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作物发育模式重构及基于甘蔗的模拟检验

马玉平 王培娟 王达 俄有浩 李莉 孙琳丽 杨建莹 霍治国

马玉平, 王培娟, 王达, 等. 作物发育模式重构及基于甘蔗的模拟检验. 应用气象学报, 2021, 32(5): 603-617. DOI:  10.11898/1001-7313.20210508..
引用本文: 马玉平, 王培娟, 王达, 等. 作物发育模式重构及基于甘蔗的模拟检验. 应用气象学报, 2021, 32(5): 603-617. DOI:  10.11898/1001-7313.20210508.
Ma Yuping, Wang Peijuan, Wang Da, et al. Reconstruction of crop development model with its simulation test based on sugarcane. J Appl Meteor Sci, 2021, 32(5): 603-617. DOI:  10.11898/1001-7313.20210508.
Citation: Ma Yuping, Wang Peijuan, Wang Da, et al. Reconstruction of crop development model with its simulation test based on sugarcane. J Appl Meteor Sci, 2021, 32(5): 603-617. DOI:  10.11898/1001-7313.20210508.

作物发育模式重构及基于甘蔗的模拟检验

DOI: 10.11898/1001-7313.20210508
资助项目: 

国家重点研发计划 2019YFD1002203

中国气象科学研究院基本科研业务费专项 2020Z005

详细信息
    通信作者:

    霍治国, 邮箱: huozg@cma.gov.cn

Reconstruction of Crop Development Model with Its Simulation Test Based on Sugarcane

  • 摘要: 发育进程是作物的生理年龄,发育模式是作物生长模型的时间指针。但目前的发育模式只关注某时段(日)气象条件对作物发育的影响,其准确率也难以满足作物生长模拟的需求。根据作物发育速率不仅与气象条件有关、还与其所处发育期有关的理论假设,重构发育进程模式,并利用1980—2019年我国甘蔗发育实测数据进行模式适应性分析,比较传统模式与重构模式的模拟能力。结果表明:重构模式中,发育单位日序模式和温度日序模式对甘蔗发育进程的适应性均较好,尤其在后期温度不断降低的发育进程以及低温年型的模拟中,其适应能力明显优于传统模式。重构及传统模式模拟能力从强到弱依次为发育单位日序模式、温度日序模式、响应适应模式、发育单位模式、发育单位温度修正模式、热量单位模式,均方根误差计算的模拟能力值依次为4.3,3.9,3.7,3.3,3.0,2.8。
  • 图  1  新植蔗全样本发育实测数据对不同发育模式的回代模拟检验

    Fig. 1  Test of different development models based on the whole sample development data of new planted sugarcane

    图  2  发育模式参数值与站点所处纬度相关关系

    Fig. 2  Relationship between parameters of development model and latitude of the station

    图  3  发育模式对新植蔗回代模拟与实测值比较

    Fig. 3  Measurements and simulations of development models based on back training for new planted sugarcane

    图  4  发育模式对新植蔗独立样本模拟值与实测值比较

    Fig. 4  Measurements and simulations of development models based on independent samples for new planted sugarcane

