ORIGINAL RESEARCH article
Sec. Land, Livelihoods and Food Security
Volume 5 - 2021 | https://doi.org/10.3389/fsufs.2021.777790
Factors Influencing the Extent of the Commercialization of Indigenous Crops Among Smallholder Farmers in the Limpopo and Mpumalanga Provinces of South Africa
- 1Centre for Transformative Agricultural and Food Systems, School of Agricultural, Earth and Environmental Sciences, College of Agriculture, Engineering and Science, University of KwaZulu-Natal, Pietermaritzburg, South Africa
- 2African Centre for Food Security, School of Agricultural, Earth and Environmental Sciences, College of Agriculture, Engineering and Science, University of KwaZulu-Natal, Pietermaritzburg, South Africa
- 3Department of Agricultural Extension and Rural Resource Management, School of Agricultural, Earth and Environmental Sciences, College of Agriculture, Engineering and Science, University of KwaZulu-Natal, Pietermaritzburg, South Africa
- 4Department of Agricultural Economics, Obafemi Awolowo University, Ile-Ife, Nigeria
- 5Disaster Management Training and Education Centre for Africa, University of the Free State, Bloemfontein, South Africa
Smallholder farmers encounter countless challenges that not only restrict them from maximizing market opportunities but also limit their access to the markets. This paper aims to achieve a thorough understanding of the factors that influence the market participation of indigenous crops by smallholder farmers while also analyzing the extent of market participation in South Africa. An analyzable sample size of 1,520 was used for the study. Household commercialization index (HCI), T-test, description analysis, and a double hurdle model with quasi-maximum likelihood fractional response model were employed to analyze the commercialization and extent of commercialization among indigenous crops by smallholder farmers in South Africa. The study demonstrated that a farmer's decision to participate in the market is highly dependent on gender, off-farm income, access to market information, and a family member being infected by HIV. Factors such as household size and access to the market had statistical significance in the extent of market participation by smallholder farmers. While we recommend the need to intensify appropriate training for farmers and extension workers involved in the area of indigenous crops, it is also important that indigenous crops are given the necessary considerations by the government and research institutions so that their demand in the market could increase. There is a need to develop a clear support plan for the few farmers that have decided to be involved in the farming of indigenous crops even though they are not highly marketable. On the other hand, there is also a need for consumer awareness campaigns in South Africa, on the income and nutritional benefits of indigenous crops.
The agricultural sector is the backbone of many South African households (Pawlak and Kołodziejczak, 2020). The majority of households residing in rural areas not only depend on agriculture for their livelihoods and well-being but also are involved in subsistence agriculture which is characterized by a combination of crop and animal production (Shackleton et al., 2001; Gautam and Andersen, 2016). As reported by Statistics South Africa (2019) in the General Household Survey report, about 15.3% of the households in South Africa are involved in agriculture. Some of the crops being produced by these households are ecologically resilient indigenous crops that can withstand a changing climate and other challenges (Akinola et al., 2020). “Indigenous crops are defined as plant species that are either genuinely native to a particular region, or which were introduced to that region for long enough to have evolved through natural processes or farmer selection” (Mahlangu, 2014). These crops are not only a source of income for several smallholder farmers but also the primary source of nutrients for food and nutritional security. Furthermore, they can contribute to sustainable food systems under climate change since they are ecologically resilient (Akinola et al., 2020; Hlatshwayo et al., 2021). Gitz et al. (2017) reported that about 70% of the poor residing in rural areas, completely or partially depend on indigenous crops for their livelihoods. However, smallholder farmers especially in developing countries are faced with numerous constraints that hinder their commercialization of indigenous crops (Meemken and Bellemare, 2020).
Smallholder farmers are faced with a lack of production and marketing knowledge, information, and skills that could enable them to compete with commercial farmers (Minot and Sawyer, 2016). Moreover, the majority of smallholder farmers are also faced with poor quality infrastructure, inadequate storage facilities and transport, and are associated with a lack of information and skills which leads to high transaction costs of participating in the market and hence, over-reliance on traditional social networks and mechanisms for marketing their produce (Ali et al., 2021). Some smallholder farmers still use bartering or gifts to exchange or obtain seeds and crops.
