Skip to main content
Log in

Application of linear models for estimation of leaf area in soybean [Glycine max (L.) Merr]

  • Original Papers
  • Published:
Photosynthetica

Abstract

Leaf area estimation is an important measurement for comparing plant growth in field and pot experiments. In this study, determination of the leaf area (LA, cm2) in soybean [Glycine max (L.) Merr] involves measurements of leaf parameters such as maximum terminal leaflet length (L, cm), width (W, cm), product of length and width (LW), green leaf dry matter (GLDM) and the total number of green leaflets per plant (TNLP) as independent variables. A two-year study was carried out during 2009 (three cultivars) and 2010 (four cultivars) under field conditions to build a model for estimation of LA across soybean cultivars. Regression analysis of LA vs. L and W revealed several functions that could be used to estimate the area of individual leaflet (LE), trifoliate (T) and total leaf area (TLA). Results showed that the LW-based models were better (highest R 2 and smallest RMSE) than models based on L or W and models that used GLDM and TNLP as independent variables. The proposed linear models are: LE = 0.754 + 0.655 LW, (R 2 = 0.98), T = −4.869 + 1.923 LW, (R 2 = 0.97), and TLA = 6.876 + 1.813 ΣLW (summed product of L and W terminal leaflets per plant), (R 2 = 0.99). The validation of the models based on LW and developed on cv. DPX showed that the correlation between calculated and measured LA was strong. Therefore, the proposed models can estimate accurately and massively the LA in soybeans without the use of expensive instrumentation.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Abbreviations

ALA:

actual leaf area

GLDM:

green leaf dry matter

L:

maximum length terminal leaflet

LA:

leaf area

LE:

leaflet area

LW:

product of length and w0idth of terminal leaflet

OLA:

observation leaf area0

PLA:

prediction leaf area

R 2 :

coefficient of determination

R 2 a :

adjusted coefficient of determination

RMSE:

root mean square error

T:

trifoliate area

TLA:

total leaf area

TNLP:

total number of green leaflets per plant

TV:

tolerance values

VIF:

variance inflation factor

W:

maximum width of terminal leaflet

SRO:

stepwise regression option

References

  • Akram-Ghaderi, F., Soltani, A.: Leaf area relationships to plant vegetative characteristics in cotton (Gossypium hirsutum L.) grown in a temperate sub-humid environment. — Int. J. Plant Prod. 1: 63–71, 2007.

    Google Scholar 

  • Bange, M.P., Hammer, G.L., Milroy, S.P., Rickert, K.G.: Improving estimates of individual leaf area of sunflower. — Agron. J. 92: 761–765, 2000.

    Article  Google Scholar 

  • Beerling, D.J., Fry, J.C.: A comparison of the accuracy, variability and speed of five different methods for estimating leaf area. — Ann. Bot. 65: 483–488, 1990.

    Google Scholar 

  • Bhatt, M., Chanda, S.V.: Prediction of leaf area in (Phaseolus vulgaris L.) by non-destructive method. — Bulgarian J. Plant Physiol. 29: 96–100, 2003.

    Google Scholar 

  • Bignami, C., Rossini, F.: Image analysis estimation of leaf area index and plant size of young hazelnut plants. — Sci. Hort. 71: 113–121, 1996.

    Google Scholar 

  • Bland, J.M., Altman, D.G.: Statistical methods for assessing agreement between two methods of clinical measurements. — Lancet 1: 307–310, 1986.

    Article  PubMed  CAS  Google Scholar 

  • Birch, C.J., Hammer, G.L., Rickert, K.G.: Improved methods for predicting individual leaf area and leaf senescence in maize (Zea mays L.). — Aust. J. Agr. Res. 49: 249–262, 1998.

    Article  Google Scholar 

  • Cankaya, S., Kayaalp, G.Y., Sangun, L., Tahtali, Y., Akar, M.: A comparative study of estimation methods for parameters in multiple linear regression model. — J. Appl. Anim. Res. 29: 43–47, 2006.

    Google Scholar 

  • Cristofori, V., Rouphael, Y., Mendoza-de Gyves, E., Bigniami, C.: A simple model for estimating leaf area of hazelnut from linear measurements. — Sci. Hort. 113: 221–225, 2007.

    Article  Google Scholar 

  • Daughtry, C.: Direct measurements of canopy structure. — Remote Sens. Rev. 5: 45–60: 1990.

    Article  Google Scholar 

  • de Jesus, W.C., Do Vale, F.X.R., Coelho, R.R., Costa, L.C.: Comparison of two methods for estimating leaf area index on common bean. — Agron. J. 93: 989–991, 2001.

    Article  Google Scholar 

  • de Swart, E.A.M., Groenwold, R., Kanne, H.J., Stam, P., Marcelis, L.F.M., Voorrips, R.E.: Non-destructive estimation of leaf area for different plant ages and accessions of Capsicum annuum L. — Hort. Sci. Biotechnol. 79: 764–770, 2004.

    Google Scholar 

  • Fallovo, C., Cristofori, V., Mendoza-de Gyves, E., et al.: Leaf area estimation model for small fruits from linear measurements. — Hort. Sci. 43: 2263–2267, 2008.

