基于二次通用旋转组合的植物生长调节剂最优组合

doi:10.6048/j.issn.1001-4330.2025.07.016

新疆农业科学 ›› 2025, Vol. 62 ›› Issue (7): 1709-1719.DOI: 10.6048/j.issn.1001-4330.2025.07.016

基于二次通用旋转组合的植物生长调节剂最优组合

杨柳¹^,²(), 唐光木¹^,²(), 刘娇², 朱杰¹^,², 郭珂妤¹^,², 张云舒¹^,², 马海刚², 徐万里¹^,²()

1.新疆农业大学资源与环境学院, 乌鲁木齐 830052
2.新疆维吾尔自治区农业科学院农业资源与环境研究所/农业农村部盐碱地改良与利用(干旱半干旱区盐碱地)重点实验室, 乌鲁木齐 830091

收稿日期:2024-12-08 出版日期:2025-07-20 发布日期:2025-09-05
通信作者: 唐光木(1983-),男,河南郏县人,研究员,硕士,研究方向为农林废弃物炭化利用,(E-mail)tangjunhui5120@126.com;
徐万里(1971-),男,陕西凤翔人,研究员,博士,研究方向为盐碱土改良与利用,(E-mail)wanlixun2005@163
作者简介:杨柳(1998-),女,内蒙古呼伦贝尔人,硕士研究生,研究方向为土壤改良与利用,(E-mail)59959383@qq.com
基金资助:
新疆维吾尔自治区重点研发计划项目“农林废弃物热解产物绿色关键技术研究”(2022B02013-3);新疆农业大学研究生科研创新项目(XJAUGRI2024038)

Research on the optimal combination of plant growth regulators based on quadratic universal rotation combination

YANG Liu¹^,²(), TANG Guangmu¹^,²(), LIU Jiao², ZHU Jie¹^,², GUO Keyu¹^,², ZHANG Yunshu¹^,², MA Haigang², XU Wanli¹^,²()

1. College of Resources and Environment, Xinjiang Agricultural University, Urumqi 830052, China
2. Key Laboratory of Saline-alkali Soil Improvement and Utilization (Saline-Alkali Land in Arid and Semi-Arid Regions), Ministry of Agriculture and Rural Affairs/Research Institute of Soil, Insitute of Agricultural Resources and Environment, Xinjiang Uygur Autonomous Region Academy of Agricultural Sciences, Urumqi 830091, China

Received:2024-12-08 Published:2025-07-20 Online:2025-09-05
Supported by:
Key R&D Program of Xinjiang Uygur Autonomous Region "Research on Green Key Technologies of Agricultural and Forestry Waste Pyrolysis Products"(2022B02013-3);Graduate Research Innovation Project of Xinjiang Agricultural University(XJAUGRI2024038)

摘要/Abstract

摘要：

【目的】探究复合双硝基酚钠(CSN)、植多苷(DSK)、丁双酰(D2)及复合奈氧(FN-6)对棉花植株抗逆能力的影响,寻求最佳配施比例。【方法】采用二次通用旋转组合设计,通过测定植株过氧化物酶(POD)、过氧化氢酶(CAT)、超氧化物歧化酶(SDO)、丙二醛(MDA)及吲哚乙酸(IAA)含量,使用Design-Expert 13为其建立函数模型,F检验,分析各回归模型及各项回归系数的显著性,利用模型分析PGR施量对植株酶活性及内源IAA含量的影响,使用熵权法选取植株POD活性为代表性指示指标对其回归模型进行模拟与筛选优化组合方案,得到最优施用比例。同时,通过TOPSIS法(Ci)、熵值法(Si)、因子分析(εj)、秩和比综合评价法(RSR)四种综合评价方法对代表性指标寻优结果进行验证,结果一致均为处在零水平施用效果最佳,施量可影响植株酶活性及内源IAA含量。【结果】随着PGR施量的增加植株POD、SOD、CAT活性与内源IAA含量呈先增加后降低趋势,MDA含量呈先下降后增加趋势。各因素对植株POD活性的影响大小为DSK>FN-6>CSN>D2,对植株CAT的影响大小为FN-6>CSN>DSK>D2,对植株SOD、MDA及内源IAA含量的影响大小为均CSN>DSK>FN-6>D2。【结论】最佳配施方案为CSN:446.04~448.73 mg/hm²、FN-6:526.28~528.96 mg/hm²、DSK:526.28~528.96 mg/hm²、D2:446.04~448.73 mg/hm²。