The literature also revealed that other factors that affect the commercialization of indigenous crops are socio-demographic factors such as education level, market information access, HIV status, source of income, and age (Key et al., 2000; Adenegan and Adewusi, 2007; Lubungu et al., 2012; Dlamini-Mazibuko et al., 2019). Smallholder farmers in South Africa are generally illiterate, aged and lack market information (Hlatshwayo et al., 2021). Smallholder farmers operate on small pieces of land which leaves them with no choice but to consume most of their produce with a minimum to sell (Rapsomanikis, 2015). Lack of land possession limits farmers from engaging in long-term investment and makes it difficult for them to access credit. Also, the government and policymakers do not recognize them and hence the benefits of indigenous crops remain unknown (Von Loeper et al., 2016).
While some studies (Karaan et al., 2006; Akinnifesi et al., 2007; Akinola et al., 2020) have been conducted in Africa on several agricultural experiments with regards to indigenous crops and their economic potential, South Africa does not have much information on the factors that affect the participation of smallholder farmers in the commercialization of indigenous crops. Mahlangu (2014) reported that there is a market for indigenous crops and, therefore, it is important to understand the impact of market participation on the livelihoods of smallholder farmers in South Africa. Lack of knowledge on the impact of marketing the indigenous crops could be the reason why some smallholder farmers are not participating in the market in the first place. The provision of information on the benefits of commercializing these crops together with the strategies to address the factors that affect their market participation will be useful to smallholder farmers and may not only influence them but also open up opportunities for them to grow for commercial purposes. Understanding the contribution of indigenous crops toward rural households or smallholder farmers' livelihoods and food security can raise awareness with regard to effective participation. They can adopt strategies to grow these and sell them to the market. The information will be useful in the implementation and formulation of relevant strategies to commercialize indigenous crops effectively.
The main purpose of this study was to identify the factors that influence the commercialization and the extent of the commercialization of indigenous crops among smallholder farmers since very little is known about the issue. It was clear from the literature that some farmers had been suffering from a lack of market information, farming equipment, and support from extension services. This should be addressed as it results in farmers making poor decisions about which channels of the market to participate in. Lastly, in line with its objective, this study has provided recommendations that will help the government with information about the importance of allowing smallholders to participate in the market, and policymakers to recognize the role of smallholder farmers in market participation.
The Study Area Description
This study was conducted in the Northern and North-East Regions of South Africa covering about two of the nine provinces in South Africa. Limpopo and Mpumalanga provinces are populated by smallholder communal farmers that mainly depend on agricultural and livestock farming for their livelihoods. Limpopo is situated in the Northern part of South Africa, covering about 125,754 km2 of the area, which is only 10.2% of the total area of the country. Its population is about 5,8 million with five districts of Mopani, Vhembe, Capricorn, Waterberg and Sekhukhune (Christopher, 2017). The people in this province are highly involved and dependent on agriculture for survival, as 89% of the peoples' occupation is agriculture. The study was conducted in the districts mentioned above.
The second study area is Mpumalanga province, which is located in the North-Eastern part of South Africa. It covers about 6.5% of the country's land area. It consists of about 4.04 million people with 72% being involved in agriculture (Christopher, 2017). The overall rainfall received in this province per year is about 1,000 mm, with its warm and temperate weather conditions as it lies 665m above sea level. This province contributes to the agricultural economy through farms produce such as corn (maize), sugar, cotton, groundnuts, potatoes, wheat, and indigenous crops such as Amaranth, Vegetable Cow-pea, African eggplant, Okra and pumpkin (Lehohla, 2016). A variety of fruit is also produced in this province including mangoes and oranges in the subtropical low-veld, whereas peaches are produced at higher elevations.
Data Types, Sources and Methods of Data Collection
While the data analyzed in this study focuses on two provinces, the research was part of a bigger baseline assessment study that was conducted in four provinces in South Africa. Therefore, the data used in this study has been extracted from an assessment study that was conducted in various provinces of South Africa by the South African Vulnerability Assessment Committee (SAVAC), led by the Secretariat hosted in the Department of Agriculture, Land Reform and Rural Development (DALRRD) in 2016. Data collected included the demographics of the participants, crops (indigenous and cash crops) produced and consumed by rural households, food security and nutrition information. However, the purpose of this particular study is to assess the factors influencing the extent of indigenous crops' smallholder farmers' market participation. Smallholder farmers were asked to list the different types of crops they produce, consume and sell. From the list of crops identified by the smallholder farmers, indigenous crops were selected (Table 1).
