药学学报

No.	Producing area	Longtitude	Latitude	Altitude/m
1	Huinong, Ningxia	106.80°	39.06°	1 093
2	Huinong, Ningxia	106.61°	39.08°	1 054
3	Huinong, Ningxia	106.53°	39.01°	1 054
4	Huinong, Ningxia	106.59°	39.06°	1 054
5	Xixia, Ningxia	106.20°	38.66°	1 078
6	Xixia, Ningxia	106.20°	38.66°	1 079
7	Xixia, Ningxia	106.14°	38.64°	1 074
8	Xixia, Ningxia	106.10°	38.64°	1 082
9	Xixia, Ningxia	106.10°	38.64°	1 082
10	Hongsipu, Ningxia	105.97°	37.40°	1 272
11	Hongsipu, Ningxia	105.95°	37.40°	1 330
12	Litong, Ningxia	106.26°	37.78°	1 136
13	Zhongning, Ningxia	105.62°	37.50°	1 188
14	Zhongning, Ningxia	105.93°	37.46°	1 260
15	Zhongning, Ningxia	105.93°	37.46°	1 260
16	Zhongning, Ningxia	105.72°	37.48°	1 200
17	Zhongning, Ningxia	105.72°	37.48°	1 200
18	Zhongning, Ningxia	105.72°	37.48°	1 200
19	Zhongning, Ningxia	105.72°	37.48°	1 200
20	Zhongning, Ningxia	105.68°	37.30°	1 174
21	Zhongning, Ningxia	105.68°	37.30°	1 174
22	Zhongning, Ningxia	105.99°	37.27°	1 223
23	Zhongning, Ningxia	105.63°	37.38°	1 213
24	Zhongning, Ningxia	105.63°	37.29°	1 312
25	Zhongning, Ningxia	105.57°	37.31°	1 347
26	Shapotou, Ningxia	105.13°	37.54°	1 189
27	Shapotou, Ningxia	105.43°	37.51°	1 179
28	Shapotou, Ningxia	105.40°	37.54°	1 170
29	Yuanzhou, Ningxia	106.16°	36.40°	1 496
30	Yuanzhou, Ningxia	106.16°	36.45°	1 525
31	Yuanzhou, Ningxia	106.10°	36.37°	1 517
32	Jingyuan, Gansu	105.27°	36.85°	1 757
33	Jingyuan, Gansu	105.16°	36.93°	1 679
34	Jingyuan, Gansu	105.16°	36.93°	1 679
35	Jingyuan, Gansu	105.02°	37.00°	1 630
36	Jingyuan, Gansu	105.02°	37.00°	1 630
37	Jingyuan, Gansu	104.86°	37.03°	1 595
38	Jingyuan, Gansu	104.86°	37.03°	1 595
39	Jingtai, Gansu	94.78°	36.44°	2 754
40	Gulang, Gansu	103.51°	37.54°	1 716
41	Gulang, Gansu	103.51°	37.54°	1 716
42	Gulang, Gansu	103.46°	37.48°	1 835
43	Gulang, Gansu	103.40°	37.54°	1 817
44	Ganzhou, Gansu	100.60°	38.87°	1 469
45	Ganzhou, Gansu	100.60°	38.87°	1 469
46	Linze, Gansu	100.28°	39.31°	1 379
47	Jinta, Gansu	99.49°	40.29°	1 128
48	Jinta, Gansu	99.51°	40.31°	1 104
49	Jinta, Gansu	98.73°	40.18°	1 189
50	Yumen, Gansu	97.86°	40.21°	1 212
51	Yumen, Gansu	97.39°	39.97°	1 657
52	Guazhou, Gansu	96.14°	40.53°	1 188
53	Guazhou, Gansu	96.51°	40.53°	1 198
54	Guazhou, Gansu	96.51°	40.53°	1 198
55	Guazhou, Gansu	95.71°	40.06°	1 534
56	Wulateqianqi, Inner Mongolia	109.07°	40.63°	1 017
57	Wulateqianqi, Inner Mongolia	109.07°	40.63°	1 017
58	Wulateqianqi, Inner Mongolia	109.07°	40.62°	1 015
59	Wulateqianqi, Inner Mongolia	109.07°	40.62°	1 015
60	Wulateqianqi, Inner Mongolia	109.07°	40.62°	1 015
61	Wulateqianqi, Inner Mongolia	109.07°	40.61°	1 014
62	Wulateqianqi, Inner Mongolia	109.08°	40.60°	1 016
63	Wulateqianqi, Inner Mongolia	109.08°	40.63°	1 015
64	Wulateqianqi, Inner Mongolia	109.08°	40.63°	1 016
65	Wulateqianqi, Inner Mongolia	109.14°	40.59°	1 015
66	Wulateqianqi, Inner Mongolia	109.14°	40.59°	1 015
67	Wuyuani, Inner Mongolia	108.24°	41.18°	1 023
68	Wuyuani, Inner Mongolia	108.24°	41.18°	1 023
69	Wuyuani, Inner Mongolia	108.24°	41.18°	1 023
70	Wuyuani, Inner Mongolia	108.20°	41.16°	1 023
71	Hangjinhouqi, Inner Mongolia	106.99°	40.96°	1 035
72	Hangjinhouqi, Inner Mongolia	106.99°	40.96°	1 035
73	Hangjinhouqi, Inner Mongolia	106.98°	40.95°	1 036
74	Hangjinhouqi, Inner Mongolia	106.96°	40.93°	1 036
75	Geermu, Qinghai	94.78°	36.44°	2 754
76	Geermu, Qinghai	94.81°	36.44°	2 778
77	Geermu, Qinghai	95.75°	36.44°	3 178
78	Dulan, Qinghai	96.42°	36.45°	2 718
79	Dulan, Qinghai	96.40°	36.45°	2 696
80	Delingha, Qinghai	97.42°	37.24°	2 862
81	Delingha, Qinghai	96.74°	37.35°	2 817
82	Delingha, Qinghai	96.72°	37.32°	2 810
83	Delingha, Qinghai	97.16°	37.30°	2 815
84	Wulan, Qinghai	98.35°	36.96°	2 924
85	Jinghe, Xingjiang	82.65°	44.54°	332
86	Jinghe, Xingjiang	82.60°	44.60°	295
87	Jinghe, Xingjiang	82.70°	44.56°	308
88	Jinghe, Xingjiang	82.63°	44.62°	301
89	Jinghe, Xingjiang	82.75°	44.54°	316
90	Jinghe, Xingjiang	82.68°	44.56°	312
91	Jinghe, Xingjiang	82.65°	44.57°	305
92	Jinghe, Xingjiang	82.62°	44.58°	303
93	Jinghe, Xingjiang	82.64°	44.59°	293
94	Jinghe, Xingjiang	82.73°	44.52°	325

No.	Producing area	Longtitude	Latitude	Altitude/m
1	Huinong, Ningxia	106.80°	39.06°	1 093
2	Huinong, Ningxia	106.61°	39.08°	1 054
3	Huinong, Ningxia	106.53°	39.01°	1 054
4	Huinong, Ningxia	106.59°	39.06°	1 054
5	Xixia, Ningxia	106.20°	38.66°	1 078
6	Xixia, Ningxia	106.20°	38.66°	1 079
7	Xixia, Ningxia	106.14°	38.64°	1 074
8	Xixia, Ningxia	106.10°	38.64°	1 082
9	Xixia, Ningxia	106.10°	38.64°	1 082
10	Hongsipu, Ningxia	105.97°	37.40°	1 272
11	Hongsipu, Ningxia	105.95°	37.40°	1 330
12	Litong, Ningxia	106.26°	37.78°	1 136
13	Zhongning, Ningxia	105.62°	37.50°	1 188
14	Zhongning, Ningxia	105.93°	37.46°	1 260
15	Zhongning, Ningxia	105.93°	37.46°	1 260
16	Zhongning, Ningxia	105.72°	37.48°	1 200
17	Zhongning, Ningxia	105.72°	37.48°	1 200
18	Zhongning, Ningxia	105.72°	37.48°	1 200
19	Zhongning, Ningxia	105.72°	37.48°	1 200
20	Zhongning, Ningxia	105.68°	37.30°	1 174
21	Zhongning, Ningxia	105.68°	37.30°	1 174
22	Zhongning, Ningxia	105.99°	37.27°	1 223
23	Zhongning, Ningxia	105.63°	37.38°	1 213
24	Zhongning, Ningxia	105.63°	37.29°	1 312
25	Zhongning, Ningxia	105.57°	37.31°	1 347
26	Shapotou, Ningxia	105.13°	37.54°	1 189
27	Shapotou, Ningxia	105.43°	37.51°	1 179
28	Shapotou, Ningxia	105.40°	37.54°	1 170
29	Yuanzhou, Ningxia	106.16°	36.40°	1 496
30	Yuanzhou, Ningxia	106.16°	36.45°	1 525
31	Yuanzhou, Ningxia	106.10°	36.37°	1 517
32	Jingyuan, Gansu	105.27°	36.85°	1 757
33	Jingyuan, Gansu	105.16°	36.93°	1 679
34	Jingyuan, Gansu	105.16°	36.93°	1 679
35	Jingyuan, Gansu	105.02°	37.00°	1 630
36	Jingyuan, Gansu	105.02°	37.00°	1 630
37	Jingyuan, Gansu	104.86°	37.03°	1 595
38	Jingyuan, Gansu	104.86°	37.03°	1 595
39	Jingtai, Gansu	94.78°	36.44°	2 754
40	Gulang, Gansu	103.51°	37.54°	1 716
41	Gulang, Gansu	103.51°	37.54°	1 716
42	Gulang, Gansu	103.46°	37.48°	1 835
43	Gulang, Gansu	103.40°	37.54°	1 817
44	Ganzhou, Gansu	100.60°	38.87°	1 469
45	Ganzhou, Gansu	100.60°	38.87°	1 469
46	Linze, Gansu	100.28°	39.31°	1 379
47	Jinta, Gansu	99.49°	40.29°	1 128
48	Jinta, Gansu	99.51°	40.31°	1 104
49	Jinta, Gansu	98.73°	40.18°	1 189
50	Yumen, Gansu	97.86°	40.21°	1 212
51	Yumen, Gansu	97.39°	39.97°	1 657
52	Guazhou, Gansu	96.14°	40.53°	1 188
53	Guazhou, Gansu	96.51°	40.53°	1 198
54	Guazhou, Gansu	96.51°	40.53°	1 198
55	Guazhou, Gansu	95.71°	40.06°	1 534
56	Wulateqianqi, Inner Mongolia	109.07°	40.63°	1 017
57	Wulateqianqi, Inner Mongolia	109.07°	40.63°	1 017
58	Wulateqianqi, Inner Mongolia	109.07°	40.62°	1 015
59	Wulateqianqi, Inner Mongolia	109.07°	40.62°	1 015
60	Wulateqianqi, Inner Mongolia	109.07°	40.62°	1 015
61	Wulateqianqi, Inner Mongolia	109.07°	40.61°	1 014
62	Wulateqianqi, Inner Mongolia	109.08°	40.60°	1 016
63	Wulateqianqi, Inner Mongolia	109.08°	40.63°	1 015
64	Wulateqianqi, Inner Mongolia	109.08°	40.63°	1 016
65	Wulateqianqi, Inner Mongolia	109.14°	40.59°	1 015
66	Wulateqianqi, Inner Mongolia	109.14°	40.59°	1 015
67	Wuyuani, Inner Mongolia	108.24°	41.18°	1 023
68	Wuyuani, Inner Mongolia	108.24°	41.18°	1 023
69	Wuyuani, Inner Mongolia	108.24°	41.18°	1 023
70	Wuyuani, Inner Mongolia	108.20°	41.16°	1 023
71	Hangjinhouqi, Inner Mongolia	106.99°	40.96°	1 035
72	Hangjinhouqi, Inner Mongolia	106.99°	40.96°	1 035
73	Hangjinhouqi, Inner Mongolia	106.98°	40.95°	1 036
74	Hangjinhouqi, Inner Mongolia	106.96°	40.93°	1 036
75	Geermu, Qinghai	94.78°	36.44°	2 754
76	Geermu, Qinghai	94.81°	36.44°	2 778
77	Geermu, Qinghai	95.75°	36.44°	3 178
78	Dulan, Qinghai	96.42°	36.45°	2 718
79	Dulan, Qinghai	96.40°	36.45°	2 696
80	Delingha, Qinghai	97.42°	37.24°	2 862
81	Delingha, Qinghai	96.74°	37.35°	2 817
82	Delingha, Qinghai	96.72°	37.32°	2 810
83	Delingha, Qinghai	97.16°	37.30°	2 815
84	Wulan, Qinghai	98.35°	36.96°	2 924
85	Jinghe, Xingjiang	82.65°	44.54°	332
86	Jinghe, Xingjiang	82.60°	44.60°	295
87	Jinghe, Xingjiang	82.70°	44.56°	308
88	Jinghe, Xingjiang	82.63°	44.62°	301
89	Jinghe, Xingjiang	82.75°	44.54°	316
90	Jinghe, Xingjiang	82.68°	44.56°	312
91	Jinghe, Xingjiang	82.65°	44.57°	305
92	Jinghe, Xingjiang	82.62°	44.58°	303
93	Jinghe, Xingjiang	82.64°	44.59°	293
94	Jinghe, Xingjiang	82.73°	44.52°	325

