CITATION: Akomdo, C., Bakang, J-E. A., Tham-Agyekum, E. K., Akese, I., Oye, S., Yankyerah, O. K., Prah, S., (2023) ADOPTION OF GOOD AGRONOMIC PRACTICES BY TOMATO FARMERS IN RURAL GHANA: AN APPLICATION OF THE UNIFIED THEORY OF ACCEPTANCE AND USE OF TECHNOLOGY, Agricultural
ADOPTION OF GOOD AGRONOMIC PRACTICES BY TOMATO FARMERS IN RURAL GHANA: AN
APPLICATION OF THE UNIFIED THEORY OF ACCEPTANCE AND USE OF TECHNOLOGY
Charlotte Akomdo, John-Eudes Andivi Bakang, Enoch Kwame Tham- Agyekum
*, Isaac Akese, Sadat Oye, Ohene Kwasi Yankyerah, Stephen Prah
Department of Agricultural Economics, Agribusiness and Extension, Kwame Nkrumah University of Science and Technology-Kumasi, Ghana
*corresponding author: [email protected]
Abstract This study uses the Unified Theory of Acceptance and Use of Technology framework to analyze tomato farmers' intention and actual use of good agronomic practices (GAPs). Using a structured questionnaire, data were collected from 300 tomato farmers selected through the multi-stage sampling procedure. Data were analyzed using descriptive and inferential statistics. The results reveal the three practices with the highest level of awareness: fertilizer application, weed control, and pest control. The GAPs practiced mostly by the tomato farmers are fertilizer application, row planting, disease control, and weed control. Results of the Tobit regression model show the extent (intention and actual use) of adoption of GAPs by tomato farmers is influenced by the age of the farmer, years spent in school, years in farming, sources of information, membership of farmer groups, availability of market, performance expectation, and social influence. The results from the study also show that among the major challenges affecting the use of GAPs, lack of credit facilities was ranked first. This study recommends that with the aid of Agricultural Extension Agents, farmers should form cooperatives to enable them to get access to financial support and enable extension workers to easily have access to them.
Keywords: Adoption, Good Agronomic Practices, Innovative Behaviour, Rural Ghana, Tomato Farmers, Unified Theory of Acceptance and Use of Technology
http://dx.doi.org/10.21776/ub.agrise.2023.023.2.8 Received 18 October 2022 Accepted 3 March 2023 Available online 30 April 2023
INTRODUCTION
One of the most powerful tools to end extreme poverty and feed a projected 9.7 billion people by 2050 is agricultural development (Kimura and Sinha, 2008). Agriculture employs 50% of the workforce in Africa and accounts for 64% of the primary source of income for rural populations (ACR, 2015). In Ghana, the sector contributes to about 19.7% of current Gross Domestic Product (GDP), accounts for over 30% of export earnings
and serves as a major source of inputs to our manufacturing industry (Ministry of Economy and Industry, 2020). However, about 80% of smallholder farmers rely on rain for their farms, staple food crops are low-yielding, value addition is minimal and postharvest losses are increasingly becoming a menace (Aidoo-Mensah, 2018;
Ministry of Food and Agriculture, 2017).
Meanwhile, growth in agricultural productivity can contribute to poverty reduction by
stimulating rural non-farm growth (Agyekum, 2015).
According to Kimura and Sinha (2008), tomato is one of the most important vegetables in the world, especially in China, India, United States of America, Turkey and Egypt (FAOSTATS, 2013). It is utilized as a fresh crop or processed into various forms such as paste, puree, and juices (Melomey et al., 2019; Agyekum, 2015) and used in Ghanaian meals such as soup, stew, and salad (Melomey et al., 2019; Osei et al., 2012; Robinson and Kolavalli, 2010).
Good agronomic practices (GAPs) are a collection of principles that address environmental, economic, and social sustainability for on-farm processes and result in safe and quality food and non-food agricultural products (FAO, 2005; 2016).
These GAPs are a vital part of farming systems and can be incorporated to improve the quality of soil, enhance usage of water and improve crop environment (Clottey et al., 2009; Bortey et al., 2011).
Despite the economic and health importance of tomatoes and their contribution to the country's economy, there is a general problem of inadequate supply of tomatoes in Ghana due to the poor use of good agronomic practices, which results in low productivity (Van Asselt et al., 2018). Between 2005 and 2013, tomato consumption increased steadily from around 280,000 metric tons to more than 450,000 metric tons (FAO, 2016), but it has not been able to meet the increasing demand (FAO, 2005; Agyekum, 2015).
Adu-Dapaah et al. (2002) showed the application of inappropriate farm management practices, such as non-adherence to fertilizer recommendations may result in the spread of diseases (Asare-Bediako et al., 2008) and eventual great impact on productivity. These trends could be reversed by the uptake of GAPs (MoFA, 2017).
The Unified Theory of Acceptance and Use of Technology (UTAUT) explains that the intention or actual use of technology (GAPs) is determined by performance expectancy, effort expectancy, social influence and facilitating conditions. Performance expectancy is when an individual (tomato farmer) believes that using the GAPs will help him or her to attain benefits or gains in their farm activities.
Effort expectancy is when an individual (tomato farmer) has less difficulty with the use of the GAPs. Social influence is when an individual (tomato farmer) perceives that others who they deem important believe he or she should use the GAPs. Facilitating conditions is when an individual (tomato farmer) believes that a farm’s technical infrastructure exists to support their adoption of GAPs. Behavioral intention helps tomato farmers
understand the long-term benefits of adopting technology, such as increased efficiency, cost savings, and sustainability. Usefulness and usability is the continuous evaluation and improvement of the technology solutions offered to tomato farmers based on their feedback and evolving needs (Venkatesh and Davis, 2003).
