Institutional Factors Influencing Sunflower Productivity in Mkalama District

Sunflower is a globally significant crop, driven by the increasing demand for edible oil. Tanzania possesses the potential for sunflower production; however, current yields fall short of projected levels. This study conducted in the Mkalama District, Singida Region, Tanzania, aimed to identify the institutional factors influencing sunflower productivity. A cross-sectional research design was used and a sample of 147 respondents was selected for this study. Data collected were analyzed using SPSS software. The study findings highlight several influential factors, including access to land for production, availability of storage facilities, and marketing availability that affect sunflower production. To bolster sunflower production, government and non-governmental organizations should prioritize efforts to ensure timely availability of quality inputs, sufficient land availability, invest in storage facilities, provide comprehensive extension services, and develop effective marketing strategies. This will improve sunflower production and ensure oil availability in Tanzania.

Introduction

Sunflower (Helianthus annuus L.) is the third most produced oilseed crop in the world [1], and its demand for edible oil has been increasing globally and regionally [1], [2]. In Tanzania, sunflower production is critical as it is one of the most important vegetable oils with high value and importance in the international market [2]. Sunflower accounts for about 40% of the national cooking oil supplied in Tanzania [3]. Despite favorable conditions for sunflower production in Tanzania, the average production is below its potential of about 3 tons per hectare, and the country imports 60% of its oil demand, which costs about US$ 294 billion of foreign currency annually [4], [5]. Smallholder farmers who cultivate one to ten acres per household are the main producers of sunflowers, and efforts have been taken by the government and non-government organizations to increase production [3], [6], [7]. Sunflower production has been taken seriously in Tanzania since the year 2000s [2]. Approximately 6% of arable land in Tanzania is used for the cultivation of sunflower [8]. The central corridor, which includes Singida and Dodoma regions, leads in production [4]. Efforts have been made to increase production by implementing protectionist policies, breeding, certifying, promoting, and distributing improved varieties, and strengthening research and extension services [3], [5], [7]. However, at Mkalama District, which is regarded as a leading district in sunflower production in the Singida Region [9], the average sunflower production is 350 to 600 kg per acre, which is lower than the optimum yield of 900 kg per acre. Therefore, this study intends to assess the factors affecting sunflower production in the Mkalama District.

Theoretical Framework

The study adopted the theory of production, which summarizes the basic factors like land, labor, capital, and their interplay with the production of goods and services. Though mainly used in economics to decide investments [10]. The theory seems to be suitable for analyzing and discussing factors related to agricultural production, like a sunflower. Therefore, this theory guided the discussion on how the presence or absence of institutional factors such as capital, entrepreneurship and marketing, access to extension services, credits, availability of quality seeds and pesticides, use of better farm inputs, and good farming practices within their institutional context might influence sunflower yield in the study area.

Capital, as a factor of production in sunflower cultivation, encompasses man-made goods like machinery, equipment and chemicals that aid in the production process. These resources differentiate themselves from consumer goods and contribute to the efficiency and productivity of sunflower farming [11], [12]. Advanced machinery and specialized chemicals can optimize planting, irrigation, harvesting, and processing activities, reducing labor requirements and enhancing overall output [13]. Access to capital is influenced by institutional factors such as credit availability and financial support programs. However, limited access to capital poses a challenge, particularly for small-scale farmers [10], [14]. To address this, inclusive access to credit and targeted financial assistance programs should be implemented to enable sunflower producers, especially those in marginalized areas, to invest in modern technologies and improve their production capabilities.

Entrepreneurship is a crucial factor of production in sunflower cultivation, involving the transformation of ideas into successful businesses and marketing. Entrepreneurs leverage land, labor, and capital to contribute to the supply of sunflower products [10]. Successful entrepreneurs in this field demonstrate innovation and a willingness to take calculated risks. They introduce new cultivation techniques, provide credits, improve product quality, and develop value-added sunflower products [10]. Institutional support is necessary to overcome challenges and create an environment conducive to entrepreneurial endeavors and marketing of sunflower products. This includes providing access to resources, addressing market uncertainties and implementing supportive policies that facilitate finance, technical assistance, training programs, extension, research and development [15], [16]. By fostering entrepreneurship, the sunflower industry can achieve sustainable growth and remain competitive.

