Optimization of Spray Drying Process for Syringa Leaf Extract via Plackett-Burman Combined With Box-Behnken Method

Abstract

Objective

Syringa leaf extract (SLE) is a promising green feed additive with antibacterial and anti-inflammatory activities, mainly attributed to its main bioactive component tyrosol. However, its large-scale application is limited by the lack of an optimized spray drying process that ensures both process efficiency and tyrosol stability.

Methods

This study optimized the spray drying process of SLE with powder yield and moisture content as core indicators, using maltodextrin as a carrier material. Plackett-Burman (PB) design screened inlet air temperature, atomization frequency and feeding speed as key factors from six parameters. Box-Behnken design (BBD) combined with response surface methodology was then used for further optimization, and thermogravimetric analysis verified the thermal stability of tyrosol, the main bioactive component of SLE. The optimized process was validated by determining the angle of repose, solubility, dispersibility, and tyrosol content.

Results

The optimal parameters were determined as inlet air temperature 163°C, atomization frequency 349Hz and feeding speed 17 r·min^-1, under which three verification batches yielded an average powder yield of 82.8% and moisture content of 2.19%, consistent with model predictions. Tyrosol was stable below 225.1°C, matching the spray drying temperature range. Physical property tests confirmed excellent flowability, solubility and dispersibility of the optimized SLE powder, and tyrosol content determination in nine batches showed a coefficient of variation of 4.38%, indicating good process stability.

Conclusion

The spray drying process optimized by the PB combined with Box-Behnken method is stable, feasible, and reproducible, which can provide a scientific reference for the large-scale preparation production of SLE.

Keywords

Plackett-Burman method Box-Behnken method spray drying process green feed additive

1. Introduction

Antibiotics have been widely used in the global animal husbandry due to their properties of promoting livestock and poultry growth and preventing diseases. Approximately 80% of antibiotics sold in the U.S. market alone are used in animal husbandry.¹ However, the overuse of antibiotics gives rise to a series of severe issues, including bacterial resistance, adverse impacts on human health, and environmental residues. Against this backdrop, China attaches great importance to the governance of food safety and animal-derived food safety, and has actively promoted the transformation towards “antibiotic prohibition” and “antibiotic reduction” in the breeding sector. In 2020, China issued Announcement No. 194, explicitly stipulating that starting from July 1, 2020, feed manufacturers shall cease the production of commercial feed containing growth-promoting pharmaceutical feed additives (excluding Chinese herbal medicines),² thus officially implementing the full-chain control policy of “antibiotic prohibition in feed, antibiotic reduction in breeding, and antibiotic-free in food”. At present, the traditional Chinese veterinary medicines approved by the Ministry of Agriculture and Rural Affairs for long-term addition to commercial feed only include Macleaya cordata Powder, Scutellaria shanhua Extract Powder, Ligustrum lucidum Extract Powder, Callicarpa Nudiflora Powder, Qihuang Wengbai Powder and other products, which are far from meeting the demand of the livestock and poultry market.

After the ban on antibiotics, the livestock and poultry breeding industry is confronted with numerous challenges. Problems such as increased incidence of diseases in pigs and poultry, rising production costs, and declining production performance have become prominent.^3,4 For farms relying on antibiotics to control digestive tract diseases in rabbits, the incidence of digestive tract diseases in rabbits has increased significantly after the feed antibiotic ban, accompanied by a rise in the mortality rate of young rabbits and a decrease in the feed conversion rate of commercial rabbits.⁵ In addition, the incidence of various reproductive system diseases and respiratory diseases in breeding rabbits has also increased obviously, leading to a significant rise in the mortality and elimination rates.⁶ How to reduce the incidence of diarrhea in suckling piglets, poultry, rabbits and other animals, while improving the feed conversion rate to reduce digestive diarrhea, has become an urgent problem to be solved for feed enterprises.

Syringa leaf extract is a natural product prepared from the dried leaves of Syringa oblata Lindley, Syringa dilatata Nakai and its subspecies Syringa oblata subsp. oblata Lindley of the Oleaceae family through extraction, impurity removal, concentration, and spray drying. In traditional Chinese medicine, Syringa leaves are bitter in taste and cold in nature, attributing to the liver, lung, and large intestine meridians. They possess the effects of clearing heat and detoxifying, promoting diuresis and relieving jaundice, and are mainly used for treating acute dysentery, icteric hepatitis, conjunctivitis, and other conditions.⁷ Syringa leaf extract contains a variety of bioactive components, including sesquiterpenes, hydroxycinnamoyl derivatives, secoiridoids, secoiridoid glycosides, phenolic compounds, lignans, and phenylpropanoids, which endow it with broad-spectrum antibacterial, anti-inflammatory, and antidiarrheal activities. It is widely used in the prevention and treatment of enteritis, bacillary dysentery, acute gastroenteritis, upper respiratory tract infections, and other diseases in livestock and poultry.⁸

Tyrosol (p-hydroxyphenylethanol, p-HPEA) is a phenol compound that exerts anti-inflammatory, antitumor, antibacterial, and antidiarrheal activities, which are highly consistent with the traditional therapeutic effects of Syringa leaves.⁹ Its mechanism of action may be related to the inhibition of the NF-κB pathway to reduce the levels of reactive oxygen species (ROS) and inflammatory factors.¹⁰Chemically, tyrosol is a stable small-molecule phenolic alcohol with excellent thermal and pH tolerance, resisting enzymatic and oxidative degradation during extraction, preparation, and storage to ensure reliable quantification.¹¹ From a quality control perspective, tyrosol meets the core criteria of specificity, efficacy, and measurability as a quality marker, supporting the standardization and international application of Folium syringae extracts.¹² In summary, tyrosol outperforms protocatechuic acid and syringopicroside in pharmacodynamic representativeness, quantitative stability, and quality control applicability, providing a robust scientific basis for ensuring batch-to-batch consistency and clinical efficacy of Folium syringae preparations.

