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High yield studies – a stepwise approach

A final progress report submitted to the MN Soybean Research and Promotion Council & MN Corn Research and Promotion Council

A 2004-2010 study at the University of Minnesota Southwest Research and Outreach Center, Lamberton, MN, examined the effect of crop rotation and management on corn and soybean yields. Intensively managed continuous corn (manure and high fertility and plant populations) out-yielded conventionally managed rotated and continuous corn but yielded less than intensively managed rotated corn. Both corn and soybean yields were increased by rotation but more than two years of corn were needed to produce a soybean yield response over an annual rotation. Corn appeared to respond to higher fertility and consistently responded to banded applications of sulfur with increased yield. Soybeans did not respond to direct fertilizer application but yields were higher where previous corn crops were intensively managed. This study provides evidence that sulfur can reduce yields if other parts of the system are limiting. Nitrates accumulate in the soil profile during corn production. Soybeans reduced residual soil nitrates when included in the rotation.

Prepared and submitted by Bruce Potter

1/25/2013

bpotter@umn.edu

(507) 752-5066

 

 

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High yield studies a stepwise approach

Contents

Background……………………………………………………………………………………….. 3 Objectives……………………………………………………………………………………....... 4 Objective I. Soil and biotic changes resulting from various input strategies................... 5

Methods…………………………………………………………………………………... 5 Site description………………………………………………………………… 5 Rotations ……………………………………………………………….. ……… 6 Management system………………………………………………………….. 6 Soil fertility.................................................................................................... 8 Insect, weed and disease management ………………………………….. 8 Data collected………………………………………………………………….. 15

Results and discussion……………………………………………………………………….. 15 Weather effects on yield……………………………………………………………… 15 Management and rotation effect on yield………………………………………….. 21 Corn………………………………………………………………………………. 20 The role of sulfur in corn yields……………………………………. 22

Soybean …………………………………………………………………......... 26 The role of sulfur in soybean yields................................................. 27 The long term management effects on soybean yield.................... 29 The effect of management and rotation on biotic factors............. 33

Nematodes.................................................................................................. 33 Other biological observations.................................................................. 34

Management and rotation effect on soil test levels…………….............................. 35 Effect of management and rotation on residual nitrate levels..................... 39

Objective I. Summary and conclusions..................................................................... 40 Objective II. Initiate new long-term yield trials at multiple locations in MN......... 43 Objective III. Create a framework to identify input components for high yield... 45 Acknowledgments........................................................................................................ 47

Appendix I. Figures.................................................................................................................. 48 Appendix II. Tables................................................................................................................... 49

 

 

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High yield studies – a stepwise approach

Background Increasing crop yield per acre is a major component in grower profitability. Higher yield,

however, is most profitable when input costs produce a relatively predictable positive return.

Corn and soybean yields have both shown relatively constant and continuous historical

increases. Much of the real increase in yield can be attributed to improvements in genetics. In

the case of corn, breeding increased tolerance to interplant competition for light, water and

nitrogen are the apparent yield drivers. Additional yield increases can be attributed to cultural

methods such as improved drainage and fertilizer management, earlier planting, the narrowing

of row spacing and increased seeding rates (corn). Questions on relative increases from these

practices and the interactions between crop genetics and cultural practices persist. Finally,

increased yield stability in the presence of insect, disease and weed pests have resulted from

crop host plant resistance genes, transgenics in particular.

Numerous fertilizer products (e.g. seed applied zinc), growth regulators and prophylactic

pesticide applications (e.g. foliar fungicides) have been marketed as vital components for

producing high yields. Fitting new products into a production system is problematic from a

producer’s perspective. Experimentation and time will tell whether new techniques will enhance

the benefits of, or reduce the need for, tillage, crop rotation, host plant resistance and other

traditional agronomic tools.

At the same time that growers are driven by economics to produce higher yields, the non-

farming public is often critical of tillage, fertilizer and pesticide application methods.

Comprehensive data sets that would provide defense for high yield crop production systems are

lacking.

Yield research is often conducted on specific components (e.g. population, N rate, tillage

method) but how these components interact in a production setting is less often studied. As a

result, although Minnesota corn and soybean producers are quite capable of producing

excellent yields, they often struggle with putting together production systems that can

consistently maximize both yield and profitability. For example, simple and inexpensive

practices (e.g. plant population, cultivar selection) are often ignored while more costly and

inconsistent inputs (e.g. insurance pesticides) are applied. In short, a recipe for increased yield

 

 

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has not been developed, nor has the research been conducted to determine the proper blend of

ingredients under diverse corn growing environments in Minnesota.

Objectives

We proposed long-term research trials designed to identify agronomic methods for intensively

managed and consistently high yielding corn and soybean production which are highly profitable

and pose limited environmental risks. We believe that long-term research that compares

current production methods to a high yield system(s) provides the best approach to ensure rapid

adoption. Both systems should be expected to evolve over time. We define current production

methods as crop production practices that are representative, to the extent possible, of a large

proportion of producers in a region. Alternatively, a high yield system could incorporate proven

components of high yield as a platform to test other management strategies. Finally, this type of

systems approach could generate data needed to determine the mechanisms responsible for

yield differences between conventionally and intensively managed production systems.

In designing this study, we operated under the assumption that most producers practice

individual parts of a high yield system but may be missing one or several pieces. We examined

the possibility that yield increases within a cropping system do not happen instantly but occur

over time. We looked for reductions in the rotation effect on corn yield from long-term intensive

management. This project examines several objectives:

I. Collect and analyze data on soil fertility and biotic changes in various input strategies from a

high yield study at the University of Minnesota Southwest Research and Outreach Center.

Specifically we ask:

• Can yield be increased by higher management?

• Can higher management minimize the rotation effect for corn?

• Can extended rotations increase soybean yield?

II. Initiate new long-term high yield studies at multiple locations in Minnesota.

III. Create a framework to identify input components for high yield production systems

Agriculture production is constantly evolving and driven by complex biological and economic

interactions. This study represents an attempt to probe agronomic questions as part of an

 

 

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evolving system over time. It was not intended as a fertilizer, seeding rate, crop rotation or pest

management experiment. It was intended to incorporate results from experiments of this type.

Objective I. Soil and biotic changes resulting from various input strategies

Methods

Researchers from the industry, academic and government sectors and local agricultural

professionals, including farmers, often repeat experiments across years or environments.

These types of replication are important to allow accurate interpretation of their observations.

However, the interpretation of experimental results is often based on short-term, single year

responses to treatments. These responses may change as biological based agricultural

systems react to a stimulus (management) over time. In fact, long-term responses may be

antithetical to initial observations.

This study was designed to add an additional treatment to the high yield system when there was

data suggesting it had a positive impact on yield.

The presentation of this experimental design and the results derived highlight their imperfect

nature; the difficulties in designing long-term agronomic experiments that reflect reality.

Site description

A high yield comparison study at the University of Minnesota Southwest Research and

Outreach Center at Lamberton, MN, was initiated in the fall of 2004. A related, but not identical,

study was placed at the University of Minnesota Southern Research and Outreach Center, at

Waseca, MN. Funding was provided by the MCR&PC and MSR&PC from 2004-2006. These

data have been reported elsewhere. During 2007 and 2008, the Lamberton site was maintained

with limited data collection other than yield. MCR&PC and MSR&PC resumed funding of this

study in 2009. The study was discontinued after the 2010 growing season.

The site consists of Normania and Vess clay loam soils with high to very high phosphorus

fertility, high potassium fertility and high organic matter. The site had been in a corn-soybean

rotation for many years. The entire study area was planted to corn in 2003.

After the study was initiated we became aware that as a result of an old experiment, the north ½

of the study area was much lower in soil test phosphorus. The research area, particularly the

 

 

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north 1/2, was not optimally tiled. Tile lines were spaced at 180 feet on the north while the

south 1/2 was spaced at 90 feet. Fortunately, both of these variables were accounted for when

replications (blocks) were assigned (Figure 1).

Research plots were established at the beginning of the study. The study contained three

rotation factors and two management factors arranged in a randomized block design with four

replications. The eight main plots were split several times during the course of the study to

explore management options, tillage, fertilizer and seed treatment chemicals. Randomized sub-

plot treatments (factors) were discontinued where no yield responses were observed. Sub-plot

treatments expected to have persistent effects (e.g. sulfur fertility) were kept at a constant

location for subsequent applications.

Figure 1. Plot diagram of the high yield study area showing initial (2003) soil test values. Dashed lines indicate drainage tile spaced at 90 or 180 feet east to west.

Rotations

The four rotations established for this study were: 1) Continuous Corn, 2) Corn-Corn-Soybean,

3) Corn-Soybean and 4) Soybean-Corn. Rotation 4 was included to ensure at least one

soybean crop was present each year. Unfortunately, space did not permit a cyclic counterpart

to treatment 2 and all rotational combinations for both crops are not present every year. These

rotations were selected to look at yield penalties for non-rotated corn and whether an extra year

of corn (rotation 2) would improve soybean yields over an annual rotation.

Management system

P - 15 ppm P - 17 ppm NK - 167 ppm K - 177 ppmpH - 5.7 pH - 5.9 W E

BLOCK 3 BLOCK 4 S

P - 47 ppm P - 54 ppmK - 168 ppm K - 161 ppmpH - 6.2 pH - 6.0

BLOCK 1 BLOCK 2

Wat

erw

ay

320'

180'

320'

180'

BO

RD

ER

BO

RD

ER

BO

RD

ER

 

 

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A high yield or intensive management was compared to a management system more commonly

practiced by area farmers. Hereafter, these management schemes are referred to as “intensive

management” and “common practices management”. The resulting eight treatments are shown

in Figure 2.

Corn stalks were moldboard plowed in the fall of 2003 and subsequently in those plots that were

to be planted back to corn and or intensive managed soybeans. Additional information on

tillage treatments is shown in Table 1.

