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Acta Agronomica Sinica ›› 2024, Vol. 50 ›› Issue (2): 464-477.doi: 10.3724/SP.J.1006.2024.31018

• TILLAGE & CULTIVATION·PHYSIOLOGY & BIOCHEMISTRY • Previous Articles     Next Articles

Sensitivity analysis and optimization of spring wheat grain growth parameters under APSIM model with the increase of temperature

ZHANG Kang1(), NIE Zhi-Gang1,*(), WANG Jun1, LI Guang2   

  1. 1College of Information Science and Technology, Gansu Agricultural University, Lanzhou 730070, Gansu, China
    2College of Forestry, Gansu Agricultural University, Lanzhou 730070, Gansu, China
  • Received:2023-03-12 Accepted:2023-09-13 Online:2024-02-12 Published:2023-10-11
  • Contact: *E-mail: niezg@gsau.edu.cn
  • Supported by:
    National Natural Science Foundation of China(32160416);Industrial Support Program of Gansu Provincial Education Department(2021CYZC-15);Industrial Support Program of Gansu Provincial Education Department(2022CYZC-41);“Innovation Star” Project of Gansu Province Outstanding Postgraduate Students(2022CXZXS-026)

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Abstract:

In order to effectively identify spring wheat yield sensitivity parameters in grain growth parameters based on APSIM model, the local model parameters were quickly and accurately estimated. Using the meteorological data of Anjiagou Village, Fengxiang Town, Anding District, Dingxi City, Gansu Province from 1971 to 2018 and the field test data of dryland spring wheat from 2000 to 2018, the sensitivity analysis of 32 model parameters under five temperature gradients (0℃, 0.5℃, 1.0℃, 1.5℃, and 2℃) was conducted by EFAST method. The particle swarm optimization algorithm is used to optimize and verify the parameters sensitive at all temperatures. The results showed that, under different temperature gradients, there were nine grain growth model parameters that had the greatest influence on the yield of spring wheat in dry land, which were extinction coefficient, the number of grains per gram of stem, the number of grains per ear, the maximum grain mass per plant, the accumulated temperature from filling to maturity, the accumulated temperature from emergence to jointing, plant height, the maximum specific leaf area, and water stress slope of photosynthetic leaf aging. The sensitivity intensity of spring wheat yield was significantly different, among which extinction coefficient and the number of seeds per gram of stem were the most influential parameters in spring wheat yield, and the sensitivity sequence of other parameters was different under different temperatures. Particle swarm optimization algorithm was used to optimize the nine parameters. Compared with before optimization, the optimized spring wheat yield, root mean square error of grain dry matter, normalized root mean square error and model validity index were significantly improved. After parameter optimization, the optimized spring wheat yield, root mean square error of grain dry matter and model validity index were significantly improved. The mean square error of yield at maturity stage decreased by 13.50-5.99 kg hm-2, 183.17-69.44 kg hm-2, and 141.69-48.51 kg hm-2, respectively. The normalized root-mean-square error decreases by 4.94%-2.19%, 10.92%-4.65%, 8.39%-2.87%, and the average model validity index increases by 0.894-0.979, 0.893-0.981, and 0.898-0.988, respectively. The optimized parameters can effectively improve the prediction accuracy of the model. This study provides a scientific basis for the local application of APSIM model and the calibration of model parameters.

Key words: parameter, sensitivity analysis, APSIM model, particle swarm optimization, spring wheat

Table 1

Soil properties of the experiment site used for specifying APSIM simulation"

土层
Soil layer
(cm)		 田间最大持水量
Drained upper limit
(mm mm-1)		 小麦有效水分下限Wheat low limit
(mm mm-1)		 容重
Bulk density
(g cm-3)		 铵态氮
NH4-N
(mg kg-1)		 硝态氮
NO3-N
(mg kg-1)
>0-5 0.27 0.09 1.29 6.30 19.10
>5-10 0.27 0.09 1.23 5.20 15.20
>10-30 0.27 0.09 1.32 5.10 23.10
>30-50 0.27 0.09 1.20 4.90 16.60
>50-80 0.26 0.09 1.14 4.60 16.80
>80-110 0.27 0.10 1.14 4.80 18.20
>110-140 0.27 0.11 1.13 4.80 16.40
>140-170 0.27 0.13 1.12 5.80 13.70
>170-200 0.27 0.15 1.11 4.10 15.40

