基于主动作物冠层传感器的冬小麦、水稻精准氮素管理
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摘要
氮肥过量施用及施用时期的不合理是我国冬小麦和水稻生产中的主要问题,导致了较低的氮肥利用率及较高的环境污染风险。然而,在实际生产中又缺乏有效的氮素营养诊断方法和氮肥推荐算法。本研究通过多年多点的冬小麦以及寒地水稻的田间试验,系统地评价了Crop Circle ACS-470主动冠层传感器在当季作物关键生育期估测其氮素营养状况指标的潜力,并分别发展了基于该传感器的氮肥推荐算法。此外,通过4年的定位试验评价了不同氮素管理策略应用于冬小麦/夏玉米轮作体系的效果。综合全文研究结果,本文获得的主要结论如下：
(1)通过3年的冬小麦田间试验,评价Crop Circle ACS-470与GreenSeeker传感器在估测冬小麦氮素营养状况时的表现。其结果表明,与GreenSeeker传感器相比,当地上部生物量大于6000kg ha-1时,获取于Crop Circle ACS-470传感器的基于红边的指数CIRE与MSR_RE具有更好的估测能力；当植株吸氮量大于130kg ha-1时,基于绿光的指数CIG和MSR_G的估测能力更好。对于植株氮浓度与氮营养指数而言,Crop Circle ACS-470传感器的表现要优于GreenSeeker传感器,其中,GRDVI在估测氮营养指数表现最好(R2=0.78)。
(2)通过4年的冬小麦田间试验,获取于Crop Circle ACS-470传感器的指数CIG以及由指数GRDVI计算的INSEY可以在冬小麦Feekes4-7时期准确估测植株前期吸氮量和产量潜力,其R2分别为0.87和0.61。基于此结果发展了基于该传感器的冬小麦氮肥推荐算法。9个农户的验证试验表明,与农户传统施肥习惯相比,基于该传感器的精准氮素管理策略可以在获得相同产量的前提下显著地提高氮肥偏生产力59-74%。
(3)通过2年的寒地水稻田间试验及农户验证试验系统地评价了Crop Circle ACS-470主动冠层传感器在水稻关键生育时期估测其氮素营养状况的潜力。其结果表明,MCARI1在全生育时期可以准确估测水稻地上部生物量(R2=0.79)和植株吸氮量(R2=0.83),并可以克服GreenSeeker NDVI的饱和问题。4个基于红边波段的指数(RESAVI、MRESAVI、REDVI和RERDVI)均与氮营养指数线性相关(R2=0.76)。对于植株氮浓度而言,最高的R2仅为0.33,且在使用农户田块的数据进行验证时没有一个指数的表现令人满意。
(4)通过2年的寒地水稻田间试验,其结果表明,在不同的生育时期,无论是估测产量潜力还是估测其对于追施氮肥的反应,Crop Circle ACS-470传感器的表现均优于GreenSeeker传感器。基于此结果,同时根据氮肥最优推荐施肥算法发展了基于该传感器的寒地水稻精准氮素管理策略。
(5)通过4年的定位试验,系统地评价了不同氮素管理策略在冬小麦/夏玉米轮作体系上的应用效果。其研究结果表明,基于土壤无机氮测试技术、GreenSeeker传感器、绿色窗口以及区域优化的氮肥管理策略的施氮量较农户传统施氮管理分别降低了45%、62%、46%以及40%,从而提高了氮肥利用效,减少了氮素盈余及表观氮素损失,且各管理策略间的产量无显著差异。比较而言,在本试验条件下,基于GreenSeeker传感器的精准氮素管理策略是应用于华北平原冬小麦厦玉米轮作体系上较优的氮肥管理策略。
Over-application of nitrogen (N) fertilizers as well as improper timing are among the major problems for winter wheat and rice management in China, and have resulted in very low N use efficiencies (NUE) and high risk of environmental contamination. However, effective N nutritional status diagnosis methods and N fertilizer recommendation algorithms are lacking in practical production. In this study, we systematically evaluated the potential of Crop Circle ACS-470sensor with the configuration of NIR, red edge and green bands for estimating winter wheat and rice N status at critical growth stages, and developed this sensor-based precision N management strategy by conducting several site-years of field experiments. In addition, four years of fixed field experiments were conducted four years to evaluate different N management strategies for intensive winter wheat-summer maize double cropping system in North China Plain (NCP). The main results were concluded as follows:
(1) Three years of winter wheat field experiments were conducted to evaluate the performance of Crop Circle ACS-470and GreenSeeker for estimating N status. The results indicated that Crop Circle CIRE and MSR_RE indices performed better for estimating biomass when biomass was above6000kg ha-1and Crop Circle CIG and MSR_G performed better for estimating plant N uptake when it was above130kg ha-1, as compared with GreenSeeker sensor. The Crop Circle ACS-470sensor had better performance for estimating plant N concentration and NNI than GreenSeeker. Across site-years, growth stages and varieties, the GRDVI performed consistently well for estimating NNI, with R2being0.78.
(2) The Crop Circle CIG and the INSEY calculated with GRDVI could be used to estimate early-season plant N uptake and grain yield potential at Feekes growth stages4-7, with R2being0.87and0.61, respectively. The Crop Circle sensor-based N fertilizer recommendation algorithm was developed for winter wheat in NCP. Nine on-farm evaluation experiments indicated that this Crop Circle sensor-based precision N management strategy achieved similar grain yield as farmer's practice, but significantly increased partial factor productivity of N fertilizer by59-74%.
(3) The results of calibration experiments and on-farm validation experiments indicated that MCARI1had consistent correlations with rice aboveground biomass (R2=0.79) and plant N uptake (R2=0.83) across growth stages. It could overcome the saturation effect of GreenSeeker NDVI. Four red edge-based indices, RESAVI, MRESAVI, REDVI and RERDVI, performed equally well for estimating NNI across growth stages (R2=0.76). For rice plant N concentration, the highest R2was0.33, and none of the indices performed satisfactorily with validation using farmers' field data.
(4) The Crop Circle ACS-470sensor had better performance than GreenSeeker sensor for estimating rice yield potential and responsiveness to additional topdressing N application at stem elongation, booting, or heading stage. Based on these results, the Crop Circle sensor-based precision N management strategy was developed for rice according to the N fertilization optimization algorithm in Northeast China.
(5) Four years of fixed field experiments were conducted to evaluate different N management strategies for the intensive winter wheat-summer maize double cropping system in NCR The N fertilizer rate determined with soil Nmin-based in-season root zoon N management (IRNM-soil Nmin), GreenSeeker-based precision N management (PNM-GS), green window-based in-season N management strategy (INM-GW) and regional optimum N management (RONM) were significantly reduced45%,62%,46%and40%compared to the farmer's N practice (FNP), respectively, without significant change in grain yield. As a result, the IRNM-soil Nmin, PNM-GS, INM-GW and RONM increased N use efficiency, reduced N surplus, apparent N losses and GHG emission. In conclusion, the PNM-GS is the better strategy for winter wheat-summer maize double cropping system in NCP for improved NUE and reduced environmental contamination compared with other N management strategy in this study.
(1)通过3年的冬小麦田间试验,评价Crop Circle ACS-470与GreenSeeker传感器在估测冬小麦氮素营养状况时的表现。其结果表明,与GreenSeeker传感器相比,当地上部生物量大于6000kg ha-1时,获取于Crop Circle ACS-470传感器的基于红边的指数CIRE与MSR_RE具有更好的估测能力；当植株吸氮量大于130kg ha-1时,基于绿光的指数CIG和MSR_G的估测能力更好。对于植株氮浓度与氮营养指数而言,Crop Circle ACS-470传感器的表现要优于GreenSeeker传感器,其中,GRDVI在估测氮营养指数表现最好(R2=0.78)。
(2)通过4年的冬小麦田间试验,获取于Crop Circle ACS-470传感器的指数CIG以及由指数GRDVI计算的INSEY可以在冬小麦Feekes4-7时期准确估测植株前期吸氮量和产量潜力,其R2分别为0.87和0.61。基于此结果发展了基于该传感器的冬小麦氮肥推荐算法。9个农户的验证试验表明,与农户传统施肥习惯相比,基于该传感器的精准氮素管理策略可以在获得相同产量的前提下显著地提高氮肥偏生产力59-74%。
(3)通过2年的寒地水稻田间试验及农户验证试验系统地评价了Crop Circle ACS-470主动冠层传感器在水稻关键生育时期估测其氮素营养状况的潜力。其结果表明,MCARI1在全生育时期可以准确估测水稻地上部生物量(R2=0.79)和植株吸氮量(R2=0.83),并可以克服GreenSeeker NDVI的饱和问题。4个基于红边波段的指数(RESAVI、MRESAVI、REDVI和RERDVI)均与氮营养指数线性相关(R2=0.76)。对于植株氮浓度而言,最高的R2仅为0.33,且在使用农户田块的数据进行验证时没有一个指数的表现令人满意。
(4)通过2年的寒地水稻田间试验,其结果表明,在不同的生育时期,无论是估测产量潜力还是估测其对于追施氮肥的反应,Crop Circle ACS-470传感器的表现均优于GreenSeeker传感器。基于此结果,同时根据氮肥最优推荐施肥算法发展了基于该传感器的寒地水稻精准氮素管理策略。
(5)通过4年的定位试验,系统地评价了不同氮素管理策略在冬小麦/夏玉米轮作体系上的应用效果。其研究结果表明,基于土壤无机氮测试技术、GreenSeeker传感器、绿色窗口以及区域优化的氮肥管理策略的施氮量较农户传统施氮管理分别降低了45%、62%、46%以及40%,从而提高了氮肥利用效,减少了氮素盈余及表观氮素损失,且各管理策略间的产量无显著差异。比较而言,在本试验条件下,基于GreenSeeker传感器的精准氮素管理策略是应用于华北平原冬小麦厦玉米轮作体系上较优的氮肥管理策略。
Over-application of nitrogen (N) fertilizers as well as improper timing are among the major problems for winter wheat and rice management in China, and have resulted in very low N use efficiencies (NUE) and high risk of environmental contamination. However, effective N nutritional status diagnosis methods and N fertilizer recommendation algorithms are lacking in practical production. In this study, we systematically evaluated the potential of Crop Circle ACS-470sensor with the configuration of NIR, red edge and green bands for estimating winter wheat and rice N status at critical growth stages, and developed this sensor-based precision N management strategy by conducting several site-years of field experiments. In addition, four years of fixed field experiments were conducted four years to evaluate different N management strategies for intensive winter wheat-summer maize double cropping system in North China Plain (NCP). The main results were concluded as follows:
(1) Three years of winter wheat field experiments were conducted to evaluate the performance of Crop Circle ACS-470and GreenSeeker for estimating N status. The results indicated that Crop Circle CIRE and MSR_RE indices performed better for estimating biomass when biomass was above6000kg ha-1and Crop Circle CIG and MSR_G performed better for estimating plant N uptake when it was above130kg ha-1, as compared with GreenSeeker sensor. The Crop Circle ACS-470sensor had better performance for estimating plant N concentration and NNI than GreenSeeker. Across site-years, growth stages and varieties, the GRDVI performed consistently well for estimating NNI, with R2being0.78.
(2) The Crop Circle CIG and the INSEY calculated with GRDVI could be used to estimate early-season plant N uptake and grain yield potential at Feekes growth stages4-7, with R2being0.87and0.61, respectively. The Crop Circle sensor-based N fertilizer recommendation algorithm was developed for winter wheat in NCP. Nine on-farm evaluation experiments indicated that this Crop Circle sensor-based precision N management strategy achieved similar grain yield as farmer's practice, but significantly increased partial factor productivity of N fertilizer by59-74%.
(3) The results of calibration experiments and on-farm validation experiments indicated that MCARI1had consistent correlations with rice aboveground biomass (R2=0.79) and plant N uptake (R2=0.83) across growth stages. It could overcome the saturation effect of GreenSeeker NDVI. Four red edge-based indices, RESAVI, MRESAVI, REDVI and RERDVI, performed equally well for estimating NNI across growth stages (R2=0.76). For rice plant N concentration, the highest R2was0.33, and none of the indices performed satisfactorily with validation using farmers' field data.
(4) The Crop Circle ACS-470sensor had better performance than GreenSeeker sensor for estimating rice yield potential and responsiveness to additional topdressing N application at stem elongation, booting, or heading stage. Based on these results, the Crop Circle sensor-based precision N management strategy was developed for rice according to the N fertilization optimization algorithm in Northeast China.
(5) Four years of fixed field experiments were conducted to evaluate different N management strategies for the intensive winter wheat-summer maize double cropping system in NCR The N fertilizer rate determined with soil Nmin-based in-season root zoon N management (IRNM-soil Nmin), GreenSeeker-based precision N management (PNM-GS), green window-based in-season N management strategy (INM-GW) and regional optimum N management (RONM) were significantly reduced45%,62%,46%and40%compared to the farmer's N practice (FNP), respectively, without significant change in grain yield. As a result, the IRNM-soil Nmin, PNM-GS, INM-GW and RONM increased N use efficiency, reduced N surplus, apparent N losses and GHG emission. In conclusion, the PNM-GS is the better strategy for winter wheat-summer maize double cropping system in NCP for improved NUE and reduced environmental contamination compared with other N management strategy in this study.