No.	Component	Regression equation	P values	Adjust R²
y₁	Zeaxanthin	y₁ = 0.206 254 8 - 0.00210 96x₆ - 0.005 089 3x₂₀ - 0.026 519 5x₃₉ + 0.004 533 2x₄₈	3.31E-11	0.443 9
y₂	β-Cryptoxanthin	y₂ = 0.001 576 - 0.000 072 49x₂₀ - 0.000 136 5x₂₃ - 0.000 010 64x₂₈ - 0.000 084 66x₄₃ + 0.000 102 0x₄₆	1.72E-10	0.435 5
y₃	β-Carotene	y3 = 0.035 737 - 0.007 060x₁₇ - 0.005 896x₁₈ - 0.006 281x₁₉ - 0.012 755x₂₁ + 0.007 614x₄₆	3.06E-12	0.477 1
y₄	Zeaxanthin dipalmitate	y₄ = -18.427 7 + 0.004 586x₄ - 0.118 425x₆ + 0.606 201x₁₇ + 0.740 070x₁₈ + 1.136 655x₁₉ + 0.929 495x₃₂ - 0.479 786x₄₄ - 0.581 787x₄₆ - 0.330 538x₄₇ - 0.551 557x₄₈	2.14E-12	0.538
y₅	Total carotenoids	y₅ = 24.321 9 - 0.165 0x₆ + 1.376 46x₁₇ + 1.107 55x₁₈ + 1.670 88x₁₉ + 1.391 11x₃₂ - 0.273 9x₃₃ - 0.529 97x₄₄ - 0.473 58x₄₅ - 1.262 67x₄₆	2.08E-14	0.592 7
y₆	Neutral polysaccharides	y₆ = 80.159 32 - 0.355 79x₆ - 0.707 18x₂₀ - 1.414 06x₂₃ - 1.219 59x₂₇ + 1.082 78x₃₅ - 0.894 85x₃₆ + 1.325 43x₄₁ - 0.283 31x₄₂ + 0.359 26x₄₈	6.78E-12	0.562 2
y₇	Acid polysaccharides	y₇ = 9.148 24 + 0.135 99x₁₈ + 0.101 36x₁₉ - 0.083 09x₄₃	1.37E-09	0.369 2
y₈	Total phenolic	y₈ = 6.845 64 + 0.412 99x₂₅ + 0.291 96x₂₆ + 0.365 91x₃₆ - 1.018 24x₄₁ - 0.042 45x₄₂	2.39E-10	0.463 3
y₉	Total flavonoids	y₉ = -5.465 896 - 0.112 732x₇ + 0.003 628x₈ - 1.827 112x₁₂ - 1.139 439x₂₃ - 0.344 761x₁₈ + 0.477 422x₁₉ + 0.231 034x₂₅ + 0.220 894x₂₆ + 1.245 965x₄₀ - 0.292 422x₄₁ - 0.199 244x₄₂ + 0.230 241x₄₃ - 0.718 579x₄₈	5.53E-06	0.679 8
y₁₀	Betaine	y₁₀ = 18.748 48 - 0.055 38x₆ - 0.965 68x₁₂ - 3.270 28x₂₃ - 2.288 40x₁₃ + 1.876 48x₃₇	6.23E-11	0.551 7
y₁₁	Protein	y₁₁ = -2.621 256 1 + 0.137 250 5x₇ - 0.002 735x₈ + 0.363 642x₃₀ + 0.289 77x₃₁ + 0.103 814 6x₃₃ - 0.603 991 1x₄₄ - 0.172 843 1x₄₅	2.41E-11	0.491 8
y₁₂	Fructose	y₁₂ = 331.3 - 0.003 527x₁ + 0.104 8x₂ + 0.026 91x₄ - 4.621x₇ + 2.637x₉ + 2.738x₃₁ - 2.956x₃₇ + 0.359x₃₈ + 9.471x₃₉ - 2.398x₄₁ - 2.405x₄₂ + 2.582x₄₇	< 2.2E-16	0.985 2
y₁₃	Glucose	y₁₃ = 451.622 46 - 0.010 031x₁ + 0.056 359x₂ + 0.050 514x₄ + 0.528 615x₆ - 0.974 702x₇ - 0.077 919x₈ + 1.242 797x₉ + 4.221 319x₁₄ - 4.653 498x₂₂ - 3.008 636x₂₅ + 3.558 910x₃₀ - 1.117 499x₃₂ - 2.156 630x₃₄ - 2.201 215x₃₇ - 0.111 315x₃₈ + 3.097 005x₄₇	< 2.2E-16	0.981 7
y₁₄	Sucrose	y₁₄ = 12.44 + 0.000 384 2x₂ - 0.002 907x₆ + 0.009 014x₇ + 0.066 31x₁₅ - 0.092 68x₂₂ + 0.010 16x₂₆ + 0.023 99x₃₃ - 0.022 72x₃₄ - 0.035 47x₃₇ + 0.010 29x₄₄ - 0.022 89x₄₅	< 2.2E-16	0.809 3
y₁₅	Maltose	y₁₅ = 3.036 29 + 0.202 90x₂₆ + 0.081 58x₃₆ - 0.258 88x₄₁	< 2.2E-16	0.613 6
y₁₆	Glutamic acid	y₁₆ = 451.987 96 - 9.318 31x₅ - 0.498 64x₇ - 17.700 01x₁₂ - 13.213 23x₂₄ + 2.786 72x₂₅ + 1.906 54x₂₆ + 5.687 64x₃₇ - 1.443 30x₄₁ - 2.832 14x₄₂	< 2.2E-16	0.719 8
y₁₇	Alanine	y₁₇ = -423.856 98 + 26.857 13x₅ + 0.212 76x₈ - 51.525 47x₂₄ + 11.245 34x₂₅ - 5.608 01x₂₇ - 10.490 46x₃₄ + 10.288 42x₃₅	< 2.2E-16	0.855 6
y₁₈	Hydroxyproline	y₁₈ = -6.030 169 2 + 0.036 182 2x₇ - 0.000 568 1x₈ + 0.096 650x₁₆ - 0.019 082 9x₁₈ + 0.097 936 2x₁₉ - 0.039 236 1x₂₀ + 0.312 212x₂₄ + 0.032 922 7x₂₆ - 0.071 307 9x₂₇ + 0.040 639 2x₃₄ - 0.038 425 1x₃₅ + 0.053 350 2x₃₇ + 0.035 562 7x₄₂ - 0.093 847 6x₄₈	< 2.2E-16	0.861 2
y₁₉	Lysine	y₁₉ = 20.108 32 - 0.197 22x₇ + 5.885 1x₁₃ + 1.262 33x₁₉ - 3.793 31x₂₄ + 0.537 49x₂₅ + 0.573 24x₂₆ + 0.908 34x₃₅ - 1.167 98x₃₆ - 3.026 31x₃₇ - 0.168 3x₃₈ + 4.957 43x₃₉ - 0.630 26x₄₂ - 0.747 16x₄₃ + 0.909 26x₄₆ - 1.832 64x₄₈	< 2.2E-16	0.936 6
y₂₀	Glutamine	y₂₀ = -735.988 81 + 0.161 58x₄ + 2.600 1x₆ + 8.238 66x₇ - 3.494 74x₉ + 8.011x₁₄ - 23.680 29x₃₁ + 9.341 62x₄₂ + 18.614 86x₄₄	< 2.2E-16	0.822 5
y₂₁	Serine	y₂₁ = -135 0 + 0.179 7x₄ + 21.31x₅ + 1.773x₆ + 14.66x₇ - 0.257 2x₈ - 14.68x₉ - 5.298x₂₈ + 11.11x₃₀ - 26.18x₃₁ + 6.816x₄₂ + 18.64x₄₄	< 2.2E-16	0.915
y₂₂	Citrulline	y₂₂ = 250.578 16 + 0.078 67x₄ - 11.436 93x₅ + 1.639 03x₇ - 18.405 28x₁₃ + 2.465 04x₂₀ - 50.008 1x₂₄ + 4.063 76x₂₅ + 18.846 5x₃₉	< 2.2E-16	0.675 4
y₂₃	Arginine	y₂₃ = 172.876 + 11.109x₂₀ + 41.535x₃₇ - 136.286x₃₉ + 10.375x₄₃ - 12.332x₄₆	2.92E-15	0.594 2
y₂₄	Aspartic acid	y₂₄ = 303.294 2 + 0.958 6x₆ + 10.431 5x₁₄ - 43.932x₂₄ + 8.628x₂₅ + 5.3407x₂₇ - 9.505 3x₃₇ - 10.432 2x₄₁	< 2.2E-16	0.692 8
y₂₅	Asnparagin	y₂₅ = -114 7 + 0.139 6x₈ - 24.19x₁₂ + 27.27x₁₄ - 13.51x₁₉ + 5.198x₂₀ - 59.59x₂₃ + 36.62x₂₅ - 2.339x₃₈ - 23.72x₄₁ - 8.57x₄₂ + 5.091x₄₃	< 2.2E-16	0.900 1
y₂₆	GABA	y₂₆ = -38.648 896 + 0.008 729x₄ - 0.572 554x₅ - 0.035 023x₈ + 0.023 51x₁₁ - 1.344 205x₁₃ - 1.090 986x₂₃ + 0.511 728x₂₆ - 0.186 655x₂₈ + 0.934 137x₃₀ + 0.703 033x₃₂ + 1.301 243x₃₇ - 1.600 242x₄₁ - 0.170 576x₄₂ - 0.028 769x₄₃	< 2.2E-16	0.872 6
y₂₇	Methionine	y₂₇ = 16.494 370 3 - 0.001 626 4x₈ - 0.856 271 9x₁₂ - 1.090 167 4x₂₄ + 0.099 139x₂₆ + 0.173 756 8x₃₅ - 0.230 753 3x₃₆ + 1.426 185 6x₃₇ - 1.051 769 9x₄₀	< 2.2E-16	0.733 5
y₂₈	Phenylalanine	y₂₈ = 5.000 61 - 0.319 43x₅ - 1.634 13x₁₂ - 0.037 86x₂₀ + 0.238 42x₂₅ - 0.067 76x₃₆ + 1.070 14x₃₇ - 0.149 5x₄₂	7.78E-13	0.550 3
y₂₉	Proline	y₂₉ = 777.673 + 20.533x₉ + 131.606x₁₂ - 91.966x₁₂ + 22.328x₂₆ - 8.06x₂₇ + 30.316x₃₆ - 59.162x₄₁ + 23.529x₄₂	< 2.2E-16	0.718 5
y₃₀	Threonine	y₃₀ = 109.297 + 0.922 5x₆ + 2.323 5x₇ - 1.922 5x₉ - 15.749 6x₁₂ - 0.7854x₁₉ - 15.232 8x₂₃ + 3.168 2x₂₅ + 4.016 6x₃₀ - 5.296 6x₃₁ - 1.562 9x₃₃ + 13.231 9x₃₇	< 2.2E-16	0.724 8
y₃₁	Tryptophan	y₃₁ = 32.329 597 6 - 0.463 908 2x₅ - 0.001 012 6x₈ + 0.212 903 4x₂₅ - 0.216 249 8x₄₁ + 0.096 804 4x₄₃ - 0.134 250 6x₄₆ + 0.094 003 2x₄₈	4.91E-13	0.562 1
y₃₂	Tyrosine	y₃₂ = 13.299 08 - 0.988 41x₁₂ + 1.461 21x₂₅ + 0.343 09x₂₇ - 1.731 78x₄₁	< 2.2E-16	0.657 8
y₃₃	Valine	y₃₃ = 109.359 554 - 0.006 006x₈ - 0.209 613x₂₀ + 0.680 462x₂₅ + 0.456 238x₃₅ - 0.643 298x₃₇ - 1.491 717x₄₁ + 0.414 893x₄₂	< 2.2E-16	0.685 3
y₃₄	Leucine	y₃₄ = 101.636 07 - 0.132 167x₆ - 0.501 552x₇ + 0.010 507x₈ - 0.026 243x₁₁ + 0.506 04x₁₉ + 0.299 252x₂₀ - 6.126 133x₂₄ + 0.700 453x₂₆ + 0.288 294x₃₅ - 0.702 286x₄₂ - 0.215 384x₄₆	< 2.2E-16	0.811 6
y₃₅	Isoleucine	y₃₅ = 4.432 25 - 1.599 46x₁₂ - 0.056 32x₁₉ - 1.485 8x₂₃ + 0.347 16x₂₅ -0.163 21x₂₇ + 0.259 38x₃₅ - 0.267 02x₃₆ + 1.195 04x₃₇ - 0.116 87x₄₂	< 2.2E-16	0.818 7
y₃₆	Uracil	y₃₆ = -101.7 - 0.277 6x₆ + 0.017 41x₈ - 5.021x₁₂ - 0.882 4x₂₀ - 6.71x₂₃ + 9.05x₂₄ + 1.816x₂₅ - 0.996 5x₂₇ - 1.006x₃₄ + 1.484x₃₅ - 0.710 8x₃₆ + 3.518x₄₀ - 0.685 1x₄₂ + 0.554 4x₄₆ - 0.968 4x₄₈	< 2.2E-16	0.735 2
y₃₇	Guanosine	y₃₇ = -81.83 + 0.161 9x₇ + 0.003 023x₈ - 4.04x₁₂ + 0.832 9x₁₆ - 2.658x₂₃ + 5.169x₂₄ + 0.898 8x₂₅ - 0.508x₂₇ + 2.37x₃₇ - 0.483 8x₄₁ + 0.662 6x₄₃ - 0.774 1x₄₆	< 2.2E-16	0.878 3
y₃₈	2'-Desoxyuridine	y₃₈ = 0.053 18 - 0.001 203x₆ - 0.001 739x₇ + 0.000 076 53x₈ + 0.005 061x₁₆ + 0.005 785x₁₉ - 0.003 084x₂₇ + 0.000 350 3x₃₈ + 0.007 261x₄₁ - 0.003 963x₄₂ + 0.004 664x₄₃ - 0.007 38x₄₆	< 2.2E-16	0.751 1
y₃₉	2'- Deoxycytidine	y₃₉ = 0.069 995 4 + 0.000 824 6x₇ - 0.004 275 6x₂₀ + 0.006 985 4x₂₂ + 0.009 380 1x₂₅ + 0.005 608 4x₂₆ - 0.003 676 2x₃₄ + 0.004 022 9x₃₅ + 0.006 909 3x₃₆ - 0.003 602 6x₄₀ - 0.021 448 7x₄₁ + 0.000 936 2x₄₆	< 2.2E-16	0.767 7
y₄₀	2'-Deoxyguanosine	y₄₀ = -0.650 9 + 0.000 016 86x₁ + 0.021 95x₁₆ + 0.039 39x₁₉ - 0.043 48x₂₃ + 0.002 003x₂₅ + 0.040 04x₄₀ + 0.015 81x₄₃ - 0.027 01x₄₆ - 0.019 01x₄₈	< 2.2E-16	0.787 8
y₄₁	Adenine	y₄₁ = 28.072 181 + 0.003 168x₈ - 1.733 71x₁₂ - 0.253 376x₂₀ - 0.870 28x₂₃ + 0.536 413x₂₅ -0.248 485x₂₇ - 0.417 505x₃₄ + 0.751 187x₃₅ - 0.522 496x₃₆ + 3.312 867x₃₉ + 0.035 772x₄₃	< 2.2E-16	0.908 8
y₄₂	Cytidine	y₄₂ = 2.274 595 7 - 0.045 453 1x₆ - 0.053 297 9x₇ + 0.003 281 7x₈ - 0.089 267 2x₂₀ + 0.124 383 6x₂₅ + 0.150 313x₂₆ - 0.162 468 3x₂₇ - 0.102 764 7x₃₄ + 0.166 437 3x₃₅ - 0.140 708 4x₄₂ + 0.024 054 8x₄₆	< 2.2E-16	0.712
y₄₃	Cytosine	y₄₃ = 0.141 7 - 0.000 004 229x₈ - 0.001 149x₁₀ - 0.016 76x₁₂ + 0.003 532x₄₀	2.00E-13	0.519 8
y₄₄	Guanine	y₄₄ = 0.284 629 3 - 0.129 538 4x₇ + 0.004 199 8x₈ + 0.105 825 5x₁₉ - 0.466 135 4x₂₄ + 0.183 057 6x₂₅ + 0.081 846 1x₂₆ + 0.096 525 2x₄₀ + 0.136 679 7x₄₆ - 0.181 945 6x₄₈	< 2.2E-16	0.723 9
y₄₅	Inosine	y₄₅ = 4.704 38 - 0.296 88x₁₂ - 0.058 27x₂₀ + 0.040 74x₂₅ - 0.068 65x₃₄ + 0.160 25x₃₅ - 0.097 9x₃₆ + 0.049 84x₄₆ - 0.086 65x₄₈	< 2.2E-16	0.806 5
y₄₆	Uridine	y₄₆ = -119.957 21 + 0.025 89x₈ + 0.044 4x₁₁ + 4.936 59x₁₃ - 0.755 37x₂₀ - 1.784 76x₂₃ + 9.883 52x₂₄ + 2.160 31x₂₅ - 1.035 52x₂₇ - 1.694 44x₃₄ + 1.702 59x₃₅ - 0.439 67x₃₆ - 0.709 75x₄₂ + 0.220 06x₄₃ - 0.565 66x₄₈	< 2.2E-16	0.886 9
y₄₇	Xanthine	y₄₇ = 5.499 942 - 0.023 861x₆ - 0.004 526x₁₁ - 0.239 788x₁₂ - 0.073 482x₂₁ + 0.0518 2x₂₆ - 0.093 824x₂₇ - 0.027 254x₃₄ + 0.138 456x₃₅ - 0.074 182x₃₆ + 0.014 472x₄₆	< 2.2E-16	0.732

