基于APSIM的胡麻光合生产与干物质积累模拟模型

doi:10.11686/cyxb2017163

摘要/Abstract

摘要： 作物光合生产与干物质积累模拟模型是作物生长模型的核心,在已有作物光合作用和干物质积累模型基础上,采用辐射利用率,考虑环境因子对光合速率的影响、呼吸作用消耗同化量,构建基于生理生态过程的胡麻光合生产与干物质积累模拟模型。通过不同肥料、播种方式、种植密度及氮磷水平的初步检验,模型具有较好的模拟效果和较强的适用性。不同肥料设置,干物质积累模拟值的RMSE值为0.3486~1.9538 g·株^-1,平均为1.0467 g·株^-1,决定系数R²取值范围在0.6311~0.9832,平均为0.8532;3种播种方式的干物质积累模拟值的RMSE值为0.5685~1.1164 g·株^-1,平均为0.8692 g·株^-1,决定系数R²取值范围在0.8745~0.9662,平均为0.9282;7种种植密度干物质积累模拟值的RMSE值为0.0807~0.2086 g·株^-1,平均为0.1584 g·株^-1,R²取值范围在0.9677~0.9965,平均为0.9869;12种氮磷水平模型检验模拟值的RMSE值为0.0952~1.2375 g·株^-1,平均为0.4000 g·株^-1,R²取值范围在0.8964~0.9959,平均为0.9700。最后对APSIM模型和AquaCrop模型在现有研究基础上对不同氮磷水平胡麻生物量的模拟进行了简单对比。研究结果为进一步构建胡麻生长模型奠定基础,为应用模型分析胡麻生长及制定生产决策提供依据。

Abstract: Photosynthesis and dry matter accumulation simulation models are the core of crop growth models. Taking existing models and using radiation use efficiency, and considering the influence of environmental factors and respiration consumption on photosynthetic rate, a physiological and ecological processes model for photosynthesis and dry matter accumulation in oilseed flax was established. This model produced improved simulation and applicability during validation experiments with different sowing methods, planting density and nitrogen and phosphorus levels. For example, the root mean squared error (RMSE) value with different planting densities ranged from 0.0807 to 0.2086, with a mean of 0.1584 while the R² ranged from 0.9677 to 0.9965, mean 0.9869. The RMSE value with different nitrogen and phosphorus levels ranged from 0.0952 to 1.2375 with a mean of 0.4000 while the R² range from 0.8964 to 0.9959, mean 0.9700. The biomass simulations from this model were compared with the APSIM (Agricultural Production System Simulator) and AquaCrop (FAO Crop Model to Simulate Yield Response to Water) with different nitrogen and phosphorus levels. The results of this study lay the foundation for the further development of oilseed flax growth models, and provide the basis for the application of growth model and management decisions in flax.

李玥, 武凌, 高珍妮, 牛俊义. 基于APSIM的胡麻光合生产与干物质积累模拟模型[J]. 草业学报, 2018, 27(3): 57-66.

LI Yue, Wu Ling, Gao Zhen-ni, Niu Jun-yi. Simulation model of photosynthesis and dry matter accumulation in oilseed flax based on APSIM[J]. Acta Prataculturae Sinica, 2018, 27(3): 57-66.

