We have introduced the use of multivariate NMR analysis in the development of accurate and robust prediction models, potentially arising from a correlation between soluble metabolite profiles and cell wall composition, for the determination of hemicellulose, cellulose and lignin contents in 8 species of greenhouse crop residues. The present paper demonstrates that discriminant buckets coming from a PLS-DA model in combination with linear models provide a useful and rapid tool for the determination of cell wall composition of these plant wastes. Regularized linear regression methods have also been applied to avoid overfitting, producing improved models specifically for lignin and cellulose determinations. The predictive models are also presented in a desktop application available at http://www2.ual.es/NMRMBC/solutions. To verify the rationality and reliability of the models, control experiments following generally accepted protocols have been performed and compared to our predicted values.

中文翻译：

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多变量核磁共振分析在温室作物残留物中半纤维素、纤维素和木质素含量预测中的应用

我们介绍了多变量 NMR 分析在开发准确和稳健的预测模型中的使用，这可能源于可溶性代谢物谱和细胞壁组成之间的相关性，用于测定 8 种温室作物残留物中的半纤维素、纤维素和木质素含量. 本论文表明，来自 PLS-DA 模型的判别桶与线性模型相结合，为确定这些植物废物的细胞壁组成提供了一种有用且快速的工具。还应用了正则化线性回归方法来避免过度拟合，从而产生专门用于木质素和纤维素测定的改进模型。预测模型也在桌面应用程序中提供，网址为 http://www2.ual.es/NMRMBC/solutions。