Page 320 - PC2019 Program & Proceedings

PLANT CANADA 2019

P213. Smart delivery of hexanal from nanomatrix for extending the shelf life of fruits
*
Ranjan, S. ; L. Lim; A. Sullivan; G. Paliyath; J. Subramanian
University of Guelph

Innovations in the post-harvest technology is an important aspect to reduce the fruits and vegetable loss.
In recent years, several novel postharvest technologies have been developed and used to minimize these
losses, and, increase the shelf life of fruits and vegetables. Hexanal is one of those technologies used to
enhance the shelf life of fruits through inhibition of Phospholipase D (PLD) enzyme during ripening.
Postharvest application of hexanal on fruits especially in fruit packaging is limited due to its high volatile
nature. Nanotechnology-based approach was used to develop fiber that can hold hexanal and sustain its
release through external stimuli. The substrate triggers the release of hexanal from the fiber due to the
increase in relative humidity developed during the respiration of fruits in the confined environment. The
developed fibers were characterized using electron microscopy and release of hexanal from the matrix
was studied using Gas Chromatography technique. The developed fibers were tested on plums and
nectarines and shelf life parameters were analyzed. Result showed that the shelf life of plums can be
extended up to 5 days and pears by 7 days. Thus, nanofiber impregnated with hexanal, when exposed on
fruits in packaging, can extend the shelf life of perishables for extended periods of time during export.

Syndhiya Ranjan (sranjan@uoguelph.ca)

TOPIC 25: Teaching in the Plant Sciences (Posters P214-P215)

P214. Environmental issues, concerns and education in rural districts
Elawana Mudiyanselage, N.
Central Environmental Authority in Sri Lanka

Abstract to be submitted

Neranjala Elawana Mudiyanselage (agri.project@yahoo.com)

P215. The power of pi: using raspberry pis to photograph actively growing plants
Meyer, C.; K. Raymond
University of Guelph

Raspberry Pis are inexpensive, modular computers that are powerful enough to be used in various
innovative ways as a part of scientific research and teaching. For instance, Pis can be used to help conduct
high-throughput plant phenotyping. Using this technology in undergraduate coursework can help students
assess plant growth and development in more comprehensive and dynamic ways, and provide students
with a meaningful introduction to computational plant biology. Raspberry Pis with cameras were
configured to perform time-lapse and infrared photography of Arabidopsis plants in growth chambers.
During the semester, students could remotely access the Pis as well as download and process images.
Students had access to thousands of images taken over seven weeks, allowing them to prepare time-lapsed
videos of Arabidopsis growth and to thoroughly characterize development through the life cycle.
Furthermore, they processed infrared photos with the Normalized Difference Vegetation Index (NDVI) to
semi-quantify chlorophyll concentrations in rosette leaves. Students appreciated the value of Raspberry Pi
and computer vision technology for their projects, and were fascinated by its broad applicability for
biological science. Future work will involve imaging seedlings on hormone-amended media and testing
semi-automated phenotyping software with a graphical user interface that leverages machine-learning
principles. Videos and additional details are available at: https://qrgo.page.link/n5fg

Chris Meyer (cmeyer02@uoguelph.ca)

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