Catalytic dehydration of glycerol to acrolein: catalysts and processes

The valorization of glycerol has been widely studied notably due to the oversupply of the latter from biodiesel production. Among the different upgrading reactions, dehydration to acrolein is of high interest due to the importance of acrolein as an intermediate for polymer industry (via acrylic acid) and for feed additive (synthon for DL-methionine). It is known that acrolein can be obtained by glycerol catalytic dehydration over acid catalysts. Zeolites and heteropolyacid catalysts are initially highly active, but deactivate rapidly with time on stream by coking, whilst mixed metal oxides are more stable catalytic systems but less selective and in addition they require an activation period. In this talk, the strategy we followed is described. It consisted in a parallel approach in which we developed supported heteropolyacid-based catalysts with increased stability and acrolein selectivity by using a ZrO2-grafted SBA-15 playing the role of the support for silico-tungstic acid active phase, as well as a new concept based on a two zones fluidized bed reactor (TZFBR) to tackle the unavoidable deactivation issue of the HPA catalysts. This type of reactor comprises – in one single capacity – reaction and regeneration zones. In the second part of the lecture the REALCAT platform was introduced. REALCAT (French acronym standing for ‘Advanced High-Throughput Technologies Platform for Biorefineries Catalysts Design’) is an highly integrated platform devoted to the acceleration of innovation in all the fields of industrial catalysis with an emphasis on emergent biorefinery catalytic processes. In this extremely competitive field, REALCAT consists in a versatile High-Throughput Technologies (HTT) platform devoted to innovation in heterogeneous, homogeneous or biocatalysts AND their combinations under the ultra-efficient very novel concept of hybrid catalysis.

QTLs mapping for primary metabolites responsible of the organoleptic and nutritional characteristics of strawberry (Fragaria x ananassa)

The cultivated strawberry (Fragaria x ananassa) is the berry fruit most consumed worldwide and is well-known for its delicate flavour and nutritional properties. However, fruit quality attributes have been lost or reduced after years of traditional breeding focusing mainly on agronomical traits. To face the obstacles encountered in the improvement of cultivated crops, new technological tools, such as genomics and high throughput metabolomics, are becoming essential for the identification of genetic factors responsible of organoleptic and nutritive traits. Integration of “omics” data will allow a better understanding of the molecular and genetic mechanisms underlying the accumulation of metabolites involved in the flavour and nutritional value of the fruit. To identify genetic components affecting/controlling? fruit metabolic composition, here we present a quantitative trait loci (QTL) analysis using a 95 F1 segregating population derived from genotypes ‘1392’, selected for its superior flavour, and ‘232’ selected based in high yield (Zorrilla-Fontanesi et al., 2011; Zorrilla-Fontanesi et al., 2012). Metabolite profiling was performed on red stage strawberry fruits using gas chromatography hyphenated to time-of-flight mass spectrometry, which is a rapid and highly sensitive approach, allowing a good coverage of the central pathways of primary metabolism. Around 50 primary metabolites, including sugars, sugars derivatives, amino and organic acids, were detected and quantified after analysis in each individual of the population. QTL mapping was performed on the ‘232’ x ‘1392’ population separately over two successive years, based on the integrated linkage map (Sánchez-Sevilla et al., 2015). First, significant associations between metabolite content and molecular markers were identified by the non-parametric test of Kruskal-Wallis. Then, interval mapping (IM), as well as the multiple QTL method (MQM) allowed the identification of QTLs in octoploid strawberry. A permutation test established LOD thresholds for each metabolite and year. A total of 132 QTLs were detected in all the linkage groups over the two years for 42 metabolites out of 50. Among them, 4 (9.8%) QTLs for sugars, 9 (25%) for acids and 7 (12.7%) for amino acids were stable and detected in the two successive years. We are now studying the QTLs regions in order to find candidate genes to explain differences in metabolite content in the different individuals of the population, and we expect to identify associations between genes and metabolites which will help us to understand their role in quality traits of strawberry fruit.