    表  1  研究数据概况

    Table  1  Overview of research data

    作物 站点 所在省份 位置 海拔/m 数据时段
    新植蔗 乌拉特前旗 40.7°N,108.7°E 1022.0 1997—2002年
    新植蔗 临河 40.8°N,107.4°E 1040.8 1992—2002年
    新植蔗 平罗 38.9°N,106.6°E 1099.9 1993—1999年
    新植蔗 赤峰 42.3°N,119.0°E 568.0 1992—2002年
    新植蔗 耿马 23.6°N,99.4°E 1105.4 1993—2020年
    新植蔗 元江 23.4°N,102.0°E 397.6 1994—2020年
    新植蔗 泰和 26.8°N,114.9°E 61.8 1993—2003年
    新植蔗 广丰 28.4°N,118.2°E 96.1 1994—2009年
    新植蔗 仙游 25.4°N,118.7°E 77.0 1993—1997年
    新植蔗 宜山 24.5°N,108.7°E 149.8 2003—2009年
    新植蔗 沙塘 24.5°N,109.4°E 99.1 2003—2010年
    新植蔗 蒙山 24.2°N,110.5°E 147.0 1980—1994年
    新植蔗 平果 23.3°N,107.6°E 112.6 1990—2009年
    新植蔗 来宾 23.8°N,109.2°E 85.2 2003—2009年
    新植蔗 贵县 23.1°N,109.6°E 56.0 1989—2009年
    新植蔗 扶绥 22.6°N,107.9°E 88.9 2003—2012年
    新植蔗 徐闻 20.3°N,110.2°E 69.0 1992—2001年
    宿根蔗 米易 26.9°N,102.1°E 1105.8 1992—1998年
    宿根蔗 德宏州 24.4°N,98.6°E 914.7 1993—2009年
    宿根蔗 耿马 23.6°N,99.4°E 1105.4 2012—2020年
    宿根蔗 蒙自 23.4°N,103.4°E 1301.7 2010—2016年
    宿根蔗 吉安 27.1°N,115.0°E 78.0 2000—2009年
    宿根蔗 泰和 26.8°N,114.9°E 61.8 1992—2009年
    宿根蔗 仙游 25.4°N,118.7°E 77.0 1998—2009年
    宿根蔗 宜山 24.5°N,108.7°E 149.8 2002—2009年
    宿根蔗 沙塘 24.5°N,109.4°E 99.1 2002—2012年
    宿根蔗 蒙山 24.2°N,110.5°E 147.0 2002—2009年
    宿根蔗 漳浦 24.1°N,117.6°E 51.1 2002—2009年
    宿根蔗 平果 23.3°N,107.6°E 112.6 2002—2009年
    宿根蔗 贵县 23.1°N,109.6°E 56.0 1996—2009年
    下载: 导出CSV

    表  2  发育模式在部分站点针对新植蔗的参数率定值

    Table  2  Calibrated parameter of development models at some sites for new planted sugarcane

    站名 纬度 发育模式
    THU CHU CHUa CHUd/105 TAd/105
    乌拉特前旗 40.7°N 1825.6 2149.1 97.4 4.34 6.34
    临河 40.8°N 1741.3 2061.7 94.8 4.04 5.88
    平罗 38.9°N 1737.1 2143.9 108.3 4.38 6.43
    赤峰 42.3°N 1662.9 2043.3 99.7 4.22 6.13
    耿马 23.6°N 3034.5 3723.5 175.2 9.27 13.0
    元江 23.4°N 4569.2 4968.3 178.1 9.93 20.1
    泰和 26.8°N 3415.9 3898.3 157.6 8.29 11.9
    广丰 28.4°N 3190.2 3633.9 145.1 7.30 10.5
    仙游 25.4°N 3804.3 4319.8 175.5 9.04 12.8
    宜山 24.5°N 3584.3 3946.0 150.9 7.82 11.2
    沙塘 24.5°N 3894.0 4366.9 175.4 8.90 12.8
    蒙山 24.2°N 3584.3 4049.9 166.8 8.63 12.4
    平果 23.3°N 4114.0 4560.1 176.2 9.04 12.9
    来宾 23.8°N 3799.4 4149.1 155.4 8.34 11.9
    贵县 23.1°N 3918.3 4315.0 164.3 8.60 12.3
    扶绥 22.6°N 4242.6 4687.0 179.4 10.4 15.0
    徐闻 20.3°N 4888.2 5446.8 207.7 12.9 18.0
    下载: 导出CSV

    表  3  发育模式对新植蔗回代模拟误差

    Table  3  Back training simulation error of development model for new planted sugarcane

