Pattern of pesticide usage among tomato farmers for sustainable production in the Bono East Region, Ghana

Abstract

The usage pattern of pesticides has been a major contributor to environmental and human health problems among smallholder farmers in most rural communities. A field survey was carried out in major tomato farming communities in the Bono East Region, Ghana to assess the factors that influence farmers’ choice of pesticide usage on their farms. A multi-stage sampling technique was adopted to sample 120 farmers. A Probit regression model was used to assess the factors that influence farmers’ choice of the use of pesticides on their tomato farms in Ghana. Findings from our study revealed that most of the farmers (70.8%) apply pesticides on the appearance of pests and diseases on their farms. We also found that most farmers adhere to the instructions on pesticides but do not fully comply with the usage of personal protective equipment during the application of pesticides on their farms. Most farmers have high knowledge of the detrimental effects of the use of pesticides on beneficial insects (92.1%), and food contaminations (83.5%) and are naïve about the effects on the environment and resistance development among the insects. Also, educational level, household size of the farmers, health problems, contact with extension agents, the combination of pesticides, and the area of cultivation significantly (p < 0.05) influenced farmers’ pesticide usage. It is recommended that there should be continuous monitoring of the change in the concept of pesticide usage and its relationship to the factors affecting their optimal use to ensure compliance with the instructions and not among farmers.

Graphical Abstract

Keywords:

• Pest management
• resistance
• knowledge
• crop protection
• sustainable agriculture

REVIEWING EDITOR:

• Manuel Tejada, Universidad de Sevilla, Spain

SUBJECTS:

• Agriculture & Environmental Sciences
• Entomology
• Environmental Studies
• Environment & Health
• Environmental Change& Pollution

1. Introduction

Tomato (Solanum lycoperisicum) belongs to the family Solanaceae, and it is known to be one of the widely grown, consumed, and nutritious fruit vegetables with supplementary sources of minerals and vitamins, such as vitamins A and C, calcium, and phosphorus in the human diet (Babalola et al., 2010; Naika et al., 2005). Tomato originates from South and Central America, has been distributed widely in all continents, and is adapted to various climatic conditions (Olmstead, 2013). It is an annual crop that is sometimes grown in the greenhouse (O’Sullivan et al., 2019; Palmitessa et al., 2020) or an open field to facilitate growth, but greenhouse production is gaining acceptance due to its potential to provide favourable conditions leading to higher yields (Gatahi, 2020; MOALF, 2015). Tomato serves as an important component in most Ghanaian diets (Osei et al., 2014) with a daily demand in many households, restaurants, and hotels. About 300,000 metric tonnes of tomato is produced in Ghana with about 90% consumed locally. The production of tomatoes as a horticultural crop is mostly carried out by small-scale farmers (Musah et al., 2016) in nine out of the 16 regions of Ghana. Sigei et al. (2014) reported that due to population increase and urbanization which has led to diminishing agricultural lands, tomato has become an important crop for small-scale farmers since it can be cultivated on a small piece of land. However, local production of tomatoes cannot meet households’ demand and are often imported from neighbouring countries like Burkina Faso. This situation is a result of pests and disease infestation during production (Osei et al., 2014). These agricultural pests when not properly regulated affect food consumption (Ofuya et al., 2023) and pose a threat to food security. According to the FAO (2021) pest infestation results in about a 40% reduction in total crop production and subsequently leads to an estimated loss of $70 billion. In the quest for farmers to control or regulate the impact of pests and diseases on the yield of vegetables on their farms, farmers tend to rely heavily on the use of chemical pesticides (Diarra & Tasie, 2017).

