Development of diagnostic tools to predict incidence of bitter pit during apple storage

• Main Author: Mirzaee, Mehrdad
• Other Authors: Colgan, Richard ; Rees, Deborah
• Published: University of Greenwich 2015
• Subjects: QD Chemistry
• Online Access: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.732841

Bitter pit is an important physiological disorder of many apple cultivars where the low uptake and poor distribution of calcium within the cortex of apples pervades. Controlled atmosphere storage and application of 1-MCP (SmartFreshSM) can delay the onset of bitter pit symptoms by delaying maturity and senescence; however, significant losses may occur in long-term stored apples. It is hard to detect internal bitter pit using external examination alone. Previous studies have focused on improving pre-harvest prediction and curative treatments before harvest. Present prediction models are based on history of orchards, mineral analysis 2-3 weeks before harvest and quality assessments and monitoring over storage time. This study aimed to identify a greater understanding of the storage potential of fruit based on destructive standard quality assessments, biochemical and molecular analysis, also a non-destructive monitoring method by chlorophyll fluorescence at the point of harvest and monitoring during storage for developing more reliable prediction models to improve storage management. The role of free and conjugated calcium in maintaining cellular integrity and the relationship between biochemical and fluorescence changes and development of bitter pit were investigated. A diagnostic model based on comparison of changes of ascorbic acid during storage was developed. Another diagnostic model based on changes in the proportion of calcium oxalate content during storage in comparison with harvest was developed to identify samples with higher propensity to bitter pit. Also chlorophyll fluorescence was investigated as a non-destructive method for monitoring fruit during storage and prediction models for detecting changes in the maturity of fruit and developing bitter pit and reduction of fluorescence during storage as an alert to identify incidence of bitter pit were developed. Furthermore, changes in gene expression profiles of a limited number of genes like calmodulin showed the differences in patterns of transcripts between apples suffering from bitter pit and healthy apples. All the suggested methods have potential of being commercialised and applied practically to improve apple fruit store management. It would be possible to build a multi variate model for predicting the onset of bitter pit development in apple by combination of two or more suggested diagnostic tools.