关键词: 二次通用旋转组合设计; 植物生长调节剂; 植株酶活; 寻优

Abstract:

【Objective】 In order to investigate the effects of compound sodium dinitrophenol (CSN), plant polysaccharides (DSK), succinyl (D2), and compound nanooxygen (FN-6) on the stress resistance of cotton plants, the optimal combination ratio is going to be sought. 【Methods】 This study used a quadratic universal rotation combination design to determine the content of plant peroxidase (POD), catalase (CAT), superoxide dismutase (SDO), malondialdehyde (MDA), and indoleacetic acid (IAA). Design Expert 13 was used to establish a functional model for it. F-test was used to analyze the significance of each regression model and regression coefficient. Afterwards, the model would be used to analyze the effect of PGR application on plant enzyme activity and endogenous IAA content and entropy weight method was used to select plant POD activity as a representative indicator to simulate and screen the optimal combination plan for its regression model. Then the optimal application ratio was obtained. At the same time, the optimization results of representative indicators were verified through four comprehensive evaluation methods: TOPSIS method (Ci), entropy method (Si), factor analysis (ε j), and rank sum ratio comprehensive evaluation method (RSR). The consistent results showed that the best application effect was achieved at the zero level, and the application amount could affect plant enzyme activity and endogenous IAA content. 【Results】 With the increase of PGR application, the activities of POD, SOD, CAT and endogenous IAA in plants showed a trend of first increasing and then decreasing, while the MDA content showed a trend of first decreasing and then increasing. The impact of various factors on plant POD activity was as follows: DSK>FN-6>CSN>D2, the impact on plant CAT was as follows: FN-6>CSN>DSK>D2, and the impact on plant SOD, MDA, and endogenous IAA content was as follows: CSN>DSK>FN-6>D2. 【Conclusion】 Through experimental simulation, the optimal application plan is CSN: 446.04-448.73 mg/hm² FN-6:526.28-528.96 mg/hm², DSK:526.28-528.96 mg/hm², D2:446.04-448.73 mg/hm².

Key words: secondary universal rotation combination design; plant growth regulators; plant enzyme activity; seeking optimization

中图分类号:

S143.8

杨柳, 唐光木, 刘娇, 朱杰, 郭珂妤, 张云舒, 马海刚, 徐万里. 基于二次通用旋转组合的植物生长调节剂最优组合[J]. 新疆农业科学, 2025, 62(7): 1709-1719.

YANG Liu, TANG Guangmu, LIU Jiao, ZHU Jie, GUO Keyu, ZHANG Yunshu, MA Haigang, XU Wanli. Research on the optimal combination of plant growth regulators based on quadratic universal rotation combination[J]. Xinjiang Agricultural Sciences, 2025, 62(7): 1709-1719.

