Production of Dangshan Pear Wine by Liquid Fermentation Based on Orthogonal Design Optimal Experiments

Shan Song1, Lijun Pan1, 2, 3, Xuefeng Wu*1, 2, 3

1. School of Biotechnology and Food Engineering, Hefei University of Technology Hefei, Anhui, The People's Republic of China

2. The Key Laboratory for Agricultural Products Processing of Anhui Province, The People's Republic of China

3. Institute of Agricultural Products Processing Technology, The People's Republic of China E-mail:applewuxf@hotmail.com

Abstract: Anhui Dangshan pear production accounts for about 13% (w/w) of the total output in China, producing pear wine using Dangshan pear is one of the effective ways to relieve the pressure on fresh fruit storage, to reduce waste of the fruit and to enhance the value of the fruit. But the key technical parameters of the pear wine production has not yet been set. In this paper, fruit wine was prepared using liquid fermentation from Dangshan pear. Single factor and orthogonal experimental design methods were used to get the optimal fermentation process for alcohol. The null columns and repeated trials were used to unbiased estimator for experimental error in the variance analysis, in order to improve the accuracy of the data processing and analysis greatly. The optimum condition for production of Dangshan pear wine were as follows: the fermentation time was 4 d, the inoculums with yeast culture (0.2 g ml-1) was 6% (v/v), the fermentation temperature was 26℃and the glucose addition was 14% (w/v), in this condition, alcohol concentration could achieved 10.35% (v/v). The results may provide certain technical support for the industrial production of Dangshan pear wine. Keywords: Dangshan Pear; wine; orthogonal experimental design. 1. Introduction

In recent years, the increased interests of ratafee which is also named as fruit wine, a kind of low-alcohol and high nutrition wine has made producing fruit wine an attractive investment, because of its benefits to brain and health. Especially in China, where there are a large number of fruits, a variety of ratafee has been popular. Dangshan pear contains sugar, minerals, organic acid and various vitamins, abundant nutrition, is a rare fruit with high quality 1-4. Dangshan pear as a specialty of Anhui Province in China, the annual output is up to1500 000 000 kg a-1. However, a considerable amount of this production is wasted, due to natural degradation, low comprehensive utilization, or because of imperfections that make marketing impracticable. Especially in the harvest year, the waste and corruption is more serious.

Orthogonal experimental design like the other experimental design method, such as response surface design method is a common optimization technique which has been widely used in scientific research, production and management areas 5-7. There are tens of thousands of research papers each year using this method to test optimization. Mostly, only the range analysis method was used to judge the primary and secondary factors. And there are no null columns and repeated trials in the orthogonal array in some experimental designs, which results in the impossiblity of estimating the random error, the variance analysis for the results of orthogonal design cannot be going, the significance of effects from each factor will be not known, and it cannot determine the accuracy of the analysis for the experimental results 5-8.

This paper intends to use Dangshan pear as raw materials which is rich in Anhui Province in China, and the orthogonal experimental design was used to optimize Dangshan pear wine’s fermentation conditions.

2. Materials and methods 2.1 Materials

Raw materials: Dangshan pear was purchased from Zhougudui fruit market, Hefei, Anhui Province, China. Instant dry yeast was purchased from Angel Yeast Co. Ltd., Yichang, Hubei Province, China.

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2.2 Methods 2.2.1 Juice preparation

Dangshan pear, purchased from Hefei City Zhougudui fruit market, was selected, after cleaning, 1 kg pear was pressed with adding 500 mL water to get the pear juice, and 10 g sodium erythorbate was added to protect the color. 2.5 g pectinase was added into the juice when the citric acid was used to adjust the value of pH to 5.4, which was bathed at 50℃ for 60 min in order to improve the juice yield, and followed by NaOH adjusted to pH 6.5, then flitted with 200 meshes 9, 10. 2.2.2 Yeast culture

20 g of yeast purchased from Angel Yeast Co. Ltd., was inoculated into a 250 mL flask containing 100 mL sterile water, cultured for 30 min at 30℃, and the yeast culture (0.2 g mL-1) was used for alcohol fermentation. 2.2.3 Alcohol fermentation

50ml Dangshan pear juice which containing 10% (w/v) glucose was poured into 250mL flask sealed with airtight sealing film, after sterling at 105 ℃ for 5 min, 2 mL of the yeast culture was inoculated and cultured at 26 ℃ with static fermentation for about 4 d.

