精准农业变量施肥理论与试验研究
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摘要
本研究针对精准农业技术体系中变量施肥这一关键环节，围绕变量施肥处方生成技术及应用系统开发，探讨了土壤养分空间分布图生成技术，提出了产量数据的误差处理方法，模拟研究了变量施肥的尺度效应问题，设计并开发了具有田间导航采样、产量数据处理和决策支持功能的变量施肥处方生成系统。通过初步的实践验证和应用效果分析，本研究成果有较好的实用价值。主要研究结果包括：
1．围绕土壤养分空间分布图生成，研究了土壤采样策略制定方法，探讨了采用Cokriging方法降低采样密度和采用电导率综合评价土壤生产潜力的可能性。结果表明，在进行土壤养分采样和插值，必须同时考虑养分的空间变异性和数值变异性，而N／S值和变异系数是比较好的指标；产量与0-30.5.cm、0-91.5cm、30.5-91.5cm三层土壤电导率之间都存在极显著的负相关关系，二次多项式较好地拟合了产量与电导率的关系，电导率图可以参与进行土壤生产潜力区的划分。
2．研究分析产量数据的获取过程，采用层次分析的原则，将可能造成产量数据误差的因素归纳为直接因素、间接因素和产生原因。分别针对不同产量数据的误差来源，设计并实现了5种过滤器：产量域值过滤器，速度过滤器、填充和清空延时过滤器、邻域均值过滤器、邻域系数过滤器；在分析比较不同过滤器过滤效果的基础上，提出了1种综合过滤器，过滤后使产量数据的正态分布性得到显著改善，对已测产小区的估计误差明显下降。
3．针对精准变量施肥的尺度问题，采用计算机模拟技术，研究不同土壤硝态氮均值、方差和相关距下，施肥单元面积对玉米的平均施肥量、产量和肥料增产效率的影响。结果表明：a．随着变量施肥单元面积的减小，平均单位面积的施肥量增加或保持不变，产量一般增加，肥料增产效率也增加；b．随着土壤养分均值增加，平均施肥量降低，平均产量增加，肥料增产效率降低，且施肥单元面积越大，不同土壤养分均值间的施肥量、产量和肥料增产效率的差异越大；c．在养分均值低于施肥临界土壤养分浓度时，随着土壤养分变异系数的增加，平均施肥量增加，平均产量降低，肥料增产效率降低；d．随着土壤养分相关距的增加，平均施肥量增加，平均产量增加，肥料增产效率增加。这些结果对我们进行变量施肥的实践有一定的指导意义。
4．在分析变量施肥决策流程的基础上，采用OLE/ActiveX技术，设计并实现了集成应用GPS、GIS和ES技术的变量施肥处方生成系统。该系统在推理机中嵌入模型语法分析构件，并采用对象连接和嵌入的自动化方式实现与GIS功能构件之间的互操作功能；将知识／模型／数据采用一体化方法存储在数据库中，通过ODBC规范实现基于多数据源的知识调度与推理；应用基于矢量网格的空间叠加分析方法解决了栅格和常规矢量数据结构在处方生成中的局限。系统可以提供田间导航采样、产量数据处理和决策支持功能，最终生成可供变量施肥机具使用的处方图，可以用于指导变量施肥实践。
5．进行了基于土壤肥力测定和基于地物光谱数据的小麦变量施肥试验研究，结果表明，在施肥总量相同的情况下，与常规均一施肥对照区相比，变量施肥使产量略降，穗粒数、千粒重、叶绿素和蛋白质变异系数增大，但降低了土壤硝态氮浓度，减小了污染地下水的可能性，生态效果明显。
Variable-rate fertilization is one of the key technologies in precision farming. In this dissertation, different topics related to variable-rate fertilization prescription were studied. Soil sampling strategies and yield data processing technologies were analyzed and studied, the influence of management zone size on variable-rate fertilization was studied theoretically, and DSS for variable-rate fertilization precision was also designed and implemented. According to the experiment, these results can provide support for variable-rate fertilization implementation. The main results are as follows:
1. Soil nutrients in the same locations are statistically related to each other and spatially related. Both spatial variability and traditional statistics need to be considered in sampling and interpolation of soil nutrients. N/S value and CV are good indicators of spatial variability and traditional statistics. Soil EC is a compositive indicator of soil physical-chemical properties and can show the productivity of farmland to certain extent. Veris 3100 EC Meter is a type of quick and cheap equipment for acquirement of soil system information.
2. The acquisition process of yield data was studied, and the principle of AHP (Analytic Hierarchy Process) was applied to systematically classify factors leading to yield data errors into direct and indirect factors. Five types of filters were designed and realized to deal with different error sources in yield data, including yield limits filter, harvester speed filter, filling and cleaning delay filter, neighbor mean filter, and neighbor coefficient filter. Based on analysis of different filters, a synthesized filter was provided to filter outliers in yield data for acquirement of reliable yield map.
3. The influence of management zone size on variable-rate fertilization under different soil fertilities was studied. Field distribution dataset series of soil nitrate concentration in 500X500m2 field were generated based on given values of mean, standard deviation and related distance. Each dataset is composed of nitrate concentration values in 104 cells, with the unit cell size of 5x5 m2. The fertilization rate was calculated using the fertilization models established by D.W. Franzen and L.J. Cihacek in North Dakota based on a common potential yield and the mean value hi each management cell size. The yield was calculated based on combination of fertilization amount and soil nitrate storage in each location with the same yield potential. Based on the fertilization rate and yield, the NUE (nitrogen use efficiency, yield increment with unit weight of fertilizer) was calculated. The result shows increasing or constant fertilization rate, increasing yield and NUE when the size of management zone for variable rate fertilization decreased. When the soil fertility increased, the fertilization rate decreased and the yield and NUE increased. As the management zone for variable rate fertilization becomes larger, the difference of the fertilization rate, yield and NUE between different soil fertility levels becomes more significant With the increase of standard deviation, the increment of the fertilization rate from large management zone size to small management size scale 1 to 100 become quicker, the difference of yield between different soil fertility levels at the same management zone size become larger, and the difference of the NUE between different soil fertility levels at the same management zone size become smaller.