The study used a quantitative research method to collect data. The multi-stage stratified random sampling technique was used to select households' representatives' samples. Characteristics such as institutional factors, sales, socio-economic characteristics, household sizes, and outputs were used to divide the farmers into groups in each site. The DAFF surveys covered random samples of about 4,286 rural smallholder farmers in four provinces of the country. However, this study has only focused on two of the provinces, namely Mpumalanga and Limpopo, with a total of 1,520 respondents selected.
Methods of Data Analysis
The most used econometric analytical techniques in the analysis of crop market participation include Tobit models, double-hurdle models, and Heckman sample selection models (Donkor et al., 2018; Chen et al., 2020; Tafesse et al., 2020). The Heckman approach is more suitable for incidental truncation where the unobserved values are represented by the zeros; for instance, in situations of wage rate models where the unemployed people are included in the sample (Heckman, 1976; Cameron and Trivedi, 2005). This study used the double-hurdle model, which has been used by many previous studies to analyze the determinants of market participation (Reyes et al., 2012; Achandi and Mujawamariya, 2016; Ingabire et al., 2017).
The double-hurdle model is a two-step decision model: (1) the household decides whether or not to participate in the indigenous crop market and (2) the household decides on the volume of indigenous crops to be marketed. The double-hurdle model (DHM) is known to be a corner solution outcome in dealing with issues of agricultural commercialization of smallholder farmers. This model allows for two types of zero: always zeros, and corner solutions (so that participants have to overcome two hurdles instead of one to sell a positive quantity). It was perfect for this study because it estimates unbiased, efficient and consistent parameters following numerous studies that have applied it (Komarek, 2010; Mather et al., 2013; Achandi and Mujawamariya, 2016). Also, it does not require the participation decision and the participation intensity to be determined in the same process. In the first stage of the double-hurdle model, values of 1 and 0 are assigned to represent the choice of the smallholder farmer's decision on whether to commercialize the produce or not. Then in the second stage, the factors that determine the extent of commercialization of indigenous crops sold to the market were analyzed using a fractional response model with quasi-maximum likelihood.
A smallholder farmer's decision to participate in indigenous crops marketing can be represented by:
Where is the latent variable that indicates whether or not the farmer participates in the market (sells the crops), x is a vector of observed independent covariates explaining the decision of market participation, β is an unobserved parameter that is to be estimated and ei is an unobserved error term capturing all other factors, and eiN(0, 1).
MARKET_PARTi is positive MARKET_PARTi = 1 if a farmer effectively participates in the selling of crop (as a seller), i.e. , and MARKET_PARTi = 0 or negative if a farmer i chooses not to or does not sell in the market. is the quantity of crops sold by smallholder farmer i Conditional to market participation decision.
In accurate terms, the probit model in stage one of assessment is expressed as:
Where Pr(MARKET_PARTi) is a smallholder farmer's probability of settling to participate in the market in the form of selling their produce or not, X0 is a constant parameter, whereas X1…Xn are parameters are to be estimated, β1…βn are identified in Tables 1 and 2 respectively as the vector of explanatory variables, e represents an error term.
From the probit model of the first hurdle, the Inverse Mills Ratio (IMR) is predicted and included as a regressor in the second stage (second hurdle). This is done purposefully to control the selection bias to obtain unbiased, consistent as well as efficient estimators using ordinary least squares. The IMR equation is expressed as follows:
Where ϕ denotes the normal probability density function. Following is the second-stage equation:
Where E denotes the assumption operator, Y representing the (continuous) extent of the vegetables sold in the market, x influences the volume of the vegetables sold and is known as the vector of independent variables, and β is said to be the vector of the comparing coefficients to be assessed.
In the second hurdle, the study employs the method recommended by Papke and Wooldridge (1996). A fractional response model was employed to estimate the level of commercialization while taking into account the type of dependent variable. The generated sample selection term IMR from the probit model (first hurdle) was fitted as an exogenous variable to account for potential selectivity bias in the fractional response model regarding the level of commercialization (Wooldridge, 2012). The second stage (level of commercialization) equation is expressed as:
where HCI is the observed response on the level of commercialization (HCI)1, E is the expectation operator; Pi is a vector of the household characteristics; β is a vector of parameters to be estimated; λ is the IMR which accounts for sample selection bias in the probit model, and ω is the associated parameter to be estimated.
