Chestnut Episperm as a Promising Natural Source of Phenolics from Agri-Food Processing by-Products: Optimisation of a Sustainable Extraction Protocol by Ultrasounds
Dario Donno (),
Federica Turrini,
Emanuele Farinini,
Maria Gabriella Mellano,
Raffaella Boggia,
Gabriele Loris Beccaro and
Giovanni Gamba
Additional contact information
Dario Donno: Department of Agriculture, Forestry and Food Science, University of Torino, Largo Braccini 2, 10095 Grugliasco, Italy
Federica Turrini: Department of Pharmacy, University of Genoa, Viale Cembrano 4, 16148 Genoa, Italy
Emanuele Farinini: Department of Pharmacy, University of Genoa, Viale Cembrano 4, 16148 Genoa, Italy
Maria Gabriella Mellano: Department of Agriculture, Forestry and Food Science, University of Torino, Largo Braccini 2, 10095 Grugliasco, Italy
Raffaella Boggia: Department of Pharmacy, University of Genoa, Viale Cembrano 4, 16148 Genoa, Italy
Gabriele Loris Beccaro: Department of Agriculture, Forestry and Food Science, University of Torino, Largo Braccini 2, 10095 Grugliasco, Italy
Giovanni Gamba: Department of Agriculture, Forestry and Food Science, University of Torino, Largo Braccini 2, 10095 Grugliasco, Italy
Agriculture, 2024, vol. 14, issue 2, 1-14
Abstract:
Chestnut processing has increasingly grown in recent years. All the processes involved in the chestnut supply chain are characterized by the production of high levels of by-products that cause several environmental and disposal issues. The Castanea spp. fruit production is related to a high number of chestnut episperm. This underutilized agricultural by-product may be evaluated as a good resource for the extraction of health-promoting natural molecules, such as phenolics. This preliminary study aimed to develop and optimize, using a multivariate statistical approach, a sustainable protocol for the ultrasound-assisted extraction (UAE) of the main phenolics from chestnut episperm (cv Marsol, C. sativa × C. crenata ). A design of experiment (DoE) approach was employed. This approach focused on the two quantitative UAE process factors: the extraction time (X 1 ), within a timeframe ranging from 10 to 30 min, and the sample-to-solvent ( w / v ) ratio (X 2 ), ranging from 1/30 to 1/10. These variables were investigated to determine their impact on phenol extraction yield. Exploratory analysis, in particular principal component analysis ( PCA ) and multiple linear regression (MLR), were carried out on the studied responses. The phenolic characterization of ten different extracts was also performed using high-performance liquid chromatography (HPLC), both to define the levels of specific phenolics selected for their health-promoting properties and to evaluate some important features, such as the total antioxidant capacity. The values of total polyphenolic content (TPC) obtained in the different experiments ranged between 97 (extract 4) and 142 (extract 6) mg GAE/g of dried weight (DW). Moreover, results from the ferric reducing antioxidant power (FRAP) test confirmed the high TPC values, highlighting that all the ultrasound extracts contained excellent levels of molecules with good antioxidant properties. In particular, extracts 2 and 3 showed the highest AOC values (about 490–505 mmol Fe 2+ /Kg of dried weight). The proposed optimized protocol allowed for obtaining formulations characterized by high levels of tannins, phenolic acids, and catechins. Indeed, episperm extracts contained high levels of chlorogenic acid (15–25 mg/100 g DW), ferulic acid (80–120 mg/100 g DW), castalagin (20–80 mg/100 g DW), and vescalagin (40–75 mg/100 g). Finally, in this research study, the potential of chestnut episperm as a source of polyphenolic molecules to be extracted by green technologies and used in several food and/or pharmaceutical applications was evaluated to valorize a sustainable reuse strategy of agri-food processing by-products, also reducing the environmental impact of this waste derived from chestnut processing.
Keywords: agri-food by-products; Castanea spp.; ultrasound-assisted extraction; phenolic composition; HPLC; DoE; principal component analysis (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)
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