Fig. 1

Structural framework of model"

Fig. 2

Flow chart of sensitivity analysis"

Fig. 3

Flow chart of APSIM model parameter calibration using particle swarm optimization algorithm"

Table 2

Upper and lower limits and distribution of parameters and model output"

参数名称
Parameter		 下限值
Lower bound		 上限值
Upper bound
每克茎籽粒数量Grains per gram stem (GGS) (grain g-1) 10 40
灌浆期籽粒日潜在灌浆速率Potential grain filling rate (PGFR) (g grain-1 d-1) 0.001 0.004
开花到灌浆期籽粒日潜在灌浆速率Potential grain growth rate (PGR) (g grain-1 d-1) 0.0005 0.0015
日潜在籽粒氮积累速率Potential grain n filling rate (PGNFR) (g grain-1 d-1) 0.000,027,5 0.000,082,5
籽粒氮日积累速率下限Minimum grain n filling rate (MFR) (g grain-1 d-1) 0.000,007,5 0.000,022,5
谷粒氮限制灌浆因子n fact grain (NFG) (-) 0 1
最小叶氮浓度y n conc min leaf (YML) (g g-1) 0 0.02
临界叶氮浓度y n conc crit leaf (YCL) (g g-1) 0 0.06
最小茎氮浓度YMS (YMS YMS) (g g-1) 0 0.02
临界茎氮浓度y n conc crit stem (YCS) (g g-1) 0 0.05
作物水分需求eo crop factor default (EFD) (-) 0.75 2.25
单株最大籽粒质量MGS (Max grain size) (g) 0.02 0.06
分蘖重Dm tiller max (DTM) (g) 0.6 1.8
单株重X stem wt (XSW) (g) 2 8
株高Y height (YH) (mm) 500 1500
穗粒数Grain num coeff (GNC) (-) 10 50
出苗到拔节积温tt end of juvenile (TOJ) (℃ d) 200 600
拔节到开花积温tt floral initiation (TFI) (℃ d) 250 800
开花到灌浆积温tt flowering (TF) (℃ d) 60 180
灌浆到成熟积温tt start grain fill (TGF) (℃ d) 200 900
作物春化敏感性指数Vern sens (VS) (-) 0 5
作物光周期敏感性指数Photop sens (PS) (-) 0 5
辐射利用效率Rue (y rue) (RYR) (g MJ-1) 1.1160 1.3640
消光系数K (y extinct coef) (K) (-) 0 1
日平均温度影响灌浆速率x temp grainfill (XTG) (-) 0 1
缺氮对光合作用的影响倍数N fact photo (NFPO) (-) 0.75 2.25
物候的氮限制因子N fact pheno (NFPE) (-) 50 150
光合叶片老化的水分胁迫斜率sen rate water (SRW) (-) 0.05 0.15
遮阴导致的叶面积老化敏感性参数sen light slope (SLS) (-) 0.001 0.003
遮阴导致老化的最大叶面积指数lai sen light (LSL) (m2 m-2) 3.5 10.5
植物开始的叶面积initial tpla (IT) (mm2) 100 300
最大比叶面积y sla max (YSM) (mm2 g-1) 22,000 45,000

Fig. 4

Coefficient of yield parameters at 0℃ GGS: the number of seeds per gram of stem; PGFR: potential daily grain filling rate during filling period; PGR: potential daily grain filling rate from flowering to filling; PGNFR: potential daily grain nitrogen accumulation rate; MFR: the lower limit of daily nitrogen accumulation rate; NFG: grain nitrogen limiting grout factor; YML: the minimum leaf nitrogen concentration; YCL: the critical leaf nitrogen concentration; YMS: the minimum stem nitrogen concentration; YCS: critical stem nitrogen concentration; EFD: crop water requirement; MGS: the maximum grain mass per plant; DTM: the tiller weight; XSW: weight per plant; YH: plant height; GNC: the number of grains per spike; TOJ: the accumulated temperature from seedling emergence to jointing; TFI: accumulated temperature from jointing to flowering; TF: temperature from flowering to grouting; TGF: accumulated temperature from grouting to maturity; VS: crop vernalization sensitivity index; PS: crop photoperiod sensitivity index; RYR: radiation utilization efficiency; K: extinction coefficient; XTG: the daily average temperature affects the grouting rate; NFPO: the influence factor of nitrogen deficiency on photosynthesis; NFPE: phenological nitrogen limiting factor; SRW: water stress slope of photosynthetic leaf aging; SLS: sensitivity parameter of leaf area aging caused by shading; LSL: the maximum leaf area index of shading induced aging; IT: the starting leaf area of the plant; YSM: the maximum specific leaf area."