4. Based on analysis of variable rate fertilization decision-making process, OLE/ActiveX
technologies were applied to integrated GPS, GIS, ES and MS into decision support system, which has the functions of navigation for sampling, yield map processing, decision support function, and variable-rate fertilization prescription. Analytic component of model expression was embedded into the inference engine. The OLE and automation made it possible for inter-operation between the system and GIS functional components. Knowledge, models,
1．围绕土壤养分空间分布图生成，研究了土壤采样策略制定方法，探讨了采用Cokriging方法降低采样密度和采用电导率综合评价土壤生产潜力的可能性。结果表明，在进行土壤养分采样和插值，必须同时考虑养分的空间变异性和数值变异性，而N／S值和变异系数是比较好的指标；产量与0-30.5.cm、0-91.5cm、30.5-91.5cm三层土壤电导率之间都存在极显著的负相关关系，二次多项式较好地拟合了产量与电导率的关系，电导率图可以参与进行土壤生产潜力区的划分。
2．研究分析产量数据的获取过程，采用层次分析的原则，将可能造成产量数据误差的因素归纳为直接因素、间接因素和产生原因。分别针对不同产量数据的误差来源，设计并实现了5种过滤器：产量域值过滤器，速度过滤器、填充和清空延时过滤器、邻域均值过滤器、邻域系数过滤器；在分析比较不同过滤器过滤效果的基础上，提出了1种综合过滤器，过滤后使产量数据的正态分布性得到显著改善，对已测产小区的估计误差明显下降。
3．针对精准变量施肥的尺度问题，采用计算机模拟技术，研究不同土壤硝态氮均值、方差和相关距下，施肥单元面积对玉米的平均施肥量、产量和肥料增产效率的影响。结果表明：a．随着变量施肥单元面积的减小，平均单位面积的施肥量增加或保持不变，产量一般增加，肥料增产效率也增加；b．随着土壤养分均值增加，平均施肥量降低，平均产量增加，肥料增产效率降低，且施肥单元面积越大，不同土壤养分均值间的施肥量、产量和肥料增产效率的差异越大；c．在养分均值低于施肥临界土壤养分浓度时，随着土壤养分变异系数的增加，平均施肥量增加，平均产量降低，肥料增产效率降低；d．随着土壤养分相关距的增加，平均施肥量增加，平均产量增加，肥料增产效率增加。这些结果对我们进行变量施肥的实践有一定的指导意义。
4．在分析变量施肥决策流程的基础上，采用OLE/ActiveX技术，设计并实现了集成应用GPS、GIS和ES技术的变量施肥处方生成系统。该系统在推理机中嵌入模型语法分析构件，并采用对象连接和嵌入的自动化方式实现与GIS功能构件之间的互操作功能；将知识／模型／数据采用一体化方法存储在数据库中，通过ODBC规范实现基于多数据源的知识调度与推理；应用基于矢量网格的空间叠加分析方法解决了栅格和常规矢量数据结构在处方生成中的局限。系统可以提供田间导航采样、产量数据处理和决策支持功能，最终生成可供变量施肥机具使用的处方图，可以用于指导变量施肥实践。
5．进行了基于土壤肥力测定和基于地物光谱数据的小麦变量施肥试验研究，结果表明，在施肥总量相同的情况下，与常规均一施肥对照区相比，变量施肥使产量略降，穗粒数、千粒重、叶绿素和蛋白质变异系数增大，但降低了土壤硝态氮浓度，减小了污染地下水的可能性，生态效果明显。
Variable-rate fertilization is one of the key technologies in precision farming. In this dissertation, different topics related to variable-rate fertilization prescription were studied. Soil sampling strategies and yield data processing technologies were analyzed and studied, the influence of management zone size on variable-rate fertilization was studied theoretically, and DSS for variable-rate fertilization precision was also designed and implemented. According to the experiment, these results can provide support for variable-rate fertilization implementation. The main results are as follows:
1. Soil nutrients in the same locations are statistically related to each other and spatially related. Both spatial variability and traditional statistics need to be considered in sampling and interpolation of soil nutrients. N/S value and CV are good indicators of spatial variability and traditional statistics. Soil EC is a compositive indicator of soil physical-chemical properties and can show the productivity of farmland to certain extent. Veris 3100 EC Meter is a type of quick and cheap equipment for acquirement of soil system information.
2. The acquisition process of yield data was studied, and the principle of AHP (Analytic Hierarchy Process) was applied to systematically classify factors leading to yield data errors into direct and indirect factors. Five types of filters were designed and realized to deal with different error sources in yield data, including yield limits filter, harvester speed filter, filling and cleaning delay filter, neighbor mean filter, and neighbor coefficient filter. Based on analysis of different filters, a synthesized filter was provided to filter outliers in yield data for acquirement of reliable yield map.
3. The influence of management zone size on variable-rate fertilization under different soil fertilities was studied. Field distribution dataset series of soil nitrate concentration in 500X500m2 field were generated based on given values of mean, standard deviation and related distance. Each dataset is composed of nitrate concentration values in 104 cells, with the unit cell size of 5x5 m2. The fertilization rate was calculated using the fertilization models established by D.W. Franzen and L.J. Cihacek in North Dakota based on a common potential yield and the mean value hi each management cell size. The yield was calculated based on combination of fertilization amount and soil nitrate storage in each location with the same yield potential. Based on the fertilization rate and yield, the NUE (nitrogen use efficiency, yield increment with unit weight of fertilizer) was calculated. The result shows increasing or constant fertilization rate, increasing yield and NUE when the size of management zone for variable rate fertilization decreased. When the soil fertility increased, the fertilization rate decreased and the yield and NUE increased. As the management zone for variable rate fertilization becomes larger, the difference of the fertilization rate, yield and NUE between different soil fertility levels becomes more significant With the increase of standard deviation, the increment of the fertilization rate from large management zone size to small management size scale 1 to 100 become quicker, the difference of yield between different soil fertility levels at the same management zone size become larger, and the difference of the NUE between different soil fertility levels at the same management zone size become smaller.
4. Based on analysis of variable rate fertilization decision-making process, OLE/ActiveX
technologies were applied to integrated GPS, GIS, ES and MS into decision support system, which has the functions of navigation for sampling, yield map processing, decision support function, and variable-rate fertilization prescription. Analytic component of model expression was embedded into the inference engine. The OLE and automation made it possible for inter-operation between the system and GIS functional components. Knowledge, models,
引文
[1] Akridge, Jay, and Linda Whipker. 2001． Precision agricultural services dealership survey results. Center for Agricultural Business, Purdue University, West Lafayette, IN.
[2] Andy D. Beck, Jody P. Roades, Stephen W. Searcy. Post-Process Filtering Techniques to Improve Yield Map Accuracy. Paper No.991048． Written for Presentation at the 1999 ASAE/CSAE-SCGR Annual International Meeting Sponsored by ASAE and CSAE
[3] Arslan Selcuk, Thomas S. Colvin. Grain Yield Mapping: Yield Sensing, Yield Reconstruction, and Errors, Precision Agriculture 3(1) : 81-94, March 2002
[4] Ascough J. C. II, Shaffer M J, Hanson J D, et al. The Great Plains Framework for Agricultural Resource Management (GPFARM): A Decision Support System for Whole Farm/Ranch Strategic Planning,ASAE, 1997, Paper No.975053 http://asae.org/meetings/am97/abstracts/975053 .html
[5] Atherton B C, Morgan M T, Shearer S A, et al. Site-specific farming: a perspective on information needs, benefits and limitations [J]. Journal of Soil and Water Conservation, 1999,2:455-461．
[6] Batte, M.T., Arnholt, M.W., Precision farming adoption and use in Ohio: case studies of six leading-edge adopters. Computers and Electronics in Agriculture, Feb 2003
[7] Berry, J. K. 1993． Beyond mapping: Concepts, algorithms, and issues in GIS. GIS World Books, Ft Collins, CO.
[8] Blackmore B. S., Wheeler P N, Morris R M, et al. The Role of Precision Farming in Sustainable Agriculture: A European Perspective[A]. Univ. of Minnesota, Proceedings of the 2nd International Conference on Site-Specific Management for Agriculture System[C]. Minneapolis, 1994,1-14．
[9] Blackmore, B. S. and C. J. Marshall. 1996． Yield Mapping: Errors and Algorithms. Presented at the 3rd International Conference on Precision Agriculture, Silsoe College, Canfield University
[10] Blackmore, B. S. and G. Larscheid. 1997 . Stategies for managing variability. Proc. First European Conf. On Prec. Agric. Pp851-859． Ed. J. V. Stafford. Silsoe Res. Inst, UK
[11] Bruce A Babcock and Gregory R Pautsch. Moving from uniform to variable fertilizer rates on iowa com: effects on rates and returns. J of Agri. and Res. Economics, 1998(2) :385-400
[12] Burrough P A. Soil variability: a late 20th century view. Soils and Fertilizers. 1993,56(5) :529-562．
[13] Chen J, Hopmans J W and Fogg G E. Sampling design for soil moisture measurements in large field trials. Soil Science. 1995,159(3) :155-161．
[14] Chen Liping, Zhao Chunjiang, Design and Implement of GIS/ES Integrated System Based On Interne/Intranet, Progress of Agricultural Information Technology, 2000,Beijing, 278-282
[15] Dahnke W. C., Fanning C., Cattanach A., 1992． Fertilizing Corn Grain, Popcorn, Silage Com, and Sweet Corn, www.extnodak.edu/extpubs/plantsci/soilfert/sf722w.htm.
[16] David Zilberman and Katti Millock. Pesticide use and regulation: making economic sense out of and externality and regulation nightmare. J of Agri. And Res. Economics, 1997(2) :321-332
[17] Doerge T. 1999． Soil electrical conductivity mapping. Crop Insights Vol.9, No.9． http:/www.pioneer.com/usa/technology/soil_conductivity_mapping_99． htm
[18] Engel.T.,G. Hoogenboom, J.W.Jones, and P.W.Wilkens, 1997, AEGISAVIN: A computer program for the application of crop simulation models across geographical areas, Agron.J.89:919-928．
[19] Finck, Charlene. 1998． Precision can pay its way. Farm Journal, Mid-January, p10-12．
[20] Genton Marc G., Reinhard Furrer. Analysis of rainfall data by simple good senseris spatial statistics worth the trouble. Http://www.geo.sbg.ac.at/staff/lorup/lv/geostats2003/docs/Genton Furrer.pdf
[21] George Rehm, 2002． A Multi-Disciplinary evaluation of precision farming, A final progress report (Minnesota) for 2001 prepared for United Soybean Board. Downloaded from www.farmresearch.com.
[22] Goel, P.K., Prasher, S.O., Landry, J.A., et al., Potential of airborne hyperspectral remote sensing to detect nitrogen deficiency and weed infestation in corn Computers and Electronics in Agriculture, Feb 2003
[23] Gotway, C. A., R. A. Ferguson, G. W. Hergeot, and et al., Comparison of Kriging and Inverse-Distance Methods for Mapping Soil Parameters, Soil Sci. Soc. Am. Journal 1996, 60:1237-1247
[24] Han S. Y. & Kim T.J.. ESSAS Expert System for Site Analysis & Selection. Computers, Environment and Urban System, 1988,12(4) :239-252
[25] Han, S., Hummel J.W., Goering C.E., and Cahn M.D.. 1994． Cell size selection for site-specific crop management. Trans. ASAE. 37:19-26．
[26] Han,S., S. M. Schneider,S. L. Rawlins, R. G. Evans. 1996． A Bitmap Method for Determining Effective Combine Cut Width in Yield Mapping. Transactions of the ASAE 40(2) :485-490
[27] Hillel D. Research in soil physics: a review. Soil Sci. 1991,151:30-34
[28] Hunner G., H.Todd Mowrer, Robin M. Reich, An Accuracy Comparison of Six Spatial Interpolation Methods for Modeling Forest Stand Structure on the Fraser Experimental Forest, Colorado. Http://www.eis.wau.ul/Accuracu2000/abstracts/Hunner.htm
[29] Isaaks, E.H., and Srivastava R.M.. 1989． An introduction to applied geostatistics. Oxford University Press, New York, NY.
[30] Jensen, T., Zeller L., and Kelly R. Mechanizing on-the-run grain sampling. 2000． Http://www.usyd.edu.au/su/agric/acpa
[31] Jess Lowenberg-Deboer. Precision farming and the new information technology: implications for farm management. Amer. J. Agr. Econ., 1996(78) : 1281-1284
[32] Jones, J.W., Hoogenboom, G.., Porter, C.H. et al., The DSSAT cropping system mode.l European Journal of Agronomy, Jan 2003(18) :235-265．
[33] Jury W. A., In Vadose Zone Modeling of Organic Pollutants, edited by S. C. Hern and S. M. Melanion (Lewis. Publishers, Inc., Chelsea, Michigan, 1989) , p. 245．
[34] Kevin Johnston, Jay M. Ver Hoef, Konstantin Krivoruchko, and Neil Lucas. Using ArcGIS geostatistical analyst. USA ESRI, 2001, pp19-26
[35] Kitchen et al., Soil Electrical Conductivity as a Crop Productivity Measure for Claypan Soils, Journal of Production Agriculture 1999(12) :607-617
[36] Kitchen, N. R., K. A. Sudduth, D.F. Hughes, et al. 1995． Comparison of variable rate to single rate nitrogen fertilizer application: Corn production and residual soil N03-N. In. Site-Specific Management for Agricultural Systems. ASA-CSSA-SSSA, Madison, WI. Pp 427-442
[37] Knighton,R. 1997． SMILEY: Remote sensing data-mining tool. Ver. 1． 0． North Dakota St. Univ. http://smiley.cs.ndsu.nodak.edu/cgi-bin/smiley.cgi.
[38] Kravchenko, A., and D. G. Bullock. 1999． A comparative study of interpolation methods for mapping soil properties. Agronomy J. 91:393-400
[39] Lambert D. & J. Lowenberg-DeBoer. Precision agriculture profitability review. http://mollisol.agry.purdue.edu/SSMC/Frames/newsoilsX.pdf
[40] Large, E.C. 1954． Growth stages in cereals. Plant Pathol. 3:128-129．
[41] Larisa Pozdnyakova,Renduo Zhang. Geostatistical analyses of soil salinity in a large filed. Precision Agriculture 1(2) :153-165
[42] Lark, R. M., J. V. Stafford, and M. A. Froment. 1997． Exploratory analysis of yield maps of combinable crops. Proc. First European Conf. on Prec. Agric. p. 887-894． Ed. J. V. Stafford. Silsoe Res. Inst, UK.
[43] Larscheid G., Blackmore B. S., M. Moore. Management Decisions Based on Yield Map. In: John V. Stafford, eds. Precision Agriculture'97． Silsoe: BIOS Scientific Publishers Ltd, 1997． 895-903
[44] Lascano R J, J L Hatfield. Spatial variability of evaporation along with two transects of a bare soil. Soil Sci Soc Am J,1992,56:341-346
[45] Laslett, G. M. 1994． Kriging and splines: An empirical comparison of their predictive performance in some applications. J. Am. Stat. Assoc. 89:391-409
[46] Long, 1996． Increasing profitability with variable rate fertilization. PROGRAM-18th ANNUAL WORKSHOP, The Manitoba-North Dakota Zero Tillage Farmers Association, downloaded from www.mandakzerotill.org/bookl 8/fcrtilization.html.
[47] Lukina, E.V, K.W. Freeman, K.J. Wynn, W.E. Thomason, R.W. Mullen, A.R. Klatt, G.V. Johnson, R.L. Elliott, M.L. Stone, J.B. Solie, and W.R. Raun. 2001． Nitrogen fertilization optimization algorithm based on in-season estimates of yield and plant nitrogen uptake. J. Plant Nutr. 24:885-898．
[48] Lund, E. D., C. D. Christy and P. E. Drummond. 1999． Practical applications of soil electrical conductivity mapping. In: Precision Agriculture '99, Proc. Of the 2nd European Conf. On Precision Agriculture, Ed. J. V. Stafford. Pp771-779
[49] McBratney A.B. and M. J. Pringle, Precision Agriculture '97, Volume 1: Spatial Variability in Soil and Crop, edited by J. V. Stafford (BIOS Scientific Publishers, Oxford, 1997) , p. 3．
[50] Michael D Weiss. Precision fanning and spatial economic analysis: research challenges and opportunities. Amer. J. Agr. Econ., 1996(78) : 1275-1280
[51] Mohamed S. B., Evans E. J., Shiel R. S.. Mapping Techniques and Intensity of Soil Sampling for Precision Farming. Proceedings of the 3rd International Conference. Minneapolis, Minnesota, June 23-26, 1996, pp217-226
[52] Murdock L. & Howe P. Profitability of Variable Rate Fertilization on a Kentucky Soil (a Theoretical Analysis). Soil Science News & Views. 1997,18(10) . http://www.uky.edu/Ag/Agronomy/Extension/ssnv/ssvl 1810． pdf
[53] Murphy, D. P., Schnug, E., Hancklaus, S. (1995) Yield Mapping-a guide to improved techniques and strategies. Proc. 2nd International Conference on Site-Specific Management for Agricultural Systems, P. C.
Robert, R. H. Rust and W. E. Larson, (Eds), Minneapolis, American Society of Agronomy
[54] Okamoto, K., M. Fukuhara, and T. Hatanaka. 1990． Mapping method of soil organic matter content of Obihiro area with a Landsat TM data, (in Janapese with English summary). J. Jpn. Sci. Photogramm. Remote Sens., 29(6) :45-52．
[55] Oliver M. A. and Frogbrook Z. L., Proceedings of the International Fertiliser Society, No 417 (1998) .
