From Waste to Reuse: The Valorization of Almond Shells (Prunus dulcis) as a Sustainable Biosorbent for the Removal and Recovery of Phenolic Compounds in Winery Wastewater
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From Waste to Reuse: The Valorization of Almond Shells (Prunus dulcis) as a Sustainable Biosorbent for the Removal and Recovery of Phenolic Compounds in Winery Wastewater
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  • Elyse Doria
    Elyse Doria
    Department of Food Science and Technology, University of California, Davis, One Shields Avenue, Davis, California 95616, United States
    More by Elyse Doria
    Orcidhttps://orcid.org/0009-0006-2921-8179
  • Robert Coleman
    Robert Coleman
    Department of Viticulture and Enology, Washington State University, Richland, Washington 99162, United States
    More by Robert Coleman
  • Larry Lerno
    Larry Lerno
    Department of Viticulture and Enology, University of California, Davis, One Shields Avenue, Davis, California 95616, United States
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    Orcidhttps://orcid.org/0000-0001-5292-3358
  • Poll Zhang
    Poll Zhang
    Department of Food Science and Technology, University of California, Davis, One Shields Avenue, Davis, California 95616, United States
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  • Lingchuan Hao
    Lingchuan Hao
    Department of Food Science and Technology, University of California, Davis, One Shields Avenue, Davis, California 95616, United States
    More by Lingchuan Hao
  • Alyson Mitchell*
    Alyson Mitchell
    Department of Food Science and Technology, University of California, Davis, One Shields Avenue, Davis, California 95616, United States
    *Email: [email protected]
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    Orcidhttps://orcid.org/0000-0003-0286-5238
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ACS Food Science & Technology

Cite this: ACS Food Sci. Technol. 2026, 6, 2, 253–264
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https://doi.org/10.1021/acsfoodscitech.5c00652
Published January 9, 2026

Copyright © 2026 The Authors. Published by American Chemical Society. This publication is licensed under

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Abstract

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Almond shell powder (ASP) derived from Nonpareil (soft-shell) and Peerless (hard-shell) almond varieties was evaluated as a natural bioadsorbent for removing phenolic compounds from model and industrial winery wastewater. Binding kinetics, particle size, mass-to-liquid ratio (m/v), and recovery efficiency were assessed. Nonpareil and Peerless adsorption fit an Elovich kinetic model (R2 = 0.986 and 0.982, respectively). Optimal adsorption occurred at a 0.2–0.5 mm particle size and a 1:10 ASP-to-wastewater ratio (m/v), yielding 79.05 ± 0.79% (0.84 ± 0.01 mg g–1) total phenolic content. Phenolic recoveries were 70.26 ± 0.18% (0.51 ± 0.01 mg g–1) for Nonpareil and 52.36 ± 0.30% (0.44 ± 0.00 mg g–1) for Peerless using optimized conditions: 50:50 ethanol/water (v/v) at a 1:25 ASP-to-solvent ratio (m/v). These findings demonstrate that ASP is a viable, low-cost, and sustainable material for phenolic removal from winery wastewater with the added benefit of enabling phenolic compound recovery.

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Introduction

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Agri-food and water waste pose significant environmental, economic, and public health challenges and have prompted increasing emphasis on the valorization of byproducts and mitigation of wastewater through sustainable and integrated management strategies. This is particularly important in California, where the agri-food industry is the largest and most diverse in the nation.
California produces approximately 81% of the U.S. wine supply, yielding over 2.3 billion liters of wine produced in 2023 (1) and generating an estimated 0.46–9.2 billion liters of winery wastewater annually. (2−4) The volume of wastewater generated varies widely depending upon production practices, with reported generation rates ranging from 0.2 to 4.0 L of wastewater per liter of wine. (2−4) The chemical composition of winery wastewater varies widely with season and individual winery practices as well as the stage of collection (e.g., after pressing, primary or secondary fermentation, bottling, or a combination of these).
Winery wastewater is characterized by high concentrations of organic matter, suspended solids, and phenolic compounds derived from grape skins, seeds, stems, and oak contact during wine processing. (3−5) Phenolic compounds, including simple phenols, flavonoids, and tannins, are of particular concern because they can be toxic to aquatic organisms, inhibit microbial activity in biological treatment systems, and resist biodegradation due to their complex aromatic structures. (6−9) Reported total phenolic concentrations in winery wastewater typically range from 50 to 1000 mg L–1, depending on the stage of production, grape variety, and cleaning practices. Although variable, winery wastewater typically has a pH between 3 and 6 and exhibits a high biological oxygen demand (BOD) and a high chemical oxygen demand (COD). (4,5,10) Due to the low pH and high organic load, winery wastewater cannot be directly released into the environment or the municipal wastewater system without pretreatment. (11) In California, regulatory limits typically require winery wastewater effluents to contain less than 10 mg L–1 total nitrogen, 300 mg L–1 BOD, and 330 mg L–1 total suspended solids. (11)
The most common winery wastewater treatment strategies involve screening and sedimentation for the removal of solids (e.g., grape skins and seeds), followed by storing the wastewater in engineered evaporation ponds that rely on microbial degradation, mechanical skimming, and aeration to reduce volume and organic matter. (12,13) Evaporation ponds are energy-intensive, require ongoing monitoring, and can lead to environmental issues such as leaching, groundwater contamination, and odor generation. (3,14,15) Identifying sustainable alternatives for winery wastewater treatment has become a priority for the wine industry. One promising approach is the targeted removal of phenolic compounds to reduce COD and improve compatibility with secondary biological treatment systems (e.g., bioreactors and vermi-biofiltration). Effective phenolic removal can enhance biodegradability, decrease toxicity, and enable integration with downstream bioreactors for more sustainable wastewater management. This strategy also aligns with global efforts to advance wastewater reuse and resource recovery, exemplified by the development of direct potable reuse (DPR) frameworks that promote sustainable water management amid increasing water scarcity and climate variability. (16,17)
In 2023, almond production in California generated approximately 715.8 million kg of shells, a volume that recurs annually. (18) The majority of this biomass is disposed of in landfills, a practice that is environmentally and economically unsustainable. Almond shells have low economic value (typically $0–20 per ton) and limited current applications, primarily as animal bedding or for bioenergy production. (19,20) Exploring alternative applications for almond byproducts (i.e., shells and hulls) is a priority goal of the California almond industry and a key component of the Almond Board of California’s 2025 Zero-Waste Initiative. (21)
Almond shells have a low moisture content and a high mechanical strength and are chemically stable, providing excellent properties for biosorbents. (22,23) The shell is composed of approximately 38% cellulose, 29% hemicellulose, and 30% lignin, varying based on the almond variety and shell type (i.e., hard shell and soft shell). (24,25) Lignin is a polymer composed of cross-linked phenolic alcohols (lignols) and is insoluble in water. (26,27) Lignin forms a dense network of polar aromatic rings and hydroxyl groups, which can reversibly bind compounds through hydrogen bonding, dipole–dipole interactions, and π–π stacking. In addition, cellulose and hemicellulose, both rich in hydroxyl groups, can facilitate hydrogen bonding. These interactions are enhanced by the well-developed pore structure of the shell, which increases the surface area for binding and makes grinding shells into powders of specific sizes possible.
To date, various approaches have been used to remove phenolic compounds from wastewater, including membrane technologies, biodegradation, distillation and evaporation, adsorption and extraction, membrane separation, and chemical oxidation. (12,13,28) These methods can be costly, vary in efficiency, require significant electrical demands, and generate their own waste streams.
Among these, polymeric resins have been widely investigated for the removal and recovery of phenolic compounds from food and food-processing waste streams. Reported adsorption capacities vary considerably (2–86 mg g–1) depending on the resin type, phenolic source, and operating conditions. (29−33) Reported values include 2.3–2.6 mg g–1 for wine vinasse using Amberlite XAD16HP and SP700, (29) 28–78 mg g–1 for phenolic acids in model solutions with XAD7HP and XAD16, (30) 21–86 mg g–1 for apple polyphenols with XAD16HP31, 47–81 mg g–1 for olive mill wastewater using XAD16N, XAD761, FPX66, and Optipore SD-2, (32) and 5.9–11.1 mg g–1 for olive waste with NKA-II, D-101, AB-8, and XDA-1 25–29. (33) Despite their high adsorption capacities and tunable surface chemistry, the practical application of polymeric resins is constrained by their long-term performance, high cost, and the need for chemical or solvent-based regeneration, while waste disposal also poses significant environmental and practical concerns.
Natural biosorbents offer a sustainable and cost-effective alternative to synthetic polymeric resins, exhibiting comparable phenolic adsorption capacities due to their abundant surface functional groups and lower environmental impacts associated with regeneration and disposal. For example, almond shells and almond-shell-derived biochar have been evaluated for the removal of organic dyes and heavy metals from aqueous solutions, demonstrating their potential as low-cost, sustainable materials for industrial wastewater treatment. (34−41) In a study by Taha et al. (2018), the biosorption of Hg(II) from aqueous solution showed capacities of 3.77 and 38.17 mg g–1 for untreated and chemically activated almond shells, respectively. (39) When applied to commercial dyes, almond shells had biosorption capacities between 12 and 127 mg g–1, including dyes like Crystal Violet (12.2 mg g–1), Brilliant Green (50 mg g–1), Methylene Blue (52 mg g–1), Toluidine Blue O (73 mg g–1), Methyl Violet (76 mg g–1), Eriochrome Black T (124 mg g–1), and Malachite Green (127 mg g–1). (34−36,42) In comparison, almond shell biochar significantly increases the biosorption of Methylene Blue dye to 415–440 mg g–1. (40,41) While biochar derived from almond shells may offer a higher adsorption capacity, its production involves energy-intensive pyrolysis, which reduces its overall sustainability. (43) In contrast, the direct utilization of almond shells eliminates the need for chemical activation or pyrolysis, making them a more environmentally friendly and cost-effective option. Given their abundance, renewability, and low cost, almond shells represent a practical and scalable biosorbent for sustainable phenolic removal and recovery.
This study investigates the valorization of untreated almond shells as a sustainable biosorbent for reducing phenolic compounds from winery wastewater. Optimal adsorption and recovery conditions were evaluated by assessing the effects of the particle size, ASP-to-solvent (m/v) ratio, and recovery solvent composition in a model winery wastewater system. Additionally, the water holding capacity (WHC) and adsorption kinetics were examined to elucidate the functional behavior of the ASP for wastewater treatment applications. Unlike energy-intensive technologies such as membrane separation, biosorption offers a low-cost, reusable, and low-waste alternative aligned with sustainable water management goals. Although almond shells have been studied for dye and metal removal, their use for phenolic removal from winery wastewater remains unexplored. The findings from this study help to establish a foundation for developing circular, biobased pretreatment strategies that leverage natural materials to enhance winery wastewater management and promote sustainable water reuse.

