CORE CONSERVATION PRACTICES 1

CORE CONSERVATION PRACTICES :

ADOPTION BARRIERS PERCEIVED

BY SMALL AND LIMITED RESOURCE FARMERS

Bulletin 646 May 2001

Alabama Agricultural Experiment Station Auburn University

Luther Waters, Director Auburn, Alabama
2 ALABAMA AGRICULTURAL EXPERIMENT STATION

CONTENTS

INTRODUCTION.................................................................................. 3

Objectives ................................................................................................ 3

Definition of Limited Resource Farmers................................................... 4

Small and Limited Resource Farmer Program Participation ...................... 4

Black and Minority-operated Farms ......................................................... 5

METHODS ....................................................................................... 7

Sample and Data Collection ..................................................................... 7

Measuring Adoption ................................................................................ 8

RESULTS ......................................................................................... 9

Income Sources...................................................................................... 11

Conservation Tillage .............................................................................. 13

Conservation Tillage Adoption............................................................... 15

Crop Nutrient Management .................................................................... 16

Crop Nutrient Management Adoption .................................................... 18

Rotation and Fertilization Practices ........................................................ 19

Integrated Pest Management .................................................................. 21

Integrated Pest Management Adoption ................................................... 23

Conservation Buffers ............................................................................. 24

Conservation Buffer Adoption ............................................................... 26

Conservation Program Participation ....................................................... 27

Determinants of NRCS Contact .............................................................. 28

Information Sources............................................................................... 30

Information Mode .................................................................................. 33

Land and Water Resources ..................................................................... 34

CONCLUSIONS ................................................................................. 36

REFERENCES .................................................................................... 38

ACKNOWLEGEMENT: We thank the USDA-Alabama Agricultural Statistics Service

for its assistance in instrument design, sampling, and data collection.

First Printing 2M, May 2001

Information contained herein is available to all persons without regard to

race, color, sex, or national origin.
 CORE CONSERVATION PRACTICES 3

CORE CONSERVATION PRACTICES :

ADOPTION BARRIERS PERCEIVED

BY SMALL AND LIMITED RESOURCE FARMERS

Molnar is a professor and Bitto is a graduate research assistant in the Department of Agricultural Economics and Rural Sociology. Brant is a sociologist with the USDA-NRCS-Social Science Institute.

OUR SETS OF FARMING PRACTICES—conservation tillage, crop nutrient management, weed and pest management, and conservation buff- F ers—are the central focus of technical assistance efforts by conservation

JOSEPH J. MOLNAR, ANNETTE BITTO, AND GAIL BRANT

INTRODUCTION

agencies. Although small and limited resource farms comprise more than threequarters of the operations in Alabama, Georgia, and Mississippi, this segment

of the farm population has disproportionately low levels of adoption of these

farming practices (also called the Core 4 practices), which are established measures for conserving soil and protecting groundwater.

The purpose of this report is to provide baseline infomation for technical

assistance for achieving national conservation objectives—specifically the

adoption of the Core 4 Practices—on small and limited resource farms in the

Deep South. Statewide samples from Alabama, Georgia, and Mississippi are

used to present detailed profiles of the conservation practices and understandings of these practices among small and limited resources farmers.

OBJECTIVES

1. Profile core conservation practices utilized by small and limited resource farmers in Alabama, Mississippi, and Georgia.

2. Compare the practices and perceptions of black and white farmers in Alabama, Georgia, and Mississippi.

3. Identify perceived barriers and disadvantages to the implementation of core

conservation practices.

4. Describe patterns of information source utilization and preferences among

small and limited resource farmers.
4 ALABAMA AGRICULTURAL EXPERIMENT STATION

DEFINITION OF LIMITED RESOURCE FARMERS

Research suggests that no all-purpose definition of a small farm can be readily

established, but that a number of common characteristics can be identified (Tweeten,

1983). Working definitions have centered on the size of the operation, gross farm

sales, and the number of hours contributed to labor and management of the farm

operation. Small and limited resource farmers have been shown to be more riskaverse and posses fewer slack resources to invest in conservation measures

(Dishongh, 1991; Zabawa, 1989; 1991). Most small farmers depend on farming to

obtain a significant part of family income, but not necessarily a majority of it. In

addition, the limited resource farmer and family members usually provide most of

the labor and management for the farm operation.

A part-time owner-operator obtains a percentage of total family income

through off-farm employment, providing a substantial part of the household’s overall budget (Molnar and Adrian, 1980). For the purpose of this report, an income

figure of $40,000 is used to distinguish limited resource farmers from commercial

farmers, although other studies with other purposes may use different standards or

combinations of criteria.1

As a target audience for USDA-NRCS programs limited resource farmers

have many of the following characteristics (NRCS, 1991b):

• Gross farm sales average $40,000 or less in each of the last three years.

• Total household net income, farm and non-farm, is 75 percent or less of the nonmetropolitan median income level for the state or county.

• Access to capital, labor, or equipment is not readily available.

• Farm or ranch size is significantly smaller than average size.

• Social, cultural, customs or language barriers may include the following: minimal awareness of USDA programs, limited management skills, levels of formal

education below the county average, and less inclination to take business risks and

adopt new technology.

SMALL AND LIMITED RESOURCE FARMER PROGRAM PARTICIP ATION

Previous research on agricultural program participation suggests a number of

basic patterns that might be expected to apply to the conservation practices used

by small and limited resource farmers in the Deep South. Decisions regarding

implementing new technology on small farms might actually cause some small

farmers to change their operation or stop farming as Gladwin and Zabawa found in

their studies of small and part-time farmers in Florida (1985; 1986). McleanMeyinesse (1994) found that Louisiana small farmers do not participate in the

Conservation Reserve Program if revenues from cropland are an important source

of income, or if they are tenants. She found that actual participation depends on

whether payments per acre are comparable to the opportunity costs of removing

1

 The USDA National Commission on Small Farms chose to use gross income to categorize farms and

defined small farms as “those with less than $250,000 gross receipts annually, on which day-to-day labor

and management are provided by the farmer and/or the farm family that owns the production or owns, or

leases, the productive assets.” This definition includes 94% of all farms in the United States.
 CORE CONSERVATION PRACTICES 5

cropland from production. Awareness of the program was positively related to

education, income, race, and average return per acre. Willingness to participate

was inversely related to age, but positively influenced by the size of the payment

per acre. Others have shown similar patterns of difference in the use of information sources (Korsching and Hoban, 1990; Hoban et al., 1986).

Limited resource farmers and socially disadvantaged minority farm operators tend not to purchase crop insurance or to participate in insurance-type programs (Dismukes et al., 1997). They tend, more than the typical U.S. farmer, to

raise livestock rather than crops. As there are no government-sponsored insurance-type programs for livestock, this seems to reduce the need for contact with

public agencies among these producers. In addition, many of those who raise crops

tend to concentrate on specialty crops such as fruits and vegetables rather than row

crops that are the focus of most government programs. In many cases, farm income makes a minor contribution to a household’s overall income. A lack of insurance for the farm enterprise may be less important for these operators than for

others more reliant on farm income.

Mishra et al. (1999) investigated the factors affecting profitability of limited

resource and other small farms. Profitability on limited resource farms—as measured by net farm income and operators’ labor and management income—depended

on the operator’s age, soil productivity, debt-to-asset ratio, and ratios of variable

and fixed costs of production to value of agricultural production. A major source

of variation in the performance measures of small and limited resource farms is the

ratio of variable costs to value of agricultural production. Unexpected variable

costs can have a disastrous effect on the profitability of a particular farm enterprise

as well as the viability of the entire operation.

One piece of conventional wisdom is that farmers must either get bigger or

get out of farming, but this assertion fails to recognize the diversity of niches for

farming in nature and society. The future is dim for small-scale production of

basic agricultural commodities such as corn, hogs, soybeans, cattle, etc. Nonetheless, Ikerd (1999) makes the case that there is a future in producing food and fiber

products by methods that both can be sustained by nature and will be sustained by

society.

 Sustainable systems must conform to marketing and ecological niches inherent in nature—including human nature. Those niches are small and diverse, not

large and uniform. Many families that operate small units depend on farming for a

significant part of their economic, social, and spiritual way of life, if not their

whole livelihood. For example, Feldman’s (1999) analysis of maple sugar operators describes their activity as a sideline and a lifeline, illustrating how small farms

can conform to the economic and ecological niches of markets and of nature.

BLACK AND MINORITY -OPERATED FARMS

The number of black-owned farms is declining at a more rapid rate than other

farms, which has called into question the treatment of minority farmers in receiving federal assistance (Yeboah and Wright, 1985). GAO (1997) reviews efforts to
6 ALABAMA AGRICULTURAL EXPERIMENT STATION

treat minority farmers in the same way as non-minority farmers in delivering program services. Many minority and limited resource farmers blame government

policies and practices for the severe decline in farm ownership by minorities, especially black farmers, in the last 70 years.

Much of the black-owned land had been held for generations, in some cases

acquired by these farm families after slavery was abolished in the 1860s. According to the Census of Agriculture, the number of farms owned by blacks fell from

925,000 in 1920, 14 percent of all farms, to only 18,000 in 1992, one percent of all

farms. Although the number of farms owned by other minorities has increased in

recent years, particularly among Hispanics, the total acres of land farmed by these

groups has actually declined. Only women have seen an increase in both number

of farms and acres farmed. During this time, the number of non-minority farmers

also has dramatically declined, although at a slower rate.

Minority farm advocates blame farm program regulations that—intentionally or not—shut out minority and limited-resource farmers from the benefits of

the programs that have helped larger non-minority producers survive the changes

in agriculture in the last 50 years (Brown and Larson, 1979). And they identify

institutional insensitivity to the differing needs of minority and limited-resource

customers and pubic agency tendencies to neglect their responsibility to reach out

and serve all that need assistance. Some farm advocates liken minority farmers to

an “endangered species” (USDA, 1997a; 1997b).

