Crops ›› 2021, Vol. 37 ›› Issue (1): 60-67.doi: 10.16035/j.issn.1001-7283.2021.01.009

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Discussion on the Application in the Regional Experiment of Maize Varieties by Entropy DTOPSIS Mode and Grey Situation Decision Methods

Qi Jianshuang1(), Xia Laikun1(), Huang Bao1, Li Chunying2, Ma Zhiyan1, Ding Yong1, Gu Limin1, Zhang Jun1, Zhang Fengqi1, Mu Xinyuan1, Tang Baojun1, Zhao Faxin1, Zhang Lanxun1   

  1. 1Cereal Crops Research Institute, Henan Academy of Agricultural Sciences/Henan Provincial Key Laboratory of Maize Biology, Zhengzhou 450002, Henan, China
    2Wheat Research Institute, Henan Academy of Agricultural Sciences, Zhengzhou 450002, Henan, China
  • Received:2020-04-02 Revised:2020-12-23 Online:2021-02-15 Published:2021-02-23
  • Contact: Xia Laikun E-mail:qijianshuang@126.com;xialaikun@126.com

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Abstract:

Improved varieties are the important carriers of agricultural science and technology. Regional trails of crop varieties is the main way to identify the high yield, stable yield and adaptability of new varieties. In this paper, DTOPSIS method and grey situation decision method based on entropy weight were applied to maize regional experiment for the first time. Eighteen varieties (including the CK) of Henan Agricultural Science Complex in 2018 were comprehensively evaluated. The results showed that the ranking order of Ci value and rij value of the two methods were almost the same. Among the 18 varieties, only five varieties had slight difference in ranking order, and the most different variety had a difference of two in ranking, while the other four only had a difference of one rank. However, the evaluated results of two methods were far from the order of yield ranking. It was also found that the two evaluation methods have obvious shortcomings. Therefore, it was suggested that the comprehensive evaluation method of maize varieties in regional trials in current should be mainly based on yield, supplemented by DTOPSIS method and grey situation decision-making method based on entropy. The comprehensive evaluation of various methods could greatly reduce the risk of the approved varieties in the actual planting and production process.

Key words: Maize regional test, Entropy, DTOPSIS method, Grey situation decision

Table 1

Mean value of indexes of 18 traits of tested maize varieties (matrix A)"

