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Allometric Models for Predicting Aboveground Biomass and Carbon Stock of Tropical Perennial C(4) Grasses in Hawaii

Biomass is a promising renewable energy option that provides a more environmentally sustainable alternative to fossil resources by reducing the net flux of greenhouse gasses to the atmosphere. Yet, allometric models that allow the prediction of aboveground biomass (AGB), biomass carbon (C) stock non...

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Autores principales: Youkhana, Adel H., Ogoshi, Richard M., Kiniry, James R., Meki, Manyowa N., Nakahata, Mae H., Crow, Susan E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5411447/
https://www.ncbi.nlm.nih.gov/pubmed/28512463
http://dx.doi.org/10.3389/fpls.2017.00650
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author Youkhana, Adel H.
Ogoshi, Richard M.
Kiniry, James R.
Meki, Manyowa N.
Nakahata, Mae H.
Crow, Susan E.
author_facet Youkhana, Adel H.
Ogoshi, Richard M.
Kiniry, James R.
Meki, Manyowa N.
Nakahata, Mae H.
Crow, Susan E.
author_sort Youkhana, Adel H.
collection PubMed
description Biomass is a promising renewable energy option that provides a more environmentally sustainable alternative to fossil resources by reducing the net flux of greenhouse gasses to the atmosphere. Yet, allometric models that allow the prediction of aboveground biomass (AGB), biomass carbon (C) stock non-destructively have not yet been developed for tropical perennial C(4) grasses currently under consideration as potential bioenergy feedstock in Hawaii and other subtropical and tropical locations. The objectives of this study were to develop optimal allometric relationships and site-specific models to predict AGB, biomass C stock of napiergrass, energycane, and sugarcane under cultivation practices for renewable energy and validate these site-specific models against independent data sets generated from sites with widely different environments. Several allometric models were developed for each species from data at a low elevation field on the island of Maui, Hawaii. A simple power model with stalk diameter (D) was best related to AGB and biomass C stock for napiergrass, energycane, and sugarcane, (R(2) = 0.98, 0.96, and 0.97, respectively). The models were then tested against data collected from independent fields across an environmental gradient. For all crops, the models over-predicted AGB in plants with lower stalk D, but AGB was under-predicted in plants with higher stalk D. The models using stalk D were better for biomass prediction compared to dewlap H (Height from the base cut to most recently exposed leaf dewlap) models, which showed weak validation performance. Although stalk D model performed better, however, the mean square error (MSE)-systematic was ranged from 23 to 43 % of MSE for all crops. A strong relationship between model coefficient and rainfall was existed, although these were irrigated systems; suggesting a simple site-specific coefficient modulator for rainfall to reduce systematic errors in water-limited areas. These allometric equations provide a tool for farmers in the tropics to estimate perennial C(4) grass biomass and C stock during decision-making for land management and as an environmental sustainability indicator within a renewable energy system.
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spelling pubmed-54114472017-05-16 Allometric Models for Predicting Aboveground Biomass and Carbon Stock of Tropical Perennial C(4) Grasses in Hawaii Youkhana, Adel H. Ogoshi, Richard M. Kiniry, James R. Meki, Manyowa N. Nakahata, Mae H. Crow, Susan E. Front Plant Sci Plant Science Biomass is a promising renewable energy option that provides a more environmentally sustainable alternative to fossil resources by reducing the net flux of greenhouse gasses to the atmosphere. Yet, allometric models that allow the prediction of aboveground biomass (AGB), biomass carbon (C) stock non-destructively have not yet been developed for tropical perennial C(4) grasses currently under consideration as potential bioenergy feedstock in Hawaii and other subtropical and tropical locations. The objectives of this study were to develop optimal allometric relationships and site-specific models to predict AGB, biomass C stock of napiergrass, energycane, and sugarcane under cultivation practices for renewable energy and validate these site-specific models against independent data sets generated from sites with widely different environments. Several allometric models were developed for each species from data at a low elevation field on the island of Maui, Hawaii. A simple power model with stalk diameter (D) was best related to AGB and biomass C stock for napiergrass, energycane, and sugarcane, (R(2) = 0.98, 0.96, and 0.97, respectively). The models were then tested against data collected from independent fields across an environmental gradient. For all crops, the models over-predicted AGB in plants with lower stalk D, but AGB was under-predicted in plants with higher stalk D. The models using stalk D were better for biomass prediction compared to dewlap H (Height from the base cut to most recently exposed leaf dewlap) models, which showed weak validation performance. Although stalk D model performed better, however, the mean square error (MSE)-systematic was ranged from 23 to 43 % of MSE for all crops. A strong relationship between model coefficient and rainfall was existed, although these were irrigated systems; suggesting a simple site-specific coefficient modulator for rainfall to reduce systematic errors in water-limited areas. These allometric equations provide a tool for farmers in the tropics to estimate perennial C(4) grass biomass and C stock during decision-making for land management and as an environmental sustainability indicator within a renewable energy system. Frontiers Media S.A. 2017-05-02 /pmc/articles/PMC5411447/ /pubmed/28512463 http://dx.doi.org/10.3389/fpls.2017.00650 Text en Copyright © 2017 Youkhana, Ogoshi, Kiniry, Meki, Nakahata and Crow. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Youkhana, Adel H.
Ogoshi, Richard M.
Kiniry, James R.
Meki, Manyowa N.
Nakahata, Mae H.
Crow, Susan E.
Allometric Models for Predicting Aboveground Biomass and Carbon Stock of Tropical Perennial C(4) Grasses in Hawaii
title Allometric Models for Predicting Aboveground Biomass and Carbon Stock of Tropical Perennial C(4) Grasses in Hawaii
title_full Allometric Models for Predicting Aboveground Biomass and Carbon Stock of Tropical Perennial C(4) Grasses in Hawaii
title_fullStr Allometric Models for Predicting Aboveground Biomass and Carbon Stock of Tropical Perennial C(4) Grasses in Hawaii
title_full_unstemmed Allometric Models for Predicting Aboveground Biomass and Carbon Stock of Tropical Perennial C(4) Grasses in Hawaii
title_short Allometric Models for Predicting Aboveground Biomass and Carbon Stock of Tropical Perennial C(4) Grasses in Hawaii
title_sort allometric models for predicting aboveground biomass and carbon stock of tropical perennial c(4) grasses in hawaii
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5411447/
https://www.ncbi.nlm.nih.gov/pubmed/28512463
http://dx.doi.org/10.3389/fpls.2017.00650
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