No.	Component	Regression equation	P values	Adjust R²
y₁	Zeaxanthin	y₁ = 0.206 254 8 - 0.00210 96x₆ - 0.005 089 3x₂₀ - 0.026 519 5x₃₉ + 0.004 533 2x₄₈	3.31E-11	0.443 9
y₂	β-Cryptoxanthin	y₂ = 0.001 576 - 0.000 072 49x₂₀ - 0.000 136 5x₂₃ - 0.000 010 64x₂₈ - 0.000 084 66x₄₃ + 0.000 102 0x₄₆	1.72E-10	0.435 5
y₃	β-Carotene	y3 = 0.035 737 - 0.007 060x₁₇ - 0.005 896x₁₈ - 0.006 281x₁₉ - 0.012 755x₂₁ + 0.007 614x₄₆	3.06E-12	0.477 1
y₄	Zeaxanthin dipalmitate	y₄ = -18.427 7 + 0.004 586x₄ - 0.118 425x₆ + 0.606 201x₁₇ + 0.740 070x₁₈ + 1.136 655x₁₉ + 0.929 495x₃₂ - 0.479 786x₄₄ - 0.581 787x₄₆ - 0.330 538x₄₇ - 0.551 557x₄₈	2.14E-12	0.538
y₅	Total carotenoids	y₅ = 24.321 9 - 0.165 0x₆ + 1.376 46x₁₇ + 1.107 55x₁₈ + 1.670 88x₁₉ + 1.391 11x₃₂ - 0.273 9x₃₃ - 0.529 97x₄₄ - 0.473 58x₄₅ - 1.262 67x₄₆	2.08E-14	0.592 7
y₆	Neutral polysaccharides	y₆ = 80.159 32 - 0.355 79x₆ - 0.707 18x₂₀ - 1.414 06x₂₃ - 1.219 59x₂₇ + 1.082 78x₃₅ - 0.894 85x₃₆ + 1.325 43x₄₁ - 0.283 31x₄₂ + 0.359 26x₄₈	6.78E-12	0.562 2
y₇	Acid polysaccharides	y₇ = 9.148 24 + 0.135 99x₁₈ + 0.101 36x₁₉ - 0.083 09x₄₃	1.37E-09	0.369 2
y₈	Total phenolic	y₈ = 6.845 64 + 0.412 99x₂₅ + 0.291 96x₂₆ + 0.365 91x₃₆ - 1.018 24x₄₁ - 0.042 45x₄₂	2.39E-10	0.463 3
y₉	Total flavonoids	y₉ = -5.465 896 - 0.112 732x₇ + 0.003 628x₈ - 1.827 112x₁₂ - 1.139 439x₂₃ - 0.344 761x₁₈ + 0.477 422x₁₉ + 0.231 034x₂₅ + 0.220 894x₂₆ + 1.245 965x₄₀ - 0.292 422x₄₁ - 0.199 244x₄₂ + 0.230 241x₄₃ - 0.718 579x₄₈	5.53E-06	0.679 8
y₁₀	Betaine	y₁₀ = 18.748 48 - 0.055 38x₆ - 0.965 68x₁₂ - 3.270 28x₂₃ - 2.288 40x₁₃ + 1.876 48x₃₇	6.23E-11	0.551 7
y₁₁	Protein	y₁₁ = -2.621 256 1 + 0.137 250 5x₇ - 0.002 735x₈ + 0.363 642x₃₀ + 0.289 77x₃₁ + 0.103 814 6x₃₃ - 0.603 991 1x₄₄ - 0.172 843 1x₄₅	2.41E-11	0.491 8
y₁₂	Fructose	y₁₂ = 331.3 - 0.003 527x₁ + 0.104 8x₂ + 0.026 91x₄ - 4.621x₇ + 2.637x₉ + 2.738x₃₁ - 2.956x₃₇ + 0.359x₃₈ + 9.471x₃₉ - 2.398x₄₁ - 2.405x₄₂ + 2.582x₄₇	< 2.2E-16	0.985 2
y₁₃	Glucose	y₁₃ = 451.622 46 - 0.010 031x₁ + 0.056 359x₂ + 0.050 514x₄ + 0.528 615x₆ - 0.974 702x₇ - 0.077 919x₈ + 1.242 797x₉ + 4.221 319x₁₄ - 4.653 498x₂₂ - 3.008 636x₂₅ + 3.558 910x₃₀ - 1.117 499x₃₂ - 2.156 630x₃₄ - 2.201 215x₃₇ - 0.111 315x₃₈ + 3.097 005x₄₇	< 2.2E-16	0.981 7
y₁₄	Sucrose	y₁₄ = 12.44 + 0.000 384 2x₂ - 0.002 907x₆ + 0.009 014x₇ + 0.066 31x₁₅ - 0.092 68x₂₂ + 0.010 16x₂₆ + 0.023 99x₃₃ - 0.022 72x₃₄ - 0.035 47x₃₇ + 0.010 29x₄₄ - 0.022 89x₄₅	< 2.2E-16	0.809 3
y₁₅	Maltose	y₁₅ = 3.036 29 + 0.202 90x₂₆ + 0.081 58x₃₆ - 0.258 88x₄₁	< 2.2E-16	0.613 6
y₁₆	Glutamic acid	y₁₆ = 451.987 96 - 9.318 31x₅ - 0.498 64x₇ - 17.700 01x₁₂ - 13.213 23x₂₄ + 2.786 72x₂₅ + 1.906 54x₂₆ + 5.687 64x₃₇ - 1.443 30x₄₁ - 2.832 14x₄₂	< 2.2E-16	0.719 8
y₁₇	Alanine	y₁₇ = -423.856 98 + 26.857 13x₅ + 0.212 76x₈ - 51.525 47x₂₄ + 11.245 34x₂₅ - 5.608 01x₂₇ - 10.490 46x₃₄ + 10.288 42x₃₅	< 2.2E-16	0.855 6
y₁₈	Hydroxyproline	y₁₈ = -6.030 169 2 + 0.036 182 2x₇ - 0.000 568 1x₈ + 0.096 650x₁₆ - 0.019 082 9x₁₈ + 0.097 936 2x₁₉ - 0.039 236 1x₂₀ + 0.312 212x₂₄ + 0.032 922 7x₂₆ - 0.071 307 9x₂₇ + 0.040 639 2x₃₄ - 0.038 425 1x₃₅ + 0.053 350 2x₃₇ + 0.035 562 7x₄₂ - 0.093 847 6x₄₈	< 2.2E-16	0.861 2
y₁₉	Lysine	y₁₉ = 20.108 32 - 0.197 22x₇ + 5.885 1x₁₃ + 1.262 33x₁₉ - 3.793 31x₂₄ + 0.537 49x₂₅ + 0.573 24x₂₆ + 0.908 34x₃₅ - 1.167 98x₃₆ - 3.026 31x₃₇ - 0.168 3x₃₈ + 4.957 43x₃₉ - 0.630 26x₄₂ - 0.747 16x₄₃ + 0.909 26x₄₆ - 1.832 64x₄₈	< 2.2E-16	0.936 6
y₂₀	Glutamine	y₂₀ = -735.988 81 + 0.161 58x₄ + 2.600 1x₆ + 8.238 66x₇ - 3.494 74x₉ + 8.011x₁₄ - 23.680 29x₃₁ + 9.341 62x₄₂ + 18.614 86x₄₄	< 2.2E-16	0.822 5
y₂₁	Serine	y₂₁ = -135 0 + 0.179 7x₄ + 21.31x₅ + 1.773x₆ + 14.66x₇ - 0.257 2x₈ - 14.68x₉ - 5.298x₂₈ + 11.11x₃₀ - 26.18x₃₁ + 6.816x₄₂ + 18.64x₄₄	< 2.2E-16	0.915
y₂₂	Citrulline	y₂₂ = 250.578 16 + 0.078 67x₄ - 11.436 93x₅ + 1.639 03x₇ - 18.405 28x₁₃ + 2.465 04x₂₀ - 50.008 1x₂₄ + 4.063 76x₂₅ + 18.846 5x₃₉	< 2.2E-16	0.675 4
y₂₃	Arginine	y₂₃ = 172.876 + 11.109x₂₀ + 41.535x₃₇ - 136.286x₃₉ + 10.375x₄₃ - 12.332x₄₆	2.92E-15	0.594 2
y₂₄	Aspartic acid	y₂₄ = 303.294 2 + 0.958 6x₆ + 10.431 5x₁₄ - 43.932x₂₄ + 8.628x₂₅ + 5.3407x₂₇ - 9.505 3x₃₇ - 10.432 2x₄₁	< 2.2E-16	0.692 8
y₂₅	Asnparagin	y₂₅ = -114 7 + 0.139 6x₈ - 24.19x₁₂ + 27.27x₁₄ - 13.51x₁₉ + 5.198x₂₀ - 59.59x₂₃ + 36.62x₂₅ - 2.339x₃₈ - 23.72x₄₁ - 8.57x₄₂ + 5.091x₄₃	< 2.2E-16	0.900 1
y₂₆	GABA	y₂₆ = -38.648 896 + 0.008 729x₄ - 0.572 554x₅ - 0.035 023x₈ + 0.023 51x₁₁ - 1.344 205x₁₃ - 1.090 986x₂₃ + 0.511 728x₂₆ - 0.186 655x₂₈ + 0.934 137x₃₀ + 0.703 033x₃₂ + 1.301 243x₃₇ - 1.600 242x₄₁ - 0.170 576x₄₂ - 0.028 769x₄₃	< 2.2E-16	0.872 6
y₂₇	Methionine	y₂₇ = 16.494 370 3 - 0.001 626 4x₈ - 0.856 271 9x₁₂ - 1.090 167 4x₂₄ + 0.099 139x₂₆ + 0.173 756 8x₃₅ - 0.230 753 3x₃₆ + 1.426 185 6x₃₇ - 1.051 769 9x₄₀	< 2.2E-16	0.733 5
y₂₈	Phenylalanine	y₂₈ = 5.000 61 - 0.319 43x₅ - 1.634 13x₁₂ - 0.037 86x₂₀ + 0.238 42x₂₅ - 0.067 76x₃₆ + 1.070 14x₃₇ - 0.149 5x₄₂	7.78E-13	0.550 3
y₂₉	Proline	y₂₉ = 777.673 + 20.533x₉ + 131.606x₁₂ - 91.966x₁₂ + 22.328x₂₆ - 8.06x₂₇ + 30.316x₃₆ - 59.162x₄₁ + 23.529x₄₂	< 2.2E-16	0.718 5
y₃₀	Threonine	y₃₀ = 109.297 + 0.922 5x₆ + 2.323 5x₇ - 1.922 5x₉ - 15.749 6x₁₂ - 0.7854x₁₉ - 15.232 8x₂₃ + 3.168 2x₂₅ + 4.016 6x₃₀ - 5.296 6x₃₁ - 1.562 9x₃₃ + 13.231 9x₃₇	< 2.2E-16	0.724 8
y₃₁	Tryptophan	y₃₁ = 32.329 597 6 - 0.463 908 2x₅ - 0.001 012 6x₈ + 0.212 903 4x₂₅ - 0.216 249 8x₄₁ + 0.096 804 4x₄₃ - 0.134 250 6x₄₆ + 0.094 003 2x₄₈	4.91E-13	0.562 1
y₃₂	Tyrosine	y₃₂ = 13.299 08 - 0.988 41x₁₂ + 1.461 21x₂₅ + 0.343 09x₂₇ - 1.731 78x₄₁	< 2.2E-16	0.657 8
y₃₃	Valine	y₃₃ = 109.359 554 - 0.006 006x₈ - 0.209 613x₂₀ + 0.680 462x₂₅ + 0.456 238x₃₅ - 0.643 298x₃₇ - 1.491 717x₄₁ + 0.414 893x₄₂	< 2.2E-16	0.685 3
y₃₄	Leucine	y₃₄ = 101.636 07 - 0.132 167x₆ - 0.501 552x₇ + 0.010 507x₈ - 0.026 243x₁₁ + 0.506 04x₁₉ + 0.299 252x₂₀ - 6.126 133x₂₄ + 0.700 453x₂₆ + 0.288 294x₃₅ - 0.702 286x₄₂ - 0.215 384x₄₆	< 2.2E-16	0.811 6
y₃₅	Isoleucine	y₃₅ = 4.432 25 - 1.599 46x₁₂ - 0.056 32x₁₉ - 1.485 8x₂₃ + 0.347 16x₂₅ -0.163 21x₂₇ + 0.259 38x₃₅ - 0.267 02x₃₆ + 1.195 04x₃₇ - 0.116 87x₄₂	< 2.2E-16	0.818 7
y₃₆	Uracil	y₃₆ = -101.7 - 0.277 6x₆ + 0.017 41x₈ - 5.021x₁₂ - 0.882 4x₂₀ - 6.71x₂₃ + 9.05x₂₄ + 1.816x₂₅ - 0.996 5x₂₇ - 1.006x₃₄ + 1.484x₃₅ - 0.710 8x₃₆ + 3.518x₄₀ - 0.685 1x₄₂ + 0.554 4x₄₆ - 0.968 4x₄₈	< 2.2E-16	0.735 2
y₃₇	Guanosine	y₃₇ = -81.83 + 0.161 9x₇ + 0.003 023x₈ - 4.04x₁₂ + 0.832 9x₁₆ - 2.658x₂₃ + 5.169x₂₄ + 0.898 8x₂₅ - 0.508x₂₇ + 2.37x₃₇ - 0.483 8x₄₁ + 0.662 6x₄₃ - 0.774 1x₄₆	< 2.2E-16	0.878 3
y₃₈	2'-Desoxyuridine	y₃₈ = 0.053 18 - 0.001 203x₆ - 0.001 739x₇ + 0.000 076 53x₈ + 0.005 061x₁₆ + 0.005 785x₁₉ - 0.003 084x₂₇ + 0.000 350 3x₃₈ + 0.007 261x₄₁ - 0.003 963x₄₂ + 0.004 664x₄₃ - 0.007 38x₄₆	< 2.2E-16	0.751 1
y₃₉	2'- Deoxycytidine	y₃₉ = 0.069 995 4 + 0.000 824 6x₇ - 0.004 275 6x₂₀ + 0.006 985 4x₂₂ + 0.009 380 1x₂₅ + 0.005 608 4x₂₆ - 0.003 676 2x₃₄ + 0.004 022 9x₃₅ + 0.006 909 3x₃₆ - 0.003 602 6x₄₀ - 0.021 448 7x₄₁ + 0.000 936 2x₄₆	< 2.2E-16	0.767 7
y₄₀	2'-Deoxyguanosine	y₄₀ = -0.650 9 + 0.000 016 86x₁ + 0.021 95x₁₆ + 0.039 39x₁₉ - 0.043 48x₂₃ + 0.002 003x₂₅ + 0.040 04x₄₀ + 0.015 81x₄₃ - 0.027 01x₄₆ - 0.019 01x₄₈	< 2.2E-16	0.787 8
y₄₁	Adenine	y₄₁ = 28.072 181 + 0.003 168x₈ - 1.733 71x₁₂ - 0.253 376x₂₀ - 0.870 28x₂₃ + 0.536 413x₂₅ -0.248 485x₂₇ - 0.417 505x₃₄ + 0.751 187x₃₅ - 0.522 496x₃₆ + 3.312 867x₃₉ + 0.035 772x₄₃	< 2.2E-16	0.908 8
y₄₂	Cytidine	y₄₂ = 2.274 595 7 - 0.045 453 1x₆ - 0.053 297 9x₇ + 0.003 281 7x₈ - 0.089 267 2x₂₀ + 0.124 383 6x₂₅ + 0.150 313x₂₆ - 0.162 468 3x₂₇ - 0.102 764 7x₃₄ + 0.166 437 3x₃₅ - 0.140 708 4x₄₂ + 0.024 054 8x₄₆	< 2.2E-16	0.712
y₄₃	Cytosine	y₄₃ = 0.141 7 - 0.000 004 229x₈ - 0.001 149x₁₀ - 0.016 76x₁₂ + 0.003 532x₄₀	2.00E-13	0.519 8
y₄₄	Guanine	y₄₄ = 0.284 629 3 - 0.129 538 4x₇ + 0.004 199 8x₈ + 0.105 825 5x₁₉ - 0.466 135 4x₂₄ + 0.183 057 6x₂₅ + 0.081 846 1x₂₆ + 0.096 525 2x₄₀ + 0.136 679 7x₄₆ - 0.181 945 6x₄₈	< 2.2E-16	0.723 9
y₄₅	Inosine	y₄₅ = 4.704 38 - 0.296 88x₁₂ - 0.058 27x₂₀ + 0.040 74x₂₅ - 0.068 65x₃₄ + 0.160 25x₃₅ - 0.097 9x₃₆ + 0.049 84x₄₆ - 0.086 65x₄₈	< 2.2E-16	0.806 5
y₄₆	Uridine	y₄₆ = -119.957 21 + 0.025 89x₈ + 0.044 4x₁₁ + 4.936 59x₁₃ - 0.755 37x₂₀ - 1.784 76x₂₃ + 9.883 52x₂₄ + 2.160 31x₂₅ - 1.035 52x₂₇ - 1.694 44x₃₄ + 1.702 59x₃₅ - 0.439 67x₃₆ - 0.709 75x₄₂ + 0.220 06x₄₃ - 0.565 66x₄₈	< 2.2E-16	0.886 9
y₄₇	Xanthine	y₄₇ = 5.499 942 - 0.023 861x₆ - 0.004 526x₁₁ - 0.239 788x₁₂ - 0.073 482x₂₁ + 0.0518 2x₂₆ - 0.093 824x₂₇ - 0.027 254x₃₄ + 0.138 456x₃₅ - 0.074 182x₃₆ + 0.014 472x₄₆	< 2.2E-16	0.732

生态因子与化学成分相关联的药用和食用枸杞子适宜生产区划研究

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卢有媛 ¹^,² , 郭盛 ¹^,^* , 严辉 ¹ , 张芳 ¹ , 王汉卿 ² , 晋玲 ³ , 段金廒 ¹^,^*

药学学报 | 研究论文 2020,55(10): 2466-2477

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药学学报 | 研究论文 2020, 55(10): 2466-2477

生态因子与化学成分相关联的药用和食用枸杞子适宜生产区划研究

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卢有媛¹^,², 郭盛¹^,^*, 严辉¹, 张芳¹, 王汉卿², 晋玲³, 段金廒¹^,^*

作者信息

1.南京中医药大学江苏省中药资源产业化过程协同创新中心/中药资源产业化与方剂创新药物国家地方联合工程研究中心/国家中医药管理局中药资源循环利用重点研究室, 江苏南京 210023

