Scientia Agricultura Sinica ›› 2020, Vol. 53 ›› Issue (7): 1348-1358.doi: 10.3864/j.issn.0578-1752.2020.07.005

• TILLAGE & CULTIVATION·PHYSIOLOGY & BIOCHEMISTRY·AGRICULTURE INFORMATION TECHNOLOGY • Previous Articles     Next Articles

Effects of Climatic Factors Under Diverse Ecological Conditions on Foxtail Millet (Setaria italica) Yield in Shandong

YanBing YANG1,Ling QIN1,RunFeng WANG1,ErYing CHEN1,XiuBo YIN2,YuQin LIU3,SuMei ZHANG3,XinJun CONG4,GuoYu LI4,LeZheng WANG5,YanAn GUAN1   

  1. 1.Institute of Crop, Shandong Academy of Agricultural Sciences/Shandong Engineering Laboratory for Featured Crop, Jinan 250100
    2. Shandong General Station of Agricultural Technology Extension, Jinan 250100
    3.Linyi Academy of Agricultural Sciences, Linyi 276000, Shandong
    4.Taian Academy of Agricultural Sciences, Taian 271000, Shandong
    5.Dezhou Academy of Agricultural Sciences, Dezhou 253000, Shandong
  • Received:2019-06-19 Accepted:2019-12-23 Online:2020-04-01 Published:2020-04-14

Abstract: 【Objective】Grain yield is one of the most important indicators in evaluating foxtail millet productivity and is greatly affected by the fluctuation of climatic factors. The researches on the effects of climatic factors on grain yield and the varietal response of grain yield to different ecological conditions in Shandong can provide scientific basis for selecting, breeding and planting high-quality foxtail millet. 【Method】 Eight newly released foxtail millet cultivars selected from the summer-sown region of North China were planted at five locations in two consecutive years (2016 and 2017). Grain yields of these cultivars were measured. Analysis of Variance (ANOVA) was used to determine the significance of differences in grain yields by Duncan’s Multiple Range Test. And correlation analysis between grain yield and air temperature, rainfall, and sunshine duration were conducted by Pearson’s method. 【Result】 ANOVA showed that growing years, growing locations × growing years, and growing locations × cultivar genotypes had highly significant effects on the variations in grain yields (P<0.01). Similarly, cultivar genotypes, cultivar genotypes × growing years, and growing years × cultivar genotypes × growing years showed significant influence on grain yields (P<0.05). Growing locations, growing locations × growing years, growing locations × cultivar genotypes and cultivar genotypes had high contribution rates (50.05%, 19.76%, 12.32%, and 8.67%, respectively), whereas growing years, cultivar genotypes × growing years had low contribution rates (2.70% and 1.69%, respectively) to the variations in grain yields. In 2017, the average yield per unit area of eight foxtail millet cultivars was 4.55% higher than that in 2016, however, that was not consistent between growing locations. The annual outputs from Jinan, Linyi and Jining in 2017 were increased by 21.64%, 18.47% and 3.96%, respectively, while from Dezhou and Taian the annual outputs were decreased by 8.66% and 9.78%, respectively, compared with those in 2016. The average yields of eight cultivars from five locations across two years were 5 657.2 kg·hm-2 ranging from 5 267.8 kg·hm-2 to 5 926.0 kg·hm-2. The yield of Yugu18 had the lowest yield while Jigu20 had the highest yield. No significant difference in grain yields was observed between cultivars Jigu20, Jigu22, Jilügu1, Jinuogu2 and Zhonggu2, however, grain yields of these cultivars were significantly higher than Jigu19 and Yugu18. Correlation analysis showed that the grain yield was positively but not significantly correlated with the average temperature and maximum temperature at each time period (P>0.05). However, it was significantly positively correlated with the total average temperature of the whole growth period (P<0.05). On the other hand, grain yield was negatively correlated with the rainfall at seedling stage (middle and late June) (P>0.05), and the rainfall during the periods from pregnancy heading to flowering (from late July to middle August) (P>0.05). Furthermore, grain yield was positively correlated with sunshine duration in middle and late September (P>0.05). 【Conclusion】 Growing years, growing locations, cultivar genotypes, growing locations × growing years and growing locations × cultivar genotypes had significant effects on the yields of foxtail millet in Shandong. The fluctuation of ecological factors across different years and different locations, especially the air temperature and rainfall were the important factors affecting the yields. Higher average air temperature during the whole growth period was beneficial to increasing grain yield. Excessive rainfall at seedling and heading stages had negative effects on grain yields. The yield of testing cultivars was significantly different between years and between experimental sites. The cultivars, Jigu20, Jigu22, Jilügu1, Jinuogu2 and Zhonggu2 had good fertility and stability across ecological conditions.

