Enhanced extraction of bioactive compounds from date seeds using a green pH-shift method: modeling, optimization, and characterization

Enhanced extraction of bioactive components is crucial for valorizing by-products. This study optimized bioactive extraction using a green pH-shift process (pH 1–11), and explored extraction temperature (20–60 °C), solute content (5–25%), and time (15–75 minutes), employing response surface methodology (RSM) and artificial neural network (ANN), and to characterize the antioxidant activities and polyphenols. Alkaline conditions yielded higher total polyphenols content (TPC) than acidic conditions. The ANN model outperformed RSM, particularly within the pH range of 4–7. Both models indicated TPC yield per unit solute decreased with increasing solute content. However, for maximization, the TPC yield of the medium time-temperature combination predicted by the RSM model was statistically similar (p > 0.05) to the TPC yield with a higher time-temperature combination predicted by the ANN model. Antioxidant activities (DPPH, and ABTS) correlated with TPC, increasing with pH-shift. Cinnamic acid derivatives were most abundant at pH 6, and alkaline pH enhanced all polyphenolic categories, while acidic pH had a limited effect. These results highlight the effectiveness of the pH-shift method, particularly in alkaline conditions, for optimizing date seed bioactive extraction for applications in multiple disciplines including but not limited to foods, cosmetics, pharmaceuticals, agriculture, and biomedicine.

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Publication Details

Journal
Cogent Food & Agriculture
Published
2024-11-21
DOI
https://doi.org/10.1080/23311932.2024.2431164
Citations
5
Primary Topic
Date Palm Research Studies
Type
article
Field-Weighted Citation Impact
3.00
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article

Enhanced extraction of bioactive compounds from date seeds using a green pH-shift method: modeling, optimization, and characterization

Anuj Niroula, Ahmad Rabbani, Akmal Nazir, Jennifer Osamede Airouyuwa et al.
5 citations
Cogent Food & Agriculture
Date Palm Research Studies
3.00
article

Enhanced extraction of bioactive compounds from date seeds using a green pH-shift method: modeling, optimization, and characterization

Anuj Niroula, Ahmad Rabbani, Akmal Nazir, Jennifer Osamede Airouyuwa, Sajid Maqsood, Abid Ali
article en
5 citations

Abstract

Enhanced extraction of bioactive components is crucial for valorizing by-products. This study optimized bioactive extraction using a green pH-shift process (pH 1–11), and explored extraction temperature (20–60 °C), solute content (5–25%), and time (15–75 minutes), employing response surface methodology (RSM) and artificial neural network (ANN), and to characterize the antioxidant activities and polyphenols. Alkaline conditions yielded higher total polyphenols content (TPC) than acidic conditions. The ANN model outperformed RSM, particularly within the pH range of 4–7. Both models indicated TPC yield per unit solute decreased with increasing solute content. However, for maximization, the TPC yield of the medium time-temperature combination predicted by the RSM model was statistically similar (p > 0.05) to the TPC yield with a higher time-temperature combination predicted by the ANN model. Antioxidant activities (DPPH, and ABTS) correlated with TPC, increasing with pH-shift. Cinnamic acid derivatives were most abundant at pH 6, and alkaline pH enhanced all polyphenolic categories, while acidic pH had a limited effect. These results highlight the effectiveness of the pH-shift method, particularly in alkaline conditions, for optimizing date seed bioactive extraction for applications in multiple disciplines including but not limited to foods, cosmetics, pharmaceuticals, agriculture, and biomedicine.

Cogent Food & AgricultureVol. 10(1)
United Arab Emirates University (AE)
Zero hunger
Openalex Percentile: Top 9%
Date Palm Research Studies
3.00
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Enhanced extraction of bioactive compounds from date seeds using a green pH-shift method: modeling, optimization, and characterization — Anuj Niroula, Ahmad Rabbani, et al. · Cogent Food & Agriculture (2024) | TGRS Research Map | TGRS