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Journal of Integrative Agriculture  2013, Vol. 12 Issue (1): 45-56    DOI: 10.1016/S2095-3119(13)60204-X
PHYSIOLOGY & BIOCHEMISTRY · TILLAGE · CULTIVATION Advanced Online Publication | Current Issue | Archive | Adv Search |
Spatial and Temporal Characteristics of Rice Potential Productivity and Potential Yield Increment in Main Production Regions of China
 JIANG Xiao-jian, TANG Liang, LIU Xiao-jun, CAO Wei-xing , ZHU Yan
National Engineering and Technology Center for Information Agriculture, Ministry of Industry and Information Technology/Key Laboratory for Information Agriculture, Science and Technology Department of Jiangsu Province/College of Agriculture, Nanjing Agricultural University, Nanjing 210095, P.R.China
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摘要  The vast area and marked variation of China make it difficult to predict the impact of climate changes on rice productivity in different regions. Therefore, analyzing the spatial and temporal characteristics of rice potential productivity and predicting the possible yield increment in main rice production regions of China is important for guiding rice production and ensuring food security. Using meteorological data of main rice production regions from 1961 to 1970 (the 1960s) and from 1996 to 2005 (the 2000s) provided by 333 stations, the potential photosynthetic, photo-thermal and climatic productivities in rice crop of the 1960s and 2000s in main rice production regions of China were predicted, and differences in the spatial and temporal distribution characteristics between two decades were analyzed. Additionally, the potential yield increment based on the high yield target and actual yield of rice in the 2000s were predicted. Compared with the 1960s, the potential photosynthetic productivity of the 2000s was seen to have decreased by 5.40%, with rates in northeastern and southwestern China found to be lower than those in central and southern China. The potential photo-thermal productivity was generally seen to decrease (2.56%) throughout main rice production regions, decreasing most in central and southern China. However, an increase was seen in northeastern and southwestern China. The potential climatic productivity was observed to be lower (7.44%) in the 2000s compared to the 1960s, but increased in parts of central and southern China. The potential yield increment from the actual yield to high yield target in the 2000s were no more than 6×103 kg ha-1 and ranged from 6×103 to 12×103 kg ha-1 in most of the single- and double-cropping rice growing regions, respectively. The yield increasing potential from the high yield target to the potential photo-thermal productivity in 2000s were less than 10×103 kg ha-1 and ranged from 10×103 to 30×103 kg ha-1 in most of the single- and double-cropping rice growing regions, respectively. The potential yield increment contributed by irrigation was between 5×103 and 20×103 kg ha-1, and between 20×103 and 40×103 kg ha-1 in most of the single- and double-cropping rice growing regions, respectively. These findings suggested that the high yield could be optimized by making full use of climatic resources and through a reasonable management plan in rice crop.

Abstract  The vast area and marked variation of China make it difficult to predict the impact of climate changes on rice productivity in different regions. Therefore, analyzing the spatial and temporal characteristics of rice potential productivity and predicting the possible yield increment in main rice production regions of China is important for guiding rice production and ensuring food security. Using meteorological data of main rice production regions from 1961 to 1970 (the 1960s) and from 1996 to 2005 (the 2000s) provided by 333 stations, the potential photosynthetic, photo-thermal and climatic productivities in rice crop of the 1960s and 2000s in main rice production regions of China were predicted, and differences in the spatial and temporal distribution characteristics between two decades were analyzed. Additionally, the potential yield increment based on the high yield target and actual yield of rice in the 2000s were predicted. Compared with the 1960s, the potential photosynthetic productivity of the 2000s was seen to have decreased by 5.40%, with rates in northeastern and southwestern China found to be lower than those in central and southern China. The potential photo-thermal productivity was generally seen to decrease (2.56%) throughout main rice production regions, decreasing most in central and southern China. However, an increase was seen in northeastern and southwestern China. The potential climatic productivity was observed to be lower (7.44%) in the 2000s compared to the 1960s, but increased in parts of central and southern China. The potential yield increment from the actual yield to high yield target in the 2000s were no more than 6×103 kg ha-1 and ranged from 6×103 to 12×103 kg ha-1 in most of the single- and double-cropping rice growing regions, respectively. The yield increasing potential from the high yield target to the potential photo-thermal productivity in 2000s were less than 10×103 kg ha-1 and ranged from 10×103 to 30×103 kg ha-1 in most of the single- and double-cropping rice growing regions, respectively. The potential yield increment contributed by irrigation was between 5×103 and 20×103 kg ha-1, and between 20×103 and 40×103 kg ha-1 in most of the single- and double-cropping rice growing regions, respectively. These findings suggested that the high yield could be optimized by making full use of climatic resources and through a reasonable management plan in rice crop.
Keywords:  rice       photosynthetic productivity       photo-thermal productivity       climatic productivity       yield increment       spatial and temporal       distribution       China  
Received: 06 December 2011   Accepted:
Fund: 

