Corn Yield Potential and Optimal Soil Productivity in Irrigated Corn/Soybean Systems[1]

 

A. Dobermann, T. Arkebauer, K. Cassman, R. Drijber, J. Lindquist, S. Madhavan, J. Markwell, L. Nelson, J. Specht, D. Walters, H. Yang, B. Amos, D. Binder, C. Murphy, G. Teichmeier

 

Department of Agronomy and Horticulture, University of Nebraska, PO Box 830915, Lincoln, NE 68583-0915

 

 

Abstract

In 1999, an interdisciplinary research team at the University of Nebraska established a field experiment to (1) quantify and understand the yield potential of corn and soybean under irrigated conditions, (2) identify efficient crop management practices to achieve yields that approach potential levels, and (3) determine the energy use efficiency, global warming and soil C-sequestration potential of intensively managed corn systems. The experiment compares systems that represent different levels of management intensity expressed as combinations of crop rotation (continuous corn, corn-soybean), plant density (low, medium, high) and nutrient management (recommended best management vs. intensive management). Detailed measurements include soil nutrient dynamics and C balance, crop growth and development, nutrient uptake and components of yield of corn and soybean, radiation use efficiency, soil surface fluxes of greenhouse gases, root biomass, C inputs through crop residues, translocation of non-structural carbohydrates, and amount, composition and activity of the microbial biomass. Selected results for corn are presented.

 

 

Rationale and Objectives

Crop yield improvement must continue unabated well into the 21st century, not only to meet the food and fiber needs of the nine billion people on earth the year 2050 (Evans, 1998), but also to minimize the conversion to agriculture of land now spared for nature (Waggoner, 1994; Young, 1999). About 30 million ha of corn are harvested annually for grain in the USA, of which eleven states in the Corn Belt produce more than 210 million t or 35% of the global corn supply (Dobermann and Cassman, 2002). Globally important intensive agricultural systems such as rainfed and irrigated continuous corn or corn-soybean will play a key role in sustaining the future global food supply because present average corn and soybean yields are only about 50% of the estimated climatic-genetic yield potential of these crops (Duvick and Cassman, 1999; Specht et al., 1999). This yield gap will not be closed by genetic technology. At the farm level, rapid producer adoption of genetic and agronomic technologies has fueled past improvements in harvest index and crop biomass per unit area. However, harvest index in many seed crops is now approaching its natural asymptotic limit (Sinclair, 1998), making future seed yield improvement substantially dependent upon increases in crop biomass. Intensified crop and soil management will be necessary to coax more out of the crop biomass potential.

Our hypothesis is that intensive agricultural systems can be designed to achieve an optimal balance of productivity, profitability, and soil C sequestration with minimal nitrate leaching and emission of greenhouse gases by improved management that achieves greater input use efficiency at yield levels that approach yield potential ceilings.

There is need to develop integrative scientific understanding of the relationships between soil productivity, crop yield potential, input use efficiency, nitrate leaching, C-sequestration, and greenhouse gas fluxes and energy use in corn-based cropping systems (Cassman, 1999). Therefore, in 1999, a group of researchers at UNL established a field experiment suitable for making detailed measurements of crop, soil, and other system parameters in a high yield setting. The long-term objectives of this project are to:

  1. Quantify the yield potential of irrigated corn and soybean and understand the physiological processes determining it.
  2. Identify cost-effective and environmentally friendly crop management practices to achieve irrigated corn and soybean yields that approach attainable levels.
  3. Determine how changes in soil quality affect the ability to achieve yields that approach yield potential levels.
  4. Quantify the nitrate leaching potential, energy use efficiency, soil C-sequestration and net radiative forcing potential of intensive corn-based systems at different levels of management.
  5. Develop improved crop and ecosystem simulation models for accurate prediction of yield potential and carbon sequestration potential under different management scenarios.

Initial focus during this period was on (1) exploring crop management practices for growing corn and soybean near optimal levels, (2) quantifying crop growth rates and dry matter distribution among various plant organs, (3) assessing and improving crop simulation models for corn, and (4) quantifying fluxes of greenhouse gases at different levels of management. First data were reported earlier (Arkebauer et al., 2001). In this paper we focus on a more detailed understanding of corn yields as well as soil processes at different cropping intensity.

