期刊
MICROCHEMICAL JOURNAL
卷 134, 期 -, 页码 125-130出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.microc.2017.05.020
关键词
Biofuel; Multivariate calibration; Bioenergy crop; Partial least squares regression
资金
- Fapemig [3013/2014]
Sweet sorghum is a very robust crop which has the potential to be used in ethanol production due to its high fermentable sugar content present in its stem juice, very similar to sugarcane. Therefore, for breeding purposes it is relevant to analyze sugar composition in the juice to characterize sweet sorghum genotypes and their period of industrial utilization within different environments for maximum ethanol yield. In this work we developed a rapid, low cost and efficient method to determine the profile of sugars (sucrose, glucose and fructose) in sorghum juice by near infrared spectroscopy and partial least square regression, and validation of the method was performed according to the high-performance liquid chromatography method. Developed models provided root mean square error of prediction of 4,1 and 0.6 mg.mL(-1) and ratio performance deviations of 8, 5 and 5 for sucrose, glucose and fructose, respectively. Relative standard deviations of three sweet sorghum juice samples were reported with content variation (low, medium and high) 02, 03, 0.8% for sucrose; 1, 2, 2% for glucose; 1, 2, 3% for fructose. Sugar profile is an asset for crop breeders to take decisions for the development of more productive cultivars and higher sugar content. (C) 2017 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据