This research was jointly supported by the Key Technologies R&D Program of China during the 12th Five-Year Plan period (2011BAD21B03), the National Basic Research Program of China (2009CB118608), and the Priority Academic Program Development of Jiangsu Higher Education Institutions, China (PAPD).

Corresponding Authors:  Correspondence ZHU Yan, Tel: +86-25-84396598, Fax: +86-25-84396672, E-mail: yanzhu@njau.edu.cn     E-mail:  yanzhu@njau.edu.cn

Cite this article: 

JIANG Xiao-jian, TANG Liang, LIU Xiao-jun, CAO Wei-xing , ZHU Yan. 2013. Spatial and Temporal Characteristics of Rice Potential Productivity and Potential Yield Increment in Main Production Regions of China. Journal of Integrative Agriculture, 12(1): 45-56.

[1]Bouman B A M, van Keulen H, van Laar H H, Rabbinge R.1996. The “School of de Wit” crop growth simulationmodels: a pedigree and historical overview.Agricultural Systems, 52, 171-198

[2]Cao W X, Luo W H. 2000. Crop System Simulation andIntelligence Management. Huawen Press, Beijing. (inChinese)

[3]Cao W X, Zhu Y. 2004. Crop Management KnowledgeModel. China Agricultural Press, Beijing. (in Chinese)

[4]Chavas D R, Izaurralde R C, Thomason AM, Gao X J. 2009.Long-term climate change impacts on agriculturalproductivity in eastern China. Agricultural and ForestMeteorology, 149, 1119-1128

[5]Chen H, Wang J Y, Lin J, Pan W H, Li L C, Cai W H. 2008.Productivity potential of climate-soil for doublecropping rice in Fujian Province based on GIStechnology. Chinese Journal of Ecology, 27, 1104-1108

[6](in Chinese)Chen L X, Shao Y N, Zhang Q F, Ren Z T, Tian G S. 1991.Preliminary analysis of climatic change during the last39 years in China. Quarterly Journal of AppliedMeteorology, 2, 164-174

[7](in Chinese)Chen L X, Zhou X J, Li W L, Luo Y F, Zhu W Q. 2004.Characteristics of the climate change and its formationmechani sm in China in last 80 years. ActaMeteorologica Sinica, 62, 634-646

[8](in Chinese)Chen L X, Zhu W Q, Wang W, Zhou X J, Li W L. 1998.Studies on climate changes in China in recent 45 years.Acta Meteorologica Sinica, 56, 257-271 (in Chinese)

[9]Chen Y M, Guo G S, Wang G X, Kang S Z, Luo H B, ZhangD Z. 1993. Research on the Contour Map of MajorCrop Water Requirement in China. China AgriculturalScience and Technology Press, Beijing. (in Chinese)

[10]Chen Z M, Liao Y P, Chen S J, He X Y, Chen Y H. 1999. Anew indica rice variety with high harvest index and goodgrain quality. Chinese Journal of Rice Science, 13, 61.(in Chinese)

[11]Collaborative Group of China’s Major Crop Water ContourMap. 1995. Main Crop Water Requirement andIrrigation of China. China Water Power Press, Beijing.(in Chinese)

[12]Coelho D T, Dale R F. 1980. An energy-crop growth variableand temperature function for predicting corn growthand development: planting to silking. AgronomyJournal, 72, 503-516

[13]Consultative Group on International Agricultural Research.2004. The CGIAR Consortium for Spatial Information.[2007-10-20]. http://srtm.csi.cgiar.org/selection/inputCoord.asp

[14]Ding Y H, Lin E D, He J K. 2009. Climate Change Researchover China: Science, Impact, Adaptation and StrategyPolicy. China Environmental Science Press, Beijing. (in Chinese)

[15]vans L T, Fischer RA. 1999. Yield potential: its definition,measurement, and significance. Crop Science, 39,1544-1551

[16]Fischer G, van Velthuizen H, Shah M, Nachtergaele F O.2002. Global agro-ecological assessment for agriculturein the 21st century: methodology and results. In:International Institute for Applied Systems Analysis.Laxenburg, Austria.

