Increasing Efficiency and Decision-Making Capability of Small, Socially Disadvantaged, and Minority Farmers

Progress report for ONE21-394

Project Type: Partnership
Funds awarded in 2021: $29,957.00
Projected End Date: 11/30/2022
Grant Recipient: University of Maryland Eastern Shore
Region: Northeast
State: Maryland
Project Leader:
Dr. Lila Karki, PhD
University of Maryland Eastern Shore
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Project Information

Project Objectives:

This project seeks to achieve the following objectives:

  1. To strengthen farmers’ technical and economic efficiency: The project will investigate the factors inhibiting small, socially disadvantaged, and minority (SSDM) farmers from allocating resource efficiently and making informed decisions. Through the interventions, the farmers’ capacity will be strengthened to maintain farm data digitally, analyze and interpret the results, and compare their farm performance with a frontier level of production. Moreover, the findings will guide them to develop a farm business plan that will help SSDM minimize factors causing inefficiency through hands-on training, an interactive online learning platform, and farm data recording and analysis. 
  2. To study the scope and market potentials of specialty crops: The project explores a course of action on how SSDM farmers can increase their household income from agriculture. Most SSDM farmers are devoid of enough knowledge of high risk-bearing and decision-making capacity to afford and scale up to mechanized farming. Hence, this project will conduct market surveys of specialty crops (fruits, vegetables, and medicinal plants) in various counties of Maryland. The findings will furnish SSDM farmers with market price information, local demand, supply potentials, and niche markets to develop a marketing plan for specialty crops and their linkage with the potential markets. 
Introduction:

Small, socially disadvantaged, and minority (SSDM) farmers across Maryland have been at the crossroads of survival in their agricultural profession. The SSDM farmers have been daunted due to ever-increasing challenges while striving to make their living from the farm, a source of sustainable household income. Despite the significance of small-scale farms, the evidence suggests that they are declining in number. On the one hand, a significant portion of small-scale producers have been abandoning farms they have inherited and farms they owned. On the other hand, the next generation seems to be reluctant to jump into the agricultural profession. According to GICA (2011), the trend of abandoning farms in Maryland has been increasing for 40 years. Gardner (2002) revealed that the average Maryland farm operator is 54-years-old, –showing that new replacement farmers are needed to prevent the declining farming trend. With a decreasing agricultural land base, –farmland has become more expensive than before for those younger farmers aspiring to get into agriculture. The loss of farmland also dries up markets established to sell commodities to other farmers in the area. Therefore, local farm employment no longer exists. The economic sustainability of the SSDM farmers, who work hard to supply fresh produce to our kitchen tables, is in a vulnerable situation. The GICA (2011) stated that due to brokers’ influence, high transaction costs, and lack of direct access to market outlets, the farmers’ share of the retail food dollar has decreased, with farmers receiving only about $0.20 out of each food dollar spent by consumers. The willingness of the SSDM farmers to be successful in agriculture is greatly challenged by the lack of demand-driven knowledge and skills, no easy access to hands-on and experiential learning opportunities, lack of market information and market access, and lack of continuous outreach and education. Dill et al. (2012) mentioned that marketing and financing were among the high-ranking issues reported by beginning farmers in Maryland.

 Considering the problems stated above, this project seeks to perform the following activities: i) needs assessment, ii) hands-on training on the basics of production economics and farm management, iii) farm data recording and analysis, iv) specialty crop market surveys, v) production of educational materials, and vi) the development of a farm business plan.

The proposed activities directly support sustainable agriculture aspects to improve the productivity of specialty crops; reduce production costs; increase net farm income; enhance employment opportunities in rural communities; and enhance the quality of life for farmers, and the farm community.

It is expected that the knowledge, aspirations, skills, and attitudes of the SSDM farmers, participating individuals in the community, farmer groups/organizations, and community people will be strengthened. The increased knowledge will lead them to maintain and analyze farm records, make informed decisions, and prepare and execute data-driven production and marketing plans. Consequently, the target clientele will be able to increase their farm household income as a direct impact, and local employment and the well-being of the community as an indirect impact. 