引文
陈鹏飞.基于高光谱估测植株氮浓度及生物量的光谱指数研究与应用：[博士学位论文].北京：中国农业大学,2009
陈新平,李志宏,王兴仁,等.土壤,植株快速测试推荐施肥技术体系的建立与应用.土壤肥料,1999,2：6-10
陈杨,樊明寿,李斐,等.氮素营养诊断技术的发展及其在马铃薯生产中的应用.中国农学通报,2009,25：66-71
冯伟.基于高光谱遥感的小麦氮素营养及生长指标监测研究：[博士学位论文].南京：南京农业大学,2007
高晓薇Crop Circle传感器在冬小麦氮营养实时诊断与调控中的应用研究：[硕士学位论文].北京：中国农业大学,2011
郭建华,王秀,孟志军,等.主动遥感光谱仪Greenseeker与SPAD对玉米氮素营养诊断的研究.植物营养与肥料学报,2008,14：43-47
郭建华,赵春江,王秀,等.作物氮素营养诊断方法的研究现状及进展.中国土壤与肥料,2008：10-14
胡昊,自由路,杨俐苹,等.基于SPAD-502与GreenSeeker的冬小麦氮营养诊断研究.中国生态农业学报,2010,18：748-752
贾良良,李斐,陈新平,等.应用IKONOS卫星影像监测冬小麦氮营养状况.中国土壤与肥料,2013,6：68-71
焦雯珺,闵庆文,林煜,等.植物氮素营养诊断的进展与展望.中国农学通报,2007,22：351-355
李俊华,董志新,朱继正.氮素营养诊断方法的应用现状及展望.石河子大学学报(自然科学版),2003,7：80-83
李志宏,刘宏斌,张云贵.叶绿素仪在氮肥推荐中的应用研究进展.植物营养与肥料学报,2006,12：125-132
梁效贵,张经廷,周丽丽,等.华北地区夏玉米临界氮稀释曲线和氮营养指数研究.作物学报,2013,39：292-299
刘芷宇.植物营养诊断的回顾与展望.土壤,1982,24：173-175
陆景陵.植物营养学.北京：中国农业大学出版社,2003
卢艳丽,李少昆,王纪华,等.冬小麦不同株型品种光谱响应及株型识别方法研究.作物学报,2006,31：1333-1339
梅安新,彭望碌,秦其明,等.遥感导论.北京：高等教育出版社,2001
浦瑞良,宫鹏.高光谱遥感及其应用.北京：高等教育出版社,2000
田国良,郭世忠.水稻光谱反射特性.自然资源,1982,2：73-81
武维华.植物生理学.北京：科学出版社,2004
薛晓萍,周治国,张丽娟,等.棉花花后临界氮浓度稀释模型的建立及在施氮量调控中的应用.生态学报,2006,26：1781-1791
闫湘,金继运,何萍,等.提高肥料利用率技术研究进展.中国农业科学,2008,41：450-459
杨长明,杨林章,韦朝领,等.不同品种水稻群体冠层光谱特征比较研究.应用生态学报,2002,13：689-692
岳善超.小麦玉米高产体系的氮肥优化管理：[博士学位论文].北京：中国农业大学,2013
张福锁,王激清,张卫峰,等.中国主要粮食作物肥料利用率现状与提高途径.土壤学报,2008,45：915-924
张俊华,张佳宝,贾科利.不同品种夏玉米光谱特征差异及其与农学参量相关性研究.土壤通报,2010：287-293
张兰民.从龙粳21的选育看黑龙江省超级稻育种.黑龙江农业科学.2011：9-12
Ahmad, I. S., Reid, J. F., Noguchi, N., et al. Nitrogen sensing for precision agriculture using chlorophyll maps. ASAE paper No.99-3035, American Society of Agricultural Engineers, St. Joseph, MI, USA, 1999
Bajwa, S., Mishra, A. and Norman, R. Canopy reflectance response to plant nitrogen accumulation in rice. Precision Agriculture,2010,11:488-506
Balasubramanian, V., Morales, A., Cruz, R., et al. On-farm adaptation of knowledge-intensive nitrogen management technologies for rice systems. Nutrient Cycling in Agroecosystems,1998,53:59-69
Barker, D. W. and Sawyer, J. E. Using active canopy sensors to quantify corn nitrogen stress and nitrogen application rate. Agronomy Journal,2010,102:964-971
Barnes, E., Clarke, T., Richards, S., et al. Coincident detection of crop water stress, nitrogen status and canopy density using ground based multispectral data. In:P. C. Robert, et al., editors, Proceding the 5th International Conference on Precision Agriculture:2000
Bausch, W. and Khosla, R. QuickBird satellite versus ground-based multi-spectral data for estimating nitrogen status of irrigated maize. Precision Agriculture,2010,11:274-290
Berntsen, J., Thomsen, A., Schelde, K., et al. Algorithms for sensor-based redistribution of nitrogen fertilizer in winter wheat. Precision Agriculture,2006,7:65-83
Bijay-Singh, Sharma, R. K., Jaspreet-Kaur, et al. Assessment of the nitrogen management strategy using an optical sensor for irrigated wheat. Agronomy for Sustainable Development,2011,31:589-603
Blackburn, G. A. Hyperspectral remote sensing of plant pigments. Journal of Experimental Botany,2007,58: 855-867
Blackmer, T., Schepers, J. and Vigil, M. Chlorophyll meter readings in corn as affected by plant spacing. Communications in Soil Science & Plant Analysis,1993,24:2507-2516
Blackmer, T. and Schepers, J. Techniques for monitoring crop nitrogen status in corn. Communications in Soil Science & Plant Analysis,1994,25:1791-1800
Blackmer, T. and Schepers, J. Use of a chlorophyll meter to monitor nitrogen status and schedule fertigation for corn. Journal of Production Agriculture,1995,8:56-60
Blackmer, T. M., Schepers, J. S. and Varvel, G. E. Light reflectance compared with other nitrogen stress measurements in corn leaves. Agronomy Jouraary,1994,86:934-938
Boggs, J. L., Tsegaye, T., Coleman, T. L., et al. Relationship between hyperspectral reflectance, soil nitrate-nitrogen, cotton leaf chlorophyll, and cotton yield:A step toward precision agriculture. Journal of Sustainable Agriculture,2003,22:5-16
Broge, N. H. and Leblanc, E. Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density. Remote Sensing of Environment,2000,76:156-172
Broge, N. H. and Mortensen, J. V. Deriving green crop area index and canopy chlorophyll density of winter wheat from spectral reflectance data. Remote Sensing of Environment,2002,81:45-57
Bronson, K. F., Chua, T. T., Booker, J., et al. In-season nitrogen status sensing in irrigated cotton. Soil Science Society of America Journal,2003,67:1439-1448
Bronson, K. F., Booker, J., Keeling, J. W., et al. Cotton canopy reflectance at landscape scale as affected by nitrogen fertilization. Agronomy Journal,2005,97:654-660
Bullock, D. and Anderson, D. Evaluation of the Minolta SPAD-502 chlorophyll meter for nitrogen management in corn. Journal of Plant Nutrition,1998,21:741-755
Buschmann, C. and Nagel, E. In vivo spectroscopy and internal optics of leaves as basis for remote sensing of vegetation. International Journal of Remote Sensing,1993,14:711-722
Cabrera, M. and Kissel, D. E. Evaluation of a method to predict nitrogen mineralized from soil organic matter under field conditions. Soil Science Society of America Journal,1988,52:1027-1031
Canfield, D. E., Glazer, A. N. and Falkowski, P. G. The evolution and future of Earth's nitrogen cycle. Science,2010,330:192-196
Cao, Q., Cui, Z., Chen, X., et al. Quantifying spatial variability of indigenous nitrogen supply for precision nitrogen management in small scale farming. Precision Agriculture,2012,13:45-61
Cartelat, A., Cerovic, Z., Goulas, Y., et al. Optically assessed contents of leaf polyphenolics and chlorophyll as indicators of nitrogen deficiency in wheat (Triticum aestivum L.). Field Crops Research,2005,91: 35-49
Cassman, K. G. Ecological intensification of cereal production systems:yield potential, soil quality, and precision agriculture. Proceedings of the National Academy of Sciences of the United States of America, 1999,96:5952-5959
Cassman, K. G., Dobermann, A. and Walters, D. T. Agroecosystems, nitrogen-use efficiency, and nitrogen management. AMBIO:A Journal of the Human Environment,2002,31:132-140
Cassman, K. G., Dobermann, A., Walters, D. T., et al. Meeting cereal demand while protecting natural resources and improving environmental quality. Annual Review of Environment and Resources,2003, 28:315-358
Cerovic, Z. G., Masdoumier, G., Ghozlen, N. B., et al. A new optical leaf-clip meter for simultaneous non-destructive assessment of leaf chlorophyll and epidermal flavonoids. Physiologia Plantarum,2012,146: 251-260
Cerrato, M. and Blackmer, A. Comparison of models for describing; corn yield response to nitrogen fertilizer. Agronomy Journal,1990,82:138-143
Chappelle, E. W., Kim, M. S. and McMurtrey III, J. E. Ratio analysis of reflectance spectra (RARS):an algorithm for the remote estimation of the concentrations of chlorophyll a, chlorophyll b, and carotenoids in soybean leaves. Remote Sensing of Environment,1992,39:239-247
Chen, J. M. Evaluation of vegetation indices and a modified simple ratio for boreal applications. Canadian Journal of Remote Sensing,1996,22:229-242
Chen, P., Wang, J., Huang, W., et al. Critical Nitrogen Curve and Remote Detection of Nitrogen Nutrition Index for Corn in the Northwestern Plain of Shandong Province, China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2013,6:682-689
Chen, X., Zhang, F., Romheld, V., et al. Synchronizing N Supply from Soil and Fertilizer and N Demand of Winter Wheat by an Improved Nmin Method. Nutrient Cycling in Agroecosystems,2006,74:91-98
Chen, X., Cui, Z., Vitousek, P. M., et al. From the Cover:Integrated soil-crop system management for food security. Proceedings of the National Academy of Sciences,2011,108:6399-6404
Cho, M. A. and Skidmore, A. K. Anew technique for extracting the red edge position from hyperspectral data: The linear extrapolation method. Remote Sensing of Environment,2006,101:181-193
Conant, R. T., Berdanier, A. B. and Grace, P. R. Patterns and trends in nitrogen use and nitrogen recovery efficiency in world agriculture. Global Biogeochemical Cycles,2013,27:558-566
Cui, Z., Chen, X., Miao, Y., et al. On-farm evaluation of the improved soil N-based nitrogen management for summer maize in North China Plain. Agronomy Journal,2008a,100:517-525
Cui, Z., Chen, X., Miao, Y, et al. On-farm evaluation of winter wheat yield response to residual soil nitrate-N in North China Plain. Agronomy Journal,2008b,100:1527-1534
Cui, Z., Zhang, F., Chen, X., et al. On-farm evaluation of an in-season nitrogen management strategy based on soil Nmin test. Field Crops Research,2008c,105:48-55
Cui, Z., Zhang, F., Miao, Y, et al. Soil nitrate-N levels required for high yield maize production in the North China Plain. Nutrient Cycling in Agroecosystems,2008d,82:187-196
Cui, Z., Zhang, F., Chen, X., et al. In-season nitrogen management strategy for winter wheat:Maximizing yields, minimizing environmental impact in an over-fertilization context. Field Crops Research,2010, 116:140-146
Cui, Z., Yue, S., Wang, G., et al. Closing the yield gap could reduce projected greenhouse gas emissions:a case study of maize production in China. Global Change Biology,2013a,19:2467-2477
Cui, Z., Yue, S., Wang, G., et al. In-season root-zone N management for mitigating greenhouse gas emission and reactive N losses in intensive wheat production. Environmental Science & Technology,2013b,47: 6015-6022
Curran, P. J. Remote sensing of foliar chemistry. Remote Sensing of Environment,1989,30:271-278
Datt, B. A New Reflectance index for remote sensing of chlorophyll content in higher plants:tests using Eucalyptus leaves. Journal of Plant Physiology,1999,154:30-36
Daughtry, C., Walthall, C., Kim, M., et al. Estimating corn leaf chlorophyll concentration from leaf and canopy reflectance. Remote Sensing of Environment,2000,74:229-239
Debaeke, P., Rouet, P. and Justes, E. Relationship between the normalized SPAD index and the nitrogen nutrition index:application to durum Wheat. Journal of Plant Nutrition,2006,29:75-92
Dellinger, A. E., Schmidt, J. P. and Beegle, D. B. Developing nitrogen fertilizer recommendations for corn using an active sensor. Agronomy Journal,2008,100:1546-1552
Diacono, M., Rubino, P. and Montemurro, F. Precision nitrogen management of wheat. A review. Agronomy for Sustainable Development,2013,33:219-241
Diaz, R. J. and Rosenberg, R. Spreading dead zones and consequences for marine ecosystems. Science,2008, 321:926-929
Dobermann, A., Witt, C., Dawe, D., et al. Site-specific nutrient management for intensive rice cropping systems in Asia. Field Crops Research,2002,74:37-66
Dobermann, A. and Cassman, K. G. Cereal area and nitrogen use efficiency are drivers of future nitrogen fertilizer consumption. Science in China Series C:Life Sciences,2005,48:745-758
Duvick, D. and Cassman, K. G. Post-green revolution trends in yield potential of temperate maize in the North-Central United States. Crop Science,1999,39:1622-1630
Eitel, J. U. H., Long, D. S., Gessler, P., et al. Using in-situ measurements to evaluate the new RapidEye■ satellite series for prediction of wheat nitrogen status. International Journal of Remote Sensing,2007,28: 4183-4190
Eitel, J. U. H., Keefe, R. F., Long, D. S., et al. Active ground optical remote sensing for improved monitoring of seedling stress in nurseries. Sensors,2010,10:2843-2850
Eitel, J. U. H., Vierling, L. A., Long, D. S., et al. Early season remote sensing of wheat nitrogen status using a green scanning laser. Agricultural and Forest Meteorology,2011,151:1338-1345
Elliott, D., Reuter, D., Growden, B., et al. Nitrogen:improved strategies for diagnosing and correcting nitrogen deficiency in spring wheat. Journal of Plant Nutrition,1987,10:1761-1770
Elwadie, M. E., Pierce, F. J. and Qi, J. Remote sensing of canopy dynamics and biophysical variables estimation of corn in Michigan. Agronomy Journal,2005,97:99-105
Engel, R. and Zubriski, J. Nitrogen concentrations in spring wheat at several growth stages. Communications in Soil Science & Plant Analysis,1982,13:531-544
Erdle, K., Mistele, B. and Schmidhalter, U. Comparison of active and passive spectral sensors in discriminating biomass parameters and nitrogen status in wheat cultivars. Field Crops Research,2011, 124:74-84
Erisman, J. W., Sutton, M. A., Galloway, J., et al. How a century of ammonia synthesis changed the world. Nature Geoscience,2008,1:636-639
Erisman, J. W, Galloway, J. N., Seitzinger, S., et al. Consequences of human modification of the global nitrogen cycle. Philosophical Transactions of the Royal Society B:Biological Sciences,2013,368: 20130116
Evenson, R. E. Assessing the Impact of the Green Revolution,1960 to 2000. Science,2003,300:758-762
FAOSTAT. FAO Statistical databases.2013:Available at http://www.fao.org
Feret, J.-B., Francois, C., Asner, G. P., et al. PROSPECT-4 and 5:Advances in the leaf optical properties model separating photosynthetic pigments. Remote Sensing of Environment,2008,112:3030-3043
Fitzgerald, G., Rodriguez, D. and O'Leary, G. Measuring and predicting canopy nitrogen nutrition in wheat using a spectral index—The canopy chlorophyll content index (CCCI). Field Crops Research,2010,116: 318-324
Flowers, M., Weisz, R. and Heiniger, R. Quantitative approaches for using color infrared photography for assessing in-season nitrogen status in winter wheat. Agronomy Journal,2003,95:1189-1200
