A new, simplified and non-destructive estimate of leaf area, leaf fresh and dry weight of greenhouse cucumber Cucumis sativus (Cucurbitaceae) by linear measurements

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Research Paper 01/07/2018
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A new, simplified and non-destructive estimate of leaf area, leaf fresh and dry weight of greenhouse cucumber Cucumis sativus (Cucurbitaceae) by linear measurements

Tahereh Alaee, Shahrzad Iranipour, Roghayeh Karimzadeh
J. Bio. Env. Sci.13( 1), 285-292, July 2018.
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Abstract

The estimation of leaf area and leaf fresh and dry weight are used in agronomy to follow the development of crops, and to predict light interception and productivity. In small plant populations using non-destructive methods of leaf area measurements could be useful. In this study because of equipment limitations, the transparent paper and simple ruler were used. A mathematical model can be assessed by correlation between leaf length (L), width (W) or length x width (LW) to the actual leaf area of a sample leaves using regression analysis. SPAD values (S) also used for high accuracy estimation of leaf fresh and dry weight. Regression models including highest R² value and lowest RMSE selected. Y=-4.043-1.415LW+1.050 L²  Y=-0.125+0.00741 LW+0.000208 LWS (R²=0.945, RMSE= 0.58), Y=-0.0435+0.0000467 LWS+0.00134 LW (R²=0.887, RMSE= 0.17) were the best predicted models for estimation of leaf area, leaf fresh weight and leaf dry weight, respectively. To evaluate the accuracy of the model, estimated values of individual leaves were plotted against measured values. The SPAD value parameter using in fresh and dry weight equation with higher accuracy, showed that SPAD meter is a relatively inexpensive, fast, easy, and non-destructive machinery for recognition of crop N nutrition that has simplified research in plant development. Therefore, it is concluded that high accuracy models can be used resulting in time and effort saving for estimation of leaf area, leaf fresh and dry weight in order to trace crops growth.

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Beerling DJ, Fry JC. 1990. A comparison of the accuracy, variability and speed of five different methods for estimating leaf area. Annals of Botany 65(5), 483-488.

Blanco F, Folegatti MV. 2005. Estimation of leaf area for greenhouse cucumber by linear measurements under salinity and grafting. Scientia Agricola 62(4), 305-309.

Caliskan O, Odabas MS, Cirak C. 2009. The modeling of the relation among the temperature and light intensity of growth in Ocimum basilicum L. Journal of Medicinal Plants Research 3(11), 965-977.

Centritto M, Loreto F, Massacci A, Pietrini F, Villani MC, Zacchini M. 2000. Improved growth and water use efficiency of cherry saplings under reduced light intensity. Ecological Research 15(4), 385-392.

Cho YY, Oh S, Oh MM, Son JE. 2007. Estimation of individual leaf area, fresh weight, and dry weight of hydroponically grown cucumbers (Cucumis sativus L.) using leaf length, width, and SPAD value. Scientia Horticulturae 111(4), 330-334.

Cittadini ED, Peri PL. 2006. Estimation of leaf area in sweet cherry using a non-destructive method. RIA. Revista de Investigaciones Agropecuarias 35(1),

Coombs J, Hall DO, Long S. 2014. Techniques in bioproductivity and photosynthesis: pergamon international library of science, technology, engineering and social studies, Elsevier.

Córcoles J, Dommingues A, Moreno M, Ortega J, De Juan J. 2015. A non-destructive method for estimating onion leaf area. Irish Journal of Agricultural and Food Research 54(1), 17-30.

de Jesus WC, Do Vale FXR, Coelho RR, Costa LC. 2001. Comparison of two methods for estimating leaf area index on common bean. Agronomy Journal 93(5), 989-991.

Gifford RM, Thorne J, Hitz W, Giaquinta RT. 1984. Crop productivity and photoassimilate partitioning. Science 225(4664), 801-808.

Hooke R. 1907. Correlation of the weather and crops. Journal of the Royal Statistical Society 70(1), 1-51.

