Non-destructive Prediction Models for Estimation of Leaf Area for Most Commonly Grown Vegetable Crops in Ethiopia

Mikias Yeshitila; Matiwos Taye

doi:doi:10.11648/j.sjams.20160405.13

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Non-destructive Prediction Models for Estimation of Leaf Area for Most Commonly Grown Vegetable Crops in Ethiopia

Mikias Yeshitila, Matiwos Taye

Published in Science Journal of Applied Mathematics and Statistics (Volume 4, Issue 5)

Received: 22 July 2015 Accepted: 3 August 2015 Published: 18 September 2016

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Abstract

Leaf area (LA) is a valuable key for evaluating plant growth, therefore rapid, accurate, simple, and nondestructive methods for LA determination are important for physiological and agronomic studies. The objective of this study was to develop a model for leaf area prediction from simple non-destructive measurements in some most commonly cultivated vegetable crops’ accessions in the country. A field experiment was carried out from May to August of 2014 at ‘Hawassa College of Agriculture’s research site, using ten selected most commonly grown vegetable species of Potato (Solanum tuberosum. L), Cabbage (Brassica campestris L.), Pepper (Capsicum annuum L.), Beetroot (Beta vulgaris), Swisschard (Beta vulgaris), Sweet potato (Ipomoea batatas L.), Snapbean (Vicia Snap L.) and Onion (Allium cepa). A standard method (LICOR LI-3000C) was also used for measuring the actual areas of the leaves. All equations produced for leaf area were derived as affected by leaf length and leaf width. As a result of ANOVA and multiple-regression analysis, it was found that there was close relationship between actual and predicted growth parameters. The produced leaf area prediction models in the present study are: AREA (cm²) = -16.882+2.533L (cm) + 4.5076W (cm) for Pepper Melka Awaze Variety. AREA (cm²) = -18.943+2.225L (cm) + 5.710W (cm) for Pepper Melka Zale Variety. AREA (cm²) = 136.8524 + 2.68L (cm) + 2.564W (cm) for Sweet-potato. AREA (cm²) = -193.518 + 8.633L (cm) + 14.018W (cm) for Beetroot. AREA (cm²) = -23.1534 + 1.1023L (cm) + 16.156W (cm) for Onion. AREA (cm²) = -260.265 + 27.115 (L (cm) * W (cm)) for Cabbage. AREA (cm²) = -422.973 + 22.752L (cm) + 8.31W (cm) for Swisschard. AREA (cm²) = 68.85 – 13.47L (cm) + 7.34W + 0.645L² (cm) -0.012W² (cm) for Snapbean. R² values (0.989, 0.976, 0.917, 0.926, 0.924, 0.966, 0.917, and 0.966 for the pepper Melka Awaze Variety, Pepper Melka Zale Variety, Sweetpotato, Beetroot, Onion, Cabbage, Swisschard and Snapbean respectively) and standard errors for all subsets of the independent variables were found to be significant at the p<0.001 level.

Published in	Science Journal of Applied Mathematics and Statistics (Volume 4, Issue 5)
DOI	10.11648/j.sjams.20160405.13
Page(s)	202-216
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

Modeling, Leaf Area, Vegetable Crops

References

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APA Style

Mikias Yeshitila, Matiwos Taye. (2016). Non-destructive Prediction Models for Estimation of Leaf Area for Most Commonly Grown Vegetable Crops in Ethiopia. Science Journal of Applied Mathematics and Statistics, 4(5), 202-216. https://doi.org/10.11648/j.sjams.20160405.13

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ACS Style

Mikias Yeshitila; Matiwos Taye. Non-destructive Prediction Models for Estimation of Leaf Area for Most Commonly Grown Vegetable Crops in Ethiopia. Sci. J. Appl. Math. Stat. 2016, 4(5), 202-216. doi: 10.11648/j.sjams.20160405.13

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AMA Style

Mikias Yeshitila, Matiwos Taye. Non-destructive Prediction Models for Estimation of Leaf Area for Most Commonly Grown Vegetable Crops in Ethiopia. Sci J Appl Math Stat. 2016;4(5):202-216. doi: 10.11648/j.sjams.20160405.13

