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Estimation of Leaflet, Trifoliolate, and Total Leaf Areas of Soybeans¹

The importance of rapid, nondestuctive, and accurate measurements of leaf area for agronomic and physiological studies is well known. Several mathematical formulas have been derived for estimating leaf areas for numerous crops, but there is little information available for soybeans [Glycine max (L.) Merr.]. The purpose of this study, therefore, was to develop prediction equations for estimating leaflet, trifoliolate, and total leaf areas of soybeans.

Statistical analyses of soybean leaf areas were divided into three levels: leaflet, trifoliolate, and total leaf area. At each level, we compared the predictive abilities of three regression equations, each involving a different independent variable. On the basis of these results, we chose one independent variable at each level for subsequent regression analyses of various hypotheses. Prediction equations derived from independent variables involving measurements of length and width were superior at each level to those involving measurements of only length or width. Our data indicate, however, that considerable savings of time, with little loss of predictive ability, could be possible by measuring only length or width in each instance.

With the use of independent variables involving measurements of length and width, regression analyses were performed to assess the effects of cultivars at each level and also the effects of leaflet orientation on the trifoliolate and the trifoliolate position on the plant at their respective levels. In general, these analyses indicated that a single regression equation could be used at each level. Leaflet, trifoliolate, and total leaf areas of the 12 cultivars we studied could be estimated by the following equations, respectively: A = 0.624 + 0.723LW (R² = 0.985); A = 0.411 + 2.008LW (terminal leaflet) (R² = 0.983); A = 6.532 + 2.045 (L₁W₁ terminal leaflets) (R² = 0.965).

Key Words: Cultivars • Models • Length-width method

² Assistant Professor, Department of Statistics and Statistical Laboratory, Iowa State University, Ames, IA 50010.

Received for publication July 2, 1974.

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