GAO (1997) identified 101 U.S. counties with the largest concentration of

minority farmers, several of which are in Alabama. One-quarter had no minority

employees in their farm service agency (FSA) offices. In those offices that did

employ minorities, most were program assistants, although one-quarter of the offices had minority county executive directors. Perhaps the lack of diversity that

minority and limited-resource customers deem to be most critical is the lack of

minority and female representation on the county committees, which can affect

access to FSA programs. In 1994, 94 percent of all U.S. county committees had no

female or minority representation.

Bagi (1984) examined the likelihood of a farmer being visited by an extension agent in West Tennessee, given the personal characteristics of the operator

and economic aspects of 80 farm-firm households. The results show that extension

agents visit some small farm operators, but even among this group of small farms,

extension agents tend to visit operators of relatively large farms. Within the small

farm group, extension agents are more likely to visit white farmers than black

farmers, and tend to visit better-educated small farm operators. In other words,

extension agents are less likely to visit those small farm operators who need more

help due to their perceived lower level of organizational and management ability.

Most of the small farm operators in the Bagi study were not being served by regular extension services.

Onianwa et al. (1999) identified factors that affect conservation practice

choices among Conservation Reserve Program (CRP) participant farmers in Alabama. Analyzing 204 useable surveys from farmers with CRP contracts, they found
 CORE CONSERVATION PRACTICES 7

that education, ratio of cropland in CRP, farm size, gender, prior crop practice, and

geographic location of contract each had a significant influence on the choice of

conservation practice. No significant differences by race were reported, however.

This study also determined that limited resource farmers do not implement conservation practices as frequently as full-time farmers.

The disparity in participation and treatment of non-minority and minority

farmers may be partially accounted for by the smaller average size of minority and

female-operated farms, their lower average crop yields, and their greater likelihood not to plant program crops. In addition, minority farmers tend to have less

sophisticated technology, insufficient collateral, poor cash flow, and poor credit

ratings (GAO, 1997). However, representatives of minority and female farm groups

point out that previous discrimination in USDA programs has helped to produce

these very conditions now used to explain disparate treatment.

Many perceive that public agencies do not place a priority on serving the

needs of small and limited resource farmers and do not support any official effort

to address this problem (USDA, 1997b). The several public agencies that serve

farmers have developed their own separate programs that may or may not be successful in responding to the numerous differences found among minority and limited resource customers. Some minority and limited resource farmers feel they do

not receive the technical assistance they require nor the basic information about

programs for which they might be eligible. Many who need help to complete application forms also need help to understand and meet eligibility requirements for

programs. They need information about how their applications will be processed.

If their application is denied, they need information on how they might succeed in

future applications. When they do receive loans or other program benefits, they

need assistance to use those benefits most effectively to improve their operations

(Schor, 1992; 1996).

This report provides basic information profiling the conservation practices

and technical assistance preferences of black and white small farm operators, a

body of information not available from any other source.

METHODS

SAMPLE AND DATA COLLECTION

The sampling design for the study was structured so as to yield approximately

equal numbers of black and white farmers in Alabama, Georgia, and Mississippi.2

A simple, random sample of white farm operators included those operations with

2

 Each USDA-National Agricultural Statistics Service state office maintains a constantly updated list of

all known agricultural producers. Names and information from the 1997 Census of Agriculture were

used to supplement the farm operator list. Every effort is made to maintain and keep the list as up-to-date

as possible. However, any list frame of farm operators will always be incomplete because of constant

changes in population due to retirements, farm sales, farm consolidations, entry of new farm operators,

changes in operating arrangements, etc. Consequently, there is an undetermined amount of incompleteness in the list frames for the states involved in this study, but it is minimal.
8 ALABAMA AGRICULTURAL EXPERIMENT STATION

TABLE 1. POPULATION COUNTS, SAMPLE SIZES, AND SURVEY RESPONSES BY STATE, 2000

——White farm operators—— ——Black farm operators——

State Population Sample Responded Population Sample Responded

Alabama 2,332 507 138 1,062 1,062 157

Georgia 2,763 552 115 688 688 119

Mississippi 1,496 487 127 1,053 1,053 178

Total 6,591 1,546 380 2,803 2,803 454

less than $40,000 gross value of sales and row crop control data for cotton, corn,

soybeans, or peanuts. All list names of black and other minority farm operators

were selected for the survey. The sample sizes and number of completed mail

surveys that were returned by black and white respondents in each state are shown

in Table 1.

Survey data were collected by mail using a self-administered survey instrument adapted in part from previous research conducted in a sample of farm operators in the Midwest (CTIC, 2001). A second request questionnaire was used to

increase the mail response. To further boost response counts, a limited amount of

non-response follow-up was done for both race groups in Georgia and the white

sample in Mississippi. Trained telephone interviewers from the NASS Alabama

State Statistical Office conducted the follow-up.

Responses are tabulated by race and state to facilitate comparisons of the data

for educators and technical assistance providers, farmers, and other professionals

with interest in the pattern of results in a particular state. Four respondents did not

provide race identification so all tables were constructed on a base of 830 cases.

Chi-square statistics are presented where appropriate to draw attention to important differences by race or state. Chi-square statistics are not appropriate for multiple response items where respondents could indicate more than one category in

response to a question.

There are several statistical caveats to the use of significance tests on these

data due to the nature of the sampling, low response rates that signal some concerns about representativeness, and other shortcomings that suggest caution in interpretation of the observed differences. Nonetheless, significance tests do draw

attention to patterns of differences that are less likely to have occurred by chance

and may be worth interpreting in a qualified way given the aforementioned limitations.

MEASURING ADOPTION

Conservation Tillage (CT) adoption was measured by four variables reflecting

precursor conditions associated with the actual use of specific CT practices. Respondents were asked to rate their level of familiarity with CT and the perceived

practicality of CT. They were asked to note possible reasons for using CT on their

farms. The measure counts how many they cited. They also were asked to check a
 CORE CONSERVATION PRACTICES 9

series of CT practices that they had implemented in their farms and the measure

counts the number of practices they reported.

Crop Nutrient Management (CNM) adoption was measured by four variables

reflecting precursor conditions associated with the actual use of specific CNM

practices. Respondents were asked to rate their level of familiarity with CNM and

the perceived practicality of CNM on their farms. They were asked to note possible reasons for using CNM. The measure counts how many they cited. They also

were asked the frequency at which they obtained soil tests for the nutrient properties of their farmland or pastures, the central feature of any program of CNM.

Integrated Pest Management (IPM) adoption was measured by four variables reflecting precursor conditions associated with the actual use of specific IPM

practices. Respondents were asked to rate their level of familiarity with IPM and

the perceived practicality of IPM on their farms. They were asked to note possible

reasons for using IPM and the measure counts how many they cited. They also

were asked to check a series of IPM practices that they had implemented in their

farms; this measure counts the number of practices they reported.

Conservation Buffer (CB) adoption was measured by four variables reflecting

precursor conditions associated with the actual use of specific CB practices. Respondents were asked to rate their level of familiarity with CB and the perceived

practicality of CB on their farms. They were asked to note possible reasons for

using CB and the measure counts how many they cited. They also were asked to

check a series of CB practices that they had implemented in their farms; this measure counts the number of practices they reported.

Statistical weighting was employed in regression analysis to restore representativeness to the combined data set due to the differential rate at which black

farm operators were sampled. The weights restore statistical representation in the

sample mirroring the statistical representation in the population of farm operators

in the three states.

RESULTS

Table 2 shows the respondents’ characteristics by state and race. Most of the

small-scale operators who responded to the study were male and—due to sample

selection procedures—were nearly equally divided between black and white in

each state. About one percent of the overall sample was Native American. These

respondents are tabulated with the white respondents primarily because there were

insufficient cases for specific analysis of this category of farmers and one focus of

the study was to examine the problems challenging black farmers.

Education varied significantly by race and state. Thirty seven percent of the

Alabama black respondents had a college education or higher, suggesting that many

part-time, hobby, or heir-property landowners may be included in the sample. In

Georgia, 28 percent of the black respondents had advanced education, compared

to 20 percent of the white farmers. This was a parallel pattern across the three states.

The black respondents had higher levels of education than the white respondents.
10 ALABAMA AGRICULTURAL EXPERIMENT STATION

TABLE 2. R ESPONDENT CHARACTERISTICS BY RACE AND STATE,

SMALL AND LIMITED RESOURCE FARMERS , 2000

—Alabama— —Georgia— —Mississipi— –Chi-square–

All White Black White Black White Black State Race

% % % % % % %

What is your gender?

Male 94 97 94 93 92 96 91

Female 6 3 6 7 8 4 9

2.2 3.2

Race

African American 54 0 100 0 100 0 100

White 46 99 0 98 0 98 0

Native American 1 1 0 3 0 2 0

N/A N/A

What is the highest level of formal education you (the operator) completed?

Less than high school 18 13 20 18 27 13 17

High school diploma 29 37 19 42 29 30 22

or GED

Some college 24 25 25 19 16 34 24

Completed 4-year 15 16 16 10 10 16 16

college degree

Graduate school 14 8 21 10 18 7 21

19.4* 36.7**

How old were you on your last birthday?

Under 35 3 6 1 3 4 4 0

35-44 13 17 7 10 12 16 15

45-54 22 17 26 14 22 21 27

55-64 35 27 32 29 26 22 15

65-69 27 13 14 16 9 12 19

70 and over 24 20 20 28 27 25 24

21.4* 16.8*

How many days did you work at least 4 hours off this operation last year (1999)?

Did not work 25 25 24 27 24 31 22

off the farm

1-49 days 19 19 13 12 18 14 19

50-200 days 22 22 26 18 27 17 30

200+ days 34 34 37 44 32 39 28

1.7 10.3*

Did your spouse work at least 4 hours per day off this operation last year (1999)?

No spouse 13 12 13 13 14 10 15

Spouse did not work 37 28 40 37 36 39 40

off the farm

1-49 days 13 18 15 12 6 9 14

50-200 days 9 9 8 8 12 9 9

200+ days 29 33 24 31 33 34 22

6.9 4.5

Number 830 137 154 118 116 129 176

*p < .05 **p<.01
 CORE CONSERVATION PRACTICES 11

Age varied significantly by race and state, though these patterns were not

consistent across categories. About 44 percent of Georgia white farmers were age

65 or over, as were about 43 percent of Mississippi black farmers.