Conceptual Framework

Conceptual framework represents the variables of the study, their functional definition and how they interact in the study (Fig. 1). The conceptual framework, as depicted in Fig. 1, illustrates the study’s key variables, their functional definitions, and their interplay within the context of sunflower production. In this framework, we consider four primary factors of production: labor, land, capital, and entrepreneurship [17]. Labor’s influence on sunflower production depends on its size; a larger labor force positively impacts production. Traditionally, this can be observed in family size. Similarly, land availability and land status play a crucial role in determining sunflower production outcomes. Capital, particularly access to credit facilities and farmers’ income, investment costs and other uses, significantly affects sunflower production. Lastly, entrepreneurship encompasses the knowledge and ability to effectively combine the resources to influence sunflower production activities [18]. This can include the ability to plan, manage, produce, and search the market after production to ensure high returns.

Fig. 1. Study conceptual framework.

Further, the study considered coercive, normatic and minetic factors influencing sunflower production in the Mkalama district [15]. Coercive factors refer to external pressures or forces that compel organizations to conform to certain practices or standards such as access to credits. The normatic factors include division of labor and access to storage facilities which are related to social norms, values, and expectations that guide organizations toward certain behaviors or structures. The minetic factors include access to market, pricing set, access to extension services and processing of sunflower which imitate or mimic the strategies, structures, and practices of successful or reputable organizations, individuals or institutes [15]. Hence, this study used both production and institutional theories. The theory of production details on productivity based on input-output relationships while the institutional theory detailed the influence of different factors including norms, routines, rules and other factors affecting productivity of sunflower [19], [20].

Methodology

Description of the Study Area

The study was conducted in Mkalama District in Singida region, Tanzania, between September and October 2022 in six villages of the district, namely, Dominiki, Mwangeza, Munguli, Hilamoto, Ikolo, and Endasiku. Mkalama District has a long history of producing sunflower and has a higher trend of leading in sunflower production than other districts in the region [21], [22]. Mkalama has a larger number of smallholder farmers than other districts in the region.

Research Design

The research design adopted for the study was a cross-sectional research design, which allowed data collection from the sample of study at one point in time using survey techniques [23]. The cross-sectional design permitted a description of the population that differs in variables of interest but shares other socioeconomic characteristics.

Study Population and Sampling Design

The study population consisted of farmers involved in sunflower production in Mkalama District, and the sampling unit or unit of analysis was a smallholder sunflower farming household. Simple random sampling was used to obtain the estimated sample size of 147 respondents determined by using the formula by [24] summarized below:

n=N1+N(e2)where

n = Required sample size

N = Population size

e = Allowable error n=2573/(1+2573(0.05×0.05))

But the size was big to use due to the time limit and budget constraint, instead the allowable error was adjusted from 0.05 to 0.08. According to [25], the 0.08 allowable error is used as a constant to account for both the qualitative and quantitative error acceptable, which is 0.03 for quantitative and 0.05 for qualitative data to be obtained. The allowable errors added together summed to 0.08.

Therefore, n = 2573/1 + 2573 (0.08 × 0.08) = 147. A sample size of 147 was the actual number of respondents participated in the study.

Data Collection

The study involved both quantitative and qualitative data. Data were collected by using a structured questionnaire containing both open and close-ended questions. Focus Group Discussions (FGDs) and key informant (KI) interviews were conducted to collect qualitative data. The quantitative data included the number of sunflower bags that a farmer harvested (65 kg bags) and demographic information such as age. The qualitative data included access to credits, extension services, market, loans and storage facilities, as well as demographic information such as sex, occupation, education level and marital status of respondents.

Data Analysis

Quantitative data were analyzed using the Statistical Package for Social Sciences (SPSS) version 20, whereby descriptive analysis was used to compute frequency, percentages, and means. A binary logistic regression model was used to test the effect of different factors on sunflower productivity as given in the equation below:

y=eb0+b1x1+b2x2+b3x3+b4x4+b5x51+eb0+b1x1+b2x2+b3x3+b4x4+b5x5where y is the predicted or expected value of the dependent variable (sunflower productivity), x₁ through x_n are distinct independent or predictor variables, b₀ is the value of y when all the independent variables are equal to zero (i.e., the y-intercept), and b₁ through b₄ are the estimated regression coefficients for each predictor variable. The independent variables (x₁ to x₅) used in the model are access to extension services, processing sunflowers, access to loans from banks, storing sunflowers and access to the market.

