Hostname: page-component-586b7cd67f-2brh9 Total loading time: 0 Render date: 2024-11-24T04:31:14.176Z Has data issue: false hasContentIssue false
  • English
  • Français

Evaluation of the CERES-Rice Model for Precision Nitrogen Management for Rice in Northeast China

Published online by Cambridge University Press:  01 June 2017

J. Zhang ,
Y. Miao  and
W.D. Batchelor
J. Zhang
Affiliation:
International Center for Agro-Informatics and Sustainable Development, College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China
Y. Miao*
Affiliation:
International Center for Agro-Informatics and Sustainable Development, College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China
W.D. Batchelor*
Affiliation:
Biosystems Engineering Department, Auburn University, Auburn, AL 36849. USA
*
†E-mail: [email protected] or [email protected]
†E-mail: [email protected] or [email protected]
Get access

Abstract

Over-application of nitrogen (N) in rice (Oryza sativa L.) production in China is common, leading to low N use efficiency (NUE) and high environmental risks. The objective of this work was to evaluate the ability of the CERES-Rice crop growth model to simulate N response in the cool climate of Northeast China, with the long term goal of using the model to develop optimum N management recommendations. Nitrogen experiments were conducted from 2011–2015 in Jiansanjiang, Heilongjiang Province in Northeast China. The CERES-Rice model was calibrated for 2014 and 2015 and evaluated for 2011 and 2013 experiments. Overall, the model gave good estimations of yield across N rates for the calibration years (R2=0.89) and evaluation years (R2=0.73). The calibrated model was then run using weather data from 2001–2015 for 20 different N rates to determine the N rate that maximized the long term marginal net return (MNR) for different N prices. The model results indicated that the optimum mean N rate was 120–130 kg N ha–1, but that the simulated optimum N rate varied each year, ranging from 100 to 200 kg N ha–1. Results of this study indicated that the CERES-Rice model was able to simulate cool season rice growth and provide estimates of optimum regional N rates that were consistent with field observations for the area.