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@article{10.11648/j.sjams.20160405.13,
  author = {Mikias Yeshitila and Matiwos Taye},
  title = {Non-destructive Prediction Models for Estimation of Leaf Area for Most Commonly Grown Vegetable Crops in Ethiopia},
  journal = {Science Journal of Applied Mathematics and Statistics},
  volume = {4},
  number = {5},
  pages = {202-216},
  doi = {10.11648/j.sjams.20160405.13},
  url = {https://doi.org/10.11648/j.sjams.20160405.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjams.20160405.13},
  abstract = {Leaf area (LA) is a valuable key for evaluating plant growth, therefore rapid, accurate, simple, and nondestructive methods for LA determination are important for physiological and agronomic studies. The objective of this study was to develop a model for leaf area prediction from simple non-destructive measurements in some most commonly cultivated vegetable crops’ accessions in the country. A field experiment was carried out from May to August of 2014 at ‘Hawassa College of Agriculture’s research site, using ten selected most commonly grown vegetable species of Potato (Solanum tuberosum. L), Cabbage (Brassica campestris L.), Pepper (Capsicum annuum L.), Beetroot (Beta vulgaris), Swisschard (Beta vulgaris), Sweet potato (Ipomoea batatas L.), Snapbean (Vicia Snap L.) and Onion (Allium cepa). A standard method (LICOR LI-3000C) was also used for measuring the actual areas of the leaves. All equations produced for leaf area were derived as affected by leaf length and leaf width. As a result of ANOVA and multiple-regression analysis, it was found that there was close relationship between actual and predicted growth parameters. The produced leaf area prediction models in the present study are: AREA (cm2) = -16.882+2.533L (cm) + 4.5076W (cm) for Pepper Melka Awaze Variety. AREA (cm2) = -18.943+2.225L (cm) + 5.710W (cm) for Pepper Melka Zale Variety. AREA (cm2) = 136.8524 + 2.68L (cm) + 2.564W (cm) for Sweet-potato. AREA (cm2) = -193.518 + 8.633L (cm) + 14.018W (cm) for Beetroot. AREA (cm2) = -23.1534 + 1.1023L (cm) + 16.156W (cm) for Onion. AREA (cm2) = -260.265 + 27.115 (L (cm) * W (cm)) for Cabbage. AREA (cm2) = -422.973 + 22.752L (cm) + 8.31W (cm) for Swisschard. AREA (cm2) = 68.85 – 13.47L (cm) + 7.34W + 0.645L2 (cm) -0.012W2 (cm) for Snapbean. R2 values (0.989, 0.976, 0.917, 0.926, 0.924, 0.966, 0.917, and 0.966 for the pepper Melka Awaze Variety, Pepper Melka Zale Variety, Sweetpotato, Beetroot, Onion, Cabbage, Swisschard and Snapbean respectively) and standard errors for all subsets of the independent variables were found to be significant at the p<0.001 level.},
 year = {2016}
}

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TY  - JOUR
T1  - Non-destructive Prediction Models for Estimation of Leaf Area for Most Commonly Grown Vegetable Crops in Ethiopia
AU  - Mikias Yeshitila
AU  - Matiwos Taye
Y1  - 2016/09/18
PY  - 2016
N1  - https://doi.org/10.11648/j.sjams.20160405.13
DO  - 10.11648/j.sjams.20160405.13
T2  - Science Journal of Applied Mathematics and Statistics
JF  - Science Journal of Applied Mathematics and Statistics
JO  - Science Journal of Applied Mathematics and Statistics
SP  - 202
EP  - 216
PB  - Science Publishing Group
SN  - 2376-9513
UR  - https://doi.org/10.11648/j.sjams.20160405.13
AB  - Leaf area (LA) is a valuable key for evaluating plant growth, therefore rapid, accurate, simple, and nondestructive methods for LA determination are important for physiological and agronomic studies. The objective of this study was to develop a model for leaf area prediction from simple non-destructive measurements in some most commonly cultivated vegetable crops’ accessions in the country. A field experiment was carried out from May to August of 2014 at ‘Hawassa College of Agriculture’s research site, using ten selected most commonly grown vegetable species of Potato (Solanum tuberosum. L), Cabbage (Brassica campestris L.), Pepper (Capsicum annuum L.), Beetroot (Beta vulgaris), Swisschard (Beta vulgaris), Sweet potato (Ipomoea batatas L.), Snapbean (Vicia Snap L.) and Onion (Allium cepa). A standard method (LICOR LI-3000C) was also used for measuring the actual areas of the leaves. All equations produced for leaf area were derived as affected by leaf length and leaf width. As a result of ANOVA and multiple-regression analysis, it was found that there was close relationship between actual and predicted growth parameters. The produced leaf area prediction models in the present study are: AREA (cm2) = -16.882+2.533L (cm) + 4.5076W (cm) for Pepper Melka Awaze Variety. AREA (cm2) = -18.943+2.225L (cm) + 5.710W (cm) for Pepper Melka Zale Variety. AREA (cm2) = 136.8524 + 2.68L (cm) + 2.564W (cm) for Sweet-potato. AREA (cm2) = -193.518 + 8.633L (cm) + 14.018W (cm) for Beetroot. AREA (cm2) = -23.1534 + 1.1023L (cm) + 16.156W (cm) for Onion. AREA (cm2) = -260.265 + 27.115 (L (cm) * W (cm)) for Cabbage. AREA (cm2) = -422.973 + 22.752L (cm) + 8.31W (cm) for Swisschard. AREA (cm2) = 68.85 – 13.47L (cm) + 7.34W + 0.645L2 (cm) -0.012W2 (cm) for Snapbean. R2 values (0.989, 0.976, 0.917, 0.926, 0.924, 0.966, 0.917, and 0.966 for the pepper Melka Awaze Variety, Pepper Melka Zale Variety, Sweetpotato, Beetroot, Onion, Cabbage, Swisschard and Snapbean respectively) and standard errors for all subsets of the independent variables were found to be significant at the p<0.001 level.
VL  - 4
IS  - 5
ER  -