Results

Respondent’s Demographic Characteristics

The social and economic characteristics are described by using frequency distribution tables and charts for the preliminary information of the respondents and other factors that play a major role in the study. In this part, demographic factors, including age, sex, marital status, household size, Highest education level and Occupation, were described by using a frequency distribution table and charts, as shown in Table I.

Table I. Demographic Factors of Respondents (n = 147)

Variables		Frequency	Percent (%)
Sex	Female	48	32.7
	Male	99	67.3
Marital status	Single	14	9.5
	Married	128	87.1
	Divorced	4	2.7
	Widow/Widower	1	0.7
Highest education level	Primary level	123	83.7
	Secondary level (O-level)	15	10.2
	Secondary (A-level)	9	6.1
	Higher learning institutions	0	0.0
Occupation	Farmer	145	98.6
	Civil servant (employed)	1	0.7
	Other	1	0.7

Results in Table I show that most of the respondents were male, accounting for about 67.3%, and females were 32.7%, almost half the population of males. For the case of marital status, most of the respondents were married, accounting for about 87.1%, followed by single, who were 9.5%, and divorced, who were 2.7%. Regarding the education background of respondents, most of the respondents (83.7%) had attained primary education level, followed by those with ordinary secondary education level (10.2%), and the rest (6.1%) had advanced education level. Further results show that most of the respondents (98.6%) were farmers, while 0.7% were civil servants.

Sunflower Productivity Level

Table II presents the production levels of sunflower across various villages, with a total of 147 respondents included in the analysis. The Table II provides information on the count and percentage distribution of sunflower production levels categorized as high, moderate and low for each village. The majority of the respondents showed a moderate production level, with Dominiki having the highest count, 37 (32.7%), followed by Mwangeza at 32 (28.3%) and Munguli at 19 (16.8%). The villages with high production levels were Munguli 18 (62.1%) and Ikolo 5 (17.2%). On the other hand, a low production level was observed in two villages: Dominiki 2 (40.0%) and Mwangeza 2 (40.0%).

Table II. Production Level of Sunflower Across Villages (n = 147)

Village	Production level
	High		Moderate		Low
	Count	Percent (%)	Count	Percent (%)	Count	Percent (%)
Dominiki	3	10.3	37	32.7	2	40.0
Endasiku	0	0.0	7	6.2	0	0.0
Hilamoto	0	0.0	6	5.3	0	0.0
Ikolo	5	17.2	12	10.6	0	0.0
Munguli	18	62.1	19	16.8	1	20.0
Mwangeza	3	10.3	32	28.3	2	40.0

The Pearson chi-square test (Chi² = 31.4, df = 10, p = 0.000503) indicated a significant association of sunflower levels across villages.

Based on the findings in Fig. 2, it can be clearly seen that only 19.72% of the respondents fall in the category of high production level. It indicates that a relatively small proportion of the respondents achieved a high level of sunflower production. About 76.87% of the interviewed respondents fall in the category of Moderate Production Level. On the other hand, low production level was represented by only 3.4% of the respondents.

Fig. 2. The overall sunflower production level.

These percentages provide a relative comparison of the distribution of sunflower production levels across the villages. It suggests that the majority of villages have a moderate level of production, followed by a smaller percentage of villages with high production and an even smaller percentage with low production. However, it is important to consider the absolute counts alongside the percentages to gain a complete understanding of the distribution.

Institutional Factors Influencing Sunflower Production

The results in Table III show that out of 147 interviewed respondents, only 29 (19.7%) had access to extension services, while the rest (80.3%) had no access to extension services. Similar to that, the majority of respondents (99.3%) had no access to loan from bank. Only one farmer (0.7%) accessed a loan from bank.

Table III. Institutional Factors to be Used in the Model (n = 147)

Variable		Frequency	Percent (%)
Access to extension services	No	118	80.3
	Yes	29	19.7
Processing sunflower	No	131	89.1
	Yes	16	10.9
Access to loan from bank	No	146	99.3
	Yes	1	0.7
Storing sunflower	No	101	68.7
	Yes	46	31.3
Access to market	No	7	4.8
	Yes	140	95.2

Also, the study results show that the majority of respondents (68.7%) had no facilities for storing sunflowers, and therefore, most of them (95.2%) sell their produce immediately after harvesting. It was further noted that most farmers 131 (89.1%) do not process sunflower. Only 16 (10.9%) processed sunflower before selling.