Cooperators

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Research

Materials and methods:

The project plans to apply the following materials and methods to achieve the stated objectives. 

Objective 1: The following six activities will be carried out:

i) Selection of specialty crop SSDM farmers: Fifteen cooperating farmers will be recruited as working farmers (13 have already shared their commitment letters) in the project. The project will recruit two more farmers later to work in the project, as a few farmers attached to the community gardens have already shown their interest in participating.

ii) Conducting a need assessment: A brief situation analysis/needs assessment of the recruited farmers will be done to prepare a need hierarchy using the SWOT (strengths, weaknesses, opportunities, and threats) tool and SMART (specific, measurable, achievable, realistic, and time-bound) technique. Simultaneously, in-person interaction will be adopted while assessing the needs of SSDM farmers as recommended by Dill et al. (2012).

iii) Providing support services: Support for a few production inputs (specialty crop seeds/seedlings, insect screen mesh, scale, fees for renting 3 acres of land as applicable; an acre each for 3 farmers based on the need to expand their specialty crop production) will be provided to cooperating farmers as a token for initiating/encouraging/promoting small-scale specialty crop farming. This kind of incentive will encourage them to let the farm use as a demonstration site in the community, a fresh supplier to the homes, a way of adopting healthy food habits, a means of creating spillover effect over to the adjacent community, and an initiative of developing a saving habit in the long run through fresh production from own garden and farm.

iv) Organizing hands-on training: Transferring technical and managerial knowledge by conducting hands-on trainings/workshops and personal counseling to fill the gap of knowledge and skills. Through this event, their knowledge and skills about the basics of production economics and farm management will be strengthened in the least cost production approach, farm planning and budgeting, farm revenue maximization, agricultural risk mitigation, farm data recording and analysis, and business planning and entrepreneurship development.

v) Introducing farm data recording and analysis: Input-output analysis is another essential component, next to hands-on training, to running a farm business successfully. One of the aspects lacking in SSDM farming has been data recording and analysis. Without having proper farm data, it is difficult to be successful at farming. Practically, farming is a business that often passes from generation to generation. To enable cooperating farmers to make informed decisions, they will be provided with tablets to execute a data recording and analysis activity as a pre-requisite to farm business planning. A digital data recording link will be provided to monitor the activity regularly while using an automated basic analysis (gross and net margin, factor productivity, sensitivity, and break-even) to mirror the situation of their farm activity.

vi) Preparing a data-based farm business plan: Cooperating farmers will be encouraged and supported in developing their short- medium- and long-term farm business plan using the analyzed results. Farmers will be able to predict their farm revenue by applying different scenarios, a supply function in the foreseeable future, and adjusting the plan accordingly. 

The project will apply purposive sampling in order to select at least two more specialty farmers who were not able to submit a letter of commitment. Once we have 15 cooperating farmers, the project will group them according to their specialty crop commodity and work accordingly. A farm tour/visit will be organized to give them exposure to a model farm/agri-business/specialty farm to pursue the scope and opportunities for developing and operating a specialty crop farm sustainably. Since the project will work with a limited number of specialty crop farmers, community gardens, and/or other types of small production systems, it will apply a case study approach to measure the outcomes of the interventions based on the commodity (fruits, vegetables, and medicinal plants). A before versus after evaluation approach will be used to measure the impact of the Objective 1 interventions on cooperating farmers participating in the project. A pre- and post-training Likert scale survey instrument will be used to assess the change in knowledge, aspiration, skill, and attitude of the participants as a result of hands-on training, a farm visit, and personal counseling. The findings of the project will be prepared and presented both in quantitative and qualitative formats. 

