Browse > Article

Estimating Grain Weight and Grain Nitrogen Content with Temperature, Solar Radiation and Growth Traits During Grain-Filling Period in Rice  

Lee, Chung-Kuen (National Institute of Crop Science, RDA)
Kim, Jun-Hwan (National Institute of Crop Science, RDA)
Son, Ji-Young (National Institute of Crop Science, RDA)
Yoon, Young-Hwan (National Institute of Crop Science, RDA)
Seo, Jong-Ho (National Institute of Crop Science, RDA)
Kwon, Young-Up (National Institute of Crop Science, RDA)
Shin, Jin-Chul (National Institute of Crop Science, RDA)
Lee, Byun-Woo (College of Agriculture and Life Science, Seoul Nat'l Univ.)
Publication Information
KOREAN JOURNAL OF CROP SCIENCE / v.55, no.4, 2010 , pp. 275-283 More about this Journal
Abstract
This experiment was conducted to construct process models to estimate grain weight (GW) and grain nitrogen content (GN) in rice. A model was developed to describe the dynamic pattern of GW and GN during grain-filling period considering their relationships with temperature, solar radiation and growth traits such as LAI, shoot dry-weight, shoot nitrogen content, grain number during grain filling. Firstly, maximum grain weight (GWmax) and maximum grain nitrogen content (GNmax) equation was formulated in relation to Accumulated effective temperature (AET) ${\times}$ Accumulated radiation (AR) using boundary line analysis. Secondly, GW and GN equation were created by relating the difference between GW and GWmax and the difference between GN and GNmax, respectively, with growth traits. Considering the statistics such as coefficient of determination and relative root mean square of error and number of predictor variables, appropriate models for GW and GN were selected. Model for GW includes GWmax determined by AET ${\times}$ AR, shoot dry weight and grain number per unit land area as predictor variables while model for GN includes GNmax determined by AET ${\times}$ AR, shoot N content and grain number per unit land area. These models could explain the variations of GW and GN caused not only by variations of temperature and solar radiation but also by variations of growth traits due to different sowing date, nitrogen fertilization amount and row spacing with relatively high accuracy.
Keywords
rice; temperature; radiation; sink; source; grain weight; grain nitrogen content; simulation;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 이충근, 권영업, 이재은, 서종호, 신진철. 2009b. Sink와 Source 관련형질 변이가 벼 종실중 및 종실질소함량 변이에 미치는 영향. 한국작물학회지54(1): 45-54   과학기술학회마을
2 이충근, 김덕수, 권영업, 이재은, 서종호, 이변우. 2009a. 등숙기기온 및 일사량이 벼 종실중 및 종실질소함량에 미치는 영향. 한국작물학회지 54(1): 36-44   과학기술학회마을
3 Zhu Y., Li W., Jing Q., Cao W., Horie T. 2007. Modeling grain protein formation in relation to nitrogen uptake and remobilization in rice plant. Agric. China 1(1): 8-16.   DOI   ScienceOn
4 김창국, 이변우, 한원식. 2001. 최대경계선을 이용한 벼 수량의 기상반응분석과 수량 예측 1. 최대경계선 분석과 수량예측 모형 구축. 한국작물학회지. 46(3): 241-247
5 Webb, R.A. 1972. Use of the boundary line in the analysis of biological data. J. Hort. Sci. 47: 309-319.
6 Van Keulen, H., Seligman, N.G. 1987. Simulation of Water Use, Nitrogen Nutrition and Growth of a Spring Wheat Crop. Simulation Monographs, Pudoc, Wageningen, 310 pp.
7 Wallach, D., Goffinet, B. 1987. Mean squared error of prediction in models for studying ecological and agronomic systems. Biometrics 43: 561-573.   DOI   ScienceOn
8 Walworth, L.L., Letzsch, W.S., Summer, M.E. 1986. Use of boundary line in establishing diagnostic norms. Soil Sci. Soc. Am. J. 50: 123-128.   DOI   ScienceOn
9 Weir, A.H., Bragg, P.L., Porter, J.R. Rayner, J.H. 1984. A winter wheat crop simulation model without water or nutrient limitations J. Agric. Sci. 102: 371-382.   DOI
10 Weiss, A.. Moreno-Sotomayer, A. 2006. Simulating grain mass and nitrogen concentration in wheat. Europ. J. Agronomy 25: 139-137.