Flynn, E. S., Dougherty, C. T. and Wendroth, O. Assessment of pasture biomass with the normalized difference vegetation index from active ground-based sensors. Agronomy Journal,2008,100:114-121
Forster, P., Ramaswamy, V., Artaxo, P., et al. Changes in atmospheric constituents and in radiative forcing. In: S. Solomon, et al., editors, Climate change 2007:The Physical Science Basis Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridege, United Kingdom and New York, NY, USA:Cambridge Universtiy Press,2007
Fowler, D., Coyle, M., Skiba, U., et al. The global nitrogen cycle in the twenty-first century. Philosophical Transactions of the Royal Society B:Biological Sciences,2013,368:20130164
Galloway, J. N., Townsend, A. R., Erisman, J. W., et al. Transformation of the nitrogen cycle:recent trends, questions, and potential solutions. Science,2008,320:889-892
Gao, B., Ju, X., Zhang, Q., et al. New estimates of direct N2O emissions from Chinese croplands from 1980 to 2007 using localized emission factors. Biogeosciences,2011,8:3011-3024
Garnett, T., Appleby, M., Balmford, A., et al. Sustainable intensification in agriculture:premises and policies. Science,2013,341:33-34
Gastal, F. and Lemaire, G. N uptake and distribution in crops:an agronomical and ecophysiological perspective. Journal of Experimental Botany,2002,53:789-799
Geraldson, C. and Tyler, K. Plant analysis as an aid in fertilizing vegetable crops. Soil Testing and Plant Analysis. SSSABook Series,1990,3:549-562
Gitelson, A. A., Kaufman, Y. J. and Merzlyak, M. N. Use of a green channel in remote sensing of global vegetation from EOS-MODIS. Remote Sensing of Environment,1996,58:289-298
Gitelson, A. A., Kaufman, Y. J., Stark, R., et al. Novel algorithms for remote estimation of vegetation fraction. Remote Sensing of Environment,2002,80:76-87
Gitelson, A. A. Remote estimation of leaf area index and green leaf biomass in maize canopies. Geophysical Research Letters,2003,30 (5):1248, http://dx.doi.org/1210.1029/2002GL016450
Gitelson, A. A., Gritz (?), Y. and Merzlyak, M. N. Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves. Journal of Plant Physiology,2003,160:271-282
Gitelson, A. A. Wide dynamic range vegetation index for remote quantification of biophysical characteristics of vegetation. Journal of Plant Physiology,2004,161:165-173
Gitelson, A. A., Vina, A. s., Ciganda, V. n., et al. Remote estimation of canopy chlorophyll content in crops. Geophysical Research Letters,2005,32:L08403, http://dx.doi.org/08410.01029/02005GL022688
Gitelson, A. A., Keydan, G. P. and Merzlyak, M. N. Three-band model for noninvasive estimation of chlorophyll, carotenoids, and anthocyanin contents in higher plant leaves. Geophysical Research Letters, 2006,33:111402
Gitelson, A. A. Remote estimation of crop fractional vegetation cover:the use of noise equivalent as an indicator of performance of vegetation indices. International Journal of Remote Sensing,2013:1-13
Gnyp, M. L., Miao, Y., Yuan, F., et al. Hyperspectral canopy sensing of paddy rice aboveground biomass at different growth stages. Field Crops Research,2014,155:42-55
Godfray, H. C. J., Beddington, J. R., Crute, I. R., et al. Food Security:The Challenge of Feeding 9 Billion People. Science,2010,327:812-818
Godoy, L. d., Boas, R. V. and Grassi Filho, H. Nitrogen fertilizing in corn based in chlorophyll meter reading and sufficiency index in nitrogen. Acta Scientiarum-Agronomy,2003,25:373-380
Goulas, Y., Cerovic, Z. G., Cartelat, A., et al. Dualex:a new instrument for field measurements of epidermal ultraviolet absorbance by chlorophyll fluorescence. Applied Optics,2004,43:4488-4496
Greenwood, D., Neeteson, J. and Draycott, A. Quantitative relationships for the dependence of growth rate of arable crops on their nitrogen content, dry weight and aerial environment. Plant and Soil,1986,91: 281-301
Greenwood, D., Gastal, F., Lemaire, G., et al. Growth rate and %N of field grown crops:theory and experiments. Annals of Botany,1991,67:181-190
Gu, B., Leach, A. M., Ma, L., et al. Nitrogen footprint in China:food, energy, and nonfood goods. Environmental Science & Technology,2013,47:9217-9224
Guo, J. H., Liu, X. J., Zhang, Y., et al. Significant acidification in major Chinese croplands. Science,2010, 327:1008-1010
Haboudane, D., Miller, J. R., Tremblay, N., et al. Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture. Remote Sensing of Environment,2002, 81:416-426
Haboudane, D. Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies:Modeling and validation in the context of precision agriculture. Remote Sensing of Environment,2004,90:337-352
Haboudane, D., Miller, J. R., Pattey, E., et al. Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies:Modeling and validation in the context of precision agriculture. Remote Sensing of Environment,2004,90:337-352
Hatfield, J. L. and Prueger, J. H. Value of using different vegetative indices to quantify agricultural crop characteristics at different growth stages under varying management practices. Remote Sensing,2010,2: 562-578
Hawkins, J. A., Sawyer, J. E., Barker, D. W., et al. Using relative chlorophyll meter values to determine nitrogen application rates for corn. Agronomy Journal,2007,99:1034-1040
Holland, K. and Schepers, J. Active-crop sensor calibration using the virtual reference concept. In:J. V. Stafford (Ed.), Precision agriculture 2011, Proceedings of the 8th European Conference on Precision Agriculture. Prague:Czech Republic, Czech Centre for Science and Society,2011,469-479
Holland, K. H. and Schepers, J. S. Derivation of a variable rate nitrogen application model for in-season fertilization of corn. Agronomy Journal,2010,102:1415-1424
Horwitz, W. Official methods of analysis. Washington, DC:Association of Official Agricultural Chemists, 1970
Houles, V., Guerif, M. and Mary, B. Elaboration of a nitrogen nutrition indicator for winter wheat based on leaf area index and chlorophyll content for making nitrogen recommendations. European Journal of Agronomy,2007,27:1-11
Huang, Y. and Tang, Y. An estimate of greenhouse gas (N2O and CO2) mitigation potential under various scenarios of nitrogen use efficiency in Chinese croplands. Global Change Biology,2010,16:2958-2970
Huete, A. R. A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment,1988,25:295-309
Hussain, F., Bronson, K. and Peng, S. Use of chlorophyll meter sufficiency indices for nitrogen management of irrigated rice in Asia. Agronomy Journal,2000,92:875-879
IFA. International Fertilizer Association Database.2010:Available at http://www.ifa.com/
IPCC. Agriculture, Forestry and Other Land Uses (AFOLU). In:S. Eggleston, et al., editors,2006 IPCC/Guidelines for National Greenhouse Gas Inventories. Kanagawa, Japan:Institute for Global Environmental Strategies,2006,54
Jacquemoud, S. and Baret, F. PROSPECT:A model of leaf optical properties spectra. Remote Sensing of Environment,1990,34:75-91
Jasper, J., Reusch, S. and Link, A. Active sensing of the N status of wheat using optimized wave-length combination:Impact of seed rate, variety and growth stage. In:E. J. v. Henten, et al., editors,9th Precision agriculture:Wageningen Academic Publishers,2009,23-30
Jeuffroy, M. H. and Recous, S. Azodyn:a simple model simulating the date of nitrogen deficiency for decision support in wheat fertilization. European Journal of Agronomy,1999,10:129-144
Johnson, G. and Raun, W. Nitrogen response index as a guide to fertilizer management. Journal of Plant Nutrition,2003,26:249-262
Ju, X. T., Xing, G. X., Chen, X. P., et al. From the Cover:Reducing environmental risk by improving N management in intensive Chinese agricultural systems. Proceedings of the National Academy of Sciences, USA,2009,106:3041-3046
Justes, E., Mary, B., Meynard, J. M., et al. Determination of a critical nitrogen dilution curve for winter wheat crops. Annals of Botany,1994,74:397-407
Justice, C. O., Vermote, E., Townshend, J. R. G., et al. The Moderate Resolution Imaging Spectroradiometer (MODIS):land remote sensing for global change research. Geoscience and Remote Sensing, IEEE Transactions on,1998,36:1228-1249
Kahrl, F., Li, Y, Su, Y, et al. Greenhouse gas emissions from nitrogen fertilizer use in China, environmental science & policy,2010,13:688-694
Kandil, F., Grace, M., Seigler, D., et al. Polyphenolics in Rhizophora mangle L. leaves and their changes during leaf development and senescence. Trees,2004,18:518-528
Kitchen, N. R., Sudduth, K. A., Drummond, S. T., et al. Ground-based canopy reflectance sensing for variable-rate nitrogen corn fertilization. Agronomy Journal,2010,102:71-84
Knipling, E. B. Physical and physiological basis for the reflectance of visible and near-infrared radiation from vegetation. Remote Sensing of Environment,1970,1:155-159
Ladha, J. K., Pathak, H., J Krupnik, T., et al. Efficiency of fertilizer nitrogen in cereal production:retrospects and prospects. Advances in Agronomy,2005,87:85-156
Lamb, D., Steyn-Ross, M., Schaare, P., et al. Estimating leaf nitrogen concentration in ryegrass (Lolium spp.) pasture using the chlorophyll red-edge:theoretical modelling and experimental observations. International Journal of Remote Sensing,2002,23:3619-3648
Le, C., Zha, Y., Li, Y., et al. Eutrophication of lake waters in China:cost, causes, and control. Environmental Management,2010,45:662-668
Le Maire, G., Francois, C. and Dufrene, E. Towards universal broad leaf chlorophyll indices using PROSPECT simulated database and hyperspectral reflectance measurements. Remote Sensing of Environment,2004,89:1-28
Leight, R. and Johnson, A. Nitrogen concentration in field grown spring barely:an experiment of the usefulness of expecting concentration on the basis of tissue water. Journal of Agricultural Science,1985, 105:397-406
Lemaire, G., Khaity, M., Onillon, B., et al. Dynamics of accumulation and partitioning of N in leaves, stems and roots of lucerne (Medicago sativa L.) in a dense canopy. Annals of Botany,1992,70:429-435
Lemaire, G. and Gastal, F. N uptake and distribution in plant canopies. Diagnosis of the nitrogen status in crops. Springer,1997,3-43
Lemaire, G., Avice, J., Kim, T., et al. Developmental changes in shoot N dynamics of lucerne (Medicago sativa L.) in relation to leaf growth dynamics as a function of plant density and hierarchical position within the canopy. Journal of Experimental Botany,2005,56:935-943
Lemaire, G., Jeuffroy, M.-H. and Gastal, F. Diagnosis tool for plant and crop N status in vegetative stage. European Journal of Agronomy,2008a,28:614-624
Lemaire, G., van Oosterom, E., Jeuffroy, M.-H., et al. Crop species present different qualitative types of response to N deficiency during their vegetative growth. Field Crops Research,2008b,105:253-265
Li, F., Miao, Y., Zhang, F., et al. In-season optical sensing improves nitrogen-use efficiency for winter wheat. Soil Science Society of America Journal,2009,73:1566-1574
Li, F., Miao, Y, Chen, X., et al. Estimating winter wheat biomass and nitrogen status using an active crop sensor. Intelligent Automation and Soft Computing,2010a,16:1221-1230
Li, F., Miao, Y, Hennig, S. D., et al. Evaluating hyperspectral vegetation indices for estimating nitrogen concentration of winter wheat at different growth stages. Precision Agriculture,2010b,11:335-357
Li, F., Mistele, B., Hu, Y., et al. Remotely estimating aerial N status of phenologically differing winter wheat cultivars grown in contrasting climatic and geographic zones in China and Germany. Field Crops Research,2012,138:21-32
Li, X., Hu, C., Delgado, J. A., et al. Increased nitrogen use efficiencies as a key mitigation alternative to reduce nitrate leaching in north china plain. Agricultural Water Management,2007,89:137-147
Liu, X., Ju, X., Zhang, F., et al. Nitrogen recommendation for winter wheat using Nmin test and rapid plant tests in North China Plain. Communications in Soil Science and Plant Analysis,2003,34:2539-2551
Liu, X., Zhang, Y, Han, W., et al. Enhanced nitrogen deposition over China. Nature,2013,494:459-462
Long, D. S., Eitel, J. U. and Huggins, D. R. Assessing nitrogen status of dryland wheat using the canopy chlorophyll content index. Crop Management,2009,8, http://dx.doi.org/10.1094/CM-2009-1211-01-RS
Lorenzen, B. and Jensen, A. Reflectance of blue, green, red and near infrared radiation from wetland vegetation used in a model discriminating live and dead above ground biomass. New Phytologist,1988, 108:345-355
Lukina, E. V, Freeman, K. W., Wynn, K. J., et al. Nitrogen fertilization optimization algorithm based on in-season estimates of yield and plant nitrogen uptake. Journal of Plant Nutrition,2001,24:885-898
Martin, K., Raun, W. and Solie, J. By-plant prediction of corn grain yield using optical sensor readings and measured plant height. Journal of Plant Nutrition,2012,35:1429-1439
Meng, Q., Sun, Q., Chen, X., et al. Alternative cropping systems for sustainable water and nitrogen use in the North China Plain. Agriculture, Ecosystems & Environment,2012,146:93-102
Miao, Y, Mulla, D. J., Hernandez, J. A, et al. Potential impact of precision nitrogen management on corn yield, protein content, and test weight. Soil Science Society of America Journal,2007,71:1490-1499