2.3 Analysis of alcohol

Alcohol was extracted from the fermented culture by diluting with methanol and filtering through a 0.22 µm membrane. And the modified method of gas chromatography 11 was used to determine the concentration of alcohol, by direct injection in an Agilent 7890A gas chromatograph (Agilent) equipped with a split/splitless injector, electronic flow control (EFC) and a flame ionization detector (FID). An aliquot of 2 μL of this mixture was injected (split 1:30) into an Agilent J and W GC Columns DB-624 fused silica capillary column of 25 m×0.2 mm and 1.12 μm film thickness (Agilent, The USA). Instrumental conditions were as follows: injector temperature of 150℃, detector temperature of 200℃, nitrogen as carrier gas at 3.3mL min−1, and nitrogen as make-up gas at 30 mL min−1. The flow rates of detector gas hydrogen and air were 40mL min−1 and 400 mL min−1, respectively. The temperature program was as follows: 50℃for 5 min, increased to 200℃at a rate of 4℃min−1 and held at 200℃for 5 min. Total running time was 15 min.

2.4 Data processing

Results of single factor experiments are expressed as mean±standard deviation (n=3). The orthogonal design experiments were performed with repeated trials with a statistical significance (P≤0.05) using the Office 2007 Excel statistical analysis program 6, 12.

3. Results and discussion 3.1 Effect of fermentation time on the concentration of alcohol

The concentration of alcohol was the largest when the fermentation time was 4 d in figure 1. And from the first day to the third day, the concentration of alcohol increased correspondingly. After the fourth day, the aroma of wine and fruit were gradually reduced, and the concentration of alcohol also showed a downward trend. Pears contain many sugar and other energy substances and these energy sources could provide enough energy for the anaerobic fermentation of yeast with changing sugar into alcohol. However, when the time was more than 4 d, only a small amount of sugar remained, and other nutrients were exhausted. Ethanol was used by yeast to decompose into CO2 and water 13.

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Fig.1 Effect of fermentation time on the concentration of alcohol

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3.2 Effect of glucose addition on the concentration of alcohol

The concentration of alcohol was the largest, when the glucose addition was 10% (w/v) in figure 2. When the glucose addition was less than 10% (w/v), the concentration of alcohol was improved significantly with the increasing of glucose concentration, but it showed a downward trend while the glucose addition more than 10% (w/v). High concentration of glucose could lead to high osmotic pressure to the cell, and the metabolic activity of yeast and the byproducts were changed, which resulting in the inhibition of anaerobic fermentation of yeast, leaving the lower alcohol production 13.

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0 2 4 6 8 10 14 18 22glucose addition (%)

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Fig.2 Effect of glucose addition on the concentration of alcohol

3.3 Effect of fermentation temperature on the concentration of alcohol

Although temperature is an environmental parameter that is easy to control, changes in temperature produce simultaneous changes in other culture variables. An increase in incubation temperature within physiological ranges enhanced the growth rate. And also the temperature affected the metabolite. In this study, the optimal temperature for the alcohol production by yeast culture were investigated. Figure 3 showed that, when the fermentation temperature was 28℃, the alcoholic concentration was the largest. When the temperature was below 28℃ , with the temperature increasing, the wine were richen for aroma of fruit and wine, the concentration of alcohol was also increased correspondingly. When the temperature was higher than 28℃the wine quality and aroma were reduced, and the concentration of alcohol showed a downward trend. The optimal temperature for yeast was 28℃ . When the temperature was above or below this temperature, it was not conducive to the anaerobic fermentation of yeast to produce ethanol. That was may be the reason for this phenomenon.