    Google Scholar 

  • Fehr, W.R., Caviness, C.E.: Stage of Soybean Development, — Iowa State University Cooperative Extension Service Special Report 80, Iowa City 1977.

  • Gamiely, S., Randle, W.M., Milks, W.A., Smittle, D.A.: A rapid and nondestructive method for estimating leaf area of onions. — Hort. Sci. 26: 206–212, 1991.

    Google Scholar 

  • Gill, J.L.: Outliers, residuals, and influence in multiple regressions. — J. Anim. Breed. Genet. 103: 161–175, 1986.

    Article  Google Scholar 

  • Hemmer, G.L., Carberry, P.S., Muchow, R.C.: Modeling genotype and environmental control of leaf area dynamics in grain sorghum. I. Whole plant level. — Field Crops Res. 33: 293–310, 1993.

    Article  Google Scholar 

  • Jonckheere, I., Fleck, S., Nackaerts, K., Muys, B., Coppin, P., Weiss, M., Baret, F.: Review of methods for in situ leaf area index determination. I: Theories, sensors and hemispherical photography. — Agr. Forest Meteorol. 121: 19–35, 2004.

    Article  Google Scholar 

  • Kandiannan, K., Parthasarathy, U., Krishnamurthy, K.S., Thankamani, C.K., Srinivasan, V.: Modeling individual leaf area of ginger (Zingiber officinale Roscoe) using leaf length and width. — Sci. Hort. 120: 532–537, 2009.

    Article  Google Scholar 

  • Kathirvelan, P., Kalaiselvan, P.: Peanut (Arachis hypogaea L.) leaf area estimation using allometric model. — Res. J. Agr. Biol. Sci. 3: 59–61, 2007.

    Google Scholar 

  • Kumar, R.: Calibration and validation of regression model for non-destructive leaf area estimation of saffron (Crocus sativus L.). — Sci. Hort. 122: 142–145, 2009.

    Article  Google Scholar 

  • Lieth, J.H., James, F., Reynolds, H., Rogers, H.: Estimation of leaf area of soybeans grown under elevated carbon dioxide levels. — Field Crops Res. 13: 193–203, 1986.

    Article  Google Scholar 

  • Lu, H.Y., Lu, C.T., Wei, M.L., Chan, L.F.: Comparison of different models for nondestructive leaf area estimation in taro. — Agron. J. 96: 448–453, 2004.

    Article  Google Scholar 

  • Ma, L., Gardener, F.P., Selamat, A.: Estimation of leaf area from leaf and total mass measurements in peanut. — Crop Sci. 32: 461–471, 1992.

    Google Scholar 

  • Marini, R.P.: Estimating mean fruit weight and mean fruit value for apple trees: comparison of two sampling methods with the true mean. — J. Am. Soc. Hort. Sci. 126: 503–510, 2001.

    Google Scholar 

  • Marquardt, D.W.: Generalized inverse, ridge regression, biased linear estimation, and nonlinear estimation. — Technometrics 12: 591–612, 1970.

    Article  Google Scholar 

  • Miranda, C., Royo, J.B.: A statistical model to estimate potential yields in peach before bloom. — J. Am. Soc. Hort. Sci. 128: 297–301, 2003.

    Google Scholar 

  • Miranda, C., Royo, J.B.: Statistical model estimates potential yield in “Golden Delicious” and “Royal Gala” apples before bloom. — J. Am. Soc. Hort. Sci. 129: 20–25, 2004.

    Google Scholar 

  • Mokhtarpour, H., Teh, C.B.S., Saleh, G., Selmat, A.B., Asadi, M.E., Kamar, B.: Non-destructive estimation of maize leaf area, fresh weight, and dry weight using leaf length and leaf width. — Commun. Biom. Crop Sci. 5: 19–26, 2010.

    Google Scholar 

  • Nesmith, D.S.: Non-destructive leaf area estimation of rabbiteye blueberries. — Hort. Sci. 26: 13–32, 1991.

    Google Scholar 

  • Neter, J., Kutner, M.H., Nachtshein, C.J., Wasserman, W.: Applied Linear Regression Models. 3rd Ed. Homewood III — Irwin, 1996.

  • Nyakwende, E., Paull, C.J., Atherton, J.G.: Non-destructive determination of leaf area in tomato plants using image processing. — J. Hort. Sci. 72: 225–262, 1997.

    Google Scholar 

  • Ogbuehi, S.N., Brandle, J.R.: Limitations in the use of dry weight and leaf number for predicting leaf area of soybeans. — Crop Sci. 21: 344–346, 1981.

    Article  Google Scholar 

  • Payne, W.A., Went, C.W., Hossner, L.R., Gates, C.E.: Estimating pearl millet leaf area and specific leaf area. — Agron. J. 83: 937–941, 1991.

    Article  Google Scholar 

  • Peksen, E.: Non-destructive leaf area estimation model for faba bean (Vicia faba L.). — Sci. Hort. 113: 322–328, 2007.