Modelling Institutional Factors Affecting Sunflower Production

Omnibus tests of model coefficients were used to test a null hypothesis if all coefficients were zero. The null hypothesis was rejected at p = 0.022. The goodness of fit of the model was tested using Hosmer and Lemeshow Test to test if all data were well fitted. The null hypothesis was accepted at p = 0.429. The binary logistic regression model results in Table IV shows the variability of influences of different factors on sunflower productivity. The model was computed at 0.05 level of significance, with the dependent variable being production per acre and the institutional factor serving as an independent variable including access to extension services, processing sunflower, access to loan from bank, storage of sunflower, access to market.

Table IV. Institutional Factors Affecting Sunflower Production (n = 147)

Variables in the equation		B	S.E.	Wald	df	Sig.	Exp(B)	95% C.I. for Exp(B)
								Lower	Upper
Step 1a	Access to extension services	1.376	0.660	4.345	1	0.037	3.960	1.086	14.446
	Process sunflower	0.206	0.809	0.065	1	0.799	1.229	0.252	6.005
	Access to loan from bank	−0.087	0.921	0.009	1	0.925	0.917	0.151	5.570
	Storing sunflower	1.331	0.592	5.045	1	0.025	3.784	1.185	12.084
	Access to market	0.372	0.301	7.002	1	0.019	1.451	1.177	5.584
	Constant	−2.808	0.544	26.641	1	0.000	0.060

Access to Extension Services

The results indicate that there was statistically significant effect (p = 0.037) on the access to extension services for farmers within the study area. The increase in unit extension services, results to 1.376 increases in productivity. This justified the necessity of extension services in bolstering sunflower production. It is noteworthy that key informants (KI) and focused groups strongly emphasized the pivotal role of extension services in boosting sunflower productivity.

In the FGD, respondents insisted on the availability of extension services for improved productivity. At Munguli and Mwangeza, villagers emphasized the necessity of agro-input provision as well as extension service provision:

“There is great importance in providing extension education and increasing the number of extension farmers, as the current ratio of one extension farmer to a large area is insufficient.”

Villagers from Endasiku village also expressed the need for knowledge and farming skills from extension officers:

“The lack of extension education on farming practices and the absence of guidelines for proper sunflower production were mentioned as key issues. There is a significant need for support in acquiring knowledge and guidance for efficient sunflower cultivation.”

The key informants, which were skilled farmers and village leaders, also highlighted the gap of inadequate input supply, extension service and poor farming techniques, which results in low productivity.

“The experienced farmers stressed the importance of accessing quality seeds and emphasized the need for extension education to enhance farmers’ knowledge and skills. Also, highlighted delays by seed distributors and expressed concerns about the high prices and scarcity of hybrid seeds. The farmer also mentioned the significance of a cropping calendar and the establishment of demonstration plots to showcase best practices. The village chairperson added insights, focusing on modern farming practices, and advocated for government interventions to renovate sunflower cultivation”. Their input from both experienced farmers and village leaders shed light on the crucial aspects of sunflower cultivation, including seed quality, knowledge dissemination, availability of hybrid seeds, and the role of government interventions. Addressing these concerns through government interventions, improved extension services, financial support, and research initiatives can revitalize and improve sunflower cultivation sector in the communities.

Availability of Storage Facility

Talking parameters estimation, results show that at 0.05 level of significance, the obtained p-value is 0.025, which is below the significance level of 0.05; hence there is a significant influence of storage facility toward the production of sunflower. This implies that for a unit increase in the use of storage, there is a 1.331 bags/acre average increase in the production of sunflower. The available storage facilities were privately owned by farmers. The residents of Ikolo village:

“They highlighted challenges related to insect problems during storage, storage facilities, and infrastructure to transport their produces to storage facilities or market” [26].

Access to the Market of Sunflower

Further results show that there is significant influence of the practice of marketing sunflower towards production of sunflower among farmers at 0.05 level of significance, the obtained p-value is 0.019, which is less than 0.05 level of significance. This implies that for every unit increase in sales of sunflower, there is an average increase in production of 0.372 bags/acre. On the other hand, factors like processing of sunflower, credit access through loan from bank and availability of market they had no influence on the level of production at 0.05 level of significance.