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Author Information

Mikias Yeshitila

Department of Plant and Horticultural Sciences, College of Agriculture, Hawassa University, Awassa, Ethiopia
Matiwos Taye

Department of Plant and Horticultural Sciences, College of Agriculture, Hawassa University, Awassa, Ethiopia

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APA Style

Mikias Yeshitila, Matiwos Taye. (2016). Non-destructive Prediction Models for Estimation of Leaf Area for Most Commonly Grown Vegetable Crops in Ethiopia. Science Journal of Applied Mathematics and Statistics, 4(5), 202-216. https://doi.org/10.11648/j.sjams.20160405.13

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ACS Style

Mikias Yeshitila; Matiwos Taye. Non-destructive Prediction Models for Estimation of Leaf Area for Most Commonly Grown Vegetable Crops in Ethiopia. Sci. J. Appl. Math. Stat. 2016, 4(5), 202-216. doi: 10.11648/j.sjams.20160405.13

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AMA Style

Mikias Yeshitila, Matiwos Taye. Non-destructive Prediction Models for Estimation of Leaf Area for Most Commonly Grown Vegetable Crops in Ethiopia. Sci J Appl Math Stat. 2016;4(5):202-216. doi: 10.11648/j.sjams.20160405.13

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@article{10.11648/j.sjams.20160405.13,
  author = {Mikias Yeshitila and Matiwos Taye},
  title = {Non-destructive Prediction Models for Estimation of Leaf Area for Most Commonly Grown Vegetable Crops in Ethiopia},
  journal = {Science Journal of Applied Mathematics and Statistics},
  volume = {4},
  number = {5},
  pages = {202-216},
  doi = {10.11648/j.sjams.20160405.13},
  url = {https://doi.org/10.11648/j.sjams.20160405.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjams.20160405.13},
  abstract = {Leaf area (LA) is a valuable key for evaluating plant growth, therefore rapid, accurate, simple, and nondestructive methods for LA determination are important for physiological and agronomic studies. The objective of this study was to develop a model for leaf area prediction from simple non-destructive measurements in some most commonly cultivated vegetable crops’ accessions in the country. A field experiment was carried out from May to August of 2014 at ‘Hawassa College of Agriculture’s research site, using ten selected most commonly grown vegetable species of Potato (Solanum tuberosum. L), Cabbage (Brassica campestris L.), Pepper (Capsicum annuum L.), Beetroot (Beta vulgaris), Swisschard (Beta vulgaris), Sweet potato (Ipomoea batatas L.), Snapbean (Vicia Snap L.) and Onion (Allium cepa). A standard method (LICOR LI-3000C) was also used for measuring the actual areas of the leaves. All equations produced for leaf area were derived as affected by leaf length and leaf width. As a result of ANOVA and multiple-regression analysis, it was found that there was close relationship between actual and predicted growth parameters. The produced leaf area prediction models in the present study are: AREA (cm2) = -16.882+2.533L (cm) + 4.5076W (cm) for Pepper Melka Awaze Variety. AREA (cm2) = -18.943+2.225L (cm) + 5.710W (cm) for Pepper Melka Zale Variety. AREA (cm2) = 136.8524 + 2.68L (cm) + 2.564W (cm) for Sweet-potato. AREA (cm2) = -193.518 + 8.633L (cm) + 14.018W (cm) for Beetroot. AREA (cm2) = -23.1534 + 1.1023L (cm) + 16.156W (cm) for Onion. AREA (cm2) = -260.265 + 27.115 (L (cm) * W (cm)) for Cabbage. AREA (cm2) = -422.973 + 22.752L (cm) + 8.31W (cm) for Swisschard. AREA (cm2) = 68.85 – 13.47L (cm) + 7.34W + 0.645L2 (cm) -0.012W2 (cm) for Snapbean. R2 values (0.989, 0.976, 0.917, 0.926, 0.924, 0.966, 0.917, and 0.966 for the pepper Melka Awaze Variety, Pepper Melka Zale Variety, Sweetpotato, Beetroot, Onion, Cabbage, Swisschard and Snapbean respectively) and standard errors for all subsets of the independent variables were found to be significant at the p<0.001 level.},
 year = {2016}
}

