干旱胁迫下春玉米冠层吐丝动态及籽粒数模拟研究

doi:10.3864/j.issn.0578-1752.2022.18.005

摘要/Abstract

摘要：

【目的】为实现干旱胁迫下玉米冠层吐丝动态的模拟,建立开花—吐丝间隔（anthesis-silking interval,ASI）和吐丝百分率与单位面积籽粒数的关系,改善干旱胁迫条件下玉米籽粒数的模拟效果。【方法】本研究基于锦州农业气象试验站干旱胁迫控制试验,测定了不同水分处理下玉米开花前后植株平均生长速率（PGR）、玉米冠层逐日吐丝百分率动态、ASI、开花后果穗生物量累积和株籽粒数等指标,利用上述数据确定了玉米冠层吐丝动态模型参数;进行了模拟吐丝百分率对植株生长速率平均值（PGR_AVE）和标准差（PGR_SD）两个输入参数的敏感性分析;基于果穗生物量累积过程,考虑干旱胁迫条件下冠层内植株个体间PGR的差异,开展开花前后不同干旱胁迫条件下冠层吐丝动态过程模拟;建立ASI与株结实率（株籽粒数占株最大潜在籽粒数的百分比）的定量关系;基于冠层吐丝动态模型模拟的开花后吐丝植株百分率、单株最大潜在籽粒数和株结实率,构建了基于冠层吐丝动态的籽粒数模型,进行了干旱胁迫下的籽粒数模拟与检验。【结果】冠层吐丝动态模型对PGR_AVE和PGR_SD的敏感性分析结果显示,与PGR_SD变化相比,PGR_AVE变化对吐丝百分率影响更大,PGR_AVE越大,PGR_SD越小,植株达到50%吐丝的时间越短。玉米冠层吐丝动态模型可以较准确地模拟开花后逐日吐丝百分率,花期干旱胁迫下观测值与模拟值的决定系数R²为0.88—0.98,均方根误差RMSE为4%—12%,归一化均方根误差NRMSE为8%—27%;耦合冠层吐丝动态模拟结果,构建了基于冠层吐丝动态的籽粒数模型,该模型可以较准确地模拟干旱胁迫下玉米单位面积籽粒数,观测值与模拟值的R²为0.85,RMSE为185粒/m²,NRMSE为10%。【结论】通过引入冠层吐丝动态模型,构建基于冠层吐丝动态的籽粒数模型,实现了干旱胁迫下玉米关键物候期（吐丝时间、开花—吐丝间隔和吐丝百分率）的模拟和籽粒数模拟,为实现干旱胁迫下基于冠层吐丝动态的产量模拟奠定基础。

关键词: 果穗生物量, 开花—吐丝间隔, 吐丝百分率, 籽粒数, 植株生长速率

Abstract:

【Objective】In order to improve simulation accuracy of maize kernel number under drought stress, the study simulated canopy silking dynamic of maize under drought stress and developed the relationships among anthesis-silking interval (ASI), canopy silking percentage and maize kernel number per unit area. 【Method】Firstly, this study measured the average plant growth rate (PGR) of maize around anthesis, daily canopy silking percentage of maize, ASI, the biomass accumulation of ear after anthesis, and the kernel number per plant under different treatments of soil water content based on drought stress controlling experiment at Jinzhou Agrometeorological Experimental Station. Secondly, the parameters of maize canopy silking dynamic model were determined with experimental data. Sensitivity analysis was conducted to investigate the impact of changes in average plan growth rate (PGR_AVE) and standard deviation (PGR_SD) on simulated canopy silking percentage. Thirdly, based on the ear biomass accumulation dynamic, the canopy silking dynamic was simulated under different drought stresses before and after anthesis by considering the differences in PGR among individual plants in the canopy. The quantitative relationship between ASI and kernel setting rate (the percentage of kernel number per plant to the maximum potential kernel number per plant) was developed based on experimental data. Finally, based on simulated canopy silking percentage after anthesis, maximum potential kernel number per plant, and the kernel setting rate by canopy silking dynamic model, the maize kernel number model was developed and validated under drought stress. 【Result】Sensitivity analysis of change in canopy silking percentage in response to changes in PGR_AVE and PGR_SD showed that PGR_AVE had a greater impact on canopy silking percentage than PGR_SD. The larger the PGR_AVE and the smaller the PGR_SD, the shorter the time for the canopy reaching silking percentage of 50%. The maize canopy silking dynamic model could accurately simulate daily silking percentage after anthesis under drought stress, and the coefficient of determination (R²), the root mean square error (RMSE), and the normalized mean square error (NRMSE) between simulated and observed canopy silking percentage ranged from 0.88 to 0.98, from 4% to 12%, and from 8% to 27%, respectively. Maize kernel number model could accurately simulate the kernel number of maize per unit area under drought stress, and R², RMSE, and NRMSE between simulated and observed kernel number was 0.85, 185 kernel/m², and 10%, respectively. 【Conclusion】By introducing the canopy silking dynamic model, the study could simulate the key phenology (silking time, anthesis-silking interval, and silking percentage) and kernel number per unit area under drought stress. The result was an important foundation for the simulation of maize yield based on canopy silking dynamic under drought stress.