Methods and Materials

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Reagents and Standards

Gallic acid (97.5–102.5%), (+)-catechin (>98%), caffeic acid (≥98%), rutin (>95%), malvidin-3-O-glucoside chloride (≥95.0%), potassium l-tartrate monobasic (99%), urea Redi-Dri (≥98%), sodium carbonate (≥99.5%), iron(III) chloride hexahydrate (≥98%), triethanolamine (≥99.0%), sodium hydroxide (≥97.0%), and Folin and Ciocalteu’s phenol reagent (1.9–2.1 N) were purchased from Sigma-Aldrich (St. Louis, MO). Optima LC/MS-grade acetonitrile and formic acid, ACS-grade dimethyl sulfoxide (DMSO), and hydrochloric acid (HCl; 12.1 N) were purchased from Fisher Scientific (Ottawa, Canada). A Millipore Milli-Q purification system was used to produce type-1 water (18.2 mΩ resistance).

Stock Solutions

Gallic acid and (+)-catechin stock solutions were made at 20 g L–1 in 50:50 ethanol/water (v/v). A caffeic acid stock solution was made in ethanol at 20 g L–1. DMSO was used to create a stock solution of 20 g L–1 for rutin. Malvidin-3-O-glucoside stock was made at 10 g L–1 in 0.01% HCl in type-1 water. Stock solutions were stored at −20 °C for up to a month. A model winery wastewater background matrix solution, composed of 2.5 g L–1 potassium tartaric acid in type-1 water, was prepared monthly and stored at 4 °C. Phenolic solutions used in adsorption and recovery studies were made the day of the study and stored protected from light. The model winery wastewater was composed of 25 mg L–1 of each gallic acid, (+)-catechin, caffeic acid, and rutin stock solution, along with 5 mg L–1 of a malvidin-3-O-glucoside stock solution in the model winery wastewater background matrix solution described above, at a pH of 3.6.
For the Harbertson–Adams assay, a urea buffer was made with 50 g L–1 urea and 50 mL L–1 triethanolamine in deionized (DI) water and adjusted to pH 9.4 with HCl. The ferric chloride reagent was composed of 2.7 g L–1 iron(III) chloride hexahydrate in DI water with 0.03% HCl (v/v). For the Folin–Ciocalteu assay, a saturated sodium carbonate solution was prepared by dissolving 200 g of sodium carbonate in 800 mL of DI water and bringing the mixture to a boil. After the mixture cooled, a few crystals of sodium carbonate were added. The solution was allowed to stand for 24 h and then filtered and diluted to 1 L with DI water.

Almond Shell Samples

Almond shells from the varieties Nonpareil (soft shell) and Peerless (hard shell) were collected by Blue Diamond Almonds (Sacramento, CA). Shells were separated from kernels, hulls, and debris manually. Shells were then ground using a Retsch SM 300 mill with a 2 mm sieve (Retsch USA Verder Scientific, Inc., Newtown, PA). Ground almond shells were further particle-sized using Gilson sieves to 0.2–0.5, 0.5–1.0, and 1.0–2.0 mm (Gilson Co., Inc., Lewis Center, OH).

Winery Wastewater Samples

Winery wastewater was collected from Beringer Winery (St. Helena, CA). One wine fermentation tank, previously containing Cabernet Sauvignon, was rinsed with approximately 250 L of water, of which 2 L was collected and stored at −20 °C until further analysis.