[17]He Y, Theakstone W H, Zhang Z L, Zhang D, Yao T D,Chen T, Shen Y P, Pang H X. 2004. AsynchronousHolocene climatic change across China. QuaternaryResearch, 61, 52-63

[18]Hijmans R J, Cameron S E, Parra J L, Jones P G, Jarvis A.2005. Very high resolution interpolated climate surfacesfor global land areas. International Journal ofClimatology, 25, 1965-1978

[19]Hoogenboom G. 2000. Contribution of agrometeorology tothe simulation of crop production and its application.Agricultural and Forest Meteorology, 103, 137-157

[20]Hutchinson M F. 2004. ANUSPLIN Version 4.3 User Guide.Center for Resource and Environment Studies, AustraliaNational University, Canberra.

[21]Jiang X J, Liu X J, Huang F, Jiang H Y, Cao W X, Zhu Y.2010. Comparison of spatial interpolation methods fordaily meteorological elements. Chinese Journal ofApplied Ecology, 21, 624-630 (in Chinese)

[22]Jiang X J, Tang L, Liu X J, Huang F, Cao,WX, Zhu Y. 2011.Spatial and temporal characteristics of rice productionclimatic resources in main growing regions of China.Transactions of the CSAE, 27, 238-245. (in Chinese)

[23]Jiao X F, Yang B X, Fei Z Y. 2006. Paddy rice area estimationusing a stratified sampling method with remote sensingin China. Transactions of the CSAE, 22, 105-110. (inChinese)

[24]Jones JW, Hoogenboom G, Porter C H, Boote K J, BatchelorW D, Hunt L A, Wilkens P W, Singh U, Gijsman A J,Ritchie J T. 2003. The DSSAT cropping system model.European Journal of Agronomy, 18, 235-265

[25]Katz R W. 2002. Techniques for estimating uncertainty in climate change scenarios and impact studies. ClimateResearch, 20, 167-185

[26]Keating B A, Carberry P S, Hammer G L, Probert M E,Robertson M J, Holzworth D, Huth N I, Hargreaves J N G,Meinke H, Hochman Z, et al. 2003.An overview ofAPSIM,a model designed for farming systems simulation.European Journal of Agronomy, 18, 267-288

[27]Liao YP, Chen ZM, He X Y, Chen S J, Chen YH. 2001. Sink,source and flow characteristics of rice varietyYuexiangzhan with high harvest index. Chinese Journalof Rice Science, 15, 73-76 (in Chinese)

[28]Liu X J, Cao J, Li Y D, Zhang Y P, Cao WX, Zhu Y. 2010. Aknowledge model for precision water management in rice.Scienica Agricultura Sinica, 43, 1571-1576 (in Chinese)

[29]Liu Z H, McVicar T R, Li L T, van Nie T G, Yang Q K, Li R,Mu X M. 2008. Interpolation for time series ofmeteorological variables using ANUSPLIN. Journal ofNorthwest A&F University (Natural Science), 36, 227-234 (in Chinese)

[30]Long S Y. 1985. The survey for potential productivity ofagroclimatic resources and its regionization in JiangsuProvince. Scientia Geographica Sinica, 5, 218-226 (in Chinese)

[31]Loomis R S, Williams W A. 1963. Maximum cropproductivity: an estimate. Crop Science, 3, 67-72

[32]Masutomi Y, Takahashi K, Harasawa H, Matsuoka Y. 2009.Impact assessment of climate change on rice productionin Asia in comprehensive consideration of process/parameter uncertainty in general circulation models.Agriculture, Ecosystems and Environment, 131, 281-291

[33]Mei F Q, Wu X Z, Yao C X, Li L P, Wang L, Chen Q Y. 1988.Rice cropping regionalization in China. Chinese Journalof Rice Science, 2, 97-110 (in Chinese)