Fig. 5

Sensitivity coefficient of yield parameters at 0.5℃ Abbreviations are the same as those given in Fig. 4."

Fig. 6

Sensitivity coefficient of yield parameters at 1℃ Abbreviations are the same as those given in Fig. 4."

Fig. 7

Sensitivity coefficient of yield parameters at 1.5℃ Abbreviations are the same as those given in Fig. 4."

Fig. 8

Sensitivity coefficient of yield parameters at 2℃ Abbreviations are the same as those given in Fig. 4."

Table 3

Initial values of spring wheat parameters related to APSIM model"

参数
Parameter		 初值
Initial value		 优化值
Optimized value
每克茎籽粒数量Grains per gram stem (GGS) (grain g-1) 24 26
单株最大籽粒质量Max. grain size (MGS) (g) 0.04 0.046
株高Y height (YH) (mm) 1000 1013.81
穗粒数Grain num coeff (GNC) (-) 30 28
出苗到拔节积温tt end of juvenile (TOJ) (℃ d) 400 360.44
灌浆到成熟积温tt start grain fill (TGF) (℃ d) 550 589.91
消光系数K y extinct coef (K) (-) 0.50 0.45
光合叶片老化的水分胁迫斜率sen rate water (SRW) (-) 0.10 0.11
最大比叶面积y sla max (YSM) (mm2 g-1) 26,000 24,317.50

Fig. 9

Linear fitting of simulated value, optimized value, and measured value of spring wheat yield"

Fig. 10

Dry matter simulation test results of spring wheat at growth stage"