Pesticides are toxic substances used to control pests during the production, storage, transport, and processing of food for man or animals, or a substance that can also be used to destroy, prevent, and repel crop pests (USEPA, 2005). Nonetheless, the use of pesticides in the production of vegetables is of great concern because these pesticides can leave chemical residues on the food crops and could result in significant negative effects on the human body causing health problems, such as headaches, catarrh, dizziness, nausea, nervousness, etc. (Kenko et al., 2017; Kenko & Kamta, 2021; Owusu Ansah et al., 2023) as well as the destruction of non-target beneficial insects (Macharia, 2015). Also, the improper use of personal protective equipment (PPE) is a challenge. However, the extent to which pests infest vegetables, such as tomatoes, leading to the intensive use of pesticides by farmers can be attributed to the farming systems, nature of the farmland, geological location, and history of pest infestation of the crop. From an economic point of view, the price of pesticides, the price of other agricultural inputs, and farmers’ profit influence the decision of pesticide usage by farmers (Sharifzadeh et al., 2018). In addition, the rate of pesticide usage in tomato production can be due to the source of seed or the variety of seed grown. Local farmers are more likely to overuse pesticides than farmers who grow hybrids and farmers’ age, farm size, level of education, other economic activities and the type of seed influenced pesticide usage by farmers (Abunyuwah et al., 2020).

According to Bortey and Osuman (2016), insect pests and diseases are some of the major constraints that affect tomato production in Ghana. Despite few studies on the usage of pesticides among farmers in Ghana (cocoa: Denkyirah et al., 2016; Owusu Ansah et al., 2023; rice: Anang & Amikuzuno, 2015; tomatoes: Abunyuwah et al., 2020 and other crops), there is limited scientific evidence and knowledge gap on the usage pattern of pesticide usage among tomato farmers in Ghana and the factors that influence their decision to the usage of pesticides on their farms. Therefore, this paper examines the factors that account for the use of pesticides in tomato production among farmers in Ghana and their practices. The findings of our present study contribute to the wealth of knowledge on the usage patterns and the factors that influence farmers’ choice in the use of pesticides on their farms. The outcome of this study could help in educating farmers on the health and environmental risks associated with the use of pesticides on their farms. Also, this would help inform agricultural extension agents of the practices engaged by farmers in tomato-growing communities and the measures that need to be taken to reduce the indiscriminate usage pattern.

2. Methodology

2.1. Study area

The present study was conducted in the Pru West District of the Bono East Region (erstwhile Brong Ahafo Region) (Figure 1). The administrative district is sandwiched between Sene West District to the east, Pru East to the north, Nkoranza South Municipal District and Atebubu-Amantin Municipal District to the south and Kintampo North Municipal District and Kintampo South District to the west. Geographically, the district lies between Longitude 8°02′5.56″ N and Latitude 1°18′47.85″ W. It experiences the tropical continental or interior savannah climate which is in the transitional agro-ecological zone. Pru West District records an average total rainfall of between 800 and 1400 mm which spans between two rainy seasons with an average yearly temperature between 26.5 and 27.2 °C. The soil of the district is classified as groundwater lateritic soil and is mainly formed over the Voltaian shales and granites. The texture of the soil is fine-textured and is mostly poorly drained (Pru West District Planning Coordinating Unit, 2018). The region is noted for its enormous contribution to large amounts of food crops in the country and is often referred to as the food basket of Ghana. Some of the major food crops produced include cassava, soya beans, cowpeas, tomatoes, groundnuts, and other important food crops.

Figure 1. Map of Pru West District showing the study locations (Zabrama, Abease, Bupe, and Dama Nkwanta) in the Bono East Region of Ghana.

2.2. Sampling method

A multi-stage sampling technique was adopted in this study to select tomato farmers for this study. First, the Bono East Region was purposively selected based on its record of high production of tomatoes in the country (Melomey et al., 2022). Secondly, the Pru West District was purposely selected. In the Pru West District, data was collected randomly from the different farming communities (Bupe, Abease, Dama-Nkwanta, and Zabrama) which are noted for their seasonal production of tomatoes. A simple random sampling method was adopted in selecting the farmers who are into the cultivation of tomatoes in the study area. Nonetheless, all farmers currently or had previously engaged in the cultivation of tomatoes on their farms were included in the sampling frame of the study while those that are not into the cultivation of tomatoes were excluded. A total of 120 farmers were selected randomly from a population of 235 tomato farmers in the community through the help of the Agricultural Extension Staff of the Ministry of Food and Agriculture (MoFA) during the data collection period.