    发育阶段 模式 相关系数 平均偏差/d 平均误差/d 平均相对误差/d 均方根误差/d 样本量
    播种-出苗 THU 0.82 1.1 6.2 19.6 8.9 66
    CHU 0.83 0.8 6.0 18.7 8.6 66
    CHUa 0.82 1.3 6.3 19.2 8.9 66
    CHUd 0.83 1.6 6.2 20.5 9.1 66
    TAd 0.83 1.4 6.1 20.0 8.9 66
    RAM 0.84 -1.5 5.4 15.1 8.7 66
    出苗-茎伸长 THU 0.90 0.5 9.5 12.2 14.2 137
    CHU 0.88 0.5 10.3 13.1 14.9 137
    CHUa 0.84 0.6 12.7 16.1 17.3 137
    CHUd 0.91 0.9 8.9 11.2 13.5 137
    TAd 0.90 0.9 8.9 11.2 13.6 137
    RAM 0.86 -0.4 8.3 12.2 16.5 137
    茎伸长-成熟 THU 0.33 8.4 25.2 20.2 43.0 120
    CHU 0.73 1.6 15.5 11.4 23.0 120
    CHUa 0.86 0.1 12.0 8.3 16.5 120
    CHUd 0.86 0.3 11.8 8.5 16.6 120
    TAd 0.76 4.9 14.9 10.3 23.9 120
    RAM 0.55 -1.4 16.2 11.9 36.1 120
    下载: 导出CSV

    表  4  发育模式对新植蔗独立样本模拟误差

    Table  4  Development model simulation errors based on independent samples for new planted sugarcane

    发育阶段 模式 相关系数 平均偏差/d 平均误差/d 平均相对误差/d 均方根误差/d 样本量
    播种-出苗 THU 0.83 2.6 6.6 31.5 9.1 24
    CHU 0.82 2.5 6.5 31.2 9.2 24
    CHUa 0.81 3.3 6.6 32.2 9.6 24
    CHUd 0.81 3.0 6.9 31.7 10.1 24
    TAd 0.81 3.0 6.9 32.0 9.9 24
    RAM 0.81 1.4 6.2 29.1 9.1 24
    出苗-茎伸长 THU 0.92 0.9 9.1 11.8 12.4 52
    CHU 0.92 1.0 9.6 12.3 12.7 52
    CHUa 0.87 1.5 11.5 14.6 15.3 52
    CHUd 0.93 3.6 8.9 11.8 12.9 52
    TAd 0.92 3.1 8.9 11.8 12.9 52
    RAM 0.73 2.7 13.0 20.3 23.2 52
    茎伸长-成熟 THU 0.58 5.0 22.9 15.1 35.0 46
    CHU 0.67 5.2 18.2 12.2 27.5 46
    CHUa 0.85 6.3 12.6 8.8 17.3 46
    CHUd 0.86 6.2 12.4 8.5 17.2 46
    TAd 0.71 14.0 19.8 13.7 32.8 46
    RAM 0.21 12.2 29.1 24.0 70.1 46
    下载: 导出CSV

    表  5  发育模式在不同检验中的模拟能力

    Table  5  Simulation ability of development models in different tests

    发育阶段 模式 新植蔗 宿根蔗 SCV
    全样本 参数率定 独立样本 全样本 参数率定 独立样本
    播种-出苗 THU 2 4 6 4.0
    CHU 5 6 4 5.0
    CHUa 1 3 3 2.3
    CHUd 3 1 1 1.7
    TAd 4 2 2 2.7
    RAM 6 5 5 5.3
    出苗/发株-茎伸长 THU 3 4 6 3 3 4 3.8
    CHU 2 3 5 2 2 3 2.8
    CHUa 1 1 2 1 1 1 1.2
    CHUd 5 6 4 4 5 6 5.0
    TAd 4 5 3 5 4 5 4.3
    RAM 6 2 1 6 6 2 3.8
    茎伸长-成熟 THU 1 1 2 2 1 1 1.3
    CHU 2 4 4 3 2 2 2.8
    CHUa 5 6 5 6 5 4 5.2
    CHUd 6 5 6 4 3 5 4.8
    TAd 4 3 3 5 4 6 4.2
    RAM 3 2 1 1 6 3 2.7
    下载: 导出CSV
  • [1] Sinclair T R, Seligman N A G.Crop modeling:From infancy to maturity. Agron J, 1996, 88(5):698-704. doi:  10.2134/agronj1996.00021962008800050004x
    [2] Monteith J L. The quest for balance in crop modeling. Agron J, 1996, 88(5): 695-697. doi:  10.2134/agronj1996.00021962008800050003x
    [3] Edwards D, Hamson M. Guide to Mathematical Modelling. London: MacMillan Press Ltd, 1989: 1-277.
    [4] Hoogenboom G. Contribution of agrometeorology to the simulation of crop production and its applications. Agr Forest Meteorol, 2000, 103(1/2): 137-157.
    [5] 马玉平, 霍治国, 王培娟, 等. 中国农业气象模式(CAMM1.0)构建与应用. 应用气象学报, 2019, 30(5): 528-542. doi:  10.11898/1001-7313.20190502