[1] Jin X, Li Z, Nie C, Xu X, Feng H, Guo W, Wang J. Parameter sensitivity analysis of the AquaCrop model based on extended fourier amplitude sensitivity under different agro-meteorological conditions and application. Field Crops Res, 2018, 226: 1-15.
doi: 10.1016/j.fcr.2018.07.002
[2] Wang J, Li X, Lu L, Fang F. Parameter sensitivity analysis of crop growth models based on the extended Fourier Amplitude Sensitivity Test method. Environ Mod Software, 2013, 48: 171-182.
[3] 崔颖, 蔺宏宏, 谢云, 刘素红. AquaCrop模型在东北黑土区作物产量预测中的应用研究. 作物学报, 2021, 47: 159-168.
doi: 10.3724/SP.J.1006.2021.03016
Cui Y, Lin H H, Xie Y, Liu S H. Application of AquaCrop model to crop yield prediction in black soil region of northeast China. Acta Agron Sin, 2011, 47: 159-168 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2021.03016
[4] 崔金涛, 丁继辉, Yesilekin N, 邓升, 邵光成. 基于EFAST的CERES-Wheat模型土壤参数敏感性分析. 农业机械学报, 2020, 51(12): 276-283.
Cui J T, Ding J H, Yesilekin N, Deng S, Shao G C. Soil parameter sensitivity analysis of CERES-wheat model based on EFAST. Trans CSAM, 2020, 51(12): 276-283 (in Chinese with English abstract).
[5] Saltelli A, Tarantola S, Chan K P S. A quantitative model- independent method for global sensitivity analysis of model output. Technometrics, 1999, 41: 39-56.
doi: 10.1080/00401706.1999.10485594
[6] Saltell A, Bolado R. An alternative way to compute fourier amplitude sensitivity test (FAST). Comput SADA, 1998, 26: 445-460.
[7] Morris M. Factorial sampling plans for preliminary computational experiments. Technometrics, 2012, 33: 161-174.
doi: 10.1080/00401706.1991.10484804
[8] 李美水, 杨晓华. 基于Sobol方法的SWMM模型参数全局敏感性分析. 中国给水排水, 2020, 36(17): 95-102.
Li M S, Yang X H. Global sensitivity analysis of SWMM model parameters based on Sobol method. China Water Drain, 2020, 36(17): 95-102 (in Chinese with English abstract).
[9] Liu J Z, Liu Z C, Zhu A X, Shen F, Lei Q L, Duan Z. Global sensitivity analysis of the APSIM-Oryza rice growth model under different environmental conditions. Sci Total Environ, 2019, 651: 953-968.
doi: 10.1016/j.scitotenv.2018.09.254
[10] Xing H M, Xiang S Y, Xin G X, Chen Y J, Feng H K, Yang G J, Chen Z X. Global sensitivity analysis of AquaCrop crop model parameters based on EFAST method. Sci Agric Sin, 2017, 16: 2444-2458.
[11] Zhao G, Bryan B A, Song X D. Sensitivity and uncertainty analysis of the APSIM-wheat model: Interactions between cultivar, environmental, and management parameters. Ecol Mod, 2014, 279: 1-11.
doi: 10.1016/j.ecolmodel.2014.02.003
[12] 何亮, 赵刚, 靳宁, 庄伟, 于强. 不同气候区和不同产量水平下APSIM-Wheat模型的全局敏感性分析. 农业工程学报, 2015, 31(14): 148-157.
He L, Zhao G, Jin N, Zhuang W, Yu Q. Global sensitivity analysis of APSIM-Wheat Model parameters under different climate zones and different yield levels. Trans CSAE, 2015, 31(14): 148-157 (in Chinese with English abstract).
[13] 邓晓垒, 董莉霞, 李广, 聂志刚, 胥建杰, 王钧, 逯玉兰. 西北春麦区Apsim-Wheat模型参数全局敏感性分析. 麦类作物学报, 2022, 42: 746-754.
Deng X L, Dong L X, Li G, Nie Z G, Xu J J, Wang J, Lu Y L. Global sensitivity analysis of Apsim-wheat model parameters in Spring wheat region of Northwest China. J Triticeae Crops, 2002, 42: 746-754 (in Chinese with English abstract).
[14] 金梦潇, 田勇, Michele L, 于江, 郑春苗. 基于Morris、Sobol和EFAST的LID设施模型参数全局敏感性分析. 中国农村水利水电, 2022, (6): 104-110.
