The output of metabolomics relies to a great extent upon the methods and instrumentation to identify, quantify, and access spatial information on as many metabolites as possible. However, the most modern machines and sophisticated tools for data analysis cannot compensate for inappropriate harvesting and/or sample preparation procedures that modify metabolic composition and can lead to erroneous interpretation of results. In addition, plant metabolism has a remarkable degree of complexity, and the number of identified compounds easily surpasses the number of samples in metabolomics analyses, increasing false discovery risk. These aspects pose a large challenge when carrying out plant metabolomics experiments. In this chapter, we address the importance of a proper experimental design taking into consideration preventable complications and unavoidable factors to achieve success in metabolomics analysis. We also focus on quality control and standardized procedures during the metabolomics workflow.

An essential step in the conversion of lignocellulosic biomass to ethanol and other biorefinery products is conversion of cell wall polysaccharides into fermentable sugars by enzymatic hydrolysis. The objective of the present study was to understand the mode of action of hemicellulolytic enzyme mixtures for pretreated sugarcane bagasse (PSB) deconstruction and wheat arabinoxylan (WA) hydrolysis on target biotechnological applications. In this study, five hemicellulolytic enzymes-two endo-1,4-xylanases (GH10 and GH11), two α-L-arabinofuranosidases (GH51 and GH54), and one β-xylosidase (GH43)-were submitted to combinatorial assays using the experimental design strategy, in order to analyze synergistic and antagonistic effects of enzyme interactions on biomass degradation. The xylooligosaccharides (XOSs) released from hydrolysis were analyzed by capillary electrophoresis and quantified by high-performance anion exchange chromatography with pulsed amperometric detection (HPAEC-PAD). Based on this analysis, it was possible to define which enzymatic combinations favor xylose (X1) or XOS production and thus enable the development of target biotechnological applications. Our results demonstrate that if the objective is X1 production from WA, the best enzymatic combination is GH11 + GH54 + GH43, and for xylobiose (X2) production from WA, it is best to combine GH11 + GH51. However, if the goal is to produce XOS, the five enzymes used in WA hydrolysis are important, but for PSB hydrolysis, only GH11 is sufficient. If the final objective is bioethanol production, GH11 is responsible for hydrolyzing 64.3 % of hemicellulose from PSB. This work provides a basis for further studies on enzymatic mechanisms for XOS production, and the development of more efficient and less expensive enzymatic mixtures, targeting commercially viable lignocellulosic ethanol production and other biorefinery products.

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Sugarcane bagasse samples were pretreated with ozone via atmospheric O2 pressure plasma. A delignification efficiency of approximately 80 % was observed within 6 h of treatment. Some hemicelluloses were removed, and the cellulose was not affected by ozonolysis. The quantity of moisture in the bagasse had a large influence on delignification and saccharification after ozonation pretreatment of the bagasse, where 50 % moisture content was found to be best for delignification (65 % of the cellulose was converted into glucose). Optical absorption spectroscopy was applied to determine ozone concentrations in real time. The ozone consumption as a function of the delignification process revealed two main reaction phases, as the ozone molecules cleave the strong carbon-carbon bonds of aromatic rings more slowly than the weak carbon-carbon bonds of aliphatic chains.

Metabolic composition is known to exert influence on several important agronomic traits, and metabolomics, which represents the chemical composition in a cell, has long been recognized as a powerful tool for bridging phenotype–genotype interactions. In this work, sixteen truly representative sugarcane Brazilian varieties were selected to explore the metabolic networks in buds and culms, the tissues involved in the vegetative propagation of this species. Due to the fact that bud sprouting is a key trait determining crop establishment in the field, the sprouting potential among the genotypes was evaluated. The use of partial least square discriminant analysis indicated only mild differences on bud outgrowth potential under controlled environmental conditions. However, primary metabolite profiling provided information on the variability of metabolic features even under a narrow genetic background, typical for modern sugarcane cultivars. Metabolite–metabolite correlations within and between tissues revealed more complex patterns for culms in relation to buds, and enabled the recognition of key metabolites (e.g., sucrose, putrescine, glutamate, serine, and myo-inositol) affecting sprouting ability. Finally, those results were associated with the genetic background of each cultivar, showing that metabolites can be potentially used as indicators for the genetic background.