Monsanto Company Petitions 10-188-01p/12-185-01p_a1 Page 1 of 65

Supplemental Information to Support the NEPA Analysis for the Determination of 

Nonregulated Status of Dicamba-Tolerant Soybean MON 87708 and Dicamba- and 

Glufosinate-Tolerant Cotton MON 88701 

Information regarding trends in tillage practices in corn, cotton and soybean 

OECD Unique Identifiers: MON-877Ø8-9 (soybean) and MON-887Ø1-3 (cotton)

Monsanto Petition Numbers: 10-SY-210U (soybean) and 12-CT-244U/ 12-CT-244U-S (cotton)

USDA Petition Numbers: 10-188-01p (soybean) and 12-185-01p_a1 (cotton)

December 19, 2013

Submitted by:

Rhonda M. Mannion, B.S.

Monsanto Company

800 North Lindbergh Blvd.

St. Louis, MO 63167

Phone: (314) 694-8785

Fax: (314) 694-3080

E-mail: rhonda.m.mannion@monsanto.com

Prepared by:

J.K. Soteres, Ph.D. and R.M. Mannion, B.S.
Release of Information 

Monsanto is submitting the infOlmation in this petition for review by the USDA as part of the 

regulatory process. By submitting this infOlmation, Monsanto does not authorize its release to 

any third party. In the event the USDA receives a Freedom of Information Act request, pursuant 

to 5 U.S.C. § 552, and 7 CFR Part 1, covering all or some of this infOlmation, Monsanto expects 

that, in advance of the release of the document(s), USDA will provide Monsanto with a copy of 

the material proposed to be released and the 0ppOliunity to object to the release of any 

infOlmation based on appropriate legal grounds, e.g., responsiveness, confidentiality, and/or 

competitive concerns. Monsanto understands that a copy of this information may be made 

available to the public in a reading room and upon individual request as part of a public comment 

period. Except in accordance with the foregoing, Monsanto does not authorize the release, 

publication or other distribution of this infOlmation (including website posting) without 

Monsanto's prior notice and consent. 

Certification 

The undersigned submits this supplement under 7 CFR §340.6 to request that the Administrator 

make a determination that the miicle should not be regulated under 7 CFR Pmi 340 

Rhonda Mannion, B. S. 

Regulatory Affairs Manager 

Tel: (314) 694-8785 

Fax: (314) 694-8414 

©2013 Monsanto Company. All Rights Reserved. 

This document is protected under copyright law. This document is for use only by the regulatory 

authority to which it has been submitted by Monsanto Company and only in support of actions 

requested by Monsanto Company. Any other use of this material, without prior written consent 

of Monsanto, is strictly prohibited. By submitting this document, Monsanto does not grant any 

party or entity any right to use or license the information or intellectual propeliy described in this 

document. 

Monsanto Company Petitions 10-188-01 p/12-185-0 1 P _ al Page 2 of65 
Monsanto Company Petitions 10-188-01p/12-185-01p_a1 Page 3 of 65

Introduction

Recently there have been speculation and in some cases, reports, that the growth of conservation 

tillage acres and, in particular, no-till acres has slowed or is reversing in some parts of the 

country. Accordingly, Monsanto undertook an analysis of grower market research information

from an independent market research company and follow up consultation with leading 

conservation tillage experts to understand more precisely current tillage trends and reasons for 

these trends in key soybean, corn and cotton growing areas.

Multiple factors could influence conservation tillage practices. Growth in the spread of 

glyphosate-resistant weed populations has been speculated or reported to be one such factor, 

because of the need for some farmers to incorporate more tillage into their farming operations in 

order to control some difficult to control weed species, such as Palmer amaranth. For example, 

where populations of glyphosate-resistant Palmer amaranth have grown large in areas such as 

Georgia, western Tennessee, and Arkansas, weed control experts recommend deep pre-plant 

tillage as one way to reduce the population before other weed control measures are applied 

(Culpepper, et al. 2013; Culpepper, et al. 2011; Price, et al. 2011). However, growers and 

leading conservation experts themselves report a range of factors other than weed management 

that can and do influence farmer practices relative to conservation tillage practices.

Materials and Methods

This analysis used market research data from an unpublished national grower survey conducted 

by a third party market research company. The data retrieved from this database included the 

number of crop acres planted conventionally, in a no-till system, or in a reduced tillage system. 

