GC-MS based nutritional and aroma profiling of date palm seeds collected from different Egyptian cultivars for valorization purposes

Abstract

Date palm (Phoenix dactylifera L.) is a globally edible fruit and a traditional dietary component in various cultures. The fruit's fleshy part is consumed for its nutritional value, while the seeds are discarded or valorized for oil production and as a coffee substitute. The current study aimed to investigate date seeds' metabolome, in addition to macro- and micro-elements composition within12 major Egyptian cultivars (cvs.) for the first time using gas chromatography coupled with mass spectrometry (GC-MS). Post-silylation GC-MS analysis and headspace coupled with solid-phase microextraction (HS-SPME) were used for nutrients and aroma profiling in roasted seeds, respectively. Furthermore, multivariate data analyses were employed for samples classification and markers identification via principal component analysis (PCA) and orthogonal projection to least square discriminant analysis (OPLS-DA). Models are further validated by permutation test. Moreover, absolute quantification of potential markers was attempted based on reference standards A total of 101 and 65 nutrient and aroma metabolites were annotated, respectively. Fatty acids/esters (38 peaks), sugars (18), organic acids (17), sugar alcohols (7), steroids/triterpenoids (5), alcohols and aldehydes (6), in addition to flavonoids (1) and phenolic acids (3) were identified as major components in GC-MS post-silylation platform. ''Khalas'' cv. seed appeared the most nutritive being enriched in sugars and fatty acids/esters. Moreover, date seed volatiles from different cvs. were dominated by fatty acids/esters (19 peaks), esters (6), and phenols/ethers (9). Anethole (peak 47) was the most abundant at 9.1-23.3% of seeds contributing to their unique aroma, especially ''Barhi'' a premium date cv. PCA score plot of primary metabolites' dataset revealed for 1-monopalmitin and monostearin as potential markers for ''Aref'' and ''Khalas''. Furthermore, ''Barhi'', ''Omeldehn'', and ''Lolo'' cvs. showed comparable aroma profile and in partial agreement with nutrient results. OPLS-DA model revealed that anethole, estragole, methyl esters of dodecanoic acid and octanoic acid were characteristic in case of ''Barhi'' cv. which are likely to impart a fine aroma and flavor. With regards to minerals, ''Zamli'', ''Barhi'', and ''Hasawi'' cvs. were most rich in calcium, copper, and selenium, respectively. This study offers new perspectives for the phytochemical makeup and valorization potentials of date palm seeds. Fatty acids/esters and sugars were the major components in date palm seeds found enriched in ''Khalas'' cv, while anethole, estragole, methyl esters of dodecanoic acid and octanoic acid were potential markers of ''Barhi'' cultivar. Such extensive profiling identified premium cvs. to be considered for food applications.

Keywords: Phoenix dactylifera L; Chemometrics; Date palm seed; GC-MS; HS-SPME; Metabolomics.

Fig. 1

Representative GC-MS chromatograms of silylated primary metabolites in seeds of date palm (P. dactylifera L.) cultivars. The peak numbers denote for the identified metabolites listed in Table S1.

Fig. 2

Pie chart showing the relative percentile (%) of the major classes of the identified primary metabolites derived from some representative date palm (P. dactylifera L.) seed cultivars. The percentile of each phytochemical class is listed in details in Table S1.

Fig. 3

Date palm seed cvs. dataset modelling of primary metabolites as analyzed by gas chromatography combined with mass spectrometry (GC-MS) post-silylation. Unsupervised data modelling of the 12 cvs. (A) Hierarchical cluster analysis (HCA), (B) Principal component analysis (PCA) score plot, and (C) PCA loading plot. Supervised orthogonal partial least squares discriminant analysis (OPLS-DA) modelling of Group 1 against Group 2 varieties as appeared in HCA model (D) Score plot, (E) OPLSA-DA S-plot. Group 1 consisted of ‘’Bahri’’, ‘’Hasawi’’, ‘’Omeldehn’’, ‘’Nabout Seif’’, ‘’Zamli’’, and ‘’Farsi’’ varieties, while Group 2 included ‘’Aref’’, ‘’Breem’’, Khalas, ‘’Lolo’’, and ‘’Zaghloul’’.

Fig. 3

Date palm seed cvs. dataset modelling of primary metabolites as analyzed by gas chromatography combined with mass spectrometry (GC-MS) post-silylation. Unsupervised data modelling of the 12 cvs. (A) Hierarchical cluster analysis (HCA), (B) Principal component analysis (PCA) score plot, and (C) PCA loading plot. Supervised orthogonal partial least squares discriminant analysis (OPLS-DA) modelling of Group 1 against Group 2 varieties as appeared in HCA model (D) Score plot, (E) OPLSA-DA S-plot. Group 1 consisted of ‘’Bahri’’, ‘’Hasawi’’, ‘’Omeldehn’’, ‘’Nabout Seif’’, ‘’Zamli’’, and ‘’Farsi’’ varieties, while Group 2 included ‘’Aref’’, ‘’Breem’’, Khalas, ‘’Lolo’’, and ‘’Zaghloul’’.

Fig. 4

Aroma total ion chromatograms (TIC) of some representative cultivars of roasted date palm (P. dactylifera L.) seed cvs. ‘’Barhi’’, ‘’Khalas’’, and ‘’Lolo’’ as analyzed using head space-solid phase micro-extraction coupled with gas chromatography and mass spectrometry (HS-SPME/GC-MS). The peak numbers denote for the identified metabolites listed in Table S2.

Fig. 5

Relative abundances (%) of the various volatile aroma classes detected in roasted date palm (P. dactylifera L.) seed cvs. as analysed using SPME coupled with GC/MS. The relative abundances of each class and identified metabolites are listed in Table S2.

Fig. 6

Date palm seed cvs. dataset modelling of volatile constituents as analyzed by head space-solid phase micro-extraction coupled with gas chromatography and mass spectrometry (HS-SPME/GC-MS). Unsupervised data modelling of the 8 cvs, including ‘’Barhi’’, ‘’Omeldehn’’, ‘’Rothana’’, ‘’Lolo’’, ‘’Nabout Seif, Khalas’’, ‘’Farsi’’, and ‘’Breem’’. (A) Hierarchical cluster analysis (HCA), (B) Principal component analysis (PCA) score plot, and (C) PCA loading plot. Supervised orthogonal partial least squares discriminant analysis (OPLS-DA) modelling of ‘’Barhi’’ cultivar against other samples (D) Score plot, (E) OPLSA-DA S-loading plot showing model validation indices by permutation test at p < 0.05.

Fig. 7

Mineral content, including macro-elements; iron (Fe), selenium (Se), copper (Cu), manganese (Mn) and boron (B) and macro-elements; calcium (Ca), magnesium (Mg) and phosphorus (P) of P. dactylifera L. seeds of different cvs. represented as ppm ± SD. Statistical analysis is carried out by one-way ANOVA, where cvs. that do not share the same letter in each element are significantly different at p < 0.05.