Scientia Agricultura Sinica ›› 2019, Vol. 52 ›› Issue (1): 129-142.doi: 10.3864/j.issn.0578-1752.2019.01.012

• FOOD SCIENCE AND ENGINEERING • Previous Articles     Next Articles

Suitability Evaluation of Apple for Chips-Processing Based on BP Artificial Neural Network

ZHANG Biao(),LIU Xuan(),BI JinFeng,WU XinYe,JIN Xin,LI Xuan,LI Xiao   

  1. Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences/Key Laboratory of Agro-Products Processing, Ministry of Agriculture and Rural Affairs, Beijing 100193
  • Received:2018-05-29 Accepted:2018-09-18 Online:2019-01-01 Published:2019-01-12
  • Contact: Xuan LIU E-mail:15829685595@163.com;liuxuancaas@126.com

Abstract:

【Objective】The aim of the paper was to establish suitability evaluation model for apple chips-processing from different cultivars and to achieve the quality prediction of apple chips based on raw material indicators.【Method】34 fresh apple samples of 21 apple varieties from 7 major growing regions were selected as research objects. Factor analysis (FA) and analytic hierarchy process (AHP) were used to establish comprehensive quality evaluation model for chips, and Error Back Propagation (BP) artificial neural network was used to establish chips-processing suitability evaluation model for apple fruits. (1) Chips were prepared by instant controlled pressure drop (DIC, French for détente instantannée controlee, also known as explosion puffing) and 17 indicators were measured. The core indexes of chips were selected by FA and correlation analysis. The weights of the core indexes were determined by AHP, and then the comprehensive quality evaluation scores of chips were calculated. (2) 22 indicators of 34 fruit samples with different cultivars and regions were measured. Then the characteristic indicators of apple fruits related to chip qualities were screened out by correlation analysis between data groups of apple fruit indicators and chip core indexes. Learning model with input of fruit characteristic indicators and output of chip comprehensive evaluation scores was established by database of 29 apple samples. 5 apple samples were chosen as test samples to verify the prediction accuracy of the learning model. Modified leaning models from different sample groups were compared by prediction accuracy, which could be the evidence to evaluate rationality and stability for application of BP neural network in the present research.【Result】The results showed that L* value, brittleness, puffing degree, titratable acid, soluble sugar and crude protein of apple chip were determined as the core indexes which the weights were 0.3724, 0.2665, 0.1583, 0.0890, 0.0569 and 0.0569, respectively. The comprehensive quality scores of chips from 34 apple samples ranged from 0.2069 to 0.7933, indicating significant variation. The top 3 apple samples with high scores were Liaoning Huahong, Liaoning Huajin and Shandong Yanfu 6, and the final ranking for Shanxi Qinguan. Correlation analysis was performed between core indexes of chips and quality indicators of apple raw materials to achieve characteristic indicators of apple fruits, including the fruit shape index, a* value (pulp), pH value, titratable acid content, Vc content, proportion of core, protein content, b* value (pulp), density, soluble solids content, crude fiber content and total sugar content. Therefore, learning models were established with input layer of the characteristic indicators value of fruit and output layer of the comprehensive quality score of apple chip, which could predict the comprehensive quality of apple chips from indicators of raw materials. Moreover, the model showed high prediction accuracy. The relative errors between the predicted and actual values of the three learning models groups did not exceed 10%, and the coefficients of determination R 2 of linear fitting were higher than 0.95.【Conclusion】Suitability evaluation of apple fruit for chips-processing could be evaluated by fruit shape index, a* value (pulp), pH value, titratable acid content, Vc content, proportion of core, protein content, b* value (pulp), density, soluble solids content, crude fiber content and total sugar content. The established model could be used to quantitatively predict apple fruit suitability for chips-processing based on the indicators of raw fruits.

Key words: apple, chips, dehydration, suitability evaluation, BP neural network

Table 1

Names and collect place and time of apples"

序号
No.
名称
Name
产地
Collect place
采收日期
Collect time
序号
No.
名称
Name
产地
Collect place
采收日期
Collect time
1 华红 Huahong 辽宁葫芦岛 Huludao, Liaoning 2016.10.15 18 新红星 Starkrimson 山东泰安 Taian, Shandong 2016.10.14
2 华金 Huajin 辽宁葫芦岛 Huludao, Liaoning 2016.10.15 19 金冠 Golden Delicious 山东淄博 Zibo, Shandong 2016.10.23
3 秋锦 Qiujin 辽宁葫芦岛 Huludao, Liaoning 2016.10.15 20 红星 Starking 山东淄博 Zibo, Shandong 2016.10.23
4 华月 Huayue 辽宁葫芦岛 Huludao, Liaoning 2016.10.15 21 富士 Fuji 山东淄博 Zibo, Shandong 2016.10.23
5 寒富 Hanfu 辽宁葫芦岛 Huludao, Liaoning 2016.10.15 22 红将军 Hongjiangjun 山东淄博 Zibo, Shandong 2016.10.23
6 乔纳金 Jonagold 辽宁葫芦岛 Huludao, Liaoning 2016.10.15 23 国光 Ralls 山东淄博 Zibo, Shandong 2016.10.23
7 长富2号 Changfu 2 辽宁葫芦岛 Huludao, Liaoning 2016.10.15 24 富士 Fuji 山东栖霞 Qixia, Shandong 2016.10.12
8 金冠 Golden Delicious 辽宁葫芦岛 Huludao, Liaoning 2016.10.15 25 烟富6号 Yanfu 6 山东青岛 Qingdao, Shandong 2016.10.11
9 新红星 Starkrimson 辽宁葫芦岛 Huludao, Liaoning 2016.10.15 26 富士 Fuji 甘肃平波 Pingbo, Gansu 2016.11.07
10 华富 Huafu 辽宁葫芦岛 Huludao, Liaoning 2016.10.15 27 金冠 Golden Delicious 甘肃平波 Pingbo, Gansu 2016.11.07
11 青苹 Granny Smith 陕西咸阳 Xianyang, Shaanxi 2016.10.22 28 花牛 Huaniu 甘肃平波 Pingbo, Gansu 2016.11.07
12 瑞阳 Ruiyang 陕西咸阳 Xianyang, Shaanxi 2016.10.22 29 秦冠 Qinguan 甘肃平波 Pingbo, Gansu 2016.11.07
13 秦冠 Qinguan 陕西咸阳 Xianyang, Shaanxi 2016.10.22 30 半坡秦冠 Banpo Qinguan 山西运城 Yuncheng, Shanxi 2016.10.28
14 秦红 Qinhong 陕西咸阳 Xianyang, Shaanxi 2016.10.22 31 坡顶富士 Poding Fuji 山西运城 Yuncheng, Shanxi 2016.10.28
15 长密欧 Changmiou 陕西咸阳 Xianyang, Shaanxi 2016.10.22 32 半坡富士 Banpo Fuji 山西运城 Yuncheng, Shanxi 2016.10.28
16 富士 Fuji 陕西咸阳 Xianyang, Shaanxi 2016.10.22 33 富士 Fuji 河北 Hebei 2016.11.03
17 金冠 Golden Delicious 山东泰安 Taian, Shandong 2016.10.14 34 富士 Fuji 新疆 Xinjiang 2016.11.07

Table 2

Data on 22 fruit indexes of 34 apple varieties"

编号
Number
X1 X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14 X15 X16 X17 X18 X19 X20 X21 X22
1 232.31 288.00 0.81 0.96 0.21 45.12 14.15 15.92 67.00 -0.53 21.51 6.56 2.36 3.41 0.47 12.90 0.86 1.10 0.36 2.10 7.80 12.10
2 207.28 261.00 0.80 0.89 0.22 53.79 -3.32 20.93 68.51 -2.57 14.24 5.74 2.09 3.52 0.34 13.30 0.88 1.10 0.38 4.80 8.60 12.50
3 152.53 195.00 0.78 0.82 0.26 32.68 7.97 9.78 63.64 -1.03 21.58 9.10 2.94 4.04 0.21 12.93 0.82 1.40 0.35 3.10 11.10 14.00
4 197.07 231.00 0.85 0.96 0.27 48.97 -1.41 19.67 63.17 -1.36 23.42 7.32 3.01 3.56 0.44 13.03 0.86 1.00 0.32 7.60 8.10 12.90
5 212.10 275.00 0.77 0.85 0.26 41.78 9.50 12.13 64.57 -2.89 19.14 6.10 2.23 3.69 0.34 9.93 0.87 0.90 0.35 2.10 8.70 9.90
6 220.56 264.00 0.84 0.90 0.27 42.42 11.54 14.45 66.66 -2.31 22.19 6.46 2.11 3.37 0.36 13.87 0.85 1.00 0.29 3.60 8.50 12.50
7 212.19 256.00 0.83 0.88 0.19 45.59 0.25 17.51 63.13 -2.45 19.48 8.83 2.80 3.68 0.33 12.70 0.84 0.90 0.48 3.50 8.60 9.20
8 193.01 245.00 0.79 0.89 0.24 51.81 -6.17 23.22 66.46 -2.02 22.02 6.97 2.66 3.45 0.39 12.37 0.85 0.90 0.58 2.40 9.60 11.70
9 239.69 296.00 0.81 0.90 0.22 29.12 15.07 6.53 64.65 -2.48 20.17 9.51 2.93 3.86 0.19 10.80 0.87 1.00 0.29 2.50 7.50 13.40
10 183.71 216.00 0.85 0.89 0.28 44.56 12.50 14.09 62.59 -0.63 20.76 9.03 2.89 3.45 0.40 14.67 0.85 1.40 0.32 2.00 9.40 14.40
11 212.26 257.00 0.82 0.90 0.28 45.85 -9.74 18.87 63.02 -4.87 18.01 12.48 3.24 2.96 0.66 13.90 0.84 0.90 0.30 4.10 9.90 12.80
12 150.85 194.00 0.78 0.95 0.32 44.12 4.64 14.93 66.86 -3.53 20.22 6.11 1.44 3.54 0.38 11.30 0.86 1.20 0.29 3.00 10.20 11.30
13 166.19 209.00 0.80 0.88 0.23 43.68 8.35 14.79 66.44 -0.33 21.85 7.72 2.54 4.51 0.15 12.30 0.83 1.20 0.44 2.90 9.10 11.40
14 178.10 225.00 0.79 0.92 0.28 40.24 14.32 12.98 62.50 1.11 21.07 9.10 2.53 3.83 0.27 12.30 0.87 1.00 0.32 1.20 7.10 8.20
15 204.79 244.00 0.84 0.86 0.28 52.70 2.57 19.25 64.94 -0.58 21.61 7.27 2.27 3.67 0.34 15.13 0.87 1.00 0.31 3.00 7.50 10.10
16 178.10 225.00 0.79 0.92 0.28 40.24 14.32 12.98 62.50 1.11 21.07 9.10 2.53 3.83 0.27 12.30 0.87 1.00 0.32 1.20 7.10 8.20
17 214.79 274.00 0.78 0.90 0.23 50.97 -8.46 21.42 67.44 -1.60 21.42 4.98 1.45 3.51 0.34 10.00 0.89 1.00 0.29 1.60 7.00 8.60
18 219.25 271.00 0.81 0.95 0.27 46.95 7.38 17.08 64.22 -1.10 22.05 7.85 1.80 4.13 0.18 10.20 0.90 1.10 0.23 1.20 8.20 10.70
19 158.77 189.00 0.84 0.86 0.27 58.57 -3.37 24.96 65.14 -1.02 22.10 5.56 1.98 3.95 0.23 12.30 0.84 1.20 0.20 0.90 9.00 11.50
20 263.10 331.00 0.80 0.92 0.24 46.53 11.18 13.61 65.44 0.16 20.92 7.35 1.99 4.08 0.16 9.30 0.89 0.80 0.28 1.00 9.50 10.70
21 257.95 306.00 0.84 0.85 0.28 42.00 15.41 11.03 64.22 -0.91 20.36 7.64 2.05 3.91 0.25 11.70 0.87 0.90 0.25 1.20 6.80 8.40
22 208.57 247.00 0.85 0.90 0.28 38.36 18.36 9.10 65.46 -1.54 21.17 8.98 2.61 3.72 0.23 13.13 0.87 1.00 0.30 0.80 10.80 11.80
23 102.33 120.00 0.86 0.80 0.34 45.08 12.93 13.69 66.28 -2.00 20.79 10.61 3.17 3.42 0.43 14.07 0.85 1.00 0.30 2.20 9.40 12.00
24 253.66 303.00 0.84 0.84 0.30 40.34 16.80 12.17 64.30 1.08 21.97 8.92 2.93 3.73 0.24 13.10 0.88 1.47 0.35 1.40 9.20 11.20
25 270.18 321.00 0.84 0.93 0.28 44.16 13.29 12.74 65.81 -1.44 20.91 7.90 2.47 3.74 0.25 12.73 0.85 1.50 0.33 1.80 9.30 11.30
26 311.25 369.00 0.85 0.91 0.34 48.49 8.20 17.19 62.94 1.31 21.93 7.71 2.57 3.97 0.31 13.60 0.84 1.60 0.25 2.10 8.60 11.80
27 244.03 312.00 0.78 0.93 0.31 60.90 -2.12 21.65 68.10 -2.00 18.72 7.23 2.23 3.50 0.38 14.33 0.85 0.96 0.28 1.80 8.50 11.10
28 310.56 393.00 0.79 0.93 0.26 27.24 15.39 6.48 65.71 -2.66 22.35 8.83 1.91 3.84 0.21 13.87 0.85 1.14 0.25 2.20 10.90 13.70
29 227.63 282.00 0.81 0.85 0.27 41.50 16.08 11.76 65.85 0.02 20.79 8.74 2.81 3.95 0.34 13.50 0.85 1.85 0.32 2.70 7.40 8.80
30 207.44 248.00 0.84 0.87 0.19 41.57 1.66 14.34 65.36 -2.73 20.29 8.96 2.70 3.85 0.24 13.90 0.86 1.00 0.30 3.20 8.00 9.00
31 204.17 238.00 0.86 0.89 0.29 40.04 16.64 11.93 63.46 0.13 20.81 8.69 2.91 3.56 0.20 13.07 0.84 1.00 0.20 2.20 10.50 11.20
32 244.80 289.00 0.85 0.91 0.31 40.90 15.88 11.51 62.73 -0.12 20.45 7.42 2.26 3.87 0.31 13.10 0.87 1.00 0.15 1.50 8.40 9.40
33 330.28 395.00 0.83 0.87 0.27 38.78 14.69 12.51 62.92 0.68 22.28 7.86 2.37 4.01 0.23 12.60 0.86 1.10 0.37 3.40 9.90 13.60
34 230.36 270.00 0.85 0.89 0.29 38.50 13.62 13.21 60.69 -0.92 21.14 9.66 2.99 3.52 0.34 15.50 0.83 1.13 0.36 3.40 10.80 14.70

Table 3

Analysis of apple fruit and chips quality indexes"

指标
Index
均值
Mean
变幅
Range
标准差
Standard deviation
变异系数
CV (%)
果实
Fruit
X1 质量 Weight (g) 217.64 102.33—330.28 47.48 21.82
X2 体积 Volume (cm3) 265.85 120.00—395.00 57.33 21.57
X3 密度 Density (g?cm-3) 0.82 0.77—0.86 0.03 3.42
X4 果形指数 Shape index 0.89 0.80—0.96 0.04 4.30
X5 果核比例 Proportion of core 0.27 0.19—0.34 0.04 13.75
X6 L*值(皮) L* value (peel) 43.93 27.24—60.9 7.09 16.14
X7 a*值(皮) a* value (peel) 8.18 -9.74—18.36 8.19 100.12
X8 b*值(皮) b* value (peel) 14.84 6.48—24.96 4.46 30.05
X9 L*值(肉) L* value (pulp) 64.79 60.69—68.51 1.85 2.85
X10 a*值(肉) a* value (pulp) -1.18 -4.87—1.31 1.45 122.83
X11 b*值(肉) b* value (pulp) 20.85 14.24—23.42 1.61 7.71
X12 果皮硬度 Hardness of peel (g) 8.01 4.98—12.48 1.53 19.11
X13 果肉硬度 Hardness of pulp (g) 2.46 1.44—3.24 0.46 18.72
X14 pH 3.72 2.96—4.51 0.29 7.68
X15 可滴定酸 Titratable acid (%) 0.31 0.15—0.66 0.10 34.22
X16 可溶性固形物 Soluble solid (%) 12.76 9.30—15.50 1.46 11.45
X17 含水率 Moisture 0.86 0.82—0.90 0.02 2.14
X18 粗纤维 Crude fiber (%) 1.11 0.80—1.85 0.23 20.73
X19 粗蛋白 Crude protein (%) 0.32 0.15—0.58 0.08 25.19
X20 VC (mg/100 g) 2.46 0.80—7.60 1.33 54.16
X21 还原糖 Reducing sugar (%) 8.85 6.80—11.10 1.21 13.71
X22 总糖 Total sugar (%) 11.30 8.20—14.70 1.84 16.32
脆片
Chips
L*L* value 69.96 58.93—84.79 6.51 9.31
a*a* value 12.82 5.51—18.70 2.88 22.46
b*b* value 31.57 24.50—37.81 2.87 9.09
硬度 Hardness (g) 10.56 6.38—23.93 3.29 31.16
脆度 Crispness (mm) 0.95 0.50—2.41 0.44 46.32
可溶性固形物 Soluble solid (%) 83.17 68.00—95.00 6.87 8.26
可滴定酸 Titratable acid (%) 1.28 0.54—2.93 0.49 38.28
总酚 Total phenol (mg?g-1) 6.03 0.60—16.07 3.11 51.58
果胶 Pectin (g?kg-1) 24.40 14.54—42.58 5.81 23.81
可溶性糖 Soluble sugar (%) 73.26 58.68—85.12 6.04 8.24
糖酸比 Sugar-acid ratio 65.50 26.57—151.31 26.07 39.80
粗蛋白 Crude protein (%) 1.95 0.54—4.25 0.78 40.00
粗纤维 Crude fat (%) 4.34 2.92—6.36 0.75 17.28
复水比 Rehydration ratio 3.48 2.57—4.80 0.52 14.94
出品率 Output ratio (%) 14.32 10.14—18.65 2.08 14.53
水分含量 Moisture (%) 6.30 2.94—8.70 1.64 26.03
膨化度 Puffing degree 1.28 1.10—1.42 0.09 7.03

Table 4

Rotating component matrix of chips indexes"

PC1 PC2 PC3 PC4 PC5 PC6
L*L* value 0.005 0.071 0.025 0.977 0.023 0.070
a*a* value 0.090 0.290 0.012 -0.915 0.031 -0.033
b*b* value 0.111 0.783 -0.222 -0.064 0.023 -0.191
硬度 Hardness 0.665 -0.396 -0.188 0.005 0.256 0.034
脆度 Crispness 0.045 -0.738 -0.368 -0.033 0.191 0.170
可溶性固形物 Soluble solid 0.031 0.308 -0.658 0.202 0.424 -0.161
可滴定酸 Titratable acid 0.947 0.031 0.070 -0.030 0.077 0.053
总酚 Total phenol -0.315 0.729 0.022 -0.223 0.049 0.059
果胶 Pectin 0.644 -0.120 -0.006 0.110 -0.252 0.143
可溶性糖 Soluble sugar -0.234 0.027 0.060 -0.017 0.835 -0.055
糖酸比 Sugar-acid ratio -0.904 0.044 -0.025 0.128 0.231 0.030
粗蛋白 Crude protein 0.069 -0.347 0.084 0.030 -0.040 0.814
粗纤维 Crude fiber -0.092 0.210 0.192 -0.020 -0.676 0.396
复水比 Rehydration ratio -0.100 0.184 0.651 -0.147 -0.017 0.432
出品率 Output ratio -0.106 -0.032 -0.072 -0.142 0.438 -0.725
水分含量Moisture 0.203 -0.153 -0.326 -0.007 0.180 0.142
膨化度 Puffing degree 0.107 0.115 0.896 0.165 0.078 -0.007
特征值 Eigen value (λ) 3.453 3.009 2.351 1.737 1.580 1.028
累计方差贡献率
Cumulative variance contribution (%)
20.313 38.016 51.844 62.061 71.356 77.402

Table 5

Judgment matrix Y-P"

Y P1 P2 P3 P4 P5 P6 权重 Weight
P1 1 2 3 4 5 5 0.3724
P2 1/2 1 3 3 4 4 0.2665
P3 1/3 1/3 1 3 3 3 0.1583
P4 1/4 1/3 1/3 1 2 2 0.0890
P5 1/5 1/4 1/3 1/2 1 1 0.0569
P6 1/5 1/4 1/3 1/2 1 1 0.0569

Table 6

Rank and score of the comprehensive quality of chips"

名称
Name
排名
Rank
得分
Score
名称
Name
排名
Rank
得分
Score
辽宁华红 Liaoning Huahong 1 0.7933 河北富士 Hebei Fuji 18 0.5051
辽宁华金 Liaoning Huajin 2 0.7408 山西半坡秦冠 Shanxi Banpo Qinguan 19 0.5021
山东烟富6号 Shandong Yanfu 6 3 0.7285 山东新红星 Shandong Starkrimson 20 0.4981
陕西青苹 Shaanxi Granny Smith 4 0.7018 甘肃花牛 Gansu Huaniu 21 0.4952
陕西瑞阳 Shaanxi Ruiyang 5 0.7010 辽宁秋锦 Liaoning Qiujin 22 0.4844
山西半坡富士 Shanxi Banpo Fuji 6 0.6816 山东红星 Shandong Starking 23 0.4601
辽宁华月 Liaoning Huayue 7 0.6713 辽宁新红星 Liaoning Starkrimson 24 0.4537
辽宁金冠 Liaoning Golden Delicious 8 0.6681 辽宁寒富 Liaoning Hanfu 25 0.4507
辽宁乔纳金 Liaoning Jonagold 9 0.6528 甘肃富士 Gansu Fuji 26 0.4482
山东富士(淄博)Shandong Fuji (Zibo) 10 0.6403 辽宁华富 Liaoning Huafu 27 0.4327
新疆富士 Xinjiang Fuji 11 0.6190 甘肃秦冠 Gansu Qinguan 28 0.4071
甘肃金冠 Gansu Golden Delicious 12 0.6055 陕西秦红 Shaanxi Qinhong 29 0.3871
山东金冠(泰安)Shandong Golden Delicious (Taian) 13 0.5870 山东富士(栖霞)Shandong Fuji (Qixia) 30 0.3709
陕西长密欧 Shaanxi Changmiou 14 0.5679 山东金冠(淄博) Shandong Golden Delicious (Zibo) 31 0.3526
陕西富士 Shaanxi Fuji 15 0.5259 山东国光 Shandong Ralls 32 0.3524
山东红将军 Shandong Hongjiangjun 16 0.5069 辽宁长富2号 Liaoning Changfu 2 33 0.3281
山西坡顶富士 Shanxi Poding Fuji 17 0.5059 陕西秦冠 Shanxi Qinguan 34 0.2069

Table 7

Analysis of correlation between indicators of raw material and core indexes of chips"

L*
L* Value
脆度
Crispness
膨化度
Puffing degree
可滴定酸Titratable acid 可溶性糖
Soluble sugar
粗蛋白
Crude protein
质量 Weight -0.005 -0.186 0.013 0.139 0.191 -0.054
体积 Volume -0.003 -0.187 -0.005 0.184 0.115 -0.010
密度 Density -0.053 -0.013 0.115 -0.266 0.450** -0.334
果形指数 Shape index 0.390* -0.272 0.136 0.006 -0.268 -0.005
果核比例 Proportion of core -0.082 -0.365* 0.183 -0.572** 0.232 -0.295
L*值(皮) L* value (peel) 0.239 -0.005 0.198 0.003 -0.200 -0.041
a*值(皮) a* value (peel) -0.273 -0.071 -0.194 -0.238 0.285 -0.252
b*值(皮) b*value (peel) 0.293 0.024 0.181 0.090 -0.271 0.034
L*值(肉) L* value (pulp) 0.305 0.101 0.117 0.210 -0.189 0.076
a*值(肉) a* value (pulp) -0.428* -0.080 -0.142 -0.317 0.160 -0.155
b*值(肉) b* value (pulp) -0.177 0.033 -0.107 -0.521** -0.160 -0.007
果皮硬度 Hardness of peel -0.319 -0.034 -0.020 -0.098 0.180 -0.097
果肉硬度 Hardness of pulp -0.191 0.019 -0.105 -0.147 0.267 -0.284
pH -0.527** 0.314 -0.229 -0.167 -0.046 0.010
可滴定酸 Titratable acid 0.554** -0.192 0.235 0.089 -0.134 0.111
可溶性固形物 Soluble solid 0.148 -0.024 0.089 -0.102 0.347* -0.336
含水率 Moisture -0.068 -0.239 0.109 0.249 -0.259 0.192
粗纤维 Crude fiber -0.212 0.073 -0.044 -0.267 0.347* -0.057
粗蛋白 Crude protein 0.185 0.352* -0.143 0.247 -0.109 -0.056
VC 0.361* 0.115 0.284 0.234 0.006 0.007
还原糖 Reducing sugar -0.145 -0.036 0.054 -0.051 0.204 -0.180
总糖 Total sugar 0.022 -0.085 0.220 0.178 0.176 -0.363*

Fig. 1

Structure diagram of BP neural network"

Table 8

Prediction result of chips-processing suitability evaluation model based on BP neural network"