Objective 2: The following six activities will be implemented under this objective.

i) Identification of specialty crop counties: Using the USDA specialty crops classification, counties will be identified based on the intensity of specialty crops grown (fruits, vegetables, and medicinal/herbal plants). The area under cultivation and types of specialty crops will be the two major criteria for identifying the counties.

ii) Identifying specialty crop markets: Markets will be identified across the state irrespective of their volume of transactions and the nature of the operation (full-time, part-time, and seasonal) as the project intends to explore the scope and opportunity of such markets in the counties. Such markets could possibly be niche, farmers, fresh, contract, cooperatives, mobile, ethnic, direct, school feeding, and others (grocers/retailers).

iii) Develop a market survey: A semi-structured questionnaire with open- and close-ended questions will be designed and tested before introducing it to the specialty markets. The questions will be about price, volume of sales/demand, the supply situation, margin (possibly the experience), supply sources, most sold specialty crops (fruits, vegetables, and medicinal plants), and their prospects from the marketers’ perspective.

iv) Conduct market surveys: The survey will be introduced to specialty crop markets selected randomly in various counties in Maryland. However, the number of responding markets will depend on the number of identified specialty markets (N) and the markets willing to participate (n) to fill out the survey. Zealously, the project will survey as many markets as possible to infer representative conclusions.

v) Analyze market information and compare with available secondary information: The data collected from market surveys will be analyzed applying the most suitable statistical tools (descriptive statistics), correlation (intra and inter-market price relationship), and t-or chi-square tests (comparing the means of market price and secondary data). In addition, the project will apply inferential statistics to investigate the factors influencing such markets to exist, operate, and be sustained in the local community.

vi) Application of market information: The most immediate use of analyzed market information is to enable the cooperating farmers to develop a strategic marketing plan based on their farm production plan. The market study will help them review the production plan (stated in Objective 1) and revise and adjust the production plan using the available price information of specialty crops in various markets following the SMART technique. Thus, cooperating farmers as producers and suppliers will be able to predict the foreseeable future of selected specialty crops, marketing scenarios, and cash flows.

Based on analyzed market information (Objective 2) and the analyzed farm data (Objective 1), the project will organize a workshop focusing on the economic potential of specialty crops to delineate the scope, opportunities, and prospects. The cooperating farmers will work as resource personnel of the study at the workshop/training. Thus, the project will give cooperating farmers an insight into farm business planning, marketing strategies, personnel management, and passing the profitable farm operation to the next generation.

Participants at the Project Orientation, Farmers' Needs Assessment, and Project Planning Workshop in Parkville, MD on 02/11/2022
Research results and discussion:

Project description:

The goal of this project is to enhance the technical and economic efficiency of small, socially disadvantaged, and minority (SSDM) farmers through learning of making informed decisions, developing a farm business plan, adopting economically sustainable practices, and optimizing farm revenue. 

Introduction

This annual progress report (2021) - starting in August and ending in December, elucidates the tasks accomplished by the research team up till now (January 2022). To be brief, of the several activities proposed, the research team has already accomplished the following activities:

Under objective 1:  

i) Selection of specialty crop SSDM farmers:

Fifteen incorporating farmers for the project have been recruited.

ii) Conducting a need assessment:

Needs assessment survey was designed, pre-tested, and a need assessment of the recruited farmers was conducted. A brief findings of the needs assessment surveys is presented below.

Methodological approach:

The research team at the University of Maryland Eastern Shore (UMES) with the financial support from Northeast SARE conducted an exploratory case study to investigate the situation and scope of urban agriculture. The research team in collaboration with the UMES researchers and local farmers identified 14 small, socially disadvantaged, and minority (SSDM) farmers from four counties, namely, Anne Arundel, Baltimore, Somerset, and Wicomico of Maryland state. A semi-structured survey that was designed to collect farmer’s background information, farming experience, size and scale of farming, reasons for farming, problems identification (in a 5-point Likert scale) and needs analysis (in a 5-point rating scale) was administered to 14 farmers. These farmers were identified as urban agriculture (UA) and community gardening (CG) farmers. The instrument consisted of a five-point Likert scale, open- and close-ended, multiple-choice, rating scale, and demographic questions. In addition, the researchers also conducted an in-person interactive workshop, online survey, email and telephone communications, and farm-field visits.

Analytical approach

The data collected through the quantitative survey was examined using the Excel and SPSS software. Because the study is exploratory in nature, at this stage, the research team primarily focused on descriptive results. The results are described below.

