Volume 3, Issue 2 (12-2021)
pbp 2021, 3(2): 18-31 |
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Salehi Sardoei A, Fazeli-Nasab B. Non-destructive estimation of leaf area of Citrus varieties of the Kotra Germplasm Bank. pbp 2021; 3 (2) :18-31
URL: http://pbp.medilam.ac.ir/article-1-78-en.html
URL: http://pbp.medilam.ac.ir/article-1-78-en.html
1- Department of Horticultural breeding and biotechnology, Gorgan Univ. of Agric. Sci. & Natur. Resour, Gorgan 49138-15739, Iran
2- Research Department of Agronomy and Plant Breeding, Agricultural Research Institute, University of Zabol, Zabol, Iran ,bfazelinasab@gmail.com
2- Research Department of Agronomy and Plant Breeding, Agricultural Research Institute, University of Zabol, Zabol, Iran ,
Abstract: (1304 Views)
Recently, mathematical modeling and computer expertise are advancing hastily. Their progression has been smooth sailing. The advancements have expedited and speeded up our scientific analyses. Hence, it is fruitful and essential to take advantage of the opportunities. Leaf area is among the most important plant properties which are directly related to ecological and physiological variables of a plant including leaf area index, light interception, evapotranspiration, photosynthesis, and growth. Thus, its calculation is extremely important. In this study, leaf area of species typica tress in Citrus and Subtropical Fruits Research Institute of Iran named Kotra Germplasm Bank include Orange (Citrus sinensis), Mandarin (Citrus reticulata), Lime (Citrus aurantifolia), and Lemon (Citrus lemon) were estimated using a non-destructive method Artificial neural network (NN) and by measuring quantitative leaf variables including width, length and a combination of width and length. For this purpose, four genera from each species were chosen and 200 leaves from different parts of their crown were collected. The width and length of the leaves were measured in the lab using a ruler, and their area was measured by a leaf area meter. This disquisition answered if GMDH-type NN was able to be applied to assess the area of the leaf as deferent according to particular variables consisting of a leaf with and leaf length. The average width, length, and area of leaves values significantly differed among the studied species as per the results.GMDH type NN provides a thriving tool for efficient detection of the model in data and precisely anticipating a proceeds indicator based on search input data and it’s able to be used to predict leaf area according to width and length.
Type of Study: Research |
Subject:
Herbal Drugs
Received: 2021/09/29 | Accepted: 2022/01/5 | Published: 2022/03/12
Received: 2021/09/29 | Accepted: 2022/01/5 | Published: 2022/03/12
References
1. Noorizadeh S, Golmohammadi M, Bagheri A, Bertaccini A. Citrus industry: Phytoplasma-associated diseases and related challenges for Asia, America and Africa. Crop protection. 2021;151(January):105822. doi:https://doi.org/10.1016/j.cropro.2021.105822.
2. Ahmadian-Moghadam H. Prediction of pepper (Capsicum annuum L.) leaf area using group method of data handling-type neural networks. International Journal of AgriScience. 2012;2(11):993-9.
3. Xiong H, Ma H, Hu B, Zhao H, Wang J, Rennenberg H, et al. Nitrogen fertilization stimulates nitrogen assimilation and modifies nitrogen partitioning in the spring shoot leaves of citrus (Citrus reticulata Blanco) trees. Journal of plant physiology. 2021;267(December):153556. doi:https://doi.org/10.1016/j.jplph.2021.153556.
4. Wang X, Christensen S, Svensgaard J, Jensen SM, Liu F. The effects of cultivar, nitrogen supply and soil type on radiation use efficiency and harvest index in spring wheat. Agronomy. 2020;10(9):1391. doi:https://doi.org/10.3390/agronomy10091391.
5. Ullah H, Santiago-Arenas R, Ferdous Z, Attia A, Datta A. Improving water use efficiency, nitrogen use efficiency, and radiation use efficiency in field crops under drought stress: A review. Advances in agronomy. 2019;156:109-57. doi:https://doi.org/10.1016/bs.agron.2019.02.002.
6. Demirsoy H. Leaf area estimation in some species of fruit tree by using models as a non-destructive method. Fruits. 2009;64(1):45-51. doi:https://doi.org/10.1051/fruits/2008049.
7. Kasaeian A, Ghalamchi M, Ahmadi MH, Ghalamchi M. GMDH algorithm for modeling the outlet temperatures of a solar chimney based on the ambient temperature. Mechanics & Industry. 2017;18(2):216. doi:https://doi.org/10.1051/meca/2016034.
8. Mendoza-de Gyves E, Rouphael Y, Cristofori V, Mira FR. A non-destructive, simple and accurate model for estimating the individual leaf area of kiwi (Actinidia deliciosa). Fruits. 2007;62(3):171-6. doi:https://doi.org/10.1051/fruits:2007012.
9. Ahmadi H, Mottaghitalab M, Nariman-Zadeh N. Group method of data handling-type neural network prediction of broiler performance based on dietary metabolizable energy, methionine, and lysine. Journal of Applied Poultry Research. 2007;16(4):494-501. doi:https://doi.org/10.3382/japr.2006-00074.
10. Ahmadi H, Mottaghitalab M, Nariman-Zadeh N, Golian A. Predicting performance of broiler chickens from dietary nutrients using group method of data handling-type neural networks. British poultry science. 2008;49(3):315-20. doi:https://doi.org/10.1080/00071660802136908.
11. Hassani SA, Sardoei AS, Sadeghian F, Bakhshi D, Fallahi S, Hossainava S. Group Method of Data Handling-Type Neural Network Prediction of Hazelnut Leaf Area Based On Length and Width of Leaf 11th Iranian horticultural Science Congress. 2019.
12. Nyakwende E, Paull C, Atherton J. Non-destructive determination of leaf area in tomato plants using image processing. Journal Of Horticultural Science. 1997;72(2):255-62. doi:https://doi.org/10.1080/14620316.1997.11515512.
13. Bhatla A, Choe SY, Fierro O, Leite F. Evaluation of accuracy of as-built 3D modeling from photos taken by handheld digital cameras. Automation in construction. 2012;28:116-27. doi:https://doi.org/10.1016/j.autcon.2012.06.003.
14. Posse RP, Sousa EFd, Bernardo S, Pereira MG, Gottardo RD. Total leaf area of papaya trees estimated by a nondestructive method. Scientia agricola. 2009;66:462-6. doi:https://doi.org/10.1590/S0103-90162009000400005.
15. Cristofori V, Rouphael Y, Mendoza-de Gyves E, Bignami C. A simple model for estimating leaf area of hazelnut from linear measurements. Scientia Horticulturae. 2007;113(2):221-5. doi:https://doi.org/10.1016/j.scienta.2007.02.006.
16. Serdar Ü, Demirsoy H. Non-destructive leaf area estimation in chestnut. Scientia Horticulturae. 2006;108(2):227-30. doi:https://doi.org/10.1016/j.scienta.2006.01.025.
17. Rivera C, Rouphael Y, Cardarelli M, Colla G. A simple and accurate equation for estimating individual leaf area of eggplant from linear measurements. European Journal of Horticultural Science. 2007;72(5):228-30.
18. Rouphael Y, Colla G, Fanasca S, Karam F. Leaf area estimation of sunflower leaves from simple linear measurements. Photosynthetica. 2007;45(2):306-8. doi:https://doi.org/10.1007/s11099-007-0051-z.
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