Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/1598
Title: Fluorescence imaging as a non-destructive method for pre-harvest detection of bitter pit in apple fruit (Malus domestica Borkh.)
Authors: Lötze, E.
HUYBRECHTS, Christy 
Sadie, A.
Theron, K.
VALCKE, Roland 
Issue Date: 2006
Publisher: Elsevier
Source: POSTHARVEST BIOLOGY AND TECHNOLOGY, 40(3). p. 287-294
Abstract: Bitter pit in apples still causes significant losses, especially in the export markets of 'Golden Delicious' apples from South Africa. Orchard practices to reduce the possibility of bitter pit are followed, as well as destructive methods to predict the probability thereof, but the occurrence of bitter pit is still unacceptably high. Fluorescence imaging is a fast, non-destructive technique, able to evaluate numerous fruit within a short time span. By applying fluorescence imaging on individual fruit before any symptoms of bitter pit were apparent, lower fluorescence was shown to be associated with bitter pit development in apples in selective cases. Our results showed that, using averaged cumulative distribution functions (CDFs) of pitted and non-pitted fruit classes, it was possible to show a difference between these classes with fluorescence imaging. However, the individual distinction between all pitted and non-pitted fruit of our total sample, could not been defined as clearly. In the majority of cases, on a single fruit basis, separation in groups was not satisfactory (less than 100% accurate) based on industry requirements for a prediction technique. Results of pre-harvest imaging on apples to identify fruit with bitter pit potential at harvest showed that pitted fruit were correctly classified (75-100%). However, misclassification of non-pitted fruit (50% and less) with fluorescence imaging is still too high to be of any commercial use.
Keywords: Apples ; Bitter pit ; Classification ; Fluorescence imaging
Document URI: http://hdl.handle.net/1942/1598
ISSN: 0925-5214
e-ISSN: 1873-2356
DOI: 10.1016/j.postharvbio.2006.02.004
ISI #: 000238235100012
Category: A1
Type: Journal Contribution
Validations: ecoom 2007
Appears in Collections:Research publications

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