No-till acres are defined as those in which the farmer does not till the ground after the harvest of 

the last crop and before planting a new crop. Reduced tillage (reduced-till) is defined as 

situations where the farmer practices various types of reduced tillage after harvest of the last crop 

and before planting the new crop where significant crop residues (~15%-30%) are left on the soil 

surface. Examples of reduced tillage practices include ridge-till (planting row crops on 

permanent ridges), strip-till (planting crops directly in narrow strips that had been tilled), and 

mulch-till (any reduced tillage system that leaves at least 1/3 of soil surface covered with crop 

residue). Conventional tillage (conventional) is defined as situations where the farmer conducts 

several tillage operations such that the new crop is planted into soil with little to no surface 

residue.

The farmer market research data was sorted by crop (soybeans, cotton, and corn) and state. 

Selected states were combined into growing regions (East, Midwest, Southeast, Mid-South, and 

West, as indicated in Table 1). Data was retrieved for the period from 1998 through 2013 for 

soybeans and corn, and through 2012 for cotton (Note: 2013 cotton data from the market 

research company is not currently available). The estimated acreage of each tillage type for each 

crop and growing region was converted to percent of total crop planted acreage and submitted 

for statistical regression analysis over the designated time period. The data was analyzed to fit a 

linear or quadratic regression model at the 5% level of significance. Details of the statistical 

analysis are provided in the statistical report found in Appendix A.
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To understand possible reasons for some of the changes observed in this data set, Monsanto 

worked with CTIC (Conservation Tillage Information Center, www.ctic.org) to conduct a survey 

of leading conservation tillage experts in select Midwest, Southeastern and Mid-South. (Note: 

experts from these areas were surveyed because they represent the major regions for the 

production of soybean, corn and cotton, and because they represent the areas with the highest 

levels of herbicide resistant weeds). In this survey, the experts were asked to indicate the level 

of importance of 11 different factors to farmers as they make decisions as to which tillage system 

and in general how much tillage they will use on their farm(s). Examples of factors included 

“manage excess crop residue,” “manage existing weeds,” “manage disease,” “economics,” and 

“prevent weed resistance.” To rank the factors, a number from 1 to 4 was assigned to each

response category, with 1 assigned to “not important or not mentioned” and 4 assigned to 

“extremely important”. The experts were not limited in the number of factors to which they 

could assign an individual ranking. (i.e., the experts could rank all – or none – of the 11 factors 

as “extremely important”). The assigned number was multiplied by the number of responses 

from the experts and then added together for each factor. The factors with the 5 highest 

numerical sums are listed in Table 3 for each crop and region. The detailed results of this survey 

for corn, soybeans and cotton can be found in Appendix B.

Table 1. States in each Geographic Region

Region Crop Focus States

East Corn, soybean Connecticut, Delaware, Maine, Maryland, Massachusetts, 

New Hampshire, New Jersey, New York, Pennsylvania, 

Rhode Island, Vermont, West Virginia

Southeast Corn, cotton, 

soybean

Alabama, Georgia, S. Carolina, N. Carolina, Virginia, 

Florida

Mid-South Corn, cotton, 

soybean

Mississippi, Louisiana, Arkansas, Tennessee

Midwest Corn, cotton, 

soybean

Ohio, Michigan, Indiana, Illinois, Wisconsin, Missouri, 

Minnesota, Iowa, Kentucky, Kansas, Nebraska, N. Dakota, 

S. Dakota

West Corn, cotton, 

soybean

Arizona, California, New Mexico, Oklahoma, Texas, 

Colorado, Idaho, Montana, Nevada, Utah, Washington, 

Wyoming 

Results and Discussion

A summary of the results of the grower market research data analysis on tillage trends can be 

found in Table 2. Key points are as follows:

• From 1998 to 2007, the conventional tillage acreage decreased and no-till acres increased 

across all crops and geographic areas. Likewise, reduced tillage acres generally increased 

during this time period, although for some areas and crops, no significant relationship 
Monsanto Company Petitions 10-188-01p/12-185-01p_a1 Page 5 of 65

between the tillage practice and time could be detected. The growth in no-till and 

reduced tillage acres coincides with, and was facilitated by, the growth in glyphosatetolerant corn, soybean and cotton acres (Givens, et al. 2009a; Givens, et al. 2009b; 

McClelland, et al. 2000; Osteen and Fernandez-Cornejo 2013; Sankula 2006; Towery and 

Werblow 2010). 

• Since 2007, however, some crops in some geographic areas have continued to see growth 

in no-till acreage, while other crops in other geographic areas have seen decreases in notill acreage, accompanied by an increase in conventional and/or reduced tillage acreage. 

A more detailed, crop-by-crop discussion is presented below.