At present, most of the research on process optimization of Syringa leaf extract adopts orthogonal test design. Although some literatures have attempted to apply response surface methodology,^13,14 they generally suffer from limitations such as a small number of investigated factors and failure to fully reveal the interactions between parameters. In contrast, the Plackett-Burman (PB) test design can more efficiently screen out key influencing factors from multiple variables.¹⁵ On this basis, combining with the Box-Behnken response surface methodology to perform polynomial fitting on the key factors and realize process parameter optimization through regression equation analysis. This research strategy combining PB screening design with Box-Behnken response surface optimization¹⁶ can more comprehensively investigate the interactions between process parameters compared with a single orthogonal test or response surface design, significantly improving the efficiency of process optimization. In this study, the thermal stability verification was conducted to lay the foundation for the applicability of the process, and the spray drying process of Syringa leaf extract was optimized by combining the PB experiment with the Box-Behnken response surface methodology, aiming to provide technical support for its clinical application and industrial production.

2. Materials and Methods

2.1. Instruments

Centrifugal spray dryer (Model: PESD-150, Wuxi Kaiyide Drying Equipment Co., Ltd.); Multifunctional extraction tank (Model: 3000L-DN1200, Zhejiang Tianlian Machinery Co., Ltd.); Thermogravimetric analyzer (NETSCH STA 449F3, Germany); AKF-2010V Intelligent Karl Fischer Moisture Titrator (Shanghai Ben’ang Scientific Instruments Co., Ltd.); PT-X powder comprehensive analyzer (Hikari Micron Group Co., Ltd.); Mastersizer 3000 laser particle size analyzer (UK Malvern Instruments Co., Ltd.); YP5002 Electronic Balance (Shanghai Hengji Scientific Instruments Co., Ltd.).

2.2. Materials and Reagents

Syringa leaf decoction pieces were purchased from Yuzhou Baicaoyuan Decoction Pieces Co., Ltd. (Place of origin: Chaoyang, Liaoning), and were identified as qualified by Professor Ji Peng from the Traditional Chinese Veterinary Medicine Teaching and Research Section, College of Veterinary Medicine, Gansu Agricultural University. Syringa leaf reference substance (Batch No. 121253-200301) and tyrosol reference substance (Batch No. 111676-200602) were both purchased from the National Institutes for Food and Drug Control. Maltodextrin was purchased from Xiwang Pharmaceutical Co., Ltd. (Executive standard: the 4th Volume of Pharmacopoeia of the People’s Republic of China (2020 Edition)).The Syringa leaf extract powder, specification: 1g of crude drug per 1ml. Batch numbers: 230301,230302,230303,230401,230402,230403, produced by Henan Muxiang Biological Co., Ltd.

2.3. Preparation of Syringa Leaf Extract

An appropriate amount of qualified identified Syringa leaf decoction pieces was taken and extracted by the water decoction method. For the first extraction, 12 times the amount of water was added and decocted for 2 hours; for the second extraction, 10 times the amount of water was added and decocted for 2 hours. The two decoctions were combined and filtered. The filtrate was concentrated under reduced pressure (-0.06MPa, 88°C) to an extract with a relative density of 1.05 - 1.10 (at 60°C), and stored at 4°C under refrigeration for later use.

2.4. Thermal Stability of Tyrosol

Spray drying technology is suitable for products with good thermal stability. To examine whether Syringa leaf extract is suitable for preparation production using spray drying technology, the thermal stability of tyrosol, the main component of Syringa leaf extract, was first studied. A thermogravimetric analyzer was used to record the thermal weight loss process of tyrosol.

2.5. Single-Factor Investigation of Spray Drying Parameters

To determine the rational investigation ranges of spray drying process parameters and provide a scientific basis for the subsequent Plackett-Burman screening design, single-factor experiments were systematically conducted with powder yield, moisture content, and tyrosol content as the core evaluation indicators. The fixed conditions for single-factor experiments were set as follows: inlet air temperature 170°C, atomization frequency 275 Hz, feeding speed 20 r/min, extract density 1.08 g/cm³ (60°C), extract temperature 50°C, maltodextrin addition ratio 1:4 (dry matter basis), and air hammer tapping frequency 15 s/time. Only one investigated parameter was adjusted for each experimental group, with 3 parallel replicates for each group. The detailed parameter settings were as follows: Inlet air temperature: Set to 130°C, 150°C, 170°C, 190°C, 210°C, respectively. Atomization frequency: Set to 150 Hz, 200 Hz, 275 Hz, 350 Hz, 400 Hz, respectively. Feeding speed: Set to 10 r/min, 15 r/min, 20 r/min, 25 r/min, 30 r/min, respectively. Extract temperature: Set to 25°C, 40°C, 50°C, 60°C, 70°C, respectively, controlled by water bath preheating. Extract density: Adjusted to 1.00 g/cm³, 1.05 g/cm³, 1.10 g/cm³, 1.15 g/cm³, 1.20 g/cm³ (measured at 60°C) via vacuum concentration or water dilution. Air hammer tapping frequency: Set to 5 s, 10 s, 15 s, 20 s, 30 s per cycle (interval time), respectively.

2.6. Plackett-Burman Experiment Design and Implementation

Based on the results of single-factor preliminary experiments, Design-Expert 12 software was used to design the PB experiment to investigate 6 factors affecting the powder formation of the extract, including inlet air temperature, atomization frequency, feeding speed, extract density, extract temperature, and air hammer tapping frequency. Each influencing factor was set at two levels, denoted as high level (1) and low level (-1), with the powder yield as the evaluation index. The factor levels, experimental design and results, and model analysis of variance are detailed in the Results section.

