Non-destructive and Destructive Methods to Determine the Leaf Area of Zucchini

Adriano Bicioni Pacheco, Jéssica Garcia Nascimento, Larissa Brêtas Moura, Tárcio Rocha Lopes, Sergio Nascimento Duarte, Rubens Duarte Coelho, Patricia Angélica Alves Marques

Abstract


Leaf area estimation is a very important indicator in studies related to plant anatomy, morphology and physiology, and in many cases, it is a fundamental criterion to understand plant response to input conditions. Although there are leaf area prediction models have been produced for some plant species, a leaf area estimation model has not yet been developed for the zucchini. The objective of this paper was to determine the leaf area based on destructive and non-destructive methods for zucchini. The accuracy of measurement methods was evaluated and compared to determinations of the leaf area by the scanning integration method (LICOR equipment LI 3100C), considered as standard procedure. Non-destructive methods consisted of digital photography and measurement of leaf dimensions (width and length) based on ImageJ software. The destructive methods used were a) leaf area integrator LI-3100C, b) determination of leaf mass and c) weighing of leaf discs punched from the leaves. According to statistical parameters that evaluate the performance of the analyzed methods: determination coefficient (R2), Pearson (r) correlation coefficient, Willmott agreement index (d) and Camargo and Sentelhas performance index (c) the parameters presented values higher than 0.8820, classifying the methods as very good, whereas the modeling efficiency index (NSE) and the percentage of bias (PBIAS) also classified the methods as very good (0.87≤NSE≤0.99; -4.80≤PBIAS≤1.40), except the ImageJ method without correction (NSE=0.77; PBIAS = -22.70).


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DOI: https://doi.org/10.5296/jas.v8i3.16299

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Copyright (c) 2020 Adriano Bicioni Pacheco, Jéssica Garcia Nascimento, Larissa Brêtas Moura, Tárcio Rocha Lopes, Sergio Nascimento Duarte, Rubens Duarte Coelho, Patricia Angélica Alves Marques

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Journal of Agricultural Studies   ISSN 2166-0379

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