Numerous studies have been conducted in the area of adoption of good production practices by tomato farmers. For instance, using the chi-square test of independence, Frimpong et al. (2021) found that factors such as farm size, education, farming experience, land tenure arrangements, access to extension services, access to credit, and point of sale are significantly associated with the adoption of best tomato production practices. Magugu et al.
(2018) and Al-Shadiadeh et al. (2012) reported farm size, years of residence, percentage income from the crop, educational level, access to information, household size, and years of farming positively and significantly influence the adoption of tomato farming practices. Baka (2020) studied the adoption levels of certain tomato cultivation practices by farmer field schools (FFS) in Sudan and found that the adoption of the cultivation practices for tomatoes significantly depended on the FFS approach. In a study by Bortey and Osuman (2016), the majority of the farmers (80%) indicated the high cost of quality seed, unavailability of improved seed varieties, unreliable markets, and pest and disease problems as challenges they face in adopting good tomato production practices. Again, Frimpong et al. (2021) found that the main constraints to double-season production were the unavailability of water and fluctuations in market demand. All these previous studies looked at the factors hindering farmers' use of good tomato production practices.
There are currently limited studies on how the Unified Theory of Acceptance and Use of Technology (UTAUT) forms the basis for use of GAPs by tomato farmers. Therefore, this study seeks to assess the farmer's use of good agronomic practices for tomato production. The specific objectives are to assess the farmers' level of awareness on the use of good agronomic practices, assess the GAPs actually used by the tomato farmers, determine the factors that influence the extent of use of GAPS, assess tomato farmers' perceptions on the use of the GAPs and identify and rank the challenges tomato farmers face in the use of the GAPs.
RESEARCH METHODS
The study area, Ada East District, has Ada- Foah as its capital town. The total land area of the district is 289.783 (square km). The district shares boundaries with Central Tongu District to the
North, South Tongu District, Ada West District, and the Gulf of Guinea to the East, West, and South, respectively (GSS, 2010).
Figure 1. Map of Ada East District
The study population included all tomato growers in the district. Since the population size of our study was not known, Cochran’s formula was used to calculate the sample size. The sample size of the study was 300 tomato farmers. The multi- stage sampling technique was used in the study.
The Ada-East District was purposively selected from the Greater Accra Region because of the predominant cultivation of tomatoes in the area. At stage two, three (3) out of four (4) zones were purposively selected. These zones, namely, Kasseh East, Kasseh West, and Big-Ada zones, are known to be the major tomato-growing areas in the district. At stage three, four (4) operational areas (Tojeh, Dogo, Tamatoku, and Amlakpo) were purposively selected from the 10 operational areas in the district. At stage four, a simple random sampling technique was used to select 8 communities from four (4) operational areas, where the names were written on slips of paper, folded and placed in a basket, and then shaken. The papers were picked without replacement to obtain the 8 communities (Tojeh-64, Asigbeykope-19, Faithkopey-39, Dogo-30, Kadjanya-57, Tamatoku- 24, Amlakpo-42 and Gbanave-25) for the study.
The tomato farmers were selected based on how easily accessible they were. Primary data was obtained using questionnaires. The questionnaire was developed through a review of literature and consultation with experts in tomato production. To achieve a high response rate, the questionnaire was personally distributed to respondents in the eight (8) communities chosen. Agricultural extension agents (AEAs) in Ada East District aided the researchers with data gathering on the field. The questionnaires were largely given out in the Ga- Adangme language because it was the district's primary language. Responses were written in the English language. The data collected was analyzed using Stata. To assess the farmers' level of awareness of the use of GAPs, descriptive statistics
(frequency, percentage, mean and standard deviation) were used. To assess the GAPs actually used by the tomato farmers, descriptive statistics (frequency and percentage) were used. To assess the tomato farmers' perceptions on the use of GAPs, descriptive statistics, a 3-point Likert scale (Where -1=disagree; 0=Neutral; 1=Agree), mean, and standard deviation were used.
The Tobit regression was used to analyze the factors that influence the extent of use of GAPs.
The dependent variable was the extent of adoption which was measured by the total number of GAPs adopted by an individual tomato farmer divided by the total number of GAPs available. Since the farmers' decision to adopt GAPs and the extent of adoption is a dependent variable that takes on an interval with positive probability and continuously distributed over the interior of the interval, the Tobit model was chosen over other models such as Cragg Double hurdle and Heckman. Tobit assumed that farmers simultaneously made decisions about adoption and the extent of adoption (Tobit, 1958).
