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Research article · 2025 · Full text

International Journal of Agriculture and Nutrition

Optimization of extraction parameters for phenolic compounds from black rice bran

Saengdao ChotikulAnong SiripunyaKanokwan Rungruang

Volume 7(4) · Pages 157–160 · DOI: 10.33545/26646064.2025.v7.i4c.428 ↗

Research areasPhytochemicals and Antioxidant ActivitiesAgricultural and Biological ResearchFood composition and properties

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Abstract

Author-written

Black rice bran is one of the richest plant-based sources of anthocyanins and phenolic acids, yet its commercial exploitation has been held back by inconsistent extraction yields. This research optimized extraction conditions for total phenolic compounds (TPC) from Thai black rice bran (cultivar Riceberry) using response surface methodology with a central composite design. Three independent variables—extraction temperature (40-80 °C), time (30-90 min), and solvent-to-solid ratio (1:10-1:30 v/w, 70% ethanol)—were investigated across 20 experimental runs. TPC ranged from 11.8 to 42.7 mg gallic acid equivalents (GAE) per gram of bran. The second-order polynomial model was significant (p

Summary

Source-checked

Plain-language reading of the full paper, prepared with AI and checked against the text. Each point links to the authors' own words.

  1. Why it matters

    • Black rice bran is a rich source of phenolic acids and anthocyanins, but inconsistent extraction yields have limited its commercial use. View evidence ↗

      Why it matters

      Black rice bran is a rich source of phenolic acids and anthocyanins, but inconsistent extraction yields have limited its commercial use.

      In the paper's own words

      “Black rice bran is one of the richest plant-based sources of anthocyanins and phenolic acids, yet its commercial exploitation has been held back by inconsistent extraction yields.”

      Page 1

      Found in: Introduction

      Read it in the full textOpen PDF at page 1 ↗
    • The Thai Riceberry cultivar is especially notable because its bran contains 3 to 5 times more phenolic compounds than brown or white rice bran. View evidence ↗

      Why it matters

      The Thai Riceberry cultivar is especially notable because its bran contains 3 to 5 times more phenolic compounds than brown or white rice bran.

      In the paper's own words

      “Among Thai cultivars, Riceberry has attracted particular attention because its bran contains 3 to 5 times more phenolic compounds than conventional white or brown rice bran”

      Page 1

      Found in: Introduction

      Read it in the full textOpen PDF at page 1 ↗
    • Phenolic compounds from rice bran have demonstrated strong anti-diabetic, anti-inflammatory, and antioxidant properties in animal and cell-culture models. View evidence ↗

      Why it matters

      Phenolic compounds from rice bran have demonstrated strong anti-diabetic, anti-inflammatory, and antioxidant properties in animal and cell-culture models.

      In the paper's own words

      “These compounds exhibit strong antioxidant, anti-inflammatory, and anti-diabetic properties in cell-culture and animal models”

      Page 1

      Found in: Introduction

      Read it in the full textOpen PDF at page 1 ↗
  2. The question

    • The study aimed to use response surface methodology (RSM-CCD) to model how temperature, time, and solvent ratio affect total phenolic compound (TPC) extraction from Riceberry bran, find the optimal conditions, and evaluate the resulting extract's antioxidant activity. View evidence ↗

      The question

      The study aimed to use response surface methodology (RSM-CCD) to model how temperature, time, and solvent ratio affect total phenolic compound (TPC) extraction from Riceberry bran, find the optimal conditions, and evaluate the resulting extract's antioxidant activity.

      In the paper's own words

      “This research aimed to (i) model the effects of temperature, time, and solvent ratio on TPC extraction from Riceberry bran using RSM-CCD, (ii) identify the optimum extraction conditions, and (iii) characterize the antioxidant activity of the extract obtained under optimized conditions.”

      Page 1

      Found in: Introduction

      Read it in the full textOpen PDF at page 1 ↗
  3. What they did

    • The study used Riceberry black rice bran obtained from a pilot mill at Southern Thai Agricultural University in March 2023. View evidence ↗

      What they did

      The study used Riceberry black rice bran obtained from a pilot mill at Southern Thai Agricultural University in March 2023.