The intensive management corn treatment consists of: biennial manure (beef feedlot), higher

seeding rates (38,000 seeds/acre), and at-plant fertilizer (dry starter 2x2 2004, otherwise 10-34-

0 at-plant, in-row). Anhydrous ammonia was applied in the fall of 2004. All other spring or fall

broadcast N applications were urea. A post-emerge, side-dress application of 28% N at 4-6 leaf

corn was also made. We did not want nutrients to be limited in intensive management. This

study was not designed to determine fertilizer rates.

The common practices management treatments consist of the same rotations without manure,

pop-up and side dress fertilizer and a lower 33,000 seeds/acre seeding rate. N, P and K were

applied based on University recommendations at the time. Fertilizer application data are shown

in Table 2.

Over the course of the study, several management techniques were tried and abandoned due to

lack of significant yield response. These include soybean seed treatments, deep tillage and

direct sulfur application to soybean. This intent of this experiment was to include practices as

they were proven to increase yield rather than remove treatments as in a dropout experiment.

Removal of treatments ran counter to the experimental design and ceased after 2006.

Each year, corn and soybeans were planted as early in the spring as conditions allowed. Corn

was planted in 30-inch rows with a John Deere MaxEmerge four-row planter. The yield

response of soybeans to narrow rows had been well documented. During 2004 and 2009,

intensive management soybeans were planted in 15 inch rows by double planting with a 30 inch

planter. The common practices soybeans were planted in 30-inch rows. Unfortunately, wet

spring soils prevented narrow row seeding with this method other years. All other soybeans

were planted in 30-inch rows.

 

 

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The corn hybrids and soybean varieties used were selected from those commonly planted in the

area. They were selected by examining yield trials from several sources and conferring with

seed company agronomists. The same hybrids and varieties were planted in both management

regimes and all rotations. Planting date and hybrid/variety information is presented in Table 3.

Soil fertility

Manure on a biennial basis (2003, 2005 and 2009) and higher rates of N were applied to the

intensive management plots. Mineralization of plant nutrients over multiple years was expected

to buffer any plant nutrient stresses for primary and micronutrients.

Moisture is often limiting during mid to late season at this location. A portion of the nitrogen

allocated for intensive managed corn was planned for fall. The intent was to provide some N

deeper in the profile if dry conditions occurred. Weather conditions did not allow this application

every fall. The location of N in the soil profile is discussed later. Side-dressed N in intensive

managed corn was intended to insure adequate N in the upper profile in the event of flooded or

wet soils.

Soil tests results revealed moderate but highly variable zinc levels. Some samples indicated the

potential for corn yield response to zinc application. This nutrient might have been handled as

annual banded or pop-up applications. Instead, it was decided to use an alternative approach.

Eight (8) pounds of zinc sulfate/acre were broadcast in the spring of 2005 to minimize yield

variability from zinc.

Several crop production retail agronomists and crop consultants were questioning whether

sulfur applications were increasing yields on fine textured soils. Intensive management plots

received approximately twenty-two pounds of sulfur/acre (110 pounds of broadcast calcium

sulfate/acre) applied to the west ½ of each plot of both crops in 2006. Twenty-eight

pounds/acre of sulfur (ammonium thiosulfate @ 10 gallons/acre) was applied with a 28% N

side-dress to corn in 2007, 2008, and 2009 as a split plot. To ensure that any yield response

was due to sulfur; the remaining ½ plot received an equivalent rate of N as 28% N. Fertilizer

and manure applications for the eight main plot treatments are shown in Table 2.

Insect, weed and disease management.

 

 

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Soybean plots were split with fungicide/insecticide seed treatments in 2004 and 2005. This

study and additional small plot research trials at this location and elsewhere did not show a yield

response. It was assumed that these treatments did not have persistent effects and these

treatments were discontinued. Soybean plots were treated as single units for disease

management from 2006-2009.

European corn borer was controlled with Bt hybrids and was not a factor in corn yields. This

site had a history of extended diapause northern corn rootworm. Rootworm larvae were

controlled with Aztec insecticide during 2004 and 2005. YieldGard® Bt CB/RW hybrids were

used in 2006–2008 and a Herculex® XTRA Bt CB/RW hybrid was used in 2009.

Soybean cyst nematode were determined to be present but at very at low levels at the

beginning of this study. PI 88788 source SCN resistance varieties were used throughout the

study period.

Soybean aphids were controlled with foliar insecticides all years except 2004 when populations

did not exceed the economic threshold. Chlorpyifos (Lorsban 4E) or bifenthrin (Tundra), are

effective against two-spotted spider mite and soybean aphid and were applied when both pests

occurred.

Glyphosate tolerant corn and soybeans were used throughout the study providing good weed

control while minimizing chance of off target injury.

Brown stem rot was observed to be prevalent at this site. During 2010, the entire study was

planted to soybeans. Main plots were split between Asgrow AG 2107 and related AG2108

varieties, the latter brown stem rot resistant.

Insect weed and disease control practices are presented in Table 4.

 

 

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Figure 2. Experimental design (Rotations and management levels) for high yield studies at Lamberton, 2004-2010.

 

 

 

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Table 1. Tillage information. High yield studies at Lamberton, 2004-2010.

Treatment Fall 2005 Spring 2006 Fall 2006 Spring 2007

1 MB Plow Field Cultivator MB Plow Field Cultivator 2 Soil Saver Field Cultivator MB Plow Field Cultivator3 Soil Saver Field Cultivator V-Rip Field Cultivator4 Soil Saver Field Cultivator V-Rip Field Cultivator5 MB Plow Field Cultivator MB Plow Field Cultivator6 Soil Saver Field Cultivator MB Plow Field Cultivator7 Soil Saver Field Cultivator MB Plow Field Cultivator8 MB Plow Field Cultivator V-Rip Field Cultivator

Treatment Fall 2007 Spring 2008 Fall 2008 Spring 2009

1 MB Plow Field Cultivator MB Plow Disk Field cultivator2 In-Line Rip Field Cultivator In-Line Rip Disk Field cultivator3 In-Line Rip Field Cultivator In-Line Rip Disk Field cultivator4 In-Line Rip Field Cultivator In-Line Rip Disk Field cultivator5 MB Plow Field Cultivator MB Plow Disk Field cultivator6 MB Plow Field Cultivator In-Line Rip Disk Field cultivator7 In-Line Rip Field Cultivator In-Line Rip Disk Field cultivator8 MB Plow Field Cultivator In-Line Rip Disk Field cultivator

Treatment Fall 2009 Spring 2010

1 In-line Rip Field cultivator 2X2 In-line Rip Field cultivator 2X3 In-line Rip Field cultivator 2X4 In-line Rip Field cultivator 2X5 In-line Rip Field cultivator 2X6 In-line Rip Field cultivator 2X7 In-line Rip Field cultivator 2X8 In-line Rip Field cultivator 2X

 

 

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Table 2. Soil fertility information. Plant food applied expressed in pounds plant food/acre. Manure values estimated from % values of manure analysis.

Fertilizer applied (# plant food /acre)

Fall 2003 Spring 20004 Fall 2004 Spring 2005Broadcast Broadcast #/acre 28%

Treatment Urea as dry beef manure Dry Starter (2x2) Broadcast Sidedress (28%)

1 170 9-23-15-1(Zn) 170# Anhydrous 18-46-0-0-0(S) -8(Zn) 2 170 9-23-15-1(Zn) 18-46-0-0-0(S) -8(Zn) 3 170 9-23-15-1(Zn) 18-46-0-0-0(S) -8(Zn) 4 135# Anhydrous 18-46-0-0-0(S) -8(Zn) 5 85 47-41-41 9-23-15-1(Zn) 135# Anhydrous 38-50-50-25(S)-8(Zn) 40-0-06 85 47-41-41 9-23-15-1(Zn) 38-50-50-25(S)-8(Zn)7 85 47-41-41 9-23-15-1(Zn) 38-50-50-25(S)-8(Zn)8 47-41-41 135# Anhydrous 38-50-50-25(S)-8(Zn) 40-0-0

Fall 2005 Spring 2006Broadcast Broadcast #/acre 10 -34 -0 Gypsum 28%

Treatment Urea as dry beef manure pop-up Broadcast sidedress

1 170 0-0-0-23S / 0-0-0-02 135 0-0-0-23S / 0-0-0-03 135 0-0-0-23S / 0-0-0-04 0-0-0-23S / 0-0-0-05 135 35-32-29 5 -17-0-0-0 0-0-0-23S / 0-0-0-0 40-0-06 135 35-32-29 5 -17-0-0-0 0-0-0-23S / 0-0-0-0 40-0-07 135 35-32-29 5 -17-0-0-0 0-0-0-23S / 0-0-0-0 40-0-08 35-32-29 0-0-0-23S / 0-0-0-0

Fall 2006 Spring 2007Broadcast 10 -34 -0 28% N/28% N + ATS

Treatment Urea pop-up sidedress

1 none 170 12-0-0-28S/13-0-0-02 none 170 12-0-0-28S/13-0-0-03 none4 none 130 12-0-0-28S/13-0-0-05 none 170 5-17-0-0-0 40-0-0-28S/40-0-0-06 none 170 5-17-0-0-0 40-0-0-28S/40-0-0-07 none8 none 130 5 -17-0-0-0 40-0-0-28S/40-0-0-0

Fall 2007 Spring 2008#/acre Broadcast 10 -34 -0 28% N/28% N + ATS

Treatment as dry beef manure Urea pop-up sidedress

1 170-0-0 13-0-0-28S/14-0-0-023 130-0-0 13-0-0-28S/14-0-0-045 25-16-17 170-0-0 5- 17 - 0 40-0-0-28S/40-0-06 25-16-177 25-16-17 130-0-0 5 - 17 - 0 40-0-0-28S/40-0-08 25-16-17

Fall 2008 Spring 2009 Fall 2009 Spring 2010Broadcast 10 -34 -0 28% N + ATS

Treatment Urea + K20 pop-up sidedress

1 none 180-0-90 13-0-0-28S/13-0-0-0 none none2 none 130-0-90 13-0-0-28S/13-0-0-0 none none3 none 0-0-90 none none4 none 130-0-90 130-0-0-28S/13-0-0-0 none none5 none 180-0-90 6-20-0-0-0 40-0-0-28S/40-0-0-0 none none6 none 130-0-90 6-20-0-0-0 40-0-0-28S/40-0-0-0 none none7 none 0-0-90 none none8 none 130-0-90 6-20-0-0-0 40-0-0-28S/40-0-0-0 none none

 

 

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Table 3. Variety and planting information. High yield studies at Lamberton, 2004-2010.