[34]Ministry of Agriculture of China. 2009. The TechnicalSpecification Model Maps for Rice High Yield in China.[2010-09-21] http://www.agri.gov.cn/ztzl/ql/jsms/P020090410579290158332.doc

[35]Ren G Y, Guo J, Xu M Z, Chu Z Y, Zhang L, Zou X K, Li QX, Liu X N. 2005. Climate changes of China’s mainlandover the past half century. Acta Meteorologica Sinica,63, 942-956. (in Chinese)

[36]Shackley S, Young P, Parkinson S, Wynne B. 1998.Uncertainty, complexity and concepts of good sciencein climate change modelling: are GCMs the best tools?Climate Change, 38, 159-205

[37]State Environmental Protection Administration. 2003.Progress Report of Trade Liberalization in theAgriculture Sector and the Environment, WithSpecific Focus on the Rice Sector in China. [2010-12-19] http://www.unep.ch/etb/events/Events2003/pdf/FinalDraftofChinaStudy.pdf

[38]Stehfest E, Heistermann M, Priess J A, Ojima D S, AlcamoJ. 2009. Simulation of global crop production with theecosystem model DayCent. Ecological Modelling, 209,203-219

[39]Sun H S, Huang J F, Li B, Wang H S. 2008. Study on theregionalization of paddy rice information acquirementthrough remote sensing technology in China. ScienicaAgricultura Sinica, 41, 4039-4047 (in Chinese)

[40]Tao F L, Hayashi Y, Zhang, Z, Sakamoto T, Yokozawa M.2008. Global warming, rice production, and water use inChina: developing a probabilistic assessment.Agricultural and Forest Meteorology, 148, 94-110

[41]Tao F L, Yokozawa M, Xu Y L, Hayashi Y, Zhao Z. 2006.Climate changes and trends in phenology and yields offield crops in China, 1981-2000 Agricultural and ForestMeteorology, 138, 82-92

[42]Thomas A. 2000. Spatial and temporal characteristics ofpotential evapotranspiration trends over China.International Journal of Climatology, 20, 381-396

[43]Thomas A. 2006. Climatic change and potential agriculturalproductivity in China. Erdkunde, 60, 157-172

[44]Xie L Y, Lin E D. 2007. Effects of CO2 enrichment on grainquality of rice and wheat: a research review. ChineseJournal of Applied Ecology, 18, 659-664 (in Chinese)

[45]Xie Y, Wang X L, Lin Y. 2003. Temporal and spatial variationof climatic potential productivity for grain crops inEastern China within forty years. Resources Science,25, 7-13 (in Chinese)

[46]Yan D C, Zhu Y, Wang S H, Cao W X. 2006. A quantitativeknowledge-based model for designing suitable growthdynamic in rice. Plant Production Science, 9, 93-105

[47]Yan H. 2004. Modeling spatial distribution of climate inChina using thin plate smoothing spline interpolation.Scientia Geographica Sinica, 24, 163-169. (in Chinese)

[48]Zhang J K, Zhang F R, Zhang L, Zhang D, Wu C G, Kong XB. 2006. Comparison between the potential grainproductivity and the actual grain yield of cultivatedlands in mainland China. Scienica Agricultura Sinica,39, 2278-2285 (in Chinese)

[49]Zhang S M, Zhang J M, Lee J R, Li M B, Wang H, Piao Z Z,Zou D T. 2009. The difference between starch chainlength distribution and main quality characteristics ofhigh resistant starch lines of Japonica rice. ScienicaAgricultura Sinica, 42, 2237-2243 (in Chinese)

[50]Zhou Z G, Meng Y L, Cao WX. 2005. Knowledge model andGIS-based crop potential productivity evaluation.Scienica Agricultura Sinica, 38, 1142-1147. (in Chinese)

[51]Zuo D K, Zhou Y H, Xiang Y Q, Zhu Z H, Xie X Q. 1991.Studies on Radiation in the Epigeosphere. SciencePress, Beijing. (in Chinese)Zuo H C, Lv S H, Hu Y Q. 2004. Variations trend of yearlymean air temperature and precipitation in China in thelast 50 years. Plateau Meteorology, 23, 238-244. (in Chinese)
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