[56] Pearson E. J. et al. An Integrated ES/GIS Approach to Mapping & Modeling Natural Hazards. EGIS'92, 1992
[57] Pierce F J and Sadler E J. The State of Site Specific Management for Agriculture. ASA Miscellaneous Publication. American Society of America, Madison, Wl,1997．
[58] Pokrajac D., Fiez T., Obradovic Z.. A data generator for evaluating spatial issues in precision agriculture. PA, 2002, 3(3) :259-281
[59] Raun, W.R., J.B. Solie, G.V. Johnson, M.L. Stone, R.W. Whitney, H.L. Lees, H. Sembiring, and S.B. Phillips. 1998． Microvariability in soil test, plant nutrient, and yield parameters in bermudagrass. Soil Sci. Soc. Am. J. 62:683-690．
[60] Raun, W.R., J.B. Solie, G.V. Johnson, M.L. Stone, R.W. Mullen, K.W. Freeman, W.E. Thomason, and E.V. Lukina, Improving Nitrogen Use Efficiency in Cereal Grain Production with Optical Sensing and Variable Rate Application. Agron. J. 94
[61] Rhoades J D, Shouse P J, Alves N A, et al. Determining soil salinity from soil electrical conductivity using different models and estimates, Soil Sci Soc Am J, 1990,54,46-54
[62] Robertson G P et al. Soil resources, microbial activity, and primary production across an agricultural ecosystem. Ecological Applications,1997,7:158-170(N/S)
[63] Sawyer, J. E., 1994． Concepts of variable rate technology with considerations for fertilizer application. J. Prod. Agric. 7:195-201
[64] Smith T. R. et al. Requirements & Principles for the Implementation & Construction of Large-scale GISes. I. J. GIS,1987,1(1) :13-31
[65] Soh,K.G., Fertilizer use by crop, A global assessment, IF A, 1995,2-3
[66] Solie, J.B., W.R. Raun, R.W. Whitney, M.L. Stone, and J.D. Ringer. 1996． Optical sensor based field element size and sensing strategy for nitrogen application. Trans. ASAE. 39:1983-1992．
[67] Stafford, J. V. Implementing Precision Agriculture in the 21st Century, Journal of Agricultural Engineering Research. 2000, Vol. 76, p.267-275
[68] Stafford, J. V., Ambler, B., Lark, R. M., Catt, J. Mapping and interpreting the yield variation in cereal crops. Computers and Electronics in Agriculture, 1996, 14:101-119
[69] Steven A Wolf and Frederick H Buttel. The political economy of precision fanning. Amer J Agr Econ, 1996(78) : 1269-1274
[70] Stone, M.L., J.B. Solie, W.R. Raun, R.W. Whitney, S.L. Taylor, and J.D. Ringer. 1996． Use of spectral radiance for correcting in-season fertilizer nitrogen deficiencies in winter wheat. Trans. ASAE. 39:1623-1631．
[71] Sudduth, K. A., N. R. Kitchen, D. F. Hughes, et al. 1997． Spatial modeling of crop yield using soil and
topographic data. In: Precision Agriculture '97． The 1st European Conf. On Prec. Agric. Pp439-447
[72] Swinton,S.M., and J.Lowenberg-DeBoer,1998． Evaluating the profitability of site specific farming. Journal of Production Agriculture, 439-446．
[73] Thompson, E. E. Duke, H. R. Westfall, G. W. et al. Interdisciplinary Integrated Precision Farming Research. Precision Agriculture, 2002, 3(1) : 47-61
[74] Thylen, L., Mruphy, D. P. L. (1996) The control of errors in momentary yield data from combine harvesters. Journal of Agricultural Engineering Research, 64:271-178
[75] ThylenL.. et al., 1997． Improving the quality of yield data. Precision Agriculture'97． Edited by John V. Stafford, BIOS Scientific Publishers Ltd. pp743-750
[76] Tom Doerge. Yield map interpretation. Crop InsightsVol. 7 No. 23． Http://www.pioneer.com/usa/technology/i971219． htm
[77] Tompson, AJ.B., Ababou, R., Gelhar, L.W., 1989． Implementation of the three dimensional turning bands random field generator. Water Resour. Res. 25(10) . 2227-2243
[78] Tsegaye T, Hill R L. Intensive tillage effects on spatial variability of soil test, plant growth, and nutrient uptake measurements. Soil Sci , 1998,163(2) :155-165
[79] Varsa, E. C., S. A. Ebelhar, T. D. Wyciskalla, et al. Using historically established yield variability for the improved prediction of nitrogen fertilizer needs of corn, http://frec.cropsci.uiuc.edu/2002/report5/index.htm
[80] Veris Technologies Company, 3 100 Soil EC Mapping System Operations Manual
[81] Voltz, M., and R. Webster. 1990． A comparison of kriging, cubic splines and classification for predicting soil properties from sample information. J. Soil Sci. 41:473-490
[82] Weber, D. D., and E.J. Englung. 1994． Evaluation and comparison of spatial interpolators II. Math. Geol. 24:589-602
[83] Weber, D. D., and Englung E.J.. 1992． Evaluation and comparison of spatial interpolators. Math. Geol. 24:381-391
[84] Wendroth, O., G. Kuhn, P. Jurschik and D. R. Nielsen. 1997． State-space approach for site-specific management decisions. Proc. First European Conf. on Prec. Agric. Ed. J.'V. Stafford, p. 835-842． Silsoe Res. Inst., UK.
[85] Wollenhaupt N. C., Mulla D. J., Gotway Crowford C. A.. Soil Sampling and Interpolation Techniques for Mapping Spatial Variability of Soil Properties. Site-Specific Management for Agricultural Systems. ASA-CSSA-SSSA, 1997, pp19-53
[86] ZHAO Chunjiang & WANG Maohua, Progress of Beijing Demonstration Project on Precision Farming, Proceedings of International Conference on Engineering and Technological Sciences 2000,. Beijing, China
[87] Zhao Chunjiang, Yang minhua, Chen Liping, et al. Strategy of Adaptive Farming Unit Based on the Analysis of Multidimensional Spatial Variability, International Conference on Agricultural Science and Technology (ICAST), Beijing, 2001, Session 6: Information Technology of Agriculture, pp.345-349
[88] Zhao,C. J., 2000． Progress of agricultural information technology. International Academic Publishers, Beijing.