Variety and Planting information

2004 2005 2006Treatment Hybrid/variety Planting date Seeding rate Hybrid/variety Planting date Seeding rate Hybrid/variety Planting date Seeding rate

1 DKC 5020 4/30/2004 33,000 DKC 52-47 4/30/2005 34,000 DKC 51-39 5/9/2006 34,0002 DKC 5020 4/30/2004 33,000 AG2107* 5/31/2005 168,000 DKC 51-39 5/9/2006 34,0003 DKC 5020 4/30/2004 33,000 AG2107* 5/31/2005 168,000 DKC 51-39 5/9/2006 34,0004 CropPlan RC2020* 5/5/2004 185,000 DKC 52-47 4/30/2005 34,000 AG2107* 5/23/2006 168,0005 DKC 5020 4/30/2004 38,000 DKC 52-47 4/30/2005 38,000 DKC 51-39 5/9/2006 38,0006 DKC 5020 4/30/2004 38,000 AG2107* 5/31/2005 168,000 DKC 51-39 5/9/2006 38,0007 DKC 5020 4/30/2004 38,000 AG2107* 5/31/2005 168,000 DKC 51-39 5/9/2006 38,0008 CropPlan RC2020* 5/5/2004 185,000 ** DKC 52-47 4/30/2005 38,000 AG2107* 5/23/2006 168,000

2007 2008 2009Treatment Hybrid/variety Planting date Seeding rate Hybrid/variety Planting date Seeding rate Hybrid/variety Planting date Seeding rate

1 DKC 52-40 5/12/2007 34,000 PIO 37N16 5/20/2008 34,000 PIO 35F44 5/4/2009 34,0002 DKC 52-40 5/12/2007 34,000 AG2002 5/22/2008 167,000 PIO 35F44 5/4/2009 34,0003 AG2107 5/12/2007 167,000 PIO 37N16 5/20/2008 34,000 CropPlan2257RR 5/11/2009 170,0004 DKC 52-40 5/16/2007 34,000 AG2002 5/22/2008 167,000 PIO 35F44 5/4/2009 34,0005 DKC 52-40 5/12/2007 38,000 PIO 37N16 5/20/2008 38,000 PIO 35F44 5/4/2009 38,0006 DKC 52-40 5/12/2007 38,000 AG2002 5/22/2008 167,000 PIO 35F44 5/4/2009 38,0007 DKC 52-40 5/12/2007 167,000 PIO 37N16 5/20/2008 38,000 CropPlan2257RR 5/11/2009 170,000**8 AG2107 5/16/2007 38,000 AG2002 5/22/2008 167,000 PIO 35F44 5/4/2009 38,000

2010Treatment Hybrid/variety Planting date Seeding rate

1 AG2107&AG2108 5/18/20010 167,0002 AG2107&AG2108 5/18/20010 167,0003 AG2107&AG2108 5/18/20010 167,0004 AG2107&AG2108 5/18/20010 167,0005 AG2107&AG2108 5/18/20010 167,0006 AG2107&AG2108 5/18/20010 167,0007 AG2107&AG2108 5/18/20010 167,0008 AG2107&AG2108 5/18/20010 167,000

* split plot CruiserMaxx ** 15 inch rows

 

 

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Table 4. Weed, insect and disease control. High yield studies at Lamberton 2004-2009. Aztec insecticide rate is expressed in oz/1000 row ft. All other rates expressed as product /acre.

 

Insect weed and disease control

2004 2005Herbicide Insecticide/ Fungicide Herbicide Insecticide/Fungicide

Corn PRE 5/08 Dual II Magnum 2 pts T-BAND 4/30 Aztec 7 oz/1000 ft POST 6/09 Round-up WeatherMax 22 fl oz T-BAND 4/30 Aztec 6oz/1000 ftPOST 6/22 Round-up WeatherMax 22 fl oz POST 7/05 Round-up WeatherMax 22 fl oz

Soybean PRE 5/08 Dual II Magnum 2 pts SEED 5/5 Cruiser Maxx 1/2 plot POST 6/09 Round-up WeatherMax 22 fl oz SEED 5/31 Cruiser Maxx 1/2 plotPOST 6/22 Round-up WeatherMax 22 fl oz POST 7/05 Round-up WeatherMax 22 fl oz POST 7/29 Warrior 3 fl oz

2006 2007Herbicide Insecticide/Fungicide Herbicide Insecticide/Fungicide

Corn POST 6/13 Round-up WeatherMax 22 fl oz PRE 5/12 Dual II Magnum 2.25 ptsPOST 6/13 Touchdown 24 fl oz

Soybean POST 6/13 Round-up WeatherMax 22 fl oz POST 7/28 Warrior 3 fl oz PRE 5/12 Dual II Magnum 2.25 pts POST 8/16 chlorpyrifos 1 ptPOST 7/5 Mirage 32 fl oz POST 6/13 Touchdown 24 fl oz

2008 2009Herbicide Insecticide/ Fungicide Herbicide Insecticide/Fungicide

Corn PPI 5/19 Outlook 1.3 pt PPI 5/02 Outlook 1.2 ptPOST 6/25 Cornerstone Plus 32 oz POST 6/11 Cornerstone Plus 24 fl oz

Soybean PPI 5/19 Outlook 1.3 pt POST 7/29 Warior 3 fl oz PPI 5/02 Outlook 1.2 pt POST 8/12 Tundra 5 fl ozPOST 6/25 Cornerstone Plus 32 oz POST 7/7 Cornerstone Plus 24 ozPOST 7/16 Cornerstone Plus 32 oz POST 7/22 Cornerstone Plus 32 oz

2010Herbicide Insecticide/ Fungicide

Corn

Soybean PPI 5/03 Outlook 1.2 pt POST 7/29 Tundra 5 fl ozPOST 6/17 Cornerstone Plus 32 oz, Fusilade 3 lf ozPOST 7/22 Cornerstone Plus 32 oz

 

 

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Data collected

Yields were obtained with small plot combines and adjusted to 15.5% moisture for corn and

13% moisture for soybean. Stand counts and crop growth and plant pest notes obtained

several times each year.

Soil samples for plant nutrients were collected in the fall of 2003, 2004, 2005, 2007 and 2010.

Twenty soil cores 0-6 inches deep were taken from each split-plot using a hand probe and

analyzed for nutrients. Soil samples to four-foot depth were obtained from each main plot with a

hydraulic probe during the fall of 2009. These were analyzed for nitrate nitrogen to examine the

long-term effects of rotation and management on nitrogen.

Most southern Minnesota crop producers understand the potential impact of soybean cyst

nematode (SCN) on soybean yields. Marketing from the crop protection chemical industry had

generated many grower questions about yield impacts from nematodes parasitic on corn roots.

To supplement other research dedicated to nematodes attacking corn, this study was used to

opportunistically search for treatment effects on nematode populations. Plots were sampled for

plant parasitic nematode and pathogen populations in the spring of 2009. The 0-6 inch soil

samples for nematodes were taken after seedbed preparation but before planting. Plant

parasitic nematodes were extracted at the University of Minnesota Plant Disease Clinic, St.

Paul, MN and nematodes counted by Dr. David MacDonald, University of Minnesota

Department of Plant Pathology. Soybean cyst nematode eggs were extracted from soil and

counted by the University of Minnesota Nematology Lab, Waseca, MN.

Twelve inch long samples of lower soybean stems were taken from each plot during fall 2010.

Stems were split and length of internal stem lesions from brown stem rot measured by Dr. Dean

Malvick, University of Minnesota Department of Plant Pathology.

Data were analyzed using Statistix 9 ©, Analytical Software, Tallahassee, FL 32317.

Results and discussion

Weather effects on yield

Weather is an obvious driver of crop yield. The 2004, 2008 and 2009 growing seasons were

cooler than normal; accumulating 2268, 2407 and 2331 growing degree days (GDD base

 

 

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50/86o F) respectively. The long-term historical average at this location is 2530 GDD. The

years 2005, 2006, 2007 and 2010 were slightly above average but only slightly so (Figure 3).

The study site has a long-term average growing season (May 1-Sepember 30) precipitation of

17.2 inches. Cumulative growing season precipitation was below average in 2007, 2008 and

2009.

Early season seed bed condition and planting date had an obvious impact on yield, corn in

particular, during the period of this study. Corn planting dates before May 5th resulted in higher

corn yields in the 2004, 2005 and 2009 season. Conversely, low yields were obtained in 2008

with a late planting date of May 20th. Soybean yields in 2005 and 2009 were high and were very

low in 2008, presumed related, in part, to planting date (Figure 6).

Inadequate tile drainage in the study area exacerbated delayed planting problems. Additionally,

early season wet soils reduced root and shoot growth in portions of some plots, particularly the

centers of plots and the northern two replications.

The 2004 and 2006 growing seasons were marked by heavy rainfall events in late May and

early June. 2005 was wet most of the first half of the growing season (Figure 4). Periods of wet

soil can be inferred from Figure 4 and Figure 5.

Early season growing conditions were excellent for the 2007 crop with excellent yield potential

until August. Unfortunately, soil moisture became limiting during the reproductive stages of both

corn and soybeans. Late season rains were too late to maintain yield on corn. Drought stress

on the high biomass, intensive management corn is suspected to be the reason for the poor

non-rotated intensive management corn yields, the only case where this treatment yielded less

than its common practices counterpart.

The late planting in 2008 has been discussed. The cool, dry 2008 combined with less than

optimum seedbeds impacted the yields of both corn and soybeans.