2.7. Box-Behnken Response Surface Experimental Design

Based on the results of the PB experiment, factor A (inlet air temperature, °C), factor B (atomization frequency, Hz), and factor C (feeding speed, r/min) were selected for analysis, with powder yield (Y1) and moisture content (Y2) as the response values. Design-Expert 12 software was used for response surface design, and each of the 3 factors was set at three levels: high, medium, and low, represented by 1, 0, and -1 respectively. The factor levels, experimental design and results, and model analysis of variance are detailed in the Results section.

2.8. Verification Test Implementation

The optimized optimal spray drying parameters obtained through the Box-Behnken experiment analysis by Design-Expert 12 software were as follows: inlet air temperature of 163°C, atomization frequency of 349Hz, and feeding speed of 17r/min, under which the optimal results were achieved. The predicted powder yield was 82.9% and the moisture content was 2.15%. Three batches of spray drying verification tests were conducted in parallel under the optimized optimal parameters to verify the powder yield and moisture content.

2.9. Measurement of Physical Indicators

The powder of Syringa leaves extracted by the best spray drying process was tested for the angle of repose, solubility and dispersibility.

2.10. Determination of the Main Component Indicators

The content of the main component of Syringa leaf extract powder, tyrosol, was determined in 3 small-scale samples (batch numbers: 230201,230202,230203) and 6 pilot-scale samples (batch numbers: 230301,230302,230303,230401,230402,230403) prepared by spray drying with the best parameters.

2.11. Statistical Analysis

All experimental data are expressed as mean ± standard deviation (SD). Design-Expert 12 software was used for Plackett-Burman design, Box-Behnken response surface methodology (RSM), and regression analysis. SPSS 26.0 software was employed for analysis of variance (ANOVA), and one-sample t-test to compare the differences between model-predicted values and measured values from verification experiments. The goodness-of-fit of the regression models was evaluated by the coefficient of determination (R²) and lack-of-fit test. A P-value < 0.05 was considered statistically significant for all analyses.

3. Results

3.1. Results and Analysis of Tyrosol Thermal Stability

The thermal stability of active components is a prerequisite for spray drying.¹⁷ As shown in Figure 1, The differential scanning calorimetry (DSC) curve of tyrosol showed an endothermic peak at 95.6°C, indicating that tyrosol was completely melted at this temperature. The thermogravimetry (TG) curve remained stable without any downward trend below 225.1°C, suggesting that tyrosol was in a stable state and did not undergo thermal decomposition during this period. When the temperature exceeded 225.1°C, tyrosol underwent violent thermal decomposition. With the continuous increase in temperature, the TG curve exhibited a steep weight loss step and dropped sharply, reaching the peak of thermal weight loss at 270.7°C. Therefore, the temperature range of 225.1°C to 271.7°C is the main thermal decomposition and weight loss stage of tyrosol, during which the decomposition was basically completed. The derivative thermogravimetry (DTG) curve indicated that tyrosol began to undergo thermal weight loss at 225.1°C, with a maximum thermal weight loss of -99.37%, which was caused by the thermal decomposition of tyrosol.

Figure 1.

Thermal stability curves of tyrosol (DSC: differential scanning calorimetry; TG: thermogravimetry; DTG: derivative thermogravimetry).

According to the performance index of the drying equipment, the spray drying temperature is generally lower than 220°C, at which tyrosol remains relatively stable. Thus, it is feasible to adopt the spray drying method for preparation production.¹⁸

3.2. Results of Single-Factor Parameter Investigation

3.2.1. Effect of Inlet Air Temperature on Spray Drying Performance

Inlet air temperature is a core parameter affecting the drying rate and thermal stability of the product. As shown in Table 1, powder yield increased significantly from 130°C to 170°C and decreased at 210°C, while moisture content declined continuously with rising temperature. Tyrosol content remained stable from 130–190°C but decreased significantly at 210°C due to thermal degradation. Accordingly, the suitable range for inlet air temperature was determined as 150–190°C.

Table 1.

Single-Factor Experimental Results of Inlet Air Temperature

Inlet air temperature(°C)	Powder yield rate(%)	Moisture content(%)	Tyrosol content(mg/g)
130	71.4 ± 1.2^d	5.62 ± 0.18^a	0.262 ± 0.005^a
150	78.9 ± 0.9^c	4.31 ± 0.12^b	0.265 ± 0.003^a
170	83.6 ± 0.7^a	3.04 ± 0.10^c	0.267 ± 0.004^a
190	81.2 ± 1.0^b	2.15 ± 0.08^d	0.261 ± 0.006^a
210	74.2 ± 1.3^d	1.28 ± 0.05^e	0.212 ± 0.008^b

Note. Different superscript letters in the same column indicate significant differences (P < 0.05, n = 3).

3.2.2. Effect of Atomization Frequency on Spray Drying Performance

The atomization frequency directly affects the droplet size distribution and drying efficiency. As shown in Table 2, powder yield increased and moisture content decreased with rising atomization frequency from 150 Hz to 350 Hz, but yield declined at 400 Hz because of fine powder loss. Tyrosol content was unaffected across all tested frequencies. The range for atomization frequency was set as 200–350 Hz.

Table 2.