[89] 白由路、金继运、杨俐苹等，基于GIS的土壤养分分区管理模型研究，中国农业科学，2001，34(1) ：46-50
[90] 陈立平，王东辉，赵春江等．掌上电脑农业专家系统开发平台的研究与开发．农业工程学报，2002a，
18(2)：142-145
[91] 陈立平，赵春江、刘学馨等，精确农业智能决策支持平台的设计与实现，农业工程学报，2002b，18(2)：145-148
[92] 程一松、胡春胜，高光谱遥感在精准农业中的应用，农业系统科学与综合研究，2001，17(3)：193-195
[93] 崔玉亭，化肥与生态环境保护，北京：化学工业出版社，2000
[94] 冯恭衍．平原地区养分分析中土壤取样方法的初步研究．土壤通报，1984，15(1)：29～325
[95] 奉公，21世纪初期的农业主导技术，科技导报，1999(1)：20-22
[96] 高山敏之．小麦实肥高品质化技术开发．农业园艺．第75卷，第4号，p．437-445(2000)
[97] 高祥照，胡克林，郭焱等，土壤养分与作物产量的空间变异特征与精确施肥，中国农业科学2002，35(6)：660-666
[98] 郭腾云．EGIS的构建方法及其应用探讨[J]，地理研究，1999，18(增刊)：94-102．
[99] 候景儒，郭光裕编著，矿床统计预测及地质统计学的理论与应用，冶金工业出版社，北京，1993，pp325—372
[100] 胡慧萍，土壤特性的空间差异及其空间插值方法研究，湘潭师范学院学报(自然科学版)，2001，23(3)：99-101，115
[101] 胡克林、李保国、林启美等，农田土壤养分的空间变异性特征，农业工程学报，1999，15(3)：33-38．
[102] 黄波，王英杰．GIS与ES的结合及其应用初探．环境遥感，1991，11(3)：234—239
[103] 黄德明，赵微平，张有山．“土壤与施肥”，见“现代化吨粮技术与实践”，宋秉彝编著．中国农业科技出版社，1995，p42
[104] 黄海，罗友丰，陈志英等，SPSS10．0 for Windows统计分析，人民邮电出版社，北京，2001，pp226-238
[105] 黄绍文，金继运．土壤特性空间变异研究进展．精准农业与土壤养分管理．金继运，白由路主编，2001，中国大地出版社，p23-29
[106] 金继运，精准农业及其在我国的应用前景，精准农业与土壤养分管理，金继运，白由路主编，北京：中国大地出版社，2001，1-7
[107] 金继运．“精确农业”及其在我国的应用前景：见：中国土壤学会第八届第二次理事会扩大会议学术论文集．成都，1997，152-159
[108] 雷志栋，杨诗秀．土壤特性空间变异性的初步研究．水利学报，1985(9)：10-21
[109] 李菊梅、李生秀，几种营养元素在土壤中的空间变异，干旱地区农业研究，1998，16(2)：58-64．
[110] 李世娟，冬小麦节水高产栽培中的氮素施用技术研究，中国农业大学博士论文，2001
[111] 李翔，郭天财，赵春江等．基于WebGIS和ES集成技术的农作物管理地理信息系统研究．华北农学报，2003(4)，待发
[112] 梁春祥、姚贤良，华中丘陵红壤物理性质的空间变异分析，土壤学报，1993，30(1)：69-77
[113] 刘爱民，封志明，徐丽明．现代精准农业及我国精准农业的发展方向。中国农业大学学报，2000，5(2)：20-25
[114] 刘刚，支持精细农业实践的农田空间分布信息处理的方法与试验研究，中国农业大学博士学位论文，2001
[115] 刘良云．高光谱遥感在精准农业中的应用研究．中国科学院遥感应用研究所博士后研究工作报告．
2002
[116] 刘世洪，精准农业的发展现状，农业科技通讯，1999，(10)：1～5
[117] 卢良恕，21世纪我国农业科学技术发展趋势与展望，中国农业科学，1998，31(2)：1-7
[118] 马蔼乃等．地理专家系统的试验研究．地理学报，1992，47(3)：252-259
[119] 马孝义，李新平，赵廷风．土壤含水量的Kriging和Cokriging估值研究．水土保持通报，2001，21(3)：59-62
[120] 马孝义、熊运章，孟海平．塿土土壤物理特性空间变异性的初步研究，现代土壤科学进展，中国农业出版社，1994．P80-85
[121] 孟志军，赵春江，陈立平等．GPS技术在精准农业中的应用．高技术通讯，2000(增刊)：79-81
[122] 莫惠栋著，农业试验统计，上海：上海科学技术出版社，1992，103，152
[123] 潘瑜春，薛绪掌，陈立平等．基于矢量网格计算的变量施肥单元大小效应研究．中国农业科学，待发
[124] 宋秉彝．现代化吨粮技术与实践．北京：中国农业科技出版社，1995，43，52
[125] 孙宇瑞、汪懋华，一种土壤电导率测量方法的数学建模与实验研究，农业工程学报，2001，17(2)：20-23
[126] 汪懋华，精细农作与现代农业科技革命，农业科技参考，1999，(12)：1-4
[127] 汪懋华．“精细农业”发展与工程技术创新．农业工程学报，1999，15(1)：1-8
[128] 王珂，沈掌泉，John S．Bailey等，精确农业土壤空间变异与采样方式研究，农业工程学报，2001，17(2)：33-36
[129] 王克林、李文样，精确农业发与农业生态工程创新，农业工程学报，2000，16(1)：5-8
[130] 王伟长．地理信息系统控件(Active X)—MapObjects培训教程．北京，科学技术出版社，2000，3
[131] 王晓方、申茂向，化肥—21世纪中国食物安全的支撑条件，1998
[132] 王学锋、章衡，土壤有机质的空间变异性，土壤，1995，27(2)；85-89
[133] 吴才聪，马成林，张书慧等．精确农业倾斜网格划分及其应用．农业工程学报，2003，19(1)：137-140
[134] 吴才聪，张书慧，马成林等．利用MapBasic划分精确农业田块网格方法的研究．农业工程学报，2002，18(2)：156-159
[135] 吴健康．智能地理信息系统KGIS的设计．黄土高原信息系统研究．北京，测绘出版社，1988
[136] 谢建昌，世界肥料使用的现状与前景，植物营养与肥料学报，1998，4(4)，321-330
[137] 徐吉炎，Webster．土壤调查数据的最佳估值研究——武县表层全氮量半方差图和块状Kriging估值[J]．土壤学报，1983，20(4)：419—430
[138] 杨俐苹，评价区域性土壤肥力的取样技术的回顾与展望，土壤肥料，2000(1)：3-8
[139] 杨俐苹、姜城、金继运等．棉田土壤养分精准管理初探，中国农业科学，2000,33(6)：67-72．
[140] 杨敏华，面向精准农业的高光谱遥感作物信息获取，中国农业大学博士论文，2002
[141] 杨敏华、陈立平、盂志军、王秀、赵春江，基于多维空间变异分析的精确农业作业单元自适应决策，农业工程学报，2002，18(2)：149-152
[142] 杨印生，马成林，冯传平．精确农业的社会经济特征和经济分析问题初探．农业工程学报，2000，16(5)；122-125
[143] 杨印生、吴才聪、冯传平，日本精确农业的研究现状，农业机械学报，2001，32(2)：107-110
[144] 喻歌农，周泳．试论精确农业及我国行动对策．自然资源学报，1999，14(1)：69～74
[145] 张书慧，马成林，于春玲．应用于精确农业变量施肥地理信息系统的开发研究．农业工程学报，2002，
18(2)：153-155
[146] 张卫建，卞新民，柯建国等，基于网络GIS的区域农业决策支持系统的集成思路与方法，南京农业大学学报，2000，23(2)：23-26，
[147] 赵春江，杨宝祝，李爱平等．网络化、构件化农业专家系统开发平台(PAID)的研究与应用．《’99智能计算机接口与应用进展》，1999，459-465
[148] 周慧珍、龚子同、Lamp J，土壤空间变异性研究，土壤学报，1996，33(3)：234-241．
[149] 佐藤一弘．土壤诊断·营养诊断基小麦高品质·安定栽培技术．日本土壤肥料学杂志，第71卷，第2号，p．254-258(2000)
[2] Andy D. Beck, Jody P. Roades, Stephen W. Searcy. Post-Process Filtering Techniques to Improve Yield Map Accuracy. Paper No.991048． Written for Presentation at the 1999 ASAE/CSAE-SCGR Annual International Meeting Sponsored by ASAE and CSAE
[3] Arslan Selcuk, Thomas S. Colvin. Grain Yield Mapping: Yield Sensing, Yield Reconstruction, and Errors, Precision Agriculture 3(1) : 81-94, March 2002
[4] Ascough J. C. II, Shaffer M J, Hanson J D, et al. The Great Plains Framework for Agricultural Resource Management (GPFARM): A Decision Support System for Whole Farm/Ranch Strategic Planning,ASAE, 1997, Paper No.975053 http://asae.org/meetings/am97/abstracts/975053 .html
[5] Atherton B C, Morgan M T, Shearer S A, et al. Site-specific farming: a perspective on information needs, benefits and limitations [J]. Journal of Soil and Water Conservation, 1999,2:455-461．
[6] Batte, M.T., Arnholt, M.W., Precision farming adoption and use in Ohio: case studies of six leading-edge adopters. Computers and Electronics in Agriculture, Feb 2003
[7] Berry, J. K. 1993． Beyond mapping: Concepts, algorithms, and issues in GIS. GIS World Books, Ft Collins, CO.