Corn and soybean yields in 2009 were very good. An October 9th frost killed corn before black

layer. As a result, test weights were low (51 lbs) and yields limited by lack of maturity. These

plots were harvested at very high moisture and combining losses are likely to have limited yield

as well. Moisture differences by treatment were not observed. The good 2009 yields are not

 

 

Page | 17 

easily explainable by growing season GDDs or rainfall alone. However, the 2009 season did

start with early planting and good seedbed conditions.

Planting was delayed in 2010 and was characterized by two heavy rain events in September.

The 2010 soybean crop yielded remarkably well considering the late planting and wet pre-

harvest weather conditions. Corn was not planted in 2010.

Yield is the result of a combination of many genetic and environmental factors and their

interactions. Dry land corn and soybean producers have little direct control on environmental

effects other than modifying soil temperature and excess moisture with tillage and tile drainage.

As previously mentioned, inadequate drainage produced obvious stress symptoms at this site in

some years. Unfortunately, this study was not designed to directly measure weather

interactions with crop growth rates or pests.

Figure 3. 2004 - 2010 and historic growing degree day accumulations base 50o F. University of Minnesota Southwest Research and Outreach Center, Lamberton, MN.

0

500

1000

1500

2000

2500

3000

5/1 6/1 7/1 8/1 9/1

Cum

ulat

ive

Gro

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g D

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ays

(bas

e 50

o F

)

day of year

2004

2005

2006

2007

2008

2009

2010

Historic GDD

 

 

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Figure 4. Cumulative growing season (May-September) precipitation. University of Minnesota Southwest Research and Outreach Center, Lamberton, MN (2004-2010 and historic).

0

5

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20

25

30

5/1 6/1 7/1 8/1 9/1

cum

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day of year

2004

2005

2006

2007

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Historic

 

 

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Figure 5. Growing season soil moistures 2004-2010. University of Minnesota Southwest Research and Outreach Center, Lamberton, MN. Total inches of water available in the top five feet of the soil profile. Soil core samples were taken near the 1st and 15th of the month.

2004 2005 2006 2007 2008 2009 2010 historical

4/15 4.48 7.08 7.11 6.81 6.45 6.34 7.63 6.04

5/1 4.39 6.66 8.29 6.87 8.44 6.82 6.45 6.56

5/15 4.36 8.26 7.52 7.22 8.27 7.22 6.66 6.5

6/1 6.42 7.97 6.61 6.62 6.95 6.39 5.87 6.82

6/15 6.94 7.48 6.65 6.73 7.26 7.6 6.7 6.68

7/1 6.6 6.28 6.26 5.43 6.05 6.33 6.5 6.14

7/15 6.77 5.92 4.98 3.19 4.84 5.6 4.74 5.22

8/1 4.78 4.35 4.26 3.17 4.21 4.48 5.44 4.66

8/15 5.06 3.6 5.32 2.58 4.45 3.96 5.02 4.32

9/1 5.73 2.95 5.18 5.05 4.21 3.72 4.71 3.96

9/15 6.65 5.41 3.92 4.58 4.34 4.11 6.18 4.26

10/1 7.25 6.43 5.06 3.62 3.32 5.19 6.92 4.38

0

1

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4

5

6

7

8

9in

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of

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Figure 6. Corn and Soybean yields under two management systems (2004-2009).

100

110

120

130

140

150

160

170

180

190

200

210

220

230

2004 2005 2006 2007 2008 2009

bu

shel

s / a

cre

Year

Effect of management practice and rotation on corn yield

High yield continuous corn Common practices continuous corn

High yield rotated corn Common practices rotated corn

Drought stress

54.3

64.3

59.9

51.5

31.3

51.9

59.2

67.1

61.4

59.3

31.3

65.9

20

25

30

35

40

45

50

55

60

65

70

2004 2005 2006 2007 2008 2009

Bu

shel

s / a

cre

Year

Effect of two management systems* on soybean yield

Common practices High yield

* across tillage , rotation and disease control practices

 

 

Page | 21 

Management and rotation effect on yield

Corn

Based on previous research, it was assumed that within reason, higher corn populations would

increase yield. 38,000 seeds per acre were planted in the intensive management plots. Other

research, conducted at the same time as this study, indicated that rates might have been

increased further without limiting yield but hybrids do not respond identically to plant population.

A somewhat conservative approach to seeding rates was used because the study design did

now allow multiple hybrids. Even so, the low yields in 2007 intensive managed continuous corn

may be due in part to moisture stress from high interplant competition.

Cropping year, management system and crop rotation influenced yield. There were significant

interactions between these three factors from 2005-2009 (Table 5). Yields were highest (over

206 bushels/acre) in 2005 and 2009, lower in 2006 (175 bushels), still lower in 2007 (164

bushels) and lowest in 2008 (129.8 bushels). This likely reflects adverse growing conditions

rather than other biological factors. Several weather related reasons (temperature, rainfall and

planting date) for yield in a given season have been previously discussed while others (solar

radiation, evapo-transpiration for example) have not. The data from this study only reinforce a

growing season’s significant, over-riding influence on yield.

Averaged across the period of the study, intensively managed corn significantly out-yielded the

common practices 183.9 to 168.8 bushels, an 8% average. The exception was the 2007 when

the intensively managed corn averaged 5 bushels less than common practices, still, however,

statistically equivalent. These differences were significantly higher in 2005, 2006, 2008 and

numerically higher in 2009. Unfortunately, the relative contribution of individual components of

the high yield system, nitrogen rate or placement, for example, cannot be evaluated with this

method.

Rotated corn out-yielded continuous corn by an average 181.1 bushels to 171.6 bushels, over

the same 2005-2009 period. Rotated corn out-yielded continuous corn except in 2009 when top

end yields were likely limited by an early frost and in 2008 when yields were suppressed;

rotated and non-rotated corn yields were equivalent in these cases.

Corn yields by year, management practice and crop rotation are presented in Table 6.

 

 

Page | 22 

All combinations of the corn-corn-soybean rotation were not present each year and are not

included in the previous or subsequent rotation analyses. This was a flaw in the experimental

design necessitated by limited space. An additional three treatments would have been required

to completely balance the every third year soybean rotation. This would have required an

additional 75% land area if room to include split plots was maintained. Nonetheless, some

information on this rotation could be gleaned. When they occurred in the corn-corn soybean

rotation, corn yields after soybean mirrored corn in the corn-soybean rotation and the second

year of corn mirrored continuous corn plots.

The role of sulfur in corn yields

Although counter to the experimental design, sulfur treatments were applied as a query, before

yield responses on these soil types were well documented. The results indicate this was a

fortuitous rule violation.

Sulfur was first applied to intensive managed corn plots in the spring of 2005 as elemental

sulfur. No yield response was oberved in the fall corn or soybean crop and the form of sulfur

broadcast was changed to Gypsum (CaSO4) in 2006. A corn, but not soybean, yield response

was observed. Sulfur applications were changed to a side-dress band of ammonium thiosulfate

to corn in 2007-2009. An analysis of varience of corn yields from 2006-2009 including previous

sulfur application is shown in Table 7. While the sulfur treatment may have increased yields

(p= 0.0861), yields were reduced numerically in 2006 (year * sulfur interaction).

Removing the non-responding 2006 gypsum application year from the analysis revealed a

highly signicant sulfur on yield (p=0.0145) but the effect changed with mangement system and

rotation (Table 8). The year, management and rotation effects and interactions were not

changed. Yields by sulfur application, management and rotation are presented in Table 9.

Sulfur significantly increased corn yields, 170 bushels/acre compared to 163.4 bushels, across

management system and rotations in 2007- 2009. However, the relationship between yield and

sulfur was numerically inverted in the common practices continuous corn treatments. These

yield differences within a management and rotation were not significant at the 5% level.

Nonetheless, a potential for a yield depressive effect of sulfur in a lower yield environment is

curious but perhaps explainable.

 

 

Page | 23 

Sulfur was always applied to same ½ plots and it cannot determined whether these sulfur

responses represent a transient or long-term effect . These data suggest 20 pounds/acre of

sulfur side-dressed as ammonium thio-sulfate can improve corn yield. Questions on optimal

sulfur rate, formulation and application method for corn yield responses are not answered. An

unfortunate shortcoming of this, and all long-term research plot design, is the inability to add

many additional treatments to answer questions as they arise. Land requirements and

statistical analysis complications get in the way.

Table 5. Factorial ANOVA for management system, two crop rotations and year (2005-2009) on corn yields.

Factor pmanagement 0.0000 ***rotation 0.0000 ***year 0.0000 ***management * rotation 0.0000 ***management * year 0.0000 ***rotation * year 0.0133 **management * rotation * year 0.0509 **

 

 

Page | 24 

Table 6. Mean corn yield by management system, rotation and year on corn yields (2005-2009). Means followed by the same letter are not different (Tukey’s HSD alpha=0.05).

Year Management Corn rotation Bushels/acre

2005 Intensive soybean‐corn 228.5 a

2005 Intensive  non‐rotated 202.0 bc

2005 Common  non‐rotated 199.2 bc

2005 Common soybean‐corn 196.5 bcd

2006 Intensive soybean‐corn 195.1 bcd

2006 Intensive  non‐rotated 181.1 cde

2006 Common soybean‐corn 168.1 ef

2006 Common  non‐rotated 155.9 fg

2007 Intensive soybean‐corn 177.9 de

2007 Intensive  non‐rotated 144.3 gh

2007 Common soybean‐corn 171.0 ef

2007 Common  non‐rotated 162.9 efg

2008 Intensive soybean‐corn 151.3 fgh

2008 Intensive  non‐rotated 128.9 hi

2008 Common soybean‐corn 118.1 i

2008 Common  non‐rotated 120.9 i

2009 Intensive  non‐rotated 215.0 ab

2009 Intensive soybean‐corn 214.8 ab

2009 Common  non‐rotated 206.2 abc

2009 Common soybean‐corn 189.4 bcde

 

 

Page | 25 

Table 7. Factorial ANOVA for rotation, management system and sulfur application effect on corn yields (2006-2009).