About a fourth of all operators did not work off the farm in the previous year.

The test statistic suggests that differences by race, but not by state, are worth attending to. More Mississippi white farmers did not work off the farm (31 percent),

but Mississippi black farmers were least likely to not work off the farm (22 percent). About 44 percent of Georgia white farmers worked full-time off the farm,

the highest rate in the sample.

About 34 percent of the sample had spouses who worked 200 or more days

off the farm, but differences were not significant by race or state. About half either

had no spouse or had a spouse who did not work off the farm.

INCOME SOURCES

Table 3 shows the sources of farm income in the sample of small and limited

resource farmers. There were large differences by race and state. Row crops such

as cotton, soybeans, and other items were grown by approximately a third of the

farmers. In each state, more white farmers reported growing row crops and they

were consistently more likely to report this enterprise as a source of 75 percent or

more of their farm income. Only 15 percent of Alabama and 20 percent of the

Mississippi black farmers reported growing row crops.

Around 70 percent of the sample had income from livestock with large differences by race and state. More white farmers did not have any livestock. Black

farmers were more likely to report that more than 75 percent of their farm income

came from livestock.

Only three percent of the sample had poultry, primarily white farmers. The

test statistics for race and state were not significant. Central to the growing industrialized sector, poultry represents the single most important agricultural product

in Alabama and Georgia. It accounts for more than half of all farm income in these

states, employing many people and generating the majority of farm exports. Small

and limited resource farmers are not participating in the most technologically dynamic and economically active components of agriculture.

Sixteen percent of small and limited resource farmers reported sales income

from fruit, vegetable, horticulture, or specialty crops. There were no significant

differences by race or state.

Roughly 74 percent of the sample received no income from government payments, though state differences were significant. About 16 percent of Georgia farmers received half or more of their income from government payments, the highest

in the sample.

About four percent indicated that 75 percent or more their income was from

the farm. Overall differences by race and state were not significant.

Farm income category differed significantly by race. More white farmers in

each state reported farm incomes in the top three categories. More black farmers in

each state were in the lower income categories.
12 ALABAMA AGRICULTURAL EXPERIMENT STATION

TABLE 3. F ARM INCOUME SOURCES AND CHARACTERISTICS BY RACE AND STATE,

SMALL AND LIMITED RESOURCE FARMERS , 2000

—Alabama— —Georgia— —Mississipi— –Chi-square–

All White Black White Black White Black State Race

% % % % % % %

What percent of the sales reported on your operation came from the following commodity groups?

Row crops such as corn, cotton, soybeans, etc.

None 67 61 85 50 63 53 80

1 to 49 percent 9 9 4 13 11 14 6

50 to 74 percent 8 12 6 14 7 5 5

75 to 100 percent 17 19 6 24 19 28 10

24.5** 45.3**

Livestock such as cattle, hogs, sheep etc.

None 30 32 18 48 32 40 20

1 to 49 percent 7 13 4 7 14 5 3

50 to 74 percent 7 5 6 8 9 7 6

75 to 100 percent 56 50 72 36 46 48 70

33.2** 34.9**

Poultry, including contract broilers, eggs, etc.

None 97 96 99 100 97 98 95

1 to 49 percent 1 1 1 0 0 2 2

50 to 74 percent 1 0 0 0 1 0 2

75 to 100 percent 1 3 0 0 2 0 1

11.2 4.7

Fruit, vegetables, horticulture, or speciality crops

None 84 83 83 81 85 86 86

1 to 49 percent 8 7 6 12 7 8 10

50 to 74 percent 2 3 4 2 3 2 1

75 to 100 percent 5 7 6 6 5 5 2

9.5 1.6

Government agricultural payments

None 74 73 79 58 72 77 78

1 to 49 percent 16 18 17 24 13 12 15

50 to 74 percent 3 3 3 8 2 4 1

75 to 100 percent 7 6 2 9 13 7 6

19.1* 8.8*

continued

Although the sample was selected to target operators of farms with less than

$40,000 in sales, about 3 percent of the sample had a higher level of annual sales.

This is due primarily to annual variability in farm income between the reporting

year and the year of the sample selection criterion. Data from these operators was

not excluded because farm income is variable from year to year and these operations qualified as small and limited resource farms in previous reporting periods.
 CORE CONSERVATION PRACTICES 13

TABLE 3, CONTINUED . FARM INCOUME SOURCES AND CHARACTERISTICS

BY RACE AND STATE, SMALL AND LIMITED RESOURCE FARMERS , 2000

—Alabama— —Georgia— —Mississipi— –Chi-square–

All White Black White Black White Black State Race

% % % % % % %

About what percent of your total 1999 household income was from farming?

Less than 25% 73 72 78 69 75 70 73

25% 17 19 17 15 15 18 18

50% 6 5 3 10 7 6 6

75% or more 4 4 3 6 3 6 3

7.9 4.4

Including ag payments, what was the total gross value of sales from this operation?

Less than $1,000 25 23 33 14 31 17 30

$1,000-$2,499 25 16 26 24 22 15 27

$2,500-$4,999 14 17 15 10 8 18 15

$5,000-$9,999 22 19 17 27 25 30 19

$10,000-$39,999 14 21 10 21 10 19 8

$40,000 and over 3 4 1 4 5 3 1

19.1 44.0**

Number 830 137 154 118 116 129 176

*p < .05 **p<.01

CONSERV ATION TILLAGE

Table 4 shows the conservation tillage (CT) experiences reported by study

respondents. Only 17 percent of the sample was very familiar with CT, but many

differences by race were significant. Black farmers were consistently less familiar

with CT than white farmers. Alabama black farmers had the highest proportion

indicating they were not familiar with CT, 44 percent. Conversely, 26 percent of

the Alabama white farmers said they were very familiar with CT, the highest proportion across the three states.

About a third of the respondents felt that CT would be practical on their

farms. Differences were significant by race showing that 20 percent of Alabama

and 29 percent of Mississippi black operators saw CT as practical on their farms,

the lowest levels in the sample.

Only about 15 percent of the respondents had crop acreage planted used CT

practices. More whites consistently had more land under CT than blacks.

Less than 10 percent used any single CT technique. No-till was the overall most

used tillage practice. Respondents were given a number of reasons for using CT and

asked to mark all that applied to them. The table ranks them in terms of the overall

frequency that each was chosen. About 20 percent felt that the main reason for using

CT was reducing soil erosion, but this was highly variable across the states. Around 10

percent noted conserving soil moisture, and 9 percent marked increasing organic matter and saving time as reasons for using CT. There were few consistent differences by

state or race, though more Mississippians felt that CT increased yields per acre.
14 ALABAMA AGRICULTURAL EXPERIMENT STATION

TABLE 4. C ONSERV ATION TILLAGE EXPERIENCES AND PERCEPTIONS BY RACE AND STATE,

SMALL AND LIMITED RESOURCE FARMERS , 2000

—Alabama— —Georgia— —Mississipi— –Chi-square–

All White Black White Black White Black State Race

% % % % % % %

How familiar with conservation tillage (CT) are you?

Not at all familiar 30 24 44 20 31 19 37

Somewhat familiar 53 50 45 60 55 63 50

Very familiar 17 26 11 20 14 18 13

7.2 31.0**

Is CT practical on your farm?

It would be good 32 40 20 32 30 40 29

Not very practical 21 23 20 30 18 25 15

No opinion 47 37 60 38 52 35 56

3.1 32.6**

What percentage of your total crop acreage was planted last year (1999) using any CT

practices?

No crop acreage 85 79 93 85 83 78 89

Less than 50 percent 5 6 4 3 7 7 5

50 percent 3 4 1 2 4 3 2

More than 50 percent 7 11 2 10 6 12 4

1.3 18.1**

What conservation tillage practices did you use?

No till 5 8 1 8 5 9 3

Reduced till 5 8 2 3 3 9 3

Mulch till 3 3 3 1 5 4 3

Strip till 1 2 1 2 1 2 2

Ridge till 1 1 0 3 3 0 1

N/A N/A

What are the main reasons you would use CT on your farming operation?

Reduces soil erosion 20 29 12 18 18 30 19

Conserves soil 10 14 5 10 10 14 9

moisture

Increases organic 9 9 6 11 11 13 4

matter

Saves time 7 9 3 6 8 13 6

Lowers production 6 9 5 6 5 8 5

costs

Increases yields 6 4 3 3 8 9 8

per acre

Reduces soil 5 3 3 6 5 7 4

compaction

Other 0 0 0 0 1 0 0

N/A N/A

continued

The main perceived problems with CT were more weeds, higher herbicide

costs, and high equipment costs, each cited by about 10 percent of the sample.

More white farmers cited disadvantages. In each state, slightly more black farmers

noted that how-to information was not available.
 CORE CONSERVATION PRACTICES 15

TABLE 4, CONTINUED . CONSERV ATION TILLAGE EXPERIENCES AND PERCEPTIONS

BY RACE AND STATE, SMALL AND LIMITED RESOURCE FARMERS , 2000

—Alabama— —Georgia— —Mississipi— –Chi-square–

All White Black White Black White Black State Race

% % % % % % %

What are the main problems you might have with CT on your operation?

More weeds 11 14 5 13 13 15 8

Higher herbicide costs 11 18 3 13 5 21 6

Equipment costs 10 12 6 11 6 15 13

too much

“How to” Information 3 3 5 3 4 2 3

not available

Crop yields are lower 2 3 1 1 3 5 2

Disease problems 1 1 1 1 3 3 1

More insects 1 0 2 2 1 2 1

Tried CT and 1 0 1 1 1 0 2

it didn’t work

Other 1 1 0 1 2 0 1

N/A N/A

Number 830 137 154 118 116 129 176

*p < .05 **p<.01

CONSERV ATION TILLAGE ADOPTION

Table 5 shows regression analyses of conservation tillage adoption variables

on selected characteristics of small and limited resource farmers. These data show

the variables that best predict a number of dimensions associated with the implementation of CT by limited resource farm operators.