编号
No.		 品种
Variety		 产量
Yield
(kg/hm2)		 穗长
Ear length
(cm)		 穗行数
Ear
rows		 单株产量
Yield per
plant (g)		 百粒重
100-grain
weight (g)		 生育期
Growth
period (d)		 株高
Plant height
(m)		 穗位高
Ear height
(m)		 倒伏率
Lodging
rate (%)		 倒折率
Pour the discount
rate (%)		 空秆率
Empty stalk
rate (%)		 含水量
Kernel
moisture (%)		 秃尖
Bald tip
length (cm)		 总叶片数
Total number
of leaves
1 漯玉16-1 9 916.5 16.9 15.1 149.4 34.4 102 2.50 1.00 1.6 1.0 0.8 28.3 0.5 20.5
2 郑单1868 9 834.0 18.2 15.5 149.6 32.3 101 2.70 1.00 0.8 0.6 1.2 26.3 1.7 19.5
3 安玉706 9 718.5 18.6 14.6 144.2 34.2 102 2.51 0.93 0.7 0.3 0.5 29.1 1.0 19.5
4 浩玉188 9 633.0 18.3 14.6 144.8 33.8 103 2.60 1.00 2.2 1.6 1.2 30.1 0.3 20.5
5 浚单56 9 612.0 18.1 16.5 145.6 29.7 101 2.60 0.90 2.1 0.6 1.1 26.6 1.0 18.5
6 敦玉107 9 546.0 16.4 16.5 141.7 29.1 101 2.40 0.90 1.3 0.3 0.7 26.5 0.9 20.0
7 浚单996 9 331.5 15.9 13.7 141.5 35.1 103 2.60 1.00 2.2 0.4 1.5 29.6 0.2 19.0
8 郑单2186 9 304.5 18.0 15.4 145.9 33.1 102 2.50 1.00 2.2 0.5 1.4 28.3 1.0 19.5
9 郑单958 9 201.0 16.9 15.1 144.1 32.7 103 2.50 1.00 2.6 1.4 1.5 28.9 0.5 21.0
10 敦玉278 9 133.5 16.1 16.1 141.0 33.3 102 2.70 1.00 1.8 0.5 1.8 25.9 0.9 19.0
11 新单92 9 106.5 16.3 16.7 141.7 32.1 103 2.90 1.10 2.0 0.4 3.0 27.5 1.0 21.0
12 新单78 9 079.5 16.2 17.1 140.9 33.5 103 3.00 1.10 0.3 0.3 1.6 28.0 1.4 20.5
13 技丰698 9 075.0 17.4 15.1 139.4 30.8 101 3.00 1.00 9.4 0.9 1.6 26.0 1.3 20.0
14 郑单2185 8 997.0 17.5 14.9 143.9 33.1 103 2.50 1.20 7.7 2.9 2.3 29.1 0.8 19.5
15 技丰853 8 869.5 17.3 16.4 138.4 33.1 102 2.80 1.00 14.6 1.1 1.7 27.2 0.7 19.0
16 郑单5166 8 821.5 20.5 15.0 149.2 34.0 102 3.00 1.00 2.4 0.4 2.1 25.9 1.3 18.5
17 技丰616 8 734.5 17.2 14.8 137.0 32.5 101 2.40 0.80 0.8 0.2 1.5 27.0 1.1 20.0
18 陕单656 8 614.5 17.3 15.6 134.0 29.9 101 2.60 0.90 11.4 2.6 2.1 24.1 0.6 18.5

Table 2

Dimensionless matrix Z and grey situation decision method matrix (L)"

编号
No.		 产量
Yield		 穗长
Ear
length		 穗行数
Ear
rows		 单株产量
Yield per
plant		 百粒重
100-grain
weight		 生育期
Growth
period		 株高
Plant
