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Assessment of a monthly data structure for growth and yield projections from early to harvest age in hybrid eucalypt stands

Whole-stand Models (WSM) have always been fitted with permanent plot data organised in a sequential age-matched database, i.e., i and i+1, where i = 1, 2, ... N plot measurements. The objectives of this study were (1) to evaluate the statistical efficiency of a monthly distributed data structure by...

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Main Authors:	Casas, Gianmarco Goycochea, Soares, Carlos Pedro Boechat, Oliveira, Marcio Leles Romarco, Binoti, Daniel Henrique Breda, Fardin, Leonardo Pereira, Limeira, Mathaus Messias Coimbra, Ismail, Zool Hilmi, Silva, Antonilmar Araujo Lopes, Leite, Helio Garcia
Format:	Article
Language:	English
Published:	UPM Press 2023
Subjects:	TA Engineering (General). Civil engineering (General)
Online Access:	http://eprints.utm.my/106197/1/ZoolHilmiIsmail2023_AssessmentofaMonthlyDataStructureforGrowth.pdf http://eprints.utm.my/106197/ http://dx.doi.org/10.47836/pjtas.46.4.04
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spelling	my.utm.1061972024-06-20T01:49:44Z http://eprints.utm.my/106197/ Assessment of a monthly data structure for growth and yield projections from early to harvest age in hybrid eucalypt stands Casas, Gianmarco Goycochea Soares, Carlos Pedro Boechat Oliveira, Marcio Leles Romarco Binoti, Daniel Henrique Breda Fardin, Leonardo Pereira Limeira, Mathaus Messias Coimbra Ismail, Zool Hilmi Silva, Antonilmar Araujo Lopes Leite, Helio Garcia TA Engineering (General). Civil engineering (General) Whole-stand Models (WSM) have always been fitted with permanent plot data organised in a sequential age-matched database, i.e., i and i+1, where i = 1, 2, ... N plot measurements. The objectives of this study were (1) to evaluate the statistical efficiency of a monthly distributed data structure by fitting the models of Clutter (1963), Buckman (1962) in the version modified by A. L. da Silva et al. (2006), and deep learning, and (2) to evaluate the possibility of gaining accuracy in yield projections made from an early age to harvest age of eucalypt stands. Three alternatives for organizing the data were analyzed. The first is with data paired in sequential measurement ages, i.e., i and i+1, where i = 1, 2, ... N plot measurements. In the second, all possible measurement intervals for each plot were considered, i.e., i, i+1; i, i+2; ...; i, N; i+1, i+2; ..., N-1, N. The third has data paired by month (j), always with an interval of one month, i.e., j, j+1; j+1, j+2; j+M-1, M, where M is the stand age of the plot measurement in months. This study shows that the accuracy and consistency of the projections depend on the organization of the monthly distributed data, except for the Clutter model. A better alternative to increasing the statistical assumptions of the forecast from early to harvest age is based on a monthly distributed data structure using a deep learning method. UPM Press 2023-11 Article PeerReviewed application/pdf en http://eprints.utm.my/106197/1/ZoolHilmiIsmail2023_AssessmentofaMonthlyDataStructureforGrowth.pdf Casas, Gianmarco Goycochea and Soares, Carlos Pedro Boechat and Oliveira, Marcio Leles Romarco and Binoti, Daniel Henrique Breda and Fardin, Leonardo Pereira and Limeira, Mathaus Messias Coimbra and Ismail, Zool Hilmi and Silva, Antonilmar Araujo Lopes and Leite, Helio Garcia (2023) Assessment of a monthly data structure for growth and yield projections from early to harvest age in hybrid eucalypt stands. Pertanika Journal of Tropical Agricultural Science, 46 (4). pp. 1127-1150. ISSN 1511-3701 http://dx.doi.org/10.47836/pjtas.46.4.04 DOI:10.47836/pjtas.46.4.04
institution	Universiti Teknologi Malaysia
building	UTM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Malaysia
content_source	UTM Institutional Repository
url_provider	http://eprints.utm.my/
language	English
topic	TA Engineering (General). Civil engineering (General)
spellingShingle	TA Engineering (General). Civil engineering (General) Casas, Gianmarco Goycochea Soares, Carlos Pedro Boechat Oliveira, Marcio Leles Romarco Binoti, Daniel Henrique Breda Fardin, Leonardo Pereira Limeira, Mathaus Messias Coimbra Ismail, Zool Hilmi Silva, Antonilmar Araujo Lopes Leite, Helio Garcia Assessment of a monthly data structure for growth and yield projections from early to harvest age in hybrid eucalypt stands
description	Whole-stand Models (WSM) have always been fitted with permanent plot data organised in a sequential age-matched database, i.e., i and i+1, where i = 1, 2, ... N plot measurements. The objectives of this study were (1) to evaluate the statistical efficiency of a monthly distributed data structure by fitting the models of Clutter (1963), Buckman (1962) in the version modified by A. L. da Silva et al. (2006), and deep learning, and (2) to evaluate the possibility of gaining accuracy in yield projections made from an early age to harvest age of eucalypt stands. Three alternatives for organizing the data were analyzed. The first is with data paired in sequential measurement ages, i.e., i and i+1, where i = 1, 2, ... N plot measurements. In the second, all possible measurement intervals for each plot were considered, i.e., i, i+1; i, i+2; ...; i, N; i+1, i+2; ..., N-1, N. The third has data paired by month (j), always with an interval of one month, i.e., j, j+1; j+1, j+2; j+M-1, M, where M is the stand age of the plot measurement in months. This study shows that the accuracy and consistency of the projections depend on the organization of the monthly distributed data, except for the Clutter model. A better alternative to increasing the statistical assumptions of the forecast from early to harvest age is based on a monthly distributed data structure using a deep learning method.
format	Article
author	Casas, Gianmarco Goycochea Soares, Carlos Pedro Boechat Oliveira, Marcio Leles Romarco Binoti, Daniel Henrique Breda Fardin, Leonardo Pereira Limeira, Mathaus Messias Coimbra Ismail, Zool Hilmi Silva, Antonilmar Araujo Lopes Leite, Helio Garcia
author_facet	Casas, Gianmarco Goycochea Soares, Carlos Pedro Boechat Oliveira, Marcio Leles Romarco Binoti, Daniel Henrique Breda Fardin, Leonardo Pereira Limeira, Mathaus Messias Coimbra Ismail, Zool Hilmi Silva, Antonilmar Araujo Lopes Leite, Helio Garcia
author_sort	Casas, Gianmarco Goycochea
title	Assessment of a monthly data structure for growth and yield projections from early to harvest age in hybrid eucalypt stands
title_short	Assessment of a monthly data structure for growth and yield projections from early to harvest age in hybrid eucalypt stands
title_full	Assessment of a monthly data structure for growth and yield projections from early to harvest age in hybrid eucalypt stands
title_fullStr	Assessment of a monthly data structure for growth and yield projections from early to harvest age in hybrid eucalypt stands
title_full_unstemmed	Assessment of a monthly data structure for growth and yield projections from early to harvest age in hybrid eucalypt stands
title_sort	assessment of a monthly data structure for growth and yield projections from early to harvest age in hybrid eucalypt stands
publisher	UPM Press
publishDate	2023
url	http://eprints.utm.my/106197/1/ZoolHilmiIsmail2023_AssessmentofaMonthlyDataStructureforGrowth.pdf http://eprints.utm.my/106197/ http://dx.doi.org/10.47836/pjtas.46.4.04
_version_	1802977239235559424
score	13.211869

Assessment of a monthly data structure for growth and yield projections from early to harvest age in hybrid eucalypt stands

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