[8] Blackmore B. S., Wheeler P N, Morris R M, et al. The Role of Precision Farming in Sustainable Agriculture: A European Perspective[A]. Univ. of Minnesota, Proceedings of the 2nd International Conference on Site-Specific Management for Agriculture System[C]. Minneapolis, 1994,1-14．
[9] Blackmore, B. S. and C. J. Marshall. 1996． Yield Mapping: Errors and Algorithms. Presented at the 3rd International Conference on Precision Agriculture, Silsoe College, Canfield University
[10] Blackmore, B. S. and G. Larscheid. 1997 . Stategies for managing variability. Proc. First European Conf. On Prec. Agric. Pp851-859． Ed. J. V. Stafford. Silsoe Res. Inst, UK
[11] Bruce A Babcock and Gregory R Pautsch. Moving from uniform to variable fertilizer rates on iowa com: effects on rates and returns. J of Agri. and Res. Economics, 1998(2) :385-400
[12] Burrough P A. Soil variability: a late 20th century view. Soils and Fertilizers. 1993,56(5) :529-562．
[13] Chen J, Hopmans J W and Fogg G E. Sampling design for soil moisture measurements in large field trials. Soil Science. 1995,159(3) :155-161．
[14] Chen Liping, Zhao Chunjiang, Design and Implement of GIS/ES Integrated System Based On Interne/Intranet, Progress of Agricultural Information Technology, 2000,Beijing, 278-282
[15] Dahnke W. C., Fanning C., Cattanach A., 1992． Fertilizing Corn Grain, Popcorn, Silage Com, and Sweet Corn, www.extnodak.edu/extpubs/plantsci/soilfert/sf722w.htm.
[16] David Zilberman and Katti Millock. Pesticide use and regulation: making economic sense out of and externality and regulation nightmare. J of Agri. And Res. Economics, 1997(2) :321-332
[17] Doerge T. 1999． Soil electrical conductivity mapping. Crop Insights Vol.9, No.9． http:/www.pioneer.com/usa/technology/soil_conductivity_mapping_99． htm
[18] Engel.T.,G. Hoogenboom, J.W.Jones, and P.W.Wilkens, 1997, AEGISAVIN: A computer program for the application of crop simulation models across geographical areas, Agron.J.89:919-928．
[19] Finck, Charlene. 1998． Precision can pay its way. Farm Journal, Mid-January, p10-12．
[20] Genton Marc G., Reinhard Furrer. Analysis of rainfall data by simple good senseris spatial statistics worth the trouble. Http://www.geo.sbg.ac.at/staff/lorup/lv/geostats2003/docs/Genton Furrer.pdf
[21] George Rehm, 2002． A Multi-Disciplinary evaluation of precision farming, A final progress report (Minnesota) for 2001 prepared for United Soybean Board. Downloaded from www.farmresearch.com.
[22] Goel, P.K., Prasher, S.O., Landry, J.A., et al., Potential of airborne hyperspectral remote sensing to detect nitrogen deficiency and weed infestation in corn Computers and Electronics in Agriculture, Feb 2003
[23] Gotway, C. A., R. A. Ferguson, G. W. Hergeot, and et al., Comparison of Kriging and Inverse-Distance Methods for Mapping Soil Parameters, Soil Sci. Soc. Am. Journal 1996, 60:1237-1247
[24] Han S. Y. & Kim T.J.. ESSAS Expert System for Site Analysis & Selection. Computers, Environment and Urban System, 1988,12(4) :239-252
[25] Han, S., Hummel J.W., Goering C.E., and Cahn M.D.. 1994． Cell size selection for site-specific crop management. Trans. ASAE. 37:19-26．
[26] Han,S., S. M. Schneider,S. L. Rawlins, R. G. Evans. 1996． A Bitmap Method for Determining Effective Combine Cut Width in Yield Mapping. Transactions of the ASAE 40(2) :485-490
[27] Hillel D. Research in soil physics: a review. Soil Sci. 1991,151:30-34
[28] Hunner G., H.Todd Mowrer, Robin M. Reich, An Accuracy Comparison of Six Spatial Interpolation Methods for Modeling Forest Stand Structure on the Fraser Experimental Forest, Colorado. Http://www.eis.wau.ul/Accuracu2000/abstracts/Hunner.htm
[29] Isaaks, E.H., and Srivastava R.M.. 1989． An introduction to applied geostatistics. Oxford University Press, New York, NY.
[30] Jensen, T., Zeller L., and Kelly R. Mechanizing on-the-run grain sampling. 2000． Http://www.usyd.edu.au/su/agric/acpa
[31] Jess Lowenberg-Deboer. Precision farming and the new information technology: implications for farm management. Amer. J. Agr. Econ., 1996(78) : 1281-1284
[32] Jones, J.W., Hoogenboom, G.., Porter, C.H. et al., The DSSAT cropping system mode.l European Journal of Agronomy, Jan 2003(18) :235-265．
[33] Jury W. A., In Vadose Zone Modeling of Organic Pollutants, edited by S. C. Hern and S. M. Melanion (Lewis. Publishers, Inc., Chelsea, Michigan, 1989) , p. 245．
[34] Kevin Johnston, Jay M. Ver Hoef, Konstantin Krivoruchko, and Neil Lucas. Using ArcGIS geostatistical analyst. USA ESRI, 2001, pp19-26
[35] Kitchen et al., Soil Electrical Conductivity as a Crop Productivity Measure for Claypan Soils, Journal of Production Agriculture 1999(12) :607-617
[36] Kitchen, N. R., K. A. Sudduth, D.F. Hughes, et al. 1995． Comparison of variable rate to single rate nitrogen fertilizer application: Corn production and residual soil N03-N. In. Site-Specific Management for Agricultural Systems. ASA-CSSA-SSSA, Madison, WI. Pp 427-442
[37] Knighton,R. 1997． SMILEY: Remote sensing data-mining tool. Ver. 1． 0． North Dakota St. Univ. http://smiley.cs.ndsu.nodak.edu/cgi-bin/smiley.cgi.
[38] Kravchenko, A., and D. G. Bullock. 1999． A comparative study of interpolation methods for mapping soil properties. Agronomy J. 91:393-400
[39] Lambert D. & J. Lowenberg-DeBoer. Precision agriculture profitability review. http://mollisol.agry.purdue.edu/SSMC/Frames/newsoilsX.pdf
[40] Large, E.C. 1954． Growth stages in cereals. Plant Pathol. 3:128-129．
[41] Larisa Pozdnyakova,Renduo Zhang. Geostatistical analyses of soil salinity in a large filed. Precision Agriculture 1(2) :153-165
[42] Lark, R. M., J. V. Stafford, and M. A. Froment. 1997． Exploratory analysis of yield maps of combinable crops. Proc. First European Conf. on Prec. Agric. p. 887-894． Ed. J. V. Stafford. Silsoe Res. Inst, UK.
[43] Larscheid G., Blackmore B. S., M. Moore. Management Decisions Based on Yield Map. In: John V. Stafford, eds. Precision Agriculture'97． Silsoe: BIOS Scientific Publishers Ltd, 1997． 895-903
[44] Lascano R J, J L Hatfield. Spatial variability of evaporation along with two transects of a bare soil. Soil Sci Soc Am J,1992,56:341-346
[45] Laslett, G. M. 1994． Kriging and splines: An empirical comparison of their predictive performance in some applications. J. Am. Stat. Assoc. 89:391-409
[46] Long, 1996． Increasing profitability with variable rate fertilization. PROGRAM-18th ANNUAL WORKSHOP, The Manitoba-North Dakota Zero Tillage Farmers Association, downloaded from www.mandakzerotill.org/bookl 8/fcrtilization.html.