Results and Discussions

Farmers’ background characteristics

Fourteen farmers from four counties, Anne Arundale, Baltimore, Baltimore City, Somerset and Wicomico were conveniently/purposively selected (Table 1). A large majority of them were from Baltimore (42.8%) and Somerset counties (36%). These farmers belonged to a diverse group of ethnic minorities: Hispanic/Latino (7%), White/Caucasian (7%), Non-Hispanic/Latino (7%), African American (15%), and Asian (64%). Thirty-six percent of them were women. Their age ranged from 26 to over 60 years. 

Table 1: Background Characteristics of Farmers (n=14).

Characteristics

N

Percent

Gender

 

 

   Female

5

35.7

   Male

9

64.3

Age Group

 

 

   26-34

2

14.3

   35-44

5

35.7

   45-50

1

7.1

   51-59

5

35.7

   Over 60

1

7.1

County of Residence

 

 

   Anne Arundel

2

14.3

   Baltimore

6

42.8

   Somerset

5

35.7

   Wicomico

1

7.1

Race/Ethnicity

 

 

   Black or African American

2

14.3

   Hispanic or Latino

1

7.1

   White

1

7.1

   Asian

9

64.3

   Non-Hispanic Latino

1

7.1

Farmer Types and Farming Experiences

According to Table 2, nearly 86 percent of the farmers reported that they were seasonal farmers and only 14 percent reported they were part-time farmers. Among the 14 farmers, 50 percent had more than 10 years of experience in farming followed by 36 percent with 1-5 years of farming experience. Nearly 86 percent of them reported that they farmed in backyard kitchen garden and the remaining 14 percent reported they farmed in community garden. Over 71 percent of the farmers reported that they do not keep any farm records. The average size of the farm was only 1.20 acres (with a median size of 0.38 acres) that ranged from 0.06 acres to a high of 11 acres (only one farmer).

Table 2: Farmer Types and Farming Experiences (n=14).

Characteristics

N

Percent

Involvement Type

 

 

   Part-time

2

14.3

   Seasonal

12

85.7

Farming Experience

 

 

   1=Under 1 year

0

0

   2=1-5 years

5

35.7

   3=6-10 years

2

14.3

   4=More than 10 years

7

50.0

Scale/type of Farming

 

 

   3=Backyard kitchen garden

12

85.7

   4= Community Garden

2

14.3

Keeps farm record

 

 

    Yes

4

28.6

    No

10

71.4

Reasons form Farming

Table 3 revealed that 79 percent, each, reported that the primary reasons for farming were outdoor and physical activity and produce for family consumption. Fifty-seven percent of them reported that the primary reasons was for supplemental income, which was followed by time pass (50%), education (14.3%) and for tax benefits (only 7%).

Table 3: Primary reasons for farming (n=14).

Reasons

N

Percent

Time pass

7

50.0

Outdoor and physical activity

11

78.6

Produce for family consumption

11

78.6

For supplemental income

8

57.1

For tax benefits

1

7.1

Educational purpose

2

14.3

Farm Enterprises

A large majority (93%) of the farmers reported that they cultivated vegetables (Table 4). Nearly 36 percent of them reported fruits, followed by 14 percent (2 farmers) raised poultry, and one farmer each (7%) reported animal and duck.

Table 4: Did you grow any vegetables, fruits or raise animals (n=14).

Farmers cultivated

N

Percent

Vegetables

13

92.9

Fruits

5

35.7

Peacock

1

7.1

Poultry

2

14.3

Ducks

1

7.1

Medicinal/herbal plants

4

28.6

Flowers

2

14.3

Shell

1

7.1

Interestingly, one farmer reported cultivating a maximum number of 16 vegetable crops. The top five most commonly grown vegetables were tomato, spinach, beans, eggplant and chili (Appendix 1). Apple, pear and fig were the fruit crops reported. Poultry, ducks and peacock were the birds. The list of vegetables, fruits, specialty crops, ethnic/minority and herbal medicinal plants reported by farmers are provided in Appendix 1 through 5, respectively.