2.3. Instrument and data collection

A semi-structured questionnaire was used for the data collection. The questionnaire included both open and closed-ended questions. The questionnaire was structured into three sections. Section A gathered information on the socio-demographic characteristics of the farmers (such as age, gender, marital status, residence status), farm characteristics, and farmers’ practices (variety cultivated, area of land cultivated); Section B solicited information on knowledge of insect pests and pesticide usage among farmers and Section C of the questionnaire gathered information on the pesticide usage pattern adopted by the farmers. Nonetheless, during the data collection, the questions were interpreted in the local dialect (Twi) by the researchers to the farmers who found it difficult to understand the questions posed in the English Language. A total of 129 questionnaires were administered during the enumeration period. After careful screening of the questionnaires by the researchers only 120 questionnaires were completely responded to, and the uncompleted questionnaires were removed from the lot.

2.4. Statistical analysis

All statistical analysis was carried out using IBM Statistical Package for Social Science Version 26 for Windows. OriginPro 2018 and Microsoft Excel were used for all graphical representations. Both descriptive and Probit regression models were used for this study. Descriptive statistics in the form of frequency and percentages were adopted for the present study. An alpha (α) level of p < 0.05 was used as the criteria for the level of statistical significance. The probit model regression model was employed to determine the factors influencing pesticide usage among tomato farmers. The probit model was used in this study because it is a statistical probability model with two categories in the dependent variable and could resolve the problem of heteroscedasticity (Asante et al., 2011; Gujarati et al., 2004). The analysis is of the cumulative normal probability distribution. The dependent variable, y, takes the value of zero (0) and one (1) (Table 1). The outcomes of y are mutually exclusive and exhaustive. The dependent variable, y, depends on observable variable X, where the probit model is presented as described in the study of Denkyirah et al. (2016): $$\mathit{\text{Pr}}\left(Y=1X\right)=\phi \left(X^{\prime }\beta \right)$$ where Pr = probability and $\phi$ = the cumulative distribution function of the standard normal distribution. The maximum likelihood analysis is used to estimate the parameters ($\beta )$. The probit model can further be written as $$Y=F\left(\alpha +\beta x_i\right)=F\left(z_i\right)$$ where Y = the discrete choice variables, F = the cumulative probability distribution function; $\beta$ denotes the vector of parameters; x denotes the vector of explanatory variables; z denotes the Z-score of $\beta x$ for the area under the normal curve. The probit model can be specified as a linear function of the variables that determine the probability. $$Y-{\beta }_0+{\beta }_i{X}_i+\dots +{\beta }_n{X}_n$$

The marginal effect is estimated for X_i. The marginal X_i is $\partial p/\partial X_i$ and it computed as $$\partial p/\partial X_i=\frac{\partial p}{\partial Y}*\frac{\partial Y}{\partial X_i}=f(Y){\beta }_i$$ f (Y) is the derivative of the cumulative standardized normal distribution and is just the standardized normal distribution itself: $$f\left(Y\right)=\frac{1}{\surd 2\pi }{e}^{-\frac{1}{2}{Z}^2}$$

The cumulative standard normal distribution is given as F (Y) and it gives the probability of the event occurring for any value of Y: $$P_i=F\left(Y\right)$$

Analytically, the probit regression model specification for this study is as follows: $$\begin{array}{l}Y={\beta }_0+{\beta }_1{X}_1+{\beta }_2{X}_2+{\beta }_3{X}_3+{\beta }_4{X}_4+{\beta }_5{X}_5+\\ \hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}\hspace{0.17em}{\beta }_6{X}_6+{\beta }_7{X}_7+{\beta }_8{X}_8+{\beta }_9{X}_9+{\beta }_{10}{X}_{10}+\epsilon \end{array}$$ $$\mathit{\text{subject}}\hspace{0.17em}\hspace{0.17em}\mathit{\text{to}}-q_i+\hspace{0.17em}\hspace{0.17em}\text{Q}\ge 0,$$

Table 1 shows the variables employed in the probit regression model and the a-priori expectations of explanatory variables. The researchers hypothesised different variables for the study.

Table 1. Description of variables used for the analysis.