    Ma Y P, Huo Z G, Wang P J, et al. The construction and application of Chinese Agrometeorological Model(CAMM1.0). J Appl Meteor Sci, 2019, 30(5): 528-542. doi:  10.11898/1001-7313.20190502
    [6] Van Diepen C A, Wolf J, van Keulen H, et al. WOFOST: A simulation model of crop production. Soil Use Manage, 1989, 5: 16-24. doi:  10.1111/j.1475-2743.1989.tb00755.x
    [7] Kropff M J, van Laar H H, Matthews R B. ORYZA1: An Ecophysiological Model for Irrigated Rice Production. SARP Research Proceedings, Wageningen(Netherlands): IRRI/AB-DLO, 1994.
    [8] Gao L Z, Jin Z Q, Huang Y, et al. Rice clock model-A computer model to simulate rice development. Agr Forest Meteorol, 1992, 60(1/2): 1-16.
    [9] Keating B A, Carberry P S, Hammer G L, et al. An overview of APSIM, a model designed for farming systems simulation. Eur J Agron, 2003, 18(3/4): 267-288.
    [10] Jones A J W, Hoogenboom B G, Porter A C H, et al. The DSSAT cropping system model. Eur J Agron, 2003, 18(3/4): 235-265. http://europepmc.org/abstract/AGR/IND44696208
    [11] Kapetanaki G, Rosenzweig C. Impact of climate change on maize yield in central and northern Greece: A simulation study with Ceres-Maize. Mitig Adapt Strat Gl, 1997, 1(3): 251-271. doi:  10.1007/BF00517806
    [12] Ceglar A, Bogataj L K. Simulation of maize yield in current and changed climatic conditions: Addressing modelling uncertainties and the importance of bias correction in climate model simulations. Eur J Agron, 2012, 37(1): 83-95. doi:  10.1016/j.eja.2011.11.005
    [13] 金之庆, 葛道阔, 郑喜莲, 等. 评价全球气候变化对我国玉米生产的可能影响. 作物学报, 1996, 22(5): 513-524. doi:  10.3321/j.issn:0496-3490.1996.05.001

    Jin Z Q, Ge D K, Zheng X L, et al. Assessing the potential impacts of global climate change on maize production in China. Acta Agronomica Sinica, 1996, 22(5): 513-524. doi:  10.3321/j.issn:0496-3490.1996.05.001
    [14] Yin X, Chasalow S D, Dourleijn C J, et al. Coupling estimated effects of QTLs for physiological traits to a crop growth model: Predicting yield variation among recombinant inbred lines in barley. Heredity(Edinb), 2000, 85(6): 539-549.
    [15] 王石立, 马玉平. 作物生长模拟模型在我国农业气象业务中的应用研究进展及思考. 气象, 2008, 34(6): 3-10. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXX200806002.htm

    Wang S L, Ma Y P. The progress in application of crop growth simulation models to agro-meteorological services in China. Meteor Mon, 2008, 34(6): 3-10. https://www.cnki.com.cn/Article/CJFDTOTAL-QXXX200806002.htm
    [16] 高亮之. 农业模型学基础. 香港: 天马图书有限公司, 2004.

