Crops ›› 2023, Vol. 39 ›› Issue (5): 212-218.doi: 10.16035/j.issn.1001-7283.2023.05.030

Previous Articles     Next Articles

Simulation Model of Relative Meteorological 1000-Grain Weight of Wheat of Luohe Based on Principal Component Regression

Huang Jie(), Ge Changbin(), Wang Jun, Cao Yanyan, Qiao Jiliang, Liao Pingʼan(), Song Danyang, Lu Wenying   

  1. Luohe Academy of Agricultural Sciences, Luohe 462300, Henan, China
  • Received:2022-04-24 Revised:2022-09-19 Online:2023-10-15 Published:2023-10-16

RichHTML

2

PDF (PC)

149

Abstract:

The correlation between meteorological factors and 1000-grain weight of wheat during different filling stages of wheat in Luohe was studied based on the meteorological data and 1000-grain weight data of three stations from 2010 to 2021, then an empirical model with key meteorological factors used to simulate relative meteorological 1000-grain weight (Yr) of wheat was established by using of the principal component regression model and stepwise regression model. The results showed that thermal factors such as average temperature and maximum temperature in rapid-increasing stage and maximum temperature in slight-increasing stage had the greatest impaction on the Yr of wheat in Luohe. The first three components of principal component analysis were “the maximum temperature factor in rapid-increasing stage and slight-increasing stage”, “the average temperature factor in rapid-increasing stage” and “the sunshine factor in rapid-increasing stage”, which could explain 89.44% of the Yr changes of wheat in Luohe. Compared with the stepwise regression model, the predicted and actual values of Yr and 1000-grain weight of wheat by using of the principal component regression model in three stations were better, especially in Wuligang. Therefore, the principal component regression model was more reasonable and accurate in estimating the Yr of Luohe. At present, it is an effective way to increase the 1000-grain weight of wheat in Luohe by breeding and screening high-temperature resistant varieties in late stage.

Key words: Luohe, Wheat, Relative meteorological 1000-grain weight, The principal component regression model

Table 1

Duration of different filling stages of wheat in Luohe during 2010-2021 d"

年份Year T1 T2 T3
2010-2011 13.84 15.49 6.66
2011-2012 16.21 16.46 7.33
2012-2013 16.32 13.17 8.52
2013-2014 14.23 13.86 12.91
2014-2015 12.68 14.63 8.68
2015-2016 9.66 15.49 11.84
2016-2017 18.25 15.49 4.25
2017-2018 12.01 12.54 13.44
2018-2019 13.46 14.63 7.91
2019-2020 12.89 16.46 11.64
2020-2021 15.96 15.49 9.55
平均Average 14.14 14.89 9.34

Table 2

Correlation factors of 1000-grain weight in Luohe during 2010-2021"

年份Year F (g) Yt (g) Yw (g) Yr (%)
2010-2011 42.05 41.36 0.69 1.67
2011-2012 41.60 41.46 0.14 0.35
2012-2013 43.20 42.15 1.05 2.48
2013-2014 44.19 42.97 1.22 2.84
2014-2015 44.78 43.69 1.09 2.49
2015-2016 44.20 43.90 0.30 0.69
2016-2017 47.74 45.43 2.31 5.08
2017-2018 46.73 45.95 0.78 1.69
2018-2019 46.71 46.26 0.45 0.98
2019-2020 46.88 46.51 0.37 0.81
2020-2021 47.98 47.10 0.88 1.88

Table 3

Correlation coefficients between the relative meteorological 1000-grain weight of wheat and meteorological factors of different filling stages"

灌浆阶段
Filling stage		 总降雨量
Precipitation		 相对湿度
Relative
humidity		 日照时数
Sunshine
hour		 平均气温
Average
temperature		 最高气温
The highest
temperature		 最低气温
The lowest
temperature		 温差
Diurnal		 风速
Wind
speed		 大型蒸发量
Large
evaporation
渐增期
Increasing stage		 0.5226 0.3797 0.2339 0.6113* 0.3601 0.1348 0.0999 0.0494 0.0599
快增期
Rapid-increasing stage		 -0.7628** 0.3007 0.7376** 0.7820** -0.7709** 0.1283 0.7600** 0.0493 0.6515*
缓增期
Slight-increasing stage		 -0.8204** -0.8250** 0.7658** 0.3804 -0.8368** 0.3940 0.4948 -0.6281* -0.6032*