Material and Methods

A long-term experiment was established in 1999 at the UNL East Campus in Lincoln, NE on a deep Kennebec silt loam (fine-silty, mixed, superactive, mesic Cumulic Hapludoll). Prior to 1999 the field was in a sorghum-soybean rotation without N fertilizer for the past 10 years. Average initial soil test values in 0 to 20 cm depth were pH 5.3, 2.7% soil organic matter, 67 ppm Bray-P, and 350 ppm exchangeable K. Lime was applied in 1999 (2 t CCE/acre).

            The 3x3x2 factorial experiment was conducted in a split-split plot randomized complete block design (4 replicates) with crop rotations (R) as main plots, plant population (P) density as sub-plots, and level of fertilizer nutrient management (M) as sub-subplots (Table 1). Sub-subplots were 6.1 m x 15.2 m (20’ x 50’) in size with 8 rows at 0.762 m (30’’) row spacing. Four border rows adjacent to the main plots were used as unfertilized control plots (M0) in 1999 and 2000. In 2001, the experiment was modified to include one smaller M0 plot (4 rows x 10 ft) embedded within each M1 or M2 treatment plot. The field was fall moldboard plowed in each year to create a deeper topsoil layer. In the fall of 1999, the field was also ripped to a depth of about 45 cm. In 1999 and 2000, the experiment was irrigated to fully replenish daily crop evapotranspiration via a surface drip tape system, with the tape placed next to the plants in each row. In 2001, a permanent subsurface drip irrigation was installed with drip tapes in alternate rows at about 12 to 15” depth. Corn hybrid Pioneer 33A14 (Bt) was planted in 1999 and 2000 and hybrid 33P67 in 2001. In the corn-soybean rotation, a high-yielding, semi-determinate soybean cultivar, NE3001, was planted in all three years. Field cultivation of all plots was done at V6 stage of corn to incorporate N fertilizer and control weeds.

Fertilizer N rates used are shown in Table 2. In M1 plots, N rates for corn were calculated using the current UNL N algorithm (Shapiro et al., 2001):

                        N = -35 + (1.2 x YG) – (8 x NO3) – (0.14 x YG x SOM) – other N credits

where N = recommended N rate (lb N/acre), YG = yield goal (200 bu/acre), NO3 = soil test nitrate-N level in spring (ppm), SOM = soil organic matter content (%), and N credit = credit of 45 lb N/acre if previous crops was soybean. In the M2 treatment, the N rate in 1999 was calculated by assuming 1 kg N uptake per bu yield for an expected yield of 250 bu/acre. In 2000 and 2001, the calculation assumed a yield goal of 300 bu/acre, an internal plant N requirement of 1.1 kg N uptake per bu yield, and an average recovery efficiency of applied N of about 60%. Measured values of indigenous N supply and residual soil nitrate were used to adjust N rates in M2 by crop rotations. In both years, no nutrients other than N were applied in the M1 treatments to both crops because soil test values were above currently suggested critical levels of sufficiency. In the M2 treatment, 92 lb P2O5/acre and 93 lb K2O/acre were applied pre-plant in addition to N on both soybean and corn crops. In 1999 and 2000, those treatments also received 19 lb S/acre, 11 lb Fe/acre and 5 lb Zn/acre. Granular pre-plant fertilizer (blend of N, P, K, S, Fe and Zn fertilizers) was broadcast and disc-incorporated, whereas sidedress applications of ammonium nitrate were surface-banded in the plant row followed by a drip tape irrigation or field cultivation.

Key measurements in this field experiment include:

 

 

 

Table 1. Treatment design for the Ecological Intensification of Maize Systems project.

Crop rotation (main plots)

      CC             Continuous corn

      CS             Corn – Soybean (corn in odd years)

      SC             Soybean – Corn (corn in even years)

Plant Population (subplots)1

      P1              Corn: 28-31,000 plants/acre

                        Soybean: 1999-2000: 150,000 seeds/acre; 2001: 105,000 seeds/acre

      P2              Corn: 35-40,000 plants/acre

                        Soybean: 1999-200: 185,000 seeds/acre; 2001: 129,500 seeds/acre

      P3              Corn: 44-47,000 plants/acre

                        Soybean: 1999-2000: 220,000 seeds/acre; 2001: 154,000 seeds/acre

Management Intensity (sub-subplots)

      M1             recommended fertilizer management based on soil testing. Maize: UNL recommendation for 200 bu/acre yield goal

      M2             intensive management aimed at yields close to yield potential. Maize yield goal 300 bu/acre, higher NPK rates, micronutrients, N in 3 splits

 

Table 2. Fertilizer N applications to corn and soybean.