 

Table 8. Factorial ANOVA for, management system, rotation and sulfur application effect on corn yields (2007-2009). These are sidedress ammonium thiosulfate data only.

Factor pmanagement 0.0000 ***rotation 0.0001 ***year 0.0000 ***sulfur 0.0861 *management * rotation 0.0002 ***management * year 0.0000 ***management * sulfur 0.5543rotation * year 0.0014 ***rotation * sulfur 0.3721year * sulfur 0.0268 **management * rotation * year 0.0576 *management * rotation * sulfur 0.1245management * year * sulfur 0.3529rotation * year * sulfur 0.6397management * rotation * year * sulfur 0.3645

Treatment pmanagement 0.0001 ***rotation 0.0060 ***year 0.0000 ***sulfur 0.0145 **management * rotation 0.0000 ***management * year 0.0000 ***management * sulfur 0.2399rotation * year 0.0002 ***rotation * sulfur 0.2830year * sulfur 0.3900management * rotation * year 0.7889management * rotation * sulfur 0.0495 **management * year * sulfur 0.5902rotation * year * sulfur 0.3833management * rotation * year * sulfur 0.9179

 

 

Page | 26 

Table 9. Management system, rotation and sulfur application effect on corn yields (2007-2009). Means followed by the same letter are not different (Tukey’s HSD alpha=0.05).

Soybean After the 2006 season, soybeans were not managed directly for high yield. Seed-applied

insecticides and fungicides had not produced a yield response or eliminated the need for foliar

insecticide treatments in 2004-2006. Elemental sulfur and Gypsum applications did not

produce a yield response in 2005 or 2006 respectively. Additionally, corn sulfur applications

were switched to post-emerge, side-dress, incompatible with soybean production, in 2007.

Direct sulfur applications were not made to soybeans after 2006.

Soybean yields in the corn-corn-soybean rotation only occurred in 2005 and 2008. These yields

were not different than in those from the corn-soybean rotation same years. These plots and

rotation were not included in the following analyses as variable.

With the exception of 2008, soybean yields were somewhat more stable than those of corn but

followed a similar annual pattern (Table 11). Soybean yields were highest in 2005 and lowest in

2008. The next highest yields in were obtained in 2006 and 2009. Penultimate yields were

obtained in 2007 and 2004.

Intensively managed soybeans yielded more than common practices, 57.3 bushels/acre and

52.2 bushels/acre respectively. However, in 2008 both management systems yielded similar

(Table 10, 12). The extreme uniformity of low 2008 soybean yields plot to plot may be a result

of a harvesting equipment problem.

Management Corn rotation Sulfur Bushels/acreIntensive soybean-corn yes 184.7 aIntensive soybean-corn no 178.0 abIntensive non-rotated yes 169.1 abcIntensive non-rotated no 156.4 ccommon soybean-corn yes 165.0 bccommon soybean-corn no 154.0 ccommon non-rotated yes 161.3 ccommon non-rotated no 165.4 bc

 

 

Page | 27 

.

Table 10. Factorial ANOVA for managemnent system effect on soybean yields (2004-2009).

Table 11. Mean soybean yields by year. High yield study. Lamberton, MN 2004-2009. Means followed by the same letter are not different (Tukey’s HSD alpha=0.05).

Table 12. Year and management system effect on soybean yields (2004-2009). Means followed by the same letter are not different (Tukey’s HSD alpha=0.05).

The role of sulfur in soybean yields

Sulfur effects on soybean are less clear than those on corn. The suspect 2008 yields are were

excluded from the analyses of sulfur effects on yield.

Factor pyear 0.0000***management 0.0000***year * management 0.0004***

Year Bushels2004 56.7 cd2005 65.7 a2006 60.6 b2007 55.4 d2008 31.3 e2009 58.9 bc

Yield Year Management Bushels/acre2004 intensive 59.2 cd

2004 common 54.3 de

2005 intensive 67.1 a

2005 common 64.3 abc

2006 intensive 61.4 abc

2006 common 59.9 bcd

2007 intensive 59.3 cd

2007 common 51.5 e

2008 intensive 31.3 f

2008 common 31.3 f

2009 intensive 65.9 ab

2009 common 51.9 e

 

 

Page | 28 

Soybean yields form 2006, 2007 and 2009 were affected by year and management but previous

sulfur applications did not have not significant effect on soybean yields overall (Table 13). Year

and management effects on soybean yield were discussed previously.

When examining soybean yield responses by individual year, sulfur increased soybean yield

only in 2009. Previous sulfur application increased yield ( p=0.0806) in intensive management

soybeans by 6.5 bushels (69.5 bushels/acre compared to 63.0 bushels/acre). Previous sulfur

application did not affect yield in the lower yielding common practices management where

soybean yielded 51.4 bushels/acre and 52.3 bushels/acre with and without previous sulfur

respectively.

The transient 2009 response to sulfur in the intensively managed soybeans begs more detailed

investigation. Sulfur is a mobile nutrient and it is possible that the response may be related to

corn stover quantity or quality. It may also relate to less easily identified changes in soil

biological processes.

Similar to corn, sulfur numerically increased yield in the intensively management soybean but

decreased yield in common practices (Table 14). Strict statistical interpretation would indicate

these non- significant differences should be ignored. The same phenomonenon occurring in

corn indicates that additional research may be valuable.

These yield data contain manure applications in intensive management but cannot answer

questions on crop response to manure compared to other plant nutrient forms.

Table 13. Factorial ANOVA for rotation, management and sulfur application effect on soybean yields (2006-2009).

Factor pyear 0.0356 **

management 0.0045 ***

previous sulfur 0.9752management * sulfur 0.0495 **

manage* year 0.5569year* sulfur 0.5664year* management* sulfur 0.1662

 

 

Page | 29 

Table 14. Management system and previous sulfur application effect on soybean yields (2006,2007 and 2009). Means followed by the same letter are not different (Tukey’s HSD alpha=0.05).

Long term management and rotation effect on soybean yield

All plots were planted to soybean in the 2010 season. This provided intervals between soybean

crops of 0, 1, and 7 years. Unfortunately, the corn-corn-soybean rotation ended as a single

corn crop between soybean crops. The 2010 soybean yields were analyzed separately

because corn was not included and more than one variety was assessed (Table 15).

Similar to results obtained in previous years, management and rotation were highly significant

and affected soybean yields (Table 16). Soybeans in intensive management yielded more than

those under the common practices regimen, 61.9 bushels to 56.2 bushels/acre respectively.

Soybeans after seven years of corn had significantly higher yield (66.4 bushels/acre) than other

rotations. The corn - soybean rotation ending with consecutive soybean crops yielded

significantly less (53.0 bushels/acre) than all other rotations. The corn-soybean and corn-corn-

soybean (soybean-corn soybean from 2008-2010) rotations had intermediate and similar yields

of 58.1 and 59.4 bushels/acre respectively. One less soybean crop in the corn-corn- soybean

rotation over the period of the study did not significantly increase yield over the soybean–corn-

soybean rotations in this study.

In all rotations, intensive management soybeans numerically out-yielded their common practices

counterparts; significantly so with the single exception of the long-term continuous corn (Table

16). Perhaps, soil fertility was minimizing or compensating for the impact of disease in shorter

rotations. Compensation for reduced water and nutrient transport from root or vascular

pathogens immediately come to mind. Alternatively, higher soil fertility could be reducing

disease infection. For example, other research has correlated low pH and low soil potassium

levels with increased brown stem rot (Phialophora gregata) severity. It should be noted that

YieldManagement Previous sulfur bushels/acre

intensive yes 64.5 aintensive no 60.2 abcommon yes 53.6 bcommon no 58.0 ab

 

 

Page | 30 

this site did not have a history of chronic low yield caused by disease or nematodes. These

data suggest several additional research studies to better understand this relationship.

Varieties yield differently (p < 0.10) but differences were affected by crop rotation. In spite of

Brown stem rot susceptibility, AG2107 had been a consistently high yielding variety for the area.

Asgrow AG2107 yielded 58.7 bushels/acre and Asgrow AG2108, the brown stem rot resistant

variety 59.8 bushels/acre. These differences may be due to the brown stem rot pathogen but

differences within rotation, and presumed disease severity, were not observed (Table 17).

These two varieties are sister lines with AG 2108 a later selection and perhaps with higher yield

potential.

When crop rotation effect on disease severity and yield are examined, part of the yield puzzle is

explained (Table 18). Brown stem rot severity declines in relation to the frequency and timing

of soybean crops. Soybeans after 7 years of corn had significantly shorter stem pith symptoms

than other rotations. The rotation with soybeans after soybeans had the longest stem

symptoms. Yields generally followed disease severity. Yield differences for the corn-corn-

soybean rotation and corn-soybean-rotation were not observed but the former had less brown

stem rot severity. This may indicate that the rotation effect is due to more than a single

pathogen, a most probable scenario.

Soybean health differences by management and rotation were easily observed at soybean

maturity. The short rotation, common practices plots were shortest and most advanced and the

continuous corn, intensive managed plots tallest and least mature.

Sulfur significantly reduced yield in the low yielding corn-soybean-soybean rotation. Sulfur

produced slight non-significant yield increases in other rotations (Table 19). This re-enforces

other observations of sulfur induced yield reductions in lower yield situations.

 

 

Page | 31 

 

Table 15. The effect of management, rotation interval, previous sulfur applications, and implied BSR resistance (variety) on 2010 soybean yield. Factorial analysis of variance (ANOVA).

Table 16. The effect of crop rotation and corn management on 2010 soybean yields. Means followed by the same letter are not different (Tukey’s alpha = 0.10).