• Corn: From 1998 to 2007, the conventional tillage acreage decreased and no-till acres 

increased across all geographic areas. From 2007 through 2013, the trends varied across 

regions:

o In the West and East, conventional tilled corn acres continued to decrease, and 

no-till acreage continued to increase. Reduced tillage acres also increased in the 

West, but there was no clear trend in the East.

o In the Midwest, conventional tilled corn acres continued to decrease but there 

appeared to be a shift from strict no-till practices to reduced tillage acres where 

some tillage is practiced but significant (15% -30%) crop residues remain on the 

surface at planting. 

o In the Southeast, conventional tillage acres planted to corn tended to level off or 

increase while no-till acres tended to decrease.

o In the Mid-South, there were no significant trends in conventional or no-till 

acreage, but reduced till acres increased throughout the time period.

• Soybean: From 1998 to 2007, the conventional tillage acreage decreased and no-till 

acres increased across all geographic areas. From 2007-2013, the trends varied across 

region:

o In the West, conventional tilled soybean acres continued to decrease, and no-till 

acreage continued to increase. There was no significant trend for reduced tillage 

acres.

o In the East, Midwest, Southeast and Mid-South regions, conventional tilled 

soybean acres were flat or increasing, while no-till acres were flat or decreasing.

Reduced tillage acres in the Midwest increased during the same time period, but 

there was no clear relationship between time and reduced tillage plantings in the 

East, Southeast or Mid-South regions (not significant at the 95% confidence 

interval). Thus, in the Midwest, the reduction in no-till acres appears in large part 

to be offset by an increase in reduced tillage acres, but similar offsetting does not 

appear to be occurring in other regions.

• Cotton: From 1998 to 2007, the conventional tillage acreage decreased and no-till acres 

increased across all geographic areas. From 2007-2012, the trends varied across regions:
Monsanto Company Petitions 10-188-01p/12-185-01p_a1 Page 6 of 65

o In the West, conventional tilled soybean acres continued to decrease, and no-till 

acreage continued to increase. Reduced tillage acres also continued to increase.

o In the Midwest, Southeast and Mid-South, conventionally-tilled cotton acres 

tended to be flat or increase, while a clear increase was found in the Mid-South

region. Reduced tillage acres increased in the Midwest and Southeast during this 

period, but both no-till and reduced tillage acreages decreased in the Mid-South 

region. Thus, in the Midwest and Southeast, the reduction in no-till acres appears 

in large part to be offset by an increase in reduced tillage acres, but similar 

offsetting does not appear to be occurring in the Mid-South.

Overall, changes in tillage practices from 2007 to 2012 (cotton)/2013 (soybean and corn) varied 

by crop and region relative to changes seen in the earlier period from 1998 to 2006 where

consistent trends were observed across all the regions (i.e., increase in no-till and reduced tillage 

with a decrease in conventional tillage systems).

In order to understand the reasons growers adopt specific tillage practices, a survey was 

conducted of top conservation tillage experts across the Midwest (for corn and soybeans), 

Southeast and Mid-South regions (combined, for corn, soybeans, and cotton). In Table 3, the top 

5 factors, according to conservation tillage experts, governing farmer decisions relative to which 

tillage practice they adopt for their farm are provided by crop and region of the country. Key 

findings included:

• Economics (i.e., the importance of cost of production and/or commodity prices), and 

managing soil moisture (i.e., less tillage conserves soil moisture) were top-5 factors 

across all the crops and regions. 

• Seed bed preparation was a top-5 factor in 4 out of 5 crop x region segments.

• Managing excessive crop residue (i.e., excessive prior crop residue may require more 

tillage) and managing weeds (existing weeds or preventing weed resistance) were 

important factors in 3 out of 5 crop x region segments. 

• Managing weeds was an important factor across all soybean and cotton regional 

segments, but was not a top 5 factor for corn in either regional segment. The difference 

between corn and the other crops is likely because growers have a broad range of 

herbicide options (including atrazine, dicamba and 2,4-D) that are effective against 

species that are difficult to control in soybeans and cotton, i.e., glyphosate resistant 

Palmer amaranth and waterhemp.

This survey of conservation tillage experts highlights that farmers consider multiple factors when 

making decisions as to what type tillage system to employ.