Problems experienced by farmers

Table 5 below shows that types of problem, how important is it, and the average index, which shows the rank or the hierarchy of each problem (the higher the index average the more important is the problem).

Table 5: Problems experienced in the farm enterprise (n=14).

 

 

Level of importance (number, percent)

Problems

1. Not at all important

2. Slightly

important

3. Moderately

important

4. Very

important

5. Extremely

important

Index

Lack of capital

1 (7.1%)

1 (7.1%)

0

1 (7.1%)

11 (78.6%)

4.4

Lack of access to land

0

2 (14.3%)

0

2 (14.3%)

10 (71.4%)

4.4

Not enough land

0

1 (7.1%)

1 (7.1%)

3 (21.4%)

9 (64.3%)

4.4

Lack of access to credit

1 (7.1%)

1 (7.1%)

0

2 (14.1%)

10 (71.4%)

4.4

Lack of family labor to support farming

2 (14.3%)

7 (50.0%)

1 (7.1%)

2 (14.1%)

2 (14.3%)

2.6

Lack of farm business planning

0

1 (7.1%)

8 (57.1%)

5 (35.7%)

0

3.3

Lack of production knowledge and skills

0

1 (7.1%)

2 (14.3%)

9 (64.3%)

2 (14.3%)

3.9

Not enough farm management skills

0

1 (7.1%)

4 (28.6%)

7 (50.0%)

2 (14.3%)

3.7

Lack of knowledge about basics of farm economics

0

1 (7.1%)

4 (28.6%)

9 (64.3%)

0

3.6

Lack of direct access to markets

0

2 (14.3%)

6 (42.9%)

4 (28.6%)

2 (14.3%)

3.4

Lack of agricultural knowledge and skills

0

3 (21.4%)

5 (35.7%)

4 (28.6%)

2 (14.3%)

3.4

Lack of produce processing facility and skills

0

6 (42.9%)

6 (42.9%)

2 (14.3%)

0

2.7

Lack of access to relevant educational materials

0

7 (50.0%)

2 (14.3%)

5 (35.7%)

0

2.9

Lack of farm records

0

5 (35.7%)

2 (14.3%)

4 (28.6%)

3 (21.7%)

3.4

Lack of farm data analytical skills

1 (7.1%)

3 (21.4%)

3 (21.4%)

6 (42.9%)

1 (7.1%)

3.2

Shortage of labor in the market

0

9 (64.3%)

3 (21.4%)

2 (14.3%)

0

2.5

Lack of access to internet

1 (7.1)

1 (7.1%)

0

2 (14.3%)

10 (71.4%)

4.4

Lack of information to start farming

1 (7.1%)

1 (7.1%)

0

11 (78.6%)

1 (7.1%)

3.7

Cannot afford for farm machinery

0

2 (14.3%)

0

1 (7.1%)

11 (78.6%)

4.5

Lack of access to market and sales outlets

0

2 (14.3%)

2 (14.3%)

7 (50.0%)

5 (21.4%)

3.9

Lack of access to a farm mentor

0

3 (21.4%)

0

9 (64.3%)

2 (14.3%)

3.7

Of the identified 21 problems, farmers grouped them in a hierarchy of 12 clusters based on index values that were reported using a 5-point Likert scale. The average indices show that – they cannot afford for farm machinery and equipment with 4.5 score was on the top followed by a lack of capital (4.4), access to land (4.4), credit (4.4), internet (4.4), and not enough land (4.4). Other problems followed a lack of direct access to markets and sales outlets (3.9) and production knowledge and skills (3.9). The least important problems reported were access to relevant educational materials (2.9), products processing facility and skills (2.7), family labor to support farming (2.6), and shortage of labor in the market (2.5). Both preference ranking and problem hierarchy approaches demonstrated the importance of the problems in similar direction.