Key words: ear biomass, anthesis-silking interval, silking percentage, kernel number, plant growth rate

王梦琪, 米娜, 王靖, 张玉书, 纪瑞鹏, 陈妮娜, 刘霞霞, 韩颖, 李王轶朴, 张佳莹. 干旱胁迫下春玉米冠层吐丝动态及籽粒数模拟研究[J]. 中国农业科学, 2022, 55(18): 3530-3542.

MengQi WANG, Na MI, Jing WANG, YuShu ZHANG, RuiPeng JI, NiNa CHEN, XiaXia LIU, Ying HAN, WangYiPu LI, JiaYing ZHANG. Simulation of Canopy Silking Dynamic and Kernel Number of Spring Maize Under Drought Stress[J]. Scientia Agricultura Sinica, 2022, 55(18): 3530-3542.

0
/ / 推荐

导出引用管理器 EndNote|Reference Manager|ProCite|BibTeX|RefWorks

链接本文: https://www.chinaagrisci.com/CN/10.3864/j.issn.0578-1752.2022.18.005

https://www.chinaagrisci.com/CN/Y2022/V55/I18/3530

图/表 9

图1

图2

图3

表1

表2

图4

图5

图6

图7

参考文献 42

[1]	中华人民共和国国家统计局. 中国统计年鉴 (2019). 北京: 中国统计出版社, 2019.
	National Bureau of Statistics of the People’s Republic of China. China Statistical Yearbook (2019). Beijing: China Statistics Press, 2019. (in Chinese)
[2]	LIU Z J, YANG X G, HUBBARD K G, LIN X M. Maize potential yields and yield gaps in the changing climate of Northeast China. Global Change Biology, 2012, 18(11): 3441-3454. doi: 10.1111/j.1365-2486.2012.02774.x
[3]	张淑杰, 张玉书, 陈鹏狮, 梁淑娥, 刘东明, 米娜, 纪瑞鹏, 王阳, 王笑影, 李广霞. 基于改进作物水分亏缺指数的玉米干旱致灾过程识别与动态定量评估. 生态学杂志, 2020, 39(12): 4241-4252.
	ZHANG S J, ZHANG Y S, CHEN P S, LIANG S E, LIU D M, MI N, JI R P, WANG Y, WANG X Y, LI G X. Identification and dynamic quantitative evaluation of maize drought-induced disaster process based on an improved crop water deficit index. Chinese Journal of Ecology, 2020, 39(12): 4241-4252. (in Chinese)
[4]	孙凤华, 吴志坚, 杨素英. 东北地区近50年来极端降水和干燥事件时空演变特征. 生态学杂志, 2006, 25(7): 779-784.
	SUN F H, WU Z J, YANG S Y. Temporal and spatial variations of extreme precipitation and dryness events in Northeast China in last 50 years. Chinese Journal of Ecology, 2006, 25(7): 779-784. (in Chinese)
[5]	杨晓晨, 明博, 陶洪斌, 王璞. 中国东北春玉米区干旱时空分布特征及其对产量的影响. 中国生态农业学报, 2015, 23(6): 758-767.
	YANG X C, MING B, TAO H B, WANG P. Spatial distribution characteristics and impact on spring maize yield of drought in Northeast China. Chinese Journal of Eco-Agriculture, 2015, 23(6): 758-767. (in Chinese)
[6]	刘志娟, 杨晓光, 王文峰, 赵俊芳, 张海林, 陈阜. 全球气候变暖对中国种植制度可能影响Ⅳ. 未来气候变暖对东北三省春玉米种植北界的可能影响. 中国农业科学, 2010, 43(11): 2280-2291.
	LIU Z J, YANG X G, WANG W F, ZHAO J F, ZHANG H L, CHEN F. The possible effects of global warming on cropping systems in China IV. The possible impact of future climatic warming on the northern limits of spring maize in three provinces of Northeast China. Scientia Agricultura Sinica, 2010, 43(11): 2280-2291. (in Chinese)
[7]	赵秀兰. 近50年中国东北地区气候变化对农业的影响. 东北农业大学学报, 2010, 41(9): 144-149.
	ZHAO X L. Influence of climate change on agriculture in Northeast China in recent 50 years. Journal of Northeast Agricultural University, 2010, 41(9): 144-149. (in Chinese)