This is specified as:
𝑍𝑖∗= 𝑋𝑖𝛽 + 𝜔𝑖 (1) 𝑍𝑖∗= { 1, 𝑖𝑓 𝑍𝑖∗> 0
0, 𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒 (2)
Where; 𝑍𝑖∗ denotes dependent variable, 𝛽 denotes unknown parameters to be estimated, 𝜔𝑖 denotes disturbance term and 𝑋𝑖denotes set of independent variables adapted from a study by Puspitasari et al., (2019) who also used the UTAUT to measure adoption; Performance Expectancy, measured on a 3-point likert scale (utilisation of perception, increasing effectiveness, productivity and ease of getting information); Effort Expectancy, measured on a 3-point likert scale (ease of interaction, ease of learning, ease of use and ease to become an expert);
Social Influence, measured on a 3-point likert scale (co-worker factor, support from influential people and assistance in use); Facilitating Conditions, measured on a 3-point likert scale (facilitating conditions, compatible devices); Socio-economic variables such as Sex (Dummy: Male-1, Female-0), Religion (Dummy: Christian-1, Others-0), Age of farmer (Continuous: years), Years spent in school (Continuous: years), Marital status (Dummy:
Married-1, Others-0), Household size (Continuous:
years), Years in farming (Continuous: years), Farm size (Continuous: acres), Land acquisition (Dummy: Own land-1, Others-0), Access to credit (Dummy: Yes-1, No-0), Sources of information (Continuous: number of sources), Access to extension (Dummy: Yes-1, No-0), Availability of market (Dummy: Yes-1, No-0), Performance expectation (Dummy: Yes-1, No-0), Effort expectancy (Dummy: Yes-1, No-0) and Social influence (Dummy: Yes-1, No-0) (Venkatesh and Davis, 2003). Further, the likelihood ratio test was computed to determine whether Tobit or Cragg
Double Hurdle best matched the discussion of the estimates. Therefore, the log-likelihood of Tobit, probit, and truncated regression models were used to estimate likelihood ratio statistic as:
𝜆 = −2(𝐿𝑅𝑝𝑟𝑜𝑏𝑖𝑡+ 𝐿𝑅𝑇𝑟𝑢𝑛𝑐𝑎𝑡𝑒𝑑− 𝐿𝑅𝑇𝑜𝑏𝑖𝑡) (3) Where; 𝐿𝑅 denotes the probit log-likelihood, Truncated log-likelihood and Tobit log-likelihood.
Following Mal et al. (2013), the Tobit regression model is used for discussion when 𝜆 is less than the critical value. Hence, the computed 𝜆 was less than the critical value justified for the use of the Tobit regression model in this study.
To assess the challenges tomato farmers face in using GAPs, the Kendall’s coefficient of concordance was used to determine the degree of agreement of the challenges among the tomato farmers. The challenge with the highest mean was ranked as the least pressing challenge, with the lowest mean being the most pressing challenge.
RESULTS AND DISCUSSION
Socio-Demographic Characteristics of the Tomato Farmers
Table 1. Socio-Demographic Distribution of the Tomato Farmers (Discrete Variables)
Sex Frequency Percent
Male 206 68.70
Female 94 31.30
Marital Status Frequency Percent
Married 245 81.70
Others (Single, divorced, widowed)
55 18.30
Access to Credit Frequency Percent
Yes 77 25.70
No 223 74.30
Land Acquisition Frequency Percent
Own land 164 54.80
Others 136 45.20
Access to Extension
Frequency Percent
Yes 231 77.00
No 69 23.00
Membership in Farmer Groups
Frequency Percent
Yes 53 17.70
No 247 82.30
Source: Field Survey, 2022
Table 1 shows that 206 of the tomato farmers were males, representing approximately 68.70%, while the remaining 94 respondents representing 31.30%
were females. This result indicates that tomato production in Ada-East has male dominance over females. Clottey et al. (2009) also asserted tomato production attracts more men than women in
Ghana. As a capital-intensive crop, tomatoes may attract more men since they have access to financial capital than women (Mamudu et al., 2009).
According to the findings, 81.70% of tomato growers in the Ada-East are married, while 18.30%
were either single, divorced, or widowed. About 74.30% of the tomato farmers did not have access to credit, while 25.70% had access to credit. The majority of the farmers (54.80%) of the farmers were farming on their own lands, while 45% were not. The majority of the farmers (77%) had access to extension services in the District. The majority of the farmers (82.30%) were not members of farmer groups, while 17.70% were members of farmer groups.
Table 2. Socio-Demographic Distribution of the Tomato Farmers (Continuous Variables)
Variables Mean Std. Dev.
Years in farming 11.94 0.14
Years spent in school 12.23 0.56
Farm size 2.3 0.26
Household size 5 0.13
Age of farmer 41.32 0.25
Sources of information 2 0.12 Performance expectation 2.91 0.09
Effort expectancy 2.76 0.15
Social influence 2.82 0.22
Facilitating conditions 2.55 0.61 Source: Field Survey, 2022
The level of experience in any business is important as it affects people's behavior towards trying new technologies relevant to the enterprise (Frimpong et al., 2021). In this study, tomato farmers had an average of 11 years of experience in tomato farming. This means they have a relatively high experience in tomato production, hence, are abreast with the risks and uncertainties associated and the best practices to employ. The mean years spent in school was 12.23. This means that tomato farmers have some level of education. This can help them understand the need to examine and apply GAPs in agricultural activities. Educated farmers use improved practices to increase production (Ibitoye et al., 2015; Adeoye, 2020;
Oyediran et al., 2020; Kabeer, 2003; Lapar and Ehui, 2003).
An average age of 41 years was recorded for the tomato farmers. The tomato farmers are relatively younger, indicating that young people are probably more interested in tomato production. A mean household size of five (5) people was recorded for the farmers. This is a little higher than the national average of four (4) members per household (GLSS 5, 2008). An increase in household size increases the availability of labor for farming activities (Frimpong et al., 2021). The average farm size used by the tomato farmers was
2.3 acres. This conforms to findings by Adu- Dapaah and Oppong-Konadu (2002), who demonstrated tomato production in Ghana is still subsistence. With small farm sizes, adopting improved production practices could enhance productivity compared to the continual use of conventional methods on these small plots (Frimpong et al., 2021; Maloney et al., 2019).