Timing of Training

Reducing knowledge gap of small-scale, minority, and beginning farmers is of paramount for their sustenance in farming. One-half of the participant farmers revealed a preference for multi-session weekend workshops compared with 36% multi-session weekday workshops (Table 6). Likewise, 29% of them favored a daylong weekend workshop over a daylong weekday workshop. The results imply farmers preference in weekend training programs than the weekday programs. Moreover, participants preferred shorter but multiple weekend session over a single daylong event.

Table 6: Program reported by participants to increase their farming knowledge and skills (n=14).

Programs

N

Percent

One-day weekend workshop

4

28.6%

One-day weekday workshop

2

14.3%

Multi-sessions weekday evening workshops

5

35.7%

Multi-sessions weekend workshops

7

50.0 %

Learning Modules and Educational Materials Need for Minority and Beginning Farmers

Of the listed 13 learning modules and educational materials, farmers ranked them in eight categories considering in a five-point Likert scale - extremely useful (5) to least useful (1) (Table 7). The descending index value shows their preference: digital learning video (4.3), comprehensive training manual (4.2), one-to-one consultation, peer-to-peer interaction, and hands-on training (3.7), Extension publications (factsheet, flyer, brochure, pamphlet, and newsletter (3.6)), webinar, interactive meeting, workshop and training, and YouTube video (3.5), farm visit/tour, field days, and one-to-one counseling (3.4), virtual presentations/learning (3.1), and the least useful learning module was a radio or tv program (2.7). 

Table 7: Programs participants report of most useful learning models/materials to increase their farming knowledge and skills (n=14).

 

 

Level of usefulness (number, percent)

Learning Models/Materials

1. Least useful

2. Slightly

useful

3. Moderately

useful

4. Very

useful

5. Extremely

useful

Index

 

Digital learning video

0

1 (7.1%)

0

7 (50.0%)

6 (42.9%)

4.3

 

Comprehensive training manual on farm business management of agricultural enterprise

0

1 (7.1%)

0

8 (57.1%)

5 (35.7%)

4.2

 

Peer-to-peer interaction

0

4 (28.6%)

0

6 (42.9%)

4 (28.6)

3.7

 

One-one consultation

0

4 (28.6%)

0

6 (42.9%)

4 (28.6%)

3.7

 

Webinar/Interactive meting/Workshop/Training

0

4 (28.6%)

1 (7.1%)

7 (50.0%)

2 (14.3%)

3.5

 

Farm visit/tour

0

5 (35.7%)

0

7 (50.0%)

2 (14.3%)

3.4

 

Field days

0

3 (21.4%)

4 (28.6%)

5 (35.7%)

2 (14.3%)

3.4

 

One-one counseling

0

5 (35.7%)

0

8 (57.1%)

1 (7.1%)

3.4

 

Hands on training

0

2 (14.3%)

1 (7.1%)

10 (71.4%)

1 (7.1%)

3.7

 

YouTube or Video

0

3 (21.4%)

2 (14.3%)

8 (57.1%)

1 (7.1%)

3.5

 

Radio or TV program

0

9 (64.3%)

1 (7.1%)

3 (21.4%)

1 (7.1%)

2.7

 

Extension publications (Fact sheet, Flyer, Brochure, Pamphlet, Newsletters)

0

2 (14.3%)

3 (21.4%)

8 (57.1%)

1 (7.1%)

3.6

 

Virtual presentations

0

5 (35.7%)

3 (21.4%)

6 (42.9%)

0

3.1

 

Learning Resources of Minority and Beginning Farmers

Participants ranked the importance of seven learning resources to update, build, and strengthen their knowledge gap. In a five-point Likert scale they ranked–most preferred (5) to the least preferred (1). Partnership with local farmers' markets, local food chain, and the community garden was on the top with an average of 4.0. Subsequently, farmers’ organizations (e.g., farmers’ group, commodity group, farmers’ association) and educational events (interactive workshops and meetings, hands-on training, farmers’ conference (3.9)), incubator farms, and in-person training and education (e.g., consultation and counseling (3.8)), digital training materials, for instance video (3.5), and virtual training such as farmers’ school (3.4) were ranked in descending index values. These preferred learning resources seem to differ from the established training and Extension modalities.

