Influence of the Abiotic Stress Conditions, Waterlogging and Drought, on the Bitter Sensometabolome as Well as Agronomical Traits of Six Genotypes of Daucus carota

Artificial intelligence decision making tools in food metabolomics: Data fusion unravels synergies within the hazelnut (Corylus avellana L.) metabolome and improves quality prediction

This study investigates the metabolome of high-quality hazelnuts (Corylus avellana L.) by applying untargeted and targeted metabolome profiling techniques to predict industrial quality. Utilizing comprehensive two-dimensional gas chromatography and liquid chromatography coupled with high-resolution mass spectrometry, the research characterizes the non-volatile (primary and specialized metabolites) and volatile metabolomes. Data fusion techniques, including low-level (LLDF) and mid-level (MLDF), are applied to enhance classification performance. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) reveal that geographical origin and postharvest practices significantly impact the specialized metabolome, while storage conditions and duration influence the volatilome. The study demonstrates that MLDF approaches, particularly supervised MLDF, outperform single-fraction analyses in predictive accuracy. Key findings include the identification of metabolites patterns causally correlated to hazelnut's quality attributes, of them aldehydes, alcohols, terpenes, and phenolic compounds as most informative. The integration of multiple analytical platforms and data fusion methods shows promise in refining quality assessments and optimizing storage and processing conditions for the food industry.

Sensory Perception and Consumer Acceptance of Carrot Cultivars Are Influenced by Their Metabolic Profiles for Volatile and Non-Volatile Organic Compounds

Sensory parameters as well as the volatile and non-volatile compound profiles of sixteen carrot cultivars were recorded to obtain insight into consumer preference decisions. The sensory test was carried out with a consumer panel of 88 untrained testers allowing a clear acceptance-based differentiation of the cultivars. Five individual sensory characters (sweetness, overall aroma, bitterness, astringency and off-flavor) supported this discrimination. Chemical analyses of volatile organic compounds, polyacetylenes, phenylpropanoids and sugars enabled us to correlate the influence of these ingredients on sensory perception. Higher concentrations of α-pinene, hexanal, styrene and acetophenone correlated with a better acceptance, as well as sweetness and overall aroma perception. In contrast, a low acceptance as well as a stronger perception of bitterness, astringency and off-flavor correlated with enhanced concentrations of camphene, bornylacetate, borneol, myristicine, falcarindiol, falcarindiol-3-acetate, laserin and epilaserin. The present study should support the development of new breeding strategies for carrot cultivars that better satisfy consumer demands.

The genetic control of polyacetylenes involved in bitterness of carrots (Daucus carota L.): Identification of QTLs and candidate genes from the plant fatty acid metabolism

BACKGROUND

Falcarinol-type polyacetylenes (PAs) such as falcarinol (FaOH) and falcarindiol (FaDOH) are produced by several Apiaceae vegetables such as carrot, parsnip, celeriac and parsley. They are known for numerous biological functions and contribute to the undesirable bitter off-taste of carrots and their products. Despite their interesting biological functions, the genetic basis of their structural diversity and function is widely unknown. A better understanding of the genetics of the PA levels present in carrot roots might support breeding of carrot cultivars with tailored PA levels for food production or nutraceuticals.

RESULTS

A large carrot F₂ progeny derived from a cross of a cultivated inbred line with an inbred line derived from a Daucus carota ssp. commutatus accession rich in PAs was used for linkage mapping and quantitative trait locus (QTL) analysis. Ten QTLs for FaOH and FaDOH levels in roots were identified in the carrot genome. Major QTLs for FaOH and FaDOH with high LOD values of up to 40 were identified on chromosomes 4 and 9. To discover putative candidate genes from the plant fatty acid metabolism, we examined an extended version of the inventory of the carrot FATTY ACID DESATURASE2 (FAD2) gene family. Additionally, we used the carrot genome sequence for a first inventory of ECERIFERUM1 (CER1) genes possibly involved in PA biosynthesis. We identified genomic regions on different carrot chromosomes around the found QTLs that contain several FAD2 and CER1 genes within their 2-LOD confidence intervals. With regard to the major QTLs on chromosome 9 three putative CER1 decarbonylase gene models are proposed as candidate genes.

CONCLUSION

The present study increases the current knowledge on the genetics of PA accumulation in carrot roots. Our finding that carrot candidate genes from the fatty acid metabolism are significantly associated with major QTLs for both major PAs, will facilitate future functional gene studies and a further dissection of the genetic factors controlling PA accumulation. Characterization of such candidate genes will have a positive impact on carrot breeding programs aimed at both lowering or increasing PA concentrations in carrot roots.