Water Holding Capacity (WHC)

The WHC of Nonpareil and Peerless almond shell powder (ASP) was determined in particle size ranges of 0.2–0.5, 0.5–1.0, and 1.0–2.0 mm. The water content was measured gravimetrically by exposing 3 g of each particle size range (n = 3) to 100 mL of DI water in an Erlenmeyer flask placed on an orbital shaker at 280 rpm for 2 h (New Brunswick Scientific Company, Inc., Edison, NJ). After 2 h, excess water was separated from the almond shells using a vacuum. Hydrated ASP was weighed into three replicates and placed in an oven at 40 °C for 24 h, after which the dry weight was measured.

Evaluation of the Particle Size

Almond shells were ground into three distinct particle size ranges, 0.2–0.5, 0.5–1.0, and 1.0–2.0 mm, and exposed to model winery wastewater in triplicate. In an Erlenmeyer flask, 1 g of ASP was combined with 10 mL of model winery wastewater and incubated at room temperature on an orbital shaker at 280 rpm for 1 h. After incubation, the supernatant was separated using a vacuum. Supernatant was transferred to a 2 mL polypropylene centrifuge tube, and samples were centrifuged for 5 min at 15000 rpm at 10 °C. A 1 mL aliquot was then transferred to a 2 mL amber autosampler vial for HPLC-DAD analysis.

Evaluation of the ASP-to-Model Winery Wastewater Ratio

ASP adsorption with 0.2–0.5 mm particles was evaluated at three different m/v ratios. In an Erlenmeyer flask, 1 g of ASP was added, with either 5, 25, or 50 mL of model winery wastewater added. Samples were incubated at room temperature on an orbital shaker set at 280 rpm for 60 min, and the supernatant was separated using a vacuum. An aliquot of each sample was taken and centrifuged for 5 min at 15000 rpm at 10 °C, after which 1 mL was transferred to a 2 mL amber autosampler vial for HPLC-DAD analysis.

Evaluation of the pH on Phenolic Adsorption

The effect of pH on phenolic adsorption on ASP was evaluated using model winery wastewater, which was brought to pH 3, 4, 5, and 6 using hydrochloric acid and sodium hydroxide. In an Erlenmeyer flask, 1 g of Nonpareil or Peerless ASP at particle sizes of 0.2–0.5 mm was added to 10 mL of model winery wastewater for each pH condition. The mixtures were incubated at room temperature on an orbital shaker at 280 rpm for 60 min. An aliquot of each sample was taken and centrifuged for 5 min at 15000 rpm at 10 °C, after which 1 mL was transferred to a 2 mL amber autosampler vial for HPLC-DAD analysis.

Evaluation of the Initial Phenolic Concentration on Adsorption

To evaluate the effect of the initial phenolic concentration on phenolic adsorption onto ASP, Nonpareil and Peerless (0.2–0.5 mm particle size) were exposed to model winery wastewater prepared at three concentrations: 12.5, 25, and 50 mg L–1 for gallic acid, (+)-catechin, caffeic acid, and rutin, corresponding to 2.5, 5, and 10 mg L–1 of malvidin-3-O-glucoside, respectively. These concentrations represent total phenolic levels of 52.5, 105, and 110 mg L–1. For each concentration, 10 mL of the model winery wastewater at the appropriate concentration was aliquoted into an Erlenmeyer flask with 1 g of ASP and incubated on an orbital shaker at room temperature at 280 rpm for 60 min. An aliquot of each sample was taken and centrifuged for 5 min at 15000 rpm at 10 °C, after which 1 mL was transferred to a 2 mL amber autosampler vial for HPLC-DAD analysis.

Adsorption Kinetics

In an Erlenmeyer flask, 1 g of Nonpareil or Peerless ASP of 0.2–0.5 mm particle size was exposed to 100 mL of model winery wastewater. Samples were placed on an orbital shaker at 280 rpm. Samples were collected at 0, 2, 5, 10, 20, 60, 120, and 240 min. At each time point, 500 μL of sample was collected in a 2 mL polypropylene tube and centrifuged for 5 min at 15000 rpm at 10 °C. An aliquot was then transferred to a 2 mL amber autosampler vial for HPLC-DAD analysis. After the last time point was collected, the remaining supernatant was separated under a vacuum, and the final volume was measured using a graduated cylinder.
Pseudo-first-order (eq 1), pseudo-second-order (eq 2), and Elovich (eq 3) nonlinear kinetic models were evaluated for each phenolic compound as well as for the total phenolic content using the coefficient of determination (R2) as an indication of the goodness of fit. The kinetic parameters from pseudo-first-order, pseudo-second-order, and Elovich models were solved using the differential evolution parameter estimation routine supplied in the DEoptim package (44) within R (45) and RStudio. (46) The parameter estimation routine minimized the sum of squares of error between the model fit and measured concentrations.
Equation 1. Pseudo-first-order model where qt (mg g–1) is the concentration of adsorbate on the adsorbent at time t (min), qe (mg g–1) is the concentration of the adsorbate on adsorbent at equilibrium, and k1 (min –1) is the rate of adsorption.
qt=qe(1−e−k1t)
(1)
Equation 2. Pseudo-second-order model where qt (mg g–1) is the concentration of the adsorbate on adsorbent at time t (min), qe (mg g–1) is the concentration of the adsorbate on adsorbent at equilibrium, and k2 (mg g–1 min–1) is the rate of adsorption.
qt=2qek2t(1+qek2t)
(2)
Equation 3. Elovich model where qt (mg g–1) is the amount of phenolics adsorbed at time t (min), α (mg g–1 min–1) represents the initial adsorption rate, and β (mg g–1 min–1) reflects the rate of decrease in adsorption over time, often associated with surface site availability.
qt=1βln(1+αβt)
(3)

Recovery of Phenolic Compounds

The recovery of phenolic compounds from ASP post-treatment with model winery wastewater was optimized for the extraction solvent composition and mass-to-volume (m/v) ratio using the 0.2–0.5 mm particle-sized Nonpareil and Peerless ASPs. After almond shells were treated with the model winery wastewater, the supernatant was separated using a vacuum and transferred to a 2 mL polypropylene tube for HPLC analysis. The almond shells were then exposed to 10 mL of extraction solvent, which consisted of type-1 water with 20%, 50%, or 70% (v/v) ethanol at pH 7. Almond shells were stirred for 20 s every 5 min for a total of 10 min, after which the vacuum was pulled and the liquid sample was collected. Samples were centrifuged for 5 min at 10 °C and 15000 rpm and then diluted with type-1 water as needed for HPLC-DAD analysis. The optimal extraction solvent (i.e., the solvent composition that recovered the greatest amount of phenolics), 50:50 ethanol/water (v/v), was subsequently used to evaluate the influence of the m/v ratio using 1:10, 1:20, and 1:25 (m/v) of treated ASP to solvent, following the same exraction and incubation mentioned above.