Following Cardoso et al. (2010), assumptions of independence and dominance of the double-hurdle model entered multiplicatively into the log-likelihood function. This allows the two parts of the DH model to be estimated separately: the participation process by a probit regression model while the second hurdle was estimated with the aid of fractional logit QML estimation approach on the sub-sample of positive observations of HCI with the Inverse Mills Ratio used as a regressor in the estimation for correcting selection bias.
The Household Commercialization Index (HCI) was useful in the analysis of the level of indigenous crop output marketed by the smallholder farmers. This is a tool that is used to determine the specific level of commercialization that each household contributes to the market. The most frequently used method of measuring agricultural commercialization in the literature is the proportion of the value of crop sold concerning the value of crop harvested (Chukwukere et al., 2012; Ochieng et al., 2016; Nwafor and van der Westhuizen, 2020). The index can be expressed as follows:
The index measures the ratio of the gross value of indigenous crop sales by household i in year j to the gross value of all indigenous crops produced by the same household i in the same year j expressed as a percentage. The index measures the extent to which household indigenous crop production is oriented toward the market. Thus, a value of zero would be an indication of a subsistence-oriented smallholder farmer whereas the closer the index is to 100, the higher the degree that the smallholder farmer is market-orientated (Hailua et al., 2015). The advantage of this approach is that commercialization is treated as a continuum thereby avoiding a crude distinction between “commercialized” and “non-commercialized” households.
Demographic and Socioeconomic Characteristics of the Household Involved in the Production and Marketing of Indigenous Crops
This sub-section of this study presents the demographic and socioeconomic features of the respondents, from a sample of 1,520 rural households. The study found these features to be of great assistance in the matter of distinctly portraying the respondents' diverse backgrounds and the impact diversity has had on the descriptive, statistical, and econometric results. The results revealed that out of 1,520 smallholder farmers that participated in the study, about 209 were involved in the production of the indigenous crops. Out of 209 smallholder indigenous farmers, about 41 were involved in the commercialization of the identified indigenous crops (Table 1). As presented in Table 3, the mostly produced indigenous crop was pumpkin (36%), followed by leafy vegetables (16%). The least (0.5%) produced indigenous crop was sorghum. This could be as a result of sorghum not being popularly consumed as food but mainly used as an ingredient in the production of traditional beer.
Table 4 showed the different indigenous crops sold by smallholder farmers. As represented in Table 4, the results showed that leafy vegetables were the most sold indigenous crops compared to the other crops. It was also revealed that indigenous crops such as millet, eggplant and cowpea were not commercialized. A possible explanation for this could be the fact that the crops were not enough for both consumption and selling. While pumpkin was found to be the most grown indigenous crop, the extent of its commercialization was limited, suggesting the need to encourage smallholder indigenous crop farmers to participate in the market.
The result of the t-test as shown in Table 5, revealed that the smallholder indigenous crop farmers' mean age and education were not significantly different among the market participants and non-participants. As represented, the mean age for smallholder farmers that participated in the market was 47.33 years, whereas the ones that did not participate in the market had a mean age of 44.23 years. Furthermore, the mean number of years of education for market participants was 9.16 as compared to the non-participants with an average of 5.44 years of formal education. This implies that the literate farmers could at least read, write and hold conversations about commercial farming. Also, they had greater opportunities in terms of taking their farming ventures into other levels of success, including having more international market access than the illiterate ones. The mean output of indigenous crops together with market participation had a significant difference (P < 0.05). From the results, at least 800.69 kg was the average yield that was harvested specifically for market participation, whereas only 200.17 kg represented those that did not participate in the market. The higher market yield for participant farmers meant that they had the privilege of consuming and selling at the same time. Amongst all the other tables of this study with demographic characteristics of smallholder farmers in Limpopo and Mpumalanga, South Africa, Tables 5, 6 present various means and standard deviations.
Table 5. Demographic characteristics of smallholder farmers that were involved in the production of indigenous crops in Limpopo and Mpumalanga provinces, South Africa.
Table 6. Demographic characteristics of indigenous crops' farmers in Limpopo and Mpumalanga provinces, South Africa.