图/表 10

参考文献 35

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编码值 Enco- ding value	实际值Actual value
编码值 Enco- ding value	X₁(CSN)	X₂(FN-6)	X₃(DSK)	X₄(D2)
2	900	900	900	900
1	693.75	693.75	693.75	693.75
0	487.5	487.5	487.5	487.5
-1	281.25	281.25	281.25	281.25
-2	75	75	75	75

编码值 Enco- ding value	实际值Actual value
编码值 Enco- ding value	X₁(CSN)	X₂(FN-6)	X₃(DSK)	X₄(D2)
2	900	900	900	900
1	693.75	693.75	693.75	693.75
0	487.5	487.5	487.5	487.5
-1	281.25	281.25	281.25	281.25
-2	75	75	75	75

Y	目标函数回归方程 Objective function regression equation	R²
POD	Y₁=45936.29-1589.79 X₁-326.88 X₂+730.63 X₃+210.12 X₄-435.19 X₁ X₂-822.81 X₁ X₃-17.56 X₁ X₄-1351.44 X₂ X₃-770.94 X₂ X₄-829.81 X₃ X₄-3168.87 X₁-3620.12 X₂-2626.25 X₃-2896.00 X₄	0.93
CAT	Y₂=14.54-0.50 X₁+0.92 X₂+0.51 X₃+0.11 X₄+0.58 X₁ X₂-0.29 X₁ X₃-0.03 X₁ X₄+0.42 X₂ X₃+0.28 X₂ X₄-0.40 X₃ X₄-2 X₁-1.39 X₂-2.32 X₃-1.31 X₄	0.84
SOD	Y₃=1771.56-298.19 X₁-27.42 X₂-119.41 X₃-33.32 X₄+71.74 X₁ X₂-156.22 X₁ X₃+101.59 X₁ X₄-58.10 X₂ X₃-0.17 X₂ X₄-38.96 X₃ X₄-223.45 X₁-126.82 X₂-171.45 X₃-308.91 X₄	0.79
MDA	Y₄=1.21+0.72 X₁+0.83 X₂+1.11 X₃+0.96 X₄+0.36 X₁ X₂-0.25 X₁ X₃-0.03 X₁ X₄ +0.002 X₂ X₃+0.06 X₂ X₄+0.06 X₃ X₄+1.07 X₁+1.39 X₂+0.78 X₃+0.80 X₄	0.95
IAA	Y₅=15.63+0.88 X₁+0.50 X₂+0.58 X₃+0.24 X₄-0.15 X₁ X₂+0.005 X₁ X₃+0.04 X₁ X₄ -0.14 X₂ X₃+0.21 X₂ X₄+0.29 X₃ X₄-2.36 X₁-1.54 X₂-1.70 X₃-2 X₄	0.85

Y	目标函数回归方程 Objective function regression equation	R²
POD	Y₁=45936.29-1589.79 X₁-326.88 X₂+730.63 X₃+210.12 X₄-435.19 X₁ X₂-822.81 X₁ X₃-17.56 X₁ X₄-1351.44 X₂ X₃-770.94 X₂ X₄-829.81 X₃ X₄-3168.87 X₁-3620.12 X₂-2626.25 X₃-2896.00 X₄	0.93
CAT	Y₂=14.54-0.50 X₁+0.92 X₂+0.51 X₃+0.11 X₄+0.58 X₁ X₂-0.29 X₁ X₃-0.03 X₁ X₄+0.42 X₂ X₃+0.28 X₂ X₄-0.40 X₃ X₄-2 X₁-1.39 X₂-2.32 X₃-1.31 X₄	0.84
SOD	Y₃=1771.56-298.19 X₁-27.42 X₂-119.41 X₃-33.32 X₄+71.74 X₁ X₂-156.22 X₁ X₃+101.59 X₁ X₄-58.10 X₂ X₃-0.17 X₂ X₄-38.96 X₃ X₄-223.45 X₁-126.82 X₂-171.45 X₃-308.91 X₄	0.79
MDA	Y₄=1.21+0.72 X₁+0.83 X₂+1.11 X₃+0.96 X₄+0.36 X₁ X₂-0.25 X₁ X₃-0.03 X₁ X₄ +0.002 X₂ X₃+0.06 X₂ X₄+0.06 X₃ X₄+1.07 X₁+1.39 X₂+0.78 X₃+0.80 X₄	0.95
IAA	Y₅=15.63+0.88 X₁+0.50 X₂+0.58 X₃+0.24 X₄-0.15 X₁ X₂+0.005 X₁ X₃+0.04 X₁ X₄ -0.14 X₂ X₃+0.21 X₂ X₄+0.29 X₃ X₄-2.36 X₁-1.54 X₂-1.70 X₃-2 X₄	0.85