Reusability

For both Nonpareil and Peerless, optimized conditions for adsorption and recovery were used. Briefly, 1 g of 0.2–0.5 mm ASP was incubated with 10 mL of model winery wastewater in an Erlenmeyer flask at room temperature for 60 min with shaking at 280 rpm. Supernatant was removed using a vacuum. A 25 mL aliquot of a 50:50 ethanol/water (v/v) extraction solvent was added to the ASP, stirring for 10 min, after which the vacuum was pulled again and the extraction liquid was separated for analysis. A total of three consecutive binding and recovery experiments were completed. Samples were centrifuged for 5 min at 10 °C and 15000 rpm and then diluted with type-1 water as needed for HPLC-DAD analysis.

Scanning Electron Microscopy (SEM) Imaging

One sample of Nonpareil and Peerless ASP at each particle size group (i.e., 0.2–0.5 mm, 0.5–1.0 mm, and 1.0–2.0 mm) was coated in a layer of gold, and SEM imaging was taken of a local 125 × 125 μm area on a Hitachi S-4100 SEM (Hitachi High-Tech; Tokyo, Japan). Imaging began at 60x and intensified in the starting area, reaching a maximum of 300x. Pore sizes were measured manually using image scale bars.

Analytical Methods

A 1200 series Agilent High-Performance Liquid Chromatograph (HPLC) coupled with a diode array detector (DAD) equipped with an autosampler, thermostatic column compartment, and binary pump with an integrated degasser was used for analysis (Agilent Technologies; Santa Clara, CA). A Poroshell 120 column EC-C18 (3.0 mm × 100 mm, 2.7 μm; Agilent Technologies) was used to resolve peaks. Compounds were quantified at the wavelength corresponding to the maximum absorbance: gallic acid and catechin were measured at 280 nm, caffeic acid at 320 nm, rutin at 360 nm, and malvidin-3-O-glucoside at 520 nm. Calibration curves ranging from 0.25 to 50 mg L–1 for each compound were used to quantify gallic acid, (+)-catechin, caffeic acid, rutin, and malvidin-3-O-glucoside. The injection volume was 15 μL, and the column compartment was set to 40 °C. Mobile phases consisted of type-1 water with 1% formic acid v/v (A) and acetonitrile with 1% formic acid v/v (B). The mobile phase gradient was as follows: 0 min, 5% B; 0.5 min, 5% B; 5 min, 25% B; 6 min, 90%B; 8 min, 90% B; 9 min, 5% B; and 12 min, 5% B. The total runtime of the method was 12 min. ChemStation (rev B.03.02) was used for data analysis.
The same instrumentation for the model winery wastewater analysis was used for the industrial winery wastewater analysis. The method was adapted from Pinton et al. (2022). (47) Briefly, a Poroshell 120 SB-C18 column (4.6 mm × 150 mm, 2.7 μm; Agilent Technologies) was used to achieve HPLC separation. For the detection and quantitation of compounds, chromatograms were recorded at 280, 320, 360, and 520 nm. Calibration curves ranging from 0.25 to 50 mg L–1 for each compound were used to quantify gallic acid, (+)-catechin, caffeic acid, rutin, and malvidin-3-O-glucoside. The injection volume was 15 μL, and the column compartment was set to 35 °C. Mobile phases consisted of type-1 water with 1.5% O-phosphoric acid (v/v)(A) and acetonitrile with 20% A (v/v) (B). The mobile phase gradient was as follows: 0 min, 10% B; 73 min, 31% B; 75 min, 62% B; 80 min, 62%B; 82 min, 10% B; 85 min, 10% B. The total runtime of the method was 85 min. Chem Station Offline (Rev. B.03.02) was used for data analysis.
The total phenolic content of winery wastewater samples was measured using a UV-1700 dual-beam UV–visible spectrophotometer (Shimadzu; Columbia, MD). Phenolics were quantified using the Harbertson-Adams modified assay (48,49) and Folin-Ciocalteu assay. (50,51) For the Harbertson-Adams assay, 75 μL of the sample was added to 800 μL of urea buffer, the sample was incubated for 10 min at room temperature, and the reaction was measured at 510 nm. A 125 μL aliquot of a ferric chloride solution was added to the sample, mixed, and incubated for an additional 10 min at room temperature. The sample was then remeasured at 510 nm. A (+)-catechin standard curve was used to convert absorbance to (+)-catechin equivalence using an 8-point curve ranging from 1 to 500 mg L–1.
For the modified Folin-Ciocalteu assay, (50,51) 15 μL of sample was added to 1.185 mL of type-1 water and 75 μL Folin-Ciocalteu reagent, which was incubated for 5 min at room temperature, after which 225 μL of saturated sodium carbonate solution was added and mixed. The samples were incubated at 40 °C in a water bath (Fisher Scientific; Ottawa, CAN) for 30 min, and the absorbance was measured at 765 nm. Absorbance was converted to gallic acid equivalence using an 8-point gallic acid standard curve ranging from 1 to 500 mg L–1.

Statistical Analysis

One-way analysis of variance (ANOVA) was conducted to evaluate treatment effects across all adsorption and desorption experiments, as well as WHC. When significant effects were detected, Tukey’s HSD post hoc tests were applied for pairwise comparisons. Statistical significance was defined as p < 0.05, and these analyses were performed using JMP (18.0.1).
For adsorption kinetics, a separate one-way multivariate analysis of variance (MANOVA) with Wilks’ Lambda was used to assess the effects of treatment on the Elovich rate constants (α and β) and adsorption capacity at 240 min (mol g–1). Where the MANOVA indicated significant differences, a follow-up ANOVA was conducted to determine which variables contributed to group separation. Canonical variable analysis (CVA) was also employed to visualize the differentiation between treatment groups and assess the relative influence of each variable. Analyses were carried out in R (45) and RStudio (46) using the ‘candisc’ package (52) and statistical significance was defined as p < 0.05.

Results and Discussion

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The physical properties of ASP were characterized and optimized to promote maximal binding of phenolic compounds in model and winery wastewater. Almond shells have a low moisture content (<7%) and do not need to be dehydrated prior to milling. (23,33,34,38) The ASP was prepared by milling shells obtained from Nonpareil (soft shell) and Peerless (hard shell) almond varieties, using sieve sizes between 0.2 and 2.0 mm to control the particle size distributions. The natural pore structure of almond shells enables efficient milling into powders of specific sizes to maximize the binding surface area. The structure of the ASP was evaluated using SEM imaging (Figure 1). Nonpareil and Peerless almond shells were imaged at three particle sizes (0.2–0.5, 0.5–1.0, and 1.0–2.0 mm) at 600× magnification to evaluate the pore structure, abundance, and surface morphology. As shown in Figure 1, the pore structures appear similar across shell types, with an estimated pore-size range of 12.5–25 μm. No significant differences in the pore distribution or abundance were observed between shell types. Previous studies on ASP have reported pore sizes ranging from 1 to 60 μm, with pore walls visibly layered, which are dependent on the cultivar, mechanical processing, and particle size. (23,34,35,39) The observed pore sizes and layered textures reported in this study align with these observations.

Figure 1

Figure 1. SEM local imaging of Nonpareil (soft shell) and Peerless (hard shell) almond shells at 0.2–0.5, 0.5–1, and 1–2 mm particle sizes at 600× magnification.

