Journal of Geosciences and Geomatics
ISSN (Print): 2373-6690 ISSN (Online): 2373-6704 Website: https://www.sciepub.com/journal/jgg Editor-in-chief: Maria TSAKIRI
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Journal of Geosciences and Geomatics. 2025, 13(1), 23-30
DOI: 10.12691/jgg-13-1-2
Open AccessArticle

Optimization of Genetic Material Collection Missions Using A Gis Approach Based on the Dijkstra Algorithm and its Implementation on A Web Platform

Fall El Hadji Malick Sy1, , Kehel Zakaria2, Hajji Rafika3 and Tine Moustapha Gning4

1SATPORT Senegal, Dakar, Senegal

2International Center for Agricultural Research in the Dry Areas (ICARDA), Rabat, Morocco

3Hassan II Agronomic and Veterinary Institute, Rabat, Morocco

4Laboratory of Mechanics and Modeling L2M, University Iba Der Thiam of Thiès, Thiès, Senegal

Pub. Date: February 23, 2025

Cite this paper:
Fall El Hadji Malick Sy, Kehel Zakaria, Hajji Rafika and Tine Moustapha Gning. Optimization of Genetic Material Collection Missions Using A Gis Approach Based on the Dijkstra Algorithm and its Implementation on A Web Platform. Journal of Geosciences and Geomatics. 2025; 13(1):23-30. doi: 10.12691/jgg-13-1-2

Abstract

Spatial Distribution Modeling and Gap Analysis of species are based essentially on the environmental and socio-economic characteristics of the specimen in question. It is therefore essential to have a mechanism for visiting a large number of sites with a high probability of the presence of genetic material in the shortest possible time. The specific aim of this project is to address the optimization of itineraries for a genetic material collection mission, based primarily on the use of shortest-path search algorithms, in particular Dijkstra's algorithm. The results of this study make it possible to ensure access to the germplasm while rationalizing the resources deployed and, consequently, the financial costs incurred. The whole process of finding the optimal route was made viable by its integration into a platform as a Web application serving as a guide for a genetic material collection mission.

Keywords:
Genetic material collection Optimization Gap Analysis Route Spatial model

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References:

[1]  A. Jarvis, K. Williams, D. Williams, L. Guarino, P. J. Caballero, et G. Mottram, «Use of GIS for Optimizing a Collecting Mission for a Rare Wild Pepper (Capsicum flexuosum Sendtn.) in Paraguay», Genet Resour Crop Evol, vol. 52, no 6, p. 671‑682, sept. 2005.
 
[2]  I. E. Putra et K. Rohendi, «Implementation of Geographic Information System with Dijkstra Algorithm Base On Mobile Application: A Model for Disaster Risk Evacuation Route in Padang City Indonesia», in Proceedings of the 1st International Conference on E-commerce, E-Business and E-Government, in ICEEG ’17. New York, NY, USA: Association for Computing Machinery, juin 2017, p. 30‑34.
 
[3]  M. D. Jennings, «Gap analysis: concepts, methods, and recent results*», Landscape Ecology, vol. 15, no 1, p. 5‑20, janv. 2000.
 
[4]  J. Ramirez-Villegas et al., « A gap analysis modelling framework to prioritize collecting for ex situ conservation of crop landraces », Diversity and Distributions, vol. 26, no 6, p. 730‑742, 2020.
 
[5]  Elith, «A statistical explanation of MaxEnt for ecologists Diversity and Distributions - Wiley Online Library». Consulté le: 8 décembre 2024. [En ligne].
 
[6]  E. W. Dijkstra, «A note on two problems in connexion with graphs», Numer. Math., vol. 1, no 1, p. 269‑271, déc. 1959.
 
[7]  M. M. Hizem, Path search in a dynamically weighted graph: Application to route optimization in road networks, École Centrale de Lille. in PhD thesis. 2011.
 
[8]  A. Iglesias, «Calcul d’itinéraire multicritère en transport multimodal», phdthesis, Université de Lyon, 2017. Consulté le: 10 décembre 2024. [En ligne]. Disponible sur: https:// theses.hal.science/tel-01848737.