Artículos de revistas
Leaf Blade Area Of Different Plants Estimated By Linear And Dry Matter Measures, Calibrated With The Imagej Software [Área Do Limbo Foliar De Diferentes Plantas Estimada Por Medidas Lineares E Matéria Seca, Calibradas Com O Software Imagej]
Registro en:
Interciencia. Interciencia Association, v. 40, n. 8, p. 570 - 575, 2015.
3781844
2-s2.0-84947743375
Institución
Resumen
Much of dry matter accumulation by plants comes from photosynthesis in the leaves. Therefore, analysis of leaf growth is useful for plant study under different climatic and soil conditions. Leaf area can be estimated with different methods and equipments, some of which are costly and time consuming, ineffective for common research conditions. However, there can be alternatives, economic and fast, through the use of imaging software, free or licensed. Thus, we aimed to estimate the area of the leaf blade of different plants based on linear and dry weight measures, calibrated with the free software ImageJ. The leaves of cotton plants (Gossypium hirsutum L) var. IMACD 6001, cashew (Anacardium occidentale L) var. FAGA 10, soybean (Glycine max L) var. M-SOY 7639RR, and corn (Zea mays L) var. Penta TL were collected from the lower third, middle and top in different phenological phases. It was found that images with a resolution of at least 7.2 megapixels can be used to estimate the actual leaf blade area, processed with the ImageJ software till 324cm2. For larger surfaces, we recommend testing with higher resolution camera, or cut a large sheet into pieces up to 324cm2. We observed a good agreement in the estimation of the leaf blade area based on linear and dry mass measures and, therefore, it is recommended to estimate leaf area leaves with damaged pieces or measures from several samples of leaves collected at the field based on the dry weight of the leaves, as it is operationally viable. 40 8 570 575 Adami, M., Hasten reiter, F.A., Flumignan, D.L., De Faria, R.T., Estimativa de área de folíolos de soja usando imagens digitais e dimensões foliares (2008) Bragantia, 67, pp. 1053-1058 Bland, J.M., Altman, D.G., Statistical methods for assessing agreement between two methods of clinical measurement (1986) Lancet, 8, pp. 307-310 Cairo, P.A.R., Oliveira, L.E.M., Mesquista, A.C., (2008) Análise de Crescimento de Plantas, 72p. , Edições UESB: Vitória da Conquista, Brasil De Camargo, A.P., Sentelhas, P.C., Avaliação do desempenho de diferentes métodos de estimativa da evapot ranspiração potencial no estado de São Paulo, Brasil (1997) Rev. Bras. Agrometeorol., 5, pp. 89-97 (2006) Sistema Brasileiro de Classificação de Solo., 306p. , 2a ed. Embrapa Solos. Empresa Brasileira de Pesquisa Agrope cuária. Rio de Janei ro, Brasil (2014) Laboratório de Imagens., , http://labimagem.cnpdia.embrapa.br, Embrapa Instrumentação Agropecuária. Empresa Brasileira de Pesquisa Agropecuária São Paulo, Brasil Hair, J.F., Jr., Anderson, R.E., Tatham, R.L., Black, W.C., (2005) Análise Multivariada de Dados, 593p. , 5a ed. Bookman. Porto Alegre, Brasil (2014) Image Processing and Analyse in Java., , http://rsbweb.nih.gov/ij/ Kerbauy, G.B., (2012) Fisiologia Vegetal, 446p. , 2a ed. Koogman. Guanabara, Brasil Larson, R., Farber, B., (2010) Estatística Aplicada., 656p. , 4a ed. Pearson. São Paulo, Brasil Laurecen, T.A., Chromy, B.A., QuickPALM: 3D real-time photoactivation nanoscopy image processing in ImageJ (2010) Nature Meth., 7, pp. 339-340 Martin, T.N., Marchese, J.A., Souza, A.N.F., Curti, G.L., Fogolari, H., Cunha, V.S., Uso do software ImageJ na estimativa de área foliar para a cultura do feijão (2013) Interciencia, 38, pp. 843-848 Naghettini, M., Pinto, E.J.A., (2007) Hidrologia Estatística, 552p. , Serviço Ecológico do Brasil. Secretaria de Geologia, Mineração e Transformação Mineral. Belo Horizonte, Brasil (2014) Exact Graphs and Data Analysis, , www.sigmaplot.com/, Vers. 12.5 Vidal, W.N., Vidal, M.R.R., (2007) Botânica Organografia: Quadros Sinóticos Ilustrados de Fanerógamos, 124p. , 4a ed. Editora UFV. Viçosa, Brasil