Conclusions 

From 1998-2007, no-till acreage increased steadily across all crops and all regions, with an 

accompanying decrease in conventional tillage. A more complicated picture emerged after 2007, 

with some crops and regions continuing to experience increases in no-till and decreases in 

conventional tillage, while other crops and regions experienced decreases in no-till acreage, 

either accompanied by increases in reduced tillage acreage and/or in conventional tillage. 
Monsanto Company Petitions 10-188-01p/12-185-01p_a1 Page 7 of 65

Based upon information provided by conservation tillage experts regarding the most important 

factors governing farmer’s decisions with respect to tillage practices, no one factor is driving 

these changes. Managing existing herbicide resistance and/or mitigating the potential for 

resistance to develop is a factor is some regions. For example, academics have been 

recommending more pre-plant tillage in parts of the Southeast and Mid-South (AR, western TN, 

and MS) in order to better manage glyphosate-resistant Palmer amaranth. But weed resistance 

management/mitigation does not appear to be a driver for other crops and regions. Indeed, the 

survey results indicate that higher corn and soybean grain prices, along with more focus on seed 

bed preparation, is likely to be a reason for some of switch to conventional tillage since a better 

stand (and thus higher potential yields) can usually be achieved in conventional tillage systems. 

Moreover, newer corn varieties can produce excessive crop residue, which may also be causing a 

move to more tillage and may be needed to optimize crop stands in this period of high grain 

prices. 

Based upon the tillage trends seen over the last 5-6 years and with the information on the factors 

most influencing farmers’ decision on tillage practices, more study, appropriately directed 

research, education, and new technology from a weed management and crop production 

standpoint are needed to maintain and further grow conservation tillage practices. In some areas 

and for some crops, managing existing herbicide resistance and/or mitigating the potential for 

resistance to develop has been reported as an important factor in influencing farmer tillage 

decisions. DT soybean and DGT cotton are two new herbicide technologies that have the 

characteristics that can significantly assist in reversing stagnated and downward trends and 

promote new growth in conservation tillage acres. Weed management has always been a 

limiting factor for many farmers in determining whether to adopt no-till production practices 

because farmers had to rely primarily on soil residual herbicides. Glyphosate, in 

glyphosate-tolerant crops, with its broad spectrum post-emergence control provided a way to 

achieve consistent weed control in these situations and facilitated an increase in adoption of notill and, in general, conservation tillage practices (Fawcett and Towry, 2002). The effectiveness 

of dicamba to provide post-emergent control of broadleaf weeds, suggests that it too will 

promote adoption of no-till and conservation tillage practices. Additionally, dicamba’s ability to 

control glyphosate resistant broadleaf weeds and its compatibility with glyphosate are 

characteristics that will facilitate the promotion of conservation tillage practices. 
Monsanto Company Petitions 10-188-01p/12-185-01p_a1 Page 8 of 65

Table 2. Trends in Tillage Practices in Soybean, Corn and Cotton 

Crop Geography Tillage system Trend

1998-

2007

2007-

2012/13

Corn West Conventional Dec Dec

No-till Inc Inc

Reduced-till Inc Inc

Midwest Conventional Dec Dec

No-till Inc Flat/Dec1

Reduced-till Dec Inc

Southeast Conventional Dec Flat/Inc1

No-till Inc Dec

Reduced-till NS NS

Mid-South Conventional NS NS

No-till NS NS

Reduced-till Inc Inc

East Conventional Dec Dec

No-till Inc Inc

Reduced-till NS NS

Soybeans West Conventional Dec Dec

No-till Inc Inc

Reduced-till NS NS

Midwest Conventional Dec Flat/Inc1

No-till Inc Dec

Reduced-till Dec Inc

Southeast Conventional Dec Flat

No-till Inc Flat

Reduced-till NS NS

Mid-South Conventional Dec Inc

No-till Inc Dec

Reduced-till NS NS

East Conventional Dec Flat/Inc1

No-till Inc Flat/Dec1

Reduced-till NS NS
Monsanto Company Petitions 10-188-01p/12-185-01p_a1 Page 9 of 65

Table 2 (continued). Trends in Tillage Practices in Soybean, Corn and Cotton 

Crop Geography Tillage system Trend

1998-

2007

2007-

2012/13

Cotton West Conventional Dec Dec

No-till Inc Inc

Reduced-till Inc Inc

Southeast Conventional Dec Flat/Inc1

No-till Inc Dec

Reduced-till Inc Inc

Midwest Conventional Dec Flat/Inc1

No-till Inc Dec

Reduced-till Inc Inc

Mid-South Conventional Dec Inc

No-till Inc Dec

Reduced-till Inc Dec

NS=no significant trend at 5% Confidence Interval Inc= Increase 

Dec=decrease Flat=no change

Source of data is propriety grower market research data (Monsanto, 2013).

1

Where the trend is indicated as two phases (i.e. Flat/Dec), this means 

that statistically the trend is for no change over the designated time 

period but the slope over the last two years of the time period tended to 

be either reflective of an increase or a decrease. 

