Emerging Lipids from Arecaceae Palm Fruits in Brazil

Abstract

Arecaceae palm tree fruits (APTFs) with pulp or kernel rich in oil are widely distributed in six Brazilian biomes. APTFs represent a great potential for the sustainable exploitation of products with high added value, but few literature studies have reported their properties and industrial applications. The lack of information leads to underutilization, low consumption, commercialization, and processing of these fruit species. This review presents and discusses the occurrence of 13 APTFs and the composition, physicochemical properties, bioactive compounds, and potential applications of their 25 oils and fats. The reported studies showed that the species present different lipid profiles. Multivariate analysis based on principal component analysis (PCA) and hierarchical cluster analysis (HCA) indicated a correlation between the composition of pulp and kernel oils. Myristic, caprylic, capric, and lauric acids are the main saturated fatty acids, while oleic acid is the main unsaturated. Carotenoids and phenolic compounds are the main bioactive compounds in APTFs, contributing to their high oxidative stability. The APTFs oils have a potential for use as foods and ingredients in the cosmetic, pharmaceutical, and biofuel industries. However, more studies are still necessary to better understand and exploit these species.

Keywords: Acrocomia; Astrocaryum; Attalea; Bactris; Butia; Euterpe; Mauritia; Oenocarpus; Syagrus; specialty oils.

Figure 1

Global production (a) and consumption (b) of vegetable oils from 2013 to 2021, and the import and export volumes of major vegetable oils worldwide in the 2021/2022 marketing year (c). * Expected production/consumption. Adapted from Refs. [1,4,5,6]. 2022, Statista.

Figure 2

Arecaceae palm trees from Brazilian biodiversity: (a) Acrocomia aculeata, (b) Astrocaryum aculeatum, (c) Astrocaryum murumuru, (d) Astrocaryum vulgare, (e) Attalea maripa, (f) Attalea speciosa, (g) Bactris gasipaes, (h) Butia spp., (i) Euterpe oleracea, (j) Mauritia flexuosa, (k) Oenocarpus bataua, (l) Oenocarpus bacaba, and (m) Syagrus coronata. Images are royalty-free and adapted from Wikimedia Commons (http://commons.wikimedia.org/, accessed on 2 June 2022), Flickr (http://flickr.com/, accessed on 2 June 2022), Brazilian Flora 2020 [26], and iNaturalist (http://inaturalist.org/, accessed on 2 June 2022).

Figure 3

Occurrence of Arecaceae species around the globe. The 60 species with higher occurrence worldwide (a); the 10 countries with the highest rate of Arecaceae species (b), and the 15 main Arecaceae species found in Brazil (c). Adapted from Ref. [8].

Figure 4

Studies related to Arecaceae on Scopus^® (a) and Web of Science (b) databases ranked by their main research areas from 1990 to 2021. Adapted from Refs. [24,25]. Accessed on 2 June 2022.

Figure 5

The evolution of studies related to 13 different Arecaceae palm trees on Scopus^® and Web of Science (a) and a comparison of total documents in each database between 1990 and 2021 (b). Adapted from Refs. [24,25]. Accessed on 2 June 2022.

Figure 6

Occurrence of 13 Arecaceae palm trees worldwide (a) and their fruits with the corresponding presence in Brazilian states (b) and Brazilian biomes (c). Adapted from Refs. [8,26]. Fruit images are royalty-free, adapted from Brazilian Agricultural Research Corporation—EMBRAPA (http://embrapa.br/imagens/, accessed on 2 June 2022) and Wikimedia Commons (http://commons.wikimedia.org/, accessed on 2 June 2022).

Figure 6

Occurrence of 13 Arecaceae palm trees worldwide (a) and their fruits with the corresponding presence in Brazilian states (b) and Brazilian biomes (c). Adapted from Refs. [8,26]. Fruit images are royalty-free, adapted from Brazilian Agricultural Research Corporation—EMBRAPA (http://embrapa.br/imagens/, accessed on 2 June 2022) and Wikimedia Commons (http://commons.wikimedia.org/, accessed on 2 June 2022).

Figure 7

Principal component analysis (PCA) and hierarchical cluster analysis (HCA) of Arecaceae palm fruit oils based on their fatty acid profile. Loading plot for principal component 1 × principal component 2 with the projection of variables (a) and score plot of oil samples (b); clustering and linkage distance of variables (c) and oil samples (d) from HCA based on Ward’s method; and the heatmap showing the similarities and differences among oils according to the main significant variables (e). Refer to Table 1 for samples’ acronyms.