Table 8: Programs participants report of most important resource for small, socially disadvantaged, and minority farmers (n=14).

 

 

Level of importance (number, percent)

Resources

1. Least important

2. Slightly important

3. Moderately important

4. Very important

5. Extremely

important

Rank Index

Local partnership (farmers’ market, local food, community garden)

0

1 (7.1%)

4 (28.6%)

3 (21.4%)

6 (42.9%)

4.0

Farmers’ organization (farmer’s association/cooperatives)

0

1 (7.1%)

1 (7.1%)

10 (71.4%)

2 (14.3%)

3.9

Training and education (in-person)

0

1 (7.1%)

3 (21.4%)

8 (57.1%)

2 (14.3%)

3.8

Incubator farmers

0

1 (7.1%)

1 (7.1%)

10 (71.4%)

1 (7.1%)

3.8

Educational events (workshop, training, meeting, conference)

0

1 (7.1%)

1 (7.1%)

11 (78.6%)

1 (7.1%)

3.9

Virtual training

0

3 (21.4%)

3 (21.4%)

7 (50.0%)

1 (7.1%)

3.4

Digital training materials

0

2 (14.3%)

4 (28.6%)

7 (50.0%)

1 (7.1%)

3.5

Appendix 1: Types of vegetables cultivated by farmers (n=14).

SN

Farmers cultivated

N

Percent

1

Tomato

7

50.0

2

Spinach*

6

42.9

3

Beans

5

35.7

4

Eggplant*

5

35.7

5

Chili

4

28.6

6

Onion

3

21.4

7

Coriander/Cilantro

3

21.4

8

Okra/Ladies Finger*

3

21.4

9

Zucchini

3

21.4

10

Pepper*

3

21.4

11

Bitter melon*

4

28.6

12

Pumpkin

2

14.3

13

Cucumber

2

14.3

14

Carrot

2

14.3

15

Garlic

2

14.3

16

Cauliflower

2

14.3

17

Mustard green

2

14.3

18

Bottle Gourd*

2

14.3

19

Swiss Chard

2

14.3

20

Potato

1

7.1

21

Corn

1

7.1

22

Mushroom

1

7.1

23

Radish

1

7.1

24

Pea

1

7.1

25

Broccoli

1

7.1

26

Colocasia/Taro*

1

7.1

27

Chamsur/Garden Cress*

1

7.1

28

Snake Gourd*

1

7.1

29

Smooth Gourd*

1

7.1

30

Ash Gourd*

1

7.1

31

Collard

1

7.1

32

Celery

1

7.1

33

Asparagus

1

7.1

34

Cabbage

1

7.1

35

Turnip

1

7.1

       

* Ethnic crops

Maximum number of vegetable crops grown by a single farmer=16

Appendix 2. Fruit Growers (n=14)

SN

Farmers cultivated

N

Percent

1

Apple

3

21.4

2

Pear

2

14.3

3

Fig

1

7.1

Appendix 3. Specialty Crops Growers (n=14)

SN

Farmers cultivated

N

Percent

7

Tomato

10

71.4

1

Onion

7

50.0

2

Pumpkin

7

50.0

3

Eggplant

7

50.0

6

Beans

7

50.0

10

Carrot

7

50.0

5

Spinach

6

42.9

8

Okra

6

42.9

11

Cucumber

5

35.7

12

Garlic

5

35.7

9

Radish

4

28.6

17

Swiss chard

4

28.6

18

Collard

4

28.6

4

Sweet Potato

3

21.4

13

Greens

3

21.4

15

Broccoli

3

21.4

16

Cauliflower

3

21.4

14

Bitter Melon

2

14.3

19

Celery

2

14.3

20

Asparagus

1

7.1

Appendix 4. Ethnic Crop Growers (n=14)

SN

Farmers cultivated

N

Percent

1

Eggplant

6

42.9

2

Spinach

5

35.7

3

Okra

7

50.0

4

Peppers

8

57.1

5

Bitter Melon/Gourd

1

7.1

6

Red Rice

1

7.1

7

Bottle Gourd

1

7.1

8

Ash Gourd

1

7.1

9

Snake Gourd

1

7.1

10

Smooth Gourd

1

7.1

11

Colocasia/Taro

1

7.1

12

Chamsur/garden cress

1

7.1

Appendix 5. Herbal Medicinal Plant Growers (n=14)