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24 26 28 30 34temperature (oC)

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Fig. 3 Effect of fermentation temperature on the concentration of alcohol

3.4 Effect of inoculum on the concentration of alcohol

The effects of the inoculum size on the alcohol production in flask were studied in detail. Different concentrations of yeast powder and yeast culture were inoculated into the production medium, respectively. As shown in Figure 4, when the inoculum of yeast powder was 1% (w/v), the alcohol concentration was the largest. And less or more inoculum of yeast powder was not benefit for improving the concentration of alcohol.

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0123456789

0.2 0.6 1.0 1.4 1.8yeast powder (%)

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Fig. 4 Effect of inoculum using yeast powder on the concentration of alcohol

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Fig. 5 Effect of inoculum using yeast culture on the concentration of alcohol

Figure 5 showed that when the inoculum using yeast culture was 5% (v/v), the alcohol concentration was the largest. And when the inoculum using yeast culture was more than 5% (v/v), the concentration of alcohol showed a downward trend. Comparing Figure 4 and figure 5, it was obvious that using yeast powder in alcohol fermentation, the concentration of alcohol was generally lower than that using yeast culture. Therefore, yeast culture was chosen as the inoculum in the subsequent alcohol fermentation.

3.5 Orthogonal design experiment to optimize the fermentation conditions of Dangshan pear wine

Analysis of variance was used for the data obtained above to determine the factors using in the orthogonal design experiment, and four factors (P<0.05) were as follows: fermentation time, fermentation temperature, glucose concentration and the inoculum using yeast culture. The standard L16(45) matrix and statistical data on the factors were computed in detail, and the methods used were based on literature 5-7. Orthogonal experiment results were shown in Table 1.The results of variance analysis are shown in Table 2.

Table 1 The orthogonal design and experimental results in alcohol fermentation using Dangshan Pear

1 2 3 4 5 alcohol (%)↑ A

time (d) B

inoculum (%) C

temperature ( oC ) D

glucose (%) E

Y1 Y2

1 1(4) 1(4.5) 1(28) 1(8) 1 7.35 7.72 2 1 2(6) 2(26) 2(14) 2 10.69 9.85 3 1 3(5.5) 3(30) 3(12) 3 8.95 9.45 4 1 4(5) 4(32) 4(10) 4 8.36 8.89 5 2(5) 1 2 3 4 9.9 9.3 6 2 2 1 4 3 8.62 8.96 7 2 3 4 1 2 7.29 7.68 8 2 4 3 2 1 9.71 10.51 9 3(3) 1 3 4 2 7.95 8.75

10 3 2 4 3 1 9.31 9.59 11 3 3 1 2 4 9.82 10.46

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12 3 4 2 1 3 7.35 7.82 13 4(2) 1 4 2 3 8.75 9.74 14 4 2 3 1 4 7.1 6.9 15 4 3 2 4 1 7.32 7.97 16 4 4 1 3 2 8.56 9.73 K1 71.26 69.46 71.22 59.21 69.48

T=280.35 Q=2493.13 CT=2456.13

K2 71.97 71.02 70.2 79.53 70.5 K3 71.05 68.94 69.32 74.79 69.64 K4 66.07 70.93 69.61 66.82 70.73 SS 2.75 0.41 0.26 30.03 0.14

The primary factor→ Secondary factor D A B C Optimal combination A2B2C1D2

Notes: Glucose, glucose addition; alcohol, alcohol concentration; K1, K2, K3, K4, the sum of the results with each level of the factor; SS, sum of square for each factor.

Table 2 Analysis of variance for the orthogonal design in alcohol fermentation using Dangshan Pear Source of variance SS f MS F significant

Time A 2.75 3 0.917 5.43 ** inoculum B 0.41 3 0.137

temperature C 0.26 3 0.087 glucose D 30.03 3 10.01 59.30 **

E e1 0.14 3 e2 3.41 16 e 3.55 19 0.187

e'=B+C+e 4.22 25 0.169 sum 37 31

Notes：F0.01(3,25)=4.68，F0.05(3,25)=2.99，F0.1(3,25)=2.32，F0.25(3,25)=1.46 SS, sum of square for each factor; f, freedom; MS, mean of sum of square for each factor; F, F-ratios,

glucose, glucose addition; e1, error 1 accumulated from the null columns; e2, error 2 accumulated from repeated trials; e, total of error; e', total of new error; sum, total of sum of square.