[47] Lukina, E.V, K.W. Freeman, K.J. Wynn, W.E. Thomason, R.W. Mullen, A.R. Klatt, G.V. Johnson, R.L. Elliott, M.L. Stone, J.B. Solie, and W.R. Raun. 2001． Nitrogen fertilization optimization algorithm based on in-season estimates of yield and plant nitrogen uptake. J. Plant Nutr. 24:885-898．
[48] Lund, E. D., C. D. Christy and P. E. Drummond. 1999． Practical applications of soil electrical conductivity mapping. In: Precision Agriculture '99, Proc. Of the 2nd European Conf. On Precision Agriculture, Ed. J. V. Stafford. Pp771-779
[49] McBratney A.B. and M. J. Pringle, Precision Agriculture '97, Volume 1: Spatial Variability in Soil and Crop, edited by J. V. Stafford (BIOS Scientific Publishers, Oxford, 1997) , p. 3．
[50] Michael D Weiss. Precision fanning and spatial economic analysis: research challenges and opportunities. Amer. J. Agr. Econ., 1996(78) : 1275-1280
[51] Mohamed S. B., Evans E. J., Shiel R. S.. Mapping Techniques and Intensity of Soil Sampling for Precision Farming. Proceedings of the 3rd International Conference. Minneapolis, Minnesota, June 23-26, 1996, pp217-226
[52] Murdock L. & Howe P. Profitability of Variable Rate Fertilization on a Kentucky Soil (a Theoretical Analysis). Soil Science News & Views. 1997,18(10) . http://www.uky.edu/Ag/Agronomy/Extension/ssnv/ssvl 1810． pdf
[53] Murphy, D. P., Schnug, E., Hancklaus, S. (1995) Yield Mapping-a guide to improved techniques and strategies. Proc. 2nd International Conference on Site-Specific Management for Agricultural Systems, P. C.
Robert, R. H. Rust and W. E. Larson, (Eds), Minneapolis, American Society of Agronomy
[54] Okamoto, K., M. Fukuhara, and T. Hatanaka. 1990． Mapping method of soil organic matter content of Obihiro area with a Landsat TM data, (in Janapese with English summary). J. Jpn. Sci. Photogramm. Remote Sens., 29(6) :45-52．
[55] Oliver M. A. and Frogbrook Z. L., Proceedings of the International Fertiliser Society, No 417 (1998) .
[56] Pearson E. J. et al. An Integrated ES/GIS Approach to Mapping & Modeling Natural Hazards. EGIS'92, 1992
[57] Pierce F J and Sadler E J. The State of Site Specific Management for Agriculture. ASA Miscellaneous Publication. American Society of America, Madison, Wl,1997．
[58] Pokrajac D., Fiez T., Obradovic Z.. A data generator for evaluating spatial issues in precision agriculture. PA, 2002, 3(3) :259-281
[59] Raun, W.R., J.B. Solie, G.V. Johnson, M.L. Stone, R.W. Whitney, H.L. Lees, H. Sembiring, and S.B. Phillips. 1998． Microvariability in soil test, plant nutrient, and yield parameters in bermudagrass. Soil Sci. Soc. Am. J. 62:683-690．
[60] Raun, W.R., J.B. Solie, G.V. Johnson, M.L. Stone, R.W. Mullen, K.W. Freeman, W.E. Thomason, and E.V. Lukina, Improving Nitrogen Use Efficiency in Cereal Grain Production with Optical Sensing and Variable Rate Application. Agron. J. 94
[61] Rhoades J D, Shouse P J, Alves N A, et al. Determining soil salinity from soil electrical conductivity using different models and estimates, Soil Sci Soc Am J, 1990,54,46-54
[62] Robertson G P et al. Soil resources, microbial activity, and primary production across an agricultural ecosystem. Ecological Applications,1997,7:158-170(N/S)
[63] Sawyer, J. E., 1994． Concepts of variable rate technology with considerations for fertilizer application. J. Prod. Agric. 7:195-201
[64] Smith T. R. et al. Requirements & Principles for the Implementation & Construction of Large-scale GISes. I. J. GIS,1987,1(1) :13-31
[65] Soh,K.G., Fertilizer use by crop, A global assessment, IF A, 1995,2-3
[66] Solie, J.B., W.R. Raun, R.W. Whitney, M.L. Stone, and J.D. Ringer. 1996． Optical sensor based field element size and sensing strategy for nitrogen application. Trans. ASAE. 39:1983-1992．
[67] Stafford, J. V. Implementing Precision Agriculture in the 21st Century, Journal of Agricultural Engineering Research. 2000, Vol. 76, p.267-275
[68] Stafford, J. V., Ambler, B., Lark, R. M., Catt, J. Mapping and interpreting the yield variation in cereal crops. Computers and Electronics in Agriculture, 1996, 14:101-119
[69] Steven A Wolf and Frederick H Buttel. The political economy of precision fanning. Amer J Agr Econ, 1996(78) : 1269-1274
[70] Stone, M.L., J.B. Solie, W.R. Raun, R.W. Whitney, S.L. Taylor, and J.D. Ringer. 1996． Use of spectral radiance for correcting in-season fertilizer nitrogen deficiencies in winter wheat. Trans. ASAE. 39:1623-1631．
[71] Sudduth, K. A., N. R. Kitchen, D. F. Hughes, et al. 1997． Spatial modeling of crop yield using soil and
topographic data. In: Precision Agriculture '97． The 1st European Conf. On Prec. Agric. Pp439-447
[72] Swinton,S.M., and J.Lowenberg-DeBoer,1998． Evaluating the profitability of site specific farming. Journal of Production Agriculture, 439-446．
[73] Thompson, E. E. Duke, H. R. Westfall, G. W. et al. Interdisciplinary Integrated Precision Farming Research. Precision Agriculture, 2002, 3(1) : 47-61
[74] Thylen, L., Mruphy, D. P. L. (1996) The control of errors in momentary yield data from combine harvesters. Journal of Agricultural Engineering Research, 64:271-178
[75] ThylenL.. et al., 1997． Improving the quality of yield data. Precision Agriculture'97． Edited by John V. Stafford, BIOS Scientific Publishers Ltd. pp743-750
[76] Tom Doerge. Yield map interpretation. Crop InsightsVol. 7 No. 23． Http://www.pioneer.com/usa/technology/i971219． htm
[77] Tompson, AJ.B., Ababou, R., Gelhar, L.W., 1989． Implementation of the three dimensional turning bands random field generator. Water Resour. Res. 25(10) . 2227-2243
[78] Tsegaye T, Hill R L. Intensive tillage effects on spatial variability of soil test, plant growth, and nutrient uptake measurements. Soil Sci , 1998,163(2) :155-165
[79] Varsa, E. C., S. A. Ebelhar, T. D. Wyciskalla, et al. Using historically established yield variability for the improved prediction of nitrogen fertilizer needs of corn, http://frec.cropsci.uiuc.edu/2002/report5/index.htm
[80] Veris Technologies Company, 3 100 Soil EC Mapping System Operations Manual
[81] Voltz, M., and R. Webster. 1990． A comparison of kriging, cubic splines and classification for predicting soil properties from sample information. J. Soil Sci. 41:473-490
[82] Weber, D. D., and E.J. Englung. 1994． Evaluation and comparison of spatial interpolators II. Math. Geol. 24:589-602
[83] Weber, D. D., and Englung E.J.. 1992． Evaluation and comparison of spatial interpolators. Math. Geol. 24:381-391
[84] Wendroth, O., G. Kuhn, P. Jurschik and D. R. Nielsen. 1997． State-space approach for site-specific management decisions. Proc. First European Conf. on Prec. Agric. Ed. J.'V. Stafford, p. 835-842． Silsoe Res. Inst., UK.
[85] Wollenhaupt N. C., Mulla D. J., Gotway Crowford C. A.. Soil Sampling and Interpolation Techniques for Mapping Spatial Variability of Soil Properties. Site-Specific Management for Agricultural Systems. ASA-CSSA-SSSA, 1997, pp19-53
[86] ZHAO Chunjiang & WANG Maohua, Progress of Beijing Demonstration Project on Precision Farming, Proceedings of International Conference on Engineering and Technological Sciences 2000,. Beijing, China
[87] Zhao Chunjiang, Yang minhua, Chen Liping, et al. Strategy of Adaptive Farming Unit Based on the Analysis of Multidimensional Spatial Variability, International Conference on Agricultural Science and Technology (ICAST), Beijing, 2001, Session 6: Information Technology of Agriculture, pp.345-349
[88] Zhao,C. J., 2000． Progress of agricultural information technology. International Academic Publishers, Beijing.