Table 3. Top 5 Factors Governing Farmer’s Tillage Practice Decisions

Factor Midwest

Corn

(14 Experts)

Midwest

Soybeans

(13 Experts)

South Corn

(6 Experts)

South 

Soybeans

(6 Experts)

South Cotton

(6 Experts)

1 Managing soil 

moisture

Excessive 

crop residue

Economics Economics Economics

2 Seed bed 

preparation

Seed bed 

preparation

Seed bed 

preparation

Managing 

existing 

weeds

Managing 

existing 

weeds

3 Economics Economics Excessive 

crop residue

Seed bed 

preparation

Availability 

of Labor

4 Excessive 

crop residue

Managing 

existing 

weeds

Improving 

water 

penetration

Managing soil 

moisture

Managing soil 

moisture

5 Managing soil 

temperature

Managing soil 

moisture

Managing soil 

moisture

Preventing 

weed 

resistance

Use of strip 

till / vertical 

tillage tools
Monsanto Company Petitions 10-188-01p/12-185-01p_a1 Page 10 of 65 

References: 

Culpepper, A.S., J. Kichler and A.C. York. 2013. University of Georgia programs for controlling 

Palmer amaranth in 2013 cotton. University of Georgia Cooperative Extension, Athens, Georgia. 

Culpepper, A.S., A.C. York and L.E. Steckel. 2011. Glyphosate-resistant Palmer amaranth 

management in cotton. 2011 Proceedings, Southern Weed Science Society, San Juan, Puerto 

Rico. 

Fawcett, R. and D. Towery. 2002. Conservation tillage and plant biotechnology: How new 

technologies can improve the environment by reducing the need to plow. Conservation 

Technology Information Center, Purdue, Indiana. 

Givens, W.A., D.R. Shaw, W.G. Johnson, S.C. Weller, B.G. Young, R.G. Wilson, M.D.K. Owen 

and D. Jordan. 2009a. A grower survey of herbicide use patterns in glyphosate-resistant cropping 

systems. Weed Technology 23:156-161. 

Givens, W.A., D.R. Shaw, G.R. Kruger, W.G. Johnson, S.C. Weller, B.G. Young, R.G. Wilson, 

M.D.K. Owen and D. Jordan. 2009b. Survey of tillage trends following the adoption of 

glyphosate-resistant crops. Weed Technology 23:150-155. 

McClelland, M.R., J.L. Barrentine, K.J. Bryant and E.P. Webster. 2000. Roundup Ready cotton 

programs in conservation tillage. Pages 197-201 in Proceedings of the 2000 Cotton Research 

Meeting, Fayetteville, Arkansas. 

Osteen, C.D. and J. Fernandez-Cornejo. 2013. Economic and policy issues of U.S. agricultural 

pesticide use trends. Pest Management Science 69:1001-1025. 

Price, A.J., K.S. Balkcom, S.A. Culpepper, J.A. Kelton, R.L. Nichols and H. Schomberg. 2011. 

Glyphosate-resistant Palmer amaranth: A threat to conservation tillage. Journal of Soil and Water 

Conservation 66:265-275. 

Sankula, S. 2006. Quantification of the impacts on US agriculture of biotechnology-derived 

crops planted in 2005. National Center for Food and Agricultural Policy, Washington, D.C. 

Towery, D. and S. Werblow. 2010. Facilitating conservation farming practices and enhancing 

environmental sustainability with agricultural biotechnology: Exective summary. Conservation 

Technology Information Center, West Lafayette, Indiana. 
Monsanto Company Petitions 10-188-01p/12-185-01p_a1 Page 11 of 65

Appendix A: Statistical Analysis of Tillage Market Research Data

Summary of Statistical Analysis of Tillage Data

Purpose 

Assess if tillage practices have significantly changed between 1998 and 2007, and between 2007 

and 2013 (or 2012, for cotton). 

Data Description

For the analysis PROC MEANS in SAS was used to calculate the acres that utilized each tillage 

type and total acres for each crop, region and year. The percent of total acres was calculated by 

dividing acres that utilized each tillage type by total acres.

Statistical Methods and Results

A quadratic regression model of the following form was fit for each crop, region and tillage type 

combination:

Percent of total acres = β0 + β1*Year + β2*Year* Year + ε (1)

in which β0 is the intercept, β1 is the linear slope, β2 is the quadratic slope and ε is the residual 

error. PROC MIXED in SAS was used to fit model (1) separately for each crop, region and 

tillage type combination. Tests were performed to determine if the quadratic slopes of the 

regression lines were significantly different from zero. These tests are displayed in Table 1. 

Twenty of the 42 tests observed quadratic slopes that were significantly different from zero at the 

5% level of significance. 