The average number of information sources used by the tomato farmers was two (2). This implies the respondents receive some level of information about GAPs. The sources of information are critical factors affecting adoption rates of innovations (Oladele and Tekena, 2010;
Okunade, 2006). Using the UTAUT framework, farmers were asked to indicate the extent of their performance expectation, effort expectation, social influence and facilitating conditions. The results show mean scores of 2.91, 2.76, 2.82, and 2.55, respectively. This shows that, on average, tomato farmers had high-performance expectations, effort expectations, social influence, and facilitating conditions.
Awareness of recommended GAPs by tomato farmers
Table 3. Awareness Level of Respondents Agrono
mic Practice s
Neve r Hear
d N (%)
Hear d Little
N (%)
Heard a Lot N (%)
To tal aw are ne ss
M ea n
St d.
D ev . Weed
Control 1 (0.30
)
10 (3.30)
289 (96.40
) 29
9 1.9
6 0.
21 Pest
Control 0 (0.00
)
18 (6.00)
282 (94.00
) 30
0 1.9
4 0.
24 Fertilize
r Applicat ion
0 (0.00
)
22 (7.30)
278 (92.70
) 30
0 1.9
3 0.
26
Disease control
1 (0.30
)
36 (12.0
0)
263 (87.70
) 29
9 1.8
7 0.
34 Row
planting 4 (1.30
)
74 (24.7
0)
222 (74.00
) 29
6 1.7
3 0.
48 Mulchin
g applicati on
40 (13.3
0)
153 (51.0)
107 (35.70
) 26
0 1.2
2 0.
67
Pruning 99 (33.0
0)
103 (34.3 0)
98 (32.70
) 20
1 1.0
0 0.
81 Staking 97
(32.4 0)
109 (36.3 0)
94 (31.30
) 19
9 0.9
9 0.
80
Source: Field Survey, 2022
NB: 1-1.49=never heard; 1.5-2.49=heard little; 2.5- 3.0=heard a lot
The data presented in Table 3 indicates 96.4%
of the respondents had heard a lot about weed control, while 3.3% had heard little, and only 0.3%
of respondents had never heard about weed control.
By implication, this shows farmers in the district were aware of weed control practices. In addition, the results show a majority of the respondents (94%) had heard a lot about pest control, while about 6% were less aware of pest control. About 92.7% of the farmers had heard a lot about fertilizer application, while 7.3% of the respondent indicated that they had heard little about fertilizer application. This clearly shows the majority of the tomato farmers in the Ada-East district were highly aware of fertilizer application.
The majority of the respondents (74%) had heard a lot about row planting, while 24.7% of the respondents had heard little, and only 1.3% had never heard about row planting. Also, the level of respondents' awareness of disease control was high, with 87%, 12% having little awareness, and only 0.3% of respondents stating that they were not aware of the practice. The results show a reasonable amount of the respondents (51%) had heard little about mulching, while 35.7% had heard a lot about mulching and only 13.3% had never heard about the practice. About 32.7% of the respondents indicated that they had heard a lot about pruning, while 34.3% had heard little, and only 33% of respondents had never heard about pruning. About 31.3% of the respondents indicated that they had heard a lot about staking, while 36.3% had heard little, and only 32.4% of respondents had never heard about staking.
Awareness of GAPs is an important antecedent to forming an outlook (Forsyth et al., 2004). This helps to facilitate the adoption of innovations. If there is a low level of awareness, it can hinder the adoption of the latest technologies (Siddiqui et al., 2006).
Use of Recommended GAPs by Tomato Farmers Table 4: Recommended GAPs practiced by the tomato farmers (multiple responses)
Recommended GAPs
Yes N (%)
No N (%) Fertilizer Application
Do you apply fertilizer?
300 (100.00) 0 (0) Type of Fertilizer Used
NPK 298 (99.30) 2 (0.70)
Urea 49 (16.30) 251 (83.70)
Manure 145 (48.30) 155 (51.70)
Method Used
Broadcasting 5 (1.70) 295 (98.30)
Drilling 2 (0.70) 298 (99.30)
Ringing 19 (6.30) 281 (93.70)
Side dressing 264 (88.00) 36 (12.00)
Spraying 10 (3.3) 290 (96.70)
Quantity used on an acre
0.5 Bag 33 (11.00) 267 (89.00)
1 Bag 155 (51.70) 145 (48.30)
1.5 Bags 33 (11.00) 267 (89.00)
2 Bags 79 (26.30) 221 (73.70)
Often Used
Once 72 (24.00) 228 (76.00)
Twice 226 (75.3) 74 (24.70)
Other 2 (0.70) 298 (99.30)
Time used 1-2 weeks after transplanting
119 (39.70) 181 (60.30) 3-4 weeks after
transplanting
130 (43.30) 170 (56.70) 5-6 weeks after
transplanting
3 (1.00) 297 (99.00)
Other 48 (16.00) 252 (84.00)
Weed Control Do you practice weed control?
299 (100.00) 0 (0) Method Used
Hand-picking 184 (61.30) 116 (38.70)
Weeding 300 (100) 0 (0)
Use of chemicals 21 (7.00) 279 (93.00) Inter-cropping 2 (0.70) 298 (99.30) How Often
Once 6 (2.00) 294 (98.00)
Twice 128 (42.70) 172 (57.30)
More than two times
166 (55.30) 134 (44.70) Time Of Practice
Pre-planning 300 (100.00) 0 (0) Farm activities 292 (97.30) 8 (2.70) During planting 9 (3.00) 291 (97.00) During harvesting 18 (6.00) 282 (94.00) Pest Control
Do you control Pests?