The Distributions of Commercialization Level of Indigenous Crops
According to Strasberg et al. (1999) the household commercialization index (HCI) measures the extent to which indigenous vegetable production gravitates toward the market. The index indicates variations in the level of indigenous vegetable commercialization across the study area. Households were divided into three categories of equal size according to their HCI. As shown in Figure 1, different levels of indigenous crops commercialization among the farmers in the study area are revealed. The results of Figure 1 show that half of the farmers (51%) are still operating almost at the subsistence level. In the same vein, a large number (31%) of the farmers are still at low-medium levels while the rest (18%) are high-level market participants.
While estimating the double-hurdle with the Quasi-maximum likelihood fractional response model, the covariates included in the models were tested for multi-collinearity using the variance inflation factor (VIF). An average VIF of 2.17 shows that the multi-collinearity problem is not an issue among the covariates used for the study. The probit model (first hurdle) was used to estimate factors influencing the commercialization of indigenous crops among the respondents in the study area. The results are shown in Table 7, where the first-hurdle model of the double-model revealed that only the salary of the household and agricultural information was significant at the 1% level. Surprisingly, education had not only no significant impact to the smallholder farmers commercializing their produce, but also it had an unexpected negative coefficient.
From the Probit results, the gender of the household head had a positive effect, at a 5% level of significance, on the determinants of the commercialization of indigenous crops. The results showed that off-farm income had a positive impact, and statistically significant at the level of 5%. Furthermore, the results revealed that if a household member was HIV positive that had a negative effect on the market participation of the farmer with a 10% level of significance. The results show that a household with a member infected with HIV is likely not to participate in the market.
The Determinants of the Commercialization Level of Indigenous Vegetable Production: A Quasi-Maximum Likelihood Estimates Fractional Logit Model
The results on factors influencing the level of commercialization among indigenous vegetable farmers are as presented in Table 8. The variable household size, gender, marital status, access to information, access to extension, and disability grant were statistically significant and discussed. To correct for selectivity bias, an inverse mill ratio (IMR) was used as a covariate in the model (second hurdle). The IMR was not statistically significant which shows that bias due to selection was not a problem. Hence, using a double hurdle model for estimating determinants and level of commercialization is justified. From the second-hurdle equation it was revealed that the household size, gender of the household head, marital status, access to extension as well as the disability grant were all statistically significant.
Table 8. Determinants of the extent of commercialization of indigenous crops (Quasi-maximum likelihood estimates fractional logit model).
The results show that the household size had a positive influence on the level of participation of smallholder farmers with statistical significance of level 10%. Contrary to the first-hurdle model, the coefficient of gender of the household head was negative and statistical significant in influencing market participation. The results also revealed that both marital status and access to information were statistically significant at level 5%, even though their coefficients were opposite (marital status had a positive coefficient whereas access to information had a negative coefficient). It was also revealed that the number of indigenous crops sold in the market was positively influenced by the access to extension services, with a 1% of significance level. This study showed that the disability grant had a negative impact on the level of participation to the market by smallholder farmers with the significance level of 10%.
The objective of the study was to determine the factors influencing the extent of commercialization of indigenous crops among smallholder farmers.
The Factors That Influence the Smallholder Farmers' Decision to Participate in the Market
The positive coefficient sign in the gender of the household head implies that gender plays a huge role in the commercialization of indigenous crops. It also provides a clear implication that when men and women work together, they achieve a positive outcome. Sebatta et al. (2014) asserted that men hold the responsibility of deciding whether to participate in the market or not and how much. On the other hand, women become more active in the marketing of arable crops. However, the results of this study differ from what Hill and Vigneri (2014) found in their study as they reported that men practice cash crops farming for the sake of taking care of their families, whereas women produce crops mainly for consumption purposes. This implies that they do not work together in the production of indigenous crops.
Gaining access to information is a key factor that mostly influences farmers' decisions to participate in the marketing of a product. Farmers with access to information can make informed decisions concerning production, crops to grow, and marketing-related information (Dlamini-Mazibuko et al., 2019). Access to information offers farmers the opportunity to make proper decisions relative to favorable product prices and transaction costs (Key et al., 2000). Having access to market information plays a huge role in the decision-making process of the farmers, about how much to sell and on which market. Farmers require such information to make the appropriate decision on the quantity of produce to market and the price to charge and also to have an idea of the market competition. As revealed from the result of this study, access to marketing information has a positive and statistically significant influence on commercialization among indigenous vegetable farmers. The result of this study aligns with the study of Dlamini-Mazibuko et al. (2019) who, in their study on factors affecting the choice of marketing outlet selection strategies by smallholder farmers in Swaziland, found a positive influence of market information, on the decision to participate in the market.
