Scientia Agricultura Sinica ›› 2024, Vol. 57 ›› Issue (20): 3945-3956.doi: 10.3864/j.issn.0578-1752.2024.20.001

• CROP GENETICS & BREEDING·GERMPLASM RESOURCES·MOLECULAR GENETICS • Previous Articles     Next Articles

Yield Gain Analysis of Wheat Varieties in Sichuan from 2000 to 2020

LUO JiangTao(), ZHENG JianMin, DENG QingYan, LIU PeiXun, PU ZongJun()   

  1. Crop Research Institute of Sichuan Academic of Agricultural Sciences (Sichuan Provincial Germplasm Resources Center)/ Environment-friendly Crop Germplasm Innovation and Genetic Improvement Key Laboratory of Sichuan Province/Key Laboratory of Wheat Biology and Genetic Improvement on Southwestern China, Ministry of Agriculture and Rural Areas, Chengdu 610066
  • Received:2024-04-02 Accepted:2024-04-22 Online:2024-10-16 Published:2024-10-24

Abstract:

【Objective】Analyzing the yield and yield related traits of Sichuan wheat varieties from 2000 to 2020, providing reference for genetic improvement of yield in Sichuan wheat varieties. 【Method】From 2019 to 2022, a community trial design was used to measure the yield and related traits of 145 wheat varieties in Sichuan Province since 2001 to 2016, as well as 60 high-yield wheat varieties (Varieties with top yields in regional trials in Sichuan Province over the years) since 2000 to 2020. This data was used to analyze the trend of yield and yield related trait changes in Sichuan wheat cultivars cultivated from 2000 to 2020. 【Result】145 Sichuan wheat varieties from 2001 to 2016 have an average annual genetic gain of 37.20 kg·hm-2 or 0.66% in yield. Grain number per spike and effective spike number per unit area showed an increasing trend, while thousand grain weight and plant height showed a decreasing trend. Correlation analysis showed that effective spike number per unit area was positively correlated with yield. Path analysis showed that the continuous increase of effective spike number per unit area (annual increase 0.42×104/hm2 or 0.13%) was the main factor for the increase of yield potential of high-yielding varieties. The average annual yield genetic gain of 60 high-yield wheat varieties from 2000 to 2020 was 61.10 kg·hm-2 or 0.89%, the effective spike number per unit area showed an increasing trend, the plant height showed a decreasing trend, and the grain number per spike and thousand grain weight had almost no change. Correlation analysis shows that there was a significant positive correlation between yield and the number of effective ears per unit area. Path analysis showed that the continuous increase in effective spike number per unit area (with an average annual increase of 1.80×104/hm2 or 0.51%) was also a major factor in improving the yield potential of 60 high-yield wheat varieties in Sichuan from 2000 to 2020. 【Conclusion】The improvement and breeding of wheat yield heritage in Sichuan Province has made some progress, especially the improvement effect of high yield breeding is remarkable, and the yield level of wheat varieties in Sichuan Province is gradually increasing. The continuous increase in effective ears per unit area was the main factor for improving the yield potential of Sichuan wheat varieties. High grain number per spike and thousand grain weight are important foundations for high yield in Sichuan wheat, but their genetic improvement is in a bottleneck period. Increasing the effective spike number per unit area is the key to furtherly improve the yield of wheat in Sichuan.

Key words: Sichuan wheat, breed, genetic gain, yield, yield related trait

Table 1

Variance analysis of yield and related traits of 145 varieties"

性状
Trait
年份
Year
品种
Varieties
重复
Repeat
年份×品种
Year×varieties
误差
Error
产量Yield 12766817.7** 241570326.9** 47606124.5** 102646779.1** 229846648.8
千粒重Thousand grain weight 276.65** 19576.32** 105.02** 3104.97** 5405.56
单位面积有效穗数Effective spike number per unit area 2526374.65** 1932820.5** 70906.31** 915112.12** 941236.15
穗粒数Grains per spike 623.4** 30898.62** 1081.06** 10600.97** 21101.79
株高Plant height 1277.33** 36620.10** 351.52** 6064.48** 8134.95

Fig. 1

Yield variation trend of 145 varieties A: Jingyang district in 2019; B: Guanghan in 2020; C: The average of two-year; D: Regional test of Sichuan province"

Table 2

Progress in improvement of yield potential of 145 varieties"

试验地点
Test site
试验年份
Test year
平均产量
Average yield (kg·hm-2)
年均遗传增益
Annual genetic gain (kg·hm-2, %)
德阳市旌阳区 Jingyang District, Deyang 2019 5782.54 +32.40 (+0.55)
广汉市 Guanghan 2020 5541.44 +41.05 (+0.74)
平均 Average 5658.10 +37.20 (+0.66)
四川省区试 Regional test of Sichuan province 5424.83 +33.81 (+0.63)

Fig. 2

Variation trend of yield-related traits of 145 varieties A: Effective spike number per unit area; B: Grains per spike; C: Thousand grain weight; D: Plant height"