    Article  Google Scholar 

  • Ramos, J.M., Delmoral, L.F.G., Recalde, L.: Dry matter and leaf area relationship in winter barley. — Agron. J. 75: 308–310, 1983.

    Article  Google Scholar 

  • Rico-GarcÍa, E., Hernández-Hernández, F., Soto-Zarazúa, G.M., Herrera-Ruiz, G.: Two new methods for the estimation of leaf area using digital photography. — Int. J. Agr. Biol. 11: 397–400, 2009.

    Google Scholar 

  • Rouphael, Y., Colla, G., Fanasca, S., Karam, F.: Leaf area estimation of sunflower leaves from simple linear measurements. — Photosynthetica 45: 306–308, 2007.

    Article  Google Scholar 

  • Rouphael, Y., Mouneimne, A.H., Ismail, A., Mendoza, E., Rivera, C.M., Colla, G.: Modeling individual leaf area of rose (Rosa hybrida L.) based on leaf length and width measurement. — Photosynthetica 48: 9–15, 2010.

    Article  Google Scholar 

  • SAS Institute: SAS/STAT user’s guide. — SAS Institute Inc., Cary 1992.

    Google Scholar 

  • Serdar, U., Demirsoy, H.: Non-destructive leaf area estimation in chestnut. — Sci. Hort. 108: 227–230, 2006.

    Article  Google Scholar 

  • Setiyono, T.D., Weiss, A., Specht, J.K., Cassman, K.G., Dobermann, A.: Leaf area index simulation in soybean grown under near-optimal conditions. — Field Crops Res. 108: 82–92, 2008.

    Article  Google Scholar 

  • Shih, S.F., Gascho, G.J., Rahi, G.S.: Modeling biomass production of sweet sorghum. — Agron. J. 73: 1027–1032, 1981.

    Article  Google Scholar 

  • Shin, S.F., Snyder, G.H.: Leaf area index and dry biomass of taro. — Agron. J. 76: 750–753, 1984.

    Article  Google Scholar 

  • Sivakumar, M.V.K.: Prediction of leaf area index in soybean. — Ann. Bot. 42: 251–253, 1978.

    Google Scholar 

  • Soltani, A., Hoogenboom, G.: A statistical comparison of stochastic weather generators WGEN and SIMMETEO. — Climate Res. 24: 215–230, 2003.

    Article  Google Scholar 

  • Soltani, A., Robertson, M.J., Mohammad-Nejad, Y., Rahemi-Karizaki, A.: Modeling chickpea growth and development: Leaf prediction and senescence. — Field Crops Res. 138: 14–23, 2006.

    Article  Google Scholar 

  • Stoppani, M.I., Wolf, R., Francescangeli, N., Martí, H.R.: A non-destructive and rapid method for estimating leaf area of broccoli. — Adv. Hort. Sci. 17: 173–175, 2003.

    Google Scholar 

  • Tsialtas, J.T., Maslaris, N.: Leaf area estimation in a sugar beet cultivar by linear model. — Photosynthetica 43: 477–479, 2005.

    Article  Google Scholar 

  • Tsialtas, J.T., Maslaris, N.: Leaf shape and its relationship with Leaf Area Index in a sugar beet (Beta vulgaris L.) cultivar. — Photosynthetica 45: 527–532, 2007.

    Article  Google Scholar 

  • Tsialtas, J.T., Maslaris, N.: Evaluation of a leaf area prediction model proposed for sunflower. — Photosynthetica 46: 294–297, 2008a.

    Article  CAS  Google Scholar 

  • Tsialtas, J.T., Maslaris, N.: Leaf area prediction model for sugar beet (Beta vulgaris L.) cultivars. — Photosynthetica 46: 291–293, 2008b.

    Article  Google Scholar 

  • Tsialtas, J.T., Maslaris, N.: Leaf allometry and prediction of specific leaf area (SLA) in a sugar beet (Beta vulgaris L.) cultivar. — Photosynthetica 46: 351–355, 2008c.

    Article  Google Scholar 

  • Tsialtas, J.T., Koundouras, S., Zioziou, E.: Leaf area estimation by simple measurements and evaluation of leaf area prediction models in Cabernet-Sauvignon grapevine leaves. — Photosynthetica 46: 452–456, 2008.

    Article  Google Scholar 

  • Villegas, C.D., Bautista, A.T., Cotejo-Jr., F.R.: Accurate and rapid techniques for leaf area measurement in cassava and sweet potato. — Radix 3: 10–15, 1981.

    Google Scholar 

  • Wiersma, J.V., Bailey, T.B.: Estimation of leaflet, trifoliate and total leaf area of soybean. — Agron. J. 67: 26–30, 1975.

    Article  Google Scholar 

Download references

Acknowledgments

We thank Mr R. Ghadiryan and Mrs N. Ramzanzadeh for their kind help during the experimentation.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to E. Bakhshandeh.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Bakhshandeh, E., Kamkar, B. & Tsialtas, J.T. Application of linear models for estimation of leaf area in soybean [Glycine max (L.) Merr]. Photosynthetica 49, 405–416 (2011). https://doi.org/10.1007/s11099-011-0048-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11099-011-0048-5

Additional key words

Navigation