    Gao L Z. Foundation of Agricultural Modeling Science. Hong-kong: Tianma Books Ltd, 2004.
    [17] 黄健熙, 黄海, 马鸿元, 等. 遥感与作物生长模型数据同化应用综述. 农业工程学报, 2018, 34(21): 144-156. doi:  10.11975/j.issn.1002-6819.2018.21.018

    Huang J X, Huang H, Ma H Y, et al. Review on data assimilation of remote sensing and crop growth models. Transactions of the Chinese Society of Agricultural Engineering, 2018, 34(21): 144-156. doi:  10.11975/j.issn.1002-6819.2018.21.018
    [18] 帅细强, 王石立, 马玉平, 等. 基于水稻生长模型的气象影响评价和产量动态预测. 应用气象学报, 2008, 19(1): 71-81. doi:  10.3969/j.issn.1001-7313.2008.01.010

    Shuai X Q, Wang S L, Ma Y P, et al. Assessment of meteorological condition effects and dynamic yield forecasting based on rice growth model. J Appl Meteor Sci, 2008, 19(1): 71-81. doi:  10.3969/j.issn.1001-7313.2008.01.010
    [19] 熊伟. CERES-Wheat模型在我国小麦区的应用效果及误差来源. 应用气象学报, 2009, 20(1): 88-94. doi:  10.3969/j.issn.1001-7313.2009.01.011

    Xiong W. The performance of CERES wheat model in wheat planting areas and its uncertainties. J Appl Meteor Sci, 2009, 20(1): 88-94. doi:  10.3969/j.issn.1001-7313.2009.01.011
    [20] 侯英雨, 张蕾, 吴门新, 等. 国家级现代农业气象业务技术进展. 应用气象学报, 2018, 29(6): 641-656. doi:  10.11898/1001-7313.20180601

    Hou Y Y, Zhang L, Wu M X, et al. Advance of modern agrometeorological service and technology in China. J Appl Meteor Sci, 2018, 29(6): 641-656. doi:  10.11898/1001-7313.20180601
    [21] 帅细强, 陆魁东, 黄晚华. 不同方法在湖南省早稻产量动态预报中的比较. 应用气象学报, 2015, 26(1): 103-111. doi:  10.11898/1001-7313.20150111

    Shuai X Q, Lu K D, Huang W H. A comparative study on dynamic forecasting of early rice yield by using different methods in Hunan Province. J Appl Meteor Sci, 2015, 26(1): 103-111. doi:  10.11898/1001-7313.20150111
    [22] 刘布春, 王石立, 庄立伟, 等. 基于东北玉米区域动力模型的低温冷害预报应用研究. 应用气象学报, 2003, 14(5): 616-625. doi:  10.3969/j.issn.1001-7313.2003.05.012

    Liu B C, Wang S L, Zhuang L W, et al. Study of low temperature damage prediction applications in Northeast China based on a scaling-up maize dynamic model. J Appl Meteor Sci, 2003, 14(5): 616-625. doi:  10.3969/j.issn.1001-7313.2003.05.012
    [23] McMaster G S, Wilhelm W W. Phenological responses of wheat and barley to water and temperature: Improving simulation models. J Agric Sci, 2003, 141(2): 129-148. doi:  10.1017/S0021859603003460
    [24] 刘健, 姚宁, 吝海霞, 等. 冬小麦物候期对土壤水分胁迫的响应机制与模拟. 农业工程学报, 2016, 32(21): 115-124. doi:  10.11975/j.issn.1002-6819.2016.21.016

    Liu J, Yao N, Lin H X, et al. Response mechanism and simulation of winter wheat phonology to soil water stress. Transactions of the Chinese Society of Agricultural Engineering, 2016, 32(21): 115-124. doi:  10.11975/j.issn.1002-6819.2016.21.016
    [25] McMaster G S, Wilhelm W W. Growing degree-days: One equation, two interpretations. Agr Forest Meteorol, 1997, 87(4): 291-300. doi:  10.1016/S0168-1923(97)00027-0
    [26] 王石立, 马玉平, 庄立伟. 东北地区玉米冷害预测评估模型改进研究. 自然灾害学报, 2008, 17(4): 12-18. doi:  10.3969/j.issn.1004-4574.2008.04.003