Variable	Description	Type	Measurement	Hypothesis	Supporting reference
Dependent variable
Pesticide usage	Usage of pesticides by farmers in their tomato farms	Binary	1 = Yes 0 = No
Independent variables
Age	Years	Continuous	Number	+	Alavalapati et al., 1995
Experience	Number of years in farming	Continuous	Years	−	Idrisa et al., 2012; Yasin et al., 2003
Education	Highest level of education	Continuous	Number	−	Denkyirah et al., 2016
Household size	Number of members per household	Continuous	Number	−	Danso-Abbeam et al., 2014
Gender	Gender of the farmer	Binary	1 = Male 0 = Female	+	Blanco-Muñoz & Lacasaña, 2011
Health problems	Problems associated with the application of insecticides	Binary	1 = Yes 0 = No	−	Zahm & Ward, 1998
Adhere to instructions for pesticides	Farmers’ adherence to instructions on insecticide usage	Binary	1 = Yes 0 = No	+/−	Abatania et al., 2010
Extension contacts	Farmers having access to extension service	Binary	1 = Yes 0 = No	−	Anang & Amikuzuno, 2015
Combine pesticides	If, a farmer combines other insecticides	Binary	1 = Yes 0 = No	+	Vidal et al., 2003
Acres of land cultivated	Size of the farm for the cultivation of tomatoes	Continuous	Number (acres)	+	Danso-Abbeam & Baiyegunhi, 2017

3. Results and discussion

3.1. Demographic characteristics of tomato farmers

The demographic characteristics of tomato farmers in the Pru West district of the Bono East Region are presented in Table 3. A total of 120 farmers were interviewed in this study area. The farmers are male dominated (72.5%) with about 27.5% being females. The high proportion of males in the study area concurs with the study of Bortey and Osuman (2016) who also reported the high dominance of males in their study in Ghana. The vast difference in the gender proportion of the tomato farmers in the present study area could be linked to the demanding and tedious nature of agricultural activities (e.g. agronomic activities etc.) as well as the land ownership status in most Ghanaian farming communities. Also, most women tend to be involved along the tomato value chain, such as harvesting, processing, sale, and transportation of the produce from the farm to the farmgate and market.

The age of the farmers ranged from 24 to 65 years with a mean age of 40 ± 0.72 which implies that most farmers are energetic, and this would improve tomato production in the district. Nonetheless, there is a need to make agriculture and most importantly vegetable production attractive to the younger generation to boost the production and food security of Ghana. More than 60% of the tomato farmers in this district have not obtained any form of formal education whereas only 21.7% have attained up to basic education and 14.2% are educated up to secondary education level. The low level of education among tomato farmers is alarming and could hinder the adoption of improved and advanced technologies that are being introduced into the agricultural space, especially during this era of the use of artificial intelligence in agriculture. This can also affect farmers’ understanding of pesticide application and usage techniques. According to Ragasa et al. (2013), the educational level of farmers substantially influences the adoption of new initiatives and agricultural technologies. Similarly, Bissah et al. (2022) also reported a low level of education among rice farmers in Ghana.

The results from the study also revealed that most of the farmers are indigenes of the study area and family heads. Even so, it was not surprising to see the high number of respondents being the household heads because, in most Ghanaian family settings, the head is mostly male which is evident in our study of the high number of male-to-female respondents (Ghana Statistical Service, 2021; Melomey et al., 2022). On the other hand, the farmers have a large household size with a mean of 8.24 and it ranges from 3 to 15 people in a household. Large household size is common among most Ghanaian farming communities. Mostly, this is due to the reliance of the household members on unpaid labour on the farms (Alidu et al., 2022; Kwapong et al., 2021) (Table 2).

Table 2. Socio-demographic characteristics of farmers (n = 120).

Variable	Frequency	Percentage (%)
Gender
Female	33	27.5
Male	87	72.5
Age (years)
20–30	18	15.0
31–40	46	38.3
41–50	48	40.0
51–60	6	5.0
61 and above	2	1.7
Level of education
None	77	64.2
Primary	26	21.7
Senior High School	17	14.2
Residence status
Indigene	78	65.0
Settler	42	35.0
Marital status
Single	16	13.3
Married	99	82.5
Divorced	5	4.2
Head of the household
Yes	86	71.7
No	34	28.3