2.宁夏医科大学药学院, 宁夏银川 750021

3.甘肃中医药大学药学院, 甘肃兰州 730000

通讯作者:

*郭盛, E-mail:guosheng@njucm.edu.cn;

段金廒, E-mail:dja@njucm.edu.cn

Regionalization of production of medicinal and edible fruit of Lycium barbarum associated with ecological factors and chemical constituents

You-yuan LU¹^,², Sheng GUO¹^,^*, Hui YAN¹, Fang ZHANG¹, Han-qing WANG², Ling JIN³, Jin-ao DUAN¹^,^*

Affiliations

1. Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, State Administration of Traditional Chinese Medicine Key Laboratory of Chinese Medicinal Resources Recycling Utilization, National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, Nanjing 210023, China

2. School of Pharmacy, Ningxia Medical University, Yinchuan 750021, China

3. School of Pharmacy, Gansu University of Chinese Medicine, Lanzhou 730000, China

出版时间: 2020-10-12 doi: 10.16438/j.0513-4870.2020-0572

文章导航

摘要

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枸杞子为药食同源之品，区分其药用和食用生产适宜区域，有利于其栽培生产的科学布局。本研究采用Maxent模型研究宁夏枸杞生态适宜区，并基于化学成分综合作用，采用GIS技术，结合文献统计分析及化学计量学等手段，研究药用枸杞子和食用枸杞子适宜生产区。研究结果显示，宁夏枸杞生态适宜区主要分布在我国西北部；药用枸杞子生产适宜区主要集中在宁夏，甘肃白银、酒泉和张掖地区及内蒙古西部部分地区，均为枸杞子药材的传统产区，与枸杞子药用古以甘州产质佳，今以宁夏中宁产为道地相一致；食用枸杞子生产适宜区主要分布在青海西北部、甘肃酒泉和张掖地区及新疆阿克苏和克孜勒苏柯尔克孜州地区，该产区枸杞子果型指数较大，果实中果糖和葡萄糖含量高，满足食用产品的商品属性。研究结果为基于利用途径的差异化实现宁夏枸杞分区域布局发展奠定了基础。

关键词

药用枸杞子 / 食用枸杞子 / 适宜生产区划 / 综合评价

Abstract

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The fruit of Lycium barbarum L. (FLB) is a food and medicinal herb. Identifying suitable production regions for this plant would be beneficial to its cultivation and production. In this study, the Maxent model was used to identify ecologically suitable regions for the growth of L. barbarum L. In addition, based on its chemical composition, the suitable regions for production were identified by literature analysis and chemometrics. The results show that suitable regions for L. barbarum L. culture are mainly distributed in the northwest of China; suitable regions for the production of medicinal FLB were mainly concentrated in the district of Ningxia, Baiyin, Jiuquan and Zhangye of Gansu, and parts district in west of Inner Mongolia. All are the traditional production regions for FLB, which is consistent with the good quality of FLB produced in Ganzhou in ancient times, and the genuine medicinal materials of FLB produced in Zhongning of Ningxia today. The suitable regions for edible FLB were mainly distributed in northwest of Qinghai, Jiuquan and Zhangye of Gansu, as well as Aksu and Kizi sukirgiz of Xinjiang. The fruit type index of FLB in these regions is large, and the content of fructose and glucose in the fruit is high, which satisfies the edible commodity property. The study results lay a foundation for realizing the regional distribution and development of L. barbarum based on its different uses.

Key words

medicinal fruit of Lycium barbarum / edible fruit of Lycium barbarum / production suitability regionalization / comprehensive evaluation

引用本文

卢有媛, 郭盛, 严辉, 张芳, 王汉卿, 晋玲, 段金廒. 生态因子与化学成分相关联的药用和食用枸杞子适宜生产区划研究. 药学学报, 2020 , 55 (10) : 2466 -2477 . DOI: 10.16438/j.0513-4870.2020-0572

You-yuan LU, Sheng GUO, Hui YAN, Fang ZHANG, Han-qing WANG, Ling JIN, Jin-ao DUAN. Regionalization of production of medicinal and edible fruit of Lycium barbarum associated with ecological factors and chemical constituents[J]. Acta Pharmaceutica Sinica, 2020 , 55 (10) : 2466 -2477 . DOI: 10.16438/j.0513-4870.2020-0572

正文

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枸杞子为茄科植物宁夏枸杞Lycium barbarum L.的干燥成熟果实, 作为药用始载于《神农本草经》, 具有滋补肝肾、益精明目功效。宁夏枸杞原产于我国北部, 内蒙古、甘肃、宁夏和新疆等地有野生^[1]。随着市场对枸杞子需求量的增加, 宁夏枸杞栽培区域逐渐扩大, 由本草记载之传统栽培区甘州、灵州、九原等地扩展为宁夏全省、甘肃中部和西北部、内蒙古西部、青海西部和新疆西北部六大主产区, 在满足市场需求的同时成为西部经济欠发达地区脱贫扶困的支柱产业^[2]。但是, 截止目前唯有宁夏中宁所产枸杞子获得道地药材认可。“诸药所生, 皆有其境”强调了生态环境对药材生长的影响, 盲目引种、扩种在影响中药材生产合理布局的同时也会削弱其道地性^[3]。宁夏枸杞种植区生态条件差异较大, 且不同生态条件下枸杞子果实形态差异较大, 青海产枸杞子呈现为长果型; 甘肃白银、宁夏和内蒙古产枸杞子呈纺锤形; 新疆和甘肃酒泉产枸杞子呈类球形^{[4, 5]}。此外, 课题组前期研究结果显示, 不同产地枸杞子中化学成分组成及含量存在差异。枸杞子为药食同源之品, 化学成分的综合作用最终表现为品质差异及药用和食用功能取向差异。基于所含化学成分的差异, 宁夏枸杞不同生态适宜区生产的枸杞子可能具有不同的用途, 如药用、食用, 或二者兼用, 但未见相关研究报道。因此选择适宜的栽培生产区域, 并基于其化学成分的组成及含量差异, 研究其药用和食用生产适宜区, 在满足经济发展的同时可以实现其资源价值的最大化。

中药生态区划通过研究药用动植物生态特征及其与自然条件的关系, 揭示其生境自然条件空间规律, 并基于自然条件空间分布规律实现生态适宜性区域划分, 为中药资源合理开发利用提供依据^{[6, 7]}。生态位模型是实现中药生态区划的常用手段, 其基于物种自身特定的小生境, 采用数据建模方法归纳出生境特点并将其映射到目标区域, 最终获得该物种的生态分布区^[8]。ENFA、CLIMEX、BIOCLIM、DOMAIN、GARP和MaxEnt为常用的生态位模型。其次, 中国中医科学院中药研究所自主研发的全球药用植物适宜产区分析系统(geographic information system for global medicinal plants, GMPGIS)也被用于药用植物生态适宜区预测^[9]。其中, MaxEnt通过已知分布信息寻找最大熵估计物种分布, 对未知分布信息不做假设、不持偏见, 预测结果准确度较高, 模拟精度好, 被广泛用于动植物潜在适宜区预测^[10-12]。基于化学成分含量与环境因子的关系模型, 结合化学计量学和GIS软件, 可以综合评价中药材中化学成分分布特征, 研究其品质或生产区划^[13-15]。

本研究以宁夏枸杞L. barbarum L.的干燥成熟果实为研究对象, 基于我国枸杞子主产区94批次样本实际分布信息和55个环境因子数据, 通过Maxent模型预测其在我国的生态适宜区, 探寻影响其生长的生态因子; 并通过多糖、单/寡糖、氨基酸、核苷和碱基、类胡萝卜素等47个化学成分含量与相关环境因子的数学模型、文献统计分析及化学计量学等手段, 结合GIS技术, 在展示不同产地枸杞子中化学成分特征的基础上体现药用和食用功能差异, 进而区分药用枸杞子和食用枸杞子适宜生产区, 为实现其资源价值最大化和合理利用提供参考依据。

材料与方法

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样品收集 课题组于2017年7~8月从宁夏、甘肃、青海、内蒙古、新疆5个产区采集枸杞子样品94份, 并记录经纬度及生境信息。样本经南京中医药大学段金廒教授鉴定为宁夏枸杞Lycium barbarum L.的干燥成熟果实, 样品采集地分布信息见表 1。

生态因子数据获取 生态因子数据来源于“中药资源空间信息网络数据库”, 包含43个气候类型数据(12个月的降水量和平均气温、19个综合气候因子)、8个土壤类型数据(土壤pH、阳离子交换能力、含沙量、含黏土量、土壤亚类、有效水含量等级、土壤质地分类、有机碳含量)、3个地形数据(海拔、坡度、坡向)和植被类型。气候类型数据根据1950~2000年间的气象观测数据插值而成, 土壤类型数据根据第二次全国土地调查提供的《1:100万中华人民共和国土壤图》制成, 植被类型以中国科学院植物研究所的《中华人民共和国植被图(1:100万)》中的植被亚类数据制成。

宁夏枸杞生态适宜区预测 基于94个采样点信息及55个生态因子数据, 利用最大熵模型(Maxent)预测枸杞子生长分布区, 采用ROC曲线评价模型预测结果, 基于响应曲线评价生态因子适宜值范围, 以采样点生态适宜度最小值划分枸杞子生态适宜区和不适宜区。参照文献^[16]方法研究枸杞子生态适宜分布区。

化学成分含量测定 基于课题组前期研究^[17]报道及研究结果测定中性多糖、酸性多糖、类胡萝卜素类、总黄酮、总酚、氨基酸类、核苷酸和碱基类、单/寡糖类、蛋白质等含量。

化学成分与环境因子关系模型 基于采样点生态因子值和化学成分含量数据, 应用R语言对化学成分含量和生态因子进行相关性分析, 选取相关系数P < 0.001的生态因子进行逐步回归分析, 构建化学成分与环境因子的关系模型。

化学成分含量空间分布 基于化学成分与环境因子的关系模型, 结合GIS空间运算及制图功能, 剔除生态适宜分布预测中不适宜分布区, 获得枸杞子中单个化学成分的含量空间分布图。

药用成分界定及权重系数 查阅关于枸杞子药理活性报道的文献, 其研究对象涉及到化学成分、提取部位和全果三大类。研究对象为化学成分即认为该成分为枸杞子中的活性成分; 研究对象为提取部位的依据提取溶剂分为水提液和醇提液两大类, 水提液具有活性则认为枸杞子中可溶于水的成分均为其活性成分, 具体包括糖类、氨基酸类、蛋白质类、核苷和碱基类、甜菜碱; 醇提液具有活性则认为总黄酮、总酚、类胡萝卜素类和甜菜碱为其活性成分; 研究对象为全果的则认为所有化学成分均为其活性成分。

基于中外文数据库, 共计查阅355篇(中文89篇, 英文266篇)关于枸杞子药理活性报道的文献。参照药用成分界定原则, 首先统计各成分在药理研究报道中出现的频率(f_i, i代表各化学成分, 如中性多糖、酸性多糖、总酚、总黄酮等); 其次, 依据其发表杂志的影响因子(X_i1、X_i2……X_in, 中文文献以“中国知网”公布的影响因子为依据), 统计各化学成分药理研究报道影响因子总值:

(1)$\mathop \sum \limits_{k = 1}^n {X_i} = {X_{i1}} + {X_{i2}} + {X_{i3}} + \cdots + {X_{in}}$

计算各化学成分在枸杞子总药理研究报道中的影响因子比率:

(2)${R_i} = {X_i}/\mathop \sum \limits_{k = 1}^n {X_i}$

各化学成分药理活性的权重系数:

(3)${{\rm{W}}_i} = {f_i} \times {R_i}$

食用成分界定及权重系数 枸杞子通常以全果形式食用, 故认为枸杞子中的所有成分均为其食用成分。各化学成分对枸杞子的食用价值并不相同, 因此基于测定化学成分在枸杞子中的含量, 采用PLS-DA进行变量重要性投影(VIP)分析各化学成分对样本的影响度和解释能力, 将各成分的VIP值作为其食用成分权重系数。

药用和食用枸杞子生产适宜区划 分别基于药用和食用成分权重系数和化学成分含量空间分布, 结合GIS空间运算及制图, 并参照运算后的适宜度值分别划分药用和食用枸杞子生产适宜区。

结果与讨论

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1 宁夏枸杞生态适宜区预测

1.1 Maxent模型预测评价

Maxent模型具有以ROC曲线下面积检验预测结果的功能, 即AUC值评价预测结果的精度。AUC介于0~1之间, < 0.6代表模型预测失败, 值越大则模型精度越高^[18]。基于94批次宁夏枸杞分布信息及相应的生态因子, 采用Maxent模型预测其分布区适宜度值, 结果显示:模型预测结果准确度和可信度较高(测试集AUC为0.994 9, 训练集AUC值为0.992 6), 可以用于宁夏枸杞生态适宜分布区研究。

1.2 影响宁夏枸杞生长的主要生态因子适宜范围

模型第一次运算时输入55个生态因子数据(43种气候数据、8种土壤数据、3个地形数据和植被类型数据), 每次弃去贡献率为0的生态因子, 经8次运算后余19个具有贡献率的生态因子, 其中海拔、温度季节性变化标准差、土壤类型和植被类型的累计贡献率达69.5%, 为影响宁夏枸杞生态适宜区分布的主要生态因子。依据各生态因子响应曲线可知(图 1), 海拔在0~6 000 m的范围均有响应, 但以1 000~3 000 m响应值较高, 因此认为海拔1 000~3 000 m时更适宜宁夏枸杞分布; 温度季节性变化标准差的适宜值范围为8~14;土壤类型以简育钙积土和耕作人为土响应值较高, 普通栗钙土和盐积冲击土次之, 耕作人为土是由于长期栽培人工改造而成, 简育钙积土多出现在降水不足、干旱和风沙侵蚀比较严重的区域, 均与宁夏枸杞生长土地相一致。植被类型中以一年一熟粮食作物及耐寒经济作物、落叶果园响应值最高, 与宁夏枸杞现主要以栽培为主相一致; 温带丛生禾草、典型草原, 高寒禾草、苔草草原和温带盐生矮半灌木荒漠次之, 其与宁夏枸杞现在生产区域植被类型基本吻合。

1.3 宁夏枸杞生态适宜区分布

基于Maxent预测结果, 采用GIS技术获得宁夏枸杞在我国的生态适宜分布区, 结果显示, 宁夏枸杞生态适宜区主要分布在我国西北部, 以宁夏、甘肃和新疆分布区域较广。生态适宜区包括宁夏河套平原, 甘肃祁连山北麓的酒泉和张掖地区及河套平原的靖远地区, 新疆塔里木盆地北部博尔塔拉、伊犁、阿克苏、克孜勒苏柯尔克孜地区, 青海西蒙古自治州和内蒙古巴彦淖尔市阴山山脉以南的河套平原区。其次, 陕西西北部也有生态适宜区分布, 西藏、山西有零星分布。研究结果与宁夏枸杞实际产区、《中国植物志》记载及王汉卿等^[14]研究结果基本一致。李静等^[15]研究结果显示, 辽宁及吉林地区有低适宜度宁夏枸杞分布区, 而本研究结果中该地区不适宜宁夏枸杞种植, 其可能原因为本研究以采样点最低适宜值(0.084 5)为下限, 认为低于该适宜值的区域为不适宜区。由于样点分布主要集中在主产区, 其适宜度会相对较高, 且辽宁及吉林地区没有样点分布, 因此可能会忽略适宜度值低于0.084 5但宁夏枸杞可以生长的区域。余意等^[19]研究结果显示, 宁夏枸杞在甘肃的生态适宜性较低, 与本研究结果相反, 也与其生长实际情况不一致, 可能与研究手段及选择的生态因子有关。

2 化学成分与环境因子的关联分析及其含量空间分布

基于前期研究结果, 测定的47个化学成分含量结果见图 2。利用R语言分析47个化学成分与51个环境因子的相关关系, 相关系数热图显示(图 3), 多数化学成分与最湿月降水、最湿季降水、最暖季降水、最冷季最低温、最冷季平均温、最干季平均温、1~2月均温、8~10月降水量、等温性、季节降水量和气温相关系数较高, 提示多数化学成分的积累同时受降水和气温因素影响。此外, 最冷季降水、最干月降水、最干季降水、1~4月降水、相对湿度和海拔与葡萄糖、果糖和蔗糖含量相关系数较高, 提示单/寡糖类成分积累与降水量密切相关。取相关系数P < 0.001的生态因子与药用成分含量进行逐步回归分析, 构建各化学成分与环境因子的关系模型, 见表 2。各回归方程校正决定系数(校正R²)均大于0.3, F检验P < 0.01, 回归系数t检验P < 0.05, 表明47个化学成分与环境因子的回归方程均达显著水平, 可以用于各成分的含量预测。

