Bioindicators for shelf-life prediction of green asparagus
Developed by Research Group Biogeosciences
- Researchs: Eric Cosio
- Duration: 2013 - 2015
- Financing: FIDECOM, Complejo Agroindustrial Beta
- Related institutions: INTE - PUCP, Complejo Agroindustrial Beta
Fresh cut asparagus is a very perishable product. From the moment you cut the asparagus stem base in the field, numerous physiological and biochemical processes are starting up until the progressive deterioration of the quality of the product. It is estimated that the life potential of fresh asparagus under optimum temperature and humidity conditions is two weeks from the harvest time. The processes carried out between harvesting and market delivery (transport, handling, fumigation and storage) introduce a new variability and affect (or reduce) its lifetime. The lack of quick and precise indicators of the physiological state of the product hinders the shelf-life prediction of green asparagus. It also impedes the identification of post-harvest processing stages that contribute to the reduction of the lifetime, but may be improved. The project works on the development of a method to assess shelf-life prediction of fresh asparagus based on the presence of early volatile bioindicators of the senescence process. The project takes advantage of the group’s strength in bioanalytical techniques for the analysis of volatile compounds in a biochemical context.
Identification of volatile organic compounds, quantitative bioindicators of asparagus senescence process, so that an electronic nose, or equivalent equipment, can be used to detect, quantify and predict the remaining shelf-life of the product. The research involves analytical technology and multivariate analysis to identify and model the senescence process of cut asparagus. The project is developed jointly with the Complejo Agroindustrial Beta S.A.(agro-industrial complex Beta S. A.). It has several aspects related to intellectual property due to the direct application of innovative analytical technologies in agro-industrial processes.