SN

Farmers cultivated

N

Percent

1

Coriander/Cilantro

6

42.9

2

Ginger

4

28.6

8

Dill

4

28.6

3

Basil

3

21.4

5

Mint

3

21.4

10

Parsley

3

21.4

11

Paprika

3

21.4

12

Rosemary

3

21.4

4

Fenugreek

2

14.3

6

Turmeric

2

14.3

7

Ginseng

2

14.3

9

Fennel

2

14.3

13

Melon

1

7.1

14

Spinach

1

7.1

15

Oregano

1

7.1

16

Sorrel

1

7.1

17

Poke wood

1

7.1

iii) Providing support services:

A demand for vegetable, specialty, and ethnic crop seeds are being assessed. They have been educated to start preparing their land to sow the seeds in early spring depending on the type of crop. Also, they were informed to search for renting 3 acres of land to start a model by expanding vegetables production. 

iv) Introducing farm data recording and analysis:

Developing farm data recording format to introduce record keeping to carry out input-output analysis of farm enterprises is on the progress.  

iv) Conduct market surveys:

The survey will be administered after finalizing the specialty and ethnic crop counties and markets in spring. 

Participation Summary
15 Farmers participating in research

Education & Outreach Activities and Participation Summary

1 Online trainings

Participation Summary:

Education/outreach description:

The project's strategic outreach plan is to disseminate its findings to the maximum possible extent so that existing, potential, and prospective stakeholders will benefit. The project will reach out to all SSDM farmers, including but not limited to: beginning, backyard, residential, school, community, and urban gardeners as well as potential and prospective producers, agricultural entrepreneurs, small farmer agriculture cooperatives, consumers, suppliers/retailers, and institutions of teaching, research, and extension. Broadly, the outreach plan will be split into two phases:

  1. During the project period: The project will make all deliverables (training materials, extension publications, and findings of the project) available to its working partners (cooperating farmers, recruited specialty farms, specialty markets, extension professionals, faculty and staff). Similarly, the University of Maryland Eastern Shore (UMES) School of Agricultural and Natural Sciences (SANS) and UMES Extension have an excellent network with farmers across Maryland through the Extension program. Thus, the findings will reach out to hundreds of farmers through its program leaders, extension educators, faculty, and staff. Simultaneously, the findings will be shared with individuals and institutions working with farmers in Maryland, such as the Maryland Department of Agriculture, twenty-four county Extension offices, the Maryland farmers association, the farmers market network, Future Harvest: Chesapeake Alliance for Sustainable Agriculture, and eXtension. Concomitantly, the findings will be disseminated during year-round events that UMES Extension organizes in various counties, such as quarterly meetings, the annual farmers conference, field days, farm demonstrations and tours, 4-H events, food safety events, human health events, nutrition and wellness events, family and community resiliency events, and food and agricultural programs. The project will also disseminate findings through extension publications (brochures, flyers, fact-sheets, pamphlets, tech-notes, and bulletins), peer-reviewed publications, social media, email, and phone communications. Correspondingly, the findings will be published in Extension's bi-monthly newsletter; Connections, the SANS monthly digest, and the annual research magazine; Ingenuity. These publications reach a wide variety of readers, including farmers. UMES Extension has maintained a listserv of over 500 farmers and agricultural professionals in order to disseminate the findings to a wider network promptly. Collectively, the findings will be disseminated to about one thousand people through direct means and an infinite number of readers will benefit from the findings through indirect ways in the foreseeable future. 
  2. After the project period: The project has a plan to create an online interactive learning platform (e.g., blog). All these deliverables will be made available to the public through this learning platform and uploaded to the UMES SANS and Extension websites. Most importantly, the findings will be shared with all 1890, 1862, and 1994 Extensions programs to disseminate to their clientele and networks. 
Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture or SARE.