Factor pmanagement 0.0000 ***rotation 0.0000 ***previous sulfur 0.1123variety 0.0561 *management * rotation 0.0016 ***management * previous sulfur 0.4435management * variety 0.5092rotation * previous sulfur 0.0977 *rotation* variety 0.0784 *previous sulfur * variety 0.1524management * rotation * previous sulfur 0.7575management * rotation * variety 0.7094rotation * previous sulfur * variety 0.3562management * rotation * previous sulfur * variety 0.5209

Corn Management Rotation Bushels /acreIntensive C-C-C-C-C-C-C-S 67.9 aCommon practices C-C-C-C-C-C-C-S 65.0 abIntensive C-C-S-C-C-S-C-S 62.1 bCommon practices C-C-S-C-C-S-C-S 56.8 cIntensive C-S-C-S-C-S-C-S 62.6 bCommon practices C-S-C-S-C-S-C-S 53.6 cdIntensive C-C-S-C-S-C-S-S 54.9 cCommon practices C-C-S-C-S-C-S-S 51.1 d

 

 

Page | 32 

.

Table 17. Rotation * brown stem rot resistance interaction. Influence on soybean yield. High yield study. Lamberton, MN 2010. Means followed by the same letter are not different (Tukey’s HSD alpha=0.10).

Table 18. The effect of soybean planting interval (rotation) on Brown Stem Rot (BSR) severity and soybean yield. High yield study. Lamberton, MN 2010. Means followed by the same letter are not different (Tukey’s HSD alpha=0.10).

Table 19. Rotation * sulfur interaction. Residual sulfur influence on soybean yield. High yield study. Lamberton, MN 2010. Means followed by the same letter are not different (Tukey’s alpha=0.10).

Variety w/ BSR YieldRotation resistance Bushels /acreC-C-C-C-C-C-C-S Yes 67.7 aC-C-C-C-C-C-C-S No 65.2 aC-C-S-C-C-S-C-S Yes 59.7 bC-C-S-C-C-S-C-S No 59.1 bC-S-C-S-C-S-C-S Yes 57.5 bcC-S-C-S-C-S-C-S No 58.7 bC-C-S-C-S-C-S-S Yes 54.3 cdC-C-S-C-S-C-S-S No 51.7 d

% stem length YieldRotation w/ BSR symptoms (bushels/acre)C-C-S-C-S-C-S-S 55.3 a 53.0 cC-S-C-S-C-S-C-S 41.9 b 58.1 bC-C-S-C-C-S-C-S 20.9 c 59.4 bC-C-C-C-C-C-C-S 6.1 d 66.4 a

Sulfur applied to YieldRotation previous corn Bushels /acreC-C-C-C-C-C-C-S Yes 67.5 aC-C-C-C-C-C-C-S No 65.4 aC-C-S-C-C-S-C-S Yes 59.8 bC-C-S-C-C-S-C-S No 59.1 bC-S-C-S-C-S-C-S Yes 59.3 bC-S-C-S-C-S-C-S No 56.9 bcC-C-S-C-S-C-S-S Yes (none in 2009) 52.3 eC-C-S-C-S-C-S-S No 53.7 cd

 

 

Page | 33 

The effect of management and rotation on biotic factors.

Plant parasitic nematode population assessment

Nematodes from the genera Pratylenchus, Helicotylenchus, Heterodera (eggs only) and

Xiphenema were observed in spring 2009 soil samples collected from this study. Continuous

corn plots had been in place for five years. The population densities of nematodes parasitic on

corn observed in this study were unlikely to cause yield loss.

Only Helicotylenchus (spiral) populations were affected by treatments in this study (Table 20).

Spiral nematodes were lowest in the high management system (Table 21). The difference

could be related to a manure history in these plots or another unknown biological factor

changed by management. Spiral nematodes at very high populations can cause yield loss in

some horticultural crops. They were least abundant in the continuous corn rotation and

populations increased by number and timing of soybean in the rotation (Table 22).

Pratylenchus (Lesion) nematodes were the most abundant. They are common corn parasitic

nematodes in fine textured soils and hurt yield when populations are high. Although numerically

slightly higher in plots where corn was grown in 2008, significant differences by crop rotation

history were not observed.

Xiphenema (dagger) nematodes were present but occurred in only a few plots but at very low

populations. Dagger nematodes are known to cause corn yield loss at high population densities

and are the most aggressive corn parasitic nematode genera sampled.

This study provides evidence that continuous corn is not at universal risk to yield reducing

populations of corn parasitic nematodes.

Soybean cyst nematode (SCN) egg populations ranged from 0 to 258 eggs/100 cc. These are

barely detectable populations of SCN. Population densities had not changed over the period of

the study. Management strategy or crop rotation did not affect SCN egg populations during the

study duration.

 

 

Page | 34 

Table 20. The effect of management system and rotation on plant parasitic nematodes. Factorial analysis of variance (ANOVA) p values.

Table 21. Management system effect on plant parasitic nematodes, spring 2009. Means followed by the same letter are not different (Tukey HSD alpha = 0.10).

Table 22. Rotation effect on plant parasitic nematodes, spring 2009. Means followed by the same letter are not different (Tukey HSD alpha = 0.10).

Other Biological observations

Late season corn diseases, common rust (Puccinia zea) and eyespot (Kabetiella zea) were

present in this study. Both became prevalent on the ear leaf and above during late dough stage

in 2009 but were present at very low levels other years. Stalk rot(s) were not prevalent during

any year although Fusarium stalk rots did reduce yield in nearby fields during 2007.

Soybean root necrosis from aerobic conditions and root diseases, primarily Fusarium spp.,

occurred after occasional periods of flooded soils. This root injury was related to landscape

position and drainage tile placement, not to rotation or fertility regime. Root regeneration

prevented mortality and stand losses were not detected in any of these events.

Brown stem rot was the most prevalent above ground soybean disease at this location and has

been previously discussed. Pod and stem blight (Diaporthae), and anthracnose

(Colletotrichum), were present at senescence all years. Bacterial blight (Psuedomonas), brown

Factor lesion dagger spiral SCN (eggs)management 0.2593 0.2593 0.0050 *** 0.7684rotation 0.3584 0.3584 0.0658 * 0.6081

Management lesion dagger spiral SCN (eggs)intensive management 32.2 a 0.4 a 22.5 b 101.7 acommon practices 38.2 a 3.1 a 67.2 a 85.3 a

Rotation lesion dagger spiral SCN (eggs)C-C-C-C-C-C 52.8 a 0.8 a 14.5 b 107.9 aC-C-S-C-C-S 27.5 a 5.5 a 39.5 ab 76.8 aC-C-S-C-S -C 39.5 a 0.0 a 55.1 ab 44.0 aC-S-C-S-C-S 21.1 a 0.8 a 70.4 a 145.4 a

 

 

Page | 35 

spot (Septoria) and downy mildew (Peronospora) were additional soybean diseases present at

low levels during the period of the study.

While a foliar fungicide comparison would have been interesting and perhaps valuable, foliar

fungicides were not applied to either crop for three reasons. First, contemporary research did

not show significant or predictable yield improvement from foliar fungicides and one of the initial

premises of this study was to include yield-enhancing parameters as they were documented to

be effective. Secondly, the incidence and severity of diseases controllable by fungicides were

low. Finally, plot size prevented an additional split within existing plots and degrees of freedom

issues would have prevented accurate analysis of potential interactions, both not uncommon,

particularly long-term research designs.

Bird cherry-oat, Rhopalosiphum padi, while present at unusually high populations below the ear

leaf in 2007 corn, were not considered to be yield limiting. Two-spotted spider mite,

Tetranychus urticae, infestations were observed but remained very low in the canopy.

Soybean aphid, Aphis glycines, reached economic threshold in this study in all years except

2004 and were well controlled with a single foliar application of insecticide. The selection of

insecticides with miticidal properties in 2007 and 2009 prevented yield loss from either pest.

Northern corn rootworm, Diabrotica barberi, was the predominant rootworm species. Beetle

populations were very low during the study period never approaching 0.10 beetles /plant.

Cursory root examinations in continuous and rotated corn revealed less than 0.10 nodes pruned

before Bt-RW hybrids were used and much less after. The low corn rootworm pressure did not

warrant more intensive adult or root sampling in any rotation or management.

Management and rotation effect on soil test levels

As expected, the 2010 topsoil samples taken at the end of study showed differences in nutrients

and pH by management and rotation (Table 23).

Higher levels of phosphorus, potassium, zinc and nitrate and pH occurred in the intensive

management treatments and correlates the additional plant nutrients applied (Table 24).

 

 

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Rotation 3 (C-C-S-C-S-C-S-S), was higher in phosphorus, potassium and zinc than Rotation 4

(C-S-C-S-C-S-C-S). The magnitude of these differences was not large and the cause unclear.

Possible explanations include: sampling variability from previous manure applications,

differences in nutrient uptake with the 2009 or previous crop and/or an interaction between

nutrients.

In both management systems, topsoil phosphorus levels were higher in continuous corn and the

biennial soybean rotations (Table 24). This correlates to nutrients applied.

Topsoil samples for sulfur availability are notoriously inaccurate for predicting yield response to

a sulfur application. In this case, we are simply measuring residual sulfur. Topsoil sulfur was

affected by management and highest under intensive management. Equivalent applications of

sulfur were made to both management systems. The exception was an initial application to

intensive management plots in the spring of 2005. The difference could be due to the initial 25

pounds of sulfur, possible even for a nutrient mobile with water through the soil profile, or the

manure history. However, corn was responding to side-dress sulfur applications in both

management systems. This leads to hypotheses that low rates of sulfur will not produce

optimum yields or that sulfur cycling within crop residue may be one of the drivers of yield

responses.

With a single exception, previous sulfur application did not affect or interact with nutrient levels,

including sulfur. This was not unexpected due to the mobile nature of sulfates in the soil. The

exception was a management * rotation * previous sulfur interaction on residual topsoil nitrogen.

This statistical interaction did not impact mean separations.

Zinc levels remained adequate after a broadcast application in 2005 (Figure 7). Both

phosphorus and potassium soil levels declined over time in common practices (Figure 9, Figure

8). Broadcast superphosphate or K20 were applied when this occurred.

These data show that soil test values can decline relatively quickly even when it is supposed

that adequate fertilizer rates are being used. Phosphorus levels did increase in intensive

management but not at an unmanageable rate. Management of rented ground for high yields

based on high soil fertility is often problematic, particularly on rented land.

