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Leaf area estimation of cassava from linear dimensions

Overview of attention for article published in Anais da Academia Brasileira de Ciências, September 2017
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Title
Leaf area estimation of cassava from linear dimensions
Published in
Anais da Academia Brasileira de Ciências, September 2017
DOI 10.1590/0001-376520172016-0475
Pubmed ID
Authors

Samara Zanetti, Laís F M Pereira, Maria Márcia P Sartori, Marcelo A Silva

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.

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The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 4 18%
Researcher 3 14%
Student > Master 2 9%
Professor 2 9%
Unspecified 1 5%
Other 2 9%
Unknown 8 36%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 27%
Computer Science 2 9%
Mathematics 1 5%
Unspecified 1 5%
Environmental Science 1 5%
Other 1 5%
Unknown 10 45%