Using Genetic Algorithms to Outline Crop Rotations and a Cropping-System Model

The idea of cropping-system is a method used by
farmers. It is an environmentally-friendly method, protecting the
natural resources (soil, water, air, nutritive substances) and increase
the production at the same time, taking into account some crop
particularities. The combination of this powerful method with the
concepts of genetic algorithms results into a possibility of generating
sequences of crops in order to form a rotation. The usage of this type
of algorithms has been efficient in solving problems related to
optimization and their polynomial complexity allows them to be used
at solving more difficult and various problems. In our case, the
optimization consists in finding the most profitable rotation of
cultures. One of the expected results is to optimize the usage of the
resources, in order to minimize the costs and maximize the profit. In
order to achieve these goals, a genetic algorithm was designed. This
algorithm ensures the finding of several optimized solutions of
cropping-systems possibilities which have the highest profit and,
thus, which minimize the costs. The algorithm uses genetic-based
methods (mutation, crossover) and structures (genes, chromosomes).
A cropping-system possibility will be considered a chromosome and
a crop within the rotation is a gene within a chromosome. Results
about the efficiency of this method will be presented in a special
section. The implementation of this method would bring benefits into
the activity of the farmers by giving them hints and helping them to
use the resources efficiently.

Authors:

• Nicolae Bold
• Daniel Nijloveanu

Keywords:

• Genetic algorithm
• chromosomes
• genes
• cropping
• agriculture.

References:

[1] Francis, C. A., Multiple cropping systems, Macmillan Publishing
Company, New York, USA, 1986.
[2] D. A. Popescu, N. Bold, A. C. Bold, An algorithm based on the
backtracking method for cropping-systems and the rotation of cultures,
The 9th International Conference INTER-ENG 2015 - Interdisciplinarity
in Engineering, 8 - 9 October, "Petru Maior" University of Tîrgu-Mureş,
Romania, 2015
[3] D. Nijloveanu, N. Bold, A Random Algorithm for Generating Cropping
– System Possibilities, The 10th International Conference on Virtual
Learning, Timişoara, Romania, October 2015
[4] S. S. Snapp, S. M. Swinton, R. Labarta, D. Mutch, J. R. Black, R. Leep,
J. Nyiraneza and K. O'Neil Evaluating Cover Crops for Benefits, Costs
and Performance within Cropping System Niches, Agronomy Journal,
Vol. 97, No. 1, p. 322-332, 2004.
[5] C. Nicolae, Rotatia culturilor, mijloc eficient de sporire a fertilitatii si a
productiei agricole pe solurile acide, Probleme agricole, Bucharest, 1971
[6] Benyamin Khoshnevisan, Elham Bolandnazar, Shahaboddin
Shamshirband, Hanifreza Motamed Shariati, Nor Badrul Anuar, Miss
Laiha Mat Kiah, Decreasing environmental impacts of cropping systems
using life cycle assessment (LCA) and multi-objective genetic
algorithm, Journal of Cleaner Production, Volume 86, Pages 67–77, 1
January 2015.
[7] Apostolos Perifanos, Petru Guș, Teodor Rusu, Simona Chetan,
Researches regarding the role of crop rotation and unconventional soil
tillage in sustainable agriculture, The 6th International Symposium Soil
Minimum Tillage Systems, p. 146-158, Cluj-Napoca, 27-29 June 2011.
[8] C.A. Francis, J.H. Sanders, Economic analysis of bean and maize
systems: monoculture versus associated cropping, Field Crops Research,
Volume 1, Pages 319-335, 1978.
[9] T. A. Delbridge, Jeffrey A. Coulter, Robert P. King, Craig C. Sheaffer
and Donald L. Wyse, Economic Performance of Long-Term Organic
and Conventional Cropping Systems in Minnesota, Agronomy Journal,
Vol. 103 No. 5, p. 1372-1382, 2010.
[10] C. O. Stöckle, M. Donatelli, R. Nelson, CropSyst, a cropping systems
simulation model, European Journal of Agronomy, Modelling Cropping
Systems: Science, Software and Applications, Volume 18, Issues 3–4,
Pages 289–307, January 2003
[11] Sin Gheorghe, Partal Elena, Influenţa rotaţiei şi a fertilizării asupra
producţiilor de grâu şi porumb în contextul variaţiilor climatice, AN.
I.N.C.D.A. Fundulea, vol. LXXVIII, nr. l, 2010
[12] C. Groșan, M. Oltean, Algoritmi Evolutivi, Ginfo, number 8, p. 30-36,
December 2011.
[13] D. A. Popescu, D. Radulescu, Monitoring of irrigation systems using
genetic algorithms, ICMSAO, IEEE Xplorer, pp. 1-4, 2015.
[14] D. A. Popescu, D. Radulescu, Approximately Similarity Measurement of
Web Sites, ICONIP, Neural Information Processing, LNCS, Springer, 9-
12 November, pp. 624-630, 2015.
[15] D. A. Popescu, D. Nicolae, Generating a class schedule with reduced
number of constraints, The 9th International Scientific Conference
eLearning and software for Education, Bucharest, April 25-26,
Proceedings, pag 297-300, 2013.
[16] D. A. Popescu, Probabilistic program that generates Langford
sequences, Buletin Stiintific - Universitatea din Pitesti, Seria Matematica
si Informatica, Nr. 12, pg. 129-133, 2006.
[17] Popescu, D. A. and Ionita, A. E. Combinatorica si Teoria Grafurilor, Ed.
Rhabon. Tg. Jiu, 2005.