Dataset Information

1H NMR chemometric models for classification of Czech wine type and variety

ABSTRACT:

A set of 917 wines of Czech origin registered in a national competition were analysed using nuclear magnetic resonance spectroscopy (NMR) with the aim to build and evaluate multivariate statistical models and machine learning methods for the classification of type (5 types), variety (13 varieties) and location (4 locations) based on 1H NMR spectra. The predictive models afforded more than 93% of correctness for classification of dry and medium dry, medium, sweet white wines and dry red wines. The trained Random Forest (RF) method is able to classify Pinot noir with 96% of correctness, Blaufränkisch 96%, Riesling 92%, Cabernet Sauvignon 77%, Chardonnay 76%, Gewürtztraminer 60%, Hibernal 60%, Grüner Veltliner 52%, Pinot gris 48%, Sauvignon Blanc 45%, Pálava 40%. Pinot blanc and Chardonnay are varieties, which are often misplaced and were discriminated with 71% of correctness. Chemometrics represents prospective tool to predict important features in wine, potentially important in quality assessment and fraud detection.

INSTRUMENT(S): Nuclear Magnetic Resonance (NMR) -

SUBMITTER: Jaroslav Havlik

PROVIDER: MTBLS1677 | MetaboLights | 2020-08-28

REPOSITORIES: MetaboLights

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	MTBLS1677	Other
	FILES	Other
	a_MTBLS1677_NMR___metabolite_profiling.txt	Txt
	i_Investigation.txt	Txt
	m_MTBLS1677_NMR___metabolite_profiling_v2_maf.tsv	Tabular

Items per page:

1 - 5 of 6

Similar Datasets

Project description:The coconut tree (Cocos nucifera L.) is an ancient palm species that since early times had been integrally exploited due to their many benefits to the habitants of the tropical and subtropical areas (Niral and Jerard, 2018). The coconut together with the oil palm (Elaeis guineensis) and date palm (Phoenix dactylifera L.) belongs to the Arecaceae family and represent a natural source of oils and carbohydrates both, highly demanded in food and pharmaceutical industries. The coconut shows high morphological variations, but grouping normally in two groups, according to their morphology and growth habits, the “Tall” and the “Dwarf” varieties. Frequently, hybrids are considered as a third variety resulting from cross pollination between Tall and Dwarfs. Tall varieties begin to flowering at 5-7 years after planting, and continue emitting inflorescences and fruits up to 80 to 100 years. When adults, tall palms reach heights between 20-30 m; producing fruits from medium to large in size with abundant solid endosperm and high oil content. In case of dwarf palm varieties, they start flowering and fruiting at 3-4 years after planting, and continue producing by almost 50 years. As adults, their height is 8-10 m, producing fruits from small to medium size with moderate amounts of solid endosperm and less oil content than tall varieties. The solid endosperm, also named as “coconut meat” and when it is dry “copra”, is the source of medium chain saturated fatty acids (MCSFA), e.g. lauric acid (C12:0), myristic acid (C14:0) and palmitic acid (C16:0), among others, and their content of total fatty acids is higher in Tall than in Dwarf varieties. Coconut Oil contains high levels of lauric acid and exhibit characteristics as increased oxidative stability, low melting points and formation of stable emulsions, all them highly appreciated in the food and chemical industries (Kumar, 2011; Reynolds et al., 2019). Moreover, due to its high content of antioxidants such as tocopherol and beta-carotene, coconut oil exhibit various health benefits, such as antibacterial, antiviral, and cardiovascular protection. Coconut fruit growth and ripening is intrinsically related with development of the different seed tissues, i.e., endosperms, embryo and pericarp. The endosperms of the coconut fruit did not accumulate synchronically with fruit maturation.

Dataset Information

1H NMR chemometric models for classification of Czech wine type and variety

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets