基于BP人工神经网络算法的苹果制干适宜性评价

doi:10.3864/j.issn.0578-1752.2019.01.012

Abstract

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

ZHANG Biao,LIU Xuan,BI JinFeng,WU XinYe,JIN Xin,LI Xuan,LI Xiao. Suitability Evaluation of Apple for Chips-Processing Based on BP Artificial Neural Network[J].Scientia Agricultura Sinica, 2019, 52(1): 129-142.

Figures/Tables 10

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 1

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 2

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 V_C (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值 L value	69.96	58.93—84.79	6.51	9.31
	a值 a value	12.82	5.51—18.70	2.88	22.46
	b值 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 3

Table 4

Table 5

Table 6

Table 7

Fig. 1

Table 8

Fig. 2

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	PC1	PC2	PC3	PC4	PC5	PC6
L值 L value	0.005	0.071	0.025	0.977	0.023	0.070
a值 a value	0.090	0.290	0.012	-0.915	0.031	-0.033
b值 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

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

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

	L值 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） bvalue (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
V_C	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*

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

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

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