Miao, Y, Mulla, D. J., Randall, G. W., et al. Combining chlorophyll meter readings and high spatial resolution remote sensing images for in-season site-specific nitrogen management of corn. Precision Agriculture,2009,10:45-62
Miao, Y, Stewart, B. A. and Zhang, F. Long-term experiments for sustainable nutrient management in China. Areview. Agronomy for Sustainable Development,2011,31:397-414
Mistele, B. and Schmidhalter, U. Estimating the nitrogen nutrition index using spectral canopy reflectance measurements. European Journal of Agronomy,2008,29:184-190
Mulla, D. J. Twenty five years of remote sensing in precision agriculture:Key advances and remaining knowledge gaps. Biosystems Engineering,2012,114:358-371
Mullen, R. W., Freeman, K. W., Raun, W. R., et al. Identifying an in-season response index and the potential to increase wheat yield with nitrogen. Agronomy Journal,2003,95:347-351
Olfs, H. W., Blankenau, K., Brentrup, F., et al. Soil-and plant-based nitrogen-fertilizer recommendations in arable farming. Journal of Plant Nutrition and Soil Science,2005,168:414-431
Patel, N., Singh, T., Sahai, B., et al. Spectral response of rice crop and its relation to yield and yield attributes. International Journal of Remote Sensing,1985,6:657-664
Peng, S., Garcia, F., Laza, R., et al. Increased N-use efficiency using a chlorophyll meter on high-yielding irrigated rice. Field Crops Research,1996,47:243-252
Peng, S., Buresh, R. J., Huang, J., et al. Strategies for overcoming low agronomic nitrogen use efficiency in irrigated rice systems in China. Field Crops Research,2006,96:37-47
Peng, S., Tang, Q. and Zou, Y. Current status and challenges of rice production in China. Plant Production Science,2009,12:3-8
Peng, S., Buresh, R. J., Huang, J., et al. Improving nitrogen fertilization in rice by sitespecific N management. A review. Agronomy for Sustainable Development,2010,30:649-656
Perry, E. M., Pierce, F. J., Davenport, J. R., et al. Comparing active optical and airborne measurements of grape canopies. International Symposium on Application of Precision Agriculture for Fruits and Vegetables,2009,824:75-83
Peterson, T. A. Using a chlorophyll meter to improve N management. Cooperative Extension, Institute of Agriculture and Natural Resources, University of Nebraska-Lincoln,1993
Piekielek, W. P., Fox, R. H., Toth, J. D., et al. Use of a chlorophyll meter at the early dent stage of corn to evaluate nitrogen sufficiency. Agronomy Journal,1995,87:403-408
Plenet, D. and Lemaire, G. Relationships between dynamics of nitrogen uptake and dry matter accumulation in maize crops. Determination of critical N concentration. Plant and Soil,2000,216:65-82
Prasad, M. and Spiers, T. Evaluation of a rapid method for plant sap nitrate analysis. Communications in Soil Science & Plant Analysis,1984,15:673-679
Prost, L. and Jeuffroy, M.-H. Replacing the nitrogen nutrition index by the chlorophyll meter to assess wheat N status. Agronomy for Sustainable Development,2007,27:321-330
Qi, J., Chehbouni, A, Huete, A., et al. A modified soil adjusted vegetation index. Remote Sensing of Environment,1994,48:119-126
Raun, W., Solie, J., Stone, M., et al. Automated calibration stamp technology for improved in-season nitrogen fertilization. Agronomy Journal,2005a,97:338-342
Raun, W., Solie, J., Taylor, R., et al. Ramp calibration strip technology for determining midseason nitrogen rates in corn and wheat. Agronomy Journal,2008,100:1088-1093
Raun, W. R. and Johnson, G. V. Improving nitrogen use efficiency for cereal production. Agronomy Journal, 1999,91:357-363
Raun, W. R., Solie, J. B., Johnson, G. V., et al. In-season prediction of potential grain yield in winter wheat using canopy reflectance. Agronomy Journal,2001,93:131-138
Raun, W. R., Solie, J. B., Johnson, G. V., et al. Improving nitrogen use efficiency in cereal grain production with optical sensing and variable rate application. Agronomy Journal,2002,94:815-820
Raun, W. R., Solie, J. B., Stone, M. L., et al. Optical sensor-based algorithm for crop nitrogen fertilization. Communications in Soil Science and Plant Analysis,2005b,36:2759-2781
Ravishankara, A., Daniel, J. S. and Portmann, R. W. Nitrous oxide (N2O):the dominant ozone-depleting substance emitted in the 21st century. Science,2009,326:123-125
Reay, D. S., Davidson, E. A., Smith, K. A., et al. Global agriculture and nitrous oxide emissions. Nature Climate Change,2012,2:410-416
Richardson, A. D., Duigan, S. P. and Berlyn, G. P. An evaluation of noninvasive methods to estimate foliar chlorophyll content. New Phytologist,2002,153:185-194
Robertson, G. P. and Vitousek, P. M. Nitrogen in agriculture:balancing the cost of an essential resource. Annual Review of Environment and Resources,2009,34:97-125
Roberts, D., Brorsen, B. W., Taylor, R., et al. Replicability of nitrogen recommendations from ramped calibration strips in winter wheat. Precision Agriculture,2011,12:653-665
Rockstrom, J., Steffen, W., Noone, K., et al. A safe operating space for humanity. Nature,2009,461:472-475
Rondeaux, G., Steven, M. and Baret, F. Optimization of soil-adjusted vegetation indices. Remote Sensing of Environment,1996,55:95-107
Roth, G., Fox, R. and Marshall, H. Plant tissue tests for predicting nitrogen fertilizer requirements of winter wheat. Agronomy Journal,1989,81:502-507
Roujean, J. L. and Breon, F. M. Estimating PAR absorbed by vegetation from bidirectional reflectance measurements. Remote Sensing of Environment,1995,51:375-384
Samborski, S. and Rozbicki, J. Use of nitrogen sufficiency index for calibration of a chlorophyll meter SPAD-502 readings in winter triticale. Book of proceedings. VII Congress of the European Society for Agronomy:2002,15-18
Samborski, S. M., Tremblay, N. and Fallon, E. Strategies to make use of plant sensors-based diagnostic information for nitrogen recommendations. Agronomy Journal,2009,101:800-816
Sawyer, J. E., Lundvall, J., Hawkins, J. S., et al. Sensing nitrogen stress in corn. Agriculture and Environment Extension Publications,2011
Scharf, P. C. and Lory, J. A Calibrating corn color from aerial photographs to predict sidedress nitrogen need. Agronomy Journal,2002,94:397-404
Scharf, P. C., Brouder, S. M. and Hoeft, R. G. Chlorophyll meter readings can predict nitrogen need and yield response of corn in the north-central USA. Agronomy Journal,2006,98:655-665
Schlemmer, M. R., Francis, D. D., Shanahan, J., et al. Remotely measuring chlorophyll content in corn leaves with differing nitrogen levels and relative water content. Agronomy Journal,2005,97:106-112
Schmidt, J., Beegle, D., Zhu, Q., et al. Improving in-season nitrogen recommendations for maize using an active sensor. Field Crops Research,2011,120:94-101
Schmidt, J. P., Dellinger, A. E. and Beegle, D. B. Nitrogen Recommendations for corn:an on-the-go sensor compared with current recommendation methods. Agronomy Journal,2009,101:916-924
Schroder, J., Neeteson, J., Oenema, O., et al. Does the crop or the soil indicate how to save nitrogen in maize production?:Reviewing the state of the art. Field Crops Research,2000,66:151-164
Seek, P. A., Diagne, A., Mohanty, S., et al. Crops that feed the world 7:Rice. Food Security,2012,4:7-24
Shapiro, C. A. Using a chlorophyll meter to manage nitrogen applications to corn with high nitrate irrigation water. Communications in Soil Science & Plant Analysis,1999,30:1037-1049
Shaver, T., Khosla, R. and Westfall, D. Evaluation of two crop canopy sensors for nitrogen recommendations in irrigated maize. Journal of Plant Nutrition,2014,37:406-419
Shaver, T. M., Khosla, R. and Westfall, D. G. Evaluation of two ground-based active crop canopy sensors in maize:growth stage, row spacing, and sensor movement speed. Soil Science Society of America Journal, 2010,74:2101-2108
Shaver, T. M., Khosla, R. and Westfall, D. G. Evaluation of two crop canopy sensors for nitrogen variability determination in irrigated maize. Precision Agriculture,2011,12:892-904
Sheehy, J., Dionora, M., Mitchell, P., et al. Critical nitrogen concentrations:implications for high-yielding rice (Oryza sativa L.) cultivars in the tropics. Field Crops Research,1998,59:31-41
Shen, J., Cui, Z., Miao, Y., et al. Transforming agriculture in China:From solely high yield to both high yield and high resource use efficiency. Global Food Security,2013,2:1-8
Shibayama, M. and Akiyama, T. Seasonal visible, near-infrared and mid-infrared spectra of rice canopies in relation to LAI and above-ground dry phytomass. Remote Sensing of Environment,1989,27:119-127
Shikada, M. and Miyakita, K. Effects of solar and view angles on reflectance for paddy field canopies. Geocarto International,1992,7:9-17
Shiratsuchi, L., Ferguson, R., Shanahan, J., et al. Water and nitrogen effects on active canopy sensor vegetation indices. Agronomy Journal,2011,103:1815-1826
Shou, L., Jia, L., Cui, Z., et al. Using high-resolution satellite imaging to evaluate nitrogen status of winter wheat. Journal of Plant Nutrition,2007,30:1669-1680
Snyder, C. S. and Fixen, P. E. Plant nutrient management and risks of nitrous oxide emission. Journal of Soil and Water Conservation,2012,67:137-144
Solan, F., Hodgen, P., Shanahan, J., et al. Time of day and maize leaf wetness effects on active sensor readings. Agronomy Abstracts,2004,4253
Solari, F., Shanahan, J., Ferguson, R., et al. Active sensor reflectance measurements of corn nitrogen status and yield potential. Agronomy Journal,2008,100:571-579
Solari, F., Shanahan, J. F., Ferguson, R. B., et al. An active sensor algorithm for corn nitrogen recommendations based on a chlorophyll meter algorithm. Agronomy Journal,2010,102:1090-1098
Soltanpour, P., Malakouti, M. and Ronaghi, A. Comparison of diagnosis and recommendation integrated system and nutrient sufficiency range for corn. Soil Science Society of America Journal,1995,59: 133-139
Sripada, R. P., Heiniger, R. W., White, J. G., et al. Aerial color infrared photography for determining late-season nitrogen requirements in corn. Agronomy Journal,2005,97:1443-1451
Sripada, R. P., Heiniger, R. W., White, J. G., et al. Aerial color infrared photography for determining early in-season nitrogen requirements in corn. Agronomy Journal,2006,98:968-977
Sripada, R. P., Schmidt, J. P., Dellinger, A. E., et al. Evaluating multiple indices from a canopy reflectance sensor to estimate corn N requirements. Agronomy Journal,2008,100:1553-1561
Stockle, C. and Debaeke, P. Modeling crop nitrogen requirements:a critical analysis. Developments in Crop Science,1997,25:217-225
Stokes, D., Sylvester-Bradley, R., Clare, R., et al. An integrated approach to nitrogen nutrition for wheat. HGCA Project Report No.159,1998
Stroppiana, D., Boschetti, M., Brivio, P. A., et al. Plant nitrogen concentration in paddy rice from field canopy hyperspectral radiometry. Field Crops Research,2009,111:119-129
Sutton, M. A., Oenema, O., Erisman, J. W., et al. Too much of a good thing. Nature,2011,472:159-161
Teal, R., Tubana, B., Girma, K., et al. In-season prediction of corn grain yield potential using normalized difference vegetation index. Agronomy Journal,2006,98:1488-1494
Tester, M. and Langridge, P. Breeding technologies to increase crop production in a changing world. Science, 2010,327:818-822
Thomas, J. and Gausman, H. Leaf reflectance vs. leaf chlorophyll and carotenoid concentrations for eight crops. Agronomy Journal,1977,69:799-802
Thomason, W. E., Phillips, S. B., Davis, P. H., et al. Variable nitrogen rate determination from plant spectral reflectance in soft red winter wheat. Precision Agriculture,2011,12:666-681
Tilman, D. Global environmental impacts of agricultural expansion:the need for sustainable and efficient practices. Proceedings of the National Academy of Sciences,1999,96:5995-6000
Tilman, D., Cassman, K. G., Matson, P. A., et al. Agricultural sustainability and intensive production practices. Nature,2002,418:671-677
Tilman, D., Balzer, C., Hill, J., et al. Global food demand and the sustainable intensification of agriculture. Proceedings of the National Academy of Sciences,2011,108:20260-20264
Tollenaar, M. and Lee, E. Yield potential, yield stability and stress tolerance in maize. Field Crops Research, 2002,75:161-169
Tremblay, N., Wang, Z. and Belec, C. Evaluation of the dualex for the assessment of corn nitrogen status. Journal of Plant Nutrition,2007,30:1355-1369
Tremblay, N., Wang, Z. and Belec, C. Performance of dualex in spring wheat for crop nitrogen status assessment, yield prediction and estimation of soil nitrate content. Journal of Plant Nutrition,2010,33: 57-70
Tremblay, N., Fallon, E. and Ziadi, N. Sensing of crop nitrogen status:Opportunities, tools, limitations, and supporting information requirements. HortTechnology,2011,21:274-281
Tremblay, N., Wang, Z. and Cerovic, Z. G. Sensing crop nitrogen status with fluorescence indicators. A review. Agronomy for Sustainable Development,2012,32:451-464
Tubafla, B., Harrell, D., Walker, T., et al. Relationships of spectral vegetation indices with rice biomass and grain yield at different sensor view angles. Agronomy Journal,2011,103:1405-1413
Tubana, B. S., Arnall, D. B., Walsh, O., et al. Adjusting midseason nitrogen rate using a sensor-based optimization algorithm to increase use efficiency in corn. Journal of Plant Nutrition,2008,31: 1393-1419