From Table 1 with the directly analysis, the optimum combination was A1B2C2D2, that is to say, the fermentation time was 4 d, inoculum with yeast culture (0.2 g ml-1) was 6% (v/v), the fermentation temperature was 26℃ and the glucose addition was 14% (w/v), and the average of alcohol concentration was 10.27% (v/v), which was the second test in Table 1.

With the computational analysis, it was not difficult to find that the optimal combination was A2B2C1D2 from the values of K1, K2, K3 and K4 (the sum of the results with each level) of each factor in Table 1, which means that when the fermentation time was 5 d, the inoculums using yeast culture (0.2 g ml-1) was 6% (v/v), the fermentation temperature was 28℃ and the glucose addition was 14% (w/v), the alcohol concentration would achieve the highest.

As we all known, there must be null columns in the orthogonal table which was used to unbiased estimate the experimental errors in the variance analysis for the result of orthogonal design. And if there are no null columns, the repeated trials must be used in order to unbiased estimate the experimental error. And it is generally reasonable and reliable with both null columns and repeated trials in the variance analysis for the result of orthogonal design, which can enhance the accuracy of the data analysis 5, 6. In this experiment the method with two manners of null columns and repeated trials was used to unbiased estimate the experimental error. And we could find from the values of MSA (mean of sum of square for the factor of time, A), MSB (mean of sum of square for the factor of inoculum, B), MSC (mean of sum of square for the factor of temperature, C) and MSD (mean of sum of square for the factor of glucose addition, D), which was 0.917, 0.137, 0.087, and 10.01, respectively, that the primary and secondary factors were D > A > B > C. The inoculum and fermentation temperature had no significant effects on the alcohol concentration, because the mean variance of inoculum and fermentation temperature which was MSB (0.137) and MSC (0.087), respectively, were smaller than the mean variance of the error MSe (0.187) (mean of sum of square for the error) which was summed of e1 (error 1 accumulated from the null columns) and e2 (error 2 accumulated from repeated trials). And the sum of SSe

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(3.55) and SSB (0.41), SSC (0.26) was used as a new error sum of square (SSe', 4.22) in the variance analysis for the result of orthogonal design in Table 2 5.

From Table 2, it could be concluded that the factors of the fermentation time and the glucose concentration were significant factors that influence alcohol concentration at 99% confidence level with F-ratios of 5.43 and 59.3, respectively. That is to say, the fermentation time and the glucose addition had highly significant effects on the alcoholic concentration. And the inoculums and fermentation temperature had no effects on the alcoholic concentration compared to the other conditions.

The results of verification tests with the optimum conditions from direct analysis and computational analysis (test results were not shown), suggested that the alcoholic concentration was higher 10.35% (v/v) with the combination A1B2C2D2. Therefore the optimal process conditions of Dangshan pear wine were as follows, the fermentation time was 4 d, inoculum with yeast culture (0.2 g ml-1) was 6% (v/v), the fermentation temperature was 26℃and the glucose addition was 14% (w/v).

4. Conclusion

Single factor experiments and orthogonal experiments were used to optimize the fermentation conditions for Dangshan pear wine. Null columns and repeated trials were used to unbiased estimator for experimental error in the variance analysis for the result of orthogonal design, which improved the accuracy of the data processing and analysis greatly. And in the optimization parameters for the alcohol fermentation using Dangshan pear, the concentration of alcohol achieved the highest which was about 10.35% (v/v). The Dangshan pear wine was brightly yellow after clarified and with a pleasant fruity aromas. This may provide some technical reference for the industrial production of the Dangshan pear wine.

Acknowledgments

Supported by the College Students' Innovative Entrepreneurial Training Program (2014CXCY545) and Young teachers innovation projects (JZ2014HGQC0124) of Hefei University of Technology, National Natural Science Foundation of China (31171741, 31371728, 31101352, 31470002) and the Key Laboratory for Agricultural Products Processing of Anhui Province, the Institute of Agricultural Products Processing Technology, the School of Biotechnology and Food Engineering, Hefei University of Technology are gratefully acknowledged.

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