依据表 2中化学成分与环境因子的关系模型, 通过GIS空间运算后制图, 获得各成分含量空间分布图。对比各产区枸杞子化学成分特征与其含量空间分布图, 结果显示, 各成分含量空间分布与其实际情况吻合, 可以用于药用和食用适宜生产区划研究。

3 药用枸杞子适宜生产区划

由于缺乏具体的临床数据, 且目前药用成分的界定并没有较为客观、明确的研究方法, 而文献报道在一定程度上可以为相关研究的开展提供参考依据。因此, 本研究暂且只能以文献报道为依据, 认为具有药理活性报道的成分或部位可以作为其药用成分或部位, 依据此原则确定各成分的药用比例, 并综合考虑各成分的药用比例和杂志影响力两个因素确定药用成分权重。研究中对于药用成分及其权重的界定存在一定的局限性, 但是为了课题的开展, 暂且只能采取该研究方法, 并期待更为客观的评价方法。

参照文献报道, 综合考虑各成分药理活性报道频率和发表杂志影响因子比率, 最终确定各类化学成分在枸杞子药理作用中的权重系数(图 4)。由图可知, 药用成分中中性多糖和酸性多糖所占权重比较高, 分别占26.4%和24.5%, 与枸杞子药理研究侧重于多糖类成分相一致^{[20, 21]}。因此, 多糖类含量为影响药用适宜区划主要指标。环境因子与化学成分相关性分析结果表明(图 3), 降水量和气温与多糖类相关系数较高, 为影响药用枸杞子适宜生产区的主要生态因子。生长季(7~10月)降水量增加和休眠期(11月~次年3月)温度升高均可以促进多糖类成分积累。

基于各成分空间分布及其药用权重, 通过GIS进行空间运算, 利用采样点药用适宜度值的正态分布曲线, 划分我国药用枸杞子适宜生态区划。结果显示, 药用枸杞适宜区主要集中在宁夏河套平原、甘肃河套平原的白银地区及祁连山北部的张掖和酒泉地区; 其次, 内蒙古鄂尔多斯高原与贺兰山相接处的部分地区适宜度较高; 次适宜区主要集中在青海海西蒙古族藏族自治州、甘肃河西走廊中部的武威地区和内蒙古巴彦淖尔市阴山山脉以南的河套平原区。此外, 新疆克孜勒苏柯尔克孜州地区产的枸杞子药用适宜度较高, 阿克苏地区产的枸杞子药用适宜度与青海产枸杞子一致。

唐《千金翼方》^[22]云: “甘州者为真, 叶厚大者是。大体出河西诸郡, 其次江池间圩埂上者。”提出了枸杞子以甘州者为真的说法, 并指出了枸杞子的产地为甘州及河西诸郡。甘州即今甘肃省张掖市, 河西则泛指黄河以西之地, 汉、唐时多指今甘肃、青海两省黄河以西的地区, 即今河西走廊和湟水流域^[23]。宋代《梦溪笔谈》^[24]中记载: “枸杞, 陕西极边生者, ……根皮如厚朴, 甘美异于他处。”依据宋朝疆域图及其边疆层级体系^[25]认为, 陕西极边指今河西走廊区域及宁夏兴庆以南区域。明代《本草品汇精要》^[26]云: “[道地]陕西甘州茂州”。甘州指今甘肃省张掖市, 曾隶属陕西; 茂州指今四川北川、汶川及茂县等地。《本草纲目》^[27]记载: “今陕之兰州、灵州、九原以西枸杞, 并是大树, 河西及甘州者, 异于他处者。”灵州即今宁夏吴忠市境内, 九原指包头市九原区。至民国, 《增订伪药条辨》^[28]记载: “以陕西甘州所产者为胜, ……宁夏产者, 颗大色红有蒂, 略次。……甘肃镇番(今甘肃民勤)长城边出者, 粒细红圆活, 味亦甘, 此货过霉天即发黑, 甚难久藏, 略次。”综上可知, 枸杞子传统产区为甘州(甘肃张掖一带)、灵州(宁夏吴忠一带)、九原以西(内蒙古乌拉特前旗一带), 并以甘肃张掖、宁夏等地产者为佳。药用适宜区划研究结果显示, 药用枸杞子适宜区主要分布在宁夏、甘肃白银、酒泉和张掖等地区, 均为枸杞子的传统产区, 与枸杞子药用古以甘州产质佳, 今以宁夏中宁产为道地相一致。

4 食用枸杞子适宜生产区划

目前, 对于食用成分没有明确的界定, 且枸杞子多以全果食用, 而全果中包含了所有的化学成分。因此, 本研究暂且只能认为其所有成分均可作为食用成分。枸杞子中化学成分变量重要性投影分析结果显示(图 5), 果糖和葡萄糖所占权重系数较高, 分别占9.4%和8.7%;其次为中性多糖、总类胡萝卜素、甜菜碱、脯氨酸、酸性多糖和玉米黄素双棕榈酸酯, 核苷和碱基类及β-隐黄素等成分权重系数较低。单/寡糖类主要为营养成分, 部分类胡萝卜素类成分为维生素E合成的前体物质, 结合各类成分在食品中的含量及作为食品添加剂的概率, 认为采用化学成分变量重要性投影确定枸杞子食用成分权重系数具有一定的科学性, 研究结果可以进一步用于食用枸杞子适宜区划研究。海拔、辐射强度、日照时数及气温和降水与影响其适宜区划的主要化学成分果糖和葡萄糖的相关系数均较高(图 3), 为影响食用枸杞子的主要生态因子。高海拔、强辐射、长日照及昼夜温差大均利于果糖和葡萄糖的积累, 生长季(4~10月)高温、休眠期(11月~次年3月)多降雨和空气湿度大均不利于果糖和葡萄糖的积累。此外, 总类胡萝卜素类和玉米黄素双棕榈酸酯主要受降水和气温的影响, 生长季(4~10月)降水量增加、温度降低可以促进二者的积累。

基于各成分空间分布及食用权重系数, 通过GIS进行空间运算, 利用采样点药用适宜度值的正态分布曲线, 划分我国食用枸杞子适宜区划。结果显示, 食用枸杞子适宜区主要分布在青海海西蒙古族藏族自治州、甘肃祁连山北部的酒泉和张掖地区及新疆阿克苏及克孜勒苏柯尔克孜州地区; 宁夏河套平原、甘肃河西走廊中部的武威地区及河套平原的白银地区、内蒙古巴彦淖尔市阴山山脉以南的河套平原产区次之。因新疆阿克苏及克孜勒苏柯尔克孜州枸杞产量少, 未做相关调查及样本研究, 但就青海和甘肃酒泉及张掖地区样本研究结果显示, 该产区枸杞子果型指数较大, 果实中果糖和葡萄糖含量高, 满足食用产品的商品属性, 与其他产区相比, 该产区枸杞子更适宜于食用。

结论

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中药材生产受自身特性、生态环境和社会因素的综合影响, 呈现明显的地域性。中药材的区域分布及其自然环境条件是开展中药材种植的重要依据^[29]。中药材种植在关注产量的同时, 更应注重其品质^[30]。研究过程中综合考虑宁夏枸杞种植区的生态环境, 预测其生态适宜分布区, 结果显示:海拔、温度季节性变化标准差、土壤和植被类型为影响宁夏枸杞分布的主要生态因子; 其生态适宜区主要分布在我国西北地区。在此基础上, 基于生态适宜区范围, 综合考虑不同产地94批次枸杞子中47种化学成分分布特征, 研究药用和食用枸杞子生产适宜区。研究结果显示, 多糖为影响枸杞子药用品质的主要活性成分, 其含量与降水量和气温相关系数较高; 药用枸杞子适宜生产区主要分布在宁夏及甘肃白银、酒泉和张掖地区, 均为枸杞子的传统产区。果糖和葡萄糖为影响枸杞子食用品质的主要化学成分, 其含量与海拔、辐射强度、日照时数及气温和降水的相关系数均较高; 食用枸杞子适宜生产区主要分布在青海及甘肃酒泉和张掖地区, 以及新疆阿克苏及克孜勒苏柯尔克孜州地区, 该产区枸杞子果型指数较大, 果实中果糖和葡萄糖含量高, 满足食用的商品属性。研究结果在揭示枸杞子生产区生态特征的同时厘清了不同产区枸杞子质量特征。依据其药食两用特性, 基于各产区化学成分特征, 区分其药用和食用功能取向, 并进行合理生产布局, 服务于枸杞子资源价值的最大化和产业高质量发展。

作者贡献:段金廒和郭盛负责文章的选题和思路的提出; 郭盛和卢有媛负责整个实验的设计、实施、文章撰写和修改; 严辉、张芳、王汉卿和晋玲参与样本采集、数据分析和文章撰写。

利益冲突:本文无利益冲突。

基金

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国家自然科学基金项目(81773837)
国家自然科学基金项目(81873189)
宁夏科技重点研发计划(东西部合作项目2017BY079)

参考文献

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文献

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参考文献引证文献

排序方式：

[1]

China

Flora Editorial Commission

. Flora of China (中国植物志)[M]. Beijing: Science Press, 1978, 67: 13.

[2]

, Liu

, Xu

et al . Investigation of production status in major wolfberry producing areas of China and some suggestion[J]. China J Chin Mater Med (中国中药杂志), 2014, 39: 1979-1984. http://www.ncbi.nlm.nih.gov/pubmed/12680213

[3]

Chen

, Suo

, Han

et al . Analysis on ecological suitability and regionalization of traditional Chinese medicinal materials[J]. Chin Tradit Herb Drug (中草药), 2007, 38: 7-13. http://www.zhangqiaokeyan.com/academic-journal-cn_chinese-traditional-herbal-drugs_thesis/0201219476344.html

[4]

Zhang

, Zheng

, Teng

et al . Comparison research on fruit quality of Lycium barbarum L. in different regions[J]. Northwest Pharm J (西北药学杂志), 2012, 27: 11-13. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=xbyxzz201203003

[5]

Zhang

, Hou

, Li

et al . Identification of micro-characters of wolfberry from different regions[J]. J Chin Med Mater (中药材), 2016, 39: 1010-1013.

[6]

Zhang

, Guo

, Huang

et al . Progress of Chinese material medical regionalization[J]. Chin J Agric Res Region Plan (中国农业资源与区划), 2010, 31: 64-69. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zgnyzyyqh201003012

[7]

, Guo

, Yan

et al . Ecology suitability study of Trollius chinesis[J]. China J Chin Mater Med (中国中药杂志), 2018, 43: 3658-3661. http://www.ncbi.nlm.nih.gov/pubmed/30384529

[8]

Peterson

. Uses and requirements of ecological niche models and related distributional models[J]. Biodivers Inform, 2006, 3: 59-72. http://www.oalib.com/paper/2098343

[9]

, Wu

, Dong

et al . Analysis of global ecology of Acanthopanx senticosus in suitability and quality[J]. Acta Pharm Sin (药学学报), 2018, 53: 313-320. http://www.yxxb.com.cn:8081/apsCN/abstract/abstract17111.shtml

[10]

Phillips

, Anderson

, Schapire

. Maximum entropy modeling of species geographic distributions[J]. Ecol Model, 2006, 190: 231-259.

https://doi.org/10.1016/j.ecolmodel.2005.03.026

[11]

Qiao

, Hu

, Huang

. Theoretical basis, future directions, and challenges for ecological nich models[J]. Sci China:Life Sci (中国科学:生命科学), 2013, 43: 915-927. http://www.tandfonline.com/servlet/linkout?suffix=CIT0083&dbid=16&doi=10.1080%2F0144929X.2018.1456563&key=10.1108%2F02651331311298573

[12]

Zhang

, Zeng

, Zhang

et al . Ecology suitability regions and ecological characteristic of Panax notoginseng (Burk.) F.H.Chen based on maximum entropy model[J]. Acta Pharm Sin (药学学报), 2016, 51: 1629-1637. http://www.yxxb.com.cn:8081/apsCN/abstract/abstract16352.shtml

[13]

, Zhang

, Yang

et al . Quality regionalization study on Gentianae Macrophyllae Radix[J]. China J Chin Mater Med (中国中药杂志), 2016, 41: 3132-3138. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zgzyzz201617004

[14]

Wang

, Wang

, Ma

et al . Production regionalization study of Lycii Fructus[J]. China J Chin Mater Med (中国中药杂志), 2016, 41: 3127-3131. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zgzyzz201617003

[15]

, Yu

, Guo

et al . Study on quality regionalization of Lycii Fructus[J]. China J Chin Mater Med (中国中药杂志), 2019, 44: 1156-1163. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zgzyzz201906014

[16]

, Yang

, Ma

et al . Ecology suitability study of Chinese material medica Gentianae Macrophyllae Radix[J]. China J Chin Mater Med (中国中药杂志), 2016, 41: 3176-3180. http://europepmc.org/abstract/MED/28920367

[17]

, Guo

, Zhang

et al . Comparison of functional components and antioxidant activity of Lycium barbarum L. fruits from different regions in China[J]. Molecules, 2019, 24: 2228.

https://doi.org/10.3390/molecules24122228

[18]

Wang

, Xie

, Wan

et al . Application of ROC curve analysis in evaluating the performance of alien species' potential distribution models[J]. Biodivers Sci (生物多样性), 2007, 15: 41-48. http://d.wanfangdata.com.cn/Periodical_swdyx200704005.aspx

[19]

, Li

, Zhang

. Research on suitable distribution Ninxia wolfberry based on remote sensing and GIS[J]. World Chin Med (世界中医药), 2018, 13: 225-229.

[20]

Zhang

, Guo

, Qian

. Research progress on extraction, purification, and molecular structural elucidation of active polysaccharide from Lycii Fructus and analysis on its industrial development status and prospect[J]. Chin Tradit Herb Drug (中草药), 2017, 48: 424-432. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zcy201703002

[21]

Zhang

, Guo

, Qian

. Resources industrialization channels and strategies of active polysaccharide from Lycii Fructus based on analysis of domestic and foreign intellectual properties[J]. China J Chin Mater Med (中国中药杂志), 2016, 41: 4285-4291. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zgzyzz201623001

[22]

Sun

. Gold Wing Party (千金翼方)[M]. Dalian: Liaoning Science and Technology Press, 1997.

[23]

Qian

, Huang

, Qiu

et al . Literature research on nature and flavor changes of Fructus Lycii[J]. China J Tradit Chin Med Pharm (中华中医药杂志), 2016, 31: 1539-1542. http://search.cnki.net/down/default.aspx?filename=BXYY201605002&dbcode=CJFD&year=2016&dflag=pdfdown

[24]

Shen

. Dream Pool Essays (梦溪笔谈)[M]. Sichuan: Bashu Publishing House, 1995.

[25]

Zheng

, Zhang

. The edge, the frontier and the suburb:the three hierarchies of the northwest border-land in the northwest Song dynasty[J]. China's bord Hist Geogr Stud (中国边疆史地研究), 2012, 22: 14-20. http://en.cnki.com.cn/Article_en/CJFDTOTAL-ZGBJ201202002.htm

[26]

Liu

. Bencao Pinhui Jingao (本草品汇精要)[M]. Beijing: People's Sanitary Publishing Press, 1982.

[27]

. Compendium of Materia Medica (本草纲目)[M]. Jinling Hu Chenglong Engraving, 1596.

[28]

Zheng

. Update of Pseudo-Drugs (增订伪药条辨)[M]. Shanghai: Shanghai Science and Technology Press, 1959.

