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THE “MAIZE-N” MODEL: TOWARD A GLOBAL APPROACH TO NITROGEN MANAGEMENT IN MAIZE D. Walters THE “MAIZE-N” MODEL: TOWARD A GLOBAL APPROACH TO NITROGEN MANAGEMENT IN MAIZE D. Walters 1, Tri Setiyono 1, H. Yang 2, K. Cassman 1, A. Dobermann 3 1 Univ. of Nebraska-Lincoln, Department of Agronomy and Horticulture, University of Nebraska, PO Box 839015, Lincoln, NE 68583 -0915; email: dwalters [email protected] edu 2 Monsanto Co. , St. Louis, MO, 3 IRRI, Manila, Philippines

Background and Rationale n Goal: obtain the economically optimal N rate (EONR) to n Background and Rationale n Goal: obtain the economically optimal N rate (EONR) to n Problem: uncertainties in N response – varies among n maximize net return to applied N for maize regions, fields, management zones, and different growing season Factors influencing the shape of the N response curve: Yield potential (Yp), yield without N application (Y 0) and the agronomic efficiency of applied N (AE) n Factors influencing Yp: weather, planting date, n Factors influencing Y 0: inherent soil conditions and hybrid, plant population soil and crop management factors (tillage, rotation, residue management)

“Maize-N” Structure n “Maize – N” structure is predicated on the relationship between yield “Maize-N” Structure n “Maize – N” structure is predicated on the relationship between yield response and uptake efficiency defined by Agronomic Efficiency (AE) which is the product of N recovery Efficiency (RE) and Physiological Efficiency (PE): AE = RE x PE = (Y-Y 0)/N RE = (U-U 0)/N PE = (Y-Y 0)/(U-U 0)

“Maize-N” Structure n Fertilizer N requirement (N): N = (Y-Y 0)/AE N = (U-U “Maize-N” Structure n Fertilizer N requirement (N): N = (Y-Y 0)/AE N = (U-U 0)/RE = (U-IN)/RE Y = expected yield (kg/ha) Y 0 = yield without N application (kg/ha) U = total crop N uptake (kg/ha) U 0 = total crop N uptake without fertilizer addition (kg/ha) AE = agronomic efficiency of applied N (kg yield increase / kg N applied) RE = recovery efficiency of applied N (kg fertilizer N recovered in the crop / kg N applied)

Input Processes Output “Maize-N” Model Flow Chart Input Processes Output “Maize-N” Model Flow Chart

Relevant yield terms in “Maize. N” Yp = Yield potential Ya = Attainable yield Relevant yield terms in “Maize. N” Yp = Yield potential Ya = Attainable yield YEONR = Yield goal Yo = Yield without fertilizer N EONR = Economically optimum N rate 18 Yp 16 Ya -1 Yield (Mg ha ) 14 Y EONR 12 10 8 Y 0 6 Observed data (Clay Center, NE 2002) 4 2 EONR 0 0 40 80 120 160 N (kg ha 200 -1 ) 240 280 *Assumes: minimal limitation from factors other than N

Options for Estimating Attainable Yield (Ya) n n “Maize-N” uses long-term site weather data Options for Estimating Attainable Yield (Ya) n n “Maize-N” uses long-term site weather data with crop management data as input to an internal yield simulation model, Hybrid Maize (Yang et al. , 20041) to estimate Yield potential (Yp). Attainable yield is then calculated as a function of Ya = f x Yp. The value chosen for f is user determined (f = 0. 85 by default) As an alternative, the user may opt to use their own estimate of Ya based on yield history. 1 Field Crops Research 87: 131 -154

OPTIMIZING HYBRID MAIZE YIELD POTENTIAL 80 locations within Lat 32. 7 -42. 7 N; OPTIMIZING HYBRID MAIZE YIELD POTENTIAL 80 locations within Lat 32. 7 -42. 7 N; Long 88 -102 W; Elev. 130 – 1390 m Hybrid-Maize simulated yield potential for corn: Hybrid: 2650 GDU (110 d CRM); Planting date: May 1, 40, 000 plants/acre Management: no limitations by water or nutrients

HYBRID-MAIZE: YIELD-BASED RANKING OF Yp RESULTS HYBRID-MAIZE: YIELD-BASED RANKING OF Yp RESULTS

Maize nutrient requirements (QUEFTS) QUEFTS Janssen et al. , 1990 1 Witt et al. Maize nutrient requirements (QUEFTS) QUEFTS Janssen et al. , 1990 1 Witt et al. , 1999 2 1 Geoderma. 46: 299 -318. 2 Field Crops Research 63: 113 -138. Data from Nebraska (NE) and South East Asia (SEA), 1997 -2006 Irrigated maize (all modern hybrids)

USA Yield potential (Mg/ha) SE Asia Spherical model for yield-uptake relations: Cubic solver for USA Yield potential (Mg/ha) SE Asia Spherical model for yield-uptake relations: Cubic solver for uptake-yield relations: y – Yield (Mg ha-1) – yield goal x – N uptake (kg ha-1) b – Yp, yield potential (Mg ha-1) c – uptake at yield approaching Yp (kg ha-1) Maize nutrient requirements (QUEFTS)

Spherical model (Dobermann et al. , 20061) Ya b Y 0 c=(Ya-Y 0)/AE Y Spherical model (Dobermann et al. , 20061) Ya b Y 0 c=(Ya-Y 0)/AE Y – yield (kg/ha) Y 0 – yield without N application (kg/ha) Ya – attainable yield (kg/ha), N – fertilizer rate (kg/ha) b – maximum yield increase from applying N (kg/ha) c – fertilizer N rate at attainable yield R – ratio of maize to N prices AE – agronomic efficiency of applied N (kg grain per kg N) 1 Proc. Great Plains Soil Fertility Conference. Kansas State Univ. , Manhattan, KS. , pp. 50 -59