Jin M X, Tian Y, Michele L, Yu J, Zheng C M. Global Sensitivity analysis of LID facility model parameters based on morris, sobol and EFAST. China Rural Water Hydrop, 2022, (6): 104-110 (in Chinese with English abstract).
[15] Guo D, Olesen J E, Pullens J W M, Guo C, Ma X. Calibrating AquaCrop model using genetic algorithm with multi-objective functions applying different weight factors. Agron J, 2021, 113: 1420-1438.
doi: 10.1002/agj2.v113.2
[16] 庄嘉祥, 姜海燕, 刘蕾蕾, 王芳芳, 汤亮, 朱艳, 曹卫星. 基于个体优势遗传算法的水稻生育期模型参数优化. 中国农业科学, 2013, 46: 2220-2231.
doi: 10.3864/j.issn.0578-1752.2013.11.005
Zhuang J X, Jiang H Y, Liu L L, Wang F F, Tang L, Zhu Y, Cao W X. Rice growth stage model parameter optimization based on individual dominance genetic algorithm. Sci Agric Sin, 2013, 46: 2220-2231 (in Chinese with English abstract).
doi: 10.3864/j.issn.0578-1752.2013.11.005
[17] 沈禹颖, 南志标, Bill B, Michael R, 陈文, 邵新庆. APSIM模型的发展与应用. 应用生态学报, 2002, 13: 1027-1032.
Shen Y Y, Nan Z B, Bill B, Michael R, Chen W, Shao X Q. Development and application of APSIM model. Chin J Appl Ecol, 2002, 13: 1027-1032 (in Chinese with English abstract).
[18] 李广, 黄高宝, William B, 陈文. APSIM模型在黄土丘陵沟壑区不同耕作措施中的适用性. 生态学报, 2009, 29: 2655-2663.
Li G, Huang G B, William B, Chen W. Application of APSIM model to different tillage practices in loess Hilly-gully region. Acta Ecol Sin, 2009, 29: 2655-2663 (in Chinese with English abstract).
[19] 李广, 黄高宝. 基于APSIM模型的降水量分配对旱地小麦和豌豆产量影响的研究. 中国生态农业学报, 2010, 18: 342-347.
Li G, Huang G B. Study on the effect of precipitation allocation on wheat and pea yield in dry land based on APSIM model. Chin J Eco-Agric, 2010, 18: 342-347 (in Chinese with English abstract).
doi: 10.3724/SP.J.1011.2010.00342
[20] 李广, 李玥, 黄高宝, 罗珠珠, 王琦, 刘强, 燕振刚, 赵有益. 基于APSIM模型旱地春小麦产量对温度和CO2浓度升高的响应. 中国生态农业学报, 2012, 20: 1088-1095.
Li G, Li Y, Huang G B, Luo Z Z, Wang Q, Liu Q, Yan Z G, Zhao Y Y. Response of spring wheat yield to temperature and CO2 concentration increase in dryland based on APSIM model. Chin J Eco-Agric, 2012, 20: 1088-1095 (in Chinese with English abstract).
doi: 10.3724/SP.J.1011.2012.01088
[21] 李广, 黄高宝, 王琦, 罗珠珠. 基于APSIM模型的旱地小麦和豌豆水肥协同效应分析. 草业学报, 2011, 20: 151-159.
Li G, Huang G B, Wang Q, Luo Z Z. Analysis of synergistic effect of water and fertilizer on wheat and pea in dry land based on APSIM model. Acta Pratac Sin, 2011, 20: 151-159 (in Chinese with English abstract).
[22] 聂志刚, 李广, 雒翠萍, 马维伟, 代永强. 利用混合蛙跳算法优化基于APSIM的旱地小麦产量形成模型参数. 作物学报, 2018, 44: 1229-1236.
doi: 10.3724/SP.J.1006.2018.01229
Nie Z G, Li G, Luo C P, Ma W W, Dai Y Q. Optimization of yield formation model parameters of dryland wheat based on APSIM by hybrid leapfrog algorithm. Acta Agron Sin, 2018, 44: 1229-1236 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2018.01229
[23] Gaydon D S, Singh B, Wang E, Poulton P L. Evaluation of the APSIM model in cropping systems of Asia. Field Crops Res, 2017, 204: 52-75.
doi: 10.1016/j.fcr.2016.12.015
[24] Anuytrecht E, Thorburn P J. Responses to atmospheric CO2 concentrations in crop simulation models: a review of current simple and semicomplex representations and options for model development. Global Change Biol, 2017, 23: 1806-1820.
doi: 10.1111/gcb.2017.23.issue-5