[29]

Kang

, Lv

, Huang

et al . Patten of ecological planning for Chinese material medica based on regional distribution[J]. China J Chin Mater Med (中国中药杂志), 2020, 45: 1982-1989. http://www.researchgate.net/publication/341941850_Pattern_of_ecological_planting_for_Chinese_materia_medica_based_on_regional_distribution

[30]

Guo

, Wang

, Yang

et al . Ecological agriculture:future of agriculture for Chinese material medica[J]. China J Chin Mater Med (中国中药杂志), 2017, 42: 231-238. http://www.ncbi.nlm.nih.gov/pubmed/28948725

2020年第55卷第10期

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文章信息

doi: 10.16438/j.0513-4870.2020-0572

接收时间：2020-04-28
首发时间：2026-01-23
出版时间：2020-10-12

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作者

出版历史

收稿日期：2020-04-28
修回日期：2020-05-20

基金

国家自然科学基金项目(81773837)

国家自然科学基金项目(81873189)

宁夏科技重点研发计划(东西部合作项目2017BY079)

作者信息

2.宁夏医科大学药学院, 宁夏银川 750021

3.甘肃中医药大学药学院, 甘肃兰州 730000

通讯作者:

*郭盛, E-mail:guosheng@njucm.edu.cn;

段金廒, E-mail:dja@njucm.edu.cn

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2种不同金属材料的力学参数

科 Family	属数 Number of genus	种数 Number of species	占总种数比例 Percentage of total species (%)	属 Genus	种数 Number of species	占总种数比例 Percentage of total species (%)
鹅膏菌科Amanitaceae	2	11	5.26	鹅膏菌属 Amanita	10	4.78
小菇科 Mycenaceae	2	12	5.74	丝盖伞属 Inocybe	5	2.39
多孔菌科 Polyporaceae	8	14	6.70	蜡蘑属 Laccaria	5	2.39
红菇科 Russulaceae	3	23	11.00	小皮伞属 Marasmius	6	2.87
				小菇属 Mycena	11	5.26
				光柄菇属 Pluteus	5	2.39
				红菇属 Russula	17	8.13
				栓菌属 Trametes	5	2.39

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TxT

No.	Producing area	Longtitude	Latitude	Altitude/m
1	Huinong, Ningxia	106.80°	39.06°	1 093
2	Huinong, Ningxia	106.61°	39.08°	1 054
3	Huinong, Ningxia	106.53°	39.01°	1 054
4	Huinong, Ningxia	106.59°	39.06°	1 054
5	Xixia, Ningxia	106.20°	38.66°	1 078
6	Xixia, Ningxia	106.20°	38.66°	1 079
7	Xixia, Ningxia	106.14°	38.64°	1 074
8	Xixia, Ningxia	106.10°	38.64°	1 082
9	Xixia, Ningxia	106.10°	38.64°	1 082
10	Hongsipu, Ningxia	105.97°	37.40°	1 272
11	Hongsipu, Ningxia	105.95°	37.40°	1 330
12	Litong, Ningxia	106.26°	37.78°	1 136
13	Zhongning, Ningxia	105.62°	37.50°	1 188
14	Zhongning, Ningxia	105.93°	37.46°	1 260
15	Zhongning, Ningxia	105.93°	37.46°	1 260
16	Zhongning, Ningxia	105.72°	37.48°	1 200
17	Zhongning, Ningxia	105.72°	37.48°	1 200
18	Zhongning, Ningxia	105.72°	37.48°	1 200
19	Zhongning, Ningxia	105.72°	37.48°	1 200
20	Zhongning, Ningxia	105.68°	37.30°	1 174
21	Zhongning, Ningxia	105.68°	37.30°	1 174
22	Zhongning, Ningxia	105.99°	37.27°	1 223
23	Zhongning, Ningxia	105.63°	37.38°	1 213
24	Zhongning, Ningxia	105.63°	37.29°	1 312
25	Zhongning, Ningxia	105.57°	37.31°	1 347
26	Shapotou, Ningxia	105.13°	37.54°	1 189
27	Shapotou, Ningxia	105.43°	37.51°	1 179
28	Shapotou, Ningxia	105.40°	37.54°	1 170
29	Yuanzhou, Ningxia	106.16°	36.40°	1 496
30	Yuanzhou, Ningxia	106.16°	36.45°	1 525
31	Yuanzhou, Ningxia	106.10°	36.37°	1 517
32	Jingyuan, Gansu	105.27°	36.85°	1 757
33	Jingyuan, Gansu	105.16°	36.93°	1 679
34	Jingyuan, Gansu	105.16°	36.93°	1 679
35	Jingyuan, Gansu	105.02°	37.00°	1 630
36	Jingyuan, Gansu	105.02°	37.00°	1 630
37	Jingyuan, Gansu	104.86°	37.03°	1 595
38	Jingyuan, Gansu	104.86°	37.03°	1 595
39	Jingtai, Gansu	94.78°	36.44°	2 754
40	Gulang, Gansu	103.51°	37.54°	1 716
41	Gulang, Gansu	103.51°	37.54°	1 716
42	Gulang, Gansu	103.46°	37.48°	1 835
43	Gulang, Gansu	103.40°	37.54°	1 817
44	Ganzhou, Gansu	100.60°	38.87°	1 469
45	Ganzhou, Gansu	100.60°	38.87°	1 469
46	Linze, Gansu	100.28°	39.31°	1 379
47	Jinta, Gansu	99.49°	40.29°	1 128
48	Jinta, Gansu	99.51°	40.31°	1 104
49	Jinta, Gansu	98.73°	40.18°	1 189
50	Yumen, Gansu	97.86°	40.21°	1 212
51	Yumen, Gansu	97.39°	39.97°	1 657
52	Guazhou, Gansu	96.14°	40.53°	1 188
53	Guazhou, Gansu	96.51°	40.53°	1 198
54	Guazhou, Gansu	96.51°	40.53°	1 198
55	Guazhou, Gansu	95.71°	40.06°	1 534
56	Wulateqianqi, Inner Mongolia	109.07°	40.63°	1 017
57	Wulateqianqi, Inner Mongolia	109.07°	40.63°	1 017
58	Wulateqianqi, Inner Mongolia	109.07°	40.62°	1 015
59	Wulateqianqi, Inner Mongolia	109.07°	40.62°	1 015
60	Wulateqianqi, Inner Mongolia	109.07°	40.62°	1 015
61	Wulateqianqi, Inner Mongolia	109.07°	40.61°	1 014
62	Wulateqianqi, Inner Mongolia	109.08°	40.60°	1 016
63	Wulateqianqi, Inner Mongolia	109.08°	40.63°	1 015
64	Wulateqianqi, Inner Mongolia	109.08°	40.63°	1 016
65	Wulateqianqi, Inner Mongolia	109.14°	40.59°	1 015
66	Wulateqianqi, Inner Mongolia	109.14°	40.59°	1 015
67	Wuyuani, Inner Mongolia	108.24°	41.18°	1 023
68	Wuyuani, Inner Mongolia	108.24°	41.18°	1 023
69	Wuyuani, Inner Mongolia	108.24°	41.18°	1 023
70	Wuyuani, Inner Mongolia	108.20°	41.16°	1 023
71	Hangjinhouqi, Inner Mongolia	106.99°	40.96°	1 035
72	Hangjinhouqi, Inner Mongolia	106.99°	40.96°	1 035
73	Hangjinhouqi, Inner Mongolia	106.98°	40.95°	1 036
74	Hangjinhouqi, Inner Mongolia	106.96°	40.93°	1 036
75	Geermu, Qinghai	94.78°	36.44°	2 754
76	Geermu, Qinghai	94.81°	36.44°	2 778
77	Geermu, Qinghai	95.75°	36.44°	3 178
78	Dulan, Qinghai	96.42°	36.45°	2 718
79	Dulan, Qinghai	96.40°	36.45°	2 696
80	Delingha, Qinghai	97.42°	37.24°	2 862
81	Delingha, Qinghai	96.74°	37.35°	2 817
82	Delingha, Qinghai	96.72°	37.32°	2 810
83	Delingha, Qinghai	97.16°	37.30°	2 815
84	Wulan, Qinghai	98.35°	36.96°	2 924
85	Jinghe, Xingjiang	82.65°	44.54°	332
86	Jinghe, Xingjiang	82.60°	44.60°	295
87	Jinghe, Xingjiang	82.70°	44.56°	308
88	Jinghe, Xingjiang	82.63°	44.62°	301
89	Jinghe, Xingjiang	82.75°	44.54°	316
90	Jinghe, Xingjiang	82.68°	44.56°	312
91	Jinghe, Xingjiang	82.65°	44.57°	305
92	Jinghe, Xingjiang	82.62°	44.58°	303
93	Jinghe, Xingjiang	82.64°	44.59°	293
94	Jinghe, Xingjiang	82.73°	44.52°	325

No.