height		 穗位高
Ear
height		 倒伏率
Lodging
rate		 倒折率
Pour the
discount rate		 空秆率
Empty stalk
rate		 含水量
Kernel
moisture		 秃尖
Bald tip
length		 总叶片数
Total number
of leaves
1 1.0000 0.8244 0.8830 0.9987 0.9475 1.0000 0.9445 0.9906 0.1875 0.2000 0.6250 0.8516 0.4000 0.9593
2 0.9917 0.8878 0.9064 1.0000 0.9910 0.9903 0.9837 0.9906 0.3750 0.3333 0.4167 0.9163 0.1176 0.9916
3 0.9800 0.9073 0.8538 0.9639 0.9531 1.0000 0.9479 0.9424 0.4286 0.6667 1.0000 0.8282 0.2000 0.9916
4 0.9714 0.8927 0.8538 0.9679 0.9643 0.9903 0.9793 0.9906 0.1364 0.1250 0.4167 0.8007 0.6667 0.9593
5 0.9693 0.8829 0.9649 0.9733 0.9184 0.9903 0.9793 0.9162 0.1429 0.3333 0.4545 0.9060 0.2000 0.9440
6 0.9626 0.8000 0.9649 0.9472 0.9032 0.9903 0.9121 0.9162 0.2308 0.6667 0.7143 0.9094 0.2222 0.9833
7 0.9410 0.7756 0.8012 0.9459 0.9286 0.9903 0.9793 0.9906 0.1364 0.5000 0.3333 0.8142 1.0000 0.9672
8 0.9383 0.8780 0.9006 0.9753 0.9847 1.0000 0.9445 0.9906 0.1364 0.4000 0.3571 0.8516 0.2000 0.9916
9 0.9278 0.8244 0.8830 0.9632 0.9968 0.9903 0.9445 0.9906 0.1154 0.1429 0.3333 0.8339 0.4000 0.9365
10 0.9210 0.7854 0.9415 0.9425 0.9788 1.0000 0.9837 0.9906 0.1667 0.4000 0.2778 0.9305 0.2222 0.9672
11 0.9183 0.7951 0.9766 0.9472 0.9851 0.9903 0.9159 0.9005 0.1500 0.5000 0.1667 0.8764 0.2000 0.9365
12 0.9156 0.7902 1.0000 0.9418 0.9730 0.9903 0.8854 0.9005 1.0000 0.6667 0.3125 0.8607 0.1429 0.9593
13 0.9151 0.8488 0.8830 0.9318 0.9478 0.9903 0.8854 0.9906 0.0319 0.2222 0.3125 0.9269 0.1538 0.9833
14 0.9073 0.8537 0.8713 0.9619 0.9847 0.9903 0.9445 0.8255 0.0390 0.0690 0.2174 0.8282 0.2500 0.9916
15 0.8944 0.8439 0.9591 0.9251 0.9847 1.0000 0.9486 0.9906 0.0205 0.1818 0.2941 0.8860 0.2857 0.9672
16 0.8896 1.0000 0.8772 0.9973 0.9587 1.0000 0.8854 0.9906 0.1250 0.5000 0.2381 0.9305 0.1538 0.9440
17 0.8808 0.8390 0.8655 0.9158 0.9971 0.9903 0.9121 0.8387 0.3750 1.0000 0.3333 0.8926 0.1818 0.9833
18 0.8687 0.8439 0.9123 0.8957 0.9236 0.9903 0.9793 0.9162 0.0263 0.0769 0.2381 1.0000 0.3333 0.9440