      In the paper's own words

      “Riceberry black rice bran was obtained from the university's pilot rice mill at Southern Thai Agricultural University, Songkhla (7.00°N, 100.47°E), immediately after milling in March 2023.”

      Page 2

      Found in: Materials

      Read it in the full textOpen PDF at page 2 ↗
    • The researchers conducted 20 experimental runs using a central composite design (CCD) to test temperature (40-80 °C), time (30-90 min), and solvent-to-solid ratio (1:10-1:30 v/w). View evidence ↗

      What they did

      The researchers conducted 20 experimental runs using a central composite design (CCD) to test temperature (40-80 °C), time (30-90 min), and solvent-to-solid ratio (1:10-1:30 v/w).

      In the paper's own words

      “A three-factor, five-level CCD with six centre-point replicates was used, generating 20 experimental runs. The independent variables were temperature (X₁: 40-80 °C), time (X₂: 30-90 min), and solvent-to-solid ratio (X₃: 1:10-1:30 v/w).”

      Page 2

      Found in: Methods

      Read it in the full textOpen PDF at page 2 ↗
    • Extractions were performed using 5.0 g of bran mixed with 70% aqueous ethanol. View evidence ↗

      What they did

      Extractions were performed using 5.0 g of bran mixed with 70% aqueous ethanol.

      In the paper's own words

      “Each extraction run used 5.0 g of bran mixed with 70 percent aqueous ethanol at the designated solvent-to-solid ratio.”

      Page 2

      Found in: Extraction Protocol

      Read it in the full textOpen PDF at page 2 ↗
  4. What they found

    • The second-order polynomial model was highly significant (p<0.001), explaining 96.4% of the variation in TPC (R² = 0.964). View evidence ↗

      What they found

      The second-order polynomial model was highly significant (p<0.001), explaining 96.4% of the variation in TPC (R² = 0.964).

      In the paper's own words

      “The model was highly significant (p<0.001) with an R² of 0.964 and an adjusted R² of 0.931, indicating that 96.4 percent of the variation in TPC was explained by the fitted model.”

      Page 2

      Found in: Methods

      Read it in the full textOpen PDF at page 2 ↗
    • Temperature was the most influential variable, contributing 38.4% to TPC variation, followed by time at 27.1%. View evidence ↗

      What they found

      Temperature was the most influential variable, contributing 38.4% to TPC variation, followed by time at 27.1%.

      In the paper's own words

      “Temperature was the dominant factor (38.4% contribution), followed by time (27.1%) and the quadratic term of temperature (11.6%).”

      Page 2

      Found in: Methods

      Read it in the full textOpen PDF at page 2 ↗
    • Phenolic yield increased from 40 to 70 °C, peaked between 68-72 °C, and decreased at 80 °C. View evidence ↗

      What they found

      Phenolic yield increased from 40 to 70 °C, peaked between 68-72 °C, and decreased at 80 °C.

      In the paper's own words

      “Phenolic yield rose steeply from 40 to 70 °C, peaked near 68-72 °C, and then declined at 80 °C”

      Page 2

      Found in: Introduction

      Read it in the full textOpen PDF at page 2 ↗
    • The optimal extraction conditions were identified as 68 °C, 54 min, and a 1:22 solvent ratio, yielding an experimental TPC of 43.1 ± 1.6 mg GAE/g. View evidence ↗

      What they found

      The optimal extraction conditions were identified as 68 °C, 54 min, and a 1:22 solvent ratio, yielding an experimental TPC of 43.1 ± 1.6 mg GAE/g.

      In the paper's own words

      “TPC (mg GAE/g) | 42.1 | 43.1 ± 1.6 | 2.3”

      Page 2

      “Table 2: Predicted and experimental values at optimum extraction conditions (68 °C, 54 min, 1:22 ratio)”

      Page 2

      Found in: Methods

      Read it in the full textOpen PDF at page 2 ↗
    • The optimized extract showed strong antioxidant activity, with DPPH and ABTS radical scavenging reaching 87.3 ± 2.1% and 91.6 ± 1.4%, respectively. View evidence ↗

      What they found

      The optimized extract showed strong antioxidant activity, with DPPH and ABTS radical scavenging reaching 87.3 ± 2.1% and 91.6 ± 1.4%, respectively.