[8]	初征, 郭建平, 赵俊芳. 东北地区未来气候变化对农业气候资源的影响. 地理学报, 2017, 72(7): 1248-1260. doi: 10.11821/dlxb201707010
	CHU Z, GUO J P, ZHAO J F. Impacts of future climate change on agroclimatic resources in Northeast China. Journal of Geographical Sciences, 2017, 72(7): 1248-1260. (in Chinese) doi: 10.11821/dlxb201707010
[9]	魏湜. 玉米生态基础. 北京: 中国农业出版社, 2010.
	WEI S. Fundamental of Maize Ecology. Beijing: China Agriculture Press, 2010. (in Chinese)
[10]	张国平, 周伟军. 作物栽培学. 杭州: 浙江大学出版社, 2001.
	ZHANG G P, ZHOU W J. Crop Production. Hangzhou: Zhejiang University Press, 2001. (in Chinese)
[11]	OTEGUI M E. Prolificacy and grain yield components in modern argentinian maize hybrids. Maydica, 1995, 40(4): 371-376.
[12]	CHAPMAN S C, EDMEADES G O. Selection improves drought tolerance in tropical maize populations: Ⅱ. Direct and correlated responses among secondary traits. Crop Science, 1999, 39(5): 1315-1324. doi: 10.2135/cropsci1999.3951315x
[13]	MI N, CAI F, ZHANG Y S, JI R P, ZHANG S J, WANG Y. Differential responses of maize yield to drought at vegetative and reproductive stages. Plant Soil and Environment, 2018, 64(6): 260-267. doi: 10.17221/141/2018-PSE
[14]	BORRÁS L, WESTGATE M E, ASTINI J P, ECHARTE L. Coupling time to silking with plant growth rate in maize. Field Crops Research, 2007, 102(1): 73-85. doi: 10.1016/j.fcr.2007.02.003
[15]	EDMEADES G O, DAYNARD T B. The development of plant-to- plant variability in maize at different planting densities. Canadian Journal of Plant Science, 1979, 59(3): 561-576. doi: 10.4141/cjps79-095
[16]	HALL A J, VILELLA F, TRAPANI N, CHIMENTI C. The effects of water stress and genotype on the dynamics of pollen-shedding and silking in maize. Field Crops Research, 1982, 5(4): 349-363. doi: 10.1016/0378-4290(82)90036-3
[17]	BORRÁS L, VITANTONIO-MAZZINI L N. Maize reproductive development and kernel set under limited plant growth environments. Journal of Experimental Botany, 2018, 69(13): 3235-3243. doi: 10.1093/jxb/erx452
[18]	BECHOUX N, BERNIER G, LEJEUNE P. Environmental effects on the early stages of tassel morphogenesis in maize (Zea mays L.). Plant Cell and Environment, 2000, 23(1): 91-98. doi: 10.1046/j.1365-3040.2000.00515.x
[19]	宋凤斌, 李晓明, 朱乃芬. 玉米高产群体适宜株行距的研究. 吉林农业大学学报, 1992, 14(4): 39-45.
	SONG F B, LI X M, ZHU N F. Study on suitable plant row spacing for high-yield maize population. Journal of Jilin Agricultural University, 1992, 14(4): 39-45. (in Chinese)
[20]	MOSS G I, DOWNEY L A. Influence of drought stress on female gametophyte development in corn (Zea mays L.) and subsequent grain yield. Crop Science, 1971, 11(3): 368-372. doi: 10.2135/cropsci1971.0011183X001100030017x