学习模型
Learning model
验证样本
Validation sample
实际得分
Actual score
预测得分
Predicted score
相对误差
Relative error (%)
1 辽宁金冠 Liaoning Golden Delicious 0.6681 0.6590 -1.35
陕西富士 Shaanxi Fuji 0.5259 0.4808 -8.58
山西坡顶富士 Shanxi Poding Fuji 0.5059 0.5235 3.48
甘肃秦冠 Gansu Qinguan 0.4071 0.4146 1.84
山东金冠(淄博) Zibo Golden Delicious 0.3526 0.3761 6.68
2 陕西瑞洋 Shaanxi Ruiyang 0.7010 0.7480 6.71
山东金冠(泰安)Taian Golden Delicious 0.5870 0.5906 0.62
甘肃秦冠 Gansu Qinguan 0.4071 0.4146 1.84
山西半坡秦冠 Shanxi Banpo Qinguan 0.5021 0.5513 9.78
山东金冠(淄博)Zibo Golden Delicious 0.3526 0.3761 6.68
3 辽宁华月 Liaoning Huayue 0.6713 0.6885 2.57
山东国光(淄博)Zibo Ralls 0.5069 0.5149 1.58
甘肃金冠 Gansu Golden Delicious 0.6055 0.6291 3.89
陕西秦红 Shaanxi Qinhong 0.3871 0.3608 -6.80
辽宁新红星 Liaoning Starkrimson 0.4537 0.4959 9.30

Fig. 2

Stability verification of chips-processing suitability evaluation model"

