Remote Sensing, Vol. 14, Pages 5942: Potential of Time-Series Sentinel 2 Data for Monitoring Avocado Crop Phenology (Remote Sensing)

The ability to accurately and systematically monitor avocado crop phenology offers significant benefits for the optimization of farm management activities, improvement of crop productivity, yield estimation, and evaluation crops’ resilience to extreme weather conditions and future climate change. In this study, Sentinel-2-derived enhanced vegetation indices (EVIs) from 2017 to 2021 were used to retrieve canopy reflectance information that coincided with crop phenological stages, such as flowering (F), vegetative growth (V), fruit maturity (M), and harvest (H), in commercial avocado orchards in Bundaberg, Queensland and Renmark, South Australia. Tukey’s honestly significant difference (Tukey-HSD) test after one-way analysis of variance (ANOVA) with EVI metrics (EVImean and EVIslope) showed statistically significant differences between the four phenological stages. From a Pearson correlation analysis, a distinctive seasonal trend of EVIs was observed (R = 0.68 to 0.95 for Bundaberg and R = 0.8 to 0.96 for Renmark) in all 5 years, with the peak EVIs being observed at the M stage and the trough being observed at the F stage. However, a Tukey-HSD test showed significant variability in mean EVI values between seasons for both the Bundaberg and Renmark farms. The variability of the mean EVIs between the two farms was also evident with a p-value < 0.001. This novel study highlights the applicability of remote sensing for the monitoring of avocado phenological stages retrospectively and near-real time. This information not only supports the ‘benchmarking’ of seasonal orchard performance to identify potential impacts of seasonal weather variation and pest and disease incursions, but when seasonal growth profiles are aligned with the corresponding annual production, it can also be used to develop phenology-based yield prediction models.