11 Triboi, E., Triboi-Blondel, A.M. 2002. Productivity and grain or seed compositions: a new approach to an old problem. Eur.J.Agron. 16, 163-186.   DOI   ScienceOn
12 Ogunlela, V.B., Eastin, J.D. 1984. Effect of elevated night temperature during panicle development on sorghum (Sorghum bicolor L.) yieId components. Cereal Res. Comm. 12: 245-251.
13 Porter, J.R. 1993. AFRCWHEAT2: a model of the growth and development of wheat incorporating responses to water and nitrogen. Eur. J. Agron. 2, 69-82. Rice Research Institute, Los Banos, Philippines. pp: 21-38   DOI
14 Rítchie, J. T. Otter, S. 1985. Description and performance of CERES-Wheat: a user-oriental wheat yieId model. In: Willis, W.O. (Ed), ARS Wheat Yield Project, pp. 159-175(USDA-ARS, ARS 38).
15 Ritchie, J.T., Godwin, D.C., Otter-Nacke, S. 1985. CERES-Wheat, AGRISTARS Publication No. YM-U3-04442-JSC-18892, Michigan State University, MI, p.252.
16 Saeed, M., Francis, C.A., Clegg, M.D. 1986. Yield component analysis in grain sorghum. Crop Sci. 26: 346-351.   DOI
17 McCown, R.L., Hammer, G.L. Hargreaves, J.N.G., Holzworth, D., Freebairn, D.M. 1996. APSIM: a novel software system for model development, model testing and simulation in agricultural systems research. Agric. Syst. 50, 255-271.   DOI   ScienceOn
18 Michele, R., Nicola, L., Zina, F. 2003. Evaluation and application of the OILCROP-SUN model for sunflower in southern Italy. Agric. Syst. 50: 255-271.
19 Lecoeur, J. Sinclair, T.R. 2001. Analysis of nitrogen partitioning in field pea resulting in linear increase in nitrogen harvest index. Field Crops Res. 71, 151-158.   DOI   ScienceOn
20 Moller-Nielsen J. and Frijs-Nielsen B. 1976. Evaluation and control of the nutritional status of cereals. Plant and Soil. 45: 339-351.   DOI
21 Asseng, S., Bar-Tal, A., Bowden, J.W. Keating, B.A., van Herwaarden, A., Palta, J.A., Huth, N.I., Probert, M.E. 2002. Simulation of grain protein content with APSIM-Nwheat. Eur. J. Agron. 16, 25-42.   DOI   ScienceOn
22 Martre, P., Porter, J. R. Jamieson, P.D., Triboi, E. 2003. Modeling grain nitrogen accumulation and protein composition to understand the sink/source regulations of nitrogen remobilization for wheat. Plant Physiol. 133, 1959-1967.   DOI   ScienceOn
23 Gregory, P.J., Crawford, D.V., McGowan. 1979. Nutrient relations of winter wheat. I. Accumulation and distribution of Na, K, Ca, Mg, P, S, N. J. Agric. Sci. Camb. 93, 485-494.   DOI
24 Jamieson, P.D., Semenov, M.A. Brooking, I.R., Francis, G.S. 1998. Sirius: a mechanistic model of wheat response to environmental variation. Eur. J. Agron. 8, 161-179.   DOI   ScienceOn
25 Bingham, J. 1967. Investigations on the physiology of yield in winter wheat, by comparisons of varieties and by artificial variation in grain number per ear. J. Agric. Sci. Camb. 68: 411-422.   DOI   ScienceOn
26 Bouman, B.A.M., Van Laar, H.H. 2006. Description and evaluation of the rice growth model ORYZA2000 under nitrogen-Iimited conditions. Agricultural Systems 87, 249-273.   DOI   ScienceOn
27 Darroch, B.A., Bakcr, R.J. 1990. Grain filling in three spring wheat genotypes : statistical analysis. Crop Sci. 30: 525-529.   DOI
28 Gao L, Jin S., Huang Y., Zhang L. 1992. Rice clock model: a computer model to simulate rice development. Agricultural and Forest Meteorology 60: 1-16.   DOI