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

• Published in: Photosynthetica Vol. 49; no. 3; pp. 405 - 416
• Main Authors: Bakhshandeh, E, Kamkar, B, Tsialtas, J. T
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer-Verlag 01.09.2011; Springer Netherlands
• Subjects: Biomedical and Life Sciences; cultivars; Glycine max; leaf area; leaves; Life Sciences; linear models; Original Papers; plant growth; Plant Physiology; regression analysis; soybeans; soybean; leaf dimensions; dry mass; number of leaflets
• ISSN: 0300-3604; 1573-9058
• DOI: 10.1007/s11099-011-0048-5

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.