Tucker, C. J. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment,1979,8:127-150
Varvel, G. E., Schepers, J. S. and Francis, D. D. Ability for in-season correction of nitrogen deficiency in corn using chlorophyll meters. Soil Science Society of America Journal,1997,61:1233-1239
Varvel, G. E., Wilhelm, W. W., Shanahan, J. F., et al. An Algorithm for corn nitrogen recommendations using a chlorophyll meter based sufficiency index. Agronomy Journal,2007,99:701-706
Verhoef, W. Earth observation modeling based on layer scattering matrices. Remote Sensing of Environment, 1985,17:165-178
Vos, J. and Bom, M. Hand-held chlorophyll meter:a promising tool to assess the nitrogen status of potato foliage. Potato Research,1993,36:301-308
Wang, G., Dobermann, A., Witt, C., et al. Performance of site-specific nutrient management for irrigated rice in southeast China. Agronomy Journal,2001,93:869-878
Wang, W., Yao, X., Yao, X., et al. Estimating leaf nitrogen concentration with three-band vegetation indices in rice and wheat. Field Crops Research,2012,129:90-98
Wehrmann, J., Scharpf, H., Boehmer, M., et al. Determination of nitrogen fertilizer requirements by nitrate analysis of the soil and of the plant. In Boehmer M. (ed.), Plant Nutrition 9th International Colloquium on Plant Nutrition:1982,202-208
Welsh, J., Wood, G., Godwin, R., et al. Developing strategies for spatially variable nitrogen application in cereals, part II:wheat. Biosystems Engineering,2003,84:495-511
Wood, G. A., Welsh, J. P., Godwin, R. J., et al. Real-time measures of canopy size as a basis for spatially varying nitrogen applications to winter wheat sown at different seed rates. Biosystems Engineering, 2003,84:513-531
Wu, J., Wang, D. and Bauer, M. E. Assessing broadband vegetation indices and QuickBird data in estimating leaf area index of corn and potato canopies. Field Crops Research,2007,102:33-42
Xue, L. and Yang, L. Recommendations for nitrogen fertiliser topdressing rates in rice using canopy reflectance spectra. Biosystems Engineering,2008,100:524-534
Xue, L., Li, G., Qin, X., et al. Topdressing nitrogen recommendation for early rice with an active sensor in south China. Precision Agriculture,2013:1-16
Yang, H., Yang, J., Lv, Y., et al. SPAD values and nitrogen nutrition index for the evaluation of rice nitrogen status. Plant Production Science,2014,17:81-92
Yao, X., Ata-Ul-Karim, S. T., Zhu, Y, et al. Development of critical nitrogen dilution curve in rice based on leaf dry matter. European Journal of Agronomy,2014a,55:20-28
Yao, X., Zhao, B., Tian, Y. C., et al. Using leaf dry matter to quantify the critical nitrogen dilution curve for winter wheat cultivated in eastern China. Field Crops Research,2014b,159:33-42
Yao, Y., Miao, Y, Huang, S., et al. Active canopy sensor-based precision N management strategy for rice. Agronomy for Sustainable Development,2012,32:925-933
Yu, K., Li, F., Gnyp, M. L., et al. Remotely detecting canopy nitrogen concentration and uptake of paddy rice in the Northeast China Plain. ISPRS Journal of Photogrammetry and Remote Sensing,2013,78: 102-115
Yue, S., Sun, F., Meng, Q., et al. Validation of a critical nitrogen curve for summer maize in the North China Plain. Pedosphere,2014,24:76-83
Yue, S., Meng, Q., Zhao, R., et al. Critical nitrogen dilution curve for optimizing nitrogen management of winter wheat production in the North China Plain. Agronomy Journal,2012a,104:523-529
Yue, S., Meng, Q., Zhao, R., et al. Change in nitrogen requirement with increasing grain yield for winter wheat. Agronomy Journal,2012b,104:1687-1693
Yue, X., Hu, Y., Zhang, H., et al. Green window approach for improving nitrogen management by farmers in small-scale wheat fields. The Journal of Agricultural Science,2014:1-9
Zebarth, B., Younie, M., Paul, J., et al. Evaluation of leaf chlorophyll index for making fertilizer nitrogen recommendations for silage corn in a high fertility environment. Communications in Soil Science and Plant Analysis,2002,33:665-684
Zhang, F., Cui, Z., Chen, X., et al. Integrated nutrient management for food security and environmental quality in China. Advances in Agronomy,2012,116:1-40
Zhang, R, Chen, X. and Vitousek, P. Chinese agriculture:An experiment for the world. Nature,2013a,497: 33-35
Zhang, H., Smeal, D., Arnold, R., et al. Potato nitrogen management by monitoring petiole nitrate level. Journal of Plant Nutrition,1996,19:1405-1412
Zhang, Q. Inaugural Article:Strategies for developing Green Super Rice. Proceedings of the National Academy of Sciences, USA,2007,104:16402-16409
Zhang, W., Dou, Z., He, P., et al. New technologies reduce greenhouse gas emissions from nitrogenous fertilizer in China. Proceedings of the National Academy of Sciences,2013b,110:8375-8380
Zhao, G., Miao, Y., Wang, H., et al. A preliminary precision rice management system for increasing both grain yield and nitrogen use efficiency. Field Crops Research,2013,154:23-30
Zhao, R., Chen, X., Zhang, F., et al. Fertilization and nitrogen balance in a wheat-maize rotation system in North China. Agronomy Journal,2006,98:938-945
Zhen, R. and Leigh, R. Nitrate accumulation by wheat (Triticum aestivum) in relation to growth and tissue N concentrations. Plant Nutrition—Physiology and Applications. Springer,1990,17-20
Zhu, Z. and Chen, D. Nitrogen fertilizer use in China-Contributions to food production, impacts on the environment and best management strategies. Nutrient Cycling in Agroecosystems,2002,63:117-127
Zhu, Z. On the methodology of recommendation for the application rate of chemical fertilizer nitrogen to crops. Plant Nutrition and Fertilizer Science,2006,12:1-4
Zarco-Tejada, P. J., Miller, J., Morales, A., et al. Hyperspectral indices and model simulation for chlorophyll estimation in open-canopy tree crops. Remote Sensing of Environment,2004,90:463-476
Ziadi, N., Brassard, M., Belanger, G., et al. Critical nitrogen curve and nitrogen nutrition index for corn in eastern Canada. Agronomy Journal,2008a,100:271-276
Ziadi, N., Brassard, M., Belanger, G., et al. Chlorophyll measurements and nitrogen nutrition index for the evaluation of corn nitrogen status. Agronomy Journal,2008b,100:1264-1273
Ziadi, N., Belanger, G., Claessens, A., et al. Determination of a critical nitrogen dilution curve for spring wheat. Agronomy Journal,2010a,102:241-250
Ziadi, N., Belanger, G., Claessens, A., et al. Plant-based diagnostic tools for evaluating wheat nitrogen status. Crop Science,2010b,50:2580-2590
Zillmann, E., Graeff, S.,Link, J., et al. Assessment of cereal nitrogen requirements derived by optical on-the-go sensors on heterogeneous soils. Agronomy Journal,2006,98:682-690
陈新平,李志宏,王兴仁,等.土壤,植株快速测试推荐施肥技术体系的建立与应用.土壤肥料,1999,2：6-10
陈杨,樊明寿,李斐,等.氮素营养诊断技术的发展及其在马铃薯生产中的应用.中国农学通报,2009,25：66-71
冯伟.基于高光谱遥感的小麦氮素营养及生长指标监测研究：[博士学位论文].南京：南京农业大学,2007
高晓薇Crop Circle传感器在冬小麦氮营养实时诊断与调控中的应用研究：[硕士学位论文].北京：中国农业大学,2011
郭建华,王秀,孟志军,等.主动遥感光谱仪Greenseeker与SPAD对玉米氮素营养诊断的研究.植物营养与肥料学报,2008,14：43-47
郭建华,赵春江,王秀,等.作物氮素营养诊断方法的研究现状及进展.中国土壤与肥料,2008：10-14
胡昊,自由路,杨俐苹,等.基于SPAD-502与GreenSeeker的冬小麦氮营养诊断研究.中国生态农业学报,2010,18：748-752
贾良良,李斐,陈新平,等.应用IKONOS卫星影像监测冬小麦氮营养状况.中国土壤与肥料,2013,6：68-71
焦雯珺,闵庆文,林煜,等.植物氮素营养诊断的进展与展望.中国农学通报,2007,22：351-355
李俊华,董志新,朱继正.氮素营养诊断方法的应用现状及展望.石河子大学学报(自然科学版),2003,7：80-83
李志宏,刘宏斌,张云贵.叶绿素仪在氮肥推荐中的应用研究进展.植物营养与肥料学报,2006,12：125-132
梁效贵,张经廷,周丽丽,等.华北地区夏玉米临界氮稀释曲线和氮营养指数研究.作物学报,2013,39：292-299
刘芷宇.植物营养诊断的回顾与展望.土壤,1982,24：173-175
陆景陵.植物营养学.北京：中国农业大学出版社,2003
卢艳丽,李少昆,王纪华,等.冬小麦不同株型品种光谱响应及株型识别方法研究.作物学报,2006,31：1333-1339
梅安新,彭望碌,秦其明,等.遥感导论.北京：高等教育出版社,2001
浦瑞良,宫鹏.高光谱遥感及其应用.北京：高等教育出版社,2000
田国良,郭世忠.水稻光谱反射特性.自然资源,1982,2：73-81
武维华.植物生理学.北京：科学出版社,2004
薛晓萍,周治国,张丽娟,等.棉花花后临界氮浓度稀释模型的建立及在施氮量调控中的应用.生态学报,2006,26：1781-1791
闫湘,金继运,何萍,等.提高肥料利用率技术研究进展.中国农业科学,2008,41：450-459
杨长明,杨林章,韦朝领,等.不同品种水稻群体冠层光谱特征比较研究.应用生态学报,2002,13：689-692
岳善超.小麦玉米高产体系的氮肥优化管理：[博士学位论文].北京：中国农业大学,2013
张福锁,王激清,张卫峰,等.中国主要粮食作物肥料利用率现状与提高途径.土壤学报,2008,45：915-924
张俊华,张佳宝,贾科利.不同品种夏玉米光谱特征差异及其与农学参量相关性研究.土壤通报,2010：287-293
张兰民.从龙粳21的选育看黑龙江省超级稻育种.黑龙江农业科学.2011：9-12
Ahmad, I. S., Reid, J. F., Noguchi, N., et al. Nitrogen sensing for precision agriculture using chlorophyll maps. ASAE paper No.99-3035, American Society of Agricultural Engineers, St. Joseph, MI, USA, 1999
Bajwa, S., Mishra, A. and Norman, R. Canopy reflectance response to plant nitrogen accumulation in rice. Precision Agriculture,2010,11:488-506
Balasubramanian, V., Morales, A., Cruz, R., et al. On-farm adaptation of knowledge-intensive nitrogen management technologies for rice systems. Nutrient Cycling in Agroecosystems,1998,53:59-69
Barker, D. W. and Sawyer, J. E. Using active canopy sensors to quantify corn nitrogen stress and nitrogen application rate. Agronomy Journal,2010,102:964-971
Barnes, E., Clarke, T., Richards, S., et al. Coincident detection of crop water stress, nitrogen status and canopy density using ground based multispectral data. In:P. C. Robert, et al., editors, Proceding the 5th International Conference on Precision Agriculture:2000
Bausch, W. and Khosla, R. QuickBird satellite versus ground-based multi-spectral data for estimating nitrogen status of irrigated maize. Precision Agriculture,2010,11:274-290
Berntsen, J., Thomsen, A., Schelde, K., et al. Algorithms for sensor-based redistribution of nitrogen fertilizer in winter wheat. Precision Agriculture,2006,7:65-83
Bijay-Singh, Sharma, R. K., Jaspreet-Kaur, et al. Assessment of the nitrogen management strategy using an optical sensor for irrigated wheat. Agronomy for Sustainable Development,2011,31:589-603
Blackburn, G. A. Hyperspectral remote sensing of plant pigments. Journal of Experimental Botany,2007,58: 855-867
Blackmer, T., Schepers, J. and Vigil, M. Chlorophyll meter readings in corn as affected by plant spacing. Communications in Soil Science & Plant Analysis,1993,24:2507-2516
Blackmer, T. and Schepers, J. Techniques for monitoring crop nitrogen status in corn. Communications in Soil Science & Plant Analysis,1994,25:1791-1800
Blackmer, T. and Schepers, J. Use of a chlorophyll meter to monitor nitrogen status and schedule fertigation for corn. Journal of Production Agriculture,1995,8:56-60
Blackmer, T. M., Schepers, J. S. and Varvel, G. E. Light reflectance compared with other nitrogen stress measurements in corn leaves. Agronomy Jouraary,1994,86:934-938
Boggs, J. L., Tsegaye, T., Coleman, T. L., et al. Relationship between hyperspectral reflectance, soil nitrate-nitrogen, cotton leaf chlorophyll, and cotton yield:A step toward precision agriculture. Journal of Sustainable Agriculture,2003,22:5-16
Broge, N. H. and Leblanc, E. Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density. Remote Sensing of Environment,2000,76:156-172
Broge, N. H. and Mortensen, J. V. Deriving green crop area index and canopy chlorophyll density of winter wheat from spectral reflectance data. Remote Sensing of Environment,2002,81:45-57
Bronson, K. F., Chua, T. T., Booker, J., et al. In-season nitrogen status sensing in irrigated cotton. Soil Science Society of America Journal,2003,67:1439-1448
Bronson, K. F., Booker, J., Keeling, J. W., et al. Cotton canopy reflectance at landscape scale as affected by nitrogen fertilization. Agronomy Journal,2005,97:654-660
Bullock, D. and Anderson, D. Evaluation of the Minolta SPAD-502 chlorophyll meter for nitrogen management in corn. Journal of Plant Nutrition,1998,21:741-755
Buschmann, C. and Nagel, E. In vivo spectroscopy and internal optics of leaves as basis for remote sensing of vegetation. International Journal of Remote Sensing,1993,14:711-722
Cabrera, M. and Kissel, D. E. Evaluation of a method to predict nitrogen mineralized from soil organic matter under field conditions. Soil Science Society of America Journal,1988,52:1027-1031
Canfield, D. E., Glazer, A. N. and Falkowski, P. G. The evolution and future of Earth's nitrogen cycle. Science,2010,330:192-196
Cao, Q., Cui, Z., Chen, X., et al. Quantifying spatial variability of indigenous nitrogen supply for precision nitrogen management in small scale farming. Precision Agriculture,2012,13:45-61
Cartelat, A., Cerovic, Z., Goulas, Y., et al. Optically assessed contents of leaf polyphenolics and chlorophyll as indicators of nitrogen deficiency in wheat (Triticum aestivum L.). Field Crops Research,2005,91: 35-49
Cassman, K. G. Ecological intensification of cereal production systems:yield potential, soil quality, and precision agriculture. Proceedings of the National Academy of Sciences of the United States of America, 1999,96:5952-5959
Cassman, K. G., Dobermann, A. and Walters, D. T. Agroecosystems, nitrogen-use efficiency, and nitrogen management. AMBIO:A Journal of the Human Environment,2002,31:132-140
Cassman, K. G., Dobermann, A., Walters, D. T., et al. Meeting cereal demand while protecting natural resources and improving environmental quality. Annual Review of Environment and Resources,2003, 28:315-358
Cerovic, Z. G., Masdoumier, G., Ghozlen, N. B., et al. A new optical leaf-clip meter for simultaneous non-destructive assessment of leaf chlorophyll and epidermal flavonoids. Physiologia Plantarum,2012,146: 251-260
Cerrato, M. and Blackmer, A. Comparison of models for describing; corn yield response to nitrogen fertilizer. Agronomy Journal,1990,82:138-143