      In the paper's own words

      “DPPH scavenging (%) | - | 87.3 ± 2.1 | - | ABTS scavenging (%) | - | 91.6 ± 1.4 | -”

      Page 2

      Found in: Methods

      Read it in the full textOpen PDF at page 2 ↗
  5. What it means

    • The authors conclude that they have provided a validated and practical framework for extracting phenolic antioxidants from black rice bran at a pilot-plant scale. View evidence ↗

      What it means

      The authors conclude that they have provided a validated and practical framework for extracting phenolic antioxidants from black rice bran at a pilot-plant scale.

      In the paper's own words

      “These findings provide a practical, validated framework for pilot-plant extraction of phenolic antioxidants from black rice bran.”

      Page 3

      Found in: Conclusion

      Read it in the full textOpen PDF at page 3 ↗
    • The authors recommend future work on extract stability during storage and scaling trials using continuous flow extractors before the process is applied commercially. View evidence ↗

      What it means

      The authors recommend future work on extract stability during storage and scaling trials using continuous flow extractors before the process is applied commercially.

      In the paper's own words

      “Scaling trials with continuous flow extractors and assessment of extract stability during storage are recommended as next steps before commercial application.”

      Page 3

      Found in: Conclusion

      Read it in the full textOpen PDF at page 3 ↗

Visual summary

2 visuals

Illustrations explain the paper; charts are replotted from the paper's own table values.

AI-generated illustration
AI-generated conceptual illustration (black rice bran). It explains the idea and does not show study data.↗ Enlarge
RSM-CCD Optimization Workflow
AI-generated conceptual illustration (black rice bran). It explains the idea and does not show study data.

AI-generated conceptual illustration (black rice bran). It explains the idea and does not show study data.

Open full-size image ↗

RSM-CCD Optimization Workflow

AI-generated conceptual illustration (black rice bran). It explains the idea and does not show study data.

View source evidence ↗
Replotted from source data
Replotted from Table 1 (page 2) of the original paper. Every bar is the paper's own table value.↗ Enlarge
Contrib. (%) / -: X₁ (Temp) vs X₂ (Time) vs X₃ (Ratio)
Replotted from Table 1 (page 2) of the original paper. Every bar is the paper's own table value.

Replotted from Table 1 (page 2) of the original paper. Every bar is the paper's own table value.

Open full-size image ↗

Contrib. (%) / -: X₁ (Temp) vs X₂ (Time) vs X₃ (Ratio)

Replotted from Table 1 (page 2) of the original paper. Every bar is the paper's own table value.

View source evidence ↗

Figures & tables

From the original paper
ANOVA results for the second-order polynomial modelTable 1Page 2Predicted and experimental values at optimum extraction conditions (68 °C, 54 min, 1:22 ratio)Table 2Page 2Scatter plot showing total phenolic content as a function of extraction temperature, with bubble size  proportional to TPC and colorFigure 1Page 2Schematic of the RSM-based extraction optimization process from bran preparation through response measurement to optimumFigure 2Page 3
FULL TEXT Original article · reflowed for reading

Introduction

Black rice varieties owe their dark pigmentation to high concentrations of anthocyaninswater-soluble flavonoids that accumulate primarily in the bran and aleurone layers [1] . Among Thai cultivars, Riceberry has attracted particular attention because its bran contains 3 to 5 times more phenolic compounds than conventional white or brown rice bran [2] . These compounds exhibit strong antioxidant, anti-inflammatory, and anti-diabetic properties in cellculture and animal models [3] . Recovering phenolics from rice bran at high yield and consistent quality requires careful control of extraction variables. Temperature drives diffusion and solubility but can degrade heat-sensitive anthocyanins above 75-80 °C [4] . Longer extraction times improve mass transfer up to a point, beyond which oxidation and polymerization reduce the measurable TPC [5] . The solvent-to-solid ratio affects the concentration gradient-the driving force for extraction-but excessive solvent volumes add cost and complicate downstream concentration steps [6] . One-factor-at-a-time experiments cannot capture interactions among these variables. Response surface methodology (RSM) based on a central composite design (CCD) allows simultaneous evaluation of multiple factors and their quadratic and interaction effects, generating a predictive model that identifies the global optimum within the design space [7] . RSM has been applied successfully to optimize phenolic extraction from grape pomace, olive leaves, and wheat bran, but reports specifically targeting Thai black rice bran remain scarce [8] . This research aimed to (i) model the effects of temperature, time, and solvent ratio on TPC extraction from Riceberry bran using RSM-CCD, (ii) identify the optimum extraction conditions, and (iii) characterize the antioxidant activity of the extract obtained under optimized conditions.

