|dc.description.abstract||Bitter pit fruit in commercial consignments of apples still poses an economic threat to
exporters from South Africa. Bitter pit develops pre-harvest, but gets progressively worse
during storage and is only traceable once the lesions appear after storage. Accurate, early
indications of bitter pit incidence will allow for remedial pre-harvest measures in the field,
e.g. Ca foliar applications, to reduce the potential losses. Similarly, the automatic detection of
a bitter pit fruit during packing will reduce financial losses by identifying unacceptable fruit
Fluorescence imaging is a fast, non-destructive technique, able to evaluate numerous fruits
individually. Results of pre-harvest imaging on apples to identify fruit susceptible to bitter pit
showed that pitted fruit were correctly classified, but misclassification of non-pitted fruit with
fluorescence imaging was still too high.
NIR-spectroscopy point meter readings could distinguish visible bitter pit lesions from
healthy tissue. Important wavelengths associated with visible bitter pit were identified. This
technique could also identify immature apples, more prone to bitter pit development. It could
however not distinguish between bitter pit and non-pitted fruit when applied randomly on the
calyx end of apples at harvest.
Pre-harvest foliar applications to increase fruit Ca content and reduce bitter pit incidence, is a
standard practice world wide. External Ca uptake by fruit was monitored to determine the
efficacy of applications during different stages of fruit development. Two periods of efficient
uptake of external Ca were identified, viz., cell division and the last few weeks before harvest.
Foliar Ca applications from 40 days after full bloom were more effective in increasing fruit Ca content and reducing bitter pit incidence than at 80 days after full bloom, which was
Mineral analysis of fruit has been used with variable success to predict bitter pit prior to
harvest. The possibility of increasing the accuracy of existing predictive models by using
analysis of individual fruit rather than pooled samples, was investigated. By improving the
normality of different mineral distributions and decreasing the overlap between pitted and
non-pitted fruit classes, it was attempted to improve the reliability of predictions based on
variable threshold values. The Ca distribution showed a variation between pitted and nonpitted
classes, but still a significant overlap between classes reduced the accuracy of the
predictive capacity of this distribution. Even though our results produced a correct
classification of 85% for non-pitted fruit, which can be useful, this was still below the
required tolerance, of less that 2%, expected on the market.
The effect of pruning and fruit bearing position on two-year-old wood on dry mass and Ca
allocation of fruit was determined. ‘Golden Delicious’ fruit set was the lowest at the basal
bearing position compared to the other positions evaluated and was contrary to expectations.
Fruit in a terminal bearing position was superior to the basal position regarding total dry
weight and fruit size. Distal wood possibly inhibited growth and set on the basal position via
auxin distribution. Ca allocation differed between seasons and cultivars and could either be
influenced by bearing position or presence or absence of re-growth.||en