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TY  - JOUR
T1  - Non-destructive Prediction Models for Estimation of Leaf Area for Most Commonly Grown Vegetable Crops in Ethiopia
AU  - Mikias Yeshitila
AU  - Matiwos Taye
Y1  - 2016/09/18
PY  - 2016
N1  - https://doi.org/10.11648/j.sjams.20160405.13
DO  - 10.11648/j.sjams.20160405.13
T2  - Science Journal of Applied Mathematics and Statistics
JF  - Science Journal of Applied Mathematics and Statistics
JO  - Science Journal of Applied Mathematics and Statistics
SP  - 202
EP  - 216
PB  - Science Publishing Group
SN  - 2376-9513
UR  - https://doi.org/10.11648/j.sjams.20160405.13
AB  - Leaf area (LA) is a valuable key for evaluating plant growth, therefore rapid, accurate, simple, and nondestructive methods for LA determination are important for physiological and agronomic studies. The objective of this study was to develop a model for leaf area prediction from simple non-destructive measurements in some most commonly cultivated vegetable crops’ accessions in the country. A field experiment was carried out from May to August of 2014 at ‘Hawassa College of Agriculture’s research site, using ten selected most commonly grown vegetable species of Potato (Solanum tuberosum. L), Cabbage (Brassica campestris L.), Pepper (Capsicum annuum L.), Beetroot (Beta vulgaris), Swisschard (Beta vulgaris), Sweet potato (Ipomoea batatas L.), Snapbean (Vicia Snap L.) and Onion (Allium cepa). A standard method (LICOR LI-3000C) was also used for measuring the actual areas of the leaves. All equations produced for leaf area were derived as affected by leaf length and leaf width. As a result of ANOVA and multiple-regression analysis, it was found that there was close relationship between actual and predicted growth parameters. The produced leaf area prediction models in the present study are: AREA (cm2) = -16.882+2.533L (cm) + 4.5076W (cm) for Pepper Melka Awaze Variety. AREA (cm2) = -18.943+2.225L (cm) + 5.710W (cm) for Pepper Melka Zale Variety. AREA (cm2) = 136.8524 + 2.68L (cm) + 2.564W (cm) for Sweet-potato. AREA (cm2) = -193.518 + 8.633L (cm) + 14.018W (cm) for Beetroot. AREA (cm2) = -23.1534 + 1.1023L (cm) + 16.156W (cm) for Onion. AREA (cm2) = -260.265 + 27.115 (L (cm) * W (cm)) for Cabbage. AREA (cm2) = -422.973 + 22.752L (cm) + 8.31W (cm) for Swisschard. AREA (cm2) = 68.85 – 13.47L (cm) + 7.34W + 0.645L2 (cm) -0.012W2 (cm) for Snapbean. R2 values (0.989, 0.976, 0.917, 0.926, 0.924, 0.966, 0.917, and 0.966 for the pepper Melka Awaze Variety, Pepper Melka Zale Variety, Sweetpotato, Beetroot, Onion, Cabbage, Swisschard and Snapbean respectively) and standard errors for all subsets of the independent variables were found to be significant at the p<0.001 level.
VL  - 4
IS  - 5
ER  -

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