Education predicted three of the adoption variables. Respondents with more

years of schooling thought that CT was more practical on their farms, they gave

more reasons for using CT on their operations, and they had actually adopted more

of the CT practices on their land.

Total gross value of sales predicted familiarity with CT and the number of

reasons given. It was not significantly related to the perceived practicality nor the

actual number of practices adopted.

Farm sales as percent of total income was associated with familiarity, perceived practicality, the number of reasons for using CT, and the actual number of

practices adopted. Dependence on farming for livelihood was linked to conditions

associated with the use of CT practices as well as how many were actually adopted.

Black farm operators were significantly less familiar with CT. The equations

explained 10 percent or less in the variation in each of the adoption variables.
16 ALABAMA AGRICULTURAL EXPERIMENT STATION

TABLE 5. R EGRESSION ANALYSIS OF CONSERV ATION TILLAGE ADOPTION VARIABLES

ON SELECTED FARM AND INDIVIDUAL CHARACTERISTICS ,

SMALL AND LIMITED RESOURCE FARMERS , 2000

———————Conservation tillage———————

Familiarity Practicality Reasons Practices

Formal education 0.051 0.096* 0.114** 0.098*

Age 0.038 -0.081 -0.037 -0.054

Total gross value of sales 0.093* 0.029 0.120* 0.066

Your outside work 0.103* 0.011 0.061 0.026

Spouse outside work 0.011 -0.013 -0.041 -0.004

Land 0.075 -0.037 0.020 -0.064

Row crops farmed 0.163* -0.029 -0.080 0.039

Livestock raised 0.088 -0.138* -0.143* -0.034

Poultry raised 0.053 -0.122** -0.056 -0.068

Fruits and vegetables raised 0.114* -0.036 -0.058 0.015

Government assistance 0.069 -0.117* -0.113* -0.012

payments received

Farm operator’s gender 0.019 0.005 -0.024 0.026

Race -0.087* 0.020 -0.068 -0.071

Farming receipts as percent 0.132** 0.183** 0.160** 0.106*

of total income

R

2 0.100 0.059 0.077 0.044

Adjusted R2 0.078 0.036 0.055 0.021

F-value 4.570** 2.598** 3.446** 1.924*

*p<.05 ** p<.01

CROP NUTRIENT MANAGEMENT

More than half of the farmers in this study were familiar with crop nutrient

management, (CNM), Table 6. Around 11 percent were very familiar, but differences were not significant by state or race. Alabama black farmers had the highest

proportion that was not familiar, 43 percent.

A quarter (24 percent) of the sample believed that CNM practices would be

practical on their operation. Mississippi black farmers gave it the highest rating,

42 percent.

There were important differences by state and race in the frequency of soil

testing. By a large margin in each state, more black than white farmers reported

never soil testing. More Georgia farmers reported testing every year. Less than 10

percent of the sample soil tested every year, and about 44 percent of the sample

tested every three years or less often.

Farmers use CNM for a variety of reasons. Overall, 21 percent of the respondents thought CNM would increase crop yield per acre. Reduction in fertilizer

costs motivated other farmers to implement CNM practices, a reason consistently

cited by more whites than blacks. About 12 percent felt that CNM improved crop

quality.
 CORE CONSERVATION PRACTICES 17

TABLE 6. CROP NUTRIENT MANAGEMENT EXPERIENCES AND PERCEPTIONS

BY RACE AND STATE, SMALL AND LIMITED RESOURCE FARMERS , 2000

—Alabama— —Georgia— —Mississipi— –Chi-square–

All White Black White Black White Black State Race

% % % % % % %

How familiar with crop nutrient management (CNM) are you?

Not at all familiar 35 26 43 36 40 36 32

Somewhat familiar 54 63 49 51 48 54 56

Very familiar 11 11 8 13 12 10 11

3.0 2.6

Is CNM practical on your farm

No opinion 55 46 59 48 53 53 45

It would be useful 24 37 31 36 36 33 42

Not very practical 20 17 10 16 11 15 13

1.9 0.3

About how often do you have your soils tested?

Never 34 27 42 15 40 30 46

3 years or more 44 48 47 43 30 48 45

2 years 14 18 8 25 17 14 7

Every year 8 7 3 18 13 8 2

4.8** 39.8**

What are the main reasons you would use CNM in your operation?

Increases crop yields

per acre 21 20 18 20 26 17 26

Reduces fertilizer cost 17 22 11 25 15 19 13

Improves crop quality 12 10 11 7 14 14 14

Better soil and water

conservation 9 12 9 9 7 9 8

Reduces soil erosion 7 6 6 6 5 9 10

Slows water runoff 3 3 2 3 2 4 2

Other 0 0 1 0 1 0 0

N/A N/A

What are the main problems you might have with CNM on your operation?

Equipment costs

too much 12 15 10 10 11 11 16

Information on

“how to do it” is not

readily available 10 9 10 7 9 12 13

It is not cost effective 10 8 9 15 10 8 10

Takes too much

of my time 5 5 5 6 6 6 6

Can’t find enough labor3 1 3 1 5 2 4

Crop yields per acre

are lower 2 2 1 0 1 2 6

I’ve tried CNM and

they didn’t work 1 0 1 0 2 0 1

Other 1 0 1 0 1 1 1

N/A N/A

Number 830 137 154 118 116 129 176

*p < .05 **p<.01
18 ALABAMA AGRICULTURAL EXPERIMENT STATION

TABLE 7. R EGRESSION ANALYSIS OF CROP NUTRIENT MANAGEMENT ADOPTION

VARIABLES ON SELECTED FARM AND INDIVIDUAL CHARACTERISTICS ,

SMALL AND LIMITED RESOURCE FARMERS , 2000

—————Crop nutrient management—————

Familiarity Practicality Reasons Testing

Formal education 0.084 0.200** 0.172** 0.028

Age 0.011 -0.076 -0.041 -0.033

Total gross value of sales 0.035 0.088 0.113* 0.228**

Your outside work 0.001 -0.003 0.021 0.034

Spouse outside work -0.011 0.064 0.062 0.081

Land 0.085 -0.077 -0.013 0.040

Row crops farmed 0.089 0.296** 0.180* 0.251*

Livestock raised 0.121 0.308** 0.236* 0.131

Poultry raised 0.051 -0.045 -0.045 0.020

Fruits and vegetables raised 0.179* 0.178** 0.172* 0.039

Government assistance 0.040 0.096 0.089 0.031

payments received

Farm operator’s gender 0.013 0.082* 0.064 0.027

Race -0.011 0.061 -0.001 -0.099*

Farming reciepts as percent 0.091 0.114* 0.079 0.063

of total income

R

2 0.051 0.109 0.087 0.168

Adjusted R2 0.028 0.087 0.064 0.148

F-value 2.221** 5.055** 3.915** 8.363**

*p<.05 ** p<.01

Around 12 percent of the farmers said that expensive equipment was the greatest problem they had with CNM on their operation. More black farmers felt they

did not have readily available information on how to use CNM. The perception

that CNM was not cost effective kept many of the respondents from using CNM on

their farm. Fifteen percent of white Georgia farmers gave this particular reason.

CROP NUTRIENT MANAGEMENT ADOPTION

Table 7 shows regression analyses of crop nutrient management adoption

variables on selected farm and individual characteristics of small and limited resource farmers. These data show the variables that best predict a number of dimensions associated with the implementation of CNM by limited resource farm operators.

Education predicted two of the four adoption precursor variables, but not

familiarity with soil testing. Respondents with more years of schooling thought

that CNM was more practical on their farms, and they gave more reasons for using

CNM.

Whether or not the respondent farmed row crops predicted perceived practicality, the number of reasons given for CNM use, and the frequency of soil testing.

The variable was not linked to differences in familiarity with CNM. Similarly,

those who raised livestock gave more reasons for using CNM and were more convinced of its practicality. Farmers growing fruit and vegetables were more familiar

with CNM, tended to view it as practical, and gave more reasons for its use.
 CORE CONSERVATION PRACTICES 19

TABLE 8. F ERTILIZER AND CROP ROTATION PRACTICES BY RACE AND STATE,

SMALL AND LIMITED RESOURCE FARMERS , 2000

—Alabama— —Georgia— —Mississipi— –Chi-square–

All White Black White Black White Black State Race

% % % % % % %

Over past five years, has the average amount of commercial fertilizer used per acre on

this operation:

Remained about 62 75 51 75 53 63 47

the same

Increased 19 12 24 11 22 19 21

No fertilizer used 12 5 22 5 17 10 22

in past five years

Decreased 8 8 3 9 8 8 10

10.1 55.1**

When is commercial fertilizer applied?

No fertilizer used 12 5 22 5 17 10 22

in past five years

At planting time 39 48 31 36 40 50 31

Before crops are 39 42 30 52 35 42 37

planted

After crops have 41 42 31 59 40 46 33

come up

(side-dressing)

Through irrigation 1 0 1 1 2 1 1

system as crops

are being watered

N/A N/A

Do you use different amounts of fertilizer in different fields?

No fertilizer used 12 5 22 5 17 10 22

in past five years

Same amount is used 61 68 54 65 55 59 50

Different amounts 21 23 17 27 18 29 19

are used

Don’t know 6 4 7 3 10 2 9

6.8 49.5**

continued

Black farmers had lower frequencies of soil testing than white farmers. There

were no other differences by race on the other adoption variables.

Farm sales, as percent of total income, were associated with the perceived

practicality of soil testing. Those more dependent on farming for their livelihood

knew more about CNM and tested their soil more frequently.

ROTATION AND F ERTILIZA TION PRACTICES

Fertilizer and crop rotation practices of small and limited resource farmers

are portrayed in Table 8. Changes in fertilizer use were significantly different by

race. Approximately 62 percent of all farmers indicated that their commercial fertilizer use had remained about the same over the past five years, although only 47
20 ALABAMA AGRICULTURAL EXPERIMENT STATION

TABLE 8, CONTINUED . F ERTILIZER AND CROP ROTATION PRACTICES BY RACE AND STATE,

SMALL AND LIMITED RESOURCE FARMERS , 2000

—Alabama— —Georgia— —Mississipi— –Chi-square–

All White Black White Black White Black State Race

% % % % % % %

Is litter or manure ever applied to the crop/pasture land that you operate?