Crop rotation

Management

Growth Stage

N rate (lb/acre)

 

 

 

1999

2000

2001

Corn after soybean

M1

Pre-plant

58

92

89

 

 

V6

58

31

27

 

 

Total

116

123

116

 

M2

Pre-plant

94

92

89

 

 

V6

54

89

45

 

 

V10

54

85

45

 

 

VT

 

 

36

 

 

Total

201

266

214

Corn after corn

M1

Pre-plant

 

92

89

 

 

V6

 

89

89

 

 

Total

 

181

179

 

M2

Pre-plant

 

92

89

 

 

V6

 

116

71

 

 

V10

 

116

71

 

 

VT

 

 

36

 

 

Total

 

324

268

Soybean

M2

Pre-plant

36

92

-

 

 

R3

49

45

36

 

 

R5

49

-

36

 

 

Total

134

137

72

Results and Discussion

Corn Grain Yield

Plant density and nutrient management levels significantly affected yield, harvest index, stover yield, components of yield, and nutrient uptake requirements of corn. Intensive fertilizer management (M2) significantly increased yield in all three years over the recommended fertility regime (Fig. 1). Maximum grain yields ranged from 249 to 257 bu/acre in all three years. In all three years, treatment CS-M2-P2 produced consistently high yields of 245 to 252 bu/acre that were close to the simulated yield potential for this plant density (Fig. 1). Continuous corn yields were below those obtained in the corn-soybean rotation at the recommended level of nutrient management (M1), but the differences diminished for M2 nutrient management.

In 1999, corn was planted late (May 13) and grain yield increased with both increasing population density and management intensity, with a high of 258 bu/acre for the CS-M2-P3 treatment. At the M2 level of nutrient management, the harvest index of maize decreased with increasing plant density due to greater vegetative biomass accumulation. Sink size (no. of kernels/m2) and nutrient uptake also increased with increasing plant density and nutrient management level (Arkebauer et al., 2001). The 100-seed weight was about 4% larger in M2 treatments than in M1, but decreased with increasing plant density.

In 2000 and 2001, corn was planted in late April and growth was much affected by hot temperatures during grain filling. Highest yield was 249 bu/acre in 2000 (CS-M2-P2 treatment) and 252 bu/acre in 2001 (CS-M2-P2 and CC-M2-P3 treatments). In 2000, at all population and nutrient management levels, grain yield in continuous corn was below that of corn grown after soybean, but the difference was smallest in M2 treatments. Similar observations were made for M1 treatments in 2001, but corn yield in M2 treatments with high plant density was similar in the CC and CS rotations (Fig. 1). Increasing plant density beyond the P2 level did not significantly increase yield and plant nutrient accumulation in 2000 and 2001, or even led to a decrease observed in 2000. Actual plant densities in the P3 treatment were about 5% greater than in 1999 (P3: average of 46,500 plants/acre in 2000 and 2001 vs. 44,200 plants/acre in 1999), which may have further accelerated crop stress under high temperatures during grain filling. Biomass x temperature interactions on crop respiration losses (see below) may explain why in 2000 and 2001 yields did not increase in the highest density treatment because the actual plant density in P3 was probably excessive, whereas it was already near optimal (37-41,000 plants/acre) in the P2 treatment.

At intensive level of nutrient management, the harvest index of maize decreased with increasing plant density due to greater vegetative biomass accumulation. Stover yield (stalks, leaves, cobs, tassels) increased with both an increase in population and fertility management. For example, averaged over three years, stover yield was 12.2 Mg dry matter/ha in corn after soybean at the currently recommended plant density (P1, 30,000 plants/acre) and fertilizer management level (M1). In contrast, stover yield at very high density (P3) and intensive fertilizer management (M2) averaged 14.1 Mg/ha. In continuous corn, annual stover yield averaged 11.7 Mg/ha for the M1-P1 treatment vs. 14.0 Mg/ha under very intensive management (M2-P3).

 

Fig. 1. Corn grain yield (15.5 m.c.) in 1999 to 2001 as affected by crop rotation (CC-continuous corn; CS – corn-soybean), fertility management (M1 – recommended; M2 – intensive), and final plant population density (P1 – 28-31,000 pl./ac; P2 – 36-41,000 pl./ac; P3 – 44-47,000 pl./ac). Values shown are treatment means and standard errors. The thin gray bars in the background show the simulated corn yield potential for each plant density – year combination (Hybrid-Maize simulations, H. Yang, unpublished data).