Table 4

Diagnosis results of collinearity among key meteorological factors"

项目Item X1 X2 X3 X4 X5 X6 X7 X8 X9
膨胀系数Coefficient of expansion 30.3009 10.7406 23.1545 37.5181 67.7000 19.0305 19.5088 59.5709 134.0738

Table 5

Principal component analysis between the relative meteorological 1000-grain weight of wheat and key meteorological factors in Luohe city"

主成分
Principal
component		 特征值
Eigenvalue		 累计贡献率
Cumulative
contribution (%)		 X1 X2 X3 X4 X5 X6 X7 X8 X9
PC1 6.51 72.37 0.2971 0.3167 0.3537 -0.2933 -0.3532 -0.2979 0.3626 0.3647 -0.3498
PC2 0.81 81.33 -0.6458 0.3133 0.3351 -0.1693 0.3252 0.3519 0.2308 -0.0631 -0.2387
PC3 0.73 89.44 0.1399 0.3425 -0.0132 0.7006 -0.2529 0.4877 0.1768 0.1909 0.0506

Fig.1

The predicted and actual values of Yr of wheat of different models in different area during 2010-2021 Correlation coefficients of the principal component regression model of Wuligang, Wuyang county, Linying county are 0.7897, 0.6767 and 0.7305, respectively; Correlation coefficients of the stepwise regression model of Wuligang, Wuyang county, Linying county are 0.6658, 0.6123 and 0.6760, respectively"

Fig.2

The root mean square error of Yr of wheat under different models in different regions"

Fig.3

The predicted and actual values of the 1000-grain weight of wheat of different models in different areas during 2010-2021 Correlation coefficients of the principal component regression model of Wuligang, Wuyang county, Linying county are 0.9878, 0.9696 and 0.9818, respectively; Correlation coefficients of the stepwise regression model of Wuligang, Wuyang county, Linying county are 0.9791, 0.9584 and 0.9750, respectively"

Fig.4

The root mean square error of the 1000-grain weight of wheat under different models in different regions"