    Wang S L, Ma Y P, Zhuang L W. Improvement study on prediction and assessment model for chilling damage of maize in Northeast China. Journal of Natural Disasters, 2008, 17(4): 12-18. doi:  10.3969/j.issn.1004-4574.2008.04.003
    [27] 马玉平, 王石立, 李维京. 基于作物生长模型的玉米生殖期冷害致灾因子研究. 作物学报, 2011, 37(9): 1642-1649. doi:  10.3969/j.issn.1000-2561.2011.09.010

    Ma Y P, Wang S L, Li W J. Chilling disaster factors in maize reproductive stage based on crop growth model. Acta Agronomica Sinica, 2011, 37(9): 1642-1649. doi:  10.3969/j.issn.1000-2561.2011.09.010
    [28] Brown D M, Chapman L J. Soybean ecology. Ⅱ. Development-temperature-moisture relationships from field studies. Agron J, 1960, 52(9): 496-499. doi:  10.2134/agronj1960.00021962005200090002x
    [29] Matthews R B, Hunt L A. GUMCAS: A model describing the growth of cassava(Manihot esculenta L. Crantz). Field Crop Res, 1994, 36(1): 69-84. doi:  10.1016/0378-4290(94)90054-X
    [30] 马玉平, 张黎, 孙琳丽, 等. 持续性温强和土壤水分对玉米发育进程的影响及其模拟. 中国农学通报, 2015, 3(3): 186-193. https://www.cnki.com.cn/Article/CJFDTOTAL-ZNTB201503032.htm

    Ma Y P, Zhang L, Sun L L, et al. Effects of continuous temperature and soil moisture on development process of maize and its simulation. Chinese Agricultural Science Bulletin, 2015, 3(3): 186-193. https://www.cnki.com.cn/Article/CJFDTOTAL-ZNTB201503032.htm
    [31] Wang E, Martre P, Zhao Z, et al. The uncertainty of crop yield projections is reduced by improved temperature response functions. Nat Plants, 2017, 3(8): 17102. doi:  10.1038/nplants.2017.102
    [32] 高亮之, 金之庆, 黄耀, 等. 作物模拟与栽培优化原理的结合-RCSODS. 作物杂志, 1994(3): 4-7. https://www.cnki.com.cn/Article/CJFDTOTAL-ZWZZ403.002.htm

    Gao L Z, Jin Z Q, Huang Y, et al. Combination of crop simulation and cultivation optimization principle-RCSODS. Crops, 1994(3): 4-7. https://www.cnki.com.cn/Article/CJFDTOTAL-ZWZZ403.002.htm
    [33] Yin X Y. A nonlinear model to quantify temperature effect on rice phenology and its application. Acta Agronomica Sinica, 1994, 20(6): 692-700.
    [34] Wu D, Wang P, Jiang C, et al. Use of a plastic temperature response function reduces simulation error of crop maturity date by half. Agr Forest Meteorol, 2020, 280: 107770. doi:  10.1016/j.agrformet.2019.107770
    [35] 黄秋燕, 覃志豪, 覃梓洪, 等. 甘蔗灾害监测研究进展及展望. 中国农业信息, 2018, 30(3): 23-40. https://www.cnki.com.cn/Article/CJFDTOTAL-NXTS201803005.htm

    Huang Q Y, Qin Z H, QiN Z H, et al. Research progress and prospect on the monitoring of sugarcane disaster. China Agricultural Informatics, 2018, 30(3): 23-40. https://www.cnki.com.cn/Article/CJFDTOTAL-NXTS201803005.htm
    [36] 李祎君, 王春乙, 赵蓓, 等. 气候变化对中国农业气象灾害与病虫害的影响. 农业工程学报, 2010, 26(增刊I): 263-271. https://www.cnki.com.cn/Article/CJFDTOTAL-NYGU2010S1049.htm