Results of Single-Factor Experiments on Atomization Frequency

Atomization frequency(Hz)	Powder yield rate(%)	Moisture content(%)	Content of tyrosol(mg/g)
150	70.5 ± 1.1^d	4.98 ± 0.15^a	0.260 ± 0.004^a
200	76.3 ± 0.8^c	4.22 ± 0.11^b	0.262 ± 0.005^a
275	81.7 ± 0.9^b	3.41 ± 0.09^c	0.265 ± 0.003^a
350	83.1 ± 0.7^a	2.86 ± 0.07^d	0.263 ± 0.004^a
400	78.4 ± 1.0^c	2.51 ± 0.06^e	0.261 ± 0.005^a

Note. Different superscript letters in the same column indicate significant differences (P < 0.05, n =3).

3.2.3. Effect of Feeding Speed on Spray Drying Performance

The feeding speed determines the drying load per unit time in the drying chamber. As shown in Table 3, increasing feeding speed significantly reduced powder yield and raised moisture content, while tyrosol content remained unchanged. Excessively high feeding speed caused insufficient drying and wall adhesion. The range for feeding speed was determined as 15–30 r/min.

Table 3.

Results of Single-Factor Experiments on Feeding Speed

Feeding speed(r/min)	Powder yield rate(%)	Moisture content(%)	Content of tyrosol(mg/g)
10	82.6 ± 0.8^a	2.15 ± 0.06^e	0.266 ± 0.003^a
15	82.1 ± 0.7^a	2.63 ± 0.09^d	0.264 ± 0.005^a
20	80.5 ± 0.9^b	3.38 ± 0.10^c	0.263 ± 0.004^a
25	76.8 ± 1.0^c	4.21 ± 0.12^b	0.261 ± 0.006^a
30	71.3 ± 1.2^d	5.03 ± 0.14^a	0.262 ± 0.004^a

Note. Different superscript letters in the same column indicate significant differences (P < 0.05, n = 3).

3.2.4. Effect of Extract Temperature on Spray Drying Performance

The extract temperature affects the viscosity and atomization performance of the feed liquid. As shown in Table 4, powder yield increased from 25°C to 50°C and decreased at 70°C due to unstable atomization. Moisture content decreased slightly with rising temperature, and tyrosol content was stable. The suitable range for extract temperature was 30–60°C.

Table 4.

Results of Single-Factor Experiments on Extract Temperature

Extract temperature(°C)	Powder yield rate(%)	Moisture content(%)	Content of tyrosol(mg/g)	Observation of atomization phenomenon
25	77.5 ± 1.2^c	3.52 ± 0.11^a	0.264 ± 0.005^a	The feed liquid is viscous, resulting in uneven atomization and occasional clogging.
40	80.3 ± 0.9^b	3.31 ± 0.09^b	0.265 ± 0.004^a	Atomization is improved, and the droplet distribution is relatively uniform.
50	82.1 ± 0.8^a	3.18 ± 0.08^c	0.267 ± 0.003^a	Good atomization, little adhesion to the tower wall
60	81.5 ± 0.9^ab	3.09 ± 0.07^c	0.262 ± 0.005^a	Good atomization with slight hot steam generated
70	79.8 ± 1.1^b	2.98 ± 0.06^d	0.258 ± 0.006^a	Excessively fine atomization, slight powder escape, and steam present on the surface of the feed liquid

Note. Different superscript letters in the same column indicate significant differences (P < 0.05, n = 3).

3.2.5. Effect of Extract Density on Spray Drying Performance

The extract density determines the solid content of the feed liquid and affects the drying load and wall adhesion behavior. As shown in Table 5, powder yield peaked at 1.10 g/cm³ and decreased at lower or higher densities due to fine powder escape or severe wall adhesion. Moisture content decreased with increasing density, and tyrosol content remained stable. The range for extract density was set as 1.05–1.15 g/cm³.

Table 5.

Single-Factor Experimental Results of Extract Density

Extract density (g/cm³,60°C)	Powder yield rate(%)	Moisture content(%)	Content of tyrosol(mg/g)	Observation of drying phenomena
1.00	72.6 ± 1.3^e	3.92 ± 0.10^a	0.261 ± 0.005^a	The feed liquid is too thin, resulting in low spray drying efficiency and a large amount of fine powder escaping
1.05	79.3 ± 1.0^c	3.35 ± 0.09^b	0.263 ± 0.004^a	Good atomization, slight wetting of the tower wall
1.10	83.4 ± 0.7^a	3.02 ± 0.08^c	0.267 ± 0.003^a	Uniform atomization, high powder yield, and clean tower wall
1.15	81.2 ± 0.9^b	2.78 ± 0.07^d	0.265 ± 0.004^a	The feed liquid is slightly thick with relatively poor atomization, resulting in a thin layer of adhesion on the tower wall.
1.20	74.8 ± 1.2^d	2.51 ± 0.06^e	0.260 ± 0.005^a	The feed liquid is viscous, making atomization difficult, and severe adhesion occurs on the tower wall

Note. Different superscript letters in the same column indicate significant differences (P < 0.05, n = 3).

3.2.6. Effect of Air Hammer Tapping Frequency on Spray Drying Performance

The tapping frequency affects the shedding efficiency of powder adhering to the tower wall, thereby influencing the powder yield. As shown in Table 6, powder yield decreased gradually as tapping intervals increased from 5 s to 30 s, while moisture content and tyrosol content showed no significant differences. Longer intervals caused increased wall deposition. The suitable range for tapping frequency was 10–20 s/time.

Table 6.