No 78 70 87 73 81 74 82

Yes 20 29 12 27 15 25 16

Don’t know 2 1 1 1 4 1 2

1.9 23.7**

How often is chicken litter or animal manure applied on your fields?

Do not use litter 80 68 83 72 80 74 81

or manure

Every 3 years 8 9 5 10 5 9 8

Every 2 years 5 9 4 6 2 7 3

Every year 7 10 3 10 8 9 5

3.8 23.0**

Is more or less commercial fertilizer used after chicken litter or animal manure is applied?

Do not use 80 68 83 72 80 74 81

commercial fertilizer

None is used 3 5 1 4 3 3 2

Less 12 19 6 16 9 14 9

Same 5 4 4 6 3 7 5

More 0 1 1 0 0 1 0

3.7 23.3**

Do you grow the same crops in the same fields year after year or do you rotate between fields?

Do not rotate crops -- 41 36 54 25 28 34 35

Always use the

same fields

Rotate crops 37 39 17 40 45 33 30

Some of each 22 20 10 28 14 28 18

26.3** 17.9**

How often are crops rotated between fields?

Do not rotate crops 41 36 54 25 28 34 36

Varies depending 24 24 8 35 18 32 15

Every year 13 15 6 12 24 9 9

2 years 13 12 10 9 14 9 13

3 years or more 9 8 3 13 3 11 11

37.5** 56.6**

Do you include legumes in rotation?

Do not rotate crops 41 36 54 25 28 34 36

Yes 28 35 10 45 30 36 22

No 16 19 11 13 15 16 19

I do not plant 8 5 6 10 14 8 7

legume crops

32.7** 40.8**

Number 830 137 154 118 116 129 176

*p < .05 **p<.01
 CORE CONSERVATION PRACTICES 21

percent of the black farmers in Mississippi said so. About 19 percent said that their

fertilizer use had increased, though only about an eighth of the white farmers in

Alabama and Georgia said so. Black farmers were much more likely to say that

they had not used fertilizer in the past five years. Previously, the data showed the

black farmers were much less likely to be involved in row crop enterprises where

fertilizer is a central tool.

Almost 41 percent of the sample used side-dressing for the application of

commercial fertilizer, followed closely by application at planting time and before

crops are planted. White farmers tended to use more of each approach to crop

fertilization.

Whites were significantly more likely to adjust the amount of fertilizer they

used in different fields. The basic knowledge for such adjustments comes from

soil testing.

More white than black farmers in each state applied litter or manure to their

fields, a statistically significant pattern. About 27 percent of the white farmers

applied litter or manure compared to about 14 percent of the black farmers. Similarly, more white farmers than blacks used chicken litter or manure and they applied it more often. White farmers were more likely to indicate that they used less

commercial fertilizer after applying litter, a statistically significant pattern.

Crop rotation varied significantly by state and race. Forty-five percent of the

Georgia black farmers reported rotating their crops, compared to 40 percent of the

Georgia white farmers but the pattern was reversed in the other states. Only 17

percent of the black Alabama producers indicated they used crop rotation.

Frequency of rotation also varied significantly by state and race. Most respondents indicated that their crop rotation cycle varied from year to year.

Inclusion of legumes in rotations differed statistically by race and state. Whites

were more likely to include legumes in their rotations in each state, but only 10

percent of black Alabama operators did so.

INTEGRA TED PEST MANAGEMENT

Familiarity with integrated pest management (IPM) varied significantly by

race and state, as shown in Table 9. About half of the sample was not familiar with

IPM. Less than eight percent of the overall sample indicated that they were very

familiar with IPM as a means for controlling weeds, insects, and other threats to

crop yield. Black farmers were less familiar with IPM than white farmers. Black

Alabama farmers were most unfamiliar with IPM compared to other categories of

producers.

About a third of the farmers believed that IPM would be practical on their

operation, but more whites in each state said that it was not very practical. About

three-quarters of the black operators had no opinion.

Only a small number of respondents reported implementing any pesticide

practices. Georgia white farmers reported using more pesticide management practices than any other category of producer.
22 ALABAMA AGRICULTURAL EXPERIMENT STATION

TABLE 9. I NTEGRATED PEST MANAGEMENT PERCEPTIONS BY RACE AND STATE,

SMALL AND LIMITED RESOURCE FARMERS , 2000

—Alabama— —Georgia— —Mississipi— –Chi-square–

All White Black White Black White Black State Race

% % % % % % %

How familiar with integrated pest management (IPM) are you?

Not at all familiar 49 46 64 33 51 40 53

Somewhat familiar 45 45 33 54 44 54 42

Very familiar 7 9 3 13 5 6 5

12.2* 23.0**

Is IPM practical on your farm?

No opinion 31 62 75 48 70 55 74

Not very practical 37 22 12 28 12 31 11

It would be good 32 16 13 24 18 14 15

9.7* 1.1

What are the main reasons you would use IPM on your farming operation?

Reduces use 8 10 5 11 11 10 6

 of pesticides

Increases crop yields 8 7 9 15 6 5 8

 per acre

Better control of 7 7 6 9 10 5 8

insects and

 other pests

Lowers production 3 2 2 6 3 4 3

 costs

Improves water 2 1 3 2 3 2 1

 quality

Maintains soil fertility 1 0 0 2 1 1 1

N/A N/A

What pesticide practices have you implemented on your farm?

Apply pesticides 10 12 5 18 13 6 9

as needed

Use lowest possible 6 5 3 11 8 6 4

application rate

Calibrate application 5 6 1 14 5 4 3

equipment

Use different 5 3 4 10 5 5 2

pesticides to reduce

pest resistance

Use pesticides 5 4 3 10 7 2 4

less harmful

to beneficial insects

Keep records 4 7 1 9 5 3 3

on pesticides used,

rates, and applications

Train workers 2 4 1 3 3 0 1

to properly handle

and apply pesticides

N/A N/A

continued
 CORE CONSERVATION PRACTICES 23

TABLE 9, CONTINUED . INTEGRATED PEST MANAGEMENT PERCEPTIONS

BY RACE AND STATE, SMALL AND LIMITED RESOURCE FARMERS , 2000

—Alabama— —Georgia— —Mississipi— –Chi-square–

All White Black White Black White Black State Race

% % % % % % %

What are the main problems you might have with IPM on your operation?

Chemicals are 6 4 5 5 8 5 7

too expensive

Crop scouting is 4 2 1 7 5 5 3

too expensive

Information on 2 2 1 3 1 4 2

“how to do it”

not available

Equipment needed 2 3 1 1 4 0 3

for IPM costs too much

Reliable crop scouts 2 3 3 3 1 0 1

not available

IPM takes too 1 1 0 3 3 1 0

much time

Tried IPM and 0 0 0 0 0 0 1

it didn’t work for me

N/A N/A

Number 830 137 154 118 116 129 176

*p < .05 **p<.01

About eight percent of the sample said that the main reason for using IPM was

that it reduced the use of pesticides, and a similar proportion thought it increased crop

yields per acre. Seven percent felt that it provided better control of insects and other

pests. The latter reason was particularly important for black farmers in Georgia.

The main problems associated with IPM pertained to the expense of the chemicals and the costs of crop scouting. Overall, less than six percent reported any

single problem.

INTEGRA TED PEST MANAGEMENT ADOPTION

Table 10 shows regression analysis of IPM adoption variables on selected

farm and individual characteristics. The data suggest that farmers with more education were more familiar with IPM and had actually adopted more IPM measures

than farmers with less education.

Age was not related to the IPM adoption variables. Farmers with more farm

sales were more familiar with IPM and gave more reasons for using IPM. Farmers

who worked more days off the farm adopted more IPM practices, but the number

of days the spouse worked off the farm was negatively related to the number of

IPM practices adopted. Those who raised row crops saw IPM as more practical,

indicated more reasons for using IPM, and had actually implemented more IPM

practices on their farms.
24 ALABAMA AGRICULTURAL EXPERIMENT STATION

Farm sales as a percent of total income predicted the four IPM adoption variables. Farmers who were more dependent on farm income were more aware of

IPM, gave more reasons for using it, and had actually implemented more IPM

practices on their farms. The background and farm characteristics explained about

12 percent of the variation in the awareness and adoption variables, but less of the

practicality and reasons variables.

CONSERV ATION BUFFERS

Familiarity with conservation buffers (CB) varied markedly between black

and white farmers, Table 11. Between 10 and 14 percent of the black farmers

indicated that they were very familiar with the concept while between 17 and 31

percent of the white farmers indicated familiarity.

More whites than blacks reported using grass filter strips on their farms. Thirty

percent of white Alabama farmers used grass filter strips compared to seven percent of black Georgia farmers, who used filter strips the least. More white farmers

than black farmers used all the various kinds of conservation buffers.

The perceived practicality of CB varied significantly by race. Whites consistently viewed CB as more useful than black farmers. Alabama white farmers had

the highest rating at 46 percent but only 25 percent of the black farmers in Georgia

thought CB to be useful on their farm.

TABLE 10. R EGRESSION ANALYSIS OF INTEGRATED PEST MANAGEMENT ADOPTION

VARIABLES ON SELECTED FARM AND INDIVIDUAL CHARACTERISTICS ,

SMALL AND LIMITED RESOURCE FARMERS , 2000

————Integrated pest management————

Familiarity Practicality Reasons Practices

Formal education 0.108** 0.037 0.078 0.101*

Age 0.079 0.005 0.057 0.015

Total gross value of sales 0.113* 0.014 0.098* 0.082

Your outside work 0.066 0.072 0.091 0.137*

Spouse outside work 0.055 -0.062 -0.049 -0.099*

Land 0.098* -0.012 0.001 0.066

Row crops farmed 0.085 0.207* 0.206* 0.196*

Livestock raised -0.123* -0.008 -0.073 -0.065

Poultry raised 0.008 -0.033 -0.048 0.002

Fruits and vegetables raised 0.028 -0.015 0.033 0.035

Government assistance -0.070 -0.004 -0.024 -0.055

payments received

Farm operator’s gender -0.040 0.069 0.049 0.029

Race -0.097* 0.141** 0.039 0.010

Farming reciepts as 0.125** 0.095* 0.151** 0.190**

 percent of total income

R

2 0.145 0.072 0.119 0.145

Adjusted R2 0.124 0.049 0.098 0.125

F-value 7.003** 3.187** 5.583** 7.027**

*p<.05 ** p<.01
 CORE CONSERVATION PRACTICES 25

TABLE 11. C ONSERVATION BUFFER PERCEPTIONS BY RACE AND STATE,

SMALL AND LIMITED RESOURCE FARMERS , 2000

—Alabama— —Georgia— —Mississipi— –Chi-square–

All White Black White Black White Black State Race

% % % % % % %

How familiar with conservation buffers (CB) are you?