3.2. Farmers’ farm characteristics and practices

Based on the area of cultivation by the tomato farmers, we found that significantly most farmers cultivate on about 1–2 acres (47.5%), 3–4 acres (37.5%), and only 14.2% cultivate <1 acre (Table 3). Our results showed that most of the farmers operate on a small-scale basis and are classified as smallholder farmers. The Food and Agriculture Organization classifies the Ghanaian agriculture farmers as smallholders (FAO, 2023). Further, most farmers are involved in the production of tomatoes as a source of income whereas few attribute their involvement to domestic use. high profitability as compared to other vegetables grown indicating that tomato production is worth its production (Table 3). Also, it is evident that the farmers are more concerned about their income level which is the motive of most smallholder farmers. The different varieties of tomato varieties cultivated in the district are shown in Figure 2. Some of the tomato varieties grown by farmers in the district include P.V. (34.2%), Bonanza (31.7%), Petomech (17.5%), and Technism (16.7%). The choice of the tomato varieties was attributed to the high-yielding nature of the tomatoes, their fast growth rate, and their ability to withstand biotic stress, such as pests and diseases.

Figure 2. Varieties of tomatoes cultivated by tomato farmers in the Pru West District of Ghana.

Table 3. Farmers’ farm characteristics.

Variables	Percentages (%)
Why do you prefer to cultivate tomatoes?
Highly profitable	36.0
Source of income	64.0
Area cultivated for tomatoes
<1 acre	14.2
1–2 acre	47.5
3–4 acres	37.5
5–6 acres	0.8

3.3. Pesticide usage pattern among tomato farmers

Our study revealed that the decision of the farmers to apply insecticides on their farms is based on the appearance of insect pests and diseases (70.8%) and prevent the infestation and damage of the crop from pests and disease (29.2%) (Table 4). A similar observation was reported by Abunyuwah et al. (2020) where farmers apply pesticides based on the appearance or detection of pest infestations in their field. Due to the presence of the pest on their farm, the farmers reported that the application of the pesticides is mostly carried out early in the morning (92.5%) or late noon (7.5%). The application of pesticides during early morning and/or late noon has been found to be the best period and practice for pesticide application. During this period, the velocity of wind is reduced, and the intensity of sunlight reduces the health risk associated with the application of pesticides outside these periods. Raimondo et al. (2022) also reported a high level of compliance with the application of pesticides between sunset and/or early morning among farmworkers in Argentina.

Table 4. Farmers adherence to pesticide usage instructions during pesticide application.

Variable	Percentage (%)
Decision to apply pesticides
Appearance of pests and diseases	70.8
Prevent crop damage from pests and diseases	29.2
Time of pesticide application
Morning	92.5
Late noon	7.5
Adherence to pesticide usage instruction
Yes	74.2
No	25.8

The usage of pesticides by the farmers is based on recommendations received from fellow farmers (74.2%) and only a few take recommendations from extension officers (25.8%) (Figure 3(a)). On the other hand, the farmers in the study area prefer to source their agrochemicals from the open market (90%), authorized dealers (54.2%), and their neighbours (24.2) (Figure 3(b)). This suggests that most of the farmers after getting recommendations from fellow farmers prefer to visit the open market for their pesticides than going to authorized dealers. Such acts could lead to the purchase of agrochemicals that are not recommended for the control of the identified pest on their farms. This act might result in agri-environmental risks, such as threats to crops, water, living organisms, and soil when inappropriate agrochemicals are used on their farms.

Figure 3. Farmers’ (a) source of information on the application and usage of agrochemicals and (b) source of agrochemicals (the results represent multiple choice of the source of agrochemicals).