299 (99.70) 1 (0.30) Method Used
Chemical control 291 (97.00) 8 (2.70)
IPM 8 (2.70) 292 (97.30)
Mechanical ways 9 (3.30) 290 (96.70) Physical and
pheromone traps
126 (42.30) 173 (57.70) Biological
enemies
1 (1.30) 298 (98.70)
Other 11 (3.70) 288 (96.30)
Disease Control Do you control disease?
299 (100.00) 0 (0) Method Used
Use of chemicals 295 (98.30) 4 (1.70) Cultural methods 7 (2.70) 292 (97.30)
Use of resistant variety
5 (1.70) 294 (98.30) Other methods 7 (2.70) 292 (97.30) Mulching
Do you practice mulching?
82 (31.54) 178 (68.46) Mulch Materials Used
Straw 70 (85.37) 12 (14.63)
Tree leaves 82 (100.00) 0 (0.00) Pruning
Do you practice pruning?
36 (17.91) 165 (82.09) Method Used
Simple pruning 34 (94.44) 2 (5.56) Top pruning 11 (30.56) 25 (69.44) How Often?
Once 22 (56.41) 14 (43.59)
Twice 23 (63.89) 13 (36.11)
More than two times
4 (11.11) 32 (88.89) Row Planting
Do you practice row planting?
296 (100.00) 0 (0.00) Staking
Do you practice staking?
33 (16.58) 166 (83.42) Time of Staking
Before transplanting
6 (18.18) 27 (81.82) After transplanting 33 (89.30) 0 (0.00)
Other 0 (0.00) 33 (89.30)
Source: Field Survey, 2022
NB: Calculations were computed out of the total number of tomato farmers who were aware of the practices
The result from Table 4 describes the GAPs of the tomato farmers. Out of the 300 tomato farmers who were aware of fertilizer application, all (100%) of them practiced fertilizer application, which shows high use of the practice. The types of fertilizers used by tomato farmers include NPK (99.30%), urea (16.30%) and manure (48.30%).
The majority of the tomato farmers (88.00%) use the side dressing method for applying fertilizers.
The majority of the tomato farmers (51.70%) use 1 bag of fertilizer per acre. About 75.30% apply fertilizer twice within a season.
Out of the 299 tomato farmers who were aware of fertilizer application, all of them (100%) practice weed control, which shows a high use of the practice. The methods used by the respondents to control weeds include hand-picking, weeding, the use of chemicals, and inter-cropping. All respondents (100%) practice weeding, 61.30%
practice hand-picking, 7% use chemicals, and 0.7%
practice inter-cropping. The majority (55.30%) of
the tomato farmers control weeds more than two times within a season. Of all the respondents who control weeds before planting, 97.3% control weeds during farm activities, 6% of the tomato farmers control weeds during harvesting, and only 3% control weeds during planting.
About 99.70% of the tomato farmers practice pest control. The majority (97.00) of the respondents use only chemicals to control pests, while 42.30% use physical and pheromone traps (42%). Only 3.7% use other methods, such as using neem extracts together. The ease of using chemicals to control pests could be the reason why the majority of the respondents use them.
Out of the 299 tomato farmers who were aware of disease control, the majority (98.3%) use chemicals to control diseases, 2.70% each use cultural methods and other methods, respectively, while 1.70% use resistant varieties. The poor use of resistant varieties could be attributed to failure from previous uses or the high cost of tomato- resistant varieties.
Out of the 260 tomato farmers who were aware of mulching, the majority (68.46%) of them do not practice mulching. Among those who practice mulching, 85.37% of them use straw, while 100% of the tomato farmers use tree leaves as mulch materials. If tomato farmers take mulching seriously, it can improve the condition of their soil and help maintain or improve water levels in the soil (Adu-Dapaah and Oppong-Konadu, 2002).
Out of the 296 tomato farmers who were aware of row planting, all (100.00%) of them practiced row planting. Out of the 201 tomato farmers who were aware of pruning, 82.09% of them do not practice pruning and only 17.91% do practice. Among those who practice pruning, 94.44% of them use simple pruning as a method of pruning, while 30.56% use top pruning. About 56.41% prune once, 63.89% prune twice, and 11.11% of them prune more than two times in a season. If tomato farmers take pruning seriously, it can help divert nutrients to flower clusters and fruits on the main stem and allow more efficient air circulation (Falodun and Ogedegbe, 2019).
The results also show the staking activities of the respondents. It indicates that out of the 199 tomato farmers who were aware of the practice, the majority of them (83.42%) do not practice staking, while only 16.58% are involved in this practice.
About 18.18% of those who stake do it before transplanting their seedlings, while 89.30% stake it after transplanting the seedling to the field.