Table 3

Entropy weights, weights and coefficient of variation of different indicators"

项目
Item		 产量
Yield		 穗长
Ear
length		 穗行数
Ear
rows		 单株产量
Yield per
plant		 百粒重
100-grain
weight		 生育期
Growth
period		 株高
Plant
height		 穗位高
Ear
height		 倒伏率
Lodging
rate		 倒折率
Pour the
discount rate		 空秆率
Empty stalk
rate		 含水量
Kernel
moisture		 秃尖
Bald tip
length		 总叶片数
Total number
of leaves
熵权Entropy weight 0.9997 0.9993 0.9995 0.9999 0.9996 1.0000 0.9991 0.9987 0.8346 0.8945 0.9742 0.9995 0.9665 0.9997
权重Weight 0.0008 0.0020 0.0016 0.0004 0.0013 0.0000 0.0028 0.0039 0.4933 0.3146 0.0769 0.0016 0.0998 0.0009
CV (%) 4.1800 6.4700 5.7800 2.9900 5.2100 0.8200 7.6500 8.9400 113.0200 88.4000 39.4500 5.7400 43.4500 4.1800

Table 4

Decision matrix R"

编号
No.		 产量
Yield		 穗长
Ear
length		 穗行数
Ear
rows		 单株产量
Yield per
plant		 百粒重
100-grain
weight		 生育期
Growth
period		 株高
Plant
height		 穗位高
Ear
height		 倒伏率
Lodging
rate		 倒折率
Pour the
discount rate		 空秆率
Empty stalk
rate		 含水量
Kernel
moisture		 秃尖
Bald tip
length		 总叶片数
Total number
of leaves
1 0.0008 0.0016 0.0014 0.0004 0.0013 0.0000 0.0027 0.0039 0.0925 0.0629 0.0481 0.0014 0.0399 0.0008
2 0.0008 0.0018 0.0015 0.0004 0.0013 0.0000 0.0028 0.0039 0.1850 0.1049 0.0321 0.0015 0.0117 0.0008
3 0.0008 0.0018 0.0014 0.0004 0.0013 0.0000 0.0027 0.0037 0.2114 0.2097 0.0769 0.0013 0.0200 0.0008
4 0.0008 0.0018 0.0014 0.0004 0.0013 0.0000 0.0028 0.0039 0.0673 0.0393 0.0321 0.0013 0.0665 0.0008
5 0.0008 0.0018 0.0016 0.0004 0.0012 0.0000 0.0028 0.0036 0.0705 0.1049 0.0350 0.0015 0.0200 0.0008
6 0.0008 0.0016 0.0016 0.0004 0.0012 0.0000 0.0026 0.0036 0.1138 0.2097 0.0549 0.0015 0.0222 0.0008
7 0.0008 0.0016 0.0013 0.0004 0.0012 0.0000 0.0028 0.0039 0.0673 0.1573 0.0256 0.0013 0.0998 0.0008
8 0.0008 0.0018 0.0015 0.0004 0.0013 0.0000 0.0027 0.0039 0.0673 0.1258 0.0275 0.0014 0.0200 0.0008
9 0.0008 0.0016 0.0014 0.0004 0.0013 0.0000 0.0027 0.0039 0.0569 0.0449 0.0256 0.0013 0.0399 0.0008
10 0.0008 0.0016 0.0015 0.0004 0.0013 0.0000 0.0028 0.0039 0.0822 0.1258 0.0214 0.0015 0.0222 0.0008
11 0.0008 0.0016 0.0016 0.0004 0.0013 0.0000 0.0026 0.0035 0.0740 0.1573 0.0128 0.0014 0.0200 0.0008
12 0.0008 0.0016 0.0016 0.0004 0.0013 0.0000 0.0025 0.0035 0.4933 0.2097 0.0240 0.0014 0.0143 0.0008
13 0.0008 0.0017 0.0014 0.0004 0.0013 0.0000 0.0025 0.0039 0.0157 0.0699 0.0240 0.0015 0.0153 0.0008
14 0.0008 0.0017 0.0014 0.0004 0.0013 0.0000 0.0027 0.0032 0.0192 0.0217 0.0167 0.0013 0.0249 0.0008
15 0.0008 0.0017 0.0016 0.0004 0.0013 0.0000 0.0027 0.0039 0.0101 0.0572 0.0226 0.0014 0.0285 0.0008
16 0.0008 0.0020 0.0014 0.0004 0.0013 0.0000 0.0025 0.0039 0.0617 0.1573 0.0183 0.0015 0.0153 0.0008
17 0.0007 0.0017 0.0014 0.0004 0.0013 0.0000 0.0026 0.0033 0.1850 0.3146 0.0256 0.0014 0.0181 0.0008
18 0.0007 0.0017 0.0015 0.0004 0.0012 0.0000 0.0028 0.0036 0.0130 0.0242 0.0183 0.0016 0.0333 0.0008

Table 5

Results by DTOPSIS method"

代号
No.		 品种
Variety		 S+ S- Ci Ci值排序
Ci value ranking		 产量
Yield (kg/hm2)		 产量排序
Yield ranking
1 漯玉16-1 0.4779 0.1026 0.1767 12 9 916.5 1
2 郑单1868 0.3857 0.1946 0.3353 5 9 834.0 2
3 安玉706 0.3112 0.2829 0.4762 3 9 718.5 3
4 浩玉188 0.5103 0.0833 0.1404 13 9 633.0 4
5 浚单56 0.4805 0.1054 0.1799 11 9 612.0 5
6 敦玉107 0.4018 0.2191 0.3528 4 9 546.0 6
7 浚单996 0.4570 0.1719 0.2734 6 9 331.5 7
8 郑单2186 0.4753 0.1200 0.2015 10 9 304.5 8
9 郑单958 0.5190 0.0607 0.1047 14 9 201.0 9
10 敦玉278 0.4623 0.1274 0.2160 9 9 133.5 10
11 新单92 0.4594 0.1501 0.2463 7 9 106.5 11
12 新单78 0.1453 0.5186 0.7812 1 9 079.5 12
13 技丰698 0.5457 0.0500 0.0839 15 9 075.0 13
14 郑单2185 0.5655 0.0165 0.0283 18 8 997.0 14
15 技丰853 0.5547 0.0405 0.0680 16 8 869.5 15
16 郑单5166 0.4707 0.1452 0.2358 8 8 821.5 16
17 技丰616 0.3230 0.3414 0.5138 2 8 734.5 17
18 陕单656 0.5682 0.0225 0.0382 17 8 614.5 18

