No abstract

Mapping of peanut crops is essential in supporting peanut production, yield prediction, and commodity forecasting. While ground-based surveys can be used over small areas, the development of remote-sensing technologies could provide rapid and inexpensive crop area estimates with high accuracy over large regions. Some of these recent earth observation satellite systems, such as the Project for On-Board Autonomy Vegetation (PROBA-V), have the advantage of increased spatial and temporal resolution. With a study area located in the South Burnett region, Queensland, Australia, the primary aim of this study was to assess the ability of timeseries PROBA-V 100-m normalized difference vegetation index (NDVI) for peanut crop mapping. Two datasets, i.e., PROBA-V NDVI time-series imagery and the corresponding phenological parameters generated from TIMESAT data analysis technique, were classified using maximum likelihood classification, spectral angle mapper, and minimum distance classification algorithms. The results show that among all methods used, the application of MLC in PROBA-V NDVI time series produced very good overall accuracy, i.e., 92.75%, with producer and user accuracy of each class ≥78.79%. For all algorithms tested, the mapping of peanut cropping areas produced satisfactory classification results, i.e., 75.95% to 100%. Our study confirmed that the use of finer resolution 100 m of PROBA-V imagery (i.e., relative to MODIS 250-m data) has contributed to the success of mapping peanut and other crops in the study area.

Because of its negative effect on health, aflatoxin has become one of the most important mycotoxins in the world. As climate stress is one of the main triggers of aflatoxin incidence, climate change could affect its geographic distribution. The primary aim of this study was to examine the effect of climate change on the future distribution of aflatoxin in peanut (Arachis hypogaea L) crops in Australia. The projected distributions in 2030, 2050, 2070, and 2100 were modelled by employing CLIMEX (CLIMatic indEX) model using two Global Climate Models (GCMs), i.e. CSIRO-Mk3.0 and MIROC-H based on SRES A2 and SRES A1B climate scenarios. This study has successfully developed CLIMEX model parameters for aflatoxin, and confirmed the climatic zones preference of aflatoxin incidence, as concluded by other studies. Therefore, the model parameters are applicable in all parts of the world. The projection results in Australia confirm that climate change affects the future distribution of aflatoxin, including the distribution in the current peanut growing areas. Shifts in aflatoxin invasion areas from the tropical and subtropical climate zones of the eastern part of Australia to the temperate climate zones of the south-eastern and south-western parts of the country were projected by 2100. Thus, adaptation and mitigation measures are needed to overcome the negative impacts in the future. Options for these measures include relocation of planting areas, development of host-plant resistance, proper agricultural practices, and mitigation actions by using physical, chemical, and biological approaches.