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14 January 2020

Analysis of the Temporal and Spatial Distribution Patterns of Abnormal Vertical Growth in Commercial Macadamia Orchards in Australia †

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Centre for Horticultural Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane 4072, Australia
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Author to whom correspondence should be addressed.
Presented at the third International Tropical Agriculture Conference (TROPAG 2019), Brisbane, Australia, 11–13 November 2019.
This article belongs to the Proceedings The Third International Tropical Agriculture Conference (TROPAG 2019)

Abstract

Abnormal vertical growth (AVG) syndrome, which has an unknown aetiology, is a serious threat to the Australian macadamia industry. AVG is characterized by vigorous upright growth and reduced flowering and nut set that results in over 70% yield loss. However, there is a deficiency in knowledge about the distribution of AVG. In this study, we used spatial analysis to provide insights into the distribution and spread of AVG in commercial macadamia orchards in Australia. Using binary data of AVG occurrence from large-scale surveys of six affected commercial orchards in Queensland (five orchards) and New South Wales (one orchard) in 2012 and 2018, spatio-temporal dynamics of AVG was evaluated. Data were subjected to point-pattern and geostatistical analyses using the R package EPIPHY. The Fisher’s index of dispersion of all orchards showed aggregated patterns of affected trees in both years, with statistical significance (p < 0.01) of chi-square test. Goodness-of-fit comparisons of incidence data of all orchards with β-binomial distributions showed that AVG incidence increased by 64% over the six-year period. AVG distribution and the β-binomial parameters exhibited strong heterogeneity, which indicates high degree of aggregation and increasing spread of AVG over time. In addition, binary power law and spatial hierarchy tests confirmed the patterns of aggregation in all orchards. These results implicate a biotic agent as the cause of AVG.

Funding

This work was supported by funds of Hort Innovation Projects MC1608 and MC15011.

Acknowledgments

Australian government RTP scholarship for M.C.M.Z., the assistance of Dr. Chris Searle and Lindsay Bryen for access to information and Dr. Vincent Mellor for his advice on statistical analysis are gratefully acknowledged.
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