Materials and Methods

Materials and Methods

Materials

Riceberry black rice bran was obtained from the university's pilot rice mill at Southern Thai Agricultural University, Songkhla (7.00°N, 100.47°E), immediately after milling in March 2023. The bran was sieved through a 40-mesh screen, packed under nitrogen, and stored at -20 °C until use. Ethanol (analytical grade, 99.8%) was purchased from RCI Labscan (Bangkok, Thailand). Folin-Ciocalteu reagent, gallic acid, quercetin, DPPH (2,2-diphenyl-1picrylhydrazyl), ABTS (2,2′-azino-bis(3ethylbenzothiazoline-6-sulfonic acid)), and Trolox were sourced from Sigma-Aldrich (Singapore).

Extraction Protocol

Each extraction run used 5.0 g of bran mixed with 70 percent aqueous ethanol at the designated solvent-to-solid ratio. The mixture was placed in a thermostatically controlled shaking water bath (Memmert WNB 22, Germany) at the specified temperature and time. After extraction, samples were centrifuged at 4,000 × g for 15 min, and the supernatant was filtered through Whatman No. 1 paper. The filtrate was stored at 4 °C and analysed within 24 hours. All runs were performed in duplicate.

Methods

A three-factor, five-level CCD with six centre-point replicates was used, generating 20 experimental runs. The independent variables were temperature (X₁: 40-80 °C), time (X₂: 30-90 min), and solvent-to-solid ratio (X₃: 1:10-1:30 v/w). TPC was measured using the Folin-Ciocalteu method [9] and expressed as mg GAE/g. Total flavonoid content (TFC) was determined by the aluminium chloride method [10] . DPPH and ABTS radical scavenging assays followed the protocols of Brand-Williams et al. [11] and Re et al. [12] , respectively. Data were fitted to a second-order polynomial model and analysed using Design-Expert 13.0 (Stat-Ease, Minneapolis, USA). Model adequacy was assessed through R², adjusted R², predicted R², lack-of-fit test, and coefficient of variation. Verification experiments at predicted optimum conditions were run in triplicate. The model was highly significant (p<0.001) with an R² of 0.964 and an adjusted R² of 0.931, indicating that 96.4 percent of the variation in TPC was explained by the fitted model. The lack-of-fit test was non-significant (p = 0.218), confirming adequate model prediction. Temperature was the dominant factor (38.4% contribution), followed by time (27.1%) and the quadratic term of temperature (11.6%).

Results

Results

Discussion

The optimum extraction temperature of 68 °C sits well below the anthocyanin degradation threshold of 75-80 °C reported for purple rice extracts [4] , explaining why TPC was maximized at this point rather than at the highest tested temperature. The decline in TPC at 80 °C (about 9% lower than at 68 °C) aligns with first-order degradation kinetics of cyanidin-3-glucoside, the dominant anthocyanin in Riceberry bran [2] . The optimal time of 54 min represents a balance between diffusion-driven extraction and oxidation losses. Extending extraction beyond 60 min at 68 °C didn't improve TPCsimilar plateau effects have been observed in phenolic extraction from blueberry pomace [5] and olive mill waste [6] . The moderate solvent ratio (1:22) reflects a compromise: sufficient ethanol to maintain the concentration gradient without the economic burden of large solvent volumes.