Single-Factor Experimental Results of Rapping Frequency

Vibration frequency(s/次)	Powder yield rate(%)	Moisture content(%)	Content of tyrosol(mg/g)	Observation of adhesion on the tower wall
5	82.9 ± 0.7^a	3.15 ± 0.07^a	0.264 ± 0.00^4a	Excessive vibration frequency, loud equipment noise, and extremely clean tower wall
10	82.5 ± 0.8^a	3.18 ± 0.08^a	0.266 ± 0.003^a	There is basically no adhesion on the tower wall.
15	81.8 ± 0.9^ab	3.21 ± 0.09^a	0.265 ± 0.005^a	Slight thin-layer adhesion on the tower wall
20	80.6 ± 1.0^b	3.24 ± 0.08^a	0.263 ± 0.004^a	Obvious powder deposits can be seen on the tower wall, but they can be removed
30	78.9 ± 1.1^c	3.30 ± 0.10^a	0.262 ± 0.006^a	The powder layer on the tower wall thickens, with caking in some areas

Note. Different superscript letters in the same column indicate significant differences (P < 0.05, n = 3).

3.3. Screening Results and Analysis of Key Factors via Plackett-Burman Method

The PB test design mainly conducts analysis by assigning two levels to each factor. It determines the significance of factors by comparing the differences between the two levels of each factor with the overall differences.¹⁹ Although this screening test design cannot distinguish between the effects of main effects and interactions, it can identify significantly influential factors, thereby achieving the purpose of screening and avoiding the waste of experimental resources in subsequent optimization tests due to an excessive number of factors or insignificant factors.

The factor levels of the PB experiment are shown in Table 7, the experimental design and results are listed in Table 8, and the model analysis of variance is presented in Table 9. The results of analysis of variance demonstrated that among the 6 factors, factor C (feeding speed), factor A (inlet air temperature), and factor B (atomization frequency) had significant effects on the powder yield (P < 0.05). The Pareto chart reflecting the results of the PB factorial design is shown in Figure 2. The other factors, namely factor F (tapping frequency), factor D (extract temperature), and factor E (extract density), had no significant effects (P > 0.05). Therefore, factor C (feeding speed), factor A (inlet air temperature), and factor B (atomization frequency) were selected as the investigation factors for the subsequent model.

Table 7.

Factors and Levels of Plackett-Burman Experiment

Level	A: Inlet air temperature	B: Atomization frequency	C: Feeding speed (r/min)	D: Extract temperature	E: Extract density	F: Tapping frequency
Level	°C	Hz	r/min	°C	g/cm^3	s
1	190	350	30	60	1.15	20
-1	150	200	15	30	1.05	10

Table 8.

Design and Results of Plackett-Burman Experiment

No.	A: Inlet air temperature	B: Atomization frequency	C: Feeding speed	D: Extract temperature	E: Extract density	F: Tapping frequency	Powder output	Powder yield
No.	°C	Hz	r/min	°C	g/cm^3	s	g	%
1	190	200	15	30	1.15	10	82	82
2	150	200	15	60	1.05	20	76	76
3	150	200	30	30	1.15	20	58.2	58.2
4	150	350	30	30	1.15	20	74.4	74.4
5	150	350	30	60	1.05	10	72	72
6	190	350	30	30	1.05	10	83	83
7	190	200	30	60	1.15	10	76.4	76.4
8	150	200	15	30	1.05	10	80	80
9	190	350	15	30	1.05	20	93.6	93.6
10	150	350	15	60	1.15	10	78	78
11	190	350	15	60	1.15	20	86.4	86.4
12	190	200	30	60	1.05	20	66.4	66.4

Table 9.

Analysis of Variance for Plackett-Burman Experiment Design

Source	Sum of squares	df	Mean square	F-value	p-value
Model	819.57	6	136.60	6.00	0.0341	significant
A-Inlet Air Temperature	201.72	1	201.72	8.86	0.0309
B-Atomization Frequency	195.21	1	195.21	8.58	0.0327
C-Feeding Speed	358.61	1	358.61	15.76	0.0106
D-Extract Temperature	21.33	1	21.33	0.9374	0.3774
E-Extract Density	20.28	1	20.28	0.8911	0.3885
F-Tapping Frequency	22.41	1	22.41	0.9849	0.3666
Residual	113.79	5	22.76
Cor Total	933.36	11

Figure 2.

Pareto chart of PB design (red line: Bonferroni limit; blue line: t-value limit)

3.4. Results and Analysis of Spray Drying Process Parameter Optimization Based on the Box-Behnken Method

3.4.1. Regression Models and Significance Analysis

The factor levels of the Box-Behnken experiment are shown in Table 10, the experimental design and results are listed in Table 11. The experimental data were analyzed using Design-Expert 12 software, and the quadratic regression fitting equations obtained are as follows: Powder yield = 87.22 - 1.82A + 0.8B - 1.85C - 2.35AB + 0.6AC + 0.2BC - 7.36A² - 4.56B² - 4.91C², with a standard deviation of 1.42 and R² of 0.9746; Moisture content = 3.24 - 0.6125A - 0.1813B + 0.4338C + 0.065AB - 0.25AC + 0.3825BC - 0.6643A² - 0.3918B² + 0.0232C², with a standard deviation of 0.1735 and R² of 0.9751. The model analysis of variance for powder yield and moisture content are shown in Tables 12 and 13, respectively. The results indicate that both models Y1 and Y2 are extremely significant (P < 0.01).

Table 10.

Factors and Levels of Box-Behnken Experiment

Level	A: Inlet air temperature	B: Atomization frequency	C: Feeding speed
Level	°C	Hz	r/min
1	190	350	30
0	170	275	22.5
-1	150	200	15

Table 11.

