# Selective Extraction of Cannabinoid Compounds from Cannabis Seed Using Pressurized Hot Water Extraction

^{*}

## Abstract

**:**

## 1. Introduction

_{2,}water is used under its supercritical form as a solvent that exhibits the same solvability properties as methanol and ethanol [21]. Pressurized hot water extraction has proved to be an excellent approach for the recovery of the polar and semi-polar bioactive compounds from plant materials [21,22]. PHWE technique is based on the use of high temperature and pressure to keep the water in the supercritical fluid form during the entire extraction process [23]. The technique has attracted attention due to its benefits as compared to other conventional and non-conventional extraction approaches [21]. PHWE has been widely used for the extraction of phenolic compounds [24]. In this technique, temperature is very important; it directly affects extraction efficiency and the mass transfer during the extraction process [25,26].

_{2}and pressure for an efficient extraction of CBD. The results showed that the solubility of cannabinoids compounds increase with the increase of the pressure. To our knowledge, there are no studies that have applied PHWE for selective extraction of cannabinoid compounds from Cannabis L Sativa seeds. Therefore, the present study includes a pressurized hot water extraction process that yields a formulated cannabinoid nutraceutical. The PHWE technique was applied to cannabis seed in order to extract more CBD and lessen the THC and CBN, reducing the psycho-activity of cannabis products.

## 2. Materials and Methods

#### 2.1. Chemicals and Reagents

#### 2.2. Plant Material

#### 2.3. Response Surface Methodology

^{−1}, respectively, according to our previous work [24]. The partial least square regression was applied to evaluate the fitting of the model and response surface. The adequacy of the models was evaluated by the R

^{2}and Q

^{2}values (where R

^{2}shows the model fit and Q

^{2}shows an estimate of the future prediction precision). The F-test was used to assess the significance of the coefficients of regression. The modeling was done with a quadratic model like linear, squared, and interaction terms.

#### 2.4. Pressurized Hot Water Extraction

#### 2.5. GCXGC-TOFMS Method

^{−1}. The oven temperature was set at 100 °C (for 2 min) and increased to 280 °C with rate of 15 °C min

^{−1}. Temperatures applied were 300 °C for injector, 250 °C for transfer line, 250 °C for ion source, and 150 °C for quadrupole. Data were acquired in the full scan mode with mass ranging from 45–600 amu. The total ion chromatograms (TIC) were integrated. Raw data (m/z) generated by UHPSFC were processed using the ChromaTOF software version 4.5.1. (LECO Corp, St. Joseph, MI, USA).

#### 2.6. Quality Assurance

#### 2.7. Model Fitting and Predictive Efficiency

^{2}), and correlation coefficients (R

^{2}). The equations used to calculate these factors are described in Table 2.

## 3. Results and Discussion

#### 3.1. Identification of Cannabinoid Compounds

#### 3.2. Experimental Design: Response Surface Methodology

^{2}= 0.96–0.99) and a cross-validated predictability ranged from 95–99% (Q

^{2}= 0.95 – 0.99), where R

^{2}shows the model fit and Q

^{2}shows an estimation of the future prediction and precision [24]. The linearity of the predicted vs. observed values plot (Figure 5) highlighted the validity of the model and its capability to predict the best condition of the extraction within the range of the design. The coefficients plot (Figure 6) reveals that collector vessel temperature, extraction temperature and time have a significant negative influence on the extracted amount of Tetrahydrocannabinol (THC) and Cannabinol (CBN) with a p-value of 0.003, whereas extraction time has shown a significant positive influence on the amount extraction of cannabidiol (CBD), cannabichromene (CBG) and cannabigerol (CBC).

#### 3.3. Model Fitting and Predictive Efficiency Analysis

^{2}) have been assessed by equations (described in Table 2. The obtained results of the statistical analysis are shown in Table 3.

#### 3.4. Universal Extraction Condition of an Extract rich in CBD, CBC, and CBG

## 4. Conclusions

^{2}, and R

^{2}have shown that RSM is an excellent statistical tool in terms of prediction and estimation capabilities. The optimization of the PHWE process by RSM predicted that the ratio between THCt (THC + CBN) portion and CBDt (CBD + CBC+ CBG) portion was 0.17 under optimum conditions of 150 °C, 160 °C and 45 min for extraction temperature, collector vessel temperature and extraction time, respectively, which means that the final extract at the optimal condition has higher amounts of CBD, CBC and CBG than THC and CBN. To conclude, the optimization of PHWE using the RSM approach provides an effective guideline for an extraction process that yields a formulated cannabinoid nutraceutical. The PHWE technique has produced Cannabis sativa extract with high amounts of non-psychoactive compounds and lower levels of THC and CBN.

