Institute of Food Research, Norwich Research Park, Colney, Norwich, NR4 7UA UK.
John Innes Centre, Norwich Research Park, Colney, Norwich, NR4 7UH UK ; Present address: Department of Biology, University of York, Wentworth Way, Heslington, York, YO10 5DD UK.
Biotechnol Biofuels. 2014 Aug 20;7(1):121. doi: 10.1186/s13068-014-0121-y. eCollection 2014.
Wheat straw is an attractive substrate for second generation ethanol production because it will complement and augment wheat production rather than competing with food production. However, like other sources of lignocellulosic biomass, even from a single species, it is heterogeneous in nature due to the different tissues and cell types, and this has implications for saccharification efficiency. The aim of this study has been to use Fourier transform infrared (FTIR) spectroscopy and Partial least squares (PLS) modelling to rapidly screen wheat cultivars for the levels of component tissues, the carbohydrate composition and lignin content, and the levels of simple cross-linking phenolics such as ferulic and diferulic acids.
FTIR spectroscopy and PLS modelling was used to analyze the tissue and chemical composition of wheat straw biomass. Predictive models were developed to evaluate the variability in the concentrations of the cell wall sugars, cell wall phenolics and acid-insoluble lignin. Models for the main sugars, phenolics and lignin were validated and then used to evaluate the variation in total biomass composition across 90 cultivars of wheat grown over two seasons.
Whilst carbohydrate and lignin components varied across the varieties, this mainly reflected differences in the ratios of the component tissues rather than differences in the composition of those tissues. Further analysis indicated that on a mol% basis, relative levels of sugars within the tissues varied to only a small degree. There were no clear associations between simple phenolics and tissues. The results provide a basis for improving biomass quality for biofuels production through selection of cultivars with appropriate tissue ratios.
小麦秸秆是第二代乙醇生产的一种有吸引力的底物,因为它将补充和增加小麦产量,而不是与粮食生产竞争。然而,与其他木质纤维素生物质来源一样,即使来自单一物种,由于不同的组织和细胞类型,它的性质也存在异质性,这对糖化效率有影响。本研究的目的是使用傅里叶变换红外(FTIR)光谱和偏最小二乘(PLS)建模来快速筛选小麦品种,以确定其成分组织、碳水化合物组成和木质素含量水平,以及简单的交联酚类物质(如阿魏酸和二阿魏酸)的水平。
使用 FTIR 光谱和 PLS 建模来分析小麦秸秆生物量的组织和化学成分。建立了预测模型来评估细胞壁糖、细胞壁酚类物质和酸不溶性木质素浓度的变化。主要糖、酚类物质和木质素模型得到了验证,然后用于评估两个季节种植的 90 个小麦品种的总生物质组成的变化。
虽然碳水化合物和木质素成分在品种之间有所不同,但这主要反映了成分组织的比例差异,而不是这些组织的组成差异。进一步分析表明,在组织内,糖的相对水平仅略有变化。简单酚类物质与组织之间没有明显的关联。研究结果为通过选择具有适当组织比例的品种来提高生物量质量以用于生物燃料生产提供了依据。