[1] 中华人民共和国国家统计局数据库. [ 2018-3-24]. . [2018-3-24].
National Bureau of Statistics of the People’s Republic of China. [ 2018-3-24]. . [2018-3-24].
[2] 宋哲, 王宏, 里程辉, 于年文, 张秀美, 李宏建 . 我国苹果产业存在的主要问题、发展趋势及解决办法. 江苏农业科学, 2016,44(9):4-8. doi: 10.15889/j.issn.1002-1302.2016.09.002.
doi: 10.15889/j.issn.1002-1302.2016.09.002
SONG Z, WANG H, LI C H, YU N W, ZHANG X M, LI H J . The main problems, development trends and solutions of apple industry in China. Agricultural Sciences of Jiangsu, 2016,44(9):4-8. doi: 10.15889 /j.issn.1002-1302.2016.09.002. (in Chinese)
doi: 10.15889/j.issn.1002-1302.2016.09.002
[3] 焦艺, 刘璇, 毕金峰, 吴昕烨, 周沫, 曾目成 . 蟠桃品种用于加工鲜榨汁的适宜性评价. 食品科学, 2015,36(1):41-45. doi: 10.7506/ spkx1002-6630-201501008.
doi: 10.7506/spkx1002-6630-201501008
JIAO Y, LIU X, BI J F, WU X Y, ZHOU M, ZENG M C . Suitability evaluation of flat peach cultivars for fresh juice-processing. Food Science, 2015,36(1):41-45. doi: 10.7506/spkx1002-6630-201501008. (in Chinese)
doi: 10.7506/spkx1002-6630-201501008
[4] 郭春苗, 周晓明, 张雯, 樊丁宇, 谢辉, 闰鹏, 卢春生 . 不同葡萄品种加工绿葡萄干的适宜性分析. 食品科学, 2012,33(19):62-66.
GUO C M, ZHOU X M, ZHANG W, FAN D Y, XIE H, RUN P, LU C S . Suitability analysis of different grape varieties for preparing green raisins. Food Science, 2012,33(19):62-66. (in Chinese)
[5] 沈月, 高美须, 杨丽, 赵鑫, 陈雪, 王志东, 李淑荣, 王丽 . 中国主栽青辣椒品种鲜切加工适宜性评价. 农业工程学报, 2016,32(s2):359-368. doi: 10.11975/j.issn.1002-6819.2016.z2.051.
doi: 10.11975/j.issn.1002-6819.2016.z2.051
SHEN Y, GAO M X, YANG L, ZHAO X, CHEN X, WANG Z D, LI S R, WANG L . Suitability analysis of fresh-cut vegetable processing for twenty main green capsicum cultivars in China. Transactions of Chinese Society of Agricultural Engineering, 2016,32(s2):359-368. doi: 10.11975/j.issn.1002-6819.2016.z2.051. (in Chinese)
doi: 10.11975/j.issn.1002-6819.2016.z2.051
[6] AGCAM E, AKYILDIZ A . A study on the quality criteria of some mandarin varieties and their suitability for juice processing. Journal of Food Processing, 2014,2014(12):1-8. doi: 10.1155/2014/982721.
[7] LAMUREANU G, ALEXE C, VINTILA M . Suitability for processing as puree of some fruit varieties of peach group. Journal of Horticulture Forestry & Biotechnology, 2014,18(3):51-57.
[8] FUJIWARA T, KUBO T . Suitability of unripe Japanese pear for semi-dried fruit processing. Nippon Shokuhin Kagaku Kogaku Kaishi, 2017,64(11):533-541. doi: 10.3136/nskkk.64.533.
doi: 10.3136/nskkk.64.533
[9] 聂继云, 毋永龙, 李海飞, 王昆, 李静, 李志霞, 徐国锋 . 苹果品种用于加工鲜榨汁的适宜性评价. 农业工程学报, 2013,29(17):271-278. doi: 10.3969/j.issn.1002-6819.2013.17.035.
doi: 10.3969/j.issn.1002-6819.2013.17.035
NIE J Y, WU Y L, LI H F, WANG K, LI J, LI Z X, XU G F . Suitability evaluation of apple cultivars for fresh juice-processing. Transactions of Chinese Society of Agricultural Engineering, 2013,29(17):271-278. doi: 10.3969/j.issn.1002-6819.2013.17.035. (in Chinese)
doi: 10.3969/j.issn.1002-6819.2013.17.035
[10] 张小燕, 赵凤敏, 兴丽, 刘威, 杨延辰, 杨炳南 . 不同马铃薯品种用于加工油炸薯片的适宜性. 农业工程学报, 2013,29(8):276-283. doi: 10.3969/j.issn.1002-6819.2013.08.033.
doi: 10.3969/j.issn.1002-6819.2013.08.033
ZHANG X Y, ZHAO F M, XING L, LIU W, YANG Y C, YANG B N . Suitability evaluation of potato varieties used for chips processing. Transactions of Chinese Society of Agricultural Engineering, 2013,29(8):276-283. doi: 10.3969/j.issn.1002-6819.2013.08.033. (in Chinese)
doi: 10.3969/j.issn.1002-6819.2013.08.033
[11] ONSEKIZOGLU P, BAHCECI K S, ACAR M J . Clarification and the concentration of apple juice using membrane processes: A comparative quality assessment. Journal of Membrane Science, 2010,352(1/2):160-165. doi: 10.1016/j.memsci.2010.02.004.
doi: 10.1016/j.memsci.2010.02.004
[12] YI J Y, ZHOU L Y, BI J F, WANG P, LIU X, Wu X Y . Influence of number of puffing times on physicochemical, color, texture, and microstructure of explosion puffing dried apple chips. Drying Technology, 2015,34(7):773-782. doi: 10.1080/07373937.2015. 1076838.
doi: 10.1080/07373937.2015.1076838
[13] 龚玲娣, 徐清渠 . GB/T 12456-2008食品中总酸的测定[S]. 北京: 中国标准出版社, 2008.
GONG L D, XU Q Q. GB/T 12456-2008 Determination of total acid in foods [S]. Beijing: Standards Press of China, 2008. ( in Chinese)
[14] 聂继云, 李静, 徐国锋, 李海飞, 毋永龙, 李志霞, 闫震, 匡立学 . NY/T 2637-2014水果和蔬菜可溶性固形物含量的测定折射仪法[S]. 北京: 中国农业出版社, 2014.
NIE J Y, LI J, XU G F, LI H F, WU Y L, LI Z X, YAN Z, KUANG L X. NY/T 2637-2014 Refractmetric method for determination of total soluble solids in fruits and vegetables [S]. Beijing: China Agriculture Press, 2014. ( in Chinese)
[15] GB 5009. 3-2016食品中水分的测定[S]. 北京: 中国标准出版社, 2016.
GB 5009. 3-2016 Determination of moisture in foods [S]. Beijing: Standards Press of China, 2016. ( in Chinese)
[16] 卫生部食品卫生监督检验所. GB /T 5009.10-2003植物类食品中粗纤维的测定[S]. 北京: 中国标准出版社, 2003.
Ministry of Health Food Hygiene Supervision and Inspection Institute. GB /T 5009.10-2003 Determination of crude fiber in vegetable foods [S]. Beijing: Standards Press of China, 2013. ( in Chinese)
[17] GB 5009. 5-2016食品中蛋白质的测定[S]. 北京: 中国标准出版社, 2016.