Table 3

Progress of genetic improvement of yield-related traits in 145 varieties"

试验地点
Test site
试验年份
Test year
单位面积有效穗数
Effective spike number per unit area
穗粒数
Grains per spike
千粒重
Thousand grain weight
株高
Plant height
均值
Average (104/hm2)
年均增益
Average annual gain (104/hm2, %)
均值
Average
年均增益
Average annual gain
均值
Average
(g)
年均增益
Average annual gain (g, %)
均值
Average
(cm)
年均增益
Average annual gain (cm, %)
德阳市旌阳区
Jingyang District, Deyang
2019 411.19 +0.47
(+0.16)
53.32 +0.30
(+0.56)
46.24 -0.03
(-0.09)
86.09 -0.39
(-0.45)
广汉市
Guanghan
2020 299.73 +0.56
(+0.19)
54.98 +0.27
(+0.51)
47.44 -0.05
(-0.12)
88.47 -0.27
(-0.31)
平均
Average
353.06 +0.42
(+0.13)
54.14 +0.28
(+0.52)
46.81 -0.05
(-0.13)
87.26 -0.34
(-0.36)

Table 4

Correlation analysis of yield and yield related traits in 145 varieties"

性状
Trait
产量
Yield
单位面积有效穗数
Effective spike number per unit area
千粒重
Thousand grain weight
穗粒数
Grains per spike
株高
Plant height
产量Yield 1.00 0.27** 0.25** 0.10 0.01
单位面积有效穗数Effective spike number per unit area 1.00 0.04 -0.39** -0.02
千粒重Thousand grain weight 1.00 -0.26* 0.43**
穗粒数Grains per spike 1.00 -0.06
株高Plant height 1.00

Table 5

Path analysis of yield and yield related traits in 145 varieties"

性状
Trait
直接通径系数
Direct path coefficient
间接通径系数 Indirect path coefficient
X1 X2 X3 X4
X1 0.4220 -0.1625 -0.0186 -0.0063
X2 0.3630 -0.1398 -0.0937 0.0200
X3 0.4210 -0.0185 -0.1086 0.1802
X4 -0.1410 -0.0021 -0.0078 0.0603

Table 6

Variance analysis of yield and related traits of 60 high-yielding varieties"

类型 Type 品种 Varieties 重复 Repeat 误差 Error
产量 Yield 104132739.70** 1008852.90* 68175557.40
千粒重 Thousand grain weight 2517.46** 658.25** 802.20
单位面积有效穗数 Effective spike number per unit area 236280.09** 14812.10* 283546.69
穗粒数 Grains per spike 11121.49** 1203.86** 16.99
株高 Plant height 3792.20** 223.63* 2896.37

Fig. 3

Yield gain trend of 60 high-yield wheat varieties A: Xindu District in 2022; B: Regional test of Sichuan province"

Table 7

Progress of genetic improvement of yield-related traits in 60 high-yielding varieties"

试验地点
Test site
试验年份
Test year
单位面积穗数
Effective spike number per unit area
穗粒数
<BOLD>G</BOLD>rains per spike
千粒重
<BOLD>T</BOLD>housand grain weight
株高
<BOLD>P</BOLD>lant height
均值
Average (104/hm2)
年均增益
Average annual gain (104/hm2, %)
均值
Average
年均增益Average annual gain (%) 均值
Average
(g)
年均增益
Average annual gain (g, %)
均值
Average
(cm)
年均增益
Average annual gain (cm, %)
成都市新都区
Xindu District, Chengdu
2022 336.15 +1.80
(+0.51)
63.42 +0.0001
(+0.001)
52.97 -0.001
(-0.02)
84.57 -0.08 (-0.10)

Fig. 4

Variation trend of yield-related traits of 60 high-yielding varieties A: Effective spike number per unit area; B: Grains per spike; C: Thousand grain weight; D: Plant height"

Table 8

Correlation analysis of yield and yield-related traits of 60 high-yielding varieties"

类型
Type
产量
Yield
单位面积穗数
Effective spike number per unit area
千粒重
Thousand grain weight
穗粒数
Grains per spike
株高
Plant height
产量Yield 1.00 0.27* 0.19 0.14 0.27*
单位面积有效穗数Effective spike number per unit area 1.00 0.05 -0.18 -0.17
千粒重Thousand grain weight 1.00 -0.39** 0.13
穗粒数Grains per spike 1.00 0.19
株高Plant height 1.00

Table 9

Path analysis of yield and yield related traits in 60 high-yielding varieties"

类型
Type
直接通径系数
Direct path coefficient
间接通径系数 Indirect path coefficient
X1 X2 X3 X4
X1 0.3470 -0.0611 0.0156 -0.0583
X2 0.2460 -0.0433 -0.0959 0.0477
X3 0.2400 0.0108 -0.0936 0.0310
X4 0.2560 -0.0430 0.0497 0.0330
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