In the 20 cases where the quadratic slopes were significant, a quadratic regression model was 

deemed appropriate. For the 22 cases where the quadratic slopes were not significant, a linear 

regression model of the following form was fit for each crop, region and tillage type 

combination:

Percent of total acres = β0 + β1*Year + ε (2)

in which β0 is the intercept, β1 is the linear slope and ε is the residual error. PROC MIXED in 

SAS was used to fit model (2) separately for each crop, region and tillage type combination. 

Tests were performed to determine if the linear slopes of the regression lines were significantly 

different from zero. These tests are displayed in Table 2. Fourteen of the 22 tests observed 

linear slopes that were significantly different from zero at the 5% level of significance. 

In the 14 cases where the linear slopes were significant, a linear regression model was deemed 

appropriate. For the 8 cases where the linear slopes were not significant, there was no significant 

change in tillage practices over time.
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Conclusions

In 8 of the 42 crop, region and tillage type combinations there was no significant change over 

time. 

In 14 of the 42 crop, region and tillage type combinations the change over time can be described 

using a linear regression model. 

In 20 of the 42 crop, region and tillage type combinations the change over time can be described 

using a quadratic regression model. 

The regression parameter estimates for the crop and region combinations with a significant the 

change over time, are displayed in Table 3.

Plots of the percent total acres data and model fit are displayed in the Appendix.
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Table A-1. Tests to Determine if the Quadratic Slopes of the Regression Lines Were Significantly 

Different From Zero 

Crop Region Tillage_Type P-value

Corn East Conservation 0.1381

Corn East Conventional 0.6663

Corn East No-Till 0.1161

Corn MidSouth Conservation 0.5547

Corn MidSouth Conventional 0.1925

Corn MidSouth No-Till 0.0582

Corn MidWest Conservation 0.0218 *

Corn MidWest Conventional 0.5444

Corn MidWest No-Till 0.0015 *

Corn Southeast Conservation 0.1322

Corn Southeast Conventional 0.0038 *

Corn Southeast No-Till 0.0018 *

Corn West Conservation 0.9108

Corn West Conventional 0.2174

Corn West No-Till 0.1183

Cotton MidSouth Conservation 0.0018 *

Cotton MidSouth Conventional <.0001 *

Cotton MidSouth No-Till <.0001 *

Cotton MidWest Conservation 0.2096

Cotton MidWest Conventional 0.0017 *

Cotton MidWest No-Till <.0001 *

Cotton Southeast Conservation 0.7367

Cotton Southeast Conventional 0.0002 *

Cotton Southeast No-Till <.0001 *

Cotton West Conservation 0.0539

Cotton West Conventional 0.0582

Cotton West No-Till 0.8615

Soybeans East Conservation 0.4610

Soybeans East Conventional 0.0051 *
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Table A-1 (continued). Tests to Determine if the Quadratic Slopes of the Regression Lines 

Were Significantly Different From Zero 

Crop Region Tillage_Type P-value

Soybeans East No-Till 0.0017 *

Soybeans MidSouth Conservation 0.5038

Soybeans MidSouth Conventional 0.0003 *

Soybeans MidSouth No-Till 0.0013 *

Soybeans MidWest Conservation 0.0006 *

Soybeans MidWest Conventional 0.0056 *

Soybeans MidWest No-Till 0.0002 *

Soybeans Southeast Conservation 0.3208

Soybeans Southeast Conventional 0.0495 *

Soybeans Southeast No-Till 0.0447 *

Soybeans West Conservation 0.1184

Soybeans West Conventional 0.0921

Soybeans West No-Till 0.7472

Note: Twenty of the 42 tests observed quadratic slopes that were significantly different from zero at the 

5% level of significance. The tests that were significant at the 5% level are marked with an ‘*’. 
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Table A-2. Tests to Determine if the Linear Slopes of the Regression Lines Were 

Significantly Different From Zero

Crop Region Tillage_Type P-value

Corn East Conservation 0.2078

Corn East Conventional <.0001 *

Corn East No-Till <.0001 *

Corn MidSouth Conservation 0.0195 *

Corn MidSouth Conventional 0.4904

Corn MidSouth No-Till 0.3690

Corn MidWest Conventional 0.0011 *

Corn Southeast Conservation 0.0835

Corn West Conservation 0.0011 *

Corn West Conventional <.0001 *

Corn West No-Till 0.0114 *

Cotton MidWest Conservation 0.0210 *

Cotton Southeast Conservation <.0001 *

Cotton West Conservation <.0001 *

Cotton West Conventional <.0001 *

Cotton West No-Till 0.0001 *

Soybeans East Conservation 0.1917

Soybeans MidSouth Conservation 0.1896

Soybeans Southeast Conservation 0.6675

Soybeans West Conservation 0.1233

Soybeans West Conventional 0.0067 *

Soybeans West No-Till 0.0002 *

Note: Fourteen of the 22 tests observed linear slopes that were significantly different from zero at the 5% 

level of significance. The tests that were significant at the 5% level are marked with an ‘*’. 
Monsanto Company Petitions 10-188-01p/12-185-01p_a1 Page 16 of 65