参考文献

[1] de Wit C T. Photosynthesis of leaf canopies//Agricultural research report No. 663. Wageningen, The Netherlands: Pudoc, 1965: 663-671.
[2] Duncan W G, Loomis R S, Williams W A, et al. A model for simulating photosynthesis in plant communities. Hilgardia, 1967, 38: 181-205.
[3] van Keulen H, Penning de Vries F W T, Drees E M. A summary model for crop growth//Penning de Vries F W T, van Laar H H. Simulation of crop growth and crop production. Wageningen, The Netherlands: Pudoc, 1982: 87-97.
[4] Penning de Vries F W T, Jansen D M, Ten Berge H F M. Simulation of ecophysiological process of growth in several annual crops. Wageningen, The Netherlands: Simulation Monographs, Pudoc, 1989: 271.
[5] Kropff M J, van Laar H H, Mathews, et al. ORYZAI: An eco-physiological model for irrigated rice production. Wageningen, The Netherlands: Pudoc, 1994: 35-40.
[6] Bouman B A M, Kropff M J, Tuong T P, et al. ORYZA2000: Modeling lowland rice. Wageningen, The Netherlands: Pudoc, 2000: 50-90.
[7] Jones C A, Kiniry J R.CERES-Maize: A simulation model of maize growth and development. College Station, United States: Texas A & M University Press, 1986: 89-110.
[8] Ritchie J T, Otter S.Description and performance of CERES-Wheat: a user-oriented wheat yield model. ARS Wheat Yield Project, 1985, 38: 159-175.
[9] Marcelis L F M, Heuvelink E, Goudriaan J. Modelling biomass production and yield of horticultural crops: a review. Scientia Horticulturea, 1998, 74: 83-111.
[10] Liu T M.Simulation on photosynthetic production and dry matter partitioning in wheat. Nanjing: Nanjing Agricultural University, 2000.
刘铁梅. 小麦光合生产与物质分配的模拟模型. 南京: 南京农业大学, 2000.
[11] Zhang L Z, Cao W X, Zhang S P, et al. A process model of photosynthetic production and dry matter accumulation in cotton. Cotton Science, 2003, 15(3): 138-145.
张立祯, 曹卫星, 张思平, 等. 棉花光合生产与干物质积累过程的模拟. 棉花学报, 2003, 15(3): 138-145.
[12] Zhu Y J, Feng L P, Yi P, et al. A dynamic model simulating photosynthetic production and dry matter accumulation for alfalfa (Medicago sativa L.). Acta Agronomical Sinica, 2007, 33(10): 1682-1687.
朱玉洁, 冯利平, 易鹏, 等. 紫花苜蓿光合生产与干物质积累模拟模型研究. 作物学报, 2007, 33(10): 1682-1687.
[13] Xue L.Study of development simulation models in sesame. Nanjing: Nanjing Agricultural University, 2012.
薛林. 芝麻生长发育模拟模型研究. 南京: 南京农业大学, 2012.
[14] Zhang Y J.Study on direct-seeding rapeseed growth simulation model. Wuhan: Huazhong Agricultural University, 2013.
张亚杰. 直播油菜生长模拟模型的研究. 武汉: 华中农业大学, 2013.
[15] Zou W.A process-based simulation model on barley growth and development. Nanjing: Nanjing Agricultural University, 2009.
邹薇. 基于过程的大麦生长发育模拟模型. 南京: 南京农业大学, 2009.
[16] Gabrielle B, Denoroy P, Gosse G, et al. Development and evaluation of a CERES-type model for winter oilseed rape. Field Crops Research, 1998, 57(1): 95-111.
[17] Tang L, Zhu Y, Ju C H, et al. Dynamic simulation on shoot dry matter partitioning and yield formation of rapeseed. Chinese Journal of Applied Ecology, 2007, 18(3): 526-530.
汤亮, 朱艳, 鞠昌华, 等. 油菜地上部干物质分配与产量形成模拟模型. 应用生态学报, 2007, 18(3): 526-530.
[18] Habekotte B.A model of the phonological development of winter oilseed rape (Brassica napus L.). Field Crops Research, 1997, 54: 127-136.
[19] Habekotte B.Description, parameterization and user guide of LINTUL-BRASNAP 1.1. A crop growth model of winter oilseed rape(Brassica napus L.). Wageningen, The Netherlands: Quant Appr (Annual Participatory Programme Review) System Annual, 1997.
[20] Keating B A, Carberry P S, Hammer G L, et al. An overview of APSIM, a model designed for farming systems simulation. European Journal of Agronomy, 2003, 18(3): 267-288.
[21] Robertson M J, Holland J F, Kirkegaard J, et al. Simulating growth and development of canola in Australia. Canberra: Proceedings of the 10th International Rapeseed Congress, 1999.
[22] GB/T 32737-2016, Determination of nitrogen in soil-ultraviolet spectrophotometry methodB/T 32737-2016, Determination of nitrogen in soil-ultraviolet spectrophotometry method. Beijing: China Standard Press, 2016.
GB/T 32737-2016, 土壤硝态氮的测定-紫外分光光度法B/T 32737-2016, 土壤硝态氮的测定-紫外分光光度法. 北京: 中国标准出版社, 2016.