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WHC

The WHC for Nonpareil and Peerless shells increases as the particle size decreases, with the smallest particle size, 0.2–0.5 mm, exhibiting the highest WHC due to its increased surface area (Table 1). Nonpareil shells retained significantly (p < 0.05) more water compared to Peerless shells, binding 2.5 times more water at the 0.2–0.5 mm particle size. Compositional differences between shell types, specifically in the ratios of lignin, cellulose, and hemicellulose, affect water retention and swelling behavior. Variations in these structural components, along with differences in fiber architecture and shell morphology, collectively influence the shell’s capacity to absorb water and undergo physical expansion. (52,53) WHC reflects the ability of an adsorbent to retain water within its pore structures, which can be associated with greater pore volume, enhanced swelling ability, and increased hydrophilic surface interactions. These properties influence the adsorption efficiency by increasing the accessibility of adsorption sites and facilitating the diffusion of phenolic compounds in the matrix. In this study, Nonpareil ASP exhibited a higher WHC than Peerless ASP, suggesting a greater potential for phenolic diffusion under hydrated conditions.
Table 1. WHC of Nonpareil and Peerless ASP at 0.2–5, 0.5–1, and 1–2 mm Particle Rangesa
shell typeparticle rangeg of water/g of dry ASP% WHC
Nonpareil (soft-shell)0.2–0.5 mm4.0 ± 0.6a398.2 ± 62.1a
 0.5–1.0 mm1.7 ± 0.4c168.9 ± 40.3c
 1.0–2.0 mm1.1 ± 0.2d110.6 ± 15.9d
Peerless (hard-shell)0.2–0.5 mm2.4 ± 0.4b237.2 ± 41.2b
 0.5–1.0 mm0.9 ± 0.1d89.6 ± 7.5d
 1.0–2.0 mm0.7 ± 0.0d69.0 ± 4.7d
a

Different letters indicate a statistically significant difference (p < 0.05) within the column based on Tukey’s HSD pairwise comparisons.

Model Winery Wastewater

A model of winery wastewater was prepared to investigate the kinetics of phenolic compound adsorption and recovery on ASP. The model winery wastewater contained predominant phenolic compounds representative of each major class previously identified in winery wastewater. These include gallic acid (hydroxybenzoic acid), (+)-catechin (flavan-3-ol), caffeic acid (hydroxycinnamic acid), rutin (flavonol glycoside), and malvidin-3-O-glucoside (anthocyanin) dissolved in 2.5 g L–1 potassium tartaric acid (pH 3.6). (53,54) Winery wastewater from the production of white wine is similar to red wine with the exception that it lacks anthocyanins.

Particle Size Effect

Phenolic binding to ASP was optimized for particle size for both Nonpareil and Peerless. Particle size had a significant effect (p < 0.05) on phenolic adsorption, with smaller particles exhibiting higher adsorption efficiency (Figure 2). Percent total phenolic adsorption was greatest in the 0.2–0.5 mm range, with Nonpareil and Peerless adsorbing 81.24 ± 2.33% and 77.09 ± 0.62%, respectively. Adsorption decreased progressively with an increasing particle size: Nonpareil adsorbed 61.25 ± 2.44% at 0.5–1.0 mm and 48.89 ± 2.10% at 1.0–2.0 mm, while Peerless adsorbed 55.21 ± 0.32% at 0.5–1.0 mm and 43.86 ± 0.26% at 1.0–2.0 mm. For the 0.5–1.0 and 1.0–2.0 mm particle size ranges, Peerless exhibited approximately 5% lower total phenolic adsorption than Nonpareil, primarily due to the reduced binding of rutin and malvidin-3-O-glucoside. This size-dependent effect is attributed to the greater surface area and shorter diffusion distances associated with smaller particles, which enhance access to both surface and intraparticle adsorption sites. In addition, compositional differences between hard- and soft-shell types may contribute to the observed variation. The denser Peerless shells, characterized by higher lignocellulosic content and reduced WHC, may limit pore swelling, thereby restricting phenolic diffusion and binding. (36,55)

Figure 2

Figure 2. Percent phenolic adsorption onto Nonpareil (soft-shell) and Peerless (hard-shell) ASP exposed to model winery wastewater at three particle size ranges: 0.2–0.5, 0.5–1.0, and 1.0–2.0 mm. Different letters indicate statistically significant differences among treatments within each compound (Tukey’s HSD, p < 0.05).

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Mass-to-Volume Ratio Effect

The ratio of ASP to the volume of model winery wastewater (m/v) had a significant effect (p < 0.05) on phenolic adsorption (Figure 3). The 1:10 m/v ratio yielded the highest percentage of total phenolic adsorption, which decreased as the m/v ratio decreased. The maximum adsorption at 1:10 m/v was 78.45 ± 0.06% for Peerless and 79.64 ± 1.57% for Nonpareil. Peerless bound greater proportions of gallic acid (1:25 m/v), (+)-catechin (1:10 m/v), and caffeic acid (across all ratios), whereas Nonpareil retained higher levels of rutin and malvidin-3-O-glucoside at several ratios. When expressed on a mass basis (mg g–1), phenolic adsorption to ASP increased with an increasing m/v ratio, in contrast to the decline observed in percent adsorption. This pattern has been previously reported, where increasing the solid-to-liquid ratio raised mg g–1 adsorption, while lowering percent binding. (36,55) At higher phenolic-to-ASP ratios, reduced mass-transfer resistance facilitates uptake at both high- and low-affinity sites, increasing total adsorption, while the percentage of bound phenolics decreases due to partial saturation of available sites on the ASP. (36,55)

Figure 3

Figure 3. Percent phenolic adsorption for Nonpariel and Peerless ASPs of 0.2–0.5 mm exposed to model winery wastewater at 1:10, 1:25, and 1:50 (m/v) ratio. Different letters indicate statistically significant differences among treatments within each compound (Tukey’s HSD, p < 0.05).

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Effect of the pH on Adsorption

Using the optimized conditions, 0.2–0.5 mm ASP at a 1:10 m/v ratio, phenolic adsorption was evaluated across a pH range of 3 to 6. The adsorption of total phenolic compounds onto both Nonpareil and Peerless ASP was significantly influenced by pH (p < 0.05). Maximum adsorption of total phenolics occurred at pH 6, averaging 74.33 ± 1.25% for Nonpareil and 84.30 ± 1.39% for Peerless. In contrast, malvidin-3-O-glucoside exhibited greater adsorption at pH 3, averaging 76.47 ± 2.20% for Nonpareil and 74.44 ± 1.02% for Peerless (Supplemental Figure 1). The pH-dependent adsorption behavior is influenced by the surface charge ofASP and the chemistry of the phenolic compounds. The pH of point zero charge (pHpzc) of ASP has been reported to be around pH 5–6, where the surface is positively charged under that range and negatively charged above. (34,56,57) Adsorption of phenolics was highest at pH 6, suggesting that moderate surface deprotonation of ASP favors hydrogen bonding and π-π interactions between phenolic compounds and lignocellulosic structures. Malvidin-3-O-glucoside showed greater adsorption under acidic conditions, consistent with its cationic form and enhanced electrostatic attraction near or below the pHpzc.