The positive coefficient implies that the involvement of indigenous crop farmers in off-farm income opportunities increases their likelihood of commercializing indigenous crops. This implies that regardless of households' other means of making income, they still manage to produce crops and participate in the market. Usually, households that have other means of making income are business-minded and can multitask. Other than farming, females always get involved in other streams of generating income, especially in female-headed households. They partake in casual jobs to take care of their families' needs. The results of this study corroborate that of Mthembu (2013) who from their findings showed that women were not only involved in the production and marketing of indigenous crops, but also worked as road maintainers, with others sewing and making grass mats.
The negative coefficient result indicates that a household with a member infected with HIV is likely not to participate in the market. This could be attributed to the fact that farmers tend to spend more time taking care of the sick and less time trying to make produce. From the study conducted by Khapayi and Celliers (2016), having a sick member could reduce labor which negatively impacts the decision to participate in the market because smallholder production depends highly on family labor in the production of crops. This result is consistent with Adenegan and Adewusi (2007) who concluded that if the number of HIV-infected households increases in the rural areas then their survival strategies together with food security get threatened as well.
The Determinants of the Level of Market Participation of Smallholder Farmers
The coefficient of access to extension had a statistically positive influence on the household level of commercialization. This study aligns with the study of Ojo and Baiyegunhi (2020) who found a positive relationship between access to extension service and the farmers' choice of the adoption of a climate change adaptation strategy. Extension services improve the understanding of farmers, which leads to higher production, a higher probability of participating in the market, and the commercialization of indigenous crops. The results of this study comply with the study of Martey et al. (2012) who indicate that the extent of commercialization is determined by farmers' access to extension service. Therefore, the importance of providing timely access to extension services would significantly contribute to how farmers make their decisions when planning to commercialize the production and marketing of indigenous crops.
The positive coefficient illustrates that as the number of household members increases, so does the quantity sold in the market. These results are in contrast with what Kyaw et al. (2018) reported. In their findings, they discovered that the size of the household had a negative impact and it was statistically significant. It was then concluded that large households are associated with fewer agricultural products to sell in the market due to prioritizing the consumption needs of the household. The findings were substantiated by Siziba et al. (2011) who posited that the larger the number of households in the family the lesser the chances of them marketing the quantity that is beyond their consumption satisfaction.
The coefficient of gender of household head was negatively signed and statistically significant. It was no surprise that the results came out negative, and this is mainly because female-headed households are more likely to be involved in the market of indigenous crops as compared to the male counterparts who mostly involved in the harvesting and marketing of cash crops. The result is in tandem with other studies conducted by Shackleton and Shackleton (2006) and Avocèvou-Ayisso et al. (2009) in South Africa and Nigeria, respectively. This study found the gender of the household head to be a significant determinant in marketing of indigenous crops. In the same vein, the findings of Sinyolo et al. (2017) revealed that female-headed households sold more quantities of maize than male-headed households. However, the results of this study were in variance with those of the past numerous studies (Boughton et al., 2007; Hlongwane et al., 2014; Sigei et al., 2014) who posited that female-headed households not only lack extension services but also suffer from limited information access on trends and the inability to secure greater contracts that could help provide them with better markets for their crops.
Contrary to the first hurdle, access to market information indicated a negative impact on the volume of the indigenous crops to be sold in the market. The result shows that the more the indigenous crops farmers has access to the market information, the volume offered for sale reduces. This is unexpected from the economic point of view. However, the plausible reason could be attributed to inadequate or unqualified staff members and poor organization, which could limit the efficient dissemination of market information (De et al., 2005; Ojo et al., 2019; Bello et al., 2020). As a result, market information might not be disseminated as efficiently as expected. This could be the fact that most indigenous crop farmers reside in remote areas with a lack of good quality infrastructure, skills in agricultural activities, and inadequate storage facilities and transport (Minot and Sawyer, 2016). This not only impedes their opportunity for competing in the international markets but also deprives them of the opportunities of earning a living through the commercialization of indigenous crops. Also, this infers that being unable to sell their produce, smallholder farmers could end up not partaking in the agricultural sector at all.
