Orchard detection, disease incidence and distribution of Bull’s Eye rot on “Cripp’s Pink” apples in the Western Cape of South Africa


Abstract: Bull’s eye rot (BER) is a latent disease complex that affects pome fruit worldwide, but information of this disease in South Africa is limited. In 2009, a high incidence of BER was reported on stored apples by producers and packhouses in Ceres and Grabouw, the major pome fruit growing regions of South Africa. A preliminary investigation revealed that, of the four species responsible for BER, only Neofabraea alba was present, with the Cripp’s Pink apple cultivar affected most. In this study, timing of fruit infection and postharvest incidence and distribution of BER for Cripp’s Pink from the Western Cape Province was determined, since infection occur in the orchard and disease symptoms only become evident after the cold storage period. Orchard detection, starting one month post full bloom, was done by sampling fruit and leaves from two commercial farms known to have a high incidence of BER, one in Ceres and one in Grabouw, for the 2011/ 2012, 2012/ 2013 and 2013/ 2014 seasons. Fruit was washed, the DNA extracted and then amplified using species specific primers. Neofabraea alba was detected as early as two months post full bloom in Ceres in 2011/ 2012 and one month post full bloom in Grabouw for the 2012/ 2013 season. Disease incidence was determined for Cripp’s Pink apples collected from five different growing regions (Witzenberg Valley, Koue Bokkeveld, Vyeboom, Elgin and Hemel-en-Aarde Valley) at packhouses in the Western Cape and placed in cold storage at -0.5 °C, regular atmosphere, for seasons 2009/2010, 2011/ 2012 and 2012/ 2013. The fruit were not subjected to any postharvest treatments. Evaluation for BER symptoms was done after a four month period. Neofabraea alba was recorded in 66% of grower-lots in 2010/ 2011 and 2012/ 2013 and in 34% in 2011/ 2012 with incidences ranging from 0 to 73% in 2010/ 2011, 0 to 6% in 2011/ 2012 and 0 to 30% in 2012/ 2013. Collection of this data will contribute to a better understanding of the disease and will also allow producers and packhouses to make more informed decisions in terms of disease forecasting, storage duration and sustainable control methods.

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