Modelling the development of postharvest diseases in fruits and vegetables

 

 

Peter L Sholberg

Pacific Agri-Food Research Centre, Agriculture and Agri-Food Canada, Summerland, BC, Canada

 

 

 

Abstract

Purpose of review: This review focuses on models developed for predicting or forecasting plant diseases that end with or are associated with postharvest storage.

Findings: Modelling opportunities exist for reducing postharvest losses in fruits and vegetables. Pathogen detection, identification and quantification are important components of any conceptual or empirical model. Models that have been developed for plant diseases are best understood as operating on a part of the disease cycle and often use duration of wetness and temperature to guide disease management decisions. New technologies based on DNA hybridisation and the use of biosensors are encouraging for solving some of the problems that have plagued model development. The majority of postharvest models in fruit crops has been used for predicting infection by Botrytis spp. and is used by managers to reduce fungicide applications. Similar models are used with different pathogens to reduce fungicide application in crops such as pears, tropical fruits and vegetables. However, some models have been developed for other purposes such as those used in citrus to indicate residue levels, interaction between chemicals, and degree of sanitation needed in the packinghouse. An alternative potato model uses the production of volatiles in storage by potatoes to predict duration of safe storage.

Directions for future research: There is a need to develop more holistic models for use in postharvest storage. Further development is also needed for specific models that operate in the field prior to harvest similar to those presently used. Instrumentation for the operation of these models and software needs to be kept up to date as disease control methods change. Furthermore these models should be extended to crops and diseases where they are now lacking. The example of the grain ecosystem model is the best example of how holistic postharvest storage models for other commodities should be designed. These models need to be developed with a full multidisciplinary compliment of researchers and thoroughly validated.

 

Keywords: detection; identification; leaf wetness; relative humidity; temperature

 

Stewart Postharvest Review 2008, 4:2

Published online 01 August 2008

doi: 10.2212/spr.2008.4.2