### Non-destructive Method for Estimating the Leaf Area of Pear cv. ‘Triunfo’

•  Vinicius de Souza Oliveira
•  Karina Tiemi Hassuda dos Santos
•  Andréia Lopes de Morais
•  Gleyce Pereira Santos
•  Jéssica Sayuri Hassuda Santos
•  Omar Schmildt
•  Marcio Paulo Czepak
•  Ivoney Gontijo
•  Rodrigo Sobreira Alexandre
•  Edilson Romais Schmildt

#### Abstract

The present study had as objective to determine mathematical equations to estimate the leaf area of pear cv. ‘Triunfo’ using linear dimensions of the leaves. For that, 300 healthy leaves of different sizes from each quadrant of plants from the small farm of Boa Vista located in the city of Montanha, at the northern side of the State of Espírito Santo, Brazil were used. The length (L) along the main vein was measured, along with the maximum width (W) of the leaf blade and observed leaf area (OLA), in addition to the product of the length and width (LW) of each leaf. From these measurements models of linear equations of first degree, quadratic and power were adjusted and their respective R2, using OLA as dependent variable and L, W and LW as independent variable. Based on the proposed equations, the data were validated obtaining the estimated leaf area (ELA). The mean of the ELA and OLA were compared by Student t test 5% probability. The mean error (E), the mean absolute error (MAE) and the root mean squared error (RMSE) was also used as validation criterion. The best equation model was defined based on the non-significant values from the comparison of means of ELA and OLA, E, MAE and RMSE values closer to zero and highest R2. The leaf area of pear cv. ‘Triunfo’ can be estimated by the equation ELA = -0.432338 + 0.712862(LW) non-destructively and with a high degree of precision.

• Issn(Print): 1916-9752
• Issn(Onlne): 1916-9760
• Started: 2009
• Frequency: monthly

### Journal Metrics

(The data was calculated based on Google Scholar Citations)

• Google-based Impact Factor (2016): 2.28
• h-index (December 2017): 31
• i10-index (December 2017): 304
• h5-index (December 2017): 22
• h5-median (December 2017): 27