Leaf area estimation of cassava from linear dimensions
ABSTRACT The objective of this study was to determine predictor models of leaf area of cassava from linear leaf measurements. The experiment was carried out in greenhouse in the municipality of Botucatu, São Paulo state, Brazil. The stem cuttings with 5-7 nodes of the cultivar IAC 576-70 were plante...
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2017-08-01
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doaj-1d9ab6836f134268bef81e134d6af9fe2020-11-24T22:33:25ZengAcademia Brasileira de CiênciasAnais da Academia Brasileira de Ciências1678-26902017-08-01010.1590/0001-376520172016-0475S0001-37652017005019107Leaf area estimation of cassava from linear dimensionsSAMARA ZANETTILAÍS F.M. PEREIRAMARIA MÁRCIA P. SARTORIMARCELO A. SILVAABSTRACT The objective of this study was to determine predictor models of leaf area of cassava from linear leaf measurements. The experiment was carried out in greenhouse in the municipality of Botucatu, São Paulo state, Brazil. The stem cuttings with 5-7 nodes of the cultivar IAC 576-70 were planted in boxes filled with about 320 liters of soil, keeping soil moisture at field capacity, monitored by puncturing tensiometers. At 80 days after planting, 140 leaves were randomly collected from the top, middle third and base of cassava plants. We evaluated the length and width of the central lobe of leaves, number of lobes and leaf area. The measurements of leaf areas were correlated with the length and width of the central lobe and the number of lobes of the leaves, and adjusted to polynomial and multiple regression models. The linear function that used the length of the central lobe LA = -69.91114 + 15.06462L and linear multiple functions LA = -69.9188 + 15.5102L + 0.0197726K - 0.0768998J or LA = -69.9346 + 15.0106L + 0.188931K - 0.0264323H are suitable models to estimate leaf area of cassava cultivar IAC 576-70.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652017005019107&lng=en&tlng=enManihot esculenta Crantzleaf biometricsstatistical modelsmultiple regression |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
SAMARA ZANETTI LAÍS F.M. PEREIRA MARIA MÁRCIA P. SARTORI MARCELO A. SILVA |
spellingShingle |
SAMARA ZANETTI LAÍS F.M. PEREIRA MARIA MÁRCIA P. SARTORI MARCELO A. SILVA Leaf area estimation of cassava from linear dimensions Anais da Academia Brasileira de Ciências Manihot esculenta Crantz leaf biometrics statistical models multiple regression |
author_facet |
SAMARA ZANETTI LAÍS F.M. PEREIRA MARIA MÁRCIA P. SARTORI MARCELO A. SILVA |
author_sort |
SAMARA ZANETTI |
title |
Leaf area estimation of cassava from linear dimensions |
title_short |
Leaf area estimation of cassava from linear dimensions |
title_full |
Leaf area estimation of cassava from linear dimensions |
title_fullStr |
Leaf area estimation of cassava from linear dimensions |
title_full_unstemmed |
Leaf area estimation of cassava from linear dimensions |
title_sort |
leaf area estimation of cassava from linear dimensions |
publisher |
Academia Brasileira de Ciências |
series |
Anais da Academia Brasileira de Ciências |
issn |
1678-2690 |
publishDate |
2017-08-01 |
description |
ABSTRACT The objective of this study was to determine predictor models of leaf area of cassava from linear leaf measurements. The experiment was carried out in greenhouse in the municipality of Botucatu, São Paulo state, Brazil. The stem cuttings with 5-7 nodes of the cultivar IAC 576-70 were planted in boxes filled with about 320 liters of soil, keeping soil moisture at field capacity, monitored by puncturing tensiometers. At 80 days after planting, 140 leaves were randomly collected from the top, middle third and base of cassava plants. We evaluated the length and width of the central lobe of leaves, number of lobes and leaf area. The measurements of leaf areas were correlated with the length and width of the central lobe and the number of lobes of the leaves, and adjusted to polynomial and multiple regression models. The linear function that used the length of the central lobe LA = -69.91114 + 15.06462L and linear multiple functions LA = -69.9188 + 15.5102L + 0.0197726K - 0.0768998J or LA = -69.9346 + 15.0106L + 0.188931K - 0.0264323H are suitable models to estimate leaf area of cassava cultivar IAC 576-70. |
topic |
Manihot esculenta Crantz leaf biometrics statistical models multiple regression |
url |
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0001-37652017005019107&lng=en&tlng=en |
work_keys_str_mv |
AT samarazanetti leafareaestimationofcassavafromlineardimensions AT laisfmpereira leafareaestimationofcassavafromlineardimensions AT mariamarciapsartori leafareaestimationofcassavafromlineardimensions AT marceloasilva leafareaestimationofcassavafromlineardimensions |
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