[25] 茹晓雅, 李广, 陈国鹏, 张统帅, 闫丽娟. 不同降水年型下水氮调控对小麦产量及生物量的影响. 作物学报, 2019, 45: 1725-1734.
doi: 10.3724/SP.J.1006.2019.91008
Ru X Y, Li G, Chen G P, Zhang T S, Yan L J. Effects of groundwater nitrogen regulation on wheat yield and biomass in different precipitation year. Acta Agron Sin, 2019, 45: 1725-1734 (in Chinese with English abstract).
[26] Simlabv3.2.5 User Manual 2009. Ispra, Italy: POLIS-JRC/ISIS, 2009. http://simlab.JrcEc.Europa.eu/docs/html/index.Html.
[27] Saltelli A, Tarantola S, Chan K. A quantitative model- independent method for global sensitivity analysis of model output. Technometrics, 1999, 41: 39-56.
doi: 10.1080/00401706.1999.10485594
[28] Dejonge K C, James I I, Ahmadi M, Andales A A, Arabi M. Global sensitivity and uncertainty analysis of a dynamic agroecosystem model under different irrigation treatments. Ecol Mod, 2012, 231: 113-125.
doi: 10.1016/j.ecolmodel.2012.01.024
[29] Kennedy J, Eberhart R C. Swarm Intelligence. Morgan: Kaufman Academic Press, 2001. pp 212-216.
[30] Guo Y, Li J Y, Zhan Z H. Efficient hyperparameter optimization for convolution neural networks in deep learning: a distributed particle swarm optimization approach. Cybernet Syst, 2020, 52: 36-57.
[31] 杨霞, 吴东伟. R语言在大数据处理中的应用. 科技资讯, 2013, (344): 19-20.
Yang X, Wu D W. Application of R language in big data processing. Technol News, 2013, (344): 19-20 (in Chinese with English abstract).
[32] Stocker T F, Qin D, Plattner G K. Climate Change 2013: The Physical Science Basis. UK: Cambridge University Press, 2013.
[33] 米荣娟, 聂志刚. 基于ETAST法的APSIM小麦产量形成参数敏感性分析. 甘肃农业大学学报, 2021, 56(4): 23-30.
Mi R J, Nie Z G. Sensitivity analysis of yield formation parameters of APSIM wheat based on ETAST method. J Gansu Agric Univ, 2021, 56(4): 23-30 (in Chinese with English abstract).
[34] Zheng B Y, Chenu K, Doherty A, Chapman S. The APSIM-wheat module (7.5 R3008) documentation. Toowoomba: APSRU, 2014. pp 18-19.
[35] 韩雪, 刘强, 王钧, 高雪慧, 车鹏鹏. 基于APSIM模型的气候变化条件下播期对旱地春小麦产量影响研究. 作物研究, 2022, 36: 499-506.
Han X, Liu Q, Wang J, Gao X H, Che P P. Effects of sowing date on spring wheat yield in dryland under climate change conditions based on APSIM model. Crop Res, 2002, 36: 499-506 (in Chinese with English abstract).
[36] 张佳运, 马淑梅, 余常兵, 王淑彬, 魏亚凤, 杨文钰, 王小春. 长江流域旱地多熟模式水分供需平衡特征与水分生产效益. 作物学报, 2022, 48: 2891-2907.
doi: 10.3724/SP.J.1006.2022.14206
Zhang J Y, Ma S M, Yu C B, Wang S B, Wei Y F, Yang W Y, Wang X C. Water supply and demand balance characteristics and water production efficiency of dryland multi-cropping model in the Yangtze River Basin. Acta Agron Sin, 2022, 48: 2891-2907 (in Chinese with English abstract).
[37] 何亮, 侯英雨, 赵刚, 邬定荣, 于强. 基于全局敏感性分析和贝叶斯方法的WOFOST作物模型参数优化. 农业工程学报, 2016, 32(2): 169-179.
He L, Hou Y Y, Zhao G, Wu D R, Yu Q. Parameter optimization of WOFOST crop model based on global sensitivity analysis and Bayesian method. Trans CSAE, 2016, 32(2): 169-179 (in Chinese with English abstract).
[38] 贡复俊. 消光系数的含义、数值变化及与作物高产的关系——兼与殷宏章、王天铎等商榷. 江苏农学院学报, 1982, (4): 36-41.
Gong F J. The meaning of extinction coefficient, its numerical variation and its relationship with crop yield: discussion with Yin Hongzhang, Wang Tianduo. J Jiangsu Agric Coll, 1982, (4): 36-41 (in Chinese with English abstract).
[39] 周延辉, 朱新开, 郭文善, 封超年. 稻茬小麦中高产水平下产量及其构成因素分析. 麦类作物学报, 2018, 38: 293-297.