Effect of the Initial Concentration on Adsorption

The effect of initial phenolic concentration on adsorption was evaluated at 52.5, 105, and 210 mg L–1 total phenolic content using the optimized conditions (0.2–0.5 mm ASP at a 1:10 m/v ratio) for both Nonpareil and Peerless ASP (Supplemental Figure 2). Percent phenolic adsorption on Nonpareil was significantly higher (p < 0.05) at the lowest initial concentration (52.5 mg L–1), with 75.42 ± 1.23% (0.37 ± 0.01 mg g–1) adsorption, as compared to 70.52 ± 0.15% (0.64 ± 0.00 mg g–1) and 67.69 ± 2.54% (1.24 ± 0.04 mg g–1) at 105 and 210 mg L–1, respectively, suggesting partial saturation of readily accessible surface binding sites at higher concentrations. In contrast, Peerless showed no statistical difference between percent total phenolic adsorption across concentrations, averaging 76.29 ± 1.80%, and corresponding to 0.37 ± 0.00 04 mg g–1, 0.71 ± 0.01 04 mg g–1, and 1.36 ± 0.01 04 mg g–1 for 52.5, 105, and 210 mg L–1, respectively. On average, Peerless adsorbed approximately 5% more phenolics than Nonpareil at 105 and 210 mg L–1, consistent with results from previous experiments. Overall, lower initial phenolic concentrations resulted in higher percent adsorption for Nonpareil, reflecting a greater proportion of available pore sites relative to the amount of phenolic compounds present at lower concentrations.

Adsorption Kinetics

The adsorption kinetics of phenolic compounds on Nonpareil and Peerless ASP were evaluated over 4 h by using multiple established kinetic models. Of these, the Elovich model provided the best fit for describing adsorption on both Nonpareil (R2 = 0.986) and Peerless (R2 = 0.982) ASP (Table 2 and Figure 4). Phenolic binding to ASP is primarily governed by reversible noncovalent interactions, and the strong fit to the Elovich model indicates that heterogeneous distribution of pore structures and surface sites across shell types significantly affects binding kinetics. (58) Nonpareil ASP exhibited a higher initial adsorption rate (α = 10.496 mg/g·min) compared to Peerless (α = 1.987 mg/g·min), suggesting a faster adsorption of phenolics. However, the higher β value observed for Nonpareil ASP indicates a more rapid decline in the adsorption rate over time, reflecting faster saturation of available binding sites (Table 2). After 4 h, Nonpareil and Peerless exhibited similar total phenolic adsorption capacities, binding 2.88 ± 0.01 mg g–1 and 3.14 ± 0.13 mg g–1, respectively.
Table 2. Summary of Model Parameters and Their Goodness-of-Fit (R2) Values for Pseudo-First-Order (PFO), Pseudo-Second-Order (PSO), and Elovich Adsorption Kinetic Models on Soft-Shell and Hard-Shell ASPs
  Nonpareil (soft-shell) 
 PFOPSOElovich
compoundk1 min–1qe mg/gR2k2 mg/g·minqe mg/gR2Α mg/g·minΒ mg/g·minR2
gallic acid0.1100.5970.8480.2320.6500.9100.3459.5880.976
(+)-catechin0.2500.6130.7730.4850.6690.8721.84411.5700.974
caffeic acid0.3390.7030.8210.5880.7610.9055.34911.4010.986
rutin0.6670.4450.8811.9330.4740.93787.39125.4110.990
malvidin-3-O-glucoside0.3350.1360.8873.5110.1450.9562.57267.3550.994
total phenolics0.2662.4750.8190.1362.6780.90410.4963.0310.986
 Peerless (hard-shell)
 PFOPSOElovich
compoundk1 min–1qe mg/gR2k2 mg/g·minqe mg/gR2Α mg/g·minΒ mg/g·minR2
gallic acid0.0530.6610.8630.1010.7270.8780.1908.2930.912
(+)-catechin0.1050.6380.8340.2190.6900.9000.4169.3100.979
caffeic acid0.1220.7580.8610.2200.8160.9270.6808.2330.992
rutin0.3100.2990.8821.4040.3200.9513.12828.5630.996
malvidin-3-O-glucoside0.1890.0950.8962.7420.1020.9590.23175.2210.999
total phenolics0.1052.4440.8490.0622.6130.9091.9872.5610.982

Figure 4

Figure 4. Mean total phenolic adsorption of phenolics onto Nonpareil (a) and Peerless ASP (b) and their fit to pseudo-first-order (PFO), pseudo-second-order (PSO), and Elovich kinetic models. Bars indicate standard deviation across replicates.

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A strong fit to the Elovich model contrasts with previous studies, which have reported pseudo-second-order (PSO) kinetics as the best fit for the adsorption of heavy metals and dyes onto almond shells. (34−36,59) A good fit to the PSO model typically indicates that the rate-limiting step involves chemisorption. In contrast, phenolic compounds primarily interact with ASP through physisorption mechanisms (dipole–dipole interactions, π–π stacking, and hydrogen bonding), supporting the conclusion that PSO kinetics do not appropriately describe our system. Moreover, comparisons with prior studies are limited due to differences in the target compounds and the modeling approaches used, including both linearized and nonlinear PSO models. To the best of our knowledge, this is the first study to evaluate ASP for the adsorption of phenolic compounds, and the Elovich model best describes the kinetics of this process.

Canonical Variate Analysis

Canonical variate analysis (CVA) was performed to determine whether adsorption kinetic parameters [α, β, and total adsorption at 240 min (mol g–1)] could reveal trends in phenolic adsorption behavior. The CVA explained 99.9% of the total variance across the first two canonical axes (CV1:91.1%, CV2:8.8%). Subsequent MANOVA and ANOVA results confirmed that compound identity significantly influenced the multivariate adsorption profile. Malvidin-3-O-glucoside correlated with the β parameter, while rutin and (+)-catechin were associated with the α term, and gallic acid and caffeic acid correlated with total absorption at 240 min (mol g–1) (Figure 5). These trends are driven by differences in the chemical structure and ionization state at pH 3.6. At this pH, malvidin-3-O-glucoside predominantly exists as a flavylium cation, while rutin and (+)-catechin are mainly in their neutral forms. Gallic acid and caffeic acid are also mostly neutral, but with approximately 10–30% present as negatively charged species. Given that the pHpzc of zero charge of ASP is around 5–6, (34,56,57) the ASP surface is positively charged at pH 3.6. Malvidin-3-O-glucoside, being a relatively large, positively charged molecule, may show a higher correlation with the β term (representing a rapid slowing in the adsorption rate) due to electrostatic repulsion and steric hindrance after initial site occupation. Despite this, adsorption still occurs through π–π stacking and hydrogen bonding, though at reduced rates compared to other compounds. Rutin and (+)-catechin, both neutral at this pH, correlate with the α term (indicating rapid initial adsorption). Rutin, the largest molecule in the mixture, may quickly bind to more accessible pore sites initially. As adsorption sites become saturated, its binding efficiency decreases due to size exclusion and competition from smaller molecules. In contrast, gallic acid and caffeic acid show correlations with total adsorption (mol g–1) at 240 min. Their partial negative charge at pH 3.6 allows favorable electrostatic interactions with the positively charged ASP, and their small molecular size enables access to narrower pores. This results in higher molar adsorption relative to that of the larger compounds.