[89] 白由路、金继运、杨俐苹等，基于GIS的土壤养分分区管理模型研究，中国农业科学，2001，34(1) ：46-50
[90] 陈立平，王东辉，赵春江等．掌上电脑农业专家系统开发平台的研究与开发．农业工程学报，2002a，
18(2)：142-145
[91] 陈立平，赵春江、刘学馨等，精确农业智能决策支持平台的设计与实现，农业工程学报，2002b，18(2)：145-148
[92] 程一松、胡春胜，高光谱遥感在精准农业中的应用，农业系统科学与综合研究，2001，17(3)：193-195
[93] 崔玉亭，化肥与生态环境保护，北京：化学工业出版社，2000
[94] 冯恭衍．平原地区养分分析中土壤取样方法的初步研究．土壤通报，1984，15(1)：29～325
[95] 奉公，21世纪初期的农业主导技术，科技导报，1999(1)：20-22
[96] 高山敏之．小麦实肥高品质化技术开发．农业园艺．第75卷，第4号，p．437-445(2000)
[97] 高祥照，胡克林，郭焱等，土壤养分与作物产量的空间变异特征与精确施肥，中国农业科学2002，35(6)：660-666
[98] 郭腾云．EGIS的构建方法及其应用探讨[J]，地理研究，1999，18(增刊)：94-102．
[99] 候景儒，郭光裕编著，矿床统计预测及地质统计学的理论与应用，冶金工业出版社，北京，1993，pp325—372
[100] 胡慧萍，土壤特性的空间差异及其空间插值方法研究，湘潭师范学院学报(自然科学版)，2001，23(3)：99-101，115
[101] 胡克林、李保国、林启美等，农田土壤养分的空间变异性特征，农业工程学报，1999，15(3)：33-38．
[102] 黄波，王英杰．GIS与ES的结合及其应用初探．环境遥感，1991，11(3)：234—239
[103] 黄德明，赵微平，张有山．“土壤与施肥”，见“现代化吨粮技术与实践”，宋秉彝编著．中国农业科技出版社，1995，p42
[104] 黄海，罗友丰，陈志英等，SPSS10．0 for Windows统计分析，人民邮电出版社，北京，2001，pp226-238
[105] 黄绍文，金继运．土壤特性空间变异研究进展．精准农业与土壤养分管理．金继运，白由路主编，2001，中国大地出版社，p23-29
[106] 金继运，精准农业及其在我国的应用前景，精准农业与土壤养分管理，金继运，白由路主编，北京：中国大地出版社，2001，1-7
[107] 金继运．“精确农业”及其在我国的应用前景：见：中国土壤学会第八届第二次理事会扩大会议学术论文集．成都，1997，152-159
[108] 雷志栋，杨诗秀．土壤特性空间变异性的初步研究．水利学报，1985(9)：10-21
[109] 李菊梅、李生秀，几种营养元素在土壤中的空间变异，干旱地区农业研究，1998，16(2)：58-64．
[110] 李世娟，冬小麦节水高产栽培中的氮素施用技术研究，中国农业大学博士论文，2001
[111] 李翔，郭天财，赵春江等．基于WebGIS和ES集成技术的农作物管理地理信息系统研究．华北农学报，2003(4)，待发
[112] 梁春祥、姚贤良，华中丘陵红壤物理性质的空间变异分析，土壤学报，1993，30(1)：69-77
[113] 刘爱民，封志明，徐丽明．现代精准农业及我国精准农业的发展方向。中国农业大学学报，2000，5(2)：20-25
[114] 刘刚，支持精细农业实践的农田空间分布信息处理的方法与试验研究，中国农业大学博士学位论文，2001
[115] 刘良云．高光谱遥感在精准农业中的应用研究．中国科学院遥感应用研究所博士后研究工作报告．
2002
[116] 刘世洪，精准农业的发展现状，农业科技通讯，1999，(10)：1～5
[117] 卢良恕，21世纪我国农业科学技术发展趋势与展望，中国农业科学，1998，31(2)：1-7
[118] 马蔼乃等．地理专家系统的试验研究．地理学报，1992，47(3)：252-259
[119] 马孝义，李新平，赵廷风．土壤含水量的Kriging和Cokriging估值研究．水土保持通报，2001，21(3)：59-62
[120] 马孝义、熊运章，孟海平．塿土土壤物理特性空间变异性的初步研究，现代土壤科学进展，中国农业出版社，1994．P80-85
[121] 孟志军，赵春江，陈立平等．GPS技术在精准农业中的应用．高技术通讯，2000(增刊)：79-81
[122] 莫惠栋著，农业试验统计，上海：上海科学技术出版社，1992，103，152
[123] 潘瑜春，薛绪掌，陈立平等．基于矢量网格计算的变量施肥单元大小效应研究．中国农业科学，待发
[124] 宋秉彝．现代化吨粮技术与实践．北京：中国农业科技出版社，1995，43，52
[125] 孙宇瑞、汪懋华，一种土壤电导率测量方法的数学建模与实验研究，农业工程学报，2001，17(2)：20-23
[126] 汪懋华，精细农作与现代农业科技革命，农业科技参考，1999，(12)：1-4
[127] 汪懋华．“精细农业”发展与工程技术创新．农业工程学报，1999，15(1)：1-8
[128] 王珂，沈掌泉，John S．Bailey等，精确农业土壤空间变异与采样方式研究，农业工程学报，2001，17(2)：33-36
[129] 王克林、李文样，精确农业发与农业生态工程创新，农业工程学报，2000，16(1)：5-8
[130] 王伟长．地理信息系统控件(Active X)—MapObjects培训教程．北京，科学技术出版社，2000，3
[131] 王晓方、申茂向，化肥—21世纪中国食物安全的支撑条件，1998
[132] 王学锋、章衡，土壤有机质的空间变异性，土壤，1995，27(2)；85-89
[133] 吴才聪，马成林，张书慧等．精确农业倾斜网格划分及其应用．农业工程学报，2003，19(1)：137-140
[134] 吴才聪，张书慧，马成林等．利用MapBasic划分精确农业田块网格方法的研究．农业工程学报，2002，18(2)：156-159
[135] 吴健康．智能地理信息系统KGIS的设计．黄土高原信息系统研究．北京，测绘出版社，1988
[136] 谢建昌，世界肥料使用的现状与前景，植物营养与肥料学报，1998，4(4)，321-330
[137] 徐吉炎，Webster．土壤调查数据的最佳估值研究——武县表层全氮量半方差图和块状Kriging估值[J]．土壤学报，1983，20(4)：419—430
[138] 杨俐苹，评价区域性土壤肥力的取样技术的回顾与展望，土壤肥料，2000(1)：3-8
[139] 杨俐苹、姜城、金继运等．棉田土壤养分精准管理初探，中国农业科学，2000,33(6)：67-72．
[140] 杨敏华，面向精准农业的高光谱遥感作物信息获取，中国农业大学博士论文，2002
[141] 杨敏华、陈立平、盂志军、王秀、赵春江，基于多维空间变异分析的精确农业作业单元自适应决策，农业工程学报，2002，18(2)：149-152
[142] 杨印生，马成林，冯传平．精确农业的社会经济特征和经济分析问题初探．农业工程学报，2000，16(5)；122-125
[143] 杨印生、吴才聪、冯传平，日本精确农业的研究现状，农业机械学报，2001，32(2)：107-110
[144] 喻歌农，周泳．试论精确农业及我国行动对策．自然资源学报，1999，14(1)：69～74
[145] 张书慧，马成林，于春玲．应用于精确农业变量施肥地理信息系统的开发研究．农业工程学报，2002，
18(2)：153-155
[146] 张卫建，卞新民，柯建国等，基于网络GIS的区域农业决策支持系统的集成思路与方法，南京农业大学学报，2000，23(2)：23-26，
[147] 赵春江，杨宝祝，李爱平等．网络化、构件化农业专家系统开发平台(PAID)的研究与应用．《’99智能计算机接口与应用进展》，1999，459-465
[148] 周慧珍、龚子同、Lamp J，土壤空间变异性研究，土壤学报，1996，33(3)：234-241．
[149] 佐藤一弘．土壤诊断·营养诊断基小麦高品质·安定栽培技术．日本土壤肥料学杂志，第71卷，第2号，p．254-258(2000)