[1] 裴磊, 刘莉, 刘新月, 等. 气象因素对旱地小麦品种灌浆特性影响的研究. 北方农业学报, 2016, 44(6):67-72.
[2] 胡刚元. 温度对冬小麦灌浆时间和灌浆速度的影响. 安徽农业科学, 2012, 40(26):12836-12837,12908.
[3] 唐进, 林昌明, 吉剑, 等. 不同小麦品种籽粒灌浆速率试验研究. 安徽农学通报, 2014, 20(16):32-33,35.
[4] 崔金梅, 朱云集, 郭天财, 等. 冬小麦粒重形成与生育中期气象条件关系的研究. 麦类作物学报, 2000, 20(2):28-34.
[5] 高金成, 王润芳. 小麦粒重形成的气象条件研究. 中国农业气象, 2001, 22(3):44-49.
[6] 武建华, 刘常青, 房稳静, 等. 气象条件对两个不同属性冬小麦品种灌浆速度影响的研究. 安徽农业科学, 2008, 36(30):13074-13076.
[7] 刘孟宜, 田博宇, 王滢颖, 等. 基于主成分分析的不同小麦品种制作的韧性饼干品质评价. 食品研究与开发, 2021, 42(10):44-53.
[8] 张腊腊, 韩明虎, 胡浩斌, 等. 基于主成分分析的苹果品质综合评价. 江苏农业科学, 2020, 48(3):209-213.
[9] Patras A, Brunton N P, Downey G, et al. Application of principal component and hierarchical cluster analysis to classify fruits and vegetables commonly consumed in Ireland based on in vitro antioxidant activity. Journal of Food Composition and Analysis, 2011, 24(2):250-256.
doi: 10.1016/j.jfca.2010.09.012
[10] 吴晓丽, 汤永禄, 李朝苏, 等. 四川盆地小麦籽粒的灌浆特性. 作物学报, 2014, 40(2):337-345.
[11] 樊明, 杨滨齐, 李红霞, 等. 不同生态类型春小麦籽粒灌浆特性研究. 宁夏农林科技, 2014(11):1-2,25.
[12] 董中东, 张东志, 陈若礼, 等. 风干和烘干条件下不同小麦品种在灌浆过程中植株和籽粒干物质积累的动态变化. 河南农业大学学报, 2012, 46(4):364-369.
[13] 刘伟昌, 徐爱东, 付详建, 等. 小麦千粒重与气象因子关系研究//中国气象学会农业气象与生态学委员会. 全国农业气象与生态环境学术年会论文集, 2006:72-74.
[14] 李炳军, 王天慧. 冬小麦不同生长阶段气象因素对产量影响的双重量化分析. 麦类作物学报, 2018, 38(4):487-492.
[15] 董京铭, 刘瑞翔, 马晨晨, 等. 利用主成分回归方法预估连云港地区水稻气象产量. 江苏农业学报, 2021, 37(3):606-612.
[16] 周忠文, 昔小丽, 赵玮, 等. 气象条件对陇东塬区冬小麦灌浆速率的影响. 麦类作物学报, 2014, 34(6):837-841.
[17] 周国勤, 谢旭东, 姜明波, 等. 不同播期豫南稻茬麦产量及其与气象因子的通径分析. 河南农业科学, 2019, 48(9):23-29.
[18] 信志红, 郭建平, 谭凯炎, 等. 气象因子对半冬性小麦灌浆速度的影响效应研究. 气象, 2019, 45(12):1736-1746.
[19] 范磊, 胡海燕, 王来刚, 等. 基于农户数据的河南中东部地区气象因子对冬小麦产量的影响分析. 中国农业气象, 2012, 33 (1):109-113.
[20] 成林, 李彤霄, 刘荣花. 主要生育期气候变化对河南省冬小麦生长及产量的影响. 中国生态农业学报, 2017, 25(6):931-940.
[21] 逯玉兰, 李广, 韩俊英, 等. 降水量和气温变化对定西地区旱地春小麦产量的影响. 湖南农业大学学报(自然科学版), 2021, 47(3):268-273.
[22] 李刘龙, 李秀, 王小燕. 灌浆期遮光对不同小麦品种产量的影响. 河南农业科学, 2020, 49(5):31-39.
[23] 张玉春, 张敏, 刘希伟, 等. 花后持续弱光对冬小麦光合特性及产量的影响. 麦类作物学报, 2017, 37(8):1038-1046.
[24] 杨晓娟, 居辉, 王治世, 等. 花后高温和干旱对冬小麦光合、抗氧化特性及粒重的影响. 麦类作物学报, 2015, 35(7):958-963.
[25] 傅晓艺, 何明琦, 史占良, 等. 灌浆期高温胁迫对小麦灌浆特性和品质的影响. 麦类作物学报, 2015, 35(6):867-872.
[26] Dai H P, Zhang P P, Lu C, et al. Leaf senescence and reactive oxygen species metabolism of broomcorn millet (Panicum miliaceum L.) under drought condition. Australian Journal of Crop Science, 2011, 5(12):1655-1660.
[27] 胡吉帮, 王晨阳, 郭天财, 等. 灌浆期高温和干旱对小麦灌浆特性的影响. 河南农业大学学报, 2008, 42(6):597-601,608.
[28] Dias A S, Lidon F C. Evaluation of grain filling rate and duration in bread and durum wheat, under heat stress after anthesis. Journal of Agronomy and Crop Science, 2010, 195(2):137-147.
doi: 10.1111/jac.2009.195.issue-2
[29] 卢红芳, 石向军, 胡阳阳, 等. 灌浆期高温与干旱对小麦籽粒淀粉合成相关酶基因表达的影响. 麦类作物学报, 2020, 40 (5):517-525.
[30] 史华伟, 孙黛珍, 王曙光, 等. 小麦功能叶对籽粒灌浆影响的研究. 农学学报, 2017, 7(5):1-5.
doi: 10.11923/j.issn.2095-4050.cjas17010025
[31] 宋维富, 李集临, 周超, 等. 灌浆期不同阶段高温胁迫对春小麦籽粒生长的影响. 麦类作物学报, 2017, 37(9):1195-1200.
[1] Wang Yifan, Ren Ning, Dong Xiangyang, Zhao Yanan, Ye Youliang, Wang Yang, Huang Yufang. Effects of Controlled-Release and Ordinary Urea on Wheat Yield, Nitrogen Absorption and Economic Benefit [J]. Crops, 2023, 39(5): 117-123.