Figure 5

Figure 5. Canonical variate analysis (CVA) of compound adsorption behavior on ASP. CVA showing a) score plot and b)loadings of adsorption parameters and compound characteristics, including α and β rates from the Elovich model, and adsorption at 240 min (mol g–1). Arrows indicate the direction and strength of each variable’s contribution to the canonical variates. CVA scores plot displaying individual compounds projected along the canonical variates.

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Optimization of Phenolic Recovery

Recovery solvent composition and mass-to-volume (m/v) ratio were evaluated and optimized for phenolic recovery from Nonpareil and Peerless ASPs at 0.2–0.5 mm particle size. Solvent composition significantly (p < 0.05) influenced phenolic recovery (Figure 6). The highest total phenolic recovery for Nonpareil (63.17 ± 0.92%) was obtained using 50:50 ethanol/water (v/v). Peerless exhibited maximum recoveries (51.62 ± 1.33%) at both 50:50 and 70:30 ethanol/water (v/v). Recoveries decreased with lower ethanol concentrations. Recoveries of individual phenolic compounds followed similar trends: rutin and malvidin-3-O-glucoside showed the greatest recoveries at 50:50 and 70:30 ethanol/water (v/v), while more polar compounds such as gallic acid and caffeic acid were best recovered in the more aqueous 50:50 ethanol:water (v/v). Nonpareil consistently yielded higher recoveries across most compounds, as compared with those of Peerless.

Figure 6

Figure 6. Percent phenolic recovery for Nonpareil and Peerless ASP of 0.2–0.5 mm exposed to ethanol:water solutions at 0:100, 20:80, 50:50, and 70:30 (v/v). Different letters indicate statistically significant differences among treatments within each compound (Tukey’s HSD, p < 0.05).

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Figure 7 illustrates the effect of the extraction mass-to-volume (m/v) ratio on the recovery of individual and total phenolic compounds from Nonpareil and Peerless ASPs. The m/v ratio significantly (p < 0.05) influenced phenolic recovery across all compounds and shell types. Total phenolic recovery at 1:20 and 1:25 m/v ratios did not differ significantly (p > 0.05) within shell type, with Nonpareil averaging 69.94 ± 0.73% and Peerless 52.09 ± 0.72%. For both shell types, recoveries of all individual phenolic compounds, with the exception of rutin, were similar between 1:20 and 1:25 m/v, while the 1:10 m/v ratio yielded significantly lower recoveries (p < 0.05). Rutin exhibited a distinct trend, with the highest recovery at 1:25 m/v, followed by a significant decline at 1:20 and 1:10 m/v. Based on these results, 50:50 ethanol/water (v/v) at a 1:25 m/v ratio was identified as the optimal extraction condition for maximizing phenolic recovery from both Nonpareil and Peerless ASPs.

Figure 7

Figure 7. Recovery of phenolic compounds from Nonpareil and Peerless ASP using 50:50 ethanol/water (v/v) and varying the ratio of ASP/winery wastewater at 1:10, 1:20, and 1:25 m/v. Different letters indicate statistically significant differences among treatments within each compound (Tukey’s HSD, p < 0.05).

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A consistent shell-type effect was observed across treatments, where Nonpareil exhibited overall higher total phenolic recoveries, approximately 15% greater than that of Peerless, primarily driven by considerably higher gallic acid and caffeic acid recovery levels. Current studies evaluating almond shells as biosorbents do not specify or differentiate between shell types, instead treating almond shells and shell powders as a homogeneous material composed of multiple varieties, making it challenging to directly compare findings. (34−36,38,39,59) Shell-type differences reflect structural and compositional variations between hard- and soft-shell varieties that likely influence the solvent permeability and mass transfer.
Together, these results demonstrate that moderately polar solvents [50:50 ethanol/water (v/v) and 70:30 ethanol/water (v/v)] and larger solvent-to-mass ratios (≥1:20 m/v) maximize phenolic recovery from almond shells. Higher phenolic recoveries at 50:50 ethanol/water (v/v) and 70:30 ethanol/water (v/v) indicate that moderately polar solvents are most effective for extracting a wider range of phenolic classes in our model winery wastewater, while highly aqueous solvents were less effective. These results align with prior studies reporting optimal phenolic recoveries using 40–80% aqueous ethanol or methanol solutions. (60−64) Additionally, phenolic recovery improves with higher solvent volumes (larger m/v ratios), consistent with previous findings that link increased recovery to greater solubilization capacity and more efficient desorption from the matrix. (65)

Reusability of ASPs

To evaluate the reusability of the almond shell material, Nonpareil and Peerless ASPs were subjected to three repeated adsorption and solvent recovery experiments under identical optimized conditions. After each recovery, the same material was reused in the subsequent experiment to assess changes in the adsorption and desorption efficiency over repeated use. Percent adsorption of total phenolics was significantly (p < 0.05) affected across the repeated experiments. In the first experiment, phenolic adsorption was consistent with previous findings, with Nonpareil binding 69.98 ± 0.19% and Peerless 74.39 ± 1.03%. For Nonpareil, total phenolic adsorption decreased significantly in the second and third experiments, averaging 56.78 ± 1.20% and 54.60 ± 0.93%, respectively. Peerless showed a similar decline, with adsorption averaging 56.33 ± 1.12% in both the second and third experiments. Comparable trends were observed across individual phenolic compounds (Supplemental Figure 3).
Recovery of phenolics from Nonpareil and Peerless significantly (p < 0.05) increased with each subsequent recovery experiment. For Nonpareil total phenolic recovery was 72.58 ± 0.70%, 87.62 ± 0.44%, and 93.14 ± 1.91% for the first, second, and third experiments, respectively. Peerless exhibited lower overall recoveries, with 59.36 ± 0.58%, 77.66 ± 0.36%, and 86.39 ± 2.20% for the first, second, and third experiments, respectively. Notably, rutin recovery exceeded 100% during the second and third experiments, likely due to incomplete desorption in the preceding recovery experiments and the subsequent release of residual bound phenolics (Supplemental Figure 4). A similar, though less pronounced, trend was observed across the other compounds.

