptable outputs for relevant industries. The proposed PhD studies aim to integrate remote sensing, climate modelling and the national map of orchard distribution and area to better understand and therefore predict yield variability in each of the tree crop systems. This information will assist with improved yield mapping and forecasting from the individual tree to regional level; harvest segregation based on market specific quality parameters (size, maturity etc.); improved varietal selection for micro-environments and surveillance tool for pest, disease and biosecurity incursions. The PhD students (one international and two domestic scholarships available) will be allocated an industry each (based on relevant experience). The students will have the unique opportunity to not only work simultaneously on these studies, but will have the support of an extensive collaborative group, including industry partners, established for the ‘Rural R&D for Profit Project – Managing Tree Crops’: Phase 2’ and the ‘Implementing precision agriculture solutions in Australian avocado production systems’ projects.
The successful candidates must be highly motivated and willing to work individually and as part of a team. Previous research and / or working experience in a field relevant to the PhD topic is essential. This includes experience in remote sensing, crop modelling/ computational science, and geographical information systems (GIS). Experience with agricultural/ horticultural science also highly desirable. The applicant must be proficient in spoken and written English and have a current driver’s licence. It is expected that the successful applicant will publish high quality journal papers as components of the PhD thesis. The PhD candidate will be based in Armidale under the principal supervision of The Applied Agricultural Remote Sensing Centre, but will be expected to undertake fieldwork across numerous Australian states, in sometimes remote and challenging conditions.
The Applied Agricultural Remote Sensing Centre are offering a scholarship to the successful PhD applicants. The scholarship value is AU$27,596 p.a. The level of the stipend will not be reduced over the period of the Scholarship. The scholarship is tax exempt and paid in fortnightly installments.