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EXPLORE | EXPERIMENT | EXECUTE
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PROBLEM
PLANT BREEDERS
INCREASING DEMAND OF FOOD
PLANT STRESS LOSSES
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Current Trends on Genetic Engineering
Developing Climatically-resilient Cultivars
Incorporating Resistance Genes
Early Stress Prediction
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PROBLEM
RESEARCHERS
NON STANDARDIZED DATA PROCESSING
UNDERUTILIZED GENOTYPING TOOLS
MISSING ATTRIBUTES
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Latest Phenotype Prediction Technology
VERY HIGH MEMORY REQUIREMENT!
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Deep phenotyping
An open source deep learning tool for phenotype/genotype classification
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DEEP
LEARNING 3 Phases of the Pipeline
* for High-Throughput Phenotyping
CLASSIFICATION
into different groups
PREDICTION
of different plant
characteristics
IDENTIFICATION
of genetic make up of
various plants
Multilayer Perceptron (MLP)
and
Artificial Neural Network (ANN)
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MLP RESULTS
FAST & ACCURATE
ACCURACY 87%
PROCESSING TIME 00:03:13
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FAST & ACCURATE
ACCURACY 78%
PROCESSING TIME 00:02:18
ANN RESULTS
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Future Work
Key features to be implemented:
● Crowdsourced Phenotype Dataset
● Crop Geotagging with KYC Verification
● Automated Standardization
● Hello World Phenotyping
● Cross validation, Ensemble Models &
Feature Engineering
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THE TEAM
Alec Xavier Manabat
Design Engineer
Analog Devices, Inc.
Shanelle Grace Recheta
Data Science Consultant
FTW Foundation | Cropital
TOWARDS INCLUSIVITY IN RICE SCIENCE!