Not at all familiar 32 22 40 27 35 22 41

Somewhat familiar 51 47 46 51 55 61 47

Very familiar 17 31 14 22 10 17 11

8.1 31.7**

Which CB are currently used on your operation?

Grass filter strips 14 30 8 14 7 23 10

Grass or shrubs

planted on land

that erodes 8 12 8 10 9 7 0

Grass waterways 8 22 5 9 3 9 3

Trees or shrubs

planted for

windbreaks 8 11 8 8 10 6 0

Contour buffer strips 4 6 3 3 2 6 5

Other 0 1 0 1 0 0 0

None 4 4 4 9 3 2 2

N/A N/A

Are CB practical on your farm?

No opinion 44 32 56 31 51 37 55

They would be useful 33 46 26 36 25 39 26

Not very practical 23 22 18 34 24 24 19

4.5 22.1**

What are the main reasons you would use CB on your farm?

Reduce soil erosion 26 41 19 25 18 34 21

Protects soil and

water from runoff 21 30 14 20 17 26 18

Supports more

birds, animals, etc. 8 12 5 14 7 10 6

Reduces pollution 5 4 4 7 5 8 3

Promotes more

hunting and fishing 4 4 4 5 5 6 2

Makes the area

look nicer 3 4 4 3 5 4 2

Other 0 0 0 1 0 0 0

N/A N/A

continued

More than 41 percent of the Alabama white respondents identified reducing soil

erosion as the main reason to use CB, but only 18 percent of the Georgia black farmers

did so. Similar patterns of difference were found for protecting soil and water from

runoff and the creation of habitat for birds and animals as reasons for using CB.

The main perceived problem with CB was that they take too much land out of

production. There were no consistent differences by race, but white farmers were
26 ALABAMA AGRICULTURAL EXPERIMENT STATION

TABLE 11, CONTINUED . CONSERV ATION BUFFER PERCEPTIONS BY RACE AND STATE,

SMALL AND LIMITED RESOURCE FARMERS , 2000

—Alabama— —Georgia— —Mississipi— –Chi-square–

All White Black White Black White Black State Race

% % % % % % %

What are the main problems with CB on your farm?

Takes too much land

 out of production 8 12 6 6 10 14 5

Costly to build and

 maintain buffers 8 12 5 10 6 11 9

Difficult to farm

around buffers 7 10 3 11 6 11 6

“How to” information

not available 4 4 5 3 2 5 5

Other 1 2 1 1 1 1 1

Tried buffers and

they didn’t work 0 0 0 0 0 0 0

N/A N/A

Number 830 137 154 118 116 129 176

*p < .05 **p<.01

more likely to cite most of the problems. The option to indicate that they had tried

buffers and they did not work was provided in the questionnaire, but was not selected by any respondent.

CONSERV ATION BUFFER ADOPTION

Table 12 shows regression analysis of conservation buffer adoption variables

on selected farm and individual characteristic. Education was a significant predictor of the operators’ familiarity with conservation buffers, the number of reasons

for using CB, and the number of practices that had been adopted. Older farmers

were less convinced of the practicality of using CB.

Farmers with more days of outside work had higher scores on each of the CB

adoption variables. Farmers with more acres of land gave more reasons for using

CB.

Those who raised fruits and vegetables were more likely to be familiar with

CB and to give more reasons for using CB. Similarly, those who received more

government payments were more familiar with CB.

Black farmers consistently had lower scores on three of the adoption measures. Black operators were less familiar with CB, gave fewer reasons for using

them, and had actually implemented fewer CB measures on their farms. Neither

gender nor dependence on farm income was related to any of the CB adoption

measures.
 CORE CONSERVATION PRACTICES 27

TABLE 12. R EGRESSION ANALYSIS OF CONSERV ATION BUFFER ADOPTION VARIABLES

ON SELECTED FARM AND INDIVIDUAL CHARACTERISTICS ,

SMALL AND LIMITED RESOURCE FARMERS , 2000

——————Conservation buffers——————

Familiarity Practicality Reasons Practices

Formal education 0.109** 0.066 0.088* 0.140**

Age -0.034 -0.113* -0.065 -0.069

Total gross value of sales 0.09* -0.034 -0.007 -0.005

Your outside work 0.075 0.146* 0.170** 0.131**

Spouse outside work 0.063 -0.029 0.026 0.038

Land 0.079 0.098 0.158** 0.081

Row crops farmed 0.147* -0.093 0.102 0.000

Livestock raised 0.172* -0.080 0.169* 0.036

Poultry raised 0.004 0.074 0.079 0.092*

Fruits and vegetables raised 0.226** -0.068 0.168* 0.069

Government assistance

payments received 0.133* 0.004 0.090 0.060

Farm operator’s gender 0.035 -0.025 0.011 0.016

Race -0.114* -0.040 -0.100* -0.158**

Farming reciepts as

percent of total income 0.043 -0.012 -0.045 -0.026

R

2 0.117 0.073 0.118 0.112

Adjusted R2 0.096 0.041 0.096 0.091

F-value 5.495** 2.293** 5.506** 5.215**

*p<.05 ** p<.01

The four equations explained a significant proportion of the variation in each

CB adoption variable. The adjusted R2 value ranged between 7.3 for practicality to

11.8 for the number of reasons given for using CB.

CONSERV ATION PROGRAM PARTICIP ATION

Approximately 30 percent of the sample reported having conservation plans for

their farms, Table 13. The differences by race and state were not statistically significant.

Of those with conservation plans, about 26 percent indicated that the plan

was fully implemented, and another 27 percent indicated it was three-quarters completed. Differences by race were statistically significant. Whites consistently reported higher levels of conservation plan completion in each of the three states. A

fourth of the black farmers said their plans were less than 25 percent completed.

The Conservation Reserve Program was the most often cited government

program in which respondents participated. Ten percent of Alabama black farmers

participated in the Forestry Incentive Program compared to five percent of the

Alabama white farmers. The rates of participation in the different programs varied

widely across states and race categories, but were most nearly equal in Georgia.
28 ALABAMA AGRICULTURAL EXPERIMENT STATION

The participation rate in the Environmental Quality Incentive Program was

highest among Alabama black farmers, at 11 percent. Georgia black farmers had

the highest participation rate in the Farmland Protection Program at nine percent.

Ten percent or less participated in the Wildlife Habitat Incentive Program, but six

percent of Georgia black farmers were in the Wetland Reserve Program, a rate

twice that for the other states. A tenth of the respondents indicated participation in

the wildlife and wetland programs.

Less than a fifth of the respondents cited a lack of understanding of program

requirements as a reason for not participating in the various conservation programs that were mentioned to them. Mississippi white farmers were least likely to

indicate lack of understanding, at 11 percent, but 23 percent of the Mississippi black

farmers cited a lack of understanding as a reason for not participating.

Half the sample had no contact with Natural Resources Conservation Servie

(NRCS) in the past year, but differences by race and state were not statistically

significant. Mississippi farmers reported the most frequent contacts. Around 40

percent indicated contacts through visits to county offices, a fifth by letter. Georgia had the highest rates of no contact.

Forty percent of Mississippi white farmers had visited an NRCS office compared to 20 percent of Georgia black farmers who had done so. There were no

other consistent patterns of difference by race or state. Mississippi black farmers

were most likely to have received a letter from NRCS (23 percent). White farmers

were more likely to report phone contacts in Alabama and Georgia (around 20 percent), but farmers were slightly more likely to report phone contact with NRCS in

Mississippi.

Respondents were asked to indicate their satisfaction with the information or

services received from NRCS. Overall, 80 percent were very or somewhat satisfied with this conservation agency. Whites were more satisfied than blacks in Alabama and Mississippi. Seventeen percent of Alabama black farmers were dissatisfied compared to seven percent or less in all the other state or race categories.

DETERMINANTS OF NRCS C ONTACT

Table 14 regresses conservation plan and NRCS contact variables on small

and limited resource farm characteristics. Those with more education, more land,

and higher levels of government payments were more likely to have a conservation plan, to have a greater proportion of it implemented, to have more previous

contacts with NRCS, and to express higher levels of satisfaction with the services

they received from the agency.

Farmers with higher gross sales had implemented more of their conservation

plans, had more contacts with NRCS, and were more satisfied with the agency.

Men and those with income from row crops were more likely to have a conservation plan and to have more of it implemented.

Those more dependent on farming for income were more likely to have a

conservation plan and to indicate that they had more of it implemented. They also

had more contacts with NRCS, but were not more satisfied with the agency’s services.
 CORE CONSERVATION PRACTICES 29

TABLE 13. C ONSERV ATION PROGRAM PARTICIP ATION BY RACE AND STATE,

SMALL AND LIMITED RESOURCE FARMERS , 2000

—Alabama— —Georgia— —Mississipi— –Chi-square–

All White Black White Black White Black State Race

% % % % % % %

Do you have a conservation plan for your farm?

No 57 53 67 54 53 54 59

Yes 30 34 24 29 33 33 28

Don’t Know 13 14 9 16 14 13 13

2.5 3.5

About how much of the conservation plan has been implemented?