Applications to Industrial Winery Wastewater

Winery wastewater obtained from rinsing a Cabernet Sauvignon primary fermentation tank was treated with Nonpareil and Peerless ASPs to assess its adsorption performance in a representative winery wastewater. The wastewater had a pH of 3.6, with measured total dissolved solids of 805 ppm and conductivity of 1643 μs cm–1. Using HPLC, gallic acid, (+)-catechin, caffeic acid, rutin, and malvidin-3-O-glucoside were quantified in the tank rinsewater before and after treatment with ASP to evaluate phenolic binding and recovery. Of these five compounds, only gallic acid and malvidin-3-O-glucoside were identified out of the 31 potential phenolic peaks detected in the HPLC chromatogram (data not shown). The amount of gallic acid and malvidin-3-O-glucoside detected prior to ASP exposure was 0.04 mg (4 mg L–1) and 0.19 mg (19 mg L–1), respectively. After ASP exposure, 53.78 ± 3.63% gallic acid and 62.59 ± 2.82% malvidin-3-O-glucoside were adsorbed. Desorption from ASP using 50:50 ethanol/water at a 1:25 m/v resulted in the recovery of 64.33 ± 12.1% of the bound gallic acid and 68.01 ± 13.66% of the bound malvidin-3-O-glucoside.
For comparison with the HPLC data, two established spectrophotometric assays, the Harbertson–Adams assay and the Folin–Ciocalteu assay, were used to determine total phenolic content in model and winery wastewater before and after treatment with Nonpareil ASP (0.2–0.5 mm particle size). Results from the Harbertson–Adams assay indicated that 72.2 ± 0.8% of phenolics was bound, with 8.5 ± 2.0% subsequently recovered. The Folin–Ciocalteu assay (total reducing capacity) yielded similar outcomes, showing 69.0 ± 3.1% total phenolic binding and 11.3 ± 1.3% recovery. Both assays demonstrated comparable binding percentages in model and industrial winery wastewater, consistent with results obtained by HPLC. This suggests that ASP effectively binds a wide range of phenolics, even in complex matrixes. However, the total phenolic content recovered from ASP and quantified by spectrophotometric assays was substantially lower than the recovered levels measured by HPLC. This discrepancy may reflect the broader range of reducing compounds detected by spectrophotometric methods, many of which may be present at low concentrations or are less efficiently recovered from the adsorbent.
Herein, the adsorption performance of ASP was evaluated as a sustainable biosorbent for the phenolic removal of winery wastewater. The ASP bound approximately 79–80% of the available phenolics (1.05 mg) within 1 h contact time, demonstrating removal within a practical operation time frame. Although the total adsorption capacity was not determined in this study, the results from model and industrial winery wastewater experiments indicate strong functional adsorption behavior with binding efficiency varying as a function of the pH and initial phenolic concentrations. Future work employing adsorption isotherm models will provide valuable insights into the maximum capacity and further understanding of the adsorption mechanisms of ASP.
Under the various conditions tested in this study, the ASP bound between 0.4 and 3.1 mg g–1 total phenolics, a range that overlaps with several synthetic resins, which exhibited adsorption capacities between 2 and 18 mg g–1. Synthetic resins are generally petroleum-derived, nonbiodegradable, and costly. In contrast, ASP is a renewable, low-cost byproduct of the almond industry that requires minimal processing, offering a biodegradable and circular alternative for wastewater treatment. Moreover, phenolic-enriched almond shells recovered from treating wastewater may be further valorized as natural bioactive materials (e.g., soil amendment) or used to recover phenolic compounds for various applications (e.g., cosmetics, food).

Supporting Information

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The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsfoodscitech.5c00652.

  • Phenolic adsorption and recoveries for Nonpareil and Peerless ASP at various pH values, initial concentrations, and reusability (PDF)

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Author Information

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  • Corresponding Author
  • Authors
    • Elyse Doria - Department of Food Science and Technology, University of California, Davis, One Shields Avenue, Davis, California 95616, United States;  Orcidhttps://orcid.org/0009-0006-2921-8179
    • Robert Coleman - Department of Viticulture and Enology, Washington State University, Richland, Washington 99162, United States
    • Larry Lerno - Department of Viticulture and Enology, University of California, Davis, One Shields Avenue, Davis, California 95616, United States;  Orcidhttps://orcid.org/0000-0001-5292-3358
    • Poll Zhang - Department of Food Science and Technology, University of California, Davis, One Shields Avenue, Davis, California 95616, United States
    • Lingchuan Hao - Department of Food Science and Technology, University of California, Davis, One Shields Avenue, Davis, California 95616, United States
  • Funding

    Resnick Agricultural Innovation Research Fund Grant (FPAFST0795) and the National Institute of Food and Agriculture, U.S. Department of Agriculture (CAD-FST-6975-H).

  • Notes
    The authors declare no competing financial interest.

Acknowledgments

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The authors thank Blue Diamond Growers and Treasury Wine Estates. We also extend our appreciation to Charlene Hui for her assistance with sample preparation and data acquisition and to Patrick Gravesen for his invaluable technical support.

Abbreviations

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ANOVA

analysis of variance

ASP

almond shell powder

BOD

oxygen demand

COD

chemical oxygen demand

CVA

canonical variate analysis

DAD

diode-array detector

DI

deionized

DPR

direct potable reuse

HPLC

high-performance liquid chromatography

MANOVA

multivariate analysis of variance

m/v

mass-to-volume

PFO

pseudo-first-order

PSO

pseudo-second-order

SEM

scanning electron microscopy

WHC

water holding capacity

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  • Abstract

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    Figure 1

    Figure 1. SEM local imaging of Nonpareil (soft shell) and Peerless (hard shell) almond shells at 0.2–0.5, 0.5–1, and 1–2 mm particle sizes at 600× magnification.

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    Figure 2

    Figure 2. Percent phenolic adsorption onto Nonpareil (soft-shell) and Peerless (hard-shell) ASP exposed to model winery wastewater at three particle size ranges: 0.2–0.5, 0.5–1.0, and 1.0–2.0 mm. Different letters indicate statistically significant differences among treatments within each compound (Tukey’s HSD, p < 0.05).

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    Figure 3

    Figure 3. Percent phenolic adsorption for Nonpariel and Peerless ASPs of 0.2–0.5 mm exposed to model winery wastewater at 1:10, 1:25, and 1:50 (m/v) ratio. Different letters indicate statistically significant differences among treatments within each compound (Tukey’s HSD, p < 0.05).

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    Figure 4

    Figure 4. Mean total phenolic adsorption of phenolics onto Nonpareil (a) and Peerless ASP (b) and their fit to pseudo-first-order (PFO), pseudo-second-order (PSO), and Elovich kinetic models. Bars indicate standard deviation across replicates.

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    Figure 5

    Figure 5. Canonical variate analysis (CVA) of compound adsorption behavior on ASP. CVA showing a) score plot and b)loadings of adsorption parameters and compound characteristics, including α and β rates from the Elovich model, and adsorption at 240 min (mol g–1). Arrows indicate the direction and strength of each variable’s contribution to the canonical variates. CVA scores plot displaying individual compounds projected along the canonical variates.

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    Figure 6

    Figure 6. Percent phenolic recovery for Nonpareil and Peerless ASP of 0.2–0.5 mm exposed to ethanol:water solutions at 0:100, 20:80, 50:50, and 70:30 (v/v). Different letters indicate statistically significant differences among treatments within each compound (Tukey’s HSD, p < 0.05).

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    Figure 7

    Figure 7. Recovery of phenolic compounds from Nonpareil and Peerless ASP using 50:50 ethanol/water (v/v) and varying the ratio of ASP/winery wastewater at 1:10, 1:20, and 1:25 m/v. Different letters indicate statistically significant differences among treatments within each compound (Tukey’s HSD, p < 0.05).

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  • Supporting Information

    Supporting Information

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    • Phenolic adsorption and recoveries for Nonpareil and Peerless ASP at various pH values, initial concentrations, and reusability (PDF)


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