Genetic Mutation of Cowpea as a Constrained Stochastic Optimization Problem in Sustainability
The search for desirable qualities in crop using non-natural breeding techniques like genetic mutation has to ensure a balance between the pillars of sustainability (human, social, economic and environmental)- Candidate optimization crop breeds target food security and sufficiency for humans,...
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Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
INTI International University
2023
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Subjects: | |
Online Access: | http://eprints.intimal.edu.my/1816/1/jods2023_13.pdf http://eprints.intimal.edu.my/1816/ http://ipublishing.intimal.edu.my/jods.html |
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Summary: | The search for desirable qualities in crop using non-natural breeding techniques like genetic
mutation has to ensure a balance between the pillars of sustainability (human, social, economic
and environmental)- Candidate optimization crop breeds target food security and sufficiency for
humans, improved income-earning capacity of farmers, better social (societal) interactions, and
environmental protection. This is to ensure we meet the needs of the present generation while not
compromising on the needs of future generations. However, uncertainties surround the genetic
engineering process, potentially making genetic mutation for sustainability a constrained
stochastic optimization (CSO) problem. Using series of experiments in Python programming, we
applied genetic algorithm to the genetic mutation of cowpea, a tropical leguminous plant and
protein-rich crop. Our experiments with genetic algorithm as a stochastic optimizer, confirmed
that the evolution from the initial random string (initial cowpea species) to the target string
(optimal cowpea solution) was smeared by uncertainties in the optimization-for-sustainability
effort. In any case, cowpeas with the desired qualities of drought tolerance and high yield gradually
emerged as we progressed from the first generation (M1) to subsequent generations with the aim
of meeting the sustainability targets. |
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