During focused group discussion (FGD), villagers from Hilamoto, Munguli and Mwangeza also insisted on the importance of market accessibility for both agro-inputs and produced products:

“There is a need for government intervention to ensure market accessibility and availability of agricultural inputs, including the reduction of seed prices and subsidized prices for agro inputs as well as good prices of harvested sunflower”.

These findings underscore the diverse challenges faced by different villages in sunflower production, including access to resources and information, infrastructure limitations, and financial constraints.

Discussions

The study found a difference in production quantity of sunflower among villages and villagers. This may be associated with land ownership and size of cultivation, as well as the quality of input and skills used in production. Specifically, individuals cultivating sunflowers over a larger area exhibited higher yields compared to those producing on smaller plots of land. The profit gained also depends on the ownership of farms or renting. This observation is consistent with previous research conducted in similar agricultural contexts [8], [27]. The positive relationship between land size and sunflower production can be attributed to several factors. Firstly, a larger cultivated area provides more space for sunflower plants to grow and receive adequate sunlight, nutrients, and water, thereby promoting optimal growth and yield [28]. Additionally, a larger land area allows for better crop management practices, such as proper spacing, effective pest and disease control, and efficient utilization of farming machinery, which collectively contribute to increased production [29]. Furthermore, the availability of resources and investment capacity often correlates with the ability to access, own and cultivate larger land areas. Farmers with more significant resources, including financial capital, agricultural inputs, and access to mechanization, are more likely to own and cultivate larger plots of land, leading to higher sunflower yields [30].

The study also found a significant influence of storage facilities on production. In agricultural production, the accessibility of storage facilities is crucial, especially for crops like sunflower that require careful storage to retain quality and avoid rotting during storage. According to this survey, only 31.3% of the farmers in the study area had access to sunflower storage facilities. This shows that to support the production and commercialization of sunflowers in the area, storage infrastructure investment is necessary. The available storage facilities can potentially impact production capacity as it introduces concerns regarding post-production storage logistics. Previous research by [31] and [32] has demonstrated the significance of storage facilities for agricultural output and trade. Farmers may experience losses and lower incomes if they are unable to store their harvests properly and retain their quality. Additionally, farmers selling their produce shortly after harvesting due to a lack of storage facilities may lead to lower prices and poorer profitability.

The study’s findings demonstrated a considerable impact on sunflower marketing, with most participants (95.2%) selling their crops following harvest. This result is in line with earlier studies [17], [33], which claimed that sunflower was a significant income crop for smallholder farmers. Farmers who can sell their sunflowers have a source of income, which can enhance their quality of life and assist in reducing poverty in the study area [34]. It is crucial to remember that sunflower prices are prone to market volatility, which may have an impact on how profitable the crop is for farmers [33]. However, it was further informed that, middlemen play a significant role in sales of sunflower, which in turn reduces farmer’s profit along the crop value chain.

According to the key informants and focus group discussions, extension services play a pivotal role in supporting sunflower farmers and enhancing their productivity. Extension services, delivered by agricultural experts and professionals, provide valuable information, technical assistance, and training to farmers, helping them adopt modern farming practices, improve crop management, and overcome challenges in sunflower cultivation [35]. The availability of extension services ensures that farmers have access to up-to-date knowledge on best practices, pest and disease management, soil health, and climate-resilient techniques. By bridging the gap between research findings and practical implementation, extension services empower sunflower farmers with the necessary skills and knowledge to optimize their yields and make informed decisions in the face of changing agricultural conditions. Moreover, these services also play a crucial role in disseminating information about government support programs, subsidies, and market opportunities, enabling farmers to make strategic choices and enhance their profitability [36].

Conclusion and Recommendation

Conclusion

This study has identified several key variables that influence the productivity and profitability of Tanzania’s sunflower industry. The findings highlight the significance of improving access to land and providing adequate storage facilities. These factors contribute to the growth of the sunflower industry and can uplift the standard of living for farmers. Selling sunflower after harvest serves as a crucial source of income for farmers and plays a role in poverty alleviation, although market access persists.

Recommendations

To enhance the overall effectiveness and competitiveness of sunflower production, policymakers and stakeholders in the agricultural sector should prioritize investments, production infrastructure, land access, technology, and knowledge transfer through extension services. By addressing these critical factors, the sunflower industry can become more profitable and sustainable, benefiting both farmers and the broader economy. This study serves as a foundation for further research and the development of policies in Tanzania’s agriculture sector, particularly regarding oil crops.