Key words: foxtail millet, yield, ecological conditions, air temperature, rainfall, sunshine

Table 1

Multiple factors variance analysis of grain yield of foxtail millet and contribution rate of variable factors"

变异来源
Source
平方和
SS
自由度
df
均方
Mean square
F
P
贡献率
Contribution rate (%)
区组Block4388491.520219424.6
年份Year3805125.913805125.927.150.00012.70
地点Location70602182.5417650545.62.530.194950.05
品种Cultivar12231908.471747415.55.130.02338.67
地点×年份Location×Year27862874.446965718.649.710.000119.76
品种×年份Cultivar×Year2382977.37340425.32.430.02231.69
地点×品种Location×Cultivar17371868.628620423.94.430.007812.32
地点×品种×年份Location×Cultivar×Year6793459.728242623.61.730.02044.81
误差Error19618704.8140140133.6
总计Total165057593.1239

Table 2

Differences of grains yield of foxtail millet at different locations in 2016-2017"

地点
Location
籽粒产量Grain yield (kg·hm-2)2017比2016增产率
Yield-increase rate (%)
20162017均值Mean
济南市Jinan5045.3c6137.3b5591.3ab21.64
德州市Dezhou5877.7b5368.5c5623.1ab-8.66
临沂市Linyi5024.7c5952.8b5488.8ab18.47
济宁市Jining6499.6a6757.3a6628.5a3.96
泰安市Taian5209.3c4699.9d4954.6b-9.78
均值Mean5531.35783.25657.24.55

Table 3

Differences and CVs of grain yields of different cultivars"

品种
Cultivar
20162017品种均值
Mean (kg·hm-2)
变异度
CV (%)
产量Yield (kg·hm-2)变异度 CV (%)产量 Yield (kg·hm-2)变异度CV(%)
济谷19 Jigu195117.7d7.745529.9bc9.255323.8bc7.02
济谷20 Jigu205914.8a2.335937.1a3.755926.0a2.14
济谷21 Jigu215463.9bc4.775742.3ab3.745603.1ab3.83
济糯谷2号Jinuogu25471.7bc6.996070.4a4.285771.0a4.82
中谷2号Zhonggu25630.0b5.495835.2ab8.145732.6a6.74
济绿谷1号Jilügu15741.8ab5.365872.4a5.095807.1a3.15
济谷22 Jigu225627.5b2.836025.6a9.545826.5a5.94
豫谷18 Yugu185283.3cd9.145252.3c6.135267.8c7.15
均值Mean5531.35783.25657.2

Table 4

Differences of grain yield of cultivars at different locations in 2016-2017"

年份
Year
品种
Cultivar
籽粒产量Grain yield (kg·hm-2)
济南市Jinan德州市Dezhou临沂市Linyi济宁市Jining泰安市Taian
2016济谷19 Jigu194956.9±57.2a4789.1±334.4b4691.9±168.9bc6111.4±156.5b5039.1±141.9b
济谷20 Jigu205285.5±198.5a6317.0±190.9a5260.0±88.1ab6967.0±346.5a5744.7±219.7a
济谷21 Jigu215153.3±24.3a5755.8±218.3ab4648.8±94.8bc6275.3±168.8b5486.4±74.6ab
济糯谷2号Jinuogu 25122.5±87.9a6358.6±219.0a4793.3±115.5bc5944.8±282.8b5139.1±63.5b
中谷2号Zhonggu 24834.9±162.3a5939.2±383.8a5641.9±324.8a6536.4±255.7ab5197.5±210.4b
济绿谷1号Jilügu 14995.2±125.2a5728.1±618.9ab5515.6±303.5a7030.9±132.5a5439.2±185.1ab
济谷22 Jigu224873.7±363.0a6117.0±122.8a5126.6±241ab6622.6±59.4ab5397.5±51.0ab
豫谷18 Yugu185140.4±87.0a6017±118.3a4519.7±108.7c6508.7±70.9ab4230.8±75.2c
均值 Mean5045.35877.75024.76499.65209.3
2017济谷19 Jigu196297.9±292.9ab4824.7±180.9a5033.6±346.4c7092.0±289.2a4401.3±152.1bc
济谷20 Jigu206518.1±136.7a5692.5±277.9a5918.1±28.9b6633.7±64.7a4923.2±102.1abc
济谷21 Jigu216315±152.6ab5069.2±38.8a5933.6±77.0b6539.2±161.3a4854.4±102.6abc
济糯谷2号Jinuogu 26234.7±109.6ab5833.6±410.6a6518.1±279.1a6700.3±91.8a5065.4±210.2ab
中谷2号Zhonggu 25845.7±208.8ab5253.6±467.7a6784.8±163.6a6911.5±407.1a4380.4±133bc
济绿谷1号Jilügu 16478.2±64.0a5606.9±405.1a5922.5±154.4b7036.5±173.8a4317.9±128bc
济谷22 Jigu225694.5±291.6b5633.6±337.9a6544.8±40.1a6572.5±258.8a5682.6±232.7a
豫谷18 Yugu185714.4±245.2b5033.6±115.7a4966.9±134.7c6572.6±180.8a3974.1±371.1c
均值 Mean6137.35368.55952.86757.34699.9

Table 5

Correlation coefficient between grain yields and meteorological factors in different periods"

月份
Month
旬段
Ten-day interval
气温
Air temperature
最高气温
Maximum temperature
降水量
Rainfall
日照时数
Sunshine hour
6月June上旬Early0.2280.3340.582-0.034
中旬Middle0.3240.467-0.2590.203
下旬Late0.4430.193-0.097-0.106
7月July上旬Early0.3780.1390.5480.158
中旬Middle0.3120.1920.3790.170
下旬Late0.1200.066-0.454-0.004
8月August上旬Early0.3700.281-0.1640.085
中旬Middle0.1260.324-0.3650.042
下旬Late0.3970.1900.169-0.164
9月September上旬Early0.0110.1440.1670.001
中旬Middle0.6100.2990.1690.222
下旬Late0.3420.1750.0450.166
平均/总Mean/Sum0.710*0.1420.170
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