Factors that Influence the Use of GAPs by Tomato Farmers
Table 5. Factors that Influence the Use of GAPs by Tomato Farmers
Parameters Coef. Std. Err. T P>t
Sex -0.11 0.14 -0.79 0.42
Religion -0.00 0.01 0.00 0.56
Age -0.31** 0.13 -2.38 0.02
Years spent in school
0.00* 0.01 0.00 0.09 Marital
status
-0.05 0.18 -0.28 0.79 Household
size
-0.09 0.03 -3.00 0.21 Years in
farming
0.03*** 0.01 3.00 0.00 Farm size 0.07 0.04 1.75 0.16 Land
acquisition
0.29 0.20 1.45 0.15 Access to
credit
0.17 0.12 1.42 0.21 Sources of
information
0.56** 0.28 2.00 0.04 Access to
extension
0.33 0.27 1.22 0.22 Membership
of farmer groups
0.13*** 0.15 0.67 0.01
Availability of market
-0.51** 0.23 -2.22 0.03 Performance
expectation
0.08* 0.27 0.30 0.07 Effort
expectancy
0.35 0.24 1.46 0.11 Social
influence
0.10* 0.21 0.48 0.06 Facilitating
conditions
-0.29 0.03 9.67 0.31 _cons 4.69 0.51 9.20 0.00 /sigma 1.18 0.05
Source: Author’s Construct, 2022
*10%, **5%, ***1%
NB: Number of observations = 300, LR chi2 (16) = 59.77, Prob > chi2 = 0.00, Log likelihood = - 601.09, Pseudo R2 = 0.55
The Tobit regression model was used to determine the factors that influence the extent of adoption of GAPs by tomato farmers. From the table, it could be said that the extent of adoption of GAPs by tomato farmers is influenced by their age, years spent in school, years in farming, sources of information, membership of farmer groups, availability of market, performance expectations, and social influence. Frimpong et al. (2021) also agree that farm size, education, farmers' experience in tomato production, and the type of variety
cultivated by tomato farmers has an association with their adoption of best tomato practices.
A negative coefficient of age suggests that younger tomato farmers are more likely to adopt good agronomic practices than the aged farmers. In a study by Min et al. (2008), the age of an individual was found to have an influence on the use of a system. Thus, the older a tomato farmer is, the slower it will be to use GAPs, and the younger tomato farmers will better appreciate and use the GAPs.
A positive coefficient of years spent in school suggests that highly educated tomato farmers are more likely to adopt good agronomic practices than those with low levels of education. A positive coefficient of years in farming suggests that highly experienced tomato farmers are more likely to adopt good agronomic practices than those with a low level of tomato farming experience. A positive coefficient of sources of information suggests that tomato farmers with more information sources are likely to adopt good agronomic practices than those with less information sources. With the kind of good agronomic practices considered in this study, Frimpong et al. (2021) agree it may also require some technical knowledge and exposure, so formal education, farming experience, and sources of information place a farmer in a better position to grasp and apply these practices much easier.
A positive coefficient of membership of farmer groups suggests that tomato farmers who were members of farmer groups were more likely to adopt good agronomic practices than those without farmer group membership. A positive coefficient of availability of market suggests that tomato farmers with available markets are more likely to adopt good agronomic practices than those without available markets. Frimpong et al. (2021) also agree that the point of marketing and adoption of improved tomato production practices have a statistically significant association. Easy access to markets and favorable prevailing market conditions, as noticed by Tampoare et al. (2012), could encourage farmers to risk and expend their resources, both physical and financial, to adopt practices and reap the benefits thereof.
A positive coefficient of performance expectation suggests that tomato farmers with high levels of performance expectation are more likely to adopt good agronomic practices than those with low levels of performance expectation. Studies by Min et al. (2008) and Puspitasari (2013) showed that the most influential variable in the adoption of technologies is the expectation of performance. A positive coefficient of social influence suggests that tomato farmers with high levels of social influence are more likely to adopt good agronomic practices than those with low levels of social influence. A
study by Puspitasari (2013) also confirms that social factors can influence the use of innovations.
Farmers' Perception of the Use of GAPs Table 6. Farmers perception on the use of GAPs
Use of GAPs Mean Std.
Dev.
Fertilizer Application
Fertilizer is not expensive to buy 0.95 0.30 I am able to acquire fertilizer
easily
0.10 0.96 It is easy to apply fertilizer to my
tomato plants
0.45 0.88 Fertilizer application does not
pose a threat to my environment and consumers
0.35 0.85
The application of fertilizer is not labor intensive
0.49 0.85
Perception index 0.47 0.60
Weeding
It is easy to control weeds on my tomato field
0.90 0.44 Weed control is not labor
intensive
0.90 0.43 I easily get chemicals to control
my weeds.
0.79 0.56 Weed control is not time
consuming
0.88 0.47
Perception index 0.90 0.48
Row planting
It is easy to plant in rows 0.21 0.97 The cost of labor for planting in
a row is low
0.26 0.96 Labourers are available to help
plant in rows
0.18 0.97
Perception index 0.30 0.97
Pest control
Methods of control are easy 0.22 0.97 Pesticides are easily available
for purchase
-0.26 0.95 Pesticides are not expensive to
buy
0.67 0.74 I get training from extension
agents on how to control pest
-0.54 0.84
Perception index 0.02 0.88
Disease Control
Chemicals are not expensive to buy
0.97 0.22 The control of diseases is not
laborious
0.38 0.92 I get training from Agric
Officers on how to effectively control diseases
-0.59 0.79
Perception index 0.76 0.64
Mulch application
Mulching is not labor intensive 0.92 0.31 Mulching is easy to apply 0.79 0.46
Mulch materials are easily accessible
0.38 0.85 I have knowledge about
mulching
0.15 0.88
Perception index 0.56 0.63
Pruning
It is easy to prune 0.83 0.54
Pruning is not time consuming 0.93 0.32 Pruning is not expensive to
practice
0.66 0.67 I get training from Extension
Agents on how to prune
0.08 0.88
Perception index 0.63 0.60
Staking
Staking is not labor intensive 0.91 0.38 It is not time-consuming 0.94 0.28 The cost I incur while staking is
low
0.56 0.75
Perception index 0.80 0.47
Source: Field Survey, 2022
NB: -1--0.49=disagree; -0.5-0.49=Neutral; 0.5- 1=Agree
The behavior of farmers is determined by their perception of sustainable agriculture (Agahi et al., 2011). Farmers' perception of a GAP shows their knowledge and behavior regarding the practice.