[2] Yang Mei, Yang Weijun, Gao Wencui, Jia Yonghong, Zhang Jinshan. Effects of Combined Application of Biochar and Nitrogen Fertilizer on Dry Matter Transport, Agronomic Characteristics and Yield of Winter Wheat in Irrigation Area [J]. Crops, 2023, 39(5): 138-144.
[3] Liu Shuhan, Chen Lei, Zhang Jianchao, Hu Gan, Sun Junyan, Liu Dongtao, Wang Junwei. Gene Differential Expression Analysis of TMS5 in the Fertility Conversion of Wheat BNS Sterile Line [J]. Crops, 2023, 39(5): 24-29.
[4] Zhang Dongxu, Hu Danzhu, Yan Jinlong, Feng Liyun, Wu Zhiyuan, Zhang Junling, Li Yanhua. Effects of Spraying Streptomyces on Yield and Photosynthetic Characteristics of Late-Sown Wheat under Different Crop Rotations [J]. Crops, 2023, 39(5): 255-263.
[5] Song Guicheng, Yu Guihong, Zhang Peng, Ma Hongxiang. Evaluation on Waterlogging Resistance of Different Wheat Varieties (Lines) at Jointing Stage [J]. Crops, 2023, 39(5): 30-36.
[6] Ge Changbin, Qin Suyan, Qiao Jiliang, Wang Jun, Qi Shuangli, Lu Wenying, Zhang Zhenyong. Comparative Analysis of Agronomic Traits, Quality and Disease Evolution of Approved Wheat Varieties in Southern Henan and Southern Huai River in Jiangsu from 2001 to 2021 [J]. Crops, 2023, 39(5): 49-58.
[7] Yang Cheng, Zhang Deqi, Du Simeng, Zhang Lijia, Jin Haiyang, Li Ying, Shao Yunhui, Wang Hanfang, Fang Baoting, Li Xiangdong, Liu Meijun. Effects of Dark and Strong Light Dehydration on the Photosystem Activity in Wheat Leaves in Vitro [J]. Crops, 2023, 39(5): 98-103.
[8] Zhang Mingwei, Ding Jinfeng, Zhu Xinkai, Guo Wenshan. Analysis of High-Yielding Planting Density and Nitrogen Application in Super-Late Sowing Wheat Following Rice [J]. Crops, 2023, 39(4): 126-135.
[9] Song Xiao, Zhang Keke, Yue Ke, Huang Chenchen, Huang Shaomin, Sun Jianguo, Guo Tengfei, Guo Doudou, Zhang Shuiqing, Pei Minnan. Differences of Enzyme Activities and Bacterial Communities in Rhizosphere Soil of Wheat Varieties with Different Nitrogen Efficiency [J]. Crops, 2023, 39(4): 188-194.
[10] Fu Xiaoyi, Wang Hongguang, Liu Zhilian, Li Dongxiao, He Mingqi, Li Ruiqi. Effects of Water Stress on Growth of Different Wheat Varieties at Seedling Stage and Selection of Drought Resistant Varieties [J]. Crops, 2023, 39(4): 224-229.
[11] Chen Yuanyuan, Li Guangsheng, Liu Yang, He Yuqi, Zhou Meiliang, Fang Zhengwu. Molecular Cloning and Functional Identification of Resistance Gene FtTIR of Tartary Buckwheat to Blight [J]. Crops, 2023, 39(4): 44-51.
[12] Liu Ying, Gu Yunyi, Zhang Weiyang, Yang Jianchang. Research Advances in the Effects of Water and Nitrogen and Their Interaction on the Grain Yield, Water and Nitrogen Use Efficiencies of Wheat [J]. Crops, 2023, 39(4): 7-15.
[13] Li Hongsheng, Li Shaoxiang, Yang Zhonghui, Yang Jiali, Liu Kun, Xiong Shian, Li Fuqian, Guo Hui, Yang Mujun. Comparison ofPhenotype and Marker Detection in Seed Purity of Thermo-Photo Sensitive Two-Line WheatHybrids [J]. Crops, 2023, 39(4): 71-76.
[14] Zhao Pengpeng, Li Luhua, Ren Mingjian, An Chang, Hong Dingli, Li Xin, Xu Ruhong. Bioinformatics and Expression Analysis of GzCIPK7-5B Gene in Wheat [J]. Crops, 2023, 39(4): 77-84.
[15] Li Haoran, Li Ruiqi, Li Yanming. Review of the Changes of Wheat Row Spacing Forms and the Affecting Factors in Haihe Plain [J]. Crops, 2023, 39(3): 12-19.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!