Jonckheere I, Fleck S, Nackaerts K, Muys, Coppin P, Weiss M, Baret F. 2004. Review of methods for in situ leaf area index determination: Part I. Theories, sensors and hemispherical photography. Agricultural and Forest Meteorology 121(1-2), 19-35.

Kandiannan K, Parthasarathy U, Krishnamurthy K, Thankamani C, Srinivasan V. 2009. Modeling individual leaf area of ginger (Zingiber officinale Roscoe) using leaf length and width. Scientia Horticulturae 120(4), 532-537.

Kumbhani NR, Kuvad RP, Thaker VS. 2017. Development of linear model for leaf area measurement of two medicinally important plants: Helicteres isora L. and Vitex negundo LJ App. Journal of Applied Biology and Biotechnology.(India) 5(03), 057-060.

Küßner R, Mosandl R. 2000. Comparison of direct and indirect estimation of leaf area index in mature Norway spruce stands of eastern Germany. Canadian Journal of Forest Research 30(3), 440-447.

Kvet J, Marshall J. 1971. Assessment of leaf area and other assimilating plant surfaces. Sestak, Z. Plant Photosynthetic Production.

Le Bail M, Jeuffroy MH, Bouchard C, Barbottin A. 2005. Is it possible to forecast the grain quality and yield of different varieties of winter wheat from Minolta SPAD meter measurements? European Journal of Agronomy 23(4), 379-391.

Lu HY, Lu CT, Wei ML, Chan LF. 2004. Comparison of different models for nondestructive leaf area estimation in taro. Agronomy Journal 96(2), 448-453.

Marshall J. 1968. Methods for leaf area maeasurement of large and small leaf samples.

Mendoza-de G, Cristofori EV, Fallovo, ouphael Y, Bignami C. 2008. Accurate and rapid technique for leaf area measurement in medlar (Mespilus germanica L.). Advances in Horticultural Science 223-226.

Mikias Yeshitila MT. 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.

Montero F, De Juan J, Cuesta A, Brasa A. 2000. Nondestructive methods to estimate leaf area in Vitis vinifera L. HortScience 35(4), 696-698.

Montgomery E. 1911. Correlation studies in corn. bulletin of the Agricultural Experiment Station of Nebraska. 24, 108-159.

NeSmith D. 1992. Estimating summer squash leaf area nondestructively. HortScience 27(1), 77-77.

Norman JM, Campbell GS. 1989. Canopy structure. Plant Physiological Ecology, Springer 301-325.

Odabas MS, Ayan AK. 2005. Leaf area prediction model for summer snowflake (Leucojum aestivum L.). International Journal of Botany.

Olfati JA, Peyvast G, Sanavi M, Salehi M, Mahdipour M, Nosratie-Rad Z. 2009. Comparisons of leaf area estimation from linear measurements of red cabbage. International Journal of Vegetable Science 15(2), 185-192.

Robbins N, Pharr D. 1987. Leaf area prediction models for cucumber from linear measurements. Hort Science (USA).

Sadik S, Al-Taweel A, Dhyeab N, Khalaf M. 2011. New computer program for estimating leaf area of siveral vegetable crops. American-Eurasian Journal of Sustainable Agriculture 304-310.

Shabani A, Sepaskhah A. 2017. Leaf area estimation by a simple and non-destructive method. Iran Agricultural Research 36(2), 101-105.

Sharratt B, Baker D. 1986. Alfalfa Leaf Area as a Function of Dry Matter 1. Crop Science 26(5), 1040-1043.

Stoppani MI, Wolf R, Francescangeli N, Marti HR. 2003. A nondestructive and rapid method for estimating leaf area of broccoli. Advances in Horticultural Science 173-175.

Uzun S, Celik H. 1999. Leaf area prediction models (Uzçelik-I) for different horticultural plants.” Turkish Journal of Agriculture and Forestry 23(6), 645-650.

Watson DJ. 1947. Comparative physiological studies on the growth of field crops: I. Variation in net assimilation rate and leaf area between species and varieties, and within and between years. Annals of Botany 11(41), 41-76.

Williams III L, Martinson TE. 2003. Nondestructive leaf area estimation of ‘Niagara’and ‘DeChaunac’grapevines. Scientia Horticulturae 98(4), 493-498.