Compared with published data on other pigmented rice brans, the TPC of 43.1 mg GAE/g obtained here is higher than values reported for Indonesian black rice bran (28.6 mg GAE/g) extracted with 60 percent methanol [8] and comparable to those from Chinese purple rice bran (39.7 mg GAE/g) optimized by ultrasound-assisted extraction [13] . The 70 percent ethanol system used in the present research offers a food-safe solvent choice suitable for pilot-scale processing.

Conclusion

This research established an optimized extraction protocol for phenolic compounds from Riceberry black rice bran.

Response surface modelling identified 68 °C, 54 min, and a 1:22 solvent-to-solid ratio with 70 percent ethanol as the conditions yielding the highest TPC (43.1 mg GAE/g).

Temperature was the single most important variable, contributing 38.4 percent of the total variation, while the temperature × time interaction accounted for an additional 4.7 percent. The optimized extract showed strong antioxidant activity-87.3 percent DPPH and 91.6 percent ABTS radical scavenging-confirming that the recovered phenolics retain their bioactive properties under the selected conditions.

These findings provide a practical, validated framework for pilot-plant extraction of phenolic antioxidants from black rice bran. The protocol uses a food-grade solvent, operates at moderate temperature, and achieves high yield within a practical extraction time. Scaling trials with continuous flow extractors and assessment of extract stability during storage are recommended as next steps before commercial application.

Figures and tables from the paper

Table 1. ANOVA results for the second-order polynomial model
SourceSSdfMSF-valuep-valueContrib. (%)
Model1847.39205.329.7<0.001-
X₁ (Temp)709.61709.6102.8<0.00138.4
X₂ (Time)500.81500.872.5<0.00127.1
X₃ (Ratio)198.41198.428.7<0.00110.7
X₁×X₂87.3187.312.60.0054.7
X₁²214.11214.131.0<0.00111.6
X₂²68.9168.910.00.0103.7
Residual69.1106.9---
Lack of Fit47.859.62.20.218-
Pure Error21.354.3---

Table text extracted from the original PDF; superscript letters are shown inline. The original table image is below.

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ANOVA results for the second-order polynomial model↗ Enlarge
Table 1
ANOVA results for the second-order polynomial model

ANOVA results for the second-order polynomial model

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Original paper tableSource PDF · page 2 ↗
Table 2. Predicted and experimental values at optimum extraction conditions (68 °C, 54 min, 1:22 ratio)
ResponsePredictedExperimentalDeviation (%)
TPC (mg GAE/g)42.143.1 ± 1.62.3
TFC (mg QE/g)-18.9 ± 0.8-
DPPH scavenging (%)-87.3 ± 2.1-
ABTS scavenging (%)-91.6 ± 1.4-

Table text extracted from the original PDF; superscript letters are shown inline. The original table image is below.

View original table image
Predicted and experimental values at optimum extraction conditions (68 °C, 54 min, 1:22 ratio)↗ Enlarge
Table 2
Predicted and experimental values at optimum extraction conditions (68 °C, 54 min, 1:22 ratio)

Predicted and experimental values at optimum extraction conditions (68 °C, 54 min, 1:22 ratio)

Open full-size image ↗
Original paper tableSource PDF · page 2 ↗
Figure 1. Scatter plot showing total phenolic content as a function of extraction temperature, with bubble size proportional to TPC and color
Scatter plot showing total phenolic content as a function of extraction temperature, with bubble size  proportional to TPC and color↗ Enlarge
Figure 1
Scatter plot showing total phenolic content as a function of extraction temperature, with bubble size  proportional to TPC and color

Scatter plot showing total phenolic content as a function of extraction temperature, with bubble size proportional to TPC and color

Open full-size image ↗
Original paper figureSource PDF · page 2 ↗
Figure 2. Schematic of the RSM-based extraction optimization process from bran preparation through response measurement to optimum
Schematic of the RSM-based extraction optimization process from bran preparation through response measurement to optimum↗ Enlarge
Figure 2
Schematic of the RSM-based extraction optimization process from bran preparation through response measurement to optimum

Schematic of the RSM-based extraction optimization process from bran preparation through response measurement to optimum

Open full-size image ↗
Original paper figureSource PDF · page 3 ↗

References

14 in the original paper
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