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      Leaf area estimation from linear measurements in different ages of Crotalaria juncea plants

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          Abstract

          ABSTRACT The goal of this study was to estimate the leaf area of Crotalaria juncea according to the linear dimensions of leaves from different ages. Two experiments were conducted with C. juncea cultivar IAC-KR1, in the 2014/2015 sowing seasons. At 59, 82, 102, 129 days after sowing (DAS) of the first and 61, 80, 92, 104 DAS of the second experiment, 500 leaves were collected, totaling 4,000 leaves. In each leaf, the linear dimensions were measured (length, width, length/width ratio and length × width product) and the specific leaf area was determined through Digimizer and Sigma Scan Pro software, after scanning images. Then, 3,200 leaves were randomly separated to generate mathematical models of leaf area (Y) in function of linear dimension (x), and 800 leaves for the models validation. In C. juncea, the leaf areas determined by Digimizer and Sigma Scan Pro software are identical. The estimation models of leaf area as a function of length × width product showed superior adjustments to those obtained based on the evaluation of only one linear dimension. The linear model Ŷ=0.7390x (R2=0.9849) of the real leaf area (Y) as a function of length × width product (x) is adequate to estimate the C. juncea leaf area.

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          Sistema brasileiro de classificação de solos

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            On the validation of models

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              Allometric models for non-destructive leaf area estimation in coffee (Coffea arabicaandCoffea canephora)

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                Author and article information

                Contributors
                Role: ND
                Role: ND
                Role: ND
                Role: ND
                Role: ND
                Journal
                aabc
                Anais da Academia Brasileira de Ciências
                An. Acad. Bras. Ciênc.
                Academia Brasileira de Ciências (Rio de Janeiro, RJ, Brazil )
                0001-3765
                1678-2690
                August 2017
                : 89
                : 3
                : 1851-1868
                Affiliations
                [2] Westphalen Rio Grande do Sul orgnameUniversidade Federal de Santa Maria orgdiv1Departamento de Ciências Agronômicas e Ambientais Brazil
                [3] Itaqui Rio Grande do Sul orgnameUniversidade Federal do Pampa Brazil
                [1] Capão do Leão Rio Grande do Sul orgnameUniversidade Federal de Pelotas orgdiv1Departamento de Botânica orgdiv2Programa de Pós-Graduação em Fisiologia Vegetal Brazil
                [4] Santa Maria Rio Grande do Sul orgnameUniversidade Federal de Santa Maria orgdiv1Departamento de Fitotecnia orgdiv2Programa de Pós-Graduação em Agronomia Brazil
                Article
                S0001-37652017000401851
                10.1590/0001-3765201720170077
                28876397
                d36ec967-1a08-482e-a3a5-feeefad26360

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                History
                : 03 February 2017
                : 10 April 2017
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 37, Pages: 18
                Product

                SciELO Brazil


                non-destructive method,image processing,mathematical models,model validation

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