Producing area

Longtitude

Latitude

Altitude/m

Huinong, Ningxia

106.80°

39.06°

1 093

Huinong, Ningxia

106.61°

39.08°

1 054

Huinong, Ningxia

106.53°

39.01°

1 054

Huinong, Ningxia

106.59°

39.06°

1 054

Xixia, Ningxia

106.20°

38.66°

1 078

Xixia, Ningxia

106.20°

38.66°

1 079

Xixia, Ningxia

106.14°

38.64°

1 074

Xixia, Ningxia

106.10°

38.64°

1 082

Xixia, Ningxia

106.10°

38.64°

1 082

Hongsipu, Ningxia

105.97°

37.40°

1 272

Hongsipu, Ningxia

105.95°

37.40°

1 330

Litong, Ningxia

106.26°

37.78°

1 136

Zhongning, Ningxia

105.62°

37.50°

1 188

Zhongning, Ningxia

105.93°

37.46°

1 260

Zhongning, Ningxia

105.93°

37.46°

1 260

Zhongning, Ningxia

105.72°

37.48°

1 200

Zhongning, Ningxia

105.72°

37.48°

1 200

Zhongning, Ningxia

105.72°

37.48°

1 200

Zhongning, Ningxia

105.72°

37.48°

1 200

Zhongning, Ningxia

105.68°

37.30°

1 174

Zhongning, Ningxia

105.68°

37.30°

1 174

Zhongning, Ningxia

105.99°

37.27°

1 223

Zhongning, Ningxia

105.63°

37.38°

1 213

Zhongning, Ningxia

105.63°

37.29°

1 312

Zhongning, Ningxia

105.57°

37.31°

1 347

Shapotou, Ningxia

105.13°

37.54°

1 189

Shapotou, Ningxia

105.43°

37.51°

1 179

Shapotou, Ningxia

105.40°

37.54°

1 170

Yuanzhou, Ningxia

106.16°

36.40°

1 496

Yuanzhou, Ningxia

106.16°

36.45°

1 525

Yuanzhou, Ningxia

106.10°

36.37°

1 517

Jingyuan, Gansu

105.27°

36.85°

1 757

Jingyuan, Gansu

105.16°

36.93°

1 679

Jingyuan, Gansu

105.16°

36.93°

1 679

Jingyuan, Gansu

105.02°

37.00°

1 630

Jingyuan, Gansu

105.02°

37.00°

1 630

Jingyuan, Gansu

104.86°

37.03°

1 595

Jingyuan, Gansu

104.86°

37.03°

1 595

Jingtai, Gansu

94.78°

36.44°

2 754

Gulang, Gansu

103.51°

37.54°

1 716

Gulang, Gansu

103.51°

37.54°

1 716

Gulang, Gansu

103.46°

37.48°

1 835

Gulang, Gansu

103.40°

37.54°

1 817

Ganzhou, Gansu

100.60°

38.87°

1 469

Ganzhou, Gansu

100.60°

38.87°

1 469

Linze, Gansu

100.28°

39.31°

1 379

Jinta, Gansu

99.49°

40.29°

1 128

Jinta, Gansu

99.51°

40.31°

1 104

Jinta, Gansu

98.73°

40.18°

1 189

Yumen, Gansu

97.86°

40.21°

1 212

Yumen, Gansu

97.39°

39.97°

1 657

Guazhou, Gansu

96.14°

40.53°

1 188

Guazhou, Gansu

96.51°

40.53°

1 198

Guazhou, Gansu

96.51°

40.53°

1 198

Guazhou, Gansu

95.71°

40.06°

1 534

Wulateqianqi, Inner Mongolia

109.07°

40.63°

1 017

Wulateqianqi, Inner Mongolia

109.07°

40.63°

1 017

Wulateqianqi, Inner Mongolia

109.07°

40.62°

1 015

Wulateqianqi, Inner Mongolia

109.07°

40.62°

1 015

Wulateqianqi, Inner Mongolia

109.07°

40.62°

1 015

Wulateqianqi, Inner Mongolia

109.07°

40.61°

1 014

Wulateqianqi, Inner Mongolia

109.08°

40.60°

1 016

Wulateqianqi, Inner Mongolia

109.08°

40.63°

1 015

Wulateqianqi, Inner Mongolia

109.08°

40.63°

1 016

Wulateqianqi, Inner Mongolia

109.14°

40.59°

1 015

Wulateqianqi, Inner Mongolia

109.14°

40.59°

1 015

Wuyuani, Inner Mongolia

108.24°

41.18°

1 023

Wuyuani, Inner Mongolia

108.24°

41.18°

1 023

Wuyuani, Inner Mongolia

108.24°

41.18°

1 023

Wuyuani, Inner Mongolia

108.20°

41.16°

1 023

Hangjinhouqi, Inner Mongolia

106.99°

40.96°

1 035

Hangjinhouqi, Inner Mongolia

106.99°

40.96°

1 035

Hangjinhouqi, Inner Mongolia

106.98°

40.95°

1 036

Hangjinhouqi, Inner Mongolia

106.96°

40.93°

1 036

Geermu, Qinghai

94.78°

36.44°

2 754

Geermu, Qinghai

94.81°

36.44°

2 778

Geermu, Qinghai

95.75°

36.44°

3 178

Dulan, Qinghai

96.42°

36.45°

2 718

Dulan, Qinghai

96.40°

36.45°

2 696

Delingha, Qinghai

97.42°

37.24°

2 862

Delingha, Qinghai

96.74°

37.35°

2 817

Delingha, Qinghai

96.72°

37.32°

2 810

Delingha, Qinghai

97.16°

37.30°

2 815

Wulan, Qinghai

98.35°

36.96°

2 924

Jinghe, Xingjiang

82.65°

44.54°

332

Jinghe, Xingjiang

82.60°

44.60°

295

Jinghe, Xingjiang

82.70°

44.56°

308

Jinghe, Xingjiang

82.63°

44.62°

301

Jinghe, Xingjiang

82.75°

44.54°

316

Jinghe, Xingjiang

82.68°

44.56°

312

Jinghe, Xingjiang

82.65°

44.57°

305

Jinghe, Xingjiang

82.62°

44.58°

303

Jinghe, Xingjiang

82.64°

44.59°

293

Jinghe, Xingjiang

82.73°

44.52°

325

No.	Component	Regression equation	P values	Adjust R²
y₁	Zeaxanthin	y₁ = 0.206 254 8 - 0.00210 96x₆ - 0.005 089 3x₂₀ - 0.026 519 5x₃₉ + 0.004 533 2x₄₈	3.31E-11	0.443 9
y₂	β-Cryptoxanthin	y₂ = 0.001 576 - 0.000 072 49x₂₀ - 0.000 136 5x₂₃ - 0.000 010 64x₂₈ - 0.000 084 66x₄₃ + 0.000 102 0x₄₆	1.72E-10	0.435 5
y₃	β-Carotene	y3 = 0.035 737 - 0.007 060x₁₇ - 0.005 896x₁₈ - 0.006 281x₁₉ - 0.012 755x₂₁ + 0.007 614x₄₆	3.06E-12	0.477 1
y₄	Zeaxanthin dipalmitate	y₄ = -18.427 7 + 0.004 586x₄ - 0.118 425x₆ + 0.606 201x₁₇ + 0.740 070x₁₈ + 1.136 655x₁₉ + 0.929 495x₃₂ - 0.479 786x₄₄ - 0.581 787x₄₆ - 0.330 538x₄₇ - 0.551 557x₄₈	2.14E-12	0.538
y₅	Total carotenoids	y₅ = 24.321 9 - 0.165 0x₆ + 1.376 46x₁₇ + 1.107 55x₁₈ + 1.670 88x₁₉ + 1.391 11x₃₂ - 0.273 9x₃₃ - 0.529 97x₄₄ - 0.473 58x₄₅ - 1.262 67x₄₆	2.08E-14	0.592 7
y₆	Neutral polysaccharides	y₆ = 80.159 32 - 0.355 79x₆ - 0.707 18x₂₀ - 1.414 06x₂₃ - 1.219 59x₂₇ + 1.082 78x₃₅ - 0.894 85x₃₆ + 1.325 43x₄₁ - 0.283 31x₄₂ + 0.359 26x₄₈	6.78E-12	0.562 2
y₇	Acid polysaccharides	y₇ = 9.148 24 + 0.135 99x₁₈ + 0.101 36x₁₉ - 0.083 09x₄₃	1.37E-09	0.369 2
y₈	Total phenolic	y₈ = 6.845 64 + 0.412 99x₂₅ + 0.291 96x₂₆ + 0.365 91x₃₆ - 1.018 24x₄₁ - 0.042 45x₄₂	2.39E-10	0.463 3
y₉	Total flavonoids	y₉ = -5.465 896 - 0.112 732x₇ + 0.003 628x₈ - 1.827 112x₁₂ - 1.139 439x₂₃ - 0.344 761x₁₈ + 0.477 422x₁₉ + 0.231 034x₂₅ + 0.220 894x₂₆ + 1.245 965x₄₀ - 0.292 422x₄₁ - 0.199 244x₄₂ + 0.230 241x₄₃ - 0.718 579x₄₈	5.53E-06	0.679 8
y₁₀	Betaine	y₁₀ = 18.748 48 - 0.055 38x₆ - 0.965 68x₁₂ - 3.270 28x₂₃ - 2.288 40x₁₃ + 1.876 48x₃₇	6.23E-11	0.551 7
y₁₁	Protein	y₁₁ = -2.621 256 1 + 0.137 250 5x₇ - 0.002 735x₈ + 0.363 642x₃₀ + 0.289 77x₃₁ + 0.103 814 6x₃₃ - 0.603 991 1x₄₄ - 0.172 843 1x₄₅	2.41E-11	0.491 8
y₁₂	Fructose	y₁₂ = 331.3 - 0.003 527x₁ + 0.104 8x₂ + 0.026 91x₄ - 4.621x₇ + 2.637x₉ + 2.738x₃₁ - 2.956x₃₇ + 0.359x₃₈ + 9.471x₃₉ - 2.398x₄₁ - 2.405x₄₂ + 2.582x₄₇	< 2.2E-16	0.985 2
y₁₃	Glucose	y₁₃ = 451.622 46 - 0.010 031x₁ + 0.056 359x₂ + 0.050 514x₄ + 0.528 615x₆ - 0.974 702x₇ - 0.077 919x₈ + 1.242 797x₉ + 4.221 319x₁₄ - 4.653 498x₂₂ - 3.008 636x₂₅ + 3.558 910x₃₀ - 1.117 499x₃₂ - 2.156 630x₃₄ - 2.201 215x₃₇ - 0.111 315x₃₈ + 3.097 005x₄₇	< 2.2E-16	0.981 7
y₁₄	Sucrose	y₁₄ = 12.44 + 0.000 384 2x₂ - 0.002 907x₆ + 0.009 014x₇ + 0.066 31x₁₅ - 0.092 68x₂₂ + 0.010 16x₂₆ + 0.023 99x₃₃ - 0.022 72x₃₄ - 0.035 47x₃₇ + 0.010 29x₄₄ - 0.022 89x₄₅	< 2.2E-16	0.809 3
y₁₅	Maltose	y₁₅ = 3.036 29 + 0.202 90x₂₆ + 0.081 58x₃₆ - 0.258 88x₄₁	< 2.2E-16	0.613 6
y₁₆	Glutamic acid	y₁₆ = 451.987 96 - 9.318 31x₅ - 0.498 64x₇ - 17.700 01x₁₂ - 13.213 23x₂₄ + 2.786 72x₂₅ + 1.906 54x₂₆ + 5.687 64x₃₇ - 1.443 30x₄₁ - 2.832 14x₄₂	< 2.2E-16	0.719 8
y₁₇	Alanine	y₁₇ = -423.856 98 + 26.857 13x₅ + 0.212 76x₈ - 51.525 47x₂₄ + 11.245 34x₂₅ - 5.608 01x₂₇ - 10.490 46x₃₄ + 10.288 42x₃₅	< 2.2E-16	0.855 6
y₁₈	Hydroxyproline	y₁₈ = -6.030 169 2 + 0.036 182 2x₇ - 0.000 568 1x₈ + 0.096 650x₁₆ - 0.019 082 9x₁₈ + 0.097 936 2x₁₉ - 0.039 236 1x₂₀ + 0.312 212x₂₄ + 0.032 922 7x₂₆ - 0.071 307 9x₂₇ + 0.040 639 2x₃₄ - 0.038 425 1x₃₅ + 0.053 350 2x₃₇ + 0.035 562 7x₄₂ - 0.093 847 6x₄₈	< 2.2E-16	0.861 2
y₁₉	Lysine	y₁₉ = 20.108 32 - 0.197 22x₇ + 5.885 1x₁₃ + 1.262 33x₁₉ - 3.793 31x₂₄ + 0.537 49x₂₅ + 0.573 24x₂₆ + 0.908 34x₃₅ - 1.167 98x₃₆ - 3.026 31x₃₇ - 0.168 3x₃₈ + 4.957 43x₃₉ - 0.630 26x₄₂ - 0.747 16x₄₃ + 0.909 26x₄₆ - 1.832 64x₄₈	< 2.2E-16	0.936 6
y₂₀	Glutamine	y₂₀ = -735.988 81 + 0.161 58x₄ + 2.600 1x₆ + 8.238 66x₇ - 3.494 74x₉ + 8.011x₁₄ - 23.680 29x₃₁ + 9.341 62x₄₂ + 18.614 86x₄₄	< 2.2E-16	0.822 5
y₂₁	Serine	y₂₁ = -135 0 + 0.179 7x₄ + 21.31x₅ + 1.773x₆ + 14.66x₇ - 0.257 2x₈ - 14.68x₉ - 5.298x₂₈ + 11.11x₃₀ - 26.18x₃₁ + 6.816x₄₂ + 18.64x₄₄	< 2.2E-16	0.915
y₂₂	Citrulline	y₂₂ = 250.578 16 + 0.078 67x₄ - 11.436 93x₅ + 1.639 03x₇ - 18.405 28x₁₃ + 2.465 04x₂₀ - 50.008 1x₂₄ + 4.063 76x₂₅ + 18.846 5x₃₉	< 2.2E-16	0.675 4
y₂₃	Arginine	y₂₃ = 172.876 + 11.109x₂₀ + 41.535x₃₇ - 136.286x₃₉ + 10.375x₄₃ - 12.332x₄₆	2.92E-15	0.594 2
y₂₄	Aspartic acid	y₂₄ = 303.294 2 + 0.958 6x₆ + 10.431 5x₁₄ - 43.932x₂₄ + 8.628x₂₅ + 5.3407x₂₇ - 9.505 3x₃₇ - 10.432 2x₄₁	< 2.2E-16	0.692 8
y₂₅	Asnparagin	y₂₅ = -114 7 + 0.139 6x₈ - 24.19x₁₂ + 27.27x₁₄ - 13.51x₁₉ + 5.198x₂₀ - 59.59x₂₃ + 36.62x₂₅ - 2.339x₃₈ - 23.72x₄₁ - 8.57x₄₂ + 5.091x₄₃	< 2.2E-16	0.900 1
y₂₆	GABA	y₂₆ = -38.648 896 + 0.008 729x₄ - 0.572 554x₅ - 0.035 023x₈ + 0.023 51x₁₁ - 1.344 205x₁₃ - 1.090 986x₂₃ + 0.511 728x₂₆ - 0.186 655x₂₈ + 0.934 137x₃₀ + 0.703 033x₃₂ + 1.301 243x₃₇ - 1.600 242x₄₁ - 0.170 576x₄₂ - 0.028 769x₄₃	< 2.2E-16	0.872 6
y₂₇	Methionine	y₂₇ = 16.494 370 3 - 0.001 626 4x₈ - 0.856 271 9x₁₂ - 1.090 167 4x₂₄ + 0.099 139x₂₆ + 0.173 756 8x₃₅ - 0.230 753 3x₃₆ + 1.426 185 6x₃₇ - 1.051 769 9x₄₀	< 2.2E-16	0.733 5
y₂₈	Phenylalanine	y₂₈ = 5.000 61 - 0.319 43x₅ - 1.634 13x₁₂ - 0.037 86x₂₀ + 0.238 42x₂₅ - 0.067 76x₃₆ + 1.070 14x₃₇ - 0.149 5x₄₂	7.78E-13	0.550 3
y₂₉	Proline	y₂₉ = 777.673 + 20.533x₉ + 131.606x₁₂ - 91.966x₁₂ + 22.328x₂₆ - 8.06x₂₇ + 30.316x₃₆ - 59.162x₄₁ + 23.529x₄₂	< 2.2E-16	0.718 5
y₃₀	Threonine	y₃₀ = 109.297 + 0.922 5x₆ + 2.323 5x₇ - 1.922 5x₉ - 15.749 6x₁₂ - 0.7854x₁₉ - 15.232 8x₂₃ + 3.168 2x₂₅ + 4.016 6x₃₀ - 5.296 6x₃₁ - 1.562 9x₃₃ + 13.231 9x₃₇	< 2.2E-16	0.724 8
y₃₁	Tryptophan	y₃₁ = 32.329 597 6 - 0.463 908 2x₅ - 0.001 012 6x₈ + 0.212 903 4x₂₅ - 0.216 249 8x₄₁ + 0.096 804 4x₄₃ - 0.134 250 6x₄₆ + 0.094 003 2x₄₈	4.91E-13	0.562 1
y₃₂	Tyrosine	y₃₂ = 13.299 08 - 0.988 41x₁₂ + 1.461 21x₂₅ + 0.343 09x₂₇ - 1.731 78x₄₁	< 2.2E-16	0.657 8
y₃₃	Valine	y₃₃ = 109.359 554 - 0.006 006x₈ - 0.209 613x₂₀ + 0.680 462x₂₅ + 0.456 238x₃₅ - 0.643 298x₃₇ - 1.491 717x₄₁ + 0.414 893x₄₂	< 2.2E-16	0.685 3
y₃₄	Leucine	y₃₄ = 101.636 07 - 0.132 167x₆ - 0.501 552x₇ + 0.010 507x₈ - 0.026 243x₁₁ + 0.506 04x₁₉ + 0.299 252x₂₀ - 6.126 133x₂₄ + 0.700 453x₂₆ + 0.288 294x₃₅ - 0.702 286x₄₂ - 0.215 384x₄₆	< 2.2E-16	0.811 6
y₃₅	Isoleucine	y₃₅ = 4.432 25 - 1.599 46x₁₂ - 0.056 32x₁₉ - 1.485 8x₂₃ + 0.347 16x₂₅ -0.163 21x₂₇ + 0.259 38x₃₅ - 0.267 02x₃₆ + 1.195 04x₃₇ - 0.116 87x₄₂	< 2.2E-16	0.818 7
y₃₆	Uracil	y₃₆ = -101.7 - 0.277 6x₆ + 0.017 41x₈ - 5.021x₁₂ - 0.882 4x₂₀ - 6.71x₂₃ + 9.05x₂₄ + 1.816x₂₅ - 0.996 5x₂₇ - 1.006x₃₄ + 1.484x₃₅ - 0.710 8x₃₆ + 3.518x₄₀ - 0.685 1x₄₂ + 0.554 4x₄₆ - 0.968 4x₄₈	< 2.2E-16	0.735 2
y₃₇	Guanosine	y₃₇ = -81.83 + 0.161 9x₇ + 0.003 023x₈ - 4.04x₁₂ + 0.832 9x₁₆ - 2.658x₂₃ + 5.169x₂₄ + 0.898 8x₂₅ - 0.508x₂₇ + 2.37x₃₇ - 0.483 8x₄₁ + 0.662 6x₄₃ - 0.774 1x₄₆	< 2.2E-16	0.878 3
y₃₈	2'-Desoxyuridine	y₃₈ = 0.053 18 - 0.001 203x₆ - 0.001 739x₇ + 0.000 076 53x₈ + 0.005 061x₁₆ + 0.005 785x₁₉ - 0.003 084x₂₇ + 0.000 350 3x₃₈ + 0.007 261x₄₁ - 0.003 963x₄₂ + 0.004 664x₄₃ - 0.007 38x₄₆	< 2.2E-16	0.751 1
y₃₉	2'- Deoxycytidine	y₃₉ = 0.069 995 4 + 0.000 824 6x₇ - 0.004 275 6x₂₀ + 0.006 985 4x₂₂ + 0.009 380 1x₂₅ + 0.005 608 4x₂₆ - 0.003 676 2x₃₄ + 0.004 022 9x₃₅ + 0.006 909 3x₃₆ - 0.003 602 6x₄₀ - 0.021 448 7x₄₁ + 0.000 936 2x₄₆	< 2.2E-16	0.767 7
y₄₀	2'-Deoxyguanosine	y₄₀ = -0.650 9 + 0.000 016 86x₁ + 0.021 95x₁₆ + 0.039 39x₁₉ - 0.043 48x₂₃ + 0.002 003x₂₅ + 0.040 04x₄₀ + 0.015 81x₄₃ - 0.027 01x₄₆ - 0.019 01x₄₈	< 2.2E-16	0.787 8
y₄₁	Adenine	y₄₁ = 28.072 181 + 0.003 168x₈ - 1.733 71x₁₂ - 0.253 376x₂₀ - 0.870 28x₂₃ + 0.536 413x₂₅ -0.248 485x₂₇ - 0.417 505x₃₄ + 0.751 187x₃₅ - 0.522 496x₃₆ + 3.312 867x₃₉ + 0.035 772x₄₃	< 2.2E-16	0.908 8
y₄₂	Cytidine	y₄₂ = 2.274 595 7 - 0.045 453 1x₆ - 0.053 297 9x₇ + 0.003 281 7x₈ - 0.089 267 2x₂₀ + 0.124 383 6x₂₅ + 0.150 313x₂₆ - 0.162 468 3x₂₇ - 0.102 764 7x₃₄ + 0.166 437 3x₃₅ - 0.140 708 4x₄₂ + 0.024 054 8x₄₆	< 2.2E-16	0.712
y₄₃	Cytosine	y₄₃ = 0.141 7 - 0.000 004 229x₈ - 0.001 149x₁₀ - 0.016 76x₁₂ + 0.003 532x₄₀	2.00E-13	0.519 8
y₄₄	Guanine	y₄₄ = 0.284 629 3 - 0.129 538 4x₇ + 0.004 199 8x₈ + 0.105 825 5x₁₉ - 0.466 135 4x₂₄ + 0.183 057 6x₂₅ + 0.081 846 1x₂₆ + 0.096 525 2x₄₀ + 0.136 679 7x₄₆ - 0.181 945 6x₄₈	< 2.2E-16	0.723 9
y₄₅	Inosine	y₄₅ = 4.704 38 - 0.296 88x₁₂ - 0.058 27x₂₀ + 0.040 74x₂₅ - 0.068 65x₃₄ + 0.160 25x₃₅ - 0.097 9x₃₆ + 0.049 84x₄₆ - 0.086 65x₄₈	< 2.2E-16	0.806 5
y₄₆	Uridine	y₄₆ = -119.957 21 + 0.025 89x₈ + 0.044 4x₁₁ + 4.936 59x₁₃ - 0.755 37x₂₀ - 1.784 76x₂₃ + 9.883 52x₂₄ + 2.160 31x₂₅ - 1.035 52x₂₇ - 1.694 44x₃₄ + 1.702 59x₃₅ - 0.439 67x₃₆ - 0.709 75x₄₂ + 0.220 06x₄₃ - 0.565 66x₄₈	< 2.2E-16	0.886 9
y₄₇	Xanthine	y₄₇ = 5.499 942 - 0.023 861x₆ - 0.004 526x₁₁ - 0.239 788x₁₂ - 0.073 482x₂₁ + 0.0518 2x₂₆ - 0.093 824x₂₇ - 0.027 254x₃₄ + 0.138 456x₃₅ - 0.074 182x₃₆ + 0.014 472x₄₆	< 2.2E-16	0.732

No.