Table A-3. Regression Parameter Estimates for the Crop and Region Combinations with a 

Significant the Change in Tillage Over Time 

Crop Region Tillage Type Intercept Year Year*Year

Corn East Conventional 3466.72 -1.7079 .

Corn East No-Till -3039.87 1.5340 .

Corn MidSouth Conservation -1769.03 0.8933 .

Corn MidWest Conservation 300587 -299.62 0.07467

Corn MidWest Conventional 1114.90 -0.5355 .

Corn MidWest No-Till -383597 381.93 -0.09506

Corn Southeast Conventional 766604 -763.20 0.1900

Corn Southeast No-Till -1202619 1198.66 -0.2987

Corn West Conservation -2375.58 1.1991 .

Corn West Conventional 3782.79 -1.8592 .

Corn West No-Till -1307.20 0.6601 .

Cotton MidSouth Conservation -1044452 1041.04 -0.2594

Cotton MidSouth Conventional 2648507 -2639.72 0.6577

Cotton MidSouth No-Till -1603955 1598.68 -0.3983

Cotton MidWest Conservation -2277.83 1.1529 .

Cotton MidWest Conventional 1707629 -1701.22 0.4237

Cotton MidWest No-Till -2295716 2289.07 -0.5706

Cotton Southeast Conservation -3534.42 1.7786 .

Cotton Southeast Conventional 1405216 -1399.58 0.3485

Cotton Southeast No-Till -1304016 1300.48 -0.3242

Cotton West Conservation -2656.63 1.3372 .

Cotton West Conventional 4244.03 -2.0828 .

Cotton West No-Till -1487.40 0.7456 .

Soybeans East Conventional 902937 -899.02 0.2238

Soybeans East No-Till -1061879 1057.33 -0.2632

Soybeans MidSouth Conventional 1373279 -1368.84 0.3411

Soybeans MidSouth No-Till -1208347 1204.77 -0.3003

Soybeans MidWest Conservation 387479 -386.03 0.09615

Soybeans MidWest Conventional 311116 -309.83 0.07714
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Table A-3 (continued). Regression Parameter Estimates for the Crop and Region 

Combinations with a Significant the Change in Tillage Over Time 

Crop Region Tillage Type Intercept Year Year*Year

Soybeans MidWest No-Till -698495 695.85 -0.1733

Soybeans Southeast Conventional 600500 -597.28 0.1485

Soybeans Southeast No-Till -768636 765.12 -0.1904

Soybeans West Conventional 3901.95 -1.9250 .

Soybeans West No-Till -6423.22 3.2204 .
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Appendix A Figures

Figures
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Appendix B: CTIC Survey Results of Leading Conservation Tillage Experts 

The following pages summarize the results of the CTIC (Conservation Tillage Information 

Center) survey of 21 total (14 in Midwest and 7 in South) leading conservation tillage experts 

across the key agronomic regions of the U.S. for soybean, corn and cotton production. These 

experts were asked to rate the importance of 11 factors that could influence tillage practices of 

growers in their region. Responses the the question below are summarized on the following 

pages.

Question: In general, how important are the following factors to the majority of the farmers in 

your region as they determine the total amount of tillage done to produce corn, regardless of 

whether the tillage is done prior to planting or done during the growing season? Choose the 

rating below that best reflects the importance of each factor in determining the amount of tillage 

being used.
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Table B-1. Midwest Corn (14 total Experts)

Number of Experts Responding

Manage 

excess 

crop 

residue

Manage 

existing 

weeds

Manage 

Disease

Manage 

Soil 

moisture

Manage Soil 

temperature

Prevent 

weed 

resistance

Seed bed 

preparation

Use of 

Strip till / 

vertical 

tillage 

tools

Economics Availability 

of Labor

Water 

penetration

Not 

important / 

Not 

mentioned

4 6 4 4 4 8 4 6 6 8 6

Sometimes 

important

4 3 5 3 3 2 2 3 1 2 4

Quite 

important

2 2 4 5 5 2 3 2 3 2

Extremely 

important

4 3 1 2 2 2 5 3 7 1 2

Ranking 

Sum1

34 30 30 33 33 26 37 30 36 25 28

1

Ranking Sum was calculated as follows, a number from 1 to 4 was assigned to each response category, with 1 assigned to ‘not important or not 

mentioned’ and 4 assigned to ‘extremely important’. The assigned number was multiplied by the number of responses from the experts and then 

added together for each factor. 
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Table B-2. Midwest Soybean (13 total Experts)