Zhou Y H, Zhu X K, Guo W S, Feng C N. Analysis of yield and its component factors at medium and high yield of rice-stubble wheat. J Triticeae Crops, 2018, 38: 293-297 (in Chinese with English abstract).
[40] 王钧, 李广, 闫丽娟, 刘强, 聂志刚. 旱地春小麦产量对不同生育阶段温度变化的响应模拟. 中国农业科学, 2020, 53: 904-916.
doi: 10.3864/j.issn.0578-1752.2020.05.004
Wang J, Li G, Yan L J, Liu Q, Nie Z G. Simulation of response of spring wheat yield to temperature change at different growth stages in dryland. Sci Agric Sin, 2020, 53: 904-916 (in Chinese with English abstract).
[41] 周宝元, 马玮, 孙雪芳, 丁在松, 李从锋, 赵明. 冬小麦-夏玉米高产模式周年气候资源分配与利用特征研究. 作物学报, 2019, 45: 589-600.
doi: 10.3724/SP.J.1006.2019.81067
Zhou B Y, Ma W, Sun X F, Ding Z S, Li C F, Zhao M. Study on annual climate resource allocation and utilization characteristics of high yield model of winter wheat and summer maize. Acta Agron Sin, 2019, 45: 589-600 (in Chinese with English abstract).
doi: 10.3724/SP.J.1006.2019.81067
[42] 赵吉平, 周伟, 郭鹏燕, 任杰成, 许瑛. 干旱胁迫对小麦品种株高与产量及抗旱性相关分析. 种子, 2020, 39: 120-123.
Zhao J P, Zhou W, Guo P Y, Ren J C, Xu Y. Correlation analysis of plant height, yield and drought resistance of wheat varieties under drought stress. Seed, 2020, 39: 120-123 (in Chinese with English abstract).
[43] 王义芹, 杨兴洪, 李滨, 童依平, 李振声. 小麦叶面积及光合速率与产量关系的研究. 华北农学报, 2008, 23: 10-15.
doi: 10.7668/hbnxb.2008.S2.003
Wang Y Q, Yang X H, Li B, Tong Y P, Li Z S. Study on the relationship between leaf area, photosynthetic rate and yield of wheat. Acta Agric Boreali-Sin, 2008, 23: 10-15 (in Chinese with English abstract).
[44] 符玉英. 水分胁迫下植物叶片光合的气孔和非气孔限制. 科技与创新, 2018, (104): 57-58.
Fu Y Y. Stomatal and non-stomatal restrictions on photosynthesis of plant leaves under water stress. Sci Technol Innov, 2018, (104): 57-58 (in Chinese with English abstract).
[45] 戴忠民, 李妍, 张红, 王丽燕, 张秀玲, 李勇, 王振林. 不同灌溉处理对小麦花后氮素积累和转运的影响. 麦类作物学报, 2015, 35: 1712-1718.
Dai Z M, Li Y, Zhang H, Wang L Y, Zhang X L, Li Y, Wang Z L. Effects of different irrigation treatments on post-anthesis nitrogen accumulation and transport in wheat. J Triticeae Crops, 2015, 35: 1712-1718 (in Chinese with English abstract).
[46] 曹广才, 吴东兵. 播种至生理拔节期间的积温对冬型小麦品种生育天数的影响. 北京农业科学, 1990, (3): 6-9.
Cao G G, Wu D B. Effects of accumulated Temperature from Sowing to physiological jointing on growth days of winter type wheat varieties. Beijing Agric Sci, 1990, (3): 6-9 (in Chinese with English abstract).
[47] 刘奕辰, 高雅洁, 张玲, 石大山. 积温和降水对主要作物产量的影响——以章丘市为例. 江西农业, 2018, (14): 52-53.
Liu Y C, Gao Y J, Zhang L, Shi D S. Effects of accumulated temperature and precipitation on yield of main crops: a case study of Zhangqiu City. Jiangxi Agric, 2018, (14): 52-53 (in Chinese).
[48] 张洁, 白青华, 马鸿勇. 气候变化对河西走廊中部地区主要农作物的影响. 干旱气象, 2013, 31: 303-308.
Zhang J, Bai Q H, Ma H Y. Effects of climate change on main crops in central Hexi Corridor. J Arid Meteorol, 2013, 31: 303-308 (in Chinese with English abstract).
[49] 刘政, 陈晓杰, 胡银岗. 春化及光周期基因的等位变异及其对冬小麦光合及产量性状的影响. 麦类作物学报, 2016, 36: 714-720.
Liu Z, Chen X J, Hu Y G. Alleles of vernalization and photoperiod genes and their effects on photosynthesis and yield traits in winter wheat. J Triticeae Crops, 2016, 36: 714-720 (in Chinese with English abstract).
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