 

 

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Table 23. Factorial analysis of variance (ANOVA) p values for pH and soil nutrients. 0-6” samples, fall 2010.

  

Table 24. Soil test pH and nutrient (PPM) means for management, rotation and interactions. 0-6” samples fall 2010. Means followed by the same letter are not different (Tukey HSD alpha = 0.05).

Factor pH P (Bray) K Zn N03 SManagement 0.0020 *** 0.0000 *** 0.0000 *** 0.0000 *** 0.0000 *** 0.0638 *Rotation 0.0070 *** 0.0630 * 0.0122 ** 0.0070 *** 0.0210 ** 0.2128Previous Sulfur 0.9004 0.8556 0.7176 0.8527 0.9480 0.4450Management * Rotation 0.8953 0.0197 ** 0.3128 0.9755 0.9682 0.0029 ***Management * Previous S 0.2631 0.8556 0.4704 0.9179 0.1387 0.9593Rotation * Previous S 0.6067 0.5349 0.7658 0,4607 0.4555 0.8366Management * Rotation* Previous S 0.7044 0.5535 0.9716 0.8162 0.0528 * 0.1193

Variable pH P (Bray) K Zn NO3 SManagementIntensive 6.0 a 44.8 a 241.5 a 2.5 a 11.8 a 8.7Common 5.9 b 23.1 b 179.4 b 1.3 b 9.3 b 7.5Rotation (2003-2010)CCCCCCCS 5.8 b 35.4 205.4 b 1.7 b 9.8 bCCSCCSCS 6.1 a 32.8 206.7 b 2.0 ab 10.6 abCCSCSCSS 6.0 ab 40.4 238.2 a 2.3 a 11.8 aCSCSCSCS 5.9 ab 27.1 191.5 b 1.6 b 10.0 bManagement * Rotation Intensive CCCCCCCS 43.4 ab 9.0 abcIntensive CCSCCSCS 40.1 bc 8.1 abcIntensive CCSCSCSS 60.6 a 10.4 aIntensive CSCSCSCS 32.9 bc 7.1 abcCommon CCCCCCCS 25.4 bc 6.3 cCommon CCSCCSCS 25.4 bc 6.7 bcCommon CCSCSCSS 20.1 c 7.3 abcCommon CSCSCSCS 21.4 c 10.1 abc

 

 

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Figure 7. Zinc levels (ppm) from fall 0-6 inch soil samples 2003-2010. Individual plots tested below 1 ppm zinc and 8 lbs/acre broadcast zinc was applied to all plots in spring 2005 to minimize variability from this nutrient.

Figure 8. Potassium levels (ppm) from fall 0-6 inch soil samples (2003-2010). Soil test levels were declining particularly within individual in common practices plots and 90 lbs./acre broadcast K was applied to all plots spring 2009.

0.0

0.5

1.0

1.5

2.0

2.5

3.0

2003 2004 2005 2006 2007 2008 2009 2010

Zin

c P

PM

Common practices Intensive management

0

50

100

150

200

250

300

2003 2004 2005 2006 2007 2008 2009 2010

Po

tass

ium

PP

M

Common practices Intensive management

 

 

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Figure 9. Phosphorus levels (ppm) from fall 0-6 inch soil samples. (2003-2010).

Effect of management and rotation on residual nitrate levels

Residual nitrates were sampled to a 48-inch depth after the 2009 harvest. Nitrate levels were higher in the intensive management. Residual levels were higher in continuous corn, intermediate in the corn-corn-soybean rotation and lowest after first year corn. Residual nitrates were much lower after soybeans (Figure10). Significant amounts of N were below the two foot depth. Nitrate nitrogen as a percentage of total nitrate N was similar for all treatments when partitioned by depth within the soil profile. The percentage contributed by unassimilated nitrogen fertilizer/ manure and from mineralization of crop residue is unknown. Available residual deep nitrogen later in the season may be a way that soybean are responding with higher yields to the intensive management system, particularly in dry years. Scavenging nitrogen may provide benefits in a corn/soybean system may provide benefits in addition to improving soybean yields. These data suggest that continuous corn production may not be as nitrogen-demanding as many corn producers believe. It is an intriguing possibility that nitrogen rates might be adjusted downward with longer-term corn rotations. This simple management practice would reduce the cost of continuous corn production while maintaining yield and minimizing any potential perceived environmental impacts from nitrogen fertilizers. The partitioning of NO3 within the profiles suggests soil sampling of continuous corn may useful in predicting N rate changes.

0

10

20

30

40

50

60

2003 2004 2005 2006 2007 2008 2009 2010

Pho

spho

rus

PP

MCommon practices Intensive management

 

 

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Figure 10. The effect of management and crop rotation on residual soil nitrogen. High yield studies, fall 2009. Lamberton, MN.

Objective I. Summary/conclusions

This study, imperfect as it is, reinforces the relationships between management input variables.

Weather is a primary driver for corn and soybean yields as it affects planting date and

subsequent crop development. Drainage, soil fertility and variety selection are tools

producers can use to reduce but not eliminate the impact of weather.

While not a specific part of this study, it should be noted that field-specific variety

selection remains important to obtaining consistently high yields. The interaction of crop

genetics with environment, field characteristics and pest pressure is second only to

weather as a yield driver.

This study suggests that additional yield may be obtained by adjusting crop rotations and

thereby allowing greater flexibility in variety selection.

 

 

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“Intensive management” has highest yields for both crops. Higher fertility and higher

corn plant populations do seem to improve yield of both crops.

Corn in a C-SB rotation has higher yield than continuous corn (5% in this study). A yield

decline occurs in second year corn but yields do not continue to decline with consecutive

corn crops. Management increases corn yield but does not remove the penalty for non-

rotation.

Soybean yields increase with reduced soybean frequency in the rotation. In this study,

brown stem rot severity was reduced with increased interval between soybean crops.

This study had relatively few pathogen problems reducing yield. The rate of yield

improvement for each year of non-soybean should not be expected to be the same for

all fields.

Continuous corn is not at universal risk to pest problems. In this study, a detectable

increase in corn disease, rootworm or plant parasitic nematodes were not observed,

even after seven years of corn.

This study indicates that in cropping systems containing both corn and soybean, neither

continuous corn nor an annual rotation between corn and soybean rotation will produce

optimum yields for both crops. Soybeans benefit from increased rotational interval and

corn yields increase after a soybean crop. Adding a second year of corn in the rotation

did not increase soybean yields but this may not reflect the situation after addition cycles

of a corn-corn- soybean rotation.

Fields under continuous corn production may develop disease or insects problems that

cause corn yields to decline. Goss’s blight and wilt and Bt-RW resistant western corn

rootworms are recent Minnesota examples. While they can be partially managed with

hybrid selection and in the case of rootworm, pesticides; a single year rotation out of

corn can eliminate or minimize problems from a field. This provides producers with

maximum flexibility, particularly in selecting hybrids for yield and other agronomic

factors. Prolonging the effective life of pesticides and genes for host plant resistance to

pests has long and short-term benefits in simplified and economical crop management.

 

 

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The same rotation is not likely to be optimal for all fields and all producers’ needs. An

infrequent soybean crop may be best for one producer’s field, one may be best with

several corn crops between soybeans and another may be fine in a long-term corn-

soybean rotation. This study provides support to the value of crop-rotation. Creative use

of rotation can produce optimum per acre yields of carbohydrates and protein and

effectively create a “third crop” within a corn-soybean rotation.

Yield of intensively management continuous corn is similar is to common practices corn-

soybean rotation but less than intensively managed corn-soybean. However, greater

early vegetative growth in a high yield situation can produce a situation where drought

stress is magnified, particularly in continuous corn.

Increased bean yields in high yield systems can be essentially “free”. Both crops need

to be accounted for in a soil fertility program. The former seems often assume and the

latter easily ignored in tight economies or on rented ground.

Phosphorus and potassium levels declined in common practices management.

Producers need to provide adequate fertilizer inputs to maintain (or increase) soil test

levels. Do not assume a fertilizer recommendation is adequate for all fields or portion

thereof.

This study documents responses to sulfur on fine textured, high organic matter glacial till

soils. Side-dress applications of sulfur (ammonium thiosulfate) produced a consistent

yield response in corn. During 2007 and 2008 both management systems showed a

response and in 2009 response was limited to the intensive management system.

Soybeans responded to sulfur as an indirect (previous crop) application in 2009.

This study suggests that sulfur may decrease corn and soybean yields in some low yield

situations. Response to sulfur might be related to quantity and quality of residue or

interactions with other nutrients, this study suggests a limiting factor.

 

 

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Nitrates accumulated through the profile with subsequent corn crops. Nitrogen rates

might be adjusted downward with nitrate soil tests. Nitrates were reduced when soybean

crops were grown.

Studies of this type may have several shortcomings. Large plots are required to provide

buffer space for soil, residue, nutrients and biotic factors between plots over years. For

better or worse, plots are fixed as soon as a rotational, tillage or soil fertility treatment is

applied. The number of comparisons that can be made is limited because of space and

statistical limitations. Multiple tillage comparisons are particularly prone to problems with

plot and equipment size and speed. The results of treatments applied to individual plots

are prone to drift over time.

This type of study does have advantages. It provides an opportunity for a treatment to

work through the system over time. In other words, yield effects might not be seen for

several years and the effects of a treatment may compound over time. Hypothetically, a

high yield environment develops over time. If new practices are added to the study there

should be some reason (data) to suggest they enhance yield. Multiple simultaneous

additions are acceptable if they have basis in research. Conversely, superimposing

treatments for exploratory purposes may provide useful information but they can

permanently disrupt plot integrity. This study suffered from this affliction.

Future needs

As typical, this study suggests additional research questions. A few examples follow:

• Is the sulfur response related to wet/dry or cool/warm weather during the growing season?

• What rate(s) and application method(s) of sulfur is optimum.

• Does a sulfur application provide a single season response or can long-term benefits occur.

