Maize Growth (<i>Zea mays l</i>.) Modeling Using the Artificial Neural Networks Method at Daloa (Côte d’Ivoire)

Kouame N’Guessan; Assidjo Nogbou Emmanuel

doi:doi:10.11648/j.aff.20211002.17

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Maize Growth (Zea mays l.) Modeling Using the Artificial Neural Networks Method at Daloa (Côte d’Ivoire)

Kouame N’Guessan, Assidjo Nogbou Emmanuel

Published in Agriculture, Forestry and Fisheries (Volume 10, Issue 2)

Received: 23 February 2021 Accepted: 8 March 2021 Published: 26 March 2021

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Abstract

The growth of maize is a complex phenomenon which involves certain parameters including the number of leaves, the length of the leaves, the width of the leaves, the height and the circumference of the plant. A study of these growth parameters was carried out in the region of Daloa (Côte d’Ivoire). These measurements could show a complexity of the growth of maize. To this end, mathematical models have been developed to predict this growth from artificial neural networks for the number of leaves, the length of the leaves, the width of the leaves, the height of the plant and the circumference of the trunk of the maize plant. The coefficients of determination between the experimental measurements and the measurements predicted by artificial neural networks are respectively 0.9914; 0.9965; 0.9872; 0.9995 and 0.9976 for plant height; the number of leaves; the circumference of the plant; leaf length and leaf width. Satisfactory results have been obtained insofar as all the coefficients of determination are greater than 0.98. These coefficients close to 1 show a good interpolation between the experimental values and those predicted by the model. Because of this, we can say that the values predicted by the artificial neural network are reliable enough to predict the growth of maize.

Published in	Agriculture, Forestry and Fisheries (Volume 10, Issue 2)
DOI	10.11648/j.aff.20211002.17
Page(s)	85-92
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Maize, Growth Parameter, Modeling, Artificial Neural Network

References

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Kouame N’Guessan, Assidjo Nogbou Emmanuel. (2021). Maize Growth (Zea mays l.) Modeling Using the Artificial Neural Networks Method at Daloa (Côte d’Ivoire). Agriculture, Forestry and Fisheries, 10(2), 85-92. https://doi.org/10.11648/j.aff.20211002.17

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ACS Style

Kouame N’Guessan; Assidjo Nogbou Emmanuel. Maize Growth (Zea mays l.) Modeling Using the Artificial Neural Networks Method at Daloa (Côte d’Ivoire). Agric. For. Fish. 2021, 10(2), 85-92. doi: 10.11648/j.aff.20211002.17

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Kouame N’Guessan, Assidjo Nogbou Emmanuel. Maize Growth (Zea mays l.) Modeling Using the Artificial Neural Networks Method at Daloa (Côte d’Ivoire). Agric For Fish. 2021;10(2):85-92. doi: 10.11648/j.aff.20211002.17

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@article{10.11648/j.aff.20211002.17,
  author = {Kouame N’Guessan and Assidjo Nogbou Emmanuel},
  title = {Maize Growth (Zea mays l.) Modeling Using the Artificial Neural Networks Method at Daloa (Côte d’Ivoire)},
  journal = {Agriculture, Forestry and Fisheries},
  volume = {10},
  number = {2},
  pages = {85-92},
  doi = {10.11648/j.aff.20211002.17},
  url = {https://doi.org/10.11648/j.aff.20211002.17},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.aff.20211002.17},
  abstract = {The growth of maize is a complex phenomenon which involves certain parameters including the number of leaves, the length of the leaves, the width of the leaves, the height and the circumference of the plant. A study of these growth parameters was carried out in the region of Daloa (Côte d’Ivoire). These measurements could show a complexity of the growth of maize. To this end, mathematical models have been developed to predict this growth from artificial neural networks for the number of leaves, the length of the leaves, the width of the leaves, the height of the plant and the circumference of the trunk of the maize plant. The coefficients of determination between the experimental measurements and the measurements predicted by artificial neural networks are respectively 0.9914; 0.9965; 0.9872; 0.9995 and 0.9976 for plant height; the number of leaves; the circumference of the plant; leaf length and leaf width. Satisfactory results have been obtained insofar as all the coefficients of determination are greater than 0.98. These coefficients close to 1 show a good interpolation between the experimental values and those predicted by the model. Because of this, we can say that the values predicted by the artificial neural network are reliable enough to predict the growth of maize.},
 year = {2021}
}

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TY  - JOUR
T1  - Maize Growth (Zea mays l.) Modeling Using the Artificial Neural Networks Method at Daloa (Côte d’Ivoire)
AU  - Kouame N’Guessan
AU  - Assidjo Nogbou Emmanuel
Y1  - 2021/03/26
PY  - 2021
N1  - https://doi.org/10.11648/j.aff.20211002.17
DO  - 10.11648/j.aff.20211002.17
T2  - Agriculture, Forestry and Fisheries
JF  - Agriculture, Forestry and Fisheries
JO  - Agriculture, Forestry and Fisheries
SP  - 85
EP  - 92
PB  - Science Publishing Group
SN  - 2328-5648
UR  - https://doi.org/10.11648/j.aff.20211002.17
AB  - The growth of maize is a complex phenomenon which involves certain parameters including the number of leaves, the length of the leaves, the width of the leaves, the height and the circumference of the plant. A study of these growth parameters was carried out in the region of Daloa (Côte d’Ivoire). These measurements could show a complexity of the growth of maize. To this end, mathematical models have been developed to predict this growth from artificial neural networks for the number of leaves, the length of the leaves, the width of the leaves, the height of the plant and the circumference of the trunk of the maize plant. The coefficients of determination between the experimental measurements and the measurements predicted by artificial neural networks are respectively 0.9914; 0.9965; 0.9872; 0.9995 and 0.9976 for plant height; the number of leaves; the circumference of the plant; leaf length and leaf width. Satisfactory results have been obtained insofar as all the coefficients of determination are greater than 0.98. These coefficients close to 1 show a good interpolation between the experimental values and those predicted by the model. Because of this, we can say that the values predicted by the artificial neural network are reliable enough to predict the growth of maize.
VL  - 10
IS  - 2
ER  -