Understanding the practice or technology can help shift the adoption paradigm (Kivlin, 2000;
Suharyani, 2018) and influence farmers' decisions on how and when to adopt a particular technology (Emmanuel, 2014). Farmers' perception of the use of the various GAPs was assessed.
Among the total farmers (300) interviewed on their perceptions of fertilizer application, the overall estimated average was 0.47 (SD = 0.60).
Thus, the fertilizer application is not expensive to buy had a mean score of 0.95 (SD = 0.30), application of fertilizer is not labor intensive averaged 0.49 (SD = 0.85), it is easy to apply fertilizer to my tomato plants averaged 0.45 (0.88), fertilizer application does not pose a threat to my environment, and consumer averaged 0.35 (SD=0.85), I am able to acquire fertilizer easily had a calculated average of 0.10 (SD = 0.96). An analysis of the results shows that tomato farmers agree with the perception about fertilizer application that it is not expensive to buy.
For perception on weed control, it is easy to control weeds on my tomato field had an average of 0.90 (SD = 0.44), weed control is not labor intensive had an average of 0.90 (SD = 0.43), weed control is not time-consuming had an average of 0.88 (SD = 0.47), I easily get chemicals to control my weeds had an average of 0.79 (SD = 0.56). The overall average index estimated was 0.90 (SD = 0.48). The results show that most of the tomato farmers agree with the perceptions of weed control.
Farmer's perception of row planting results were presented in Table 6 above: It is easy to plant in rows (M = 0.21, SD = 0.97), cost of labor for planting in a row is low (M = 0.26, SD = 0.96), laborers are available to help plant in rows. The overall average index was 0.30 (SD = 0.97). The findings indicate that few of the tomato farmers agreed on their perceptions of row planting. The average score obtained were between 0.18 and 0.26, from slightly above neutral and just below agree. ATA (2013) found out that the promotion program of row planting led to increased yields at farm levels than those managed on demonstration plots. Thus, if more farmers adopt the use of row planting, the above-mentioned practice will increase productivity as well as ensure effective and efficient weeding.
For perception on pest control, methods of control are easy on the field had an average of 0.22 (SD = 0.97), pesticides are not expensive to buy had an average of 0.67 (SD = 0.74), pesticides are easily available for purchase had an average of - 0.26 (SD = 0.95), I get training from extension agents on how to control pest had an average of - 0.54 (SD = 0.84). The overall average index estimated was 0.02 (SD = 0.88). The results show that most of the tomato farmers were slightly below neutral to agree with the perceptions of pest control. That is, the scores are between -0.26 and 0.67, from slightly below neutral to agree. It can be deduced that pest control activities are not much clear to the farmers and need to be improved to increase their production because they had an overall index of 0.67, indicating weak negative perceptions for all four statements for pest control.
Farmer's perception of disease control results was presented in Table 6 above: chemicals are not expensive to buy (M = 0.97, SD = 0.22), the control of disease is not laborious (M = 0.38, SD = 0.92), I get training from Agric Officers on how to effectively control diseases (M = -0.59, SD =0.79).
The overall average index was 0.76 (SD = 0.64).
The findings indicate that most of the tomato farmers agreed on their perceptions of disease control. Training has been reported to improve knowledge and change farmer's attitudes in crop disease and pest management, which leads to better yields (Asare-Bediao et al., 2008).
For perception on mulching, mulching is not labor intensive on the field had an average of 0.92 (SD = 0.31), mulching is easy to apply had an average of 0.79 (SD = 0.46), mulch materials are easily accessible had an average of 0.38 (SD = 0.85), I have knowledge about mulching had an average of 0.15 (SD = 0.88). The overall average index estimated was 0.56 (SD = 0.63). The results show that most of the tomato farmers were slightly above neutral to agree with the perceptions of mulching. That is, the scores are between 0.15 and
0.92, from slightly above neutral to agree.
Mulching is not labor intensive on tomato fields was rated the strongest; I have knowledge that mulching was scored the weakest. Farmers need to be educated to know that the use of mulch on their farms can help reduce weed infestation (Vander Zaag et al., 1986). From the summarized results in Table 6, it showed that the mulch activities are not much clear to the farmers and need to be improved to increase their production because they have an overall index of 0.56, indicating weak negative perceptions for all four statements for pest control.
Framers' perceptions of pruning in tomato production was sought and the results show the following; pruning is not time-consuming, (M = 0.93, SD = 0.32), It is easy to prune (M = 0.83, SD
= 0.54), pruning is not expensive to practice (M
=0.66, SD = 0.67), I get training from extension agents on how to prune (M =0.08, SD =0.60). The overall average index was calculated, and it was 0.63 (SD = 0.60). The results show that most of the tomato farmers slightly agree with the perceptions on pruning. The mean scores are between 0.08 and 0.93, just from slightly neutral to strongly agree.