• Would fall N or higher sub-soil levels of other nutrients have improved corn yields in dry conditions?

• Can N rates be reduced in continuous corn with mimimal risk.

 

 

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• How far can tillage be reduced in a high yield system (residue management)?

• How would improved drainage change results?

• Which pest problems are best managed by rotation and high fertility.

• Can rotation eliminate Bt-RW resistant western corn rootworm from a field or geographic area.

• What are economic impacts?

Objective II

Initiate new long-term yield trials at multiple locations in Minnesota

Unfortunately, little progress has been made on this objective. Cooperators can be identified

with relative ease but valid and consistent guidelines for cooperators are critical and difficult to

define. For example, since the conclusion of this study, researchers at the University of

Minnesota Research and Outreach Centers have expended considerable effort in developing a

common protocol for implementation of long-term agricultural research at these sites. They

have been less than completely successful, highlighting the difficulties in establishing long- term

multivariate studies.

As mentioned in the summary of Objective I, there are several problems in establishing a long

term research plot. It is difficult to design trials that do not confound the analysis of variables

that were unplanned at the onset but become important to understanding results. Results can

be hard to publish, reducing participation by academic researchers.

The size of production agriculture machinery severely limit the number of accurate comparisons

possible in a producer managed experiment. Conversely, farm scale equipment operates at a

scale and speed incompatible with use in small plots. The dilemma is frustrating to both

producer and academic researchers. Physics indicates that the speed, weight and pass

width/wheel traffic used by farmers could give different outcomes. Mathematics and geography

indicate that strip trials across soil types, and pest populations might show differences that are

due to factors other than those studied.

The economy dictates how long a trial dealing with rotation can be maintained; this is especially

true of producer’s fields but also hinders long term work on University fields. Nonetheless, the

 

 

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University of Minnesota Research and Outreach Centers are best situated to host a

comprehensive long-term study on yield increases over time.

Individual producers benefit from high yields and should participate in validating research.

Based on numerous conversations with producers, participation will follow the development of a

clean protocol.

This method was intended to add a single variable at a time. This would simplify

implementation, particularly for producer researchers, as experiments evolved over time.

Remember that both current management and intensive would be evolving over time. The

difficulty is... which variable? Management skills and yield constraints or fields fall across a

wide continuum.

A possible framework is briefly outlined in Objective III. It is not incompatible with techniques

demonstrated and described under Objective I.

Objective III

Create framework to identify input components for high yield production

Hybrid selection, seeding rate, N, P, K, Zn, S fertilizer rate and in-row residue management are

important components that need to be included in small plot and on-farm comparisons on yield.

Some researchers have included individual components of yield, seeding rates and individual

nutrients for example, in on-farm experiments. These data are valuable. A cropping system

often responds to a single management input but by its very nature the system cannot respond

to that variable to the exclusion of others. In other words, it is easier to identify individual

elements that may improve yield than understand how they fit into a high yield system.

Since 2009, new problems affecting corn and soybean growers have developed. These have

been mentioned previously and include Goss’s blight and wilt, western corn rootworms resistant

to Bt, two-spotted spider mites resistant to chlorpyrifos, and weeds resistant to multiple

herbicide modes of action. These pests, if studied as individual components, can quickly

change agronomic research from yield enhancement to yield maintenance. Studies on

Individual components of pesticide or variety selection are needed and provide basic efficacy

information. Real efficacy and yield/economic benefit can only be determined after the

 

 

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component is examined with crop rotation, nutrient and drainage management and overall yield

potential.

What may be most helpful is a series of experiments that adventurous growers can apply to

their own farms. These could also apply to small plot studies superimposed on treatments in

grower’s fields and serve as a benchmark for applied agronomic research. The difficulties of

doing meaningful research on tillage and other mechanical based management in small plots

can be overcome. Interactions can be studied if small plots can be placed within plots

implemented with equipment used on the scale it was created for. This does require good

cooperation between all parties to avoid drift issues and any premature combining phenomena.

These experiments need to be formulated along a progression of management for example

water management, soil fertility, crop rotation planting date and row spacing, variety selection,

pest management (including all of these). Ideally, fact sheets or other educational materials

would be developed as part of this.

Researchers can also choose from research questions along this progression as high yield

systems are developed. To be blunt, it makes little sense to increase seeding or fertilizer rates

if a field drowns out on a regular basis. Other producers may only need to improve application

timings or variety selection. To be effectively developed, this series of experiment will need

considerable input from multiple disciplines. Frankly, obtaining this input has been one of the

impediments to the process.

On the other hand, producers and others in ag industry often see yield responses before

researchers understand the mechanism. Examples include yield increases from insecticides on

Bt-RW corn, sulfur responses on high organic matter soils, declining phosphorus soil tests.

Again these can be evaluated with field scale experiments, small plots within field scale strips,

or highly structured small plot research.

Committees already exist to determine research priorities. It would be relatively simple to use

these provide lists of those proposed and funded research that have produced yield positive

results for inclusion in the high yield system.

Positive, accurate (yield increasing) results, regardless of how they were initiated (academic,

industry, and producer) can then be incorporated into the long-term high yield locations and

menu of on-farm experiments for further validation.

 

 

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Acknowlegements This research was funded by: Minnesota Soybean Research and Promotion Council Minnesota Corn Research and Promotion Council Several researchers and Extension specialists have provide suggestions over the course on this project: Jeff Coulter, Dale Hicks and Seth Naeve, U of M Agronomy and Plant Genetics; Dan Kaiser, John Lamb and George Rehm, U of M Soil, Water and Climate; Dean Malvick, U of M Plant Pathology, Kent Olson, U of M applied economics. Numerous producers and other ag professionals provided much appreciated input, both solicited and volunteered input. Mark Colter, Jeff Irbeck, Lee Klossner and Steve Quiring and 6 years worth of student interns provided the work for this project at the

 

 

 

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Appendix I. Figures.

Figure 1. Plot diagram of the high yield study area showing initial (2003) soil test values.

.......................................................................................................................................................6

Figure 2. Experimental design (Rotations and management levels) for high yield studies at Lamberton, 2004-2010. .............................................................................................................10

Figure 3. 2004 - 2010 and historic growing degree day accumulations base 50o F. University of Minnesota Southwest Research and Outreach Center, Lamberton, MN....................................17 Figure 4. Cumulative growing season (May-September) precipitation. University of Minnesota Southwest Research and Outreach Center, Lamberton, MN (2004-2010 and historic).............18 Figure 5. Growing season soil moistures 2004-2010, University of Minnesota Southwest Research and Outreach Center, Lamberton, MN. Total inches of water available in the top five feet of the soil profile...................................................................................................................19 Figure 6. Corn and Soybean yields under two management systems (2004-2009..................20

Figure 7. Zinc levels (ppm) from fall 0-6 inch soil samples 2003-2010. High yield study, Lamberton, MN. Individual plots tested below 1 ppm zinc and 8 lbs/acre broadcast zinc was applied to all plots in spring 2005 to minimize variability from this nutrient.................................38

Figure 8. Potassium levels (ppm) from fall 0-6 inch soil samples 2003-2010. Soil test levels were declining particularly within individual in common practices plots and 90 lbs./acre broadcast K was applied to all plots spring 2009.......................................................................38

Figure 9. Phosphorus levels (ppm) from fall 0-6 inch soil samples. High yield study, Lamberton, MN. 2003 - 2010......................................................................................................39

Figure 10. The effect of management and crop rotation on residual soil nitrogen. High yield studies fall 2009, Lamberton, MN................................................................................................40

 

 

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Appendix II. Tables

Table 1. Tillage information. High yield studies. Lamberton, MN 2004 2010...........................11

Table 2. Soil fertility information. Plant food applied expressed in pounds plant food/acre......12

Table 3. Variety and planting information (2004-2010)............................................................ 13

Table 4. Weed, insect and disease control. Aztec rate expressed in oz/1000 row ft. All other rates expressed as product /acre................................................................................................14

Table 5. Factorial ANOVA for management system, two crop rotations and year (2005-2009) .....................................................................................................................................................23

Table 6. Means corn yields by management system, rotation and year on corn yields (2005-2009).......................................................................................................................................... 24

Table 8. Factorial ANOVA for, management system, rotation and sulfur application effect on corn yields (2007-2009).............................................................................................................. 25

Table 9. Management system, rotation and sulfur application effect on corn yields (2007-2009)...........................................................................................................................................26

Table 10. Factorial ANOVA for managemnent system effect on soybean yields (2004-2009). 27

Table 11. Mean soybean yields by year (2004-2009)................................................................27

Table 12. Year and management system effect on soybean yields (2004-2009).....................27

Table 13. Factorial ANOVA for rotation, management and sulfur application effect on soybean yields (2006-2009)...................................................................................................................... 29

Table 14. Management system and previous sulfur application effect on soybean yields (2006,2007 and 2009)................................................................................................................ 29

Table 15. The effect of management, rotation interval, previous sulfur applications, and implied BSR resistance (variety) on 2010 soybean yield. Factorial analysis of variance (ANOVA........ 31

Table 16. The effect of crop rotation and corn management on 2010 soybean yields............. 31

Table 17. Rotation*brown stem rot resistance interaction. Influence on soybean yield 2010.. 32

Table 18. The effect of soybean planting interval (rotation) on Brown Stem Rot (BSR) severity and soybean yield. 2010..............................................................................................................32

Table 19. Rotation * sulfur interaction. Residual sulfur influence on soybean yield. 2010.......32

Table 20. The effect of management system and rotation on plant parasitic nematodes. Factorial analysis of variance (ANOVA) p values.......................................................................34

 

 

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Table 21. Management system effect on plant parasitic nematodes, spring 2009.................. 34

Table 22. Rotation effect on plant parasitic nematodes, spring 2009.......................................34

Table 23. Factorial analysis of variance (ANOVA) p values for pH and soil nutrients. 0-6” samples, fall 2010........................................................................................................................37

Table 24. Soil test pH and nutrient (PPM) means for management, rotation and interactions. 0-6” samples, fall 2010............................................................................................................... 37