The positive relationship between the access to extension services and farmer's commercialization of indigenous crops implies that having access to extension services provides the smallholder farmers with the privilege of being aware of market availability. It also comes in handy in enhancing their knowledge of production by making them aware of information on improved varieties. These results manifest the importance of the urgency of implementing not only improved technology but also support services in the promotion of market sales. Apind et al. (2015) found similar positive results to this study specifying that the extension services had a positive coefficient and significantly influenced the volume of rice that the smallholder farmers sold in the market. Alemu et al. (2012) added that the access to extension services in Ethiopia increased the probability of smallholder farmers opting for the contract market rather than settling for the spot market.
The negative coefficient on disability grants implies that the rise in the income of households that receive the disability grant may entrench an entitlement and culture of dependency among them. This could result in them being lazy or even not growing crops, let alone engaging in income-generating ventures. Similar findings were also reported by Aliber and Hall (2012) and Tirivayi et al. (2016). However, not participating in the market could also be due to the physical condition of the smallholder farmer.
Conclusion and Recommendations
The participation of smallholder farmers in marketing of produce can play a critical role in meeting their goals such as food and nutrition security, poverty alleviation and sustainable agriculture. This study found that the market participation and sales ratio of smallholder indigenous crop farmers are constrained by numerous factors, such as socioeconomic, market and institutional factors. The commercialization of the indigenous crop for smallholder farmers in the market was affected by gender, educational level, off-farm income, agricultural information, and a member being infected by HIV. The household size, gender of household head, access to market information, extension services and disability grant were found to highly influence the extent of commercialization among the smallholder indigenous vegetable farmers.
To fully realize the optimum contribution of indigenous crops to household food and nutrition security, support from the stakeholders must be geared toward the smallholder indigenous farmers through the provision of farm training for an effective and efficient grasp of agricultural and marketing information. To improve smallholder farmers' access to markets, government also needs to ensure that their support for the production of indigenous crops is timely and well-targeted in order to upscale its production for consumption and commercialization. Where possible, government and other stakeholders need to channel their support through organized cooperatives that exist within the smallholder farmers. Much attention and support need to be given to women's involvement in market participation, and they also need to be empowered by the government and other interested stakeholders to participate fully in the decision making relating to the price of their produce and where to sell it. More workshops especially for young people and women need to be conducted in rural areas to raise awareness on the nutritional importance of indigenous crops and the need to include these indigenous crops into South Africa's dietary guidelines.
Data Availability Statement
The data analyzed in this study is subject to the following licenses/restrictions: This dataset belongs to the South African Vulnerability Assessment Committee (SAVAC), hosted by the Department of Agriculture, Land Reform and Rural Development (DALRRD). If you want it you apply from SAVAC. Requests to access these datasets should be directed to the website for DALRRD, www.dalrrd.gov.za.
All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.
This research was funded in whole, or in part, by the Sustainable and Healthy Food Systems (SHEFS) program supported by the Wellcome Trust's Our Planet, Our Health program (Grant Number: 205200/Z/16/Z) and ZN, MN, and SH are supported by this grant. The National Research Foundation (Grant Number: MND200705540811).
Conflict of Interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
The South African Vulnerability Assessment Committee (SAVAC), led by the Secretariat hosted at the Department of Agriculture, Land Reform and Rural Development is acknowledged for making data available for use by the authors.
1. ^The outcome variable for the second hurdle, level of commercialization, is the HCI index from the indigenous farmers in the study area.
Achandi, E. L., and Mujawamariya, G. (2016). Market participation by smallholder rice farmers in Tanzania: a double hurdle analysis. Stud. Agric. Econ. 118, 112–115. doi: 10.7896/j.1528
Adenegan, K. O., and Adewusi, O. A. (2007). Determinants of food security status of rural households living with HIV/AIDS in Southwestern Nigeria. Afr. J. Biomed. Res 10, 9–18. doi: 10.4314/ajbr.v10i1.48917
Akinnifesi, F. K., Ajayi, O. C., Sileshi, G., Kadzere, I., and Akinnifesi, A. I. (2007). Domesticating and commercializing indigenous fruit and nut tree crops for food security and income generation in sub-saharan Africa.
Akinola, R., Pereira, L. M., Mabhaudhi, T., de Bruin, F. M., and Rusch