变异来源 Source of variation	F值
变异来源 Source of variation	POD(Y₁)	CAT(Y₂)	SOD(Y₃)	MDA(Y₄)	IAA(Y₅)
X₁	13.500^***	1.470	17.130^***	21.540^***	4.510^**
X₂	0.571	4.890^**	0.145	28.430^***	1.450
X₃	2.850	1.540	2.750	51.100^***	1.940
X₄	0.236	0.068	0.214	37.900^***	0.331
X₁X₂	0.674	1.290	0.661	3.660^*	0.092
X₁X₃	2.410	0.315	3.140^*	1.740	0.000
0.001	0.003	1.330	0.023	0.007
X₂X₃	6.500^**	0.678	0.434	0.000	0.078
X₂X₄	2.120	0.305	0.000	0.092	0.179
X₃X₄	2.450	0.631	0.195	0.103	0.318
X₁	63.910^***	27.680^***	11.460^***	55.930^***	38.770^***
X₂	83.410^***	13.370^***	3.690^*	95.190^***	16.500^***
X₃	43.900^***	37.400^***	6.750^**	30.030^***	20.010^***
X₄	53.380^***	11.860^***	21.910^***	31.090^***	27.710^***
总模型Model Overall Model	15.570^***	5.820^***	4.340^***	22.130^***	6.280^***
失拟Lf Misfitting Lf	1.140	0.392	0.179	2.050	0.909

基于二次通用旋转组合的植物生长调节剂最优组合

Research on the optimal combination of plant growth regulators based on quadratic universal rotation combination

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图/表 10

参考文献 35

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Metrics

处理 Treat- ments	二次通用旋转组合设计 Secondary universal rotation combination design
处理 Treat- ments	X₁(CSN)	X₂(FN-6)	X₃(DSK)	X₄(D2)
1	1	1	1	1
2	1	1	1	-1
3	1	1	-1	1
4	1	1	-1	-1
5	1	-1	1	1
6	1	-1	1	-1
7	1	-1	-1	1
8	1	-1	-1	-1
9	-1	1	1	1
10	-1	1	1	-1
11	-1	1	-1	1
12	-1	1	-1	-1
13	-1	-1	1	1
14	-1	-1	1	-1
15	-1	-1	-1	1
16	-1	-1	-1	-1
17	2	0	0	0
18	-2	0	0	0
19	0	2	0	0
20	0	-2	0	0
21	0	0	2	0
22	0	0	-2	0
23	0	0	0	2
24	0	0	0	-2
25	0	0	0	0
26	0	0	0	0
27	0	0	0	0
28	0	0	0	0
29	0	0	0	0
30	0	0	0	0
31	0	0	0	0

变异来源 Source of variation	POD (Y₁)	CAT (Y₂)	SOD (Y₃)	MDA (Y₄)	IAA (Y₅)
X₁	2.203	1.396	2.319	2.512	1.752
X₂	1.675	1.833	0.729	2.318	1.250
X₃	2.638	1.324	1.829	2.160	1.435
X₄	1.541	0.916	1.078	1.941	0.964

指示指标 Indicator indicators	熵权法 Entropy weighting method
指示指标 Indicator indicators	信息熵值e Information entropy value e	信息效用值d Information utility value d	权重 Weight (%)
POD	0.908	0.092	28.92
CAT	0.940	0.060	18.64
IAA	0.949	0.051	15.95
SOD	0.938	0.062	19.31
MDA	0.945	0.055	17.18