[21]	HALL A J, LEMCOFF J H, TRAPANI N. Water stress before and during flowering in maize and its effects on yield, its components, and their determinants. Maydica, 1981, 26(1): 19-38.
[22]	BOLAÑOS J, EDMEADES G O. The importance of the anthesis- silking interval in breeding for drought tolerance in tropical maize. Field Crops Research, 1996, 48(1): 65-80. doi: 10.1016/0378-4290(96)00036-6
[23]	李叶蓓, 陶洪斌, 王若男, 张萍, 吴春江, 雷鸣, 张巽, 王璞. 干旱对玉米穗发育及产量的影响. 中国生态农业学报, 2015, 23(4): 383-391.
	LI Y B, TAO H B, WANG R N, ZHANG P, WU C J, LEI M, ZHANG X, WANG P. Effect of drought on ear development and yield of maize. Chinese Journal of Eco-Agriculture, 2015, 23(4): 383-391. (in Chinese)
[24]	TURC O, BOUTEILLÉ M, FUAD-HASSAN A, WELCKER C, TARDIEU F. The growth of vegetative and reproductive structures (leaves and silks) respond similarly to hydraulic cues in maize. New Phytologist, 2016, 212(2): 377-388. doi: 10.1111/nph.14053
[25]	李红伟, 江艳平, 贾双杰, 赵国强, 王泳超, 杨青华, 刘天学, 李潮海, 邵瑞鑫. 干旱胁迫影响玉米穗发育的研究进展. 玉米科学, 2020, 28(2): 90-95.
	LI H W, JIANG Y P, JIA S J, ZHAO G Q, WANG Y C, YANG Q H, LIU T X, LI C H, SHAO R X. Research progress on drought stress affecting ear and tassel development of maize. Journal of Maize Sciences, 2020, 28(2): 90-95. (in Chinese)
[26]	方缘, 张玉书, 米娜, 孙沛, 刘刚, 王当, 贾越, 冯艾琳, 刘斌. 干旱胁迫及补水对玉米生长发育和产量的影响. 玉米科学, 2018, 26(1): 89-97.
	FANG Y, ZHANG Y S, MI N, SUN P, LIU G, WANG D, JIA Y, FENG A L, LIU B. Effect of drought stress and water-recharge to maize growth and yield. Journal of Maize Sciences, 2018, 26(1): 89-97. (in Chinese)
[27]	米娜, 张玉书, 蔡福, 纪瑞鹏, 方缘, 张淑杰, 陈妮娜. 干旱胁迫对玉米物候及产量组成的影响及模拟研究. 中国生态农业学报(中英文), 2019, 27(12): 1779-1788.
	MI N, ZHANG Y S, CAI F, JI R P, FANG Y, ZHANG S J, CHEN N N. Effect of drought stress on maize phenology and yield components and its simulation. Chinese Journal of Eco-Agriculture, 2019, 27(12): 1779-1788. (in Chinese)
[28]	ÇAKIR R. Effect of water stress at different development stages on vegetative and reproductive growth of corn. Field Crops Research, 2004, 89(1): 1-16. doi: 10.1016/j.fcr.2004.01.005
[29]	米娜, 蔡福, 张玉书, 纪瑞鹏, 于文颖, 张淑杰, 方缘. 不同生育期持续干旱对玉米的影响及其与减产率的定量关系. 应用生态学报, 2017, 28(5): 1563-1570. doi: 10.13287/j.1001-9332.201705.025
	MI N, CAI F, ZHANG Y S, JI R P, YU W Y, ZHANG S J, FANG Y. Effects of continuous drought during different growth stages on maize and its quantitative relationship with yield loss. Chinese Journal of Applied Ecology, 2017, 28(5): 1563-1570. (in Chinese) doi: 10.13287/j.1001-9332.201705.025
[30]	JONES J W, HOOGENBOOM G, PORTER C H, BOOTE K J, BATCHELOR W D, HUNT L A, WILKENS P W, SINGH U, GIJSMAN A J, RITCHIE J T. The DSSAT cropping system model. European Journal of Agronomy, 2003, 18(3/4): 235-265. doi: 10.1016/S1161-0301(02)00107-7
