Evaluating satellite remote sensing as a method for measuring yield variability in Avocado and Macadamia tree crops

Abstract

Accurate yield forecasting in high value fruit tree crops provides vital management information to growers as well as supporting improved decision making, including postharvest handling, storage and forward selling. Current research evaluated the 8 spectral band WorldView 3 (WV-3) with a spatial resolution of 1.2 m, as a tool for exploring the relationship between individual tree canopy reflectance and a number of tree growth parameters, including yield. WV-3 imagery was captured on the 7th of April, 2016, over two Macadamia ('Macadamia integrifolia') and three Avocado ('Persea americana') orchards growing near the Queensland township of Bundaberg, Australia. Using the extent of each block, the WV-3 imagery was sub-setted and classified into 8 Normalised Difference Vegetation index (NDVI) classes. From these classes 6 replicate trees were selected to represent high, medium and low NDVI regions (n=18) and subsequently ground truthed for a number of yield parameters during April and May, 2016. The measured parameters were then correlated against 20 structural and pigment based vegetation indices derived from the 8 band spectral information corresponding to each individual tree canopy (12.6 m2). The results identified a positive relationship between derived vegetation indices (VI) and fruit weight (kg/tree) R2 > 0.69 for Macadamia and R2 > 0.68 for Avocado; and fruit number R2 > 0.6 for Macadamia and R2 > 0.61 for Avocado. The algorithm derived between the optimum VI and yield for each block was then applied across the entire block to derive a yield map. The results show that remote sensing of tree canopy condition can be used to measure yield parameters in Macadamia and Avocado grown in the Bundaberg region.