Validating the potential of precision technology in Queensland vegetable and strawberry production
The use of precision technology has been adopted to varying extents in Australian agricultural industries (e.g., grains), and internationally in broad acre cropping and European horticulture. While technology with the necessary precision for intensive horticulture is readily available, significant optimisation and validation is required for tropical and sub-tropical horticultural systems. Despite relatively high adoption of auto-steer and satellite guidance, the current adoption rate of other precision technologies (e.g., crop sensing, variable rate applications, yield monitoring) in Queensland (Qld) horticulture is <5% of producers. Qualitative and quantitative data gathered by the authors throughout 2011-2013 indicates that horticulture producers believe that managing spatial variability, precise input and yield management are the next steps in optimising their investment in precision agriculture (PA). Importantly, further adoption was being hampered by insufficient knowledge of the potential and efficacy of PA in intensive horticulture. In collaboration with vegetable (carrot, sweet corn and green bean) and strawberry producers, the authors are validating Greenseeker® biomass sensors along with remote sensing and variable rate or prescription mapping. The aim is to ascertain whether significant spatial variability in crop performance exists, and to determine whether it can be managed to improve marketable yield. Early detection of crop stress or poor performance due to a range of biotic and abiotic factors has the potential to improve marketable yields through improved input management and targeted chemical programs. The following paper outlines the progress in this collaborative approach to develop precision agriculture systems in Queensland horticulture.
Layden, I.A. and O¿Halloran, J. (2016). Validating the potential of precision technology in Queensland vegetable and strawberry production. Acta Hortic. 1130, 613-618
variability, adoption, sensors, biomass, imagery, mapping