Identification of blueberry leaf rust pathogen and quantification of disease infection levels in a blueberry plantation in Hastings, NZ : a thesis presented in partial fulfilment of the requirements for the degree of Master of AgriScience in Horticulture at Massey University, Turitea Campus, Palmerston North, New Zealand
Loading...
Files
Date
2019
DOI
Open Access Location
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Massey University
Rights
The Author
Abstract
Blueberries (Vaccinium spp.) are a favourite fruit and they are produced worldwide. In
New Zealand, blueberries are the main export berry fruit and contribute greatly to
export income. More than 2,800 tonnes of blueberries were produced in the 2017/2018
harvesting season and earned $34.8 million export income in 2018. Currently, 740 ha
of the blueberry plantations can be found in both the South Island and North Island.
Otautau is the main growing region in the South Island while Waihopo, the Waikato
regions of Ngatea and Ohaupo, the Bay of Plenty and Hastings are the regions in the
North Island, producing most of the fresh blueberries in New Zealand.
However, blueberry leaf rust has become a prevalent disease in blueberry production
and a concerning issue for blueberry growers. In Hastings production sites, serious
infections have been found in recent years. Although fungicides were applied to control
blueberry leaf rust, this form of control is incomplete and unsustainable for blueberry
production. The deployment of varieties that are naturally resistant would be a better
option for managing blueberry leaf rust disease. Currently, few cultivars are available
for this purpose, but breeding for rust resistance can address this demand. The main
issues preventing the production of resistant varieties are insufficient knowledge about
this rust pathogen in New Zealand, and the lack of resistant germplasm sources and
efficient resistance screening procedures.
In this study, using the morphological characteristics and genome sequencing results
based on the Internal Transcribed Spacer (ITS) regions, Thekospora minima was
identified as the causal organism of blueberry leaf rust disease in Hastings, Hawke’s
Bay, New Zealand. Additionally, a field assessment was used for understanding the
blueberry rust disease resistance levels in current blueberry cultivars. The disease
incidence and disease severity of 23 blueberry cultivars, including five rabbiteye, three
northern highbush and fifteen southern highbush, were assessed using Fiji software
during the 2019 harvesting season. Based on a Tukey Honest Significant Differences
(TukeyHSD) analysis, these observed blueberry cultivars were divided into four
infection levels of blueberry leaf rust using the percentage of the infected area on the
leaf (PIAL). ‘Scintilla’ was highly susceptible to blueberry leaf rust disease, while ‘Blue
Moon’ and ‘Southern Splendour’ were moderately susceptible. Nineteen blueberry
cultivars, made up of ‘Rahi’, ‘Centra Blue’, ‘Centurion’, ‘Titan’, ‘Sky Blue’, ‘Nui’,
‘Duke’, ‘Camellia’, ‘Misty’, ‘Springhigh’, ‘Snowchaser’, ‘Miss Jackie’, ‘Miss Lily’,
‘Georgia Dawn’, ‘Suziblue’, ‘Kestrel’, ‘Flicker’, ‘Sweetcrisp’ and ‘Palmetto’, showed
susceptibility to this rust disease, and ‘‘O’ Neal’ was the one that showed partial
resistance to the blueberry rust infection. Furthermore, using 1.5×104 concentration
inoculum, an inoculation test was completed in a temperature-controlled room at the
Plant Growth Unit of Massey University. The inoculum was sprayed on the healthy
leaves from detached branches of the ‘Sky Blue’ blueberry cultivar and they were
grown in reverse osmosis water for a 35-day observation on rust symptom development.
Fiji software was applied in the assessment of disease severity in this inoculation test.
A strong correlation (>0.99) was found between the increase in lesion area (ILA) from
the inoculation test and the PIAL from field assessment. A preliminary prediction
equation was established by a simple linear regression model. This equation can be used
to predict the blueberry leaf rust level on different blueberry cultivars and breeding
materials under field conditions by using the results from an inoculation test. This
model would be an efficient approach for assisting the screening on blueberry leaf rust
of blueberries.
Description
Keywords
Blueberries, Diseases and pests, New Zealand, Disease and pest resistance, Data processing