Keywords

CERES-RicePrecision nitrogen managementCrop growth modelSustainable developmentNitrogen use efficiency
Type
Precision Nitrogen
Information
Advances in Animal Biosciences , Volume 8 , Special Issue 2: Papers presented at the 11th European Conference on Precision Agriculture (ECPA 2017), John McIntyre Centre, Edinburgh, UK, July 16–20 2017 , July 2017 , pp. 328 - 332
Copyright
© The Animal Consortium 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Ata-Ul-Karim, ST, Liu, X, Lu, Z, Yuan, Z, Zhu, Y and Cao, W 2016. In-season estimation of rice grain yield using critical nitrogen dilution curve. Field Crops Research 195, 1–8.Google Scholar
Ahmad, S, Ahmad, A, Tojo Soler, CM, Ali, H, Zia-Ul-Haq, M, Anothai, J, et al. 2012. Application of the CSM-CERES-Rice model for evaluation of plant density and nitrogen management of fine transplanted rice for an irrigated semiarid environment. Precision Agriculture 13, 200–218.Google Scholar
Batchelor, WD, Basso, B and Paz, JO 2002. Examples of strategies to analyze spatial and temporal yield variability using crop models. European Journal of Agronomy 18 (1-2), 141–158.CrossRefGoogle Scholar
Batchelor, WD, Paz, JO and Jones, JW 2003. Estimating break-even cost to move from single to multiple soybean variety management within a field. Proceedings of the 4th European Conference on Precision Agriculture, pp 69–75, edited by J Stafford and A Werner. Wageningen: Academic publishers.Google Scholar
Bei, JH, Wang, KR, Chu, ZD, Chen, B and Li, SK 2005. Comparative study on the measure methods of the leaf area. Journal of Shihezi University (Natural Science). 23, 216–218.Google Scholar
Cao, Q, Miao, Y, Wang, H, Huang, S, Cheng, S, Khosla, R and Jiang, R 2013. Non-destructive estimation of rice plant nitrogen status with Crop Circle multispectral active canopy sensor. Field Crops Research 154, 133–144.Google Scholar
Cheyglinted, S, Ranamukhaarachchi, SL and Singh, G 2001. Assessment of the CERES-Rice model for rice production in the central plain of Thailand. Journal of Agricultural Science. 137, 289–298.Google Scholar
Diacono, M, Rubino, P and Montemurro, F 2013. Precision nitrogen management of wheat. A review. Agronomy for Sustainable Development 74, 219–241.CrossRefGoogle Scholar
Hoogenboom, G, Jones, JW, Porter, CH, Wilkens, PW, Boote, KJ, Hunt, LA and Tsuji, GY 2010. Decision Support System for Agrotechnology Transfer Version 4.5. Volume 1, Overview. University of Hawaii, Honolulu, HI USA.Google Scholar
Link, EJ, Graeff, SS, Batchelor, WD and Claupein, W 2006. Evaluating the economic and environmental impact of a German compensation payment policy under uniform and variable-rate nitrogen management strategies using a crop model. Agricultural Systems 91, 135–153.Google Scholar
Link, EJ, Graeff, S and Batchelor, WD 2008. Evaluation of current and model-based site-specific nitrogen applications on wheat (Triticum aestivum L.) yield and environmental quality. Precision Agriculture, 251–267.Google Scholar
Miao, Y, Mulla, DJ, Batchelor, WD, Paz, JO and Robert, PC 2006. Evaluating management zone optimal N rates with a crop growth model. Agronomy Journal 98 (3), 545–553.Google Scholar
Miao, Y, Mulla, DJ, Hernandez, JA, Wiebers, M and Robert, PC 2007. Potential impact of precision nitrogen management on corn yield, protein content, and test weight. Soil Science Society of America Journal 71, 1490–1499.Google Scholar
Mulla, DJ 2013. Twenty five years of remote sensing in precision agriculture, key advances and remaining knowledge gaps. Biosystems Engineering 114, 358–371.Google Scholar
Pan, GX, Li, LQ, Wu, LS and Zhang, XH 2003. Storage and sequestration potential of topsoil organic carbon in China’s paddy soils. Global Change Biology 10, 79–92.CrossRefGoogle Scholar
Paz, JO, Batchelor, WD, Colvin, TS, Logsdon, SD, Kaspar, TC and Karlen, DL 1998. Calibration of a crop growth model to predict spatial yield variability. Transactions of the ASAE 41 (5), 1527–1534.Google Scholar
Paz, JO, Batchelor, WD, Colvin, TS, Logsdon, SD, Kaspar, TC, Karlen, DL, et al. 1999. Model-based techniques to determine variable rate nitrogen for corn. Agricultural Systems 60 (1999), 69–75.Google Scholar
Paz, JO, Batchelor, WD and Jones, JW 2003. Estimating potential economic return for variable rate soybean variety management. Transactions of the ASAE 46 (4), 1225–1234.Google Scholar
Peng, S, Buresh, RJ, Huang, J, Zhong, X, Zou, Y, Yang, J et al 2010. Improving nitrogen fertilization in rice by site-specific N management—a review. Agronomy for Sustainable Development 30, 649–656.Google Scholar
Seck, PA, Diagne, A, Mohanty, S and Wopereis, MCS 2012. Crops that feed the world 7, rice. Food Security 4, 7–24.Google Scholar
Thorp, KR, Batchelor, WD, Paz, JO, Steward, BL and Caragea, PC 2006. Methodology to link production and environmental risks of precision nitrogen management strategies in corn. Agricultural Systems 89 (2-3), 272–298.Google Scholar
Vilayvong, S, Banterng, P, Patanothai, A and Pannangpetch, K 2012. Evaluation of CSM-CERES-Rice in simulating the response of lowland rice cultivars to nitrogen application. Australian Journal of Crop Science 6, 1534–1541.Google Scholar
Yao, F, Xu, Y, Feng, Q, Lin, E and Yan, X 2005. Simulation and validation of CERES-rice model in main rice ecological zones in China. Acta Agronomica Sinica 31, 545–550.Google Scholar
Yan, M, Deng, W and Chen, P 2002. Climate change in the Sanjiang Plain disturbed by large-scale reclamation. Journal of Geographic Science 12, 405–412.Google Scholar
Yadav, R, Dwivedi, B, Prasad, K, Tomar, O, Shurpali, N and Pandey, P 2000. Yield trends, and changes in soil organic-C and available NPK in a long-term rice–wheat system under integrated use of manures and fertilizers. Field Crops Research 68, 219–246.Google Scholar
Zhang, FS, Chen, XP and Chen, Q 2009. Guidelines for fertilization in Northeast China. Guide to fertilization for major crops in China. China Agricultural University Press, Beijing, China. pp 48–53.Google Scholar