Robson, Andrew; Rahman, Muhammad Moshiur; Muir, Jasmine; Saint, Ashley; Simpson, Chad; Searle, Chris

Author(s)

Robson, Andrew

Rahman, Muhammad Moshiur

Muir, Jasmine

Saint, Ashley

Simpson, Chad

Searle, Chris

Publication Date

2016

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.

Citation

19th Precision Agriculture Symposium Proceedings, p. 36-43

Link

https://hdl.handle.net/1959.11/20119

Publisher

Society of Precision Agriculture Australia (SPAA)

Title

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

Type of document

Conference Publication

Entity Type

Publication

Author(s)	Robson, Andrew Rahman, Muhammad Moshiur Muir, Jasmine Saint, Ashley Simpson, Chad Searle, Chris
Publication Date	2016
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.
Citation	19th Precision Agriculture Symposium Proceedings, p. 36-43
Link	https://hdl.handle.net/1959.11/20119
Publisher	Society of Precision Agriculture Australia (SPAA)
Title	Evaluating satellite remote sensing as a method for measuring yield variability in Avocado and Macadamia tree crops
Type of document	Conference Publication
Entity Type	Publication

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

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