Empirical Baseline Agronomic Efficiency (AE) in Relation Ya-Yo Empirical Baseline Agronomic Efficiency (AE) in Relation Ya-Yo

Indigenous N supply (IN) – DK-C&N model §“Maize-N” simulates daily mineralization of soil organic Indigenous N supply (IN) – DK-C&N model §“Maize-N” simulates daily mineralization of soil organic matter, crop residues and manure based on substrate C: N following the approach of Yang and Janssen (20001, 20022). k = substrate reactivity that varies over time Y 0 = Initial organic substrate Y = amount of substrate at time=t R = initial substrate reactivity S = speed at which k decreases over time (speed of aging) Tcoef = Q 10 for temperature effect on decomposition 1 Eur. J. Soil Sci. , 51(3): 517 -529 2 Plant & Soil, 239: 215 -224

Calculation of (Yo) and (Uo) n n DK & C Simulated Indigenous N (IN) Calculation of (Yo) and (Uo) n n DK & C Simulated Indigenous N (IN) supply is Used to Calculate the Yield of Unfertilized Maize (Yo) , Uptake of IN by Yo (Uo), Uptake efficiency of IN is set at a default value of 0. 85 but may be changed. The QUEFTS N response curve is used to calculate (Ya-Yo) and (Ua-Uo) along with AE.

Yield without applied N (Y 0) and indigenous N uptake (IN) Y 0 and Yield without applied N (Y 0) and indigenous N uptake (IN) Y 0 and IN A) USA NE IR F) INDONESIA RF B) USA MW IR G) ECUADOR RFW C) USA MW RF H) BRAZIL RF D) CHINA RF I) BRAZIL RF E) INDONESIA IR J) N. VIETNAM Data include 161 site x year

DK & N OUTPUT - IN DK & N OUTPUT - IN

Sim. Vs Obs. EONR USA NE, Indonesia, Brazil, China Sim. Vs Obs. EONR USA NE, Indonesia, Brazil, China

Dataset– perspective Dataset– perspective

CONCLUSIONS n n The Maize-N model is a computer simulation program for recommendation of CONCLUSIONS n n The Maize-N model is a computer simulation program for recommendation of nitrogen (N) fertilizer rate for maize crop (Zea mays L. ). It deploys a series of systematic and mechanistic analyses of climatic information, soil properties, and cropping system characteristics of a given field. The Maize-N model is composed of three major modules: n (1) maize yield module for estimating maize yield potential and its variation with the HYBRID-MAIZE model, n (2) carbon (C) and N mineralization module for estimating soil indigenous N supply with the DK&N model n (3) yield response module for estimating economically optimal N rate via the QUEFTS model

CONCLUSIONS n n Compared with conventional N rate recommendation schemes, the Maize-N model provides CONCLUSIONS n n Compared with conventional N rate recommendation schemes, the Maize-N model provides an analysis of the biophysical and climatic parameters that govern N supply, N use efficiency and Uptake in maize N systems. Maize-N also allows for the estimate of site- specific climate influences on the expression of yield potential (Yp) for today’s modern hybrids. The Maize-N Model provides a knowledge-based decision-aid that is global in scope and where N uptake is yield potential based.

References n n n n Dobermann, A. , Ferguson, R. , Hergert, G. , References n n n n Dobermann, A. , Ferguson, R. , Hergert, G. , Shapiro, C. , Tarkalson, D. , Walters, D. T. , Wortman, C. , 2006. Nitrogen response in high-yielding corn systems of Nebraska. In: Schlegel, A. J. (Ed. ), Proceedings of the Great Plains Soil Fertility Conference, Denver, CO March 7 -8, 2006. Kansas State University, Manhattan, KS. , pp. 50 -59. Janssen, B. H. , Guiking, F. C. T. , van der Eijk, et al. 1992. A system for quantitative evaluation of the fertility of tropical soil (QUEFTS). Geoderma. 46: 299 -318. Witt, C. , Dobermann, A. , Abdulrachman, S. , et al. 1999. Internal nutrient uise efficiencies of irrigated lowland rice in tropical and subtropical Asia. Field Crops Research 63: 113 -138. Yang, H, S. Janssen, B. H. . 2000. A mono-component model of carbon mineralization with a dynamic rate constant. European Journal of Soil Science, 51(3): 517 -529. Yang, H, S. Janssen, B. H. . 2002. A mono-component model of carbon mineralization with a dynamic rate constant. European Journal of Soil Science, 51(3): 517 -529. Yang, H. S. , Dobermann A. , Cassman, K. G. , Walters, D. T. 2004 a. DK-C&N: A simulation model for carbon and nitrogen. University of Nebraska Lincoln. Yang, H. S. , Dobermann, A. , Lindquist, J. L. , Walters, D. T. , Arkebauer, T. J. , K. G. Cassman. 2004 b. Hybrid-maize – a maize simulation model that combines two crop modeling approaches. Field Crops Research 87: 131 -154.

Acknowledgements We thank: • The International Plant Nutrition Institute of Agriculture and Natural Resources Acknowledgements We thank: • The International Plant Nutrition Institute of Agriculture and Natural Resources (IANR) of University of Nebraska • The Fluid Fertilizer Foundation for support of the development of the Maize-N model and for sponsoring our Ecological Intensive effort