Chappelle, E. W., Kim, M. S. and McMurtrey III, J. E. Ratio analysis of reflectance spectra (RARS):an algorithm for the remote estimation of the concentrations of chlorophyll a, chlorophyll b, and carotenoids in soybean leaves. Remote Sensing of Environment,1992,39:239-247
Chen, J. M. Evaluation of vegetation indices and a modified simple ratio for boreal applications. Canadian Journal of Remote Sensing,1996,22:229-242
Chen, P., Wang, J., Huang, W., et al. Critical Nitrogen Curve and Remote Detection of Nitrogen Nutrition Index for Corn in the Northwestern Plain of Shandong Province, China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2013,6:682-689
Chen, X., Zhang, F., Romheld, V., et al. Synchronizing N Supply from Soil and Fertilizer and N Demand of Winter Wheat by an Improved Nmin Method. Nutrient Cycling in Agroecosystems,2006,74:91-98
Chen, X., Cui, Z., Vitousek, P. M., et al. From the Cover:Integrated soil-crop system management for food security. Proceedings of the National Academy of Sciences,2011,108:6399-6404
Cho, M. A. and Skidmore, A. K. Anew technique for extracting the red edge position from hyperspectral data: The linear extrapolation method. Remote Sensing of Environment,2006,101:181-193
Conant, R. T., Berdanier, A. B. and Grace, P. R. Patterns and trends in nitrogen use and nitrogen recovery efficiency in world agriculture. Global Biogeochemical Cycles,2013,27:558-566
Cui, Z., Chen, X., Miao, Y., et al. On-farm evaluation of the improved soil N-based nitrogen management for summer maize in North China Plain. Agronomy Journal,2008a,100:517-525
Cui, Z., Chen, X., Miao, Y, et al. On-farm evaluation of winter wheat yield response to residual soil nitrate-N in North China Plain. Agronomy Journal,2008b,100:1527-1534
Cui, Z., Zhang, F., Chen, X., et al. On-farm evaluation of an in-season nitrogen management strategy based on soil Nmin test. Field Crops Research,2008c,105:48-55
Cui, Z., Zhang, F., Miao, Y, et al. Soil nitrate-N levels required for high yield maize production in the North China Plain. Nutrient Cycling in Agroecosystems,2008d,82:187-196
Cui, Z., Zhang, F., Chen, X., et al. In-season nitrogen management strategy for winter wheat:Maximizing yields, minimizing environmental impact in an over-fertilization context. Field Crops Research,2010, 116:140-146
Cui, Z., Yue, S., Wang, G., et al. Closing the yield gap could reduce projected greenhouse gas emissions:a case study of maize production in China. Global Change Biology,2013a,19:2467-2477
Cui, Z., Yue, S., Wang, G., et al. In-season root-zone N management for mitigating greenhouse gas emission and reactive N losses in intensive wheat production. Environmental Science & Technology,2013b,47: 6015-6022
Curran, P. J. Remote sensing of foliar chemistry. Remote Sensing of Environment,1989,30:271-278
Datt, B. A New Reflectance index for remote sensing of chlorophyll content in higher plants:tests using Eucalyptus leaves. Journal of Plant Physiology,1999,154:30-36
Daughtry, C., Walthall, C., Kim, M., et al. Estimating corn leaf chlorophyll concentration from leaf and canopy reflectance. Remote Sensing of Environment,2000,74:229-239
Debaeke, P., Rouet, P. and Justes, E. Relationship between the normalized SPAD index and the nitrogen nutrition index:application to durum Wheat. Journal of Plant Nutrition,2006,29:75-92
Dellinger, A. E., Schmidt, J. P. and Beegle, D. B. Developing nitrogen fertilizer recommendations for corn using an active sensor. Agronomy Journal,2008,100:1546-1552
Diacono, M., Rubino, P. and Montemurro, F. Precision nitrogen management of wheat. A review. Agronomy for Sustainable Development,2013,33:219-241
Diaz, R. J. and Rosenberg, R. Spreading dead zones and consequences for marine ecosystems. Science,2008, 321:926-929
Dobermann, A., Witt, C., Dawe, D., et al. Site-specific nutrient management for intensive rice cropping systems in Asia. Field Crops Research,2002,74:37-66
Dobermann, A. and Cassman, K. G. Cereal area and nitrogen use efficiency are drivers of future nitrogen fertilizer consumption. Science in China Series C:Life Sciences,2005,48:745-758
Duvick, D. and Cassman, K. G. Post-green revolution trends in yield potential of temperate maize in the North-Central United States. Crop Science,1999,39:1622-1630
Eitel, J. U. H., Long, D. S., Gessler, P., et al. Using in-situ measurements to evaluate the new RapidEye■ satellite series for prediction of wheat nitrogen status. International Journal of Remote Sensing,2007,28: 4183-4190
Eitel, J. U. H., Keefe, R. F., Long, D. S., et al. Active ground optical remote sensing for improved monitoring of seedling stress in nurseries. Sensors,2010,10:2843-2850
Eitel, J. U. H., Vierling, L. A., Long, D. S., et al. Early season remote sensing of wheat nitrogen status using a green scanning laser. Agricultural and Forest Meteorology,2011,151:1338-1345
Elliott, D., Reuter, D., Growden, B., et al. Nitrogen:improved strategies for diagnosing and correcting nitrogen deficiency in spring wheat. Journal of Plant Nutrition,1987,10:1761-1770
Elwadie, M. E., Pierce, F. J. and Qi, J. Remote sensing of canopy dynamics and biophysical variables estimation of corn in Michigan. Agronomy Journal,2005,97:99-105
Engel, R. and Zubriski, J. Nitrogen concentrations in spring wheat at several growth stages. Communications in Soil Science & Plant Analysis,1982,13:531-544
Erdle, K., Mistele, B. and Schmidhalter, U. Comparison of active and passive spectral sensors in discriminating biomass parameters and nitrogen status in wheat cultivars. Field Crops Research,2011, 124:74-84
Erisman, J. W., Sutton, M. A., Galloway, J., et al. How a century of ammonia synthesis changed the world. Nature Geoscience,2008,1:636-639
Erisman, J. W, Galloway, J. N., Seitzinger, S., et al. Consequences of human modification of the global nitrogen cycle. Philosophical Transactions of the Royal Society B:Biological Sciences,2013,368: 20130116
Evenson, R. E. Assessing the Impact of the Green Revolution,1960 to 2000. Science,2003,300:758-762
FAOSTAT. FAO Statistical databases.2013:Available at http://www.fao.org
Feret, J.-B., Francois, C., Asner, G. P., et al. PROSPECT-4 and 5:Advances in the leaf optical properties model separating photosynthetic pigments. Remote Sensing of Environment,2008,112:3030-3043
Fitzgerald, G., Rodriguez, D. and O'Leary, G. Measuring and predicting canopy nitrogen nutrition in wheat using a spectral index—The canopy chlorophyll content index (CCCI). Field Crops Research,2010,116: 318-324
Flowers, M., Weisz, R. and Heiniger, R. Quantitative approaches for using color infrared photography for assessing in-season nitrogen status in winter wheat. Agronomy Journal,2003,95:1189-1200
Flynn, E. S., Dougherty, C. T. and Wendroth, O. Assessment of pasture biomass with the normalized difference vegetation index from active ground-based sensors. Agronomy Journal,2008,100:114-121
Forster, P., Ramaswamy, V., Artaxo, P., et al. Changes in atmospheric constituents and in radiative forcing. In: S. Solomon, et al., editors, Climate change 2007:The Physical Science Basis Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridege, United Kingdom and New York, NY, USA:Cambridge Universtiy Press,2007
Fowler, D., Coyle, M., Skiba, U., et al. The global nitrogen cycle in the twenty-first century. Philosophical Transactions of the Royal Society B:Biological Sciences,2013,368:20130164
Galloway, J. N., Townsend, A. R., Erisman, J. W., et al. Transformation of the nitrogen cycle:recent trends, questions, and potential solutions. Science,2008,320:889-892
Gao, B., Ju, X., Zhang, Q., et al. New estimates of direct N2O emissions from Chinese croplands from 1980 to 2007 using localized emission factors. Biogeosciences,2011,8:3011-3024
Garnett, T., Appleby, M., Balmford, A., et al. Sustainable intensification in agriculture:premises and policies. Science,2013,341:33-34
Gastal, F. and Lemaire, G. N uptake and distribution in crops:an agronomical and ecophysiological perspective. Journal of Experimental Botany,2002,53:789-799
Geraldson, C. and Tyler, K. Plant analysis as an aid in fertilizing vegetable crops. Soil Testing and Plant Analysis. SSSABook Series,1990,3:549-562
Gitelson, A. A., Kaufman, Y. J. and Merzlyak, M. N. Use of a green channel in remote sensing of global vegetation from EOS-MODIS. Remote Sensing of Environment,1996,58:289-298
Gitelson, A. A., Kaufman, Y. J., Stark, R., et al. Novel algorithms for remote estimation of vegetation fraction. Remote Sensing of Environment,2002,80:76-87
Gitelson, A. A. Remote estimation of leaf area index and green leaf biomass in maize canopies. Geophysical Research Letters,2003,30 (5):1248, http://dx.doi.org/1210.1029/2002GL016450
Gitelson, A. A., Gritz (?), Y. and Merzlyak, M. N. Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves. Journal of Plant Physiology,2003,160:271-282
Gitelson, A. A. Wide dynamic range vegetation index for remote quantification of biophysical characteristics of vegetation. Journal of Plant Physiology,2004,161:165-173
Gitelson, A. A., Vina, A. s., Ciganda, V. n., et al. Remote estimation of canopy chlorophyll content in crops. Geophysical Research Letters,2005,32:L08403, http://dx.doi.org/08410.01029/02005GL022688
Gitelson, A. A., Keydan, G. P. and Merzlyak, M. N. Three-band model for noninvasive estimation of chlorophyll, carotenoids, and anthocyanin contents in higher plant leaves. Geophysical Research Letters, 2006,33:111402
Gitelson, A. A. Remote estimation of crop fractional vegetation cover:the use of noise equivalent as an indicator of performance of vegetation indices. International Journal of Remote Sensing,2013:1-13
Gnyp, M. L., Miao, Y., Yuan, F., et al. Hyperspectral canopy sensing of paddy rice aboveground biomass at different growth stages. Field Crops Research,2014,155:42-55
Godfray, H. C. J., Beddington, J. R., Crute, I. R., et al. Food Security:The Challenge of Feeding 9 Billion People. Science,2010,327:812-818
Godoy, L. d., Boas, R. V. and Grassi Filho, H. Nitrogen fertilizing in corn based in chlorophyll meter reading and sufficiency index in nitrogen. Acta Scientiarum-Agronomy,2003,25:373-380
Goulas, Y., Cerovic, Z. G., Cartelat, A., et al. Dualex:a new instrument for field measurements of epidermal ultraviolet absorbance by chlorophyll fluorescence. Applied Optics,2004,43:4488-4496
Greenwood, D., Neeteson, J. and Draycott, A. Quantitative relationships for the dependence of growth rate of arable crops on their nitrogen content, dry weight and aerial environment. Plant and Soil,1986,91: 281-301
Greenwood, D., Gastal, F., Lemaire, G., et al. Growth rate and %N of field grown crops:theory and experiments. Annals of Botany,1991,67:181-190
Gu, B., Leach, A. M., Ma, L., et al. Nitrogen footprint in China:food, energy, and nonfood goods. Environmental Science & Technology,2013,47:9217-9224
Guo, J. H., Liu, X. J., Zhang, Y., et al. Significant acidification in major Chinese croplands. Science,2010, 327:1008-1010
Haboudane, D., Miller, J. R., Tremblay, N., et al. Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture. Remote Sensing of Environment,2002, 81:416-426
Haboudane, D. Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies:Modeling and validation in the context of precision agriculture. Remote Sensing of Environment,2004,90:337-352
Haboudane, D., Miller, J. R., Pattey, E., et al. Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies:Modeling and validation in the context of precision agriculture. Remote Sensing of Environment,2004,90:337-352
Hatfield, J. L. and Prueger, J. H. Value of using different vegetative indices to quantify agricultural crop characteristics at different growth stages under varying management practices. Remote Sensing,2010,2: 562-578
Hawkins, J. A., Sawyer, J. E., Barker, D. W., et al. Using relative chlorophyll meter values to determine nitrogen application rates for corn. Agronomy Journal,2007,99:1034-1040
Holland, K. and Schepers, J. Active-crop sensor calibration using the virtual reference concept. In:J. V. Stafford (Ed.), Precision agriculture 2011, Proceedings of the 8th European Conference on Precision Agriculture. Prague:Czech Republic, Czech Centre for Science and Society,2011,469-479
Holland, K. H. and Schepers, J. S. Derivation of a variable rate nitrogen application model for in-season fertilization of corn. Agronomy Journal,2010,102:1415-1424
Horwitz, W. Official methods of analysis. Washington, DC:Association of Official Agricultural Chemists, 1970
Houles, V., Guerif, M. and Mary, B. Elaboration of a nitrogen nutrition indicator for winter wheat based on leaf area index and chlorophyll content for making nitrogen recommendations. European Journal of Agronomy,2007,27:1-11
Huang, Y. and Tang, Y. An estimate of greenhouse gas (N2O and CO2) mitigation potential under various scenarios of nitrogen use efficiency in Chinese croplands. Global Change Biology,2010,16:2958-2970
Huete, A. R. A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment,1988,25:295-309
Hussain, F., Bronson, K. and Peng, S. Use of chlorophyll meter sufficiency indices for nitrogen management of irrigated rice in Asia. Agronomy Journal,2000,92:875-879
IFA. International Fertilizer Association Database.2010:Available at http://www.ifa.com/
IPCC. Agriculture, Forestry and Other Land Uses (AFOLU). In:S. Eggleston, et al., editors,2006 IPCC/Guidelines for National Greenhouse Gas Inventories. Kanagawa, Japan:Institute for Global Environmental Strategies,2006,54