 

 

 

Simulated Corn Yield Potential

Crop simulation modeling is a useful tool for gaining improved understanding of environmental controls on crop growth and development. It also can improve the efficiency of targeting research that seeks to develop improved management practices for optimizing crop performance, soil quality, and addressing environmental concerns, especially at yield levels that approach the yield potential ceiling. Before using a model as a tool to guide research, however, it must be evaluated comprehensively under circumstances similar to the intended applications. Most corn models have so far been evaluated at moderate grain yields of 150 to 200 bu/acre, although yields of 300 bu/acre or more have been reported in the north-central USA.

Published versions of four existing corn models were used to simulate the climatic-genetic yield potential for all three experimental years (Table 3). Neither model formulations nor default values of parameters were modified except for those parameters that require site- and season-specific settings. The crop data from the EI field trial were obtained from the intensive nutrient management treatment in the corn-soybean rotation. There were no obvious abiotic (water, nutrients) or biotic stresses that limited crop growth. Hence, all functions for these stresses in the models were ‘turned off’ so that the simulations would reflect cop growth under non-limiting conditions driven by climate (temperature, solar radiation) for a specific planting date and plant density.

The general pattern of simulated aboveground biomass accumulation was in reasonable agreement among the models, but the simulated leaf area index (LAI) varied considerably. The models accurately tracked the actual dry matter accumulation during the establishment phase of the crop, but underestimated actual growth rates during the linear growth phase. As a result, the models underestimated the measured grain yield at near-optimal growth by an average of 6 to 26% (Table 3). Underestimation of stover biomass at maturity was even larger than that (11 to 29%) and the models mostly failed to account for the measured decrease in harvest index (HI) at higher plant populations. Greater variability in the accuracy of simulating vegetative biomass compared to grain yield is a concern when modeling long-term C balances to predict C sequestration in high-yield systems because of cumulative effects of underestimating crop residue inputs.

Efforts were made to develop a new corn model, Hybrid-Maize. This model combines components of several of the crop models tested as well as unique formulations that were derived from the literature and data collected in the UN-L ecological intensification experiment (H. Yang et al., UN-L, unpublished). Initial validation suggests that Hybrid Maize simulated yield, biomass, harvest index, and LAI in near yield potential situations more accurately than other corn models (Table 3). Other advantages include a greater sensitivity to plant density and the ability to simulate maturity based on cumulative growing degree days rather than as a user-defined date, making it easier to use for scenario analysis. Simulations done for each experimental year (Fig. 1) and plant density suggest that (i) simulated yield potential in normal plant density treatments (P1) was matched by the measured yields in both rotations and at both nutrient management levels, (ii) measured yields were typically below the simulated yield potential at increased plant density (P2 and P3), but the difference was largest for M1 treatments. The latter suggests a resource limitation, which was at least partially overcome by applying more nutrients in the M2 treatments. However, the model was unable to predict the decrease in yield in the M2-P3 treatments in 2000, which appeared to be associated with climatic factors rather than resource limitation.

It remains unclear whether even this improved model is capable of simulating the true yield potential of corn because several fundamental relationships used in it will require better calibration using data sets collected at yield potential levels. Key issues for model improvement are LAI prediction, radiation use efficiency (RUE), density effects on harvest index, and response to temperature, especially during the reproductive growth phase.

Understanding Corn Performance at High Yield Levels

Climatic Variation and Yield Potential of Corn

The main value of quantitative tools such as a crop simulation model is probably to develop hypotheses about the effects of climate and crop management on yield-forming processes as a means for identifying most suitable mitigation options. The experimental years differed markedly in their climatic conditions, which caused significant differences in plant responses such as rate of plant development, leaf emergence, respiration, grain filling, and senescence as well as soil processes. Below we attempt to understand those differences with the help of the Hybrid-Maize model.

Table 3. Actual corn grain yield and total aboveground biomass as measured in the field experiments conducted from 1999 to 2001, and the simulated values for these parameters using five corn simulation models. All values are derived from the M2 nutrient management treatment for corn following soybean at a plant population of 37,000 to 40,000 plants/acre (P2). Values in parenthesis are deviations (%) of model simulations from the actual values measured in the field (H. Yang, unpublished data).

Data/crop model

Year

Grain yield 1

 

Total biomass 1

 

 

bu DM/acre

%

 

ton DM/acre

%

Measured (EI trial)

1999

245

 

 

11.3