Main Article Content
The objective of this study was to determine the best equation for estimating the leaf area of Acacia mangium Willd. from the linear dimensions of the leaflets of non-destructive form. For this, 476 leaflets of plants belonging to Lajeado farm were collected in the municipality of Ecoporanga, in the north of the State of Espírito Santo, Brazil. From each leaflet was determined the length (L) along the main midrib, the largest width (W), the product of the multiplication between the length and the width (LW) the observed leaf area (OLA). For the modeling, we used 382 leaflets in which OLA was the dependent variable in function of L, W or LW as independent variable, being adjusted the linear models of first degree, quadratic and power. For the validation, the values of L, W and LW of 94 leaflets were replaced in the equations obtained in the modeling thus obtaining the estimated leaf area (ELA). The means of ELA and OLA were compared by Student's t test at 5% probability. . It was also determined the mean absolute error (MAE), the root mean square error (RMSE) and Willmott's index d. In order to select the best equation, the following criteria were used: : not significant of the comparison of the means of ELA and OLA, values of MAE and RMSE with closer to zero and index d closer to one. The power model equation represented by is the most adequate to predict the leaf area of Acacia mangium Willd. quickly and non-destructively.
Vidal WN, Vidal MRR. Botânica organografia: Quadros ilustrados de fanerógamas. Ed.UFV. 2006;4:78-80.
Sacinelli TS, Ribeiro Jr. ES, Dias LE, Lynch LS. Symptoms of nutritional deficiency in seedlings of Acacia holosericea submitted to absence of macronutrients. Revista Árvore. 2004;28: 173-181. Available:http://www.scielo.br/pdf/rarv/v28n2/20981.pdf
Lopes CM, Andrade I, Pedroso V, Martins S. Empirical models for leaf area estimation of the grapevine cv. Jaen. Ciência e Técnica Vitivinícola. 2004;19(2): 61-75. Available:http://www.scielo.mec.pt/pdf/ctv/v19n2/v19n2a02.pdf
Mota CS, Leite HG, Cano MAO.Equations to estimate leaf area of Acrocomia aculeta leaflets. Pesquisa Florestal Brasileira. 2014;34(79):217-224. Available:http://doi.org/10.4336/2014.pfb.34.79.684
Partelli FL, Vieira HD, Detmann E, Campostrini E. Estimative of leaf foliar area of Coffea canephora based on leaf length. Revista Ceres. 2016;53(306):204-210.
Toebe M, Cargnelutti Filho A, Loose LH, Heldwein AB, Zanon AJ. Leaf area of snap bean (Phaseolus vulgaris L.) according to leaf dimensions. Semina: Ciências Agrárias. 2012;33(1):2491-2500.
Carvalho JO, Toebe M, Tartaglio FL, Bandeira CT, Tambara AL. Leaf area estimation from linear measurements in different ages of Crotalaria juncea plants. Anais da Academia Brasileira de Ciências. 2017;89(3):1851-1868. Available:http://doi.org/10.1590/0001-3765201720170077
Oliveira PS, Silva W, Costa AAM, Schmildt ER, Vitória EL. Leaf area estimation in litchi by means of allometric relationships. Revista Brasileira de Fruticultura. 2017;39(Special):1-6. Available:http://doi.org/10.1590/0100-29452017403
Oliveira VS, Hell LR, Santos KTH, Pelegrini HR, Santos JSH, Oliveira GE, Nascimento AL, Santos GP, Schmildt O, Czepak MP, Arantes SD, Alexandre RS, Schmildt ER. Estimation of leaf area of jackfruit through non-destructive method. Journal of Agricultural Science. 2019; 11(6):77-85. Available:https://doi.org/10.5539/jas.v11n6p77
Toebe M, Souza RR, Mello AC, Melo PJ, Segatto A, Castanha AC. Leaf area estimation of squash ‘Brasileirinha’ by leaf dimensions. Ciência Rural. 2019;49(4):1-11.
Leite MLMV, Lucena LRR, Cruz MG, Sá Júnior EH, Simões VJLP. Leaf area estimate of Pennisetum glaucum by linear dimensions. Acta Scientiarum. Animal Sciences. 2019;41:1-7.
Ribeiro AMS, Mundim DA, Mendonça DC, Santos KTH, Santos JSH, Oliveira VS, Santos GP, Rosa LVCA, Santana WR, Schmildt O, Vitória EL, Schmildt ER. Leaf area estimation of garden boldo from linear dimensions. Journal of Agricultural Science. 2019;11(4):461-469.
Pompelli MF, Santos JNB, Santos MA. Estimating leaf area of Jatropha nana through non-destructive allometric models. AIMS Environmental Science. 2019;6(2): 59–76. Available:http://www.aimspress.com/journal/environmental
Alvares CA, Stape JL, Sentelhas PC, Gonçalves JLM, Sparovek G. Köppen's climate classification map for Brazil. Meteorologische Zeitschrift. 2014;22(6): 711-728.
Schindelin J, Rueden CT, Hiner MC, Eliceiri KW. The imagej ecosystem: An open platform for biomedical image analysis. Molecular Reproduction and Development. 2015;82(7-8):518–529. Available:https:// doi.org/10.1002/mrd.22489
Willmott CJ. On the validation of models. Physical Geography. 1981;2(2):184-194.
R Core Team. R: A language and environment for statistical computing. Vienna: R Foundation for Statistical Computing. Vienna, Austria; 2018.
Ferreira EB, Cavalcanti PP, Nogueira DA. Package ‘Exp Des. pt’; 2018.
Levine DM, Stephan DF, Szabat KA. Estatistic for managers using Microsoft Excel: Global edition (8th ed.). London: Person. 2017;728.
Blanco FF, Folegatti MV. Estimation of leaf area for greenhouse cucumber by linear measurements under salinity and grafting. Scientia Agricola. 2005;62(4):305-309.