    Li Y J, Wang C Y, Zhao B, et al. Effects of climate change on agricultural meteorological disaster and crop insects diseases. Transactions of the Chinese Society of Agricultural Engineering, 2010, 26(Suppl I): 263-271. https://www.cnki.com.cn/Article/CJFDTOTAL-NYGU2010S1049.htm
    [37] 潘小军, 张忠斌, 蒲成毅. 全球气候异常下甘蔗气象灾害风险分析. 保险研究, 2014(12): 51-58. https://www.cnki.com.cn/Article/CJFDTOTAL-BXYJ201412007.htm

    Pan X J, Zhang Z B, Pu C Y. Risk analysis of sugarcane meteorological disaster under global climate anomaly. Insurance Studies, 2014(12): 51-58. https://www.cnki.com.cn/Article/CJFDTOTAL-BXYJ201412007.htm
    [38] 李莉, 匡昭敏, 莫建飞, 等. 广西甘蔗秋旱灾害风险评估技术初步研究. 应用气象学报, 2016, 27(1): 95-101. doi:  10.11898/1001-7313.20160110

    Li L, Kuang Z M, Mo J F, et al. Assessment of autumn drought risk of sugarcane in Guangxi. J Appl Meteor Sci, 2016, 27(1): 95-101. doi:  10.11898/1001-7313.20160110
    [39] 匡昭敏, 李强, 尧永梅, 等. EOS/MODIS数据在甘蔗寒害监测评估中的应用. 应用气象学报, 2009, 20(3): 360-364. doi:  10.3969/j.issn.1001-7313.2009.03.013

    Kuang Z M, Li Q, Yao Y M, et al. Application of EOS/MODIS data to monitoring sugarcane cold damage. J Appl Meteor Sci, 2009, 20(3): 360-364. doi:  10.3969/j.issn.1001-7313.2009.03.013
    [40] 廖东声, 覃思静. 广西甘蔗产业生产成本核算及控制问题分析. 学术论坛, 2013(8): 83-87. doi:  10.3969/j.issn.1004-4434.2013.08.018

    Liao D S, Qin S J. Analysis on production cost accounting and control of sugarcane industry in Guangxi. Academic Forum, 2013(8): 83-87. doi:  10.3969/j.issn.1004-4434.2013.08.018
    [41] Inman-bamber N G, Everingham Y L, Muchow R C. Modelling Water Stress Response in Sugarcane: Validation and Application of the APSIM-Sugarcane Model. (2001-02-01)[2020-12-08]. http://www.regional.org.au/au/asa/2001/6/d/inmanbamber.htm.
    [42] Keating B A, Robertson M J, Muchow R C, et al. Modelling sugarcane production systems Ⅰ. Development and performance of the sugarcane module. Field Crop Res, 1999, 61(3): 253-271. doi:  10.1016/S0378-4290(98)00167-1
    [43] Liu D L, Bull T A. Simulation of biomass and sugar accumulation in sugarcane using a process-based model. Ecol Model, 2001, 144(2/3): 181-211.
    [44] Inman-Bamber N G. A growth model for sugar-cane based on a simple carbon balance and the CERES-Maize water balance. South African Journal of Plant and Soil, 1991, 8(2): 93-99. doi:  10.1080/02571862.1991.10634587
    [45] Leary G J O. A review of three sugarcane simulation models with respect to their prediction of sucrose yield. Field Crop Res, 2000, 68(2): 97-111. doi:  10.1016/S0378-4290(00)00112-X
    [46] 王培娟, 马玉平, 霍治国, 等. 土壤水分对冬小麦叶片光合速率影响模型构建. 应用气象学报, 2020, 31(3): 267-279. doi:  10.11898/1001-7313.20200302

    Wang P J, Ma Y P, Huo Z G, et al. Construction of the model for soil moisture effects on leaf photosynthesis rate of winter wheat. J Appl Meteor Sci, 2020, 31(3): 267-279. doi:  10.11898/1001-7313.20200302
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  • 收稿日期:  2021-03-20
  • 修回日期:  2021-06-09
  • 刊出日期:  2021-09-30

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