Component

Regression equation

P values

Adjust R²

y₁

Zeaxanthin

y₁ = 0.206 254 8 - 0.00210 96x₆ - 0.005 089 3x₂₀ - 0.026 519 5x₃₉ + 0.004 533 2x₄₈

3.31E-11

0.443 9

y₂

β-Cryptoxanthin

y₂ = 0.001 576 - 0.000 072 49x₂₀ - 0.000 136 5x₂₃ - 0.000 010 64x₂₈ - 0.000 084 66x₄₃ + 0.000 102 0x₄₆

1.72E-10

0.435 5

y₃

β-Carotene

y3 = 0.035 737 - 0.007 060x₁₇ - 0.005 896x₁₈ - 0.006 281x₁₉ - 0.012 755x₂₁ + 0.007 614x₄₆

3.06E-12

0.477 1

y₄

Zeaxanthin dipalmitate

y₄ = -18.427 7 + 0.004 586x₄ - 0.118 425x₆ + 0.606 201x₁₇ + 0.740 070x₁₈ + 1.136 655x₁₉ + 0.929 495x₃₂ - 0.479 786x₄₄ - 0.581 787x₄₆ - 0.330 538x₄₇ - 0.551 557x₄₈

2.14E-12

0.538

y₅

Total carotenoids

y₅ = 24.321 9 - 0.165 0x₆ + 1.376 46x₁₇ + 1.107 55x₁₈ + 1.670 88x₁₉ + 1.391 11x₃₂ - 0.273 9x₃₃ - 0.529 97x₄₄ - 0.473 58x₄₅ - 1.262 67x₄₆

2.08E-14

0.592 7

y₆

Neutral polysaccharides

y₆ = 80.159 32 - 0.355 79x₆ - 0.707 18x₂₀ - 1.414 06x₂₃ - 1.219 59x₂₇ + 1.082 78x₃₅ - 0.894 85x₃₆ + 1.325 43x₄₁ - 0.283 31x₄₂ + 0.359 26x₄₈

6.78E-12

0.562 2

y₇

Acid polysaccharides

y₇ = 9.148 24 + 0.135 99x₁₈ + 0.101 36x₁₉ - 0.083 09x₄₃

1.37E-09

0.369 2

y₈

Total phenolic

y₈ = 6.845 64 + 0.412 99x₂₅ + 0.291 96x₂₆ + 0.365 91x₃₆ - 1.018 24x₄₁ - 0.042 45x₄₂

2.39E-10

0.463 3

y₉

Total flavonoids

y₉ = -5.465 896 - 0.112 732x₇ + 0.003 628x₈ - 1.827 112x₁₂ - 1.139 439x₂₃ - 0.344 761x₁₈ + 0.477 422x₁₉ + 0.231 034x₂₅ + 0.220 894x₂₆ + 1.245 965x₄₀ - 0.292 422x₄₁ - 0.199 244x₄₂ + 0.230 241x₄₃ - 0.718 579x₄₈

5.53E-06

0.679 8

y₁₀

Betaine

y₁₀ = 18.748 48 - 0.055 38x₆ - 0.965 68x₁₂ - 3.270 28x₂₃ - 2.288 40x₁₃ + 1.876 48x₃₇

6.23E-11

0.551 7

y₁₁

Protein

y₁₁ = -2.621 256 1 + 0.137 250 5x₇ - 0.002 735x₈ + 0.363 642x₃₀ + 0.289 77x₃₁ + 0.103 814 6x₃₃ - 0.603 991 1x₄₄ - 0.172 843 1x₄₅

2.41E-11

0.491 8

y₁₂

Fructose

y₁₂ = 331.3 - 0.003 527x₁ + 0.104 8x₂ + 0.026 91x₄ - 4.621x₇ + 2.637x₉ + 2.738x₃₁ - 2.956x₃₇ + 0.359x₃₈ + 9.471x₃₉ - 2.398x₄₁ - 2.405x₄₂ + 2.582x₄₇

< 2.2E-16

0.985 2

y₁₃

Glucose

y₁₃ = 451.622 46 - 0.010 031x₁ + 0.056 359x₂ + 0.050 514x₄ + 0.528 615x₆ - 0.974 702x₇ - 0.077 919x₈ + 1.242 797x₉ + 4.221 319x₁₄ - 4.653 498x₂₂ - 3.008 636x₂₅ + 3.558 910x₃₀ - 1.117 499x₃₂ - 2.156 630x₃₄ - 2.201 215x₃₇ - 0.111 315x₃₈ + 3.097 005x₄₇

< 2.2E-16

0.981 7

y₁₄

Sucrose

y₁₄ = 12.44 + 0.000 384 2x₂ - 0.002 907x₆ + 0.009 014x₇ + 0.066 31x₁₅ - 0.092 68x₂₂ + 0.010 16x₂₆ + 0.023 99x₃₃ - 0.022 72x₃₄ - 0.035 47x₃₇ + 0.010 29x₄₄ - 0.022 89x₄₅

< 2.2E-16

0.809 3

y₁₅

Maltose

y₁₅ = 3.036 29 + 0.202 90x₂₆ + 0.081 58x₃₆ - 0.258 88x₄₁

< 2.2E-16

0.613 6

y₁₆

Glutamic acid

y₁₆ = 451.987 96 - 9.318 31x₅ - 0.498 64x₇ - 17.700 01x₁₂ - 13.213 23x₂₄ + 2.786 72x₂₅ + 1.906 54x₂₆ + 5.687 64x₃₇ - 1.443 30x₄₁ - 2.832 14x₄₂

< 2.2E-16

0.719 8

y₁₇

Alanine

y₁₇ = -423.856 98 + 26.857 13x₅ + 0.212 76x₈ - 51.525 47x₂₄ + 11.245 34x₂₅ - 5.608 01x₂₇ - 10.490 46x₃₄ + 10.288 42x₃₅

< 2.2E-16

0.855 6

y₁₈

Hydroxyproline

y₁₈ = -6.030 169 2 + 0.036 182 2x₇ - 0.000 568 1x₈ + 0.096 650x₁₆ - 0.019 082 9x₁₈ + 0.097 936 2x₁₉ - 0.039 236 1x₂₀ + 0.312 212x₂₄ + 0.032 922 7x₂₆ - 0.071 307 9x₂₇ + 0.040 639 2x₃₄ - 0.038 425 1x₃₅ + 0.053 350 2x₃₇ + 0.035 562 7x₄₂ - 0.093 847 6x₄₈

< 2.2E-16

0.861 2

y₁₉

Lysine

y₁₉ = 20.108 32 - 0.197 22x₇ + 5.885 1x₁₃ + 1.262 33x₁₉ - 3.793 31x₂₄ + 0.537 49x₂₅ + 0.573 24x₂₆ + 0.908 34x₃₅ - 1.167 98x₃₆ - 3.026 31x₃₇ - 0.168 3x₃₈ + 4.957 43x₃₉ - 0.630 26x₄₂ - 0.747 16x₄₃ + 0.909 26x₄₆ - 1.832 64x₄₈

< 2.2E-16

0.936 6

y₂₀

Glutamine

y₂₀ = -735.988 81 + 0.161 58x₄ + 2.600 1x₆ + 8.238 66x₇ - 3.494 74x₉ + 8.011x₁₄ - 23.680 29x₃₁ + 9.341 62x₄₂ + 18.614 86x₄₄

< 2.2E-16

0.822 5

y₂₁

Serine

y₂₁ = -135 0 + 0.179 7x₄ + 21.31x₅ + 1.773x₆ + 14.66x₇ - 0.257 2x₈ - 14.68x₉ - 5.298x₂₈ + 11.11x₃₀ - 26.18x₃₁ + 6.816x₄₂ + 18.64x₄₄

< 2.2E-16

0.915

y₂₂

Citrulline

y₂₂ = 250.578 16 + 0.078 67x₄ - 11.436 93x₅ + 1.639 03x₇ - 18.405 28x₁₃ + 2.465 04x₂₀ - 50.008 1x₂₄ + 4.063 76x₂₅ + 18.846 5x₃₉

< 2.2E-16

0.675 4

y₂₃

Arginine

y₂₃ = 172.876 + 11.109x₂₀ + 41.535x₃₇ - 136.286x₃₉ + 10.375x₄₃ - 12.332x₄₆

2.92E-15

0.594 2

y₂₄

Aspartic acid

y₂₄ = 303.294 2 + 0.958 6x₆ + 10.431 5x₁₄ - 43.932x₂₄ + 8.628x₂₅ + 5.3407x₂₇ - 9.505 3x₃₇ - 10.432 2x₄₁

< 2.2E-16

0.692 8

y₂₅

Asnparagin

y₂₅ = -114 7 + 0.139 6x₈ - 24.19x₁₂ + 27.27x₁₄ - 13.51x₁₉ + 5.198x₂₀ - 59.59x₂₃ + 36.62x₂₅ - 2.339x₃₈ - 23.72x₄₁ - 8.57x₄₂ + 5.091x₄₃

< 2.2E-16

0.900 1

y₂₆

GABA

y₂₆ = -38.648 896 + 0.008 729x₄ - 0.572 554x₅ - 0.035 023x₈ + 0.023 51x₁₁ - 1.344 205x₁₃ - 1.090 986x₂₃ + 0.511 728x₂₆ - 0.186 655x₂₈ + 0.934 137x₃₀ + 0.703 033x₃₂ + 1.301 243x₃₇ - 1.600 242x₄₁ - 0.170 576x₄₂ - 0.028 769x₄₃

< 2.2E-16

0.872 6

y₂₇

Methionine

y₂₇ = 16.494 370 3 - 0.001 626 4x₈ - 0.856 271 9x₁₂ - 1.090 167 4x₂₄ + 0.099 139x₂₆ + 0.173 756 8x₃₅ - 0.230 753 3x₃₆ + 1.426 185 6x₃₇ - 1.051 769 9x₄₀

< 2.2E-16

0.733 5

y₂₈

Phenylalanine

y₂₈ = 5.000 61 - 0.319 43x₅ - 1.634 13x₁₂ - 0.037 86x₂₀ + 0.238 42x₂₅ - 0.067 76x₃₆ + 1.070 14x₃₇ - 0.149 5x₄₂

7.78E-13

0.550 3

y₂₉

Proline

y₂₉ = 777.673 + 20.533x₉ + 131.606x₁₂ - 91.966x₁₂ + 22.328x₂₆ - 8.06x₂₇ + 30.316x₃₆ - 59.162x₄₁ + 23.529x₄₂

< 2.2E-16

0.718 5

y₃₀

Threonine

y₃₀ = 109.297 + 0.922 5x₆ + 2.323 5x₇ - 1.922 5x₉ - 15.749 6x₁₂ - 0.7854x₁₉ - 15.232 8x₂₃ + 3.168 2x₂₅ + 4.016 6x₃₀ - 5.296 6x₃₁ - 1.562 9x₃₃ + 13.231 9x₃₇

< 2.2E-16

0.724 8

y₃₁

Tryptophan

y₃₁ = 32.329 597 6 - 0.463 908 2x₅ - 0.001 012 6x₈ + 0.212 903 4x₂₅ - 0.216 249 8x₄₁ + 0.096 804 4x₄₃ - 0.134 250 6x₄₆ + 0.094 003 2x₄₈

4.91E-13

0.562 1

y₃₂

Tyrosine

y₃₂ = 13.299 08 - 0.988 41x₁₂ + 1.461 21x₂₅ + 0.343 09x₂₇ - 1.731 78x₄₁

< 2.2E-16

0.657 8

y₃₃

Valine

y₃₃ = 109.359 554 - 0.006 006x₈ - 0.209 613x₂₀ + 0.680 462x₂₅ + 0.456 238x₃₅ - 0.643 298x₃₇ - 1.491 717x₄₁ + 0.414 893x₄₂

< 2.2E-16

0.685 3

y₃₄

Leucine

y₃₄ = 101.636 07 - 0.132 167x₆ - 0.501 552x₇ + 0.010 507x₈ - 0.026 243x₁₁ + 0.506 04x₁₉ + 0.299 252x₂₀ - 6.126 133x₂₄ + 0.700 453x₂₆ + 0.288 294x₃₅ - 0.702 286x₄₂ - 0.215 384x₄₆

< 2.2E-16

0.811 6

y₃₅

Isoleucine

y₃₅ = 4.432 25 - 1.599 46x₁₂ - 0.056 32x₁₉ - 1.485 8x₂₃ + 0.347 16x₂₅ -0.163 21x₂₇ + 0.259 38x₃₅ - 0.267 02x₃₆ + 1.195 04x₃₇ - 0.116 87x₄₂

< 2.2E-16

0.818 7

y₃₆

Uracil

y₃₆ = -101.7 - 0.277 6x₆ + 0.017 41x₈ - 5.021x₁₂ - 0.882 4x₂₀ - 6.71x₂₃ + 9.05x₂₄ + 1.816x₂₅ - 0.996 5x₂₇ - 1.006x₃₄ + 1.484x₃₅ - 0.710 8x₃₆ + 3.518x₄₀ - 0.685 1x₄₂ + 0.554 4x₄₆ - 0.968 4x₄₈

< 2.2E-16

0.735 2

y₃₇

Guanosine

y₃₇ = -81.83 + 0.161 9x₇ + 0.003 023x₈ - 4.04x₁₂ + 0.832 9x₁₆ - 2.658x₂₃ + 5.169x₂₄ + 0.898 8x₂₅ - 0.508x₂₇ + 2.37x₃₇ - 0.483 8x₄₁ + 0.662 6x₄₃ - 0.774 1x₄₆

< 2.2E-16

0.878 3

y₃₈

2'-Desoxyuridine

y₃₈ = 0.053 18 - 0.001 203x₆ - 0.001 739x₇ + 0.000 076 53x₈ + 0.005 061x₁₆ + 0.005 785x₁₉ - 0.003 084x₂₇ + 0.000 350 3x₃₈ + 0.007 261x₄₁ - 0.003 963x₄₂ + 0.004 664x₄₃ - 0.007 38x₄₆

< 2.2E-16

0.751 1

y₃₉

2'- Deoxycytidine

y₃₉ = 0.069 995 4 + 0.000 824 6x₇ - 0.004 275 6x₂₀ + 0.006 985 4x₂₂ + 0.009 380 1x₂₅ + 0.005 608 4x₂₆ - 0.003 676 2x₃₄ + 0.004 022 9x₃₅ + 0.006 909 3x₃₆ - 0.003 602 6x₄₀ - 0.021 448 7x₄₁ + 0.000 936 2x₄₆

< 2.2E-16

0.767 7

y₄₀

2'-Deoxyguanosine

y₄₀ = -0.650 9 + 0.000 016 86x₁ + 0.021 95x₁₆ + 0.039 39x₁₉ - 0.043 48x₂₃ + 0.002 003x₂₅ + 0.040 04x₄₀ + 0.015 81x₄₃ - 0.027 01x₄₆ - 0.019 01x₄₈

< 2.2E-16

0.787 8

y₄₁

Adenine

y₄₁ = 28.072 181 + 0.003 168x₈ - 1.733 71x₁₂ - 0.253 376x₂₀ - 0.870 28x₂₃ + 0.536 413x₂₅ -0.248 485x₂₇ - 0.417 505x₃₄ + 0.751 187x₃₅ - 0.522 496x₃₆ + 3.312 867x₃₉ + 0.035 772x₄₃

< 2.2E-16

0.908 8

y₄₂

Cytidine

y₄₂ = 2.274 595 7 - 0.045 453 1x₆ - 0.053 297 9x₇ + 0.003 281 7x₈ - 0.089 267 2x₂₀ + 0.124 383 6x₂₅ + 0.150 313x₂₆ - 0.162 468 3x₂₇ - 0.102 764 7x₃₄ + 0.166 437 3x₃₅ - 0.140 708 4x₄₂ + 0.024 054 8x₄₆

< 2.2E-16

0.712

y₄₃

Cytosine

y₄₃ = 0.141 7 - 0.000 004 229x₈ - 0.001 149x₁₀ - 0.016 76x₁₂ + 0.003 532x₄₀

2.00E-13

0.519 8

y₄₄

Guanine

y₄₄ = 0.284 629 3 - 0.129 538 4x₇ + 0.004 199 8x₈ + 0.105 825 5x₁₉ - 0.466 135 4x₂₄ + 0.183 057 6x₂₅ + 0.081 846 1x₂₆ + 0.096 525 2x₄₀ + 0.136 679 7x₄₆ - 0.181 945 6x₄₈

< 2.2E-16

0.723 9

y₄₅

Inosine

y₄₅ = 4.704 38 - 0.296 88x₁₂ - 0.058 27x₂₀ + 0.040 74x₂₅ - 0.068 65x₃₄ + 0.160 25x₃₅ - 0.097 9x₃₆ + 0.049 84x₄₆ - 0.086 65x₄₈

< 2.2E-16

0.806 5

y₄₆

Uridine

y₄₆ = -119.957 21 + 0.025 89x₈ + 0.044 4x₁₁ + 4.936 59x₁₃ - 0.755 37x₂₀ - 1.784 76x₂₃ + 9.883 52x₂₄ + 2.160 31x₂₅ - 1.035 52x₂₇ - 1.694 44x₃₄ + 1.702 59x₃₅ - 0.439 67x₃₆ - 0.709 75x₄₂ + 0.220 06x₄₃ - 0.565 66x₄₈

< 2.2E-16

0.886 9

y₄₇

Xanthine

y₄₇ = 5.499 942 - 0.023 861x₆ - 0.004 526x₁₁ - 0.239 788x₁₂ - 0.073 482x₂₁ + 0.0518 2x₂₆ - 0.093 824x₂₇ - 0.027 254x₃₄ + 0.138 456x₃₅ - 0.074 182x₃₆ + 0.014 472x₄₆

< 2.2E-16

0.732