Only 74.2% of the farmers adhere to the instructions on the labels whereas 25.8% indicated negative adherence to instructions (Table 4). On the usage of personal protective equipment, most of the farmers adhere to the use of raincoats (61.7%), hats (68.3%), and boots (98.3%) whereas an appreciable number of farmers use nose masks (43.3%), hand gloves (45%) (Figure 4). Damalas and Koutroubas (2016) indicated that the entrance of pesticides into the human body is mainly through inhalation, oral, and dermal routine. This shows that the use of PPEs could potentially reduce the risk associated with the non-usage of PPEs during pesticide applications. The result from our study shows that farmers do not use the full PPEs which could be referred to as the incorrect or improper usage of the PPEs to prevent exposure to the toxicity of the pesticides. A similar observation was reported by Owusu Ansah et al. (2023) among cocoa farmers on their improper usage of PPEs during weedicide applications. Yarpuz-Bozdogan (2018) also revealed that the usage of PPEs protects farmers from exposure to pesticides and their associated health effects. In general, PPEs are important items that are worn to protect one against hazardous and poisonous agrochemicals or substances. It is essential due to its safety and protection against health risks or accidents on the farms. However, the inappropriate usage by some farmers as reported in our study might pose a lot of health risks and challenges to them. Therefore, this stresses the need for continuous education to the farmers on safe practices for the usage of pesticides on their farms to prevent health complications. Nonetheless, several studies have indicated that the inappropriate or incomplete usage of PPEs poses a lot of health risks to the farmers, such as headaches, stomach aches, catarrh, dizziness, nausea, nervousness, etc. (Kenko et al., 2017; Kenko & Kamta, 2021; Owusu Ansah et al., 2023). Kenko and Kamta (2021) in their study found that the failure to use PPEs leads to impaired vision and fatigue among farmers in Cameroun.

Figure 4. Use of personal protective equipment (PPE) among tomato farmers’.

3.4. Knowledge about pesticide usage among tomato farmers

The knowledge of the tomato farmers was assessed based on their usage of insecticides in their tomato farms (Table 5) and there was a significant difference among the variables assessed. Most farmers attributed the use of pesticides in their tomato farms due to their availability (100%), fast knockdown effect (100%), cheapness (100%), and claim of being environmentally friendly (88.3%). Surprisingly, almost all the farmers (99.2%) are not aware of the active ingredients in the insecticides used in the control of insect pests when identified. Despite their low knowledge of the active ingredients in the pesticides, most farmers (67.5%) resort to the combination of two or more pesticides in their quest to control insect pests in their field. The mixture of pesticides could result in physical and chemical inconsistencies and can be harmful to the soil, environment, and health of the farmers as well as the produce leading to phytotoxicity since most farmers do not consider the active ingredient in the pesticides. However, Ahmad et al. (2008) argued that the mixture of different insecticides may lead to effective pest management due to the different modes of action of these pesticides when applied. On the contrary, Gandini et al. (2020) indicated that a combination of insecticides within the Organophosphate group may negatively affect beneficial insects while their effect on other organisms is unknown. Nonetheless, farmers mix pesticides with the notion of increasing the efficacy of the pesticides against target pests.

Table 5. Farmer’s knowledge of pesticide usage.

Variables	Percentage (%)
Reason for pesticide usage
Advisable	100
Fast knockdown effect	100
Cheaper	12.5
Environmentally Safe	88.3
Knowledge of active ingredient	0.8
Yes
Mixing of pesticide during application
Yes	67.5

Notwithstanding, most of the farmers are knowledgeable about the problems associated with the misuse of pesticides and improper calibration of the types of equipment used during the application of pesticides. For example, 92.1% indicated that it leads to the death of beneficial insects, food contaminations (83.5%), and poisoning of the farmers (95.1%). However, most of the farmers are not aware the indiscriminate use of pesticides could lead to environmental contamination (69.9%), and the development of resistance by the target insect pest (81.6%) (Figure 5). This shows that the level of awareness of the detrimental effect of pesticides on human health and the environment is very low and there is a need to sensitize farmers on the potential risks associated with the usage of pesticides. The United Nations Environment Programme (2022) reported that these pesticides were designed to cause the death of unwanted insects, and pests and negatively also result in the death of living organisms that are not the target organism. The indiscriminate usage of pesticides creates potential risks to both humans and the environment. Also, pesticide resistance is a great challenge for global agriculture and there is a need for farmers to be educated.

Figure 5. Farmers’ knowledge of the misuse/inappropriate usage of pesticides in the control of pests on their farms. Red colour represents affirmation (yes), and blue colour represents no.