## Author Contributions

## Funding

## Conflicts of Interest

## References

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Sample Availability: Cannabis samples are available from the authors. |

**Figure 1.**Pressurized hot water extraction setup with showing trap solution and oil heat bath for collector.

Run Order | Extraction Time (min) | Extraction Temp. (°C) | Collector Temp.(°C) | THC (%) | CBD (%) | CBC (%) | CBG (%) | CBN (%) |
---|---|---|---|---|---|---|---|---|

19 | 15 | 80 | 25 | 0.5700 | 0.2989 | 0.2033 | 0.1345 | 0.1308 |

25 | 37.5 | 80 | 25 | 0.7900 | 0.4589 | 0.3121 | 0.2065 | 0.1812 |

7 | 60 | 80 | 25 | 0.9584 | 0.8978 | 0.6105 | 0.4040 | 0.2204 |

1 | 15 | 80 | 113 | 0.3989 | 0.2890 | 0.1965 | 0.1301 | 0.0917 |

4 | 37.5 | 80 | 113 | 0.9088 | 0.4556 | 0.3098 | 0.2050 | 0.2091 |

9 | 60 | 80 | 113 | 0.4278 | 0.8926 | 0.6070 | 0.4017 | 0.0984 |

21 | 15 | 80 | 200 | 0.2078 | 0.2699 | 0.1835 | 0.1215 | 0.0478 |

5 | 37.5 | 80 | 200 | 0.1889 | 0.3174 | 0.2158 | 0.1428 | 0.0435 |

18 | 60 | 80 | 200 | 0.1089 | 0.3878 | 0.2637 | 0.1745 | 0.0251 |

12 | 15 | 140 | 25 | 3.1504 | 1.4589 | 0.9921 | 0.6565 | 0.7246 |

10 | 37.5 | 140 | 25 | 2.8062 | 2.9819 | 2.0277 | 1.3419 | 0.6454 |

29 | 60 | 140 | 25 | 1.8639 | 3.7532 | 2.5522 | 1.6889 | 0.4287 |

15 | 15 | 140 | 113 | 1.4193 | 6.3856 | 4.3422 | 2.8735 | 0.3264 |

16 | 37.5 | 140 | 113 | 1.3032 | 7.0702 | 4.8077 | 3.1816 | 0.2997 |

20 | 60 | 140 | 113 | 1.0187 | 9.9046 | 6.7351 | 4.4571 | 0.2343 |

6 | 15 | 140 | 200 | 0.9537 | 1.0347 | 0.7036 | 0.4656 | 0.2194 |

2 | 37.5 | 140 | 200 | 0.6547 | 1.8502 | 1.2581 | 0.8326 | 0.1506 |

30 | 60 | 140 | 200 | 0.5809 | 2.9506 | 2.0064 | 1.3278 | 0.1336 |

11 | 37.5 | 140 | 113 | 0.7637 | 6.9309 | 4.9930 | 4.3189 | 0.1757 |

27 | 37.5 | 140 | 113 | 0.8428 | 5.6506 | 5.0824 | 3.1928 | 0.1938 |

14 | 37.5 | 140 | 113 | 0.6904 | 7.8078 | 5.5893 | 4.7135 | 0.1588 |

17 | 15 | 200 | 25 | 0.1444 | 0.1229 | 0.0836 | 0.0553 | 0.0332 |

23 | 37.5 | 200 | 25 | 0.1015 | 0.3353 | 0.2280 | 0.1509 | 0.0233 |

22 | 60 | 200 | 25 | 0.0927 | 0.4536 | 0.3085 | 0.2041 | 0.0213 |

8 | 15 | 200 | 113 | 0.0702 | 0.1099 | 0.0747 | 0.0495 | 0.0162 |

26 | 37.5 | 200 | 113 | 0.0497 | 0.1653 | 0.1124 | 0.0744 | 0.0114 |

3 | 60 | 200 | 113 | 0.0312 | 0.2221 | 0.1510 | 0.0999 | 0.0072 |

13 | 15 | 200 | 200 | 0.0201 | 0.0384 | 0.0261 | 0.0173 | 0.0046 |

24 | 37.5 | 200 | 200 | 0.0148 | 0.0407 | 0.0277 | 0.0183 | 0.0034 |

28 | 60 | 200 | 200 | 0.0105 | 0.0751 | 0.0511 | 0.0338 | 0.0024 |

Error | Equation |
---|---|

Absolute average deviation | $\mathrm{AAD}=\left[\frac{{{\displaystyle \sum}}_{i=1}^{n}\left(\raisebox{1ex}{$\left(\left|{Y}_{iexp}-{Y}_{ical}\right|\right)$}\!\left/ \!\raisebox{-1ex}{${Y}_{iexp}$}\right.\right)}{n}\right]$ |

Root mean square error | RMSE $=\sqrt{\frac{{{\displaystyle \sum}}_{\mathrm{i}=1}^{\mathrm{n}}{\left({\mathrm{Y}}_{\mathrm{i},\mathrm{e}}-{\mathrm{Y}}_{\mathrm{i},\mathrm{p}}\right)}^{2}}{\mathrm{n}}}$ |