Jacquemoud, S. and Baret, F. PROSPECT:A model of leaf optical properties spectra. Remote Sensing of Environment,1990,34:75-91
Jasper, J., Reusch, S. and Link, A. Active sensing of the N status of wheat using optimized wave-length combination:Impact of seed rate, variety and growth stage. In:E. J. v. Henten, et al., editors,9th Precision agriculture:Wageningen Academic Publishers,2009,23-30
Jeuffroy, M. H. and Recous, S. Azodyn:a simple model simulating the date of nitrogen deficiency for decision support in wheat fertilization. European Journal of Agronomy,1999,10:129-144
Johnson, G. and Raun, W. Nitrogen response index as a guide to fertilizer management. Journal of Plant Nutrition,2003,26:249-262
Ju, X. T., Xing, G. X., Chen, X. P., et al. From the Cover:Reducing environmental risk by improving N management in intensive Chinese agricultural systems. Proceedings of the National Academy of Sciences, USA,2009,106:3041-3046
Justes, E., Mary, B., Meynard, J. M., et al. Determination of a critical nitrogen dilution curve for winter wheat crops. Annals of Botany,1994,74:397-407
Justice, C. O., Vermote, E., Townshend, J. R. G., et al. The Moderate Resolution Imaging Spectroradiometer (MODIS):land remote sensing for global change research. Geoscience and Remote Sensing, IEEE Transactions on,1998,36:1228-1249
Kahrl, F., Li, Y, Su, Y, et al. Greenhouse gas emissions from nitrogen fertilizer use in China, environmental science & policy,2010,13:688-694
Kandil, F., Grace, M., Seigler, D., et al. Polyphenolics in Rhizophora mangle L. leaves and their changes during leaf development and senescence. Trees,2004,18:518-528
Kitchen, N. R., Sudduth, K. A., Drummond, S. T., et al. Ground-based canopy reflectance sensing for variable-rate nitrogen corn fertilization. Agronomy Journal,2010,102:71-84
Knipling, E. B. Physical and physiological basis for the reflectance of visible and near-infrared radiation from vegetation. Remote Sensing of Environment,1970,1:155-159
Ladha, J. K., Pathak, H., J Krupnik, T., et al. Efficiency of fertilizer nitrogen in cereal production:retrospects and prospects. Advances in Agronomy,2005,87:85-156
Lamb, D., Steyn-Ross, M., Schaare, P., et al. Estimating leaf nitrogen concentration in ryegrass (Lolium spp.) pasture using the chlorophyll red-edge:theoretical modelling and experimental observations. International Journal of Remote Sensing,2002,23:3619-3648
Le, C., Zha, Y., Li, Y., et al. Eutrophication of lake waters in China:cost, causes, and control. Environmental Management,2010,45:662-668
Le Maire, G., Francois, C. and Dufrene, E. Towards universal broad leaf chlorophyll indices using PROSPECT simulated database and hyperspectral reflectance measurements. Remote Sensing of Environment,2004,89:1-28
Leight, R. and Johnson, A. Nitrogen concentration in field grown spring barely:an experiment of the usefulness of expecting concentration on the basis of tissue water. Journal of Agricultural Science,1985, 105:397-406
Lemaire, G., Khaity, M., Onillon, B., et al. Dynamics of accumulation and partitioning of N in leaves, stems and roots of lucerne (Medicago sativa L.) in a dense canopy. Annals of Botany,1992,70:429-435
Lemaire, G. and Gastal, F. N uptake and distribution in plant canopies. Diagnosis of the nitrogen status in crops. Springer,1997,3-43
Lemaire, G., Avice, J., Kim, T., et al. Developmental changes in shoot N dynamics of lucerne (Medicago sativa L.) in relation to leaf growth dynamics as a function of plant density and hierarchical position within the canopy. Journal of Experimental Botany,2005,56:935-943
Lemaire, G., Jeuffroy, M.-H. and Gastal, F. Diagnosis tool for plant and crop N status in vegetative stage. European Journal of Agronomy,2008a,28:614-624
Lemaire, G., van Oosterom, E., Jeuffroy, M.-H., et al. Crop species present different qualitative types of response to N deficiency during their vegetative growth. Field Crops Research,2008b,105:253-265
Li, F., Miao, Y., Zhang, F., et al. In-season optical sensing improves nitrogen-use efficiency for winter wheat. Soil Science Society of America Journal,2009,73:1566-1574
Li, F., Miao, Y, Chen, X., et al. Estimating winter wheat biomass and nitrogen status using an active crop sensor. Intelligent Automation and Soft Computing,2010a,16:1221-1230
Li, F., Miao, Y, Hennig, S. D., et al. Evaluating hyperspectral vegetation indices for estimating nitrogen concentration of winter wheat at different growth stages. Precision Agriculture,2010b,11:335-357
Li, F., Mistele, B., Hu, Y., et al. Remotely estimating aerial N status of phenologically differing winter wheat cultivars grown in contrasting climatic and geographic zones in China and Germany. Field Crops Research,2012,138:21-32
Li, X., Hu, C., Delgado, J. A., et al. Increased nitrogen use efficiencies as a key mitigation alternative to reduce nitrate leaching in north china plain. Agricultural Water Management,2007,89:137-147
Liu, X., Ju, X., Zhang, F., et al. Nitrogen recommendation for winter wheat using Nmin test and rapid plant tests in North China Plain. Communications in Soil Science and Plant Analysis,2003,34:2539-2551
Liu, X., Zhang, Y, Han, W., et al. Enhanced nitrogen deposition over China. Nature,2013,494:459-462
Long, D. S., Eitel, J. U. and Huggins, D. R. Assessing nitrogen status of dryland wheat using the canopy chlorophyll content index. Crop Management,2009,8, http://dx.doi.org/10.1094/CM-2009-1211-01-RS
Lorenzen, B. and Jensen, A. Reflectance of blue, green, red and near infrared radiation from wetland vegetation used in a model discriminating live and dead above ground biomass. New Phytologist,1988, 108:345-355
Lukina, E. V, Freeman, K. W., Wynn, K. J., et al. Nitrogen fertilization optimization algorithm based on in-season estimates of yield and plant nitrogen uptake. Journal of Plant Nutrition,2001,24:885-898
Martin, K., Raun, W. and Solie, J. By-plant prediction of corn grain yield using optical sensor readings and measured plant height. Journal of Plant Nutrition,2012,35:1429-1439
Meng, Q., Sun, Q., Chen, X., et al. Alternative cropping systems for sustainable water and nitrogen use in the North China Plain. Agriculture, Ecosystems & Environment,2012,146:93-102
Miao, Y, Mulla, D. J., Hernandez, J. A, et al. Potential impact of precision nitrogen management on corn yield, protein content, and test weight. Soil Science Society of America Journal,2007,71:1490-1499
Miao, Y, Mulla, D. J., Randall, G. W., et al. Combining chlorophyll meter readings and high spatial resolution remote sensing images for in-season site-specific nitrogen management of corn. Precision Agriculture,2009,10:45-62
Miao, Y, Stewart, B. A. and Zhang, F. Long-term experiments for sustainable nutrient management in China. Areview. Agronomy for Sustainable Development,2011,31:397-414
Mistele, B. and Schmidhalter, U. Estimating the nitrogen nutrition index using spectral canopy reflectance measurements. European Journal of Agronomy,2008,29:184-190
Mulla, D. J. Twenty five years of remote sensing in precision agriculture:Key advances and remaining knowledge gaps. Biosystems Engineering,2012,114:358-371
Mullen, R. W., Freeman, K. W., Raun, W. R., et al. Identifying an in-season response index and the potential to increase wheat yield with nitrogen. Agronomy Journal,2003,95:347-351
Olfs, H. W., Blankenau, K., Brentrup, F., et al. Soil-and plant-based nitrogen-fertilizer recommendations in arable farming. Journal of Plant Nutrition and Soil Science,2005,168:414-431
Patel, N., Singh, T., Sahai, B., et al. Spectral response of rice crop and its relation to yield and yield attributes. International Journal of Remote Sensing,1985,6:657-664
Peng, S., Garcia, F., Laza, R., et al. Increased N-use efficiency using a chlorophyll meter on high-yielding irrigated rice. Field Crops Research,1996,47:243-252
Peng, S., Buresh, R. J., Huang, J., et al. Strategies for overcoming low agronomic nitrogen use efficiency in irrigated rice systems in China. Field Crops Research,2006,96:37-47
Peng, S., Tang, Q. and Zou, Y. Current status and challenges of rice production in China. Plant Production Science,2009,12:3-8
Peng, S., Buresh, R. J., Huang, J., et al. Improving nitrogen fertilization in rice by sitespecific N management. A review. Agronomy for Sustainable Development,2010,30:649-656
Perry, E. M., Pierce, F. J., Davenport, J. R., et al. Comparing active optical and airborne measurements of grape canopies. International Symposium on Application of Precision Agriculture for Fruits and Vegetables,2009,824:75-83
Peterson, T. A. Using a chlorophyll meter to improve N management. Cooperative Extension, Institute of Agriculture and Natural Resources, University of Nebraska-Lincoln,1993
Piekielek, W. P., Fox, R. H., Toth, J. D., et al. Use of a chlorophyll meter at the early dent stage of corn to evaluate nitrogen sufficiency. Agronomy Journal,1995,87:403-408
Plenet, D. and Lemaire, G. Relationships between dynamics of nitrogen uptake and dry matter accumulation in maize crops. Determination of critical N concentration. Plant and Soil,2000,216:65-82
Prasad, M. and Spiers, T. Evaluation of a rapid method for plant sap nitrate analysis. Communications in Soil Science & Plant Analysis,1984,15:673-679
Prost, L. and Jeuffroy, M.-H. Replacing the nitrogen nutrition index by the chlorophyll meter to assess wheat N status. Agronomy for Sustainable Development,2007,27:321-330
Qi, J., Chehbouni, A, Huete, A., et al. A modified soil adjusted vegetation index. Remote Sensing of Environment,1994,48:119-126
Raun, W., Solie, J., Stone, M., et al. Automated calibration stamp technology for improved in-season nitrogen fertilization. Agronomy Journal,2005a,97:338-342
Raun, W., Solie, J., Taylor, R., et al. Ramp calibration strip technology for determining midseason nitrogen rates in corn and wheat. Agronomy Journal,2008,100:1088-1093
Raun, W. R. and Johnson, G. V. Improving nitrogen use efficiency for cereal production. Agronomy Journal, 1999,91:357-363
Raun, W. R., Solie, J. B., Johnson, G. V., et al. In-season prediction of potential grain yield in winter wheat using canopy reflectance. Agronomy Journal,2001,93:131-138
Raun, W. R., Solie, J. B., Johnson, G. V., et al. Improving nitrogen use efficiency in cereal grain production with optical sensing and variable rate application. Agronomy Journal,2002,94:815-820
Raun, W. R., Solie, J. B., Stone, M. L., et al. Optical sensor-based algorithm for crop nitrogen fertilization. Communications in Soil Science and Plant Analysis,2005b,36:2759-2781
Ravishankara, A., Daniel, J. S. and Portmann, R. W. Nitrous oxide (N2O):the dominant ozone-depleting substance emitted in the 21st century. Science,2009,326:123-125
Reay, D. S., Davidson, E. A., Smith, K. A., et al. Global agriculture and nitrous oxide emissions. Nature Climate Change,2012,2:410-416
Richardson, A. D., Duigan, S. P. and Berlyn, G. P. An evaluation of noninvasive methods to estimate foliar chlorophyll content. New Phytologist,2002,153:185-194
Robertson, G. P. and Vitousek, P. M. Nitrogen in agriculture:balancing the cost of an essential resource. Annual Review of Environment and Resources,2009,34:97-125
Roberts, D., Brorsen, B. W., Taylor, R., et al. Replicability of nitrogen recommendations from ramped calibration strips in winter wheat. Precision Agriculture,2011,12:653-665
Rockstrom, J., Steffen, W., Noone, K., et al. A safe operating space for humanity. Nature,2009,461:472-475
Rondeaux, G., Steven, M. and Baret, F. Optimization of soil-adjusted vegetation indices. Remote Sensing of Environment,1996,55:95-107
Roth, G., Fox, R. and Marshall, H. Plant tissue tests for predicting nitrogen fertilizer requirements of winter wheat. Agronomy Journal,1989,81:502-507
Roujean, J. L. and Breon, F. M. Estimating PAR absorbed by vegetation from bidirectional reflectance measurements. Remote Sensing of Environment,1995,51:375-384
Samborski, S. and Rozbicki, J. Use of nitrogen sufficiency index for calibration of a chlorophyll meter SPAD-502 readings in winter triticale. Book of proceedings. VII Congress of the European Society for Agronomy:2002,15-18
Samborski, S. M., Tremblay, N. and Fallon, E. Strategies to make use of plant sensors-based diagnostic information for nitrogen recommendations. Agronomy Journal,2009,101:800-816
Sawyer, J. E., Lundvall, J., Hawkins, J. S., et al. Sensing nitrogen stress in corn. Agriculture and Environment Extension Publications,2011
Scharf, P. C. and Lory, J. A Calibrating corn color from aerial photographs to predict sidedress nitrogen need. Agronomy Journal,2002,94:397-404
Scharf, P. C., Brouder, S. M. and Hoeft, R. G. Chlorophyll meter readings can predict nitrogen need and yield response of corn in the north-central USA. Agronomy Journal,2006,98:655-665
Schlemmer, M. R., Francis, D. D., Shanahan, J., et al. Remotely measuring chlorophyll content in corn leaves with differing nitrogen levels and relative water content. Agronomy Journal,2005,97:106-112
Schmidt, J., Beegle, D., Zhu, Q., et al. Improving in-season nitrogen recommendations for maize using an active sensor. Field Crops Research,2011,120:94-101