GB 5009. 5-2016 Determination of protein in foods[S]. Beijing: Standards Press of China, 2016. ( in Chinese)
[18] GB 5009. 86-2016食品安全国家标准食品中抗坏血酸的测定[S]. 北京: 中国标准出版社, 2016.
GB 5009. 86-2016 Determination of Ascorbic Acid in Foods [S]. Beijing: Standards Press of China, 2016. ( in Chinese)
[19] SU H K, CHOI Y J, LEE H, LEE S H, AHN J B, NOH B S, MIN S H . Physicochemical properties of jujube powder from air, vacuum, and freeze drying and their correlations. Applied Biological Chemistry, 2012,55(2):271-279. doi: 10.1007/s13765-012-1039-3.
doi: 10.1007/s13765-012-1039-3
[20] ABID M, JABBAR S, WU T, HASHIM M M, HU B, LEI S C, ZHANG X, ZENG X X . Effect of ultrasound on different quality parameters of apple juice. Ultrasonics Sonochemistry, 2013,20(5):1182-1187. doi: 10.1016/j.ultsonch.2013.02.010.
doi: 10.1016/j.ultsonch.2013.02.010 pmid: 23522904
[21] 方金豹, 庞荣丽, 何为华, 李君, 吴斯洋, 郭琳琳, 俞宏 . NY/T 2016-2011水果及其制品中果胶含量的测定—分光光度法[S]. 北京: 中国农业出版社, 2011.
FANG J B, PANG R L, HE W H, LI J, WU S Y, GUO L L, YU H. NY/T 2016-2011 Determination of pectin content in fruits and derived products—Spectrophotometry method[S]. Beijing: China Agriculture Press, 2011. ( in Chinese)
[22] 聂继云, 李志霞, 匡立学, 李静, 李海飞, 徐国锋, 闫震 . NY/T 2742-2015 水果及制品可溶性糖的测定—3, 5-二硝基水杨酸比色法. 北京: 中国农业出版社, 2015.
NIE J Y, LI Z X, KUANG L X, LI J, LI H F, XU G F, YAN Z. NY/T 2742-2015 Determination of soluble sugars in fruits and derived products- 3,5-dinitrosalicylic acid colorimetry. Beijing: China Agriculture Press, 2015. ( in Chinese)
[23] 龙映均, 刘四新, 余敏华, 陈桃, 李从发 . 椰纤果热风干燥工艺优化研究. 食品与机械, 2011,27(4):146-148, 162. doi: 10.3969/j.issn. 1003-5788.2011.04.043.
doi: 10.3969/j.issn.1003-5788.2011.04.043
LONG Y J, LIU S X, YU M H, CHEN T, LI C F . Optimization of the hot-air drying processing condition of nata. Science and Technology of Food Industry, 2011,27(4):146-148,162. doi: 10.3969/j.issn.1003- 5788.2011.04.043. (in Chinese)
doi: 10.3969/j.issn.1003-5788.2011.04.043
[24] 王沛, 毕金峰, 白沙沙, 公丽艳, 王轩 . 不同原料品种的苹果脆片品质评价及其相关性分析. 食品与机械, 2012,28(2):9-10. doi: 10.3969/j.issn.1003-5788.2012.02.003.
WANG P, BI J F, BAI S S, GONG L Y, WANG X . Determination of quality evaluation and correlation analysis of varieties apple chips. Science and Technology of Food Industry, 2012,28(2):9-10. doi: 10.3969/j.issn.1003-5788.2012.02.003. (in Chinese)
[25] 毕金峰, 王雪媛, 周林燕, 吴昕烨, 高琨, 吕健, 彭健 . 脉动压差闪蒸处理对苹果片水分散失特性及品质影响. 农业工程学报, 2016
doi: 10.11975/j.issn.1002-6819.2016.z2.053
32(2):376-382. doi: 10.11975/j.issn.1002-6819.2016.z2.053.
doi: 10.11975/j.issn.1002-6819.2016.z2.053
26 BI J F, WANG X Y, ZHOU L Y, WU X Y, GAO K, LV J, PENG J . Effect of instant controlled pressure drop drying on water loss and quality in apple slices. Transactions of Chinese Society of Agricultural Engineering, 2016,32(2):376-382. doi: 10.11975/j.issn.1002-6819. 2016.z2.053. (in Chinese)
doi: 10.11975/j.issn.1002-6819.2016.z2.053
[26] 孙修东, 李宗斌, 陈富民 . 基于人工神经网络的多指标综合评价方法研究. 郑州轻工业学院学报(自然科学版), 2003,18(2):11-14. doi: 10.3969/j.issn.1004-1478.2003.02.003.
SUN X D, LI Z B, CHEN F M . Research on multiple attribute synthetical evaluation methods based on artificial neural network. Journal of Zhengzhou Institute of light Industry (Natural Science Edition), 2003,18(2):11-14. doi: 10.3969/j.issn.1004-1478.2003.02. 003. (in Chinese)
[27] 刘俊威, 吕惠进 . 人工神经网络在水质预测中的应用研究. 长江科学院院报, 2012,29(9):95-97. doi: 10.3969/j.issn.1001-5485.2012.09. 022.
doi: 10.3969/j.issn.1001-5485.2012.09.022
LIU J W, LV H J . Artificial Neural Network applied in water quality prediction. Journal of Yangtze River Scientific Research Institute, 2012,29(9):95-97. doi: 10.3969/j.issn.1001-5485.2012.09.022. (in Chinese)
doi: 10.3969/j.issn.1001-5485.2012.09.022
[28] 潘玉成, 叶乃兴, 潘玉华, 赵仕宇 . 人工神经网络在坦洋工夫红茶感官品质评定中的应用研究. 茶叶科学, 2015(5):465-472. doi: 10.3969/j.issn.1000-369X.2015.05.013.
PAN Y C, YE N X, PAN Y H, ZHAO S Y . Application research of Artificial Neural Network in sensory quality evaluation of TanYang GongFu black tea.Journal of Tea Science, 2015(5):465-472. doi: 10.3969/j.issn.1000-369X.2015.05.013. (in Chinese)
[29] 吴殿廷, 李东方 . 层次分析法的不足及其改进的途径. 北京师范大学学报(自然科学版), 2004,40(2):264-268. doi: 10.3321/j.issn: 0476-0301.2004.02.025.
doi: 10.3321/j.issn:0476-0301.2004.02.025
WU D T, LI D F . Shortcomings of Analytical hierarchy process and the pain to Improve the method. Journal of Beijing Normal University (Natural Science Edition), 2004,40(2):264-268. doi: 10.3321/j.issn: 0476-0301.2004.02.025. (in Chinese)
doi: 10.3321/j.issn:0476-0301.2004.02.025
[30] XIA M, FANG J, TANG Y, WANG Z . Dynamic depression control of chaotic neural networks for associative memory. Neurocomputing, 2010,73(4/6):776-783. doi: 10.1016/j.neucom.2009.10.015.
doi: 10.1016/j.neucom.2009.10.015
[31] FUNES E, ALLOUCHE Y, BELTRAN G, JIMENEZ A . A Review: Artificial Neural Networks as tool for control food industry process. Journal of Sensor Technology, 2015,5(1):28.
doi: 10.4236/jst.2015.51004
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