Number of Experts Responding

Manage 

excess 

crop 

residue

Manage 

existing 

weeds

Manage 

Disease

Manage 

Soil 

moisture

Manage Soil 

temperature

Prevent 

weed 

resistance

Seed bed 

preparation

Use of 

Strip till / 

vertical 

tillage 

tools

Economics Availability 

of Labor

Water 

penetration

Not 

important / 

Not 

mentioned

6 4 7 3 5 6 4 10 4 2 4

Sometimes 

important

0 4 2 6 4 3 2 1 3 6 5

Quite 

important

1 2 2 2 1 2 3 0 2 3 2

Extremely 

important

6 3 2 2 3 2 4 2 4 1 1

Ranking 

Sum1

33 30 25 29 28 26 33 20 32 27 24

1

Ranking Sum was calculated as follows, a number from 1 to 4 was assigned to each response category, with 1 assigned to ‘not important or not 

mentioned’ and 4 assigned to ‘extremely important’. The assigned number was multiplied by the number of responses from the experts and then 

added together for each factor. 
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Table B-3. South Corn (6 total Experts)

Number of Experts Responding

Manage 

excess 

crop 

residue

Manage 

existing 

weeds

Manage 

Disease

Manage 

Soil 

moisture

Manage Soil 

temperature

Prevent 

weed 

resistance

Seed bed 

preparation

Use of 

Strip till / 

vertical 

tillage 

tools

Economics Availability 

of Labor

Water 

penetration

Not 

important / 

Not 

mentioned

2 2 3 1 2 2 1 2

Sometimes 

important

1 1 2 4 5 2 1 2 1 3 1

Quite 

important

3 1 1 2 1 4 2 2 1 1

Extremely 

important

1 1 1 3 1 2

Ranking 

Sum1

13 11 10 14 11 13 18 12 20 14 15

1

Ranking Sum was calculated as follows, a number from 1 to 4 was assigned to each response category, with 1 assigned to ‘not important or not 

mentioned’ and 4 assigned to ‘extremely important’. The assigned number was multiplied by the number of responses from the experts and then 

added together for each factor.
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Table B-4. South- Soybean (6 total Experts)

Number of Experts Responding

Manage 

excess 

crop 

residue

Manage 

existing 

weeds

Manage 

Disease

Manage 

Soil 

moisture

Manage Soil 

temperature

Prevent 

weed 

resistance

Seed bed 

preparation

Use of 

Strip till / 

vertical 

tillage 

tools

Economics Availability 

of Labor

Water 

penetration

Not 

important / 

Not 

mentioned

3 4 2 1 1 1

Sometimes 

important

2 2 1 3 4 1 2 3 1 2 3

Quite 

important

1 3 1 2 4 3 2 3 1 1

Extremely 

important

1 1 1 1 2 1 1

Ranking 

Sum1

10 17 9 16 10 18 17 13 19 12 14

1

Ranking Sum was calculated as follows, a number from 1 to 4 was assigned to each response category, with 1 assigned to ‘not important or not 

mentioned’ and 4 assigned to ‘extremely important’. The assigned number was multiplied by the number of responses from the experts and then 

added together for each factor.
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Table B-5. South- Cotton (6 total Experts)

Number of Experts Responding

Manage 

excess 

crop 

residue

Manage 

existing 

weeds

Manage 

Disease

Manage 

Soil 

moisture

Manage Soil 

temperature

Prevent 

weed 

resistance

Seed bed 

preparation

Use of 

Strip till / 

vertical 

tillage 

tools

Economics Availability 

of Labor

Water 

penetration

Not 

important / 

Not 

mentioned

3 2 1 2

Sometimes 

important

4 3 2 2 3 4 1 3 2 1

Quite 

important

1 1 1 3 1 1 3 2 4 3 2

Extremely 

important

1 2 1 1 1 1 2 1 1

Ranking 

Sum1

15 17 10 17 11 18 16 16 20 17 14

1

Ranking Sum was calculated as follows, a number from 1 to 4 was assigned to each response category, with 1 assigned to ‘not important or not 

mentioned’ and 4 assigned to ‘extremely important’. The assigned number was multiplied by the number of responses from the experts and then 

added together for each factor.