Whilst pruning is not expensive to buy was rated the highest, I get training from Extension Agents on how to prune is the lowest. Pruning in tomatoes can increase yields and quality of fruits (Srinivasan et al., 2001)
Farmer's perception of staking shows the following: it is not time-consuming (M = 0.94, SD
= 0.28), staking is not labor intensive (M = 0.91, SD = 0.38), the cost I incur while staking is low (M
= 0.56, SD = 0.75). The overall index estimated was 0.80 (SD = 0.47). Most of the tomato farmers agree with the perception of staking. That is, the scores are between 0.56 and 0.91, from just above neutral to just below agree. While staking is not labor intensive was rated the strongest, while the cost I incur, while staking is low, was scored the weakest. Staking can improve the yield of tomatoes (Ledo et al., 1998).
Challenges tomato farmers face in using Good Agronomic Practices
Table 7. Ranking of Challenges
Challenges Mean Rank Ranking
Inadequate knowledge of GAPs
6.13 7th
Farm input unavailability
6.72 8th
Lack of credit facility
1.57 1st
Lack of
awareness about the GAPs
4.99 5th
Lack of training 3.46 3rd
High cost of use of GAPs
3.06 2nd
It is time consuming to use GAPs
5.60 6th
Difficulty in using GAPs
4.82 4th
Cultural beliefs limit the use of GAPs
8.66 9th
Test statistics N: 300
Kendall’s W: 0.600 Chi-Square: 1439.176 df: 8
Asymp. Sig: 0.00
Source: Field Survey, 2022
Table 7 reveals that the majority of the tomato farmers identified and rated lack of credit facility (Mean rank=1.57) as the most severe. This was followed by the high cost of use of GAPs (Mean rank=3.06), lack of training (Mean rank=3.46), difficulty in using GAPs (Mean rank=4.82), and lack of awareness about the GAPs (Mean rank=4.99). The remaining five challenges hindering farmers' use of GAPs are. Namely, lack of awareness about the use of GAPs is time- consuming to use GAPs, Inadequate knowledge about GAPs, Farm input availability, cultural beliefs limiting the use of GAPs and their mean ranked values are 4.99, 5.60, 6.13, 6.72 and 8.66 respectively. As revealed by Table 4.20, the most severe challenge for tomato farmers in the Ada- East district was noticed to be the lack of credit facilities for the respondents. This finding is corroborated by Bortey and Osuman (2016), who also identified financial constraints as a reason farmers do not readily make use of GAPs.
CONCLUSIONS
Tomato is a very important vegetable consumed all over the world, and in order for tomato farmers to have quality fruit and high yield, it is necessary to adhere to the recommended Good Agronomic Practices in tomato production. In assessing the use of GAPs among tomato farmers in the Ada East District, which was known to be one of the major tomato-producing districts in the Greater Accra Region, the study found the level of awareness to be high on practices such as fertilizer application, weed control, planting in rows, pest and disease control to be high, but low on mulching, pruning, and staking.
The study again found that all the farmers in the district apply fertilizer to the tomato plants, and as such majority of them use 1 bag of NPK fertilizer, which is applied twice during the season
using side-dressing. Weed control is one of the agronomic practices that all the tomato farmers in the district are engaged in, and all of them control the weeds by weeding, while just a few use chemicals to control the weeds. According to some farmers, the low-rate usage of chemicals to control weeds is as a result of past failures of the chemicals as well the high cost of the chemicals. With regards to pest and disease control, the study shows that all the farmers control pests and diseases on their tomato fields, with chemicals being the dominant method used. Some farmers use physical pheromone traps to control pests on the farm.
Others also use neem extracts and magic powder to control pests. Mulching, pruning, and staking are the agronomic practices that most of the farmers in the district are not familiar with. Of the few who practice mulching, the majority of them use tree leaves as mulch materials. Those who prune the plants use simple pruning methods, and this is done once in the season.
The Tobit regression model showed the extent of adoption of GAPs by tomato farmers is influenced by their age, years spent in school, years in farming, sources of information, membership of farmer groups, and availability of market. An overall perception index of 0.56 indicates that the farmers had a good perception of the recommended agronomic practices from the study. Among the challenges presented to the farmers, lack of credit facilities was ranked first, indicating that the farmers are challenged when it comes to financing their production.
In applying the UTAUT model in this study, it was found that tomato farmers with high levels of performance expectation and social influence are more likely to adopt good agronomic practices.
Certainly, the UTAUT model can be a helpful framework to guide adoption of GAPs by tomato farmers. In terms of performance expectancy, the study suggests that extension agents need to emphasize the benefits of using GAPs in tomato farming. They must highlight how the technology can improve crop yield, quality, resource efficiency, pest management, and overall profitability. Researchers can provide empirical evidence and case studies to support the claims and increase farmers' performance expectancy. They must also provide demonstrations or case studies showcasing successful implementations of GAPs in tomato farming.
For social influence, tomato farmers can leverage it by sharing success stories and testimonials from other tomato farmers who have adopted GAps in their farming operations. They can also encourage farmers to collaborate and share their experiences with each other, fostering a supportive community. Tomato farmers must be engaged throughout the research process to ensure
their active participation and ownership of new technology or GAPs. Extension agents could offer comprehensive training programs and educational resources to tomato farmers to enhance their knowledge and skills related to technology adoption. Facilitate knowledge sharing and networking among tomato farmers who have successfully adopted technology. Organize farmer- led workshops, field visits, or virtual forums where experienced farmers can share their experiences, challenges, and best practices. This will enhance social influence and encourage behavioral intention.
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