Non-destructive Prediction Models for Estimation of Leaf Area for Most Commonly Grown Vegetable Crops in Ethiopia
Science Journal of Applied Mathematics and Statistics
Volume 4, Issue 5, October 2016, Pages: 202-216
Received: Jul. 22, 2015; Accepted: Aug. 3, 2015; Published: Sep. 18, 2016
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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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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.
Modeling, Leaf Area, Vegetable Crops
To cite this article
Mikias Yeshitila, Matiwos Taye, Non-destructive Prediction Models for Estimation of Leaf Area for Most Commonly Grown Vegetable Crops in Ethiopia, Science Journal of Applied Mathematics and Statistics. Vol. 4, No. 5, 2016, pp. 202-216. doi: 10.11648/j.sjams.20160405.13
Gifford R. M., Thorne J. H., Witz W. D. and Giaquinta R. T. 1984. Crop productivity and photoassimilate partitioning. Science 225: 801–808.
Pearce R. B., Brown R. H., and Blaser R. E. 1965. Relationships between leaf area index, light interception and net photosynthesis in orchardgrass. Crop Sci. 5: 553–556.
Watson D. J. 1947. Comparative physiological studies on the growth of field crops: I. Variation in net assimilation rate and leaf area between species and varieties, and with and between years. Ann. Bot. (Lond.). 11: 41–76.
Manivel L. and Weaver R. J. 1974. Biometric correlations between leaf area and length measurement of ‘Grenache’ grape leaves. Hort-Science 9: 27–28.
De Swart E. A. M., Groenwold R., Kanne H. J., Stam P., Marcelis L. F. M. and Voorrips R. E. 2004. Non-destructive estimation of leaf area for different plant ages and accessions of Capsicum annuum L. Journal of Horticultural Science & Biotechnology 79: 764-770.
NeSmith D. S. 1991. Nondestructive leaf area estimation of rabbiteye blueberries. HortScience 26 (10): 1332.
NeSmith D. S. 1992. Estimating summer squash leaf area nondestructively. HortScience 27 (1): 77.
Gamiely S., Randle W. M., Mills H. A. and Smittle D. A. 1991. A Rapid and nondestructive method for estimating leaf area of onions. Hort Science, 26 (2): 206.
Robbins N. S., Pharr D. M. 1987. Leaf area prediction models for cucumber from linear measurments. Hortscience, 22 (6): 1264-1266.
Poethig, R. S. 1997. Leaf morphogenesis in flowering plants. The Plant Cell, 9, 1077–87.
Antunes W. C., Pompelli M. F., Carretero D. M., and DaMatta F. M. 2008. Allometric models for non-destructive leaf area estimation in coffee (Coffea arabica and Coffea canephora). Annals of Applied Biology 153: 33-40.
Kandiannan K., Parthasarathy U., Krishnamurthy K. S., Thankamani C. K. and Srinivasan V. 2009. Modelling individual leaf area of ginger (Zingiber officinale Roscoe) using leaf length and width. Scientia Horticulturae 120: 532-537.
Spann T. M. and Heerema R. J. 2010. A simple method for nondestructive estimation of total shoot leaf area in tree fruit crops. Scientia Horticulturae. 125: 528-533.
Rouphael Y., Mouneimne A. H., Rivera C. M., Cardarelli M., Marucci A. and Colla G. 2010. Allometric models for non-destructive leaf area estimation in grafted and un-grafted watermelon (Citrillus lanatus Thunb.) Journal of Food Agriculture and Environment. 8: 161-165.
Schwarz D. and Kläring H. P. 2001. Allometry to estimate leaf area of tomato. Journal of Plant Nutrition. 24: 1291-1309.
Verwijst T. and Wen D. Z. 1996. Leaf allometry of Salix viminalis during the first growing season. Tree Physiology, 16, 655–60.
Demirsoy H., Demirsoy L., Uzun S. and Ersoy B. 2004. Nondestructive leaf area estimation in peach. European Journal of Horticultural Science 69: 144-146.
Serdar U. and Demirsoy H. 2006. Non-destructive leaf area estimation in chestnut. Scientia Horticulturae. 108: 227-230.
Cristofori V., Fallovo C., Mendoza-De Gyves E., Rivera C. M., Bignami C., and Rouphael Y. 2008. Non-destructive, analogue model for leaf area estimation in persimmon (Diospyros kaki L. f.) based on leaf length and width measurement. European Journal of Horticultural Science 73: 216-221.
Mendoza-de Gyves E., Rouphael Y., Cristofori V. and Rosana Mira F. 2007. A non-destructive, simple and accurate model for estimating the individual leaf area of kiwi (Actinidia deliciosa). Fruits 62: 171-176.
Fallovo C., Cristofori V., Mendoza-De Gyves E., Rivera C. M., Fanasca S. and Bignami C. 2008. Leaf area estimation model for small fruits from linear measurements. Hort Science 43: 2263-2267.
Salerno A., Rivera C. M. Rouphael Y. Colla G. Cardarelli M. and Pierandrei F. 2005. Leaf area estimation of radish from linear measurements. Advances in Horticultural Science. 19: 213-215.
Rivera C. M., Rouphael Y., Cardarelli M. and Colla G. 2007. A simple and accurate equation for estimating individual leaf area of eggplant from linear measurements. European Journal of Horticultural Science 70: 228-230.
Wikipidia, 2013. Hawassa agro-ecology. (http://www.fao.or~/GIE WS). (Accessed on 21 July 2000)
Sokal R R & Rohif F I. 1981. Biometry: the principles and practice of statistics in biological research. San Francisco: W. H. Freeman, 1969. 776 p. [Department of Ecology and Evolution, State University of New York, Stony Brook, NYJ.
Sezgin U. and Hüseyin Ç. 1999. Leaf Area Prediction Models (Uzçelik-I) For Different Horticultural Plants. Tr. J. of Agriculture and Forestry. 23: 645-650.
Sadik S. K., AL-Taweel A. A, and Dhyeab N. S. 2011. New Computer Program for Estimating Leaf Area of Several Vegetable Crops. American-Eurasian Journal of Sustainable Agriculture, 5 (2): 304-309.
Erkut P. 2007. Non-destructive leaf area estimation model for Snap bean (Vicia Snap L.). Scientia Horticulturae. 113: 322–328.
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