Less than 25% 16 4 30 6 29 7 20

25% 10 9 16 9 8 12 8

50% 21 17 11 24 32 17 27

75% 27 30 27 35 18 29 24

100% 26 39 16 26 13 36 20

5.9 25.0**

Are you currently participating in any conservation programs?

Conservation Reserve 23 22 13 29 32 19 20

Program (CRP)

Forestry Incentive 11 5 10 9 9 12 11

Program (FIP)

Environmental Quality 8 5 11 4 7 5 0

Incentive Program

(EQUIP)

Farmland Protection 6 3 6 5 9 5 6

Program (FPP)

Wildlife Habitat 10 4 2 3 4 4 3

Incentive Program

(WHIP)

Wetland Reserve 3 1 3 3 6 2 3

Program (WRP)

N/A N/A

Why are you not participating in EQIP?

Don’t understand 16 17 14 13 17 11 23

program

requirements

Other reasons 7 7 6 8 10 8 8

Cannot afford this 7 6 5 8 5 6 10

particular program

EQIP excludes 4 0 6 3 4 3 6

poorer farmers

Application takes 3 1 3 2 2 6 3

too much time

and paperwork

I don’t like this 2 2 1 2 3 2 1

particular program

EQIP is not flexible 2 1 1 3 3 1 1

My county is not 0 1 0 0 1 0 1

eligible

N/A N/A

continued
30 ALABAMA AGRICULTURAL EXPERIMENT STATION

TABLE 13, CONTINUED . CONSERV ATION PROGRAM PARTICIP ATION BY RACE AND STATE,

SMALL AND LIMITED RESOURCE FARMERS , 2000

—Alabama— —Georgia— —Mississipi— –Chi-square–

All White Black White Black White Black State Race

% % % % % % %

How often did you have contact with the NRCS during the past twelve months?

No contact 49 48 51 51 58 43 45

1-2 times 24 28 22 25 21 25 23

3-4 times 15 13 15 14 12 17 14

5+ times 11 8 10 8 9 15 15

10.5 2.2

How was contact made with NRCS?

No contact reported 49 48 51 51 58 43 45

Visit to an NRCS office 28 28 24 29 20 40 30

By letter 16 14 12 9 17 20 23

Received the NRCS 16 20 19 12 7 21 16

Newsletter

Telephone 16 19 14 20 12 15 15

Someone from NRCS 7 7 9 8 6 5 9

visited my farm

Heard an NRCS 4 3 5 2 5 2 8

employee speak

at a meeting

N/A N/A

How satisfied were you with the information or services received from NRCS?

Very satisfied 39 49 33 32 48 38 37

Somewhat satisfied 40 40 36 45 29 41 45

Neither satisfied or 14 9 15 16 19 15 12

dissatisfied

Somewhat dissatisfied 4 3 10 5 2 1 4

Very dissatisfied 3 0 7 2 2 4 1

4.9 2.7

Number 830 137 154 118 116 129 176

*p < .05 **p<.01

The farm and individual characteristics explained around 12 percent of the

conservation plan variables but less than nine percent of the NRCS contact and

satisfaction variables. Having a conservation plan is a linked qualification for many

farm programs associated with crop production. Thus, those more dependent on

crops and income from farming were more attentive to having a conservation plan.

INFORMA TION SOURCES

Respondents were asked to rate a series of information sources on a fivepoint scale as to the importance of each source for making conservation decisions.

Table 15 ranks the sources in terms of the mean importance of each item where a

high score means more important. F-tests of analysis of variance indicate whether

means differ significantly by race or by state.
 CORE CONSERVATION PRACTICES 31

TABLE 14. R EGRESSION ANALYSIS OF CONSERV ATION PLAN AND NRCS C ONTACT

VARIABLES ON SMALL AND LIMITED RESOURCE FARMERS , 2000

———Conservation plan and NRCS contact———

Conservation Percent NRCS NRCS

plan implemented contact satisfaction

Formal education 0.210* 0.179* 0.158** 0.172*

Age -0.019 -0.020 -0.005 0.017

Total gross value of sales 0.029 0.098* 0.105* 0.156*

Your days of outside work 0.041 -0.009 0.073 0.055

Spouse days of outside work 0.045 0.062 0.033 0.002

Land operated 0.102* 0.103* 0.077* 0.088*

Row crops farmed 0.149* 0.186* -0.033 0.080

Livestock raised 0.153* 0.146* 0.042 0.085

Poultry raised 0.009 -0.005 -0.007 -0.022

Fruits and vegetables raised 0.151* 0.099 0.086 0.107

Government payments received 0.234** 0.233* 0.164* 0.159*

Male 0.071* 0.085* 0.041 0.025

Black 0.038 -0.023 0.026 0.003

Farm sales as percent of total income 0.169* 0.135* 0.101* 0.062

R

2 0.140 0.151 0.109 0.112

Adjusted R2 0.117 0.129 0.086 0.088

F-value 6.106* 6.719** 4.636** 4.757**

*p<.05 ** p<.01

The mean importance of the cooperative Extension agent as an information

source varied significantly by race but not by state. Limited resource farmers consistently ranked the cooperative extension agent as the most important information source across states and race categories, except white Alabama farmers. This

segment ranked extension as the second most important source. In each state, black

farmers gave higher importance ratings to extension than white farmers.

Farm magazines or newsletters were the next most important source. Again

black farmers tend to give higher ratings to this source than white farmers, but the

differences were not significant.

The third most important information source was “another farmer or family

member.” This source was particularly important for white farmers in Alabama—

rating even higher than extension for that group, but there were no significant

differences by state or race.

NRCS was fourth ranked as an information source in the overall sample.

Black farmers, particularly in Alabama and Mississippi, tended to give higher ratings to NRCS as a conservation information source but these differences were not

statistically significant.

Farm demonstrations and field days were ranked next. Media information

was particularly important for black farmers in Mississippi and Alabama. The rated

importance of these two information sources differed significantly across race categories.
32 ALABAMA AGRICULTURAL EXPERIMENT STATION

TABLE 15. M EAN IMPORTANCE OF INFORMATION SOURCES BY RACE AND STATE,

SMALL AND LIMITED RESOURCE FARMERS , 2000

—Alabama— —Georgia— —Mississipi— ––F-ratio––

All White Black White Black White Black State Race

mean mean mean mean mean mean mean

How important is each source of information for making decisions about conservation

practices?

Cooperative 3.6 3.5 3.7 3.5 3.6 3.4 3.6 1.0 3.1*

extension agent

Farm magazine 3.4 3.5 3.7 3.1 3.3 3.2 3.6 1.3 2.6

or newsletter

Another farmer 3.3 3.6 3.3 3.1 3.1 3.3 3.3 0.5 0.5

or family member

Natural Resources 3.3 3.3 3.4 3.0 3.1 3.2 3.4 0.5 1.5

Conservation Service

(NRCS)

Farm demonstrations 2.8 2.8 3.1 2.6 2.8 2.4 3.0 2.1 3.5*

and field days

Newspaper, radio, 2.7 2.3 3.0 2.2 3.1 2.4 3.1 1.6 11.7**

or television

Pesticide company 2.4 2.3 2.4 2.2 2.4 2.4 2.5 0.6 0.9

reps or dealer

A banker, community 2.3 2.3 2.5 2.0 2.2 2.0 2.7 0.7 3.8*

leader or farm leader

Private consultant 2.3 2.2 2.3 1.9 2.2 2.2 2.6 1.0 1.6

Internet 2.0 1.9 2.1 1.5 2.2 1.8 2.2 0.8 2.9**

(World Wide Web)

Number 830 137 154 118 116 129 176

*p < .05 **p<.01

Newspapers, radio, and television were significantly more important as information sources for black farmers, but particularly so in Georgia and Mississippi. Differences between black and white farmers were wider on this item than

on any other. Black farmers relied more heavily on the media for their conservation information.

Pesticide company representatives, local leaders, and private consultants were

respectively the next most important information sources as rated by the farmers.

Black farmers consistently rated leaders as more important information sources

than did white farmers, a pattern of differences that was statistically significant.

Low importance was given to the Internet as a source of information, though

blacks consistently rated it as more important than whites, a statistically signifi-
 CORE CONSERVATION PRACTICES 33

cant difference. Other research shows that less than10 percent of farmers have

home access to the Internet, but the rate is much higher among farms with $500,000

or more in annual sales.

INFORMA TION MODE

Table 16 profiles preferences for receiving government information about

conservation. The farmers were presented a list of possible information sources

and asked to mark the ones they preferred. Respondents could check multiple items.

The table rank orders the items in terms of overall percentage of those who selected it.

About 64 percent of the sample indicated that printed materials such as bulletins, newsletters, and other publications was their preferred means of receiving

information. There were no statistically significant differences by race or state.

TABLE 16. C ONSERV ATION INFORMA TION PREFERENCES BY RACE AND STATE,

SMALL AND LIMITED RESOURCE FARMERS , 2000

—Alabama— —Georgia— —Mississipi— –Chi-square–

All White Black White Black White Black State Race

% % % % % % %

How would you like to receive government information?

Printed materials 64 62 68 61 60 74 63 3.1 0.4

such as bulletins,

newsletters, etc.

Direct contact with 41 36 41 41 38 43 44 1.8 0.3

Farm Service Agency

(FSA) offices

Group meetings 18 9 24 14 18 12 27 2.4 19.5**

or seminars

At workshops 16 12 19 10 19 12 24 2.6 14.4**

where I receive

“hands on” training

The news media 14 7 16 13 26 12 15 11.2* 6.5

(radio, TV, newspaper)

By free telephone 13 12 14 8 18 11 14 0.0 3.9

hotline (1-800 number)

Websites on 10 10 9 7 11 13 9 0.4 0.1

the Internet

University specialists 7 4 9 6 11 2 7 2.3 7.6*

Electronic media 7 6 11 3 8 5 7 2.5 6.1*

(videotapes, CD-ROMs)

Teleconference or 2 3 2 0 3 2 1 0.5 0.6

satellite broadcast

at a central location

Number 830 137 154 118 116 129 176

*p < .05 **p<.01
34 ALABAMA AGRICULTURAL EXPERIMENT STATION

Farm Service Agency offices were the next most frequently cited, by 41 percent of the sample. There were no significant differences by race or state.