编码值 Encoding value	X₁		X₂		X₃		X₄
编码值 Encoding value	次数 Frequency	频率 Frequency	次数 Frequency	频率 Frequency	次数 Frequency	频率 Frequency	次数 Frequency	频率 Frequency
-2	0	0.000	0	0.000	0	0.000	0	0.000
-1	18	0.300	15	0.286	16	0.264	19	0.326
0	25	0.405	27	0.476	29	0.477	23	0.441
1	17	0.326	15	0.271	15	0.264	17	0.326
2	0	0.000	0	0.000	0	0.000	0	0.000
标准误 Standard error	0.102 4		0.098 7		0.096 4		0.102 5
95%置信区间 95% confidence interval	-0.201~0.201		-0.188~0.188		-0.188~0.188		-0.201~0.201
农艺措施 Agronomic measures	446.04~448.73		526.28~528.96		526.28~528.96		446.04~448.73

处理 Treatments	TOPSIS法 TOPSIS method		熵值法 Entropy method		因子分析法 Factor analysis method		秩和比综合评价法 Rank sum ratio comprehensive evaluation method
处理 Treatments	Ci	排序 Sort	Si	排序 Sort	εj	排序 Sort	RSR	排序 Sort
1	0.205 7	30	0.144 6	30	-1.063 1	30	0.172 1	30
2	0.248 7	27	0.208 0	29	-0.775 4	28	0.233 5	29
3	0.279 0	26	0.250 2	26	-0.591 5	22	0.274 4	26
4	0.298 1	25	0.288 0	22	-0.550 3	19	0.310 9	22
5	0.244 4	29	0.222 4	28	-0.870 5	29	0.247 5	28
6	0.299 4	24	0.275 1	25	-0.641 3	26	0.298 5	25
7	0.299 5	23	0.283 9	23	-0.608 3	25	0.307 0	23
8	0.324 9	20	0.276 4	24	-0.592 0	23	0.299 7	24
9	0.246 2	28	0.237 5	27	-0.721 3	27	0.262 1	27
10	0.417 2	10	0.416 3	9	0.039 4	8	0.435 1	9
11	0.354 8	15	0.350 6	13	-0.274 8	14	0.371 5	13
12	0.380 6	13	0.347 8	15	-0.365 5	16	0.368 8	15
13	0.377 8	14	0.374 2	12	-0.177 0	10	0.394 3	12
14	0.453 7	8	0.449 3	8	0.037 0	9	0.467 1	8
15	0.335 2	18	0.302 6	20	-0.596 5	24	0.325 1	20
16	0.382 7	12	0.348 9	14	-0.189 6	12	0.369 9	14
17	0.136 3	31	0.113 1	31	-1.340 0	31	0.141 7	31
18	0.431 0	9	0.413 7	10	-0.182 2	11	0.432 6	10
19	0.345 3	17	0.322 9	17	-0.283 9	15	0.344 7	17
20	0.317 8	21	0.288 7	21	-0.563 7	21	0.311 7	21
21	0.314 0	22	0.308 4	19	-0.540 2	18	0.330 7	19
22	0.417 0	11	0.392 6	11	-0.254 1	13	0.412 2	11
23	0.334 2	19	0.329 5	16	-0.399 6	17	0.351 2	16
24	0.345 6	16	0.311 2	18	-0.555 6	20	0.333 4	18
25	0.682 8	7	0.763 5	5	1.470 2	5	0.771 2	5
26	0.752 9	4	0.781 5	4	1.602 6	4	0.788 6	4
27	0.868 1	1	0.901 0	1	2.151 6	1	0.904 2	1
28	0.698 8	6	0.701 6	7	1.270 9	7	0.711 2	7
29	0.848 9	2	0.872 4	2	2.068 9	2	0.876 5	2
30	0.827 5	3	0.856 6	3	2.025 6	3	0.861 2	3
31	0.727 7	5	0.744 7	6	1.470 1	6	0.752 9	6

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