Design and Results of Box-Behnken Experiment

No.	A: Inlet air temperature	B: Atomization frequency	C: Feeding speed	Powder output	Powder yield	Moisture content
No.	°C	Hz	r/min	g	%	%
1	170	275	22.5	89.5	89.5	3.27
2	150	275	30	75.1	75.1	4.04
3	170	275	22.5	86.4	86.4	3.18
4	170	275	22.5	88.2	88.2	3.41
5	190	275	30	71.6	71.6	2.28
6	170	200	30	75	75	3.02
7	150	200	22.5	73.1	73.1	2.97
8	170	200	15	79.6	79.6	3.18
9	150	350	22.5	80.1	80.1	2.58
10	190	275	15	73.6	73.6	1.65
11	170	275	22.5	85.4	85.4	3.2
12	170	350	30	76.3	76.3	3.32
13	170	350	15	80.1	80.1	1.95
14	190	350	22.5	72.8	72.8	1.52
15	170	275	22.5	86.6	86.6	3.12
16	150	275	15	79.5	79.5	2.41
17	190	200	22.5	75.2	75.2	1.65

Table 12.

Analysis of Variance for Box-Behnken Experiment (Powder Yield)

Source	Sum of squares	df	Mean square	F-value	p-value
Model	545.77	9	60.64	29.87	< 0.0001	significant
A-Inlet Air Temperature	26.64	1	26.64	13.12	0.0085
B-Atomization Frequency	5.12	1	5.12	2.52	0.1563
C-Feeding Speed	27.38	1	27.38	13.48	0.0079
AB	22.09	1	22.09	10.88	0.0131
AC	1.44	1	1.44	0.7092	0.4275
BC	0.1600	1	0.1600	0.0788	0.7870
A²	228.08	1	228.08	112.33	< 0.0001
B²	87.55	1	87.55	43.12	0.0003
C²	101.51	1	101.51	49.99	0.0002
Residual	14.21	7	2.03
Lack of Fit	3.69	3	1.23	0.4667	0.7213	not significant
Pure Error	10.53	4	2.63
Cor Total	559.98	16

Table 13.

Analysis of Variance for Box-Behnken Experiment (Moisture Content)

Source	Sum of squares	df	Mean square	F-value	p-value
Model	8.25	9	0.9170	30.48	< 0.0001	significant
A-Inlet Air Temperature	3.00	1	3.00	99.76	< 0.0001
B-Atomization Frequency	0.2628	1	0.2628	8.74	0.0212
C-Feeding Speed	1.51	1	1.51	50.03	0.0002
AB	0.0169	1	0.0169	0.5617	0.4780
AC	0.2500	1	0.2500	8.31	0.0236
BC	0.5852	1	0.5852	19.45	0.0031
A²	1.86	1	1.86	61.75	0.0001
B²	0.6462	1	0.6462	21.48	0.0024
C²	0.0023	1	0.0023	0.0757	0.7912
Residual	0.2106	7	0.0301
Lack of Fit	0.1613	3	0.0538	4.36	0.0944	not significant
Pure Error	0.0493	4	0.0123
Cor Total	8.46	16

3.4.2. Effects of Various Factors on Response Values

The factors affecting powder yield are ranked as C > A > B, among which factor C (feeding speed) and factor A (inlet air temperature) have extremely significant effects (P < 0.01), and the lack-of-fit term is not significant. The factors affecting moisture content are ranked as A > C > B, among which factor C (feeding speed) and factor A (inlet air temperature) have extremely significant effects (P < 0.01), factor B (atomization frequency) has a significant effect (P < 0.05), and the lack-of-fit term is not significant. For the RSM results, the curvature of the response surface plots was derived from the extremely significant quadratic terms in both regression models (all P < 0.01), while the asymmetric fluctuation of the plots was attributed to the significant interaction between factors (AB term for powder yield, BC term for moisture content, both P < 0.05). The parabolic trend of each factor was determined by the matching degree between the process parameter setting and the heat and mass transfer capacity of the spray drying tower. These results indicate that the predicted values of the quadratic equations are highly consistent with the actual measured values. The contour plots and three-dimensional response surface plots corresponding to each equation are shown in Figure 3.

Figure 3.

Contour plots and 3D response surfaces of Box-Behnken design

3.4.3. Optimal Parameters and Verification

The Box-Behnken experimental optimizer in Design-Expert 12 software was used, with the target value of powder yield set to the maximum and the target value of moisture content set to the minimum. As shown in Figure 4, the optimal spray drying process parameters were obtained: inlet air temperature of 163°C, atomization frequency of 349 Hz, and feeding speed of 17 r/min. The model predicted a powder yield of 82.9% and a moisture content of 2.15%.

Figure 4.

Optimization results of Box-Behnken design (ramps solutions)

3.5. Verification Results and Reliability Analysis

Three parallel confirmation experiments were performed under the optimal spray drying conditions (163°C, 349 Hz, 17 r·min^-1) to validate the Box-Behnken model. The results are summarized in Table 14. For powder yield, the average value of the three batches was 82.833%±0.25%, which is highly consistent with the model-predicted value of 82.9%. One-sample t-test confirmed no significant difference (t=0.218, df=2, P=0.848), thus verifying the excellent prediction accuracy of the model. For moisture content, the average measured value was 2.193%±0.015%, slightly higher than the predicted value of 2.15%. The one-sample t-test indicated a statistically significant difference (t=4.914, df=2, P=0.039). However, the relative deviation was only 2.00%, well within the acceptable range (<5%) for industrial production. This minor difference is caused by slight environmental fluctuations and does not compromise the feasibility of the optimized process.

Table 14.

Spray Drying Verification

Process verification	Powder output(g)	Powder yield(%)	Moisture content(%)
1	82.6	82.6	2.19
2	83.1	83.1	2.21
3	82.8	82.8	2.18

In conclusion, the model predictions agree well with experimental data, demonstrating high reliability and stability of the optimized spray drying process.