Table 6

Results by grey situation decision method"

编号
No.		 品种
Variety		 rij rij值排序
rij value
ranking		 产量
Yield
(kg/hm2)		 产量排序
Yield
ranking
1 漯玉16-1 0.2578 10 9 916.5 1
2 郑单1868 0.3485 6 9 834.0 2
3 安玉706 0.5323 3 9 718.5 3
4 浩玉188 0.2196 13 9 633.0 4
5 浚单56 0.2447 12 9 612.0 5
6 敦玉107 0.4147 4 9 546.0 6
7 浚单996 0.3641 5 9 331.5 7
8 郑单2186 0.2550 11 9 304.5 8
9 郑单958 0.1817 14 9 201.0 9
10 敦玉278 0.2662 9 9 133.5 10
11 新单92 0.2781 7 9 106.5 11
12 新单78 0.7552 1 9 079.5 12
13 技丰698 0.1393 15 9 075.0 13
14 郑单2185 0.0963 18 8 997.0 14
15 技丰853 0.1330 16 8 869.5 15
16 郑单5166 0.2672 8 8 821.5 16
17 技丰616 0.5571 2 8 734.5 17
18 陕单656 0.1031 17 8 614.5 18
[1] 张群远, 孔繁玲, 廖琴, 等. 作物品种区域试验的评价体系及评价方法. 农业系统科学与综合研究, 2000(2):81-86.
[2] 孙世贤. 中国农作物品种管理与推广. 北京: 中国农业科技出版社, 2003.
[3] 陈洪梅, 杨峻芸, 谭静. 玉米区域试验精确度分析及品种的灰色综合评判. 西南农业学报, 2004,17(增刊):228-232.
[4] 金石桥, 许乃银. GGE双标图在中国农作物品种试验中应用的必要性探讨. 种子, 2012,31(12):89-92.
[5] 何代元, 胡宁, 马兆锦, 等. AMMI模型在玉米区域试验中的应用. 玉米科学, 2009,17(4):144-147,152.
[6] 杨锦忠, 郝建平, 姚宏亮, 等. 基于AMMI模型的玉米区域试验地点鉴别力的重演性研究. 玉米科学, 2011,19(4):145-148.
[7] 朱正梅, 楼肖成, 吕学高, 等. 浙江省2011年玉米区试产量的AMMI模型分析. 浙江农业科学, 2013(6):645-647.
[8] 苏义臣, 苏桂华, 金明华, 等. GGE双标图在玉米区域试验中的应用. 吉林农业科学, 2015,40(3):4-7.
[9] 梁黔云, 李清超, 吴瑞, 等. GGE双标图在玉米品种区域实验中的应用. 中国农学通报, 2014,30(6):224-228.
[10] 杨禹伟, 陈华, 姜波, 等. 一种加工番茄品质的多性状评价方法. 中国农业大学学报, 2017,22(3):131-137.
[11] 昝凯, 周青, 张志民, 等. 灰色关联度和DTOPSIS法综合分析河南区域试验中大豆新品种(系)的农艺性状表现. 大豆科学, 2018,37(5):664-671.
[12] 余文远, 李霖超. 运用灰色局势决策法综合评价鲜食大豆新品系. 湖南农业科学, 2015(10):26-28.
[13] 吴志会, 白玉龙, 董玉武, 等. DTOPSIS法综合评价冀中北冬小麦新品种的初步研究. 麦类作物学报, 2005(6):108-111.
doi: 10.7606/j.issn.1009-1041.2005.06.257
[14] 宋洁, 李婉琳, 郭华春. DTOPSIS法评价44份CIP引进马铃薯新品系的适应性. 中国马铃薯, 2017,31(4):193-200.
[15] 夏来坤, 齐建双, 谷利敏, 等. 基于熵权的DTOPSIS法和灰色局势决策法在宜机收玉米品种综合评价中的应用. 南方农业学报, 2019,50(9):1953-1959.