[23] Qian B, Liu L, Xiao X.Comparison and analysis of soil organic matter determination method. Journal of Hehai University (Natural Science Edition), 2011, (1): 36-38.
钱宝, 刘凌, 肖潇. 土壤有机质测定方法对比分析. 河海大学学报(自然科学版), 2011, (1): 36-38.
[24] Hua M, Wang J.Soil physics. Beijing: Beijing Agricultural University Press, 1993: 38.
华孟, 王坚. 土壤物理学. 北京: 北京农业大学出版社, 1993: 38.
[25] Laboratory of Soil Physics, Nanjing Soil Research Institute, Chinese Academy of Sciences. Determination of physical properties of soils. Beijing: Science Press, 1978: 10.
中国科学院南京土壤研究所土壤物理研究室. 土壤物理性质测定法. 北京: 科学出版社, 1978: 10.
[26] Gong Z P.Soil science and agriculture science. Beijing: China Water & Power Press, 2009.
龚振平. 土壤学与农作学. 北京: 中国水利水电出版社, 2009.
[27] Rural Water Resources Department of the Ministry of Water Resources. Classification and observation standard of main crops growth period. (2012-07-06) [2017-11-18]. .
Classification and observation standard of main crops growth period. (2012-07-06) [2017-11-18]. http://www.docin.com/p-436365186.html.
水利部农村水利司. 主要作物生育时期划分及观测标准. (2012-07-06) [2017-11-18]. . 主要作物生育时期划分及观测标准. (2012-07-06) [2017-11-18]. http://www.docin.com/p-436365186.html.
[28] Zong M, Wu G L, Zheng A F.Improvement of experiment on the plant photosynthetic intensity of the improved half-method. Modern Agricultural Science and Technology, 2011, 4: 30-33.
宗梅, 吴甘霖, 郑爱芳. 改良半叶法测定植物光合强度实验的改进. 现代农业科技, 2011, 4: 30-33.
[29] Commonwealth Scientific and Industrial Research Organisation. Agricultural production system simulator. (2014-03-25) [2015-11-01]. . Agricultural production system simulator. (2014-03-25) [2015-11-01]. http://www.apsim.info.
[30] Roderick M L.Estimating the diffuse component from daily and monthly measurements of global radiation. Agricultural and Forest Meteorology, 1999, 95(3): 169-185.
[31] Reyenga P J, Howden S M, Meinke H, et al. Modelling global change impacts on wheat cropping in south-east Queensland, Australia. Environmental Modelling & Software, 1999, 14(4): 297-306.
[32] Sinclair T R.Water and nitrogen limitations in soybean grain production. I. Model development. Field Crops Research, 1986, 15(2): 125-141.
[33] McCree K. Equations for the rate of dark respiration of white clover and grain sorghum, as functions of dry weight, photosynthetic rate, and temperature. Crop Science, 1974, 14(4): 509-514.
[34] Goudriaan J, Van Laar H H. Modelling potential crop growth processes: Textbook with exercises. Dordrecht: Kluwer Academic Publishers, 1994: 175-195.
[35] Tanner C B, Endo T R.Efficient water use in crop production: research or re-search//Taylor H M, Jordan W R, Sinclair T R. Limitations to efficient water use in crop production. Madison Wisconsin: American Society of Agronomy, 1983: 1-27.
[36] Li Y, Niu J Y, Guo L Z, et al. Application and validation of AquaCrop model in simulating biomass and yield of oil flax in Northwest China. Chinese Journal of Eco-Agriculture, 2014, 22(1): 93-103.
李玥, 牛俊义, 郭丽琢, 等. AquaCrop模型在西北胡麻生物量及产量模拟中的应用和验证. 中国生态农业学报, 2014, 22(1): 93-103.
[37] Farré M J, Robertson G H, Walton S, et al. Simulating response of canola to sowing date in western Australia. Hobart, Tasmania: 10th Australian Agronomy Conference, 2000.
[38] Robertson M J, Holland J, Cawley S, et al. Phenology of canola cultivars in the northern region and implications for frost risk. Hobart, Tasmania: 10th Australian Agronomy Conference, 2001.
[39] Fu Q.Data processing methods and their agricultural applications. Beijing: Science Press, 2006.
付强. 数据处理方法及其农业应用. 北京: 科学出版社, 2006.
[40] Asseng S, Fillery I R P, Anderson G C, et al. Use of the APSIM wheat model to predict yield, drainage, and NO₃^- leaching for deep sand. Australian Journal of Experimental Agriculture, 1998, 49(3): 363-378.
[41] Asseng S, Foster I, Turner N C.The impact of temperature variability on wheat yields. Global Change Biology, 2011, 17(2): 997-1012.
[42] Asseng S, Keating B A, Fillery I R P, et al. Performance of the APSIM-wheat model in Western Australia. Field Crops Research, 1998, 57(2): 163-179.
[43] Hochman Z, Dang Y P, Schwenke G D, et al. Simulating the effects of saline and sodic subsoils on wheat crops growing on vertisols. Australian Journal of Agricultural Research, 2007, 58(8): 802-810.