Youkhana Adel H, Ogoshi Richard M, Kiniry James R, Meki Manyowa N, Nakahata Mae H, Crow Susan E
Department of Tropical Plant and Soil Sciences, University of Hawaii at Manoa, HonoluluHI, USA.
Grassland Soil and Water Research Laboratory, United States Department of Agriculture, Agricultural Research Service, TempleTX, USA.
Front Plant Sci. 2017 May 2;8:650. doi: 10.3389/fpls.2017.00650. eCollection 2017.
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 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, ( = 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 grass biomass and C stock during decision-making for land management and as an environmental sustainability indicator within a renewable energy system.
生物质是一种很有前景的可再生能源选择,通过减少温室气体向大气中的净通量,为化石资源提供了一种更具环境可持续性的替代方案。然而,对于目前在夏威夷以及其他亚热带和热带地区被视为潜在生物能源原料的热带多年生碳四草本植物,尚未开发出能够无损预测地上生物量(AGB)、生物量碳(C)储量的异速生长模型。本研究的目的是建立最优的异速生长关系和特定地点模型,以预测在可再生能源种植实践下象草、能源甘蔗和甘蔗的AGB、生物量碳储量,并针对来自环境差异很大的地点生成的独立数据集验证这些特定地点模型。利用夏威夷毛伊岛一个低海拔田地的数据,为每个物种开发了几个异速生长模型。对于象草、能源甘蔗和甘蔗,一个简单的包含茎直径(D)的幂模型与AGB和生物量碳储量的相关性最好(分别为 = 0.98、0.96和0.97)。然后,利用从一个环境梯度上的独立田地收集的数据对这些模型进行测试。对于所有作物,这些模型在茎直径较小的植株中高估了AGB,但在茎直径较大的植株中低估了AGB。与颈部高度(从基部切口到最近露出的叶颈部的高度)模型相比,使用茎直径的模型在生物量预测方面表现更好,后者的验证性能较弱。尽管茎直径模型表现更好,然而,所有作物的均方误差(MSE)-系统误差占MSE的比例在23%至43%之间。尽管这些是灌溉系统,但模型系数与降雨量之间存在很强的关系;这表明在水资源有限的地区,可以使用一个简单的针对降雨量的特定地点系数调节器来减少系统误差。这些异速生长方程为热带地区的农民提供了一种工具,以便在土地管理决策过程中估算多年生碳四草本植物的生物量和碳储量,并作为可再生能源系统中的环境可持续性指标。