3.6. Results of Physical Parameter Measurements

The powder of plant extracts exhibits an angle of repose of 30-35°, indicating good flowability. When the angle of repose exceeds 45°, the material becomes less fluid and prone to forming “mouse holes” or bridging in hoppers or pipelines. Syringa leaves, refined from plant leaves, demonstrate a angle of repose below 35°, solubility within 50 seconds (30-60 seconds), and a dispersion Q value of 0.04 (<0.05). These results confirm that the Syringa leaf extract produced through optimal spray drying technology exhibits excellent flowability, dispersibility, and solubility. Detailed test results are presented in Table 15.

Table 15.

Results of Determination of Angle of Repose, Dispersion, Solubility, and Particle Size

Determinant		Numeric value	Result determination
angle of repose/°		34.62±3.02	Good flowability
dispersity/%		0.04±0.01	<0.05, good
solubility/s		49.23±3.12	good solubility
particle size determination	D10/µm	2.31±0.04	The smaller the span (approaching 1), the more concentrated and uniform the particle size distribution is.
	D50/µm	5.05±0.39
	D90/µm	7.46±1.03
	Span	1.02

3.7. Results of the Determination of Main Component Indicators

Three batches of lab-scale samples (batch numbers: 230201,230202,230203) and six batches of pilot-scale samples (batch numbers: 230301,230302,230303,230401,230402,230403) of Syringa leaf extract powder were prepared under optimal spray drying process parameters. Under selected chromatographic conditions, both the test solution and reference solution were simultaneously prepared. Precise 10 µl samples were injected for determination, and chromatograms were recorded. The tyrosol content in the test samples was calculated using the external standard method. The minimum tyrosol content in the three pilot-scale samples and six pilot-scale products was 0.253 mg/g, with an average content of 0.269 mg/g. The coefficient of variation (CV=4.38%) was <5%, indicating good inter-batch consistency of tyrosol content in Syringa leaf extract, stable production process, effective quality control, and detailed test results are shown in Table 16.

Table 16.

Tyrosol Content in Syringa Leaf Extracts From Different Batches

Lot number	Tyrosol content (mg/g)	Standard deviation (s)	Coefficient of variation (CV)
230201	0.279	0.012	4.38%
230202	0.286
230203	0.285
230301	0.254
230302	0.253
230303	0.260
230401	0.265
230402	0.267
230403	0.272

4. Discussion

Spray drying is a pivotal unit operation in the industrial production of botanical extracts, as it directly determines powder yield, moisture content, flowability, and the retention of thermo-sensitive bioactive ingredients. In this study, the spray drying process of Syringa leaf extract was systematically optimized using a combination of single-factor parameter investigation,PB screening and Box–Behnken response surface methodology (BBD–RSM), with tyrosol as the key quality marker, which significantly improved the efficiency and accuracy of process optimization.²⁰

Before process parameter optimization, thermogravimetric analysis (TGA) confirmed that tyrosol remained stable below 225.1 °C, which laid a clear thermal safety boundary for subsequent parameter setting.²¹ The results confirmed that tyrosol possesses sufficient thermal stability for spray drying.²² Such pre-optimization stability evaluation is often neglected in conventional process studies, which may lead to overestimation of component retention or unexpected thermal degradation. The single-factor investigation in this study clarified the influence trend of each parameter and determined the reasonable level range for the subsequent Plackett-Burman (PB) design, avoiding the distortion of factor screening results caused by unreasonable level setting.

The preliminary PB design efficiently screened six influencing factors with only 12 experimental runs. Pareto chart and ANOVA analysis identified inlet air temperature, atomization frequency, and feeding speed as the most significant variables affecting powder yield (P < 0.05). Extract density, extract temperature, and air hammer frequency showed no significant effects within the pre-determined ranges, which was consistent with the results of single-factor investigation. This is probably because the extract concentration was already suitable for atomization, feed preheating had limited influence on droplet formation, and the drying chamber structure effectively reduced wall deposition.²³ By excluding non-significant factors, the PB design avoided redundant experiments and greatly improved the efficiency of the subsequent RSM optimization.

Based on the PB screening results, a three-factor, three-level Box–Behnken design was employed to establish quadratic regression models for powder yield and moisture content, both of which exhibited excellent fitting performance (R² = 0.9746 and 0.9751, respectively) with non-significant lack-of-fit tests, confirming high prediction accuracy. Inlet air temperature was the most influential factor affecting moisture content, while feeding speed had the strongest effect on powder yield; increasing temperature enhanced water evaporation but reduced yield at excessively high levels due to particle fragmentation and wall deposition, whereas higher feeding speed lowered yield and increased moisture by shortening drying residence time.²⁴ Atomization frequency affected droplet size and drying efficiency, with an optimal value near 349 Hz to balance drying uniformity and powder recovery. Significant interactions were observed between inlet temperature and atomization frequency for powder yield, and between atomization frequency and feeding speed for moisture content, reflecting coordinated effects on heat–mass transfer.

Three parallel validation experiments verified the robustness of the optimized conditions, with powder yields ranging from 82.6% to 83.1% and moisture contents from 2.18% to 2.21%, both highly consistent with the predicted values. The low relative deviations confirmed the high prediction accuracy of the models. The optimized Syringa leaf extract powder showed satisfactory flowability (angle of repose 34.62°), good dispersibility (Q = 0.04%), and rapid solubility (49.23 s), which are critical for uniform mixing and automatic application in feed production. In addition, the tyrosol content in nine batches (three lab-scale and six pilot-scale) showed a low coefficient of variation (CV = 4.38%), suggesting that the optimized spray drying process does not cause obvious degradation of tyrosol and is feasible for scaled-up production.