[31]	LIZASO J I, WESTGATE M E, BATCHELOR W D, FONSECA A. Predicting potential kernel set in maize from simple flowering characteristics. Crop Science, 2003, 43(3): 892-903. doi: 10.2135/cropsci2003.8920
[32]	ANDRADE F H, CALVINO P, CIRILO A, BARBIERI P. Yield responses to narrow rows depend on increased radiation interception. Agronomy Journal, 2002, 94(5): 975-980. doi: 10.2134/agronj2002.9750
[33]	TOLLENAAR M, DWYER L M, STEWART D W. Ear and kernel formation in maize hybrids representing three decades of grain yield improvement in Ontario. Crop Science, 1992, 32(2): 432-438. doi: 10.2135/cropsci1992.0011183X003200020030x
[34]	MOSS D N, STINSON H T. Differential response of corn hybrids to shade. Crop Science, 1961, 1: 416-418. doi: 10.2135/cropsci1961.0011183X000100060009x
[35]	BORRÁS L, ASTINI J P, WESTIGATE M E, SEVERINI A D. Modeling anthesis to silking in maize using a plant biomass framework. Crop Science, 2009, 49(3): 937-948. doi: 10.2135/cropsci2008.05.0286
[36]	OTEGUI M E. Kernel set and flower synchrony within the ear of maize: Ⅱ. Plant population effects. Crop Science, 1997, 37(2): 448-455. doi: 10.2135/cropsci1997.0011183X003700020024x
[37]	VEGA C R C, ANDRADE F H, SADRAS V O, UHART S A, VALENTINUZ O R. Seed number as a function of growth. A comparative study in soybean, sunflower, and maize. Crop Science, 2001, 41(3): 748-754. doi: 10.2135/cropsci2001.413748x
[38]	EDMEADES G O, BOLAÑOS J, HERNÁNDEZ M, BELLO S. Causes for silk delay in a lowland tropical maize population. Crop Science, 1993, 33(5): 1029-1035. doi: 10.2135/cropsci1993.0011183X003300050031x
[39]	ANDRADE F H, VEGA C, UHART S, CIRILO A, CANTARERO M, VALENTINUZ O, FISCHER. Kernel number determination in maize. Crop Science, 1999, 39(2): 453-459. doi: 10.2135/cropsci1999.0011183X0039000200026x
[40]	LIZASO J I, RUIZ-RAMOS M, RODRIGUEZ L, GABALDON- LEAL C, OLIVEIRA J A, LORITE I J, RODRÍGUEZ A, MADDONNI G A, OTEGUI M E. Modeling the response of maize phenology, kernel set, and yield components to heat stress and heat shock with CSM-IXIM. Field Crops Research, 2017, 214: 239-252. doi: 10.1016/j.fcr.2017.09.019
[41]	BORRÁS L, SLAFER G A, OTEGUI M E. Seed dry weight response to source-sink manipulations in wheat, maize and soybean: A quantitative reappraisal. Field Crops Research, 2004, 86(2/3): 131-146. doi: 10.1016/j.fcr.2003.08.002
[42]	FONSECA A E, LIZASO J I, WESTGATE M E, GRASS L, DORNBOS D L. Simulating potential kernel production in maize hybrid seed fields. Crop Science, 2004, 44(5): 1696-1709. doi: 10.2135/cropsci2004.1696

年份 Year	处理 Treatment	日期Date			平均值 Mean (g/ear)
年份 Year	处理 Treatment	07-21 (g/ear)	07-24 (g/ear)	07-29 (g/ear)	平均值 Mean (g/ear)
2020	T1	1.1	1.6	2.9	1.9
	T2	1.6	2.2	2.3	2.0
	CK	2.0	1.5	1.9	1.8
2021	T2'	1.6	1.0	2.3	1.6
2021	CK'	1.8	1.2	2.2	1.7