[16] 邵美红, 程楚, 程思明, 等. 运用DTOPSIS法对鲜食甜玉米新品种在浙西北地区适应性的综合评价. 江西农业学报, 2017,29(6):25-28.
[17] 郭永忠, 杨彩霞, 邹军, 等. 灰色局势决策在玉米品种综合评价中的应用. 西北农业学报, 2007,16(4):92-95.
[18] 李文砚, 韦优, 孔方南, 等. DTOPSIS法在草莓品种综合评价中的应用研究. 植物生理学报, 2018,54(5):925-930.
[19] 吴梦烟, 杨侃, 刘朗, 等. 基于灰色局势决策和组合赋权法的再生水评价. 水资源与水工程学报, 2018,29(3):111-117.
[20] 李彦平, 李淑君, 吴娟霞, 等. DTOPSIS 法和灰色关联度法在新引烤烟新品种综合评价中的应用比较. 中国烟草学报, 2012,18(4):35-40.
[21] 杨昆, 吴才文, 覃伟, 等. DTOPSIS 法和灰色关联度法在甘蔗新品种综合评价中的应用比较. 西南农业学报, 2015,28(4):1542-1547.
[22] 马辉, 戴路, 刘燕. 灰色关联度法和DTOPSIS法在机采棉品种综合评价中的应用. 中国棉花, 2015,42(6):27-29.
doi: 1000-632X（2015）06-0027-03
[23] 杨禹伟, 陈华, 姜波, 等. 一种加工番茄品质的多性状评价方法. 中国农业大学学报, 2017,22(3):131-137.
[24] 吴玥, 李威, 马德志, 等. 基于熵值赋权的DTOPSIS法对不同玉米品种综合评价研究. 玉米科学, 2019,27(4):32-41.
[25] 经建芳, 唐兴中, 蓝明新, 等. 基于熵权—灰色局势决策法的金属切削液配方优选研究. 工具技术, 2015,49(3):12-16.
[26] 宋秀丽, 吴玥, 杨锡朗, 等. 基于熵值赋权的DTOPSIS法与灰色关联度分析在玉米品种综合评价中的比较. 玉米科学, 2020,28(2):41-46.
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[7] Hongqu Liao,Hongli Chen,Wensi Fan,Yu Chen,Qiujing Han,Jianjun Yu,Ming Ma. Fractal Characteristics of Soil Particles and Their Effects on Physicochemical Properties of Tobacco Leaves in Main Tobacco Growing Areas in Henan[J]. Crops, 2018, 34(1): 118 -125 .
[8] Ruiqi Ma,Zhen Qi,Xuhong Chang,Demei Wang,Zhiqiang Tao,Yushuang Yang,Jinfeng Feng,Min Sun,Guangcai Zhao. Regulation Effects of Growth Regulators on Plant Characters, Yield and Quality of Winter Wheat[J]. Crops, 2018, 34(1): 133 -140 .
[9] Jiani Zhu,Huiping Dai,Shuhe Wei,Genliang Jia,Dejing Chen,Jinjin Pei,Qing Zhang,Long Qiang. Effects of Applying Zn on the Growth and Zn Accumulation in Soybean at Flowering Stage[J]. Crops, 2018, 34(1): 152 -155 .
[10] Tianle Ma,Jianxin Zhang. Effects of Different Multiple Cropping Methods on Dry Matter Accumulation, Distribution and Yield of Summer Soybean[J]. Crops, 2018, 34(1): 156 -159 .