Black farmers preferred group meetings or seminars more than whites, a statistically significant difference. Similarly, blacks preferred workshops more than

whites did.

The news media was preferred as an information source by black Georgia

farmers. News media preference differed significantly by state. There were no

differences in preference for toll-free hotlines or websites.

Black farmers did prefer university specialists as information sources more than

white farmers. They also preferred electronic media for home use such as videotapes

more than white farmers. Both differences were statistically significant. Whites preferred news media more than blacks, a statistically significant difference.

LAND AND WATER RESOURCES

Getting conservation on the ground is a difficult task for public agencies serving

a diverse population of resource owners with many different orientations and capabilities of following recommended land treatment strategies. Table 17 suggests that the

many small farm operators in the region control a substantial amount of land resources.

Acres own differed statistically by race and state, but particularly by race.

More white farmers reported owning larger acreages in each state. Most of

the respondents in our sample had between 50 and 179 acres, although 41 percent

of Alabama black-owned farms were between 10 and 49 acres in size. More Georgia white farmers had larger holdings and more Mississippi black farmers owned

farms less than 50 acres in size. Nine percent owned no land. Slightly more blacks

than whites in each state owned no land.

A third of the sample rented land from other farmers, but the pattern of differences was not statistically significant. More Mississippi and Alabama black farmers rented land from others, but more Alabama farmers of both races rented land

from others than did farmers in other states.

Roughly 10 percent of the small and limited resource farmers rented land to

others, although Georgia farmers of both races were slightly more likely to rent

out land. This pattern was statistically significant by race.

The net acres operated were computed by summing the acres owned plus the

acres rented from others, minus the acres rented to others. The modal category for

land operated was 50 to 179 acres except for Georgia black operators who most

frequently cited 10 to 49 acres as the category of net acres operated. Differences

by race and state were each significant, but the largest contrasts were between

races.

The last item in the table shows the water bodies found on the respondents’ farm,

rank ordered in the frequency that the item was selected in the overall sample. Creeks

or streams were the most frequently reported on-farm water resource. Nearly half the

farmers had a creek or stream on their property, but about 30 percent had no water

body or watercourse on their land at all. Forty-one percent of the Georgia black farmers said they had no water bodies on their land, but only 17 percent Mississippi white
 CORE CONSERVATION PRACTICES 35

TABLE 17. L AND AND WATER RESOURCES BY RACE AND STATE,

SMALL AND LIMITED RESOURCE FARMERS , 2000

—Alabama— —Georgia— —Mississipi— –Chi-square–

All White Black White Black White Black State Race

% % % % % % %

How many acres do you own?

None 9 6 11 6 8 9 12

1-9 acres 7 7 8 4 6 2 12

10-49 acres 27 26 41 13 33 16 28

50-179 acres 40 39 34 46 39 48 38

180-499 acres 15 17 5 26 11 23 9

500 acres or more 3 5 1 5 3 2 1

26.6* 61.1**

How many acres do you rent from others, included land used rent free?

None 60 57 56 68 67 62 56

1-9 acres 4 4 3 5 3 3 3

10-49 acres 17 17 23 10 20 16 15

50-179 acres 16 19 14 11 8 15 23

180-499 acres 3 2 4 5 2 3 3

500 acres or more 1 1 0 1 1 2 0

15.3 6.1

How many acres do you rent to others?

None 90 91 97 83 89 91 95

1-9 acres 1 2 0 1 2 0 1

10-49 acres 3 2 1 4 3 2 4

50-179 acres 6 5 1 12 5 8 1

180-499 acres 0 0 0 0 1 0 0

17.2 17.7*

What are the net acres you operate?

1-9 acres 4 1 4 3 2 2 7

10-49 acres 26 22 39 13 42 16 23

50-179 acres 48 50 47 51 38 47 55

180-499 acres 19 20 9 27 15 32 14

500 acres or more 3 6 1 6 3 3 1

19.6* 57.2**

Waterbodies on farm

None 31 30 30 29 41 17 30

Creek/stream 44 45 47 42 35 61 35

Drainage ditch 23 21 24 13 12 28 35

Wetlands 10 7 14 19 9 10 6

Swamp 9 7 9 12 10 10 5

Lake 8 9 7 17 6 9 5

Waterway 3 2 4 8 1 1 3

River 3 6 1 3 1 3 2

N/A N/A

Number 830 137 154 118 116 129 176

*p < .05 **p<.01
36 ALABAMA AGRICULTURAL EXPERIMENT STATION

farmers said they had none. More than a third of the Mississippi black farmers reported

drainage ditches on their farms, the highest proportion across the states.

CONCLUSIONS

The first objective of this study was to profile the core conservation practices

utilized by small and limited resource farmers in Alabama, Mississippi, and Georgia. Research shows that conservation tillage is familiar to three-fourths of the

farmers in each state, although not at all familiar to a large proportion of black

farmers. A fifth of all the farmers viewed conservation tillage as not practical on

their farms. A fifth cited weeds and herbicide costs as main CT problems. These

data suggest that many farmers have been reached by the efforts of NRCS, extension, and other public agencies, but they also suggest that many have not been

supplied with the CT solutions that fit their farm situations. A lack of how-to information was more often cited by black farmers as a barrier to performing conservation techniques on their operations.

Nutrient management awareness and implementation is probably best indicated by the regular practice of soil testing on a farm. Soil testing is a fundamental

step in economically sound and environmentally responsible farming. A third of

the sample never engaged in soil testing. Given that seven of eight small and limited resource farmers used commercial fertilizer, and that about one in five used

broiler litter on the land, the information from a soil test is a basic part of making

nutrient management decisions. Reaching the unaware and the uncommitted with

the basic precepts of land management will require an extended effort of outreach

and technical support.

Integrated pest management is not a widely understood concept among small

and limited resource farmers in Alabama, Georgia, and Mississippi. About half the

sample was not familiar with the term and only a third thought it would be good

for their farm operation. Alabama black farmers were most unfamiliar with this

technique. Conservation buffers represented the most traditional and well-known

category of soil and water protection interventions. Nonetheless, a third of the

farmers were not familiar with the term and only a third thought these measures

would be useful on their farm. Alabama producers were most familiar with this

class of interventions and most convinced of their usefulness.

Another objective of the study was to compare the conservation practices and

perceptions of black and white small and limited resource farmers in Alabama,

Georgia, and Mississippi. Black and white limited resource farmers who participated in the study differed in a number of basic ways. More black farmers had less

than a high school education and more white farmers tended to grow row crops

and engage in other more intensive farm enterprises. Many of our survey respondents of both races had college educations and advanced degrees, pointing to the

rapidly growing segment of part-time, hobby, and lifestyle farm residents that may

have felt and unfelt needs for guidance on land treatment strategies. The challenge

to public agencies is to provide timely and appropriate responses to the felt needs
 CORE CONSERVATION PRACTICES 37

for technical assistance. In addition, the agencies must find a way to stimulate a

demand for conservation assistance by increasing awareness of the practical tools

that are available for protecting soil resources and water quality.

The data also pointed to the diversity within the small and limited resource

farm segment of the farm population. Some small and limited resource farmers

were poor; some were pensioned; some were prosperous by other means. Any

initiatives to expand adherence to core conservation principles and increase participation in conservation programs must begin by recognizing this diversity.

A third objective was to identify perceived barriers and disadvantages to the

implementation of core conservation practices. Each set of core conservation practices has obstacles to implementation by the full gamut of small and limited resource farms. Some obstacles reflect defects and limits in the outreach mechanisms of the public agencies. Some reflect limits in the applicability and fit of the

recommended practices on each individual small and limited resource farm. Other

obstacles to implementation bear on the interests and capabilities of the individual

farm operator. Lifecycle stage, personality, financial capability, and technical capacity all shape an individual farm operator’s ability to consider and use the interventions recommended by NRCS and other public agencies.

Nonetheless, the data revealed a large segment of operators who had no contact with NRCS or other public agencies. It was not that core conservation practices have been tried and found wanting on these farms; rather, they have been

found wanting to be tried. It was a statistical reality that the overall number of

farms tended to decline in the past decades, but now the number of small and

limited resource farms are increasing due to better counting methods and the growing number of part-time, lifestyle, and hobby farms.

Marketing core conservation to small and limited resource farmers will require mass mailings and other methods to reach farmers not regularly participating

in NRCS and other public agency land and water programs (Lovejoy, 1999). There

are myriad of reasons why individual producers have not participated in programs.

Mass approaches may lead some to seek NRCS technical assistance, but others

will require one-on-one personal interaction to realize the possibilities of core conservation principles on their land.

The fourth objective of the study was to describe patterns of information

source utilization and preferences among small and limited resource farmers. The

data suggested that farmers remain wedded to printed materials as a fundamental

source of reference information for their conservation decisions. Although information technology is rapidly changing, most small and limited resource farmers

will require simple and direct technical materials to implement core conservation

measures. The demand for the materials is clearly present, but farmers may not be

aware of the actual supply of information that is available or how to access it.

Targeted mailings to small and limited resource producers might provide publication lists highlighting the information that is available upon request (Napier et al.,

2000).
38 ALABAMA AGRICULTURAL EXPERIMENT STATION

It is also clear that NRCS must rely on the goodwill and respect that farmers

have for other farm agencies, particularly the Cooperative Extension Service, that

are already well-regarded and familiar to farmers. Although no public agency is

without its limits, NRCS’ conservation partners often have access to and relationships with small and limited resource farmers that would be difficult or inefficient

to duplicate.

NRCS has ongoing efforts to develop working relationships with community-based organizations and educational institutions that could help communicate

programs to small and limited resource farmers. Other public agencies and nongovernmental organizations might help overcome cultural and language differences that sometimes interfere with minority participation in farm programs. These

partners can help address the special needs of small-scale and limited-resource

enterprises in implementing the technological improvements, alternative enterprises, and conservation measures that protect the land and enhance water

quality.When NRCS is perceived as addressing the primary needs of small and

limited resource farm communities, producer interest in conservation measures is

likely to increase.

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