3.5. Factors influencing pesticide usage among farmers

Table 6 presents the probit regression model results of the factors influencing farmers’ pesticide usage in tomato production. The probit model reveals a significance of 0.001 with a Wald Chi-Square value of 77.73, a pseudo-R square of 0.55, and a log-likelihood value of −31.72. As a result, the probit model’s choice is a well-fitted model. From Table 6, the results show that the level of education had a negative influence on the usage of pesticides by tomato farmers and this conformed to the a-priori expectation. This could be attributed that farmers can read and know the dangers associated with pesticide usage and how it can cause health issues. The marginal effect of 0.156 shows that a unit increase in the level of education decreases the probability of pesticide usage by 15.6%. The finding contradicts Denkyirah et al. (2016) who found a positive relationship between the level of education and pesticide usage among cocoa farmers. However, Bagheri et al. (2018) reported that a high level of education leads to safe pesticide usage among farmers. Further, the household size had a negative influence on the use of pesticide usage at a 1% significant level, confirming the a-priori expectation. Large household sizes could increase members’ number in farm activities, such as applying pesticide usage, manual weeding, etc. Also, large household size could be a hindrance to family expenditure in financing resources, such as pesticide purchases and hence probably reducing pesticide usage in their tomato farms. Also, a unit of 0.333 in household size will decrease the probability of pesticide usage by 33.3%. The result corroborates the findings of Migheli (2017) that an increase in family size increases the availability of family labour vital for implementing farm activities which reduces the quantity of pesticide applied. Danso-Abbeam et al. (2014) also indicated that large family size negatively influenced investment in agrochemical inputs in cocoa production.

Table 6. Factors influencing the usage of pesticides in tomato farms.

Variable	Coefficient	Std. error	p-Value	Marginal effect
Age	−0.024	0.028	0.380	−0.004
Experience	0.450	0.282	0.110	0.066
Educational level	−1.075	0.513	0.036*	−0.158
Household size	−2.268	0.508	0.0001***	−0.334
Sex	−0.115	0.612	0.851	−0.017
Health problems	−1.740	0.526	0.001***	−0.256
Adherence to instruction	0.074	0.446	0.869	0.011
Extension contacts	−0.308	0.092	0.001***	−0.046
Combination of pesticides	1.268	0.469	0.007***	0.187
Area cultivated	0.670	0.324	0.039*	0.099
Constant	5.949	2.157	0.006***
Prob > chi^2				0.001
Wald chi^2				77.73
Log-likelihood				−31.717
Pseudo R^2				0.551

*p-Value <0.05;  ***p-value <0.001.

Health problems had a negative influence on the usage of pesticides at a 1% significant level, confirming the a-priori expectation. This could be attributed that farmers are aware of the dangers and risks associated with pesticide usage in their tomato farms. Zahm and Ward (1998) reported in their studies that families of farmers have increased risks of neuroblastoma, nervous system tumours, Hodgkin disease, and bone and brain cancers due to long-term exposure to pesticide and pesticide residue in food crops. Also, the results indicate that extension agent contact was negative and statistically significant (p < 0.01) on pesticide usage on tomato farms. This conformed to the a-priori which showed that access to extension agent decreases the probability of using pesticides. This could be because farmers who meet extension agents are able to reduce the use of pesticides on their farms. Farmers who have access to extension services are active in agricultural activities (Adekunle et al., 2017), and therefore may look for alternative ways to control pests in their farms instead of using pesticides. The result confirms the findings of Anang and Amikuzuno (2015) which state that access to extension services influences farmers to be less likely to adopt pesticides to control pests and diseases on their farms.

With regards to the combination of different types of pesticides by farmers, there was positive and statistically significant (p < 0.01) on the usage of pesticides. This confirms the a-priori expectation. This could be because different pesticides with different active ingredients make pesticides more effective for farmers to use on their farms. The findings concur with the observation of Jensen et al. (2011) in Cambodia where most farmers were mixing various pesticides to make it more effective. Further, the number of acres cultivated was positive and statistically significant (p < 0.05) on the use of pesticides for the control of insect pests in their field. This could be that as the area of acres cultivated increases more pesticides are used to prevent pests and disease infestation on the farms since manual work becomes difficult to control pests. The marginal effect of 0.099 shows that a unit increase in acre of land increases the probability of pesticide usage by 9.90%. The finding is at odds with the results of Yasin et al. (2003) who found a negative correlation between farm size and pesticide usage. Danso-Abbeam and Baiyegunhi (2017) also revealed that farmers with large farms had a higher likelihood of increasing their investment in agrochemical inputs, such as fertilizers, fungicides, and insecticides as compared to their counterparts.