Mean absolute error | $\mathrm{MAE}=\frac{\mathrm{i}}{\mathrm{n}}{\displaystyle \sum}_{\mathrm{i}=1}^{\mathrm{n}}\left|{\mathrm{Y}}_{\mathrm{i},\mathrm{e}}-{\mathrm{Y}}_{\mathrm{i},\mathrm{p}}\right|$ |

Standard error of prediction (%) | SEP$(\%)=\frac{\mathrm{RMSE}}{{\mathrm{Y}}_{\mathrm{i},\mathrm{e}}}\times 100$ |

Model predictive error (%) | MPE$(\%)=\frac{100}{\mathrm{n}}{\displaystyle \sum}_{\mathrm{i}=1}^{\mathrm{n}}\left|\frac{{\mathrm{Y}}_{\mathrm{i},\mathrm{e}}-{\mathrm{Y}}_{\mathrm{i},\mathrm{p}}}{{\mathrm{Y}}_{\mathrm{i},\mathrm{p}}}\right|$ |

Chi-square (χ^{2}) | ${\mathsf{\chi}}^{2}={\displaystyle \sum}_{\mathrm{i}=1}^{\mathrm{n}}\frac{{\mathrm{Y}}_{\mathrm{i},\mathrm{p}}-{\mathrm{Y}}_{\mathrm{i},\mathrm{e}}}{{\mathrm{Y}}_{\mathrm{i},\mathrm{p}}}$ |

Correlation R^{2} | ${\mathrm{R}}^{2}=\frac{{{\displaystyle \sum}}_{\mathrm{i}=1}^{\mathrm{n}}\left({\mathrm{Y}}_{\mathrm{i},\mathrm{p}}-{\mathrm{Y}}_{\mathrm{i},\mathrm{e}}\right)}{{{\displaystyle \sum}}_{\mathrm{i}=1}^{\mathrm{n}}{\left({\mathrm{Y}}_{\mathrm{i},\mathrm{p}}-{\mathrm{Y}}_{\mathrm{i},\mathrm{e}}\right)}^{2}}$ |

^{2}: Chi-square statistic, R

^{2}: Correlation coefficients.

**Table 3.**Statistical results of response surface methodology model fitting and predictive efficiency analysis.

Parameter | THC | CBD | CBC | CBG | CBN |
---|---|---|---|---|---|

AAD | 0.0067 | 0.0036 | 0.0021 | 0.0018 | 0.0014 |

RMSE | 0.0400 | 0.0300 | 0.0600 | 0.0800 | 0.0700 |

MAE | 0.0050 | 0.0020 | 0.0010 | 0.0020 | 0.0010 |

SEP | 0.0120 | 0.0210 | 0.0140 | 0.0160 | 0.0190 |

MPE | 0.0290 | 0.0160 | 0.0080 | 0.0090 | 0.0040 |

χ^{2} | 0.0005 | 0.0002 | 0.0005 | 0.0003 | 0.0009 |

Responses | Predicted Values | Experimental Value (n = 3) | Repeatability (%RSD) | Reproducibility (%RSD) |
---|---|---|---|---|

THC | 2.00 | 2.03 ± 0.20 | 90.23 ± 2.45 | 89.78 ± 2.34 |

CBD | 5.40 | 5.60 ± 0.35 | 89.45 ± 2.87 | 91.34 ± 1.32 |

CBC | 4.50 | 5.00 ± 0.60 | 92.45 ± 3.71 | 89.70 ± 5.60 |

CBG | 3.50 | 4.10 ± 0.80 | 90.56 ± 3.56 | 92.56 ± 2.31 |

CBN | 2.90 | 0.34 ± 0.09 | 92.61 ± 4.5 | 90.78 ± 2.19 |

THCt ^{*}/CBDt ^{*} | 0.17 | 0.18 | - | - |

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**MDPI and ACS Style**

Nuapia, Y.; Tutu, H.; Chimuka, L.; Cukrowska, E.
Selective Extraction of Cannabinoid Compounds from Cannabis Seed Using Pressurized Hot Water Extraction. *Molecules* **2020**, *25*, 1335.
https://doi.org/10.3390/molecules25061335

**AMA Style**

Nuapia Y, Tutu H, Chimuka L, Cukrowska E.
Selective Extraction of Cannabinoid Compounds from Cannabis Seed Using Pressurized Hot Water Extraction. *Molecules*. 2020; 25(6):1335.
https://doi.org/10.3390/molecules25061335

**Chicago/Turabian Style**

Nuapia, Yannick, Hlanganani Tutu, Luke Chimuka, and Ewa Cukrowska.
2020. "Selective Extraction of Cannabinoid Compounds from Cannabis Seed Using Pressurized Hot Water Extraction" *Molecules* 25, no. 6: 1335.
https://doi.org/10.3390/molecules25061335