Schmidt, J. P., Dellinger, A. E. and Beegle, D. B. Nitrogen Recommendations for corn:an on-the-go sensor compared with current recommendation methods. Agronomy Journal,2009,101:916-924
Schroder, J., Neeteson, J., Oenema, O., et al. Does the crop or the soil indicate how to save nitrogen in maize production?:Reviewing the state of the art. Field Crops Research,2000,66:151-164
Seek, P. A., Diagne, A., Mohanty, S., et al. Crops that feed the world 7:Rice. Food Security,2012,4:7-24
Shapiro, C. A. Using a chlorophyll meter to manage nitrogen applications to corn with high nitrate irrigation water. Communications in Soil Science & Plant Analysis,1999,30:1037-1049
Shaver, T., Khosla, R. and Westfall, D. Evaluation of two crop canopy sensors for nitrogen recommendations in irrigated maize. Journal of Plant Nutrition,2014,37:406-419
Shaver, T. M., Khosla, R. and Westfall, D. G. Evaluation of two ground-based active crop canopy sensors in maize:growth stage, row spacing, and sensor movement speed. Soil Science Society of America Journal, 2010,74:2101-2108
Shaver, T. M., Khosla, R. and Westfall, D. G. Evaluation of two crop canopy sensors for nitrogen variability determination in irrigated maize. Precision Agriculture,2011,12:892-904
Sheehy, J., Dionora, M., Mitchell, P., et al. Critical nitrogen concentrations:implications for high-yielding rice (Oryza sativa L.) cultivars in the tropics. Field Crops Research,1998,59:31-41
Shen, J., Cui, Z., Miao, Y., et al. Transforming agriculture in China:From solely high yield to both high yield and high resource use efficiency. Global Food Security,2013,2:1-8
Shibayama, M. and Akiyama, T. Seasonal visible, near-infrared and mid-infrared spectra of rice canopies in relation to LAI and above-ground dry phytomass. Remote Sensing of Environment,1989,27:119-127
Shikada, M. and Miyakita, K. Effects of solar and view angles on reflectance for paddy field canopies. Geocarto International,1992,7:9-17
Shiratsuchi, L., Ferguson, R., Shanahan, J., et al. Water and nitrogen effects on active canopy sensor vegetation indices. Agronomy Journal,2011,103:1815-1826
Shou, L., Jia, L., Cui, Z., et al. Using high-resolution satellite imaging to evaluate nitrogen status of winter wheat. Journal of Plant Nutrition,2007,30:1669-1680
Snyder, C. S. and Fixen, P. E. Plant nutrient management and risks of nitrous oxide emission. Journal of Soil and Water Conservation,2012,67:137-144
Solan, F., Hodgen, P., Shanahan, J., et al. Time of day and maize leaf wetness effects on active sensor readings. Agronomy Abstracts,2004,4253
Solari, F., Shanahan, J., Ferguson, R., et al. Active sensor reflectance measurements of corn nitrogen status and yield potential. Agronomy Journal,2008,100:571-579
Solari, F., Shanahan, J. F., Ferguson, R. B., et al. An active sensor algorithm for corn nitrogen recommendations based on a chlorophyll meter algorithm. Agronomy Journal,2010,102:1090-1098
Soltanpour, P., Malakouti, M. and Ronaghi, A. Comparison of diagnosis and recommendation integrated system and nutrient sufficiency range for corn. Soil Science Society of America Journal,1995,59: 133-139
Sripada, R. P., Heiniger, R. W., White, J. G., et al. Aerial color infrared photography for determining late-season nitrogen requirements in corn. Agronomy Journal,2005,97:1443-1451
Sripada, R. P., Heiniger, R. W., White, J. G., et al. Aerial color infrared photography for determining early in-season nitrogen requirements in corn. Agronomy Journal,2006,98:968-977
Sripada, R. P., Schmidt, J. P., Dellinger, A. E., et al. Evaluating multiple indices from a canopy reflectance sensor to estimate corn N requirements. Agronomy Journal,2008,100:1553-1561
Stockle, C. and Debaeke, P. Modeling crop nitrogen requirements:a critical analysis. Developments in Crop Science,1997,25:217-225
Stokes, D., Sylvester-Bradley, R., Clare, R., et al. An integrated approach to nitrogen nutrition for wheat. HGCA Project Report No.159,1998
Stroppiana, D., Boschetti, M., Brivio, P. A., et al. Plant nitrogen concentration in paddy rice from field canopy hyperspectral radiometry. Field Crops Research,2009,111:119-129
Sutton, M. A., Oenema, O., Erisman, J. W., et al. Too much of a good thing. Nature,2011,472:159-161
Teal, R., Tubana, B., Girma, K., et al. In-season prediction of corn grain yield potential using normalized difference vegetation index. Agronomy Journal,2006,98:1488-1494
Tester, M. and Langridge, P. Breeding technologies to increase crop production in a changing world. Science, 2010,327:818-822
Thomas, J. and Gausman, H. Leaf reflectance vs. leaf chlorophyll and carotenoid concentrations for eight crops. Agronomy Journal,1977,69:799-802
Thomason, W. E., Phillips, S. B., Davis, P. H., et al. Variable nitrogen rate determination from plant spectral reflectance in soft red winter wheat. Precision Agriculture,2011,12:666-681
Tilman, D. Global environmental impacts of agricultural expansion:the need for sustainable and efficient practices. Proceedings of the National Academy of Sciences,1999,96:5995-6000
Tilman, D., Cassman, K. G., Matson, P. A., et al. Agricultural sustainability and intensive production practices. Nature,2002,418:671-677
Tilman, D., Balzer, C., Hill, J., et al. Global food demand and the sustainable intensification of agriculture. Proceedings of the National Academy of Sciences,2011,108:20260-20264
Tollenaar, M. and Lee, E. Yield potential, yield stability and stress tolerance in maize. Field Crops Research, 2002,75:161-169
Tremblay, N., Wang, Z. and Belec, C. Evaluation of the dualex for the assessment of corn nitrogen status. Journal of Plant Nutrition,2007,30:1355-1369
Tremblay, N., Wang, Z. and Belec, C. Performance of dualex in spring wheat for crop nitrogen status assessment, yield prediction and estimation of soil nitrate content. Journal of Plant Nutrition,2010,33: 57-70
Tremblay, N., Fallon, E. and Ziadi, N. Sensing of crop nitrogen status:Opportunities, tools, limitations, and supporting information requirements. HortTechnology,2011,21:274-281
Tremblay, N., Wang, Z. and Cerovic, Z. G. Sensing crop nitrogen status with fluorescence indicators. A review. Agronomy for Sustainable Development,2012,32:451-464
Tubafla, B., Harrell, D., Walker, T., et al. Relationships of spectral vegetation indices with rice biomass and grain yield at different sensor view angles. Agronomy Journal,2011,103:1405-1413
Tubana, B. S., Arnall, D. B., Walsh, O., et al. Adjusting midseason nitrogen rate using a sensor-based optimization algorithm to increase use efficiency in corn. Journal of Plant Nutrition,2008,31: 1393-1419
Tucker, C. J. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment,1979,8:127-150
Varvel, G. E., Schepers, J. S. and Francis, D. D. Ability for in-season correction of nitrogen deficiency in corn using chlorophyll meters. Soil Science Society of America Journal,1997,61:1233-1239
Varvel, G. E., Wilhelm, W. W., Shanahan, J. F., et al. An Algorithm for corn nitrogen recommendations using a chlorophyll meter based sufficiency index. Agronomy Journal,2007,99:701-706
Verhoef, W. Earth observation modeling based on layer scattering matrices. Remote Sensing of Environment, 1985,17:165-178
Vos, J. and Bom, M. Hand-held chlorophyll meter:a promising tool to assess the nitrogen status of potato foliage. Potato Research,1993,36:301-308
Wang, G., Dobermann, A., Witt, C., et al. Performance of site-specific nutrient management for irrigated rice in southeast China. Agronomy Journal,2001,93:869-878
Wang, W., Yao, X., Yao, X., et al. Estimating leaf nitrogen concentration with three-band vegetation indices in rice and wheat. Field Crops Research,2012,129:90-98
Wehrmann, J., Scharpf, H., Boehmer, M., et al. Determination of nitrogen fertilizer requirements by nitrate analysis of the soil and of the plant. In Boehmer M. (ed.), Plant Nutrition 9th International Colloquium on Plant Nutrition:1982,202-208
Welsh, J., Wood, G., Godwin, R., et al. Developing strategies for spatially variable nitrogen application in cereals, part II:wheat. Biosystems Engineering,2003,84:495-511
Wood, G. A., Welsh, J. P., Godwin, R. J., et al. Real-time measures of canopy size as a basis for spatially varying nitrogen applications to winter wheat sown at different seed rates. Biosystems Engineering, 2003,84:513-531
Wu, J., Wang, D. and Bauer, M. E. Assessing broadband vegetation indices and QuickBird data in estimating leaf area index of corn and potato canopies. Field Crops Research,2007,102:33-42
Xue, L. and Yang, L. Recommendations for nitrogen fertiliser topdressing rates in rice using canopy reflectance spectra. Biosystems Engineering,2008,100:524-534
Xue, L., Li, G., Qin, X., et al. Topdressing nitrogen recommendation for early rice with an active sensor in south China. Precision Agriculture,2013:1-16
Yang, H., Yang, J., Lv, Y., et al. SPAD values and nitrogen nutrition index for the evaluation of rice nitrogen status. Plant Production Science,2014,17:81-92
Yao, X., Ata-Ul-Karim, S. T., Zhu, Y, et al. Development of critical nitrogen dilution curve in rice based on leaf dry matter. European Journal of Agronomy,2014a,55:20-28
Yao, X., Zhao, B., Tian, Y. C., et al. Using leaf dry matter to quantify the critical nitrogen dilution curve for winter wheat cultivated in eastern China. Field Crops Research,2014b,159:33-42
Yao, Y., Miao, Y, Huang, S., et al. Active canopy sensor-based precision N management strategy for rice. Agronomy for Sustainable Development,2012,32:925-933
Yu, K., Li, F., Gnyp, M. L., et al. Remotely detecting canopy nitrogen concentration and uptake of paddy rice in the Northeast China Plain. ISPRS Journal of Photogrammetry and Remote Sensing,2013,78: 102-115
Yue, S., Sun, F., Meng, Q., et al. Validation of a critical nitrogen curve for summer maize in the North China Plain. Pedosphere,2014,24:76-83
Yue, S., Meng, Q., Zhao, R., et al. Critical nitrogen dilution curve for optimizing nitrogen management of winter wheat production in the North China Plain. Agronomy Journal,2012a,104:523-529
Yue, S., Meng, Q., Zhao, R., et al. Change in nitrogen requirement with increasing grain yield for winter wheat. Agronomy Journal,2012b,104:1687-1693
Yue, X., Hu, Y., Zhang, H., et al. Green window approach for improving nitrogen management by farmers in small-scale wheat fields. The Journal of Agricultural Science,2014:1-9
Zebarth, B., Younie, M., Paul, J., et al. Evaluation of leaf chlorophyll index for making fertilizer nitrogen recommendations for silage corn in a high fertility environment. Communications in Soil Science and Plant Analysis,2002,33:665-684
Zhang, F., Cui, Z., Chen, X., et al. Integrated nutrient management for food security and environmental quality in China. Advances in Agronomy,2012,116:1-40
Zhang, R, Chen, X. and Vitousek, P. Chinese agriculture:An experiment for the world. Nature,2013a,497: 33-35
Zhang, H., Smeal, D., Arnold, R., et al. Potato nitrogen management by monitoring petiole nitrate level. Journal of Plant Nutrition,1996,19:1405-1412
Zhang, Q. Inaugural Article:Strategies for developing Green Super Rice. Proceedings of the National Academy of Sciences, USA,2007,104:16402-16409
Zhang, W., Dou, Z., He, P., et al. New technologies reduce greenhouse gas emissions from nitrogenous fertilizer in China. Proceedings of the National Academy of Sciences,2013b,110:8375-8380
Zhao, G., Miao, Y., Wang, H., et al. A preliminary precision rice management system for increasing both grain yield and nitrogen use efficiency. Field Crops Research,2013,154:23-30
Zhao, R., Chen, X., Zhang, F., et al. Fertilization and nitrogen balance in a wheat-maize rotation system in North China. Agronomy Journal,2006,98:938-945
Zhen, R. and Leigh, R. Nitrate accumulation by wheat (Triticum aestivum) in relation to growth and tissue N concentrations. Plant Nutrition—Physiology and Applications. Springer,1990,17-20
Zhu, Z. and Chen, D. Nitrogen fertilizer use in China-Contributions to food production, impacts on the environment and best management strategies. Nutrient Cycling in Agroecosystems,2002,63:117-127
Zhu, Z. On the methodology of recommendation for the application rate of chemical fertilizer nitrogen to crops. Plant Nutrition and Fertilizer Science,2006,12:1-4
Zarco-Tejada, P. J., Miller, J., Morales, A., et al. Hyperspectral indices and model simulation for chlorophyll estimation in open-canopy tree crops. Remote Sensing of Environment,2004,90:463-476
Ziadi, N., Brassard, M., Belanger, G., et al. Critical nitrogen curve and nitrogen nutrition index for corn in eastern Canada. Agronomy Journal,2008a,100:271-276
Ziadi, N., Brassard, M., Belanger, G., et al. Chlorophyll measurements and nitrogen nutrition index for the evaluation of corn nitrogen status. Agronomy Journal,2008b,100:1264-1273
Ziadi, N., Belanger, G., Claessens, A., et al. Determination of a critical nitrogen dilution curve for spring wheat. Agronomy Journal,2010a,102:241-250
Ziadi, N., Belanger, G., Claessens, A., et al. Plant-based diagnostic tools for evaluating wheat nitrogen status. Crop Science,2010b,50:2580-2590
Zillmann, E., Graeff, S.,Link, J., et al. Assessment of cereal nitrogen requirements derived by optical on-the-go sensors on heterogeneous soils. Agronomy Journal,2006,98:682-690
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