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Author Information

Kouame N’Guessan

Agricultural Production Improvement Laboratory, University Jean Lorougnon Guede, Agroforestry Training and Research Unit, Daloa, C?te d’Ivoire
Assidjo Nogbou Emmanuel

Laboratory of Industrial Synthesis and Environment Processes, National Polytechnic Institute Felix Houphou?t-Boigny, Yamoussoukro, C?te d’Ivoire

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APA Style

Kouame N’Guessan, Assidjo Nogbou Emmanuel. (2021). Maize Growth (Zea mays l.) Modeling Using the Artificial Neural Networks Method at Daloa (Côte d’Ivoire). Agriculture, Forestry and Fisheries, 10(2), 85-92. https://doi.org/10.11648/j.aff.20211002.17

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ACS Style

Kouame N’Guessan; Assidjo Nogbou Emmanuel. Maize Growth (Zea mays l.) Modeling Using the Artificial Neural Networks Method at Daloa (Côte d’Ivoire). Agric. For. Fish. 2021, 10(2), 85-92. doi: 10.11648/j.aff.20211002.17

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AMA Style

Kouame N’Guessan, Assidjo Nogbou Emmanuel. Maize Growth (Zea mays l.) Modeling Using the Artificial Neural Networks Method at Daloa (Côte d’Ivoire). Agric For Fish. 2021;10(2):85-92. doi: 10.11648/j.aff.20211002.17

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@article{10.11648/j.aff.20211002.17,
  author = {Kouame N’Guessan and Assidjo Nogbou Emmanuel},
  title = {Maize Growth (Zea mays l.) Modeling Using the Artificial Neural Networks Method at Daloa (Côte d’Ivoire)},
  journal = {Agriculture, Forestry and Fisheries},
  volume = {10},
  number = {2},
  pages = {85-92},
  doi = {10.11648/j.aff.20211002.17},
  url = {https://doi.org/10.11648/j.aff.20211002.17},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.aff.20211002.17},
  abstract = {The growth of maize is a complex phenomenon which involves certain parameters including the number of leaves, the length of the leaves, the width of the leaves, the height and the circumference of the plant. A study of these growth parameters was carried out in the region of Daloa (Côte d’Ivoire). These measurements could show a complexity of the growth of maize. To this end, mathematical models have been developed to predict this growth from artificial neural networks for the number of leaves, the length of the leaves, the width of the leaves, the height of the plant and the circumference of the trunk of the maize plant. The coefficients of determination between the experimental measurements and the measurements predicted by artificial neural networks are respectively 0.9914; 0.9965; 0.9872; 0.9995 and 0.9976 for plant height; the number of leaves; the circumference of the plant; leaf length and leaf width. Satisfactory results have been obtained insofar as all the coefficients of determination are greater than 0.98. These coefficients close to 1 show a good interpolation between the experimental values and those predicted by the model. Because of this, we can say that the values predicted by the artificial neural network are reliable enough to predict the growth of maize.},
 year = {2021}
}

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TY  - JOUR
T1  - Maize Growth (Zea mays l.) Modeling Using the Artificial Neural Networks Method at Daloa (Côte d’Ivoire)
AU  - Kouame N’Guessan
AU  - Assidjo Nogbou Emmanuel
Y1  - 2021/03/26
PY  - 2021
N1  - https://doi.org/10.11648/j.aff.20211002.17
DO  - 10.11648/j.aff.20211002.17
T2  - Agriculture, Forestry and Fisheries
JF  - Agriculture, Forestry and Fisheries
JO  - Agriculture, Forestry and Fisheries
SP  - 85
EP  - 92
PB  - Science Publishing Group
SN  - 2328-5648
UR  - https://doi.org/10.11648/j.aff.20211002.17
AB  - The growth of maize is a complex phenomenon which involves certain parameters including the number of leaves, the length of the leaves, the width of the leaves, the height and the circumference of the plant. A study of these growth parameters was carried out in the region of Daloa (Côte d’Ivoire). These measurements could show a complexity of the growth of maize. To this end, mathematical models have been developed to predict this growth from artificial neural networks for the number of leaves, the length of the leaves, the width of the leaves, the height of the plant and the circumference of the trunk of the maize plant. The coefficients of determination between the experimental measurements and the measurements predicted by artificial neural networks are respectively 0.9914; 0.9965; 0.9872; 0.9995 and 0.9976 for plant height; the number of leaves; the circumference of the plant; leaf length and leaf width. Satisfactory results have been obtained insofar as all the coefficients of determination are greater than 0.98. These coefficients close to 1 show a good interpolation between the experimental values and those predicted by the model. Because of this, we can say that the values predicted by the artificial neural network are reliable enough to predict the growth of maize.
VL  - 10
IS  - 2
ER  -

Copy | Download