In terms of the influence mechanism of spray drying parameters, inlet air temperature was the most critical factor affecting moisture content in this study (F=99.76, P<0.0001), with powder moisture decreasing significantly as temperature increased, consistent with the findings of Lee et al.²⁵ Meanwhile, powder yield showed a parabolic trend with rising inlet temperature, peaking at 163°C and decreasing significantly when the temperature exceeded 180°C, which was mainly attributed to particle fragmentation and increased wall deposition caused by excessive thermal stress. Critically, the optimized inlet temperature (163°C) in this study was far below the thermal decomposition threshold of tyrosol (225.1°C), thereby effectively preventing the thermal degradation of tyrosol, the major phenolic active ingredient. It should be noted that existing studies have shown that total phenolic components in most plant extracts undergo content changes above 145°C, but this phenomenon exhibits considerable complexity. On the one hand, Georgetti et al²⁶ pointed out that the high temperature during spray drying might cause oxidation or decomposition of some unstable polyphenols. On the other hand, Liu et al²⁷ found that heat treatment could release bound soluble polyphenols and flavonoids from plant tissues, leading to a significant increase in total phenolic content after 140°C due to the accelerated release rate. Similarly, Mishra et al²⁸ also observed in the spray drying study of Emblica officinalis juice that the total phenolic content decreased significantly in the range of 125-175°C, but rebounded after exceeding 175°C due to the massive release of bound components. This result aligns with the conclusion of Lemmadi et al²⁹ who confirmed that controlling inlet air temperature below the decomposition temperature of active ingredients with maltodextrin as the carrier can significantly improve the stability of phenolic compounds during spray drying.

Feeding speed was the dominant factor for powder yield (F=13.48, P=0.0079), with higher feeding speeds leading to significantly reduced yield and increased moisture content, consistent with the aforementioned chamomile extract study.²⁵ The optimized feeding speed of 17 r·min^-1 in this study achieves a balance between drying efficiency, powder quality, and actual production throughput. Atomization frequency regulated drying performance by affecting droplet size distribution: the optimized frequency of 349 Hz produced uniform and moderately sized droplets, which balanced drying efficiency and powder yield, and endowed the optimized powder with good flowability (angle of repose 34.62°). This is consistent with the findings of Jovanović et al,³⁰ who reported that appropriate atomization conditions can reduce fine powder loss and improve the flowability of spray-dried plant extract powder. Furthermore, unlike most studies that only focus on conventional process indicators such as powder yield and moisture content, this study established a comprehensive quality evaluation system covering the thermal safety window of tyrosol, key physical properties of the powder, and excellent batch-to-batch consistency of tyrosol content (CV=4.38%). As confirmed by the study on Lonicera caerulea L. juice powders, the physical properties of spray-dried powder directly determine its application adaptability in terminal products, which is particularly critical for the uniform mixing of this product as a feed additive.

Several limitations of this study should also be noted. First, all experiments were performed on a pilot-scale dryer; further fine-tuning of parameters may be required during large-scale industrial production due to differences in airflow and residence time. Second, tyrosol was used as the sole marker compound, whereas Syringa leaf extract contains multiple bioactive ingredients that may also be affected by drying conditions.³¹ A multi-component fingerprint method would provide a more holistic quality evaluation. Third, the long-term storage stability (e.g., 6 or 12 months) of the spray-dried powder was not investigated, which is necessary for commercial registration of feed additives. Future research will focus on scale-up verification, accelerated stability tests, and the establishment of a multi-component quality standard system.

5. Conclusion

In this study, with the powder yield and moisture content of Syringa leaf extract as the core indicators, the PB design and Box-Behnken response surface methodology were used to optimize its spray drying process, and the reliability of the process was confirmed by combining thermal stability analysis and verification experiments. Thermogravimetric analysis showed that tyrosol, the main active ingredient, had good stability at <225.1°C, which was suitable for the conventional operating temperature of spray drying. The PB experiment screened out inlet air temperature, atomization frequency, and feeding speed as key factors from 6 factors; the quadratic regression model established by the Box-Behnken method had excellent fitting degrees (R² were 0.9746 and 0.9751 respectively), and the optimized best parameters were obtained: inlet air temperature 163°C, atomization frequency 349 Hz, feeding speed 17 r/min. The average powder yield of three batches of verification tests was 82.8% and the moisture content was 2.19%, which were highly consistent with the predicted values.The physical indexes of the extract, such as the angle of repose, solubility, dispersibility, and the quantitative determination of the main active ingredient, tyrosol, were obtained, which verified the feasibility of spray drying technology. In conclusion, the key process parameters for optimizing Syringa leaf extract by PB design and Box-Behnken response surface methodology were clarified, providing a scientific basis for the large-scale production of the extract and the industrial application of feed additives.

Footnotes

Acknowledgments

We are grateful to all other staff in the Institute of Traditional Chinese Veterinary Medicine of Gansu Agricultural University, Henan Muxiang Biotechnology Co., Ltd., and Henan University of Animal Husbandry and Economy for their assistance in the experiments.

ORCID iDs

Bin Wang

Peng Ji

Ethical Considerations

Ethical Approval is not applicable for this article.

Consent to Participate

There are no human subjects in this article and informed consent is not applicable.

Authors’ contribution

Bin Wang: Conceptualization, methodology, investigation, formal analysis, and draft writing.

Fengxia Lv: Methodology, validation.

Peng Ji: Investigation, data organization, review, and editing.

Yanming Wei: Supervision, project management, review, and editing.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by Industrial Support Project of Gansu Provincial Department of Education (2025CYZC-038), Henan Provincial Key Research and Development Program (No. 221111111600), Science and Technology Plan of Gansu Province (24ZDNA001), Ministry of Finance and Ministry of Agriculture and Rural Development: National Modern Agricultural Industrial Technology System (CARS-37).

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

Data will be made available on request.*

Statement of Human and Animal Rights

This article does not contain any studies with human or animal subjects.

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