Subventions et des contributions :

Titre :
Automated screening of canola seeds using GPU-based deep learning: A functional prototype
Numéro de l’entente :
EGP2
Valeur d'entente :
12 500,00 $
Date d'entente :
14 juin 2017 -
Organisation :
Conseil de recherches en sciences naturelles et en génie du Canada
Location :
Alberta, Autre, CA
Numéro de référence :
GC-2017-Q1-00566
Type d'entente :
subvention
Type de rapport :
Subventions et des contributions
Informations supplémentaires :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2018-2019)

Nom légal du bénéficiaire :
Joseph, Dileepan (University of Alberta)
Programme :
Subvention d'engagement partenarial Plus pour les universités
But du programme :

This Engage Plus Grant gives 20/20 Seed Labs, an Albertan company, access to unique knowledge andx000D
expertise available in Dr. Dileepan Joseph's lab at the University of Alberta. The purpose is to address ax000D
company-specific problem, namely the automated screening of canola seeds using optical microscopy.x000D
Canola, bred from rapeseed in the 1970s and continuously improved thereafter, is a Canadian innovation ofx000D
worldwide importance. In Canada alone, the canola industry "generates $19.3 billion annually in economicx000D
activity and nearly a quarter of a million jobs," according to the Canola Council of Canada. Moreover, "canolax000D
oil has the science to prove its benefits on [critical] health issues," and canola meal is an excellent livestockx000D
feed to help meet the world's growing demand for protein.x000D
To meet trade requirements, seed purity is always a concern. The Canadian Food Inspection Agency hasx000D
some of the highest standards in the world regarding seed and 20/20 Seed Labs is the first private lab in Canadax000D
to be accredited by the International Seed Testing Association. Automating visual aspects of purity analysis,x000D
i.e., to identify unwanted seeds that resemble canola, is a prerequisite for automated cleaning, something thatx000D
currently is only partially accomplished by colour sorting.x000D
In a previous Engage Grant, this industry-university partnership successfully demonstrated the feasibility ofx000D
discriminating canola from six unwanted species using multilayer convolutional neural networks, an approachx000D
also known as deep learning. As expected, parallel processing proved important and, after some investigation,x000D
graphics processing units, i.e., GPUs, appeared to be most suitable.x000D
The objective of this Engage Plus Grant is to make the above proof of concept functionally useful forx000D
automated purity analysis. In addition to improving software delivered by the Engage Grant, entitled Purityx000D
Analyzer 1.0, a prototype comprising both software and custom hardware will be designed, implemented, andx000D
tested to perform automated screening of canola seeds in real time.