Pre-harvest determination of bitter pit potential in apples
Thesis (PhD(Agric) (Horticulture))--University of Stellenbosch, 2005.
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 before shipping. 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 recommended previously. 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.