دورية أكاديمية
Exploratory analysis of nutrient concentrations in Eucalyptus leaf color patterns
| العنوان: | Exploratory analysis of nutrient concentrations in Eucalyptus leaf color patterns |
|---|---|
| المؤلفون: | Oliveira, Luiz Felipe Ramalho de, Santana, Reynaldo Campos |
| المصدر: | Advances in Forestry Science; v. 7 n. 2 (2020): Advances in Forestry Science; 973-979 ; Advances in Forestry Science; Vol. 7 No. 2 (2020): Advances in Forestry Science; 973-979 ; Advances in Forestry Science; Vol. 7 Núm. 2 (2020): Advances in Forestry Science; 973-979 ; 2357-8181 ; 2359-6570 ; 10.34062/afs.v7i2 |
| بيانات النشر: | Universidade Federal de Mato Grosso |
| سنة النشر: | 2020 |
| المجموعة: | Portal de Revistas Científicas da UFMT (Universidade Federal de Mato Grosso) |
| مصطلحات موضوعية: | Leaf senescence, Remobilization, Munsell color, Visual diagnosis |
| الوصف: | The aim of this study was to evaluate the use of leaf color pattern to analyze leaf nutrient concentrations in Eucalyptus and to establish relationships between color patterns and leaf nutrient concentrations. The study was carried out in Eucalyptus stands at 25 months old using three leaves from the lower of tree crowns classified into five color patterns of Munsell color charts for plant tissues. The principal component analyses and the self-organizing maps were used to aid in the classification of samples in leaf color patterns. Subsequently, the k-means cluster algorithm was performed. In principal component analysis, the 7.5 GY 8/8 leaf color pattern stood out from the others and it was mainly influenced by nitrogen, phosphorous, copper, and potassium concentrations. The samples of 7.5 GY 8/4 leaf color pattern did not present a great nitrogen, phosphorous, sulfur, copper and potassium concentrations as the 7.5 GY 8/8 neither a great manganese, calcium, boron, zinc and iron concentrations as others leaf color patterns. The self-organizing map provides a greater proximity between the 7.5 GY 8/8 and 7.5 GY 8/4 leaf color patterns and the others leaf color patterns were randomly distributed in the U-matrix. Although the k-means algorithm presented two clusters in both analyses, the self-organizing map presented a slight superiority than principal component analysis. Using leaf color patterns was possible to infer about leaf nutrient concentrations in Eucalyptus. Both methods were able to distinguish only the healthy leaves 7.5 GY 8/8 from those whose were in the leaf senescence process. |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | application/pdf |
| اللغة: | English |
| العلاقة: | https://periodicoscientificos.ufmt.br/ojs/index.php/afor/article/view/8647/pdfTest; https://periodicoscientificos.ufmt.br/ojs/index.php/afor/article/view/8647Test |
| الإتاحة: | https://doi.org/10.34062/afs.v7i2Test https://periodicoscientificos.ufmt.br/ojs/index.php/afor/article/view/8647Test |
| حقوق: | Copyright (c) 2020 Advances in Forestry Science |
| رقم الانضمام: | edsbas.6FD95681 |
| قاعدة البيانات: | BASE |
| الوصف غير متاح. |