4. Conclusion and recommendations

The study analysed the pesticide usage pattern and knowledge of tomato farmers in the Pru West District as well as the factors influencing farmers’ decision to use pesticides on their farms for insect pest control. The results of the analysis revealed that the appearance of pests, diseases, and crop damage were the decisions most farmers look for before applying pesticides. Morning and late noon were the times of pesticide application and the majority of the farmers adhered to instructions before applying pesticides. Moreover, availability, fast knockdown effect, cheapness, and claim of being environmentally friendly were linked to the knowledge of pesticide usage among most farmers. Out of the factors considered to influence the usage of pesticides among the farmers, six of the factors significantly influenced their choice of pesticide usage. Education, household size, health problems, and extension contact had a negative relationship with pesticide usage while the combination of pesticides and the area under which the crop was cultivated had a positive relationship with pesticide usage. The findings of this study have helped to assess the adherence of tomato farmers in Ghana to the existing pesticide regulations and guidelines. Further, this study adds to the knowledge of the safety of tomato consumption in Ghana. On a policy basis, we propose the continuous monitoring of the change in the concept of pesticide use and its relationship to the factors affecting their optimal use to ensure compliance with the instructions or not. Also, policymakers and regulatory bodies need to strengthen and enforce relevant regulations on the usage of pesticides among farmers in relation to environmental safety.

Ethical approval

Farmers were informed that the data collected would be exclusively used for academic purposes, thereby ensuring the confidentiality of their identities. Furthermore, it was made clear that individuals selected for the present survey retained the prerogative to opt-out at any point during the interview process or decline to respond to specific questions should they find them discomforting.

Permission to reproduce material from other sources

Not applicable.

Author contributions

Remember Roger Adjei: Conceptualization, Formal Analysis, Investigation, Data Curation, Writing -Original draft; Evans Kyere: Investigation, Data Curation, Najeeb Ibrahim: Formal Analysis, Data Curation, Writing - review & editing; Amanda Sarfo Boateng: Writing - review and editing; Shadrack Asomah: Writing - review and editing; Samuel Kwesi Asomaning: Writing - review & editing; Charles Adarkwah: Writing - review & editing. All the authors read and approved the final version of the manuscript.

Acknowledgements

The authors are grateful to the extension agents who assisted in reaching out to the farmers in the communities. We are also grateful to the farmers for taking the time to respond to our calls and avail themselves of this study to be conducted. Special thanks to the four anonymous reviewers for their valuable comments and suggestions for improving this article.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data will be made available upon reasonable request from the corresponding author.

Additional information

Funding

This research received no specific grant from the public, commercial, or non-governmental funding agencies.

Notes on contributors

Remember Roger Adjei

Remember Roger Adjei is a Research Scientist in Crop Science. His research area includes agronomy, crop modelling, plant physiology, plant breeding and integrated pest management.

Evans Kyere

Evans Kyere is a graduate in Agriculture (Crop Production) from the University of Energy and Natural Resources (UENR).

Najeeb Ibrahim

Najeeb Ibrahim is a graduate in Agribusiness and a research consultant. His research interests includes econometric models, Agribusiness markets, Supply Chain, Agrifinance and Investment Portfolio, consumer studies and agribusiness Trade and Impact assessment, Standards and Certification, Risks and Social Protection.

Amanda Sarfo Boateng

Amanda Sarfo Boateng is a graduate in Crop Science with research interests in Nitrogen Use Efficiency, Agronomy and Soil Science.

Shadrack Asomah

Shadrack Asomah is a laboratory technician and research associate at UENR with research interest in integrated pest management, entomophagy and crop science.

Samuel Kwesi Asomaning

Dr. Samuel Kwesi Asomaning is a Senior Lecturer at the Department of Horticulture and Crop Production (UENR). His scope of research and practice has been Soil fertility management and plant nutrition and Soil chemistry, with special interest in Soil Phosphorus management and sorption studies.

Charles Adarkwah

Prof. Charles Adarkwah is a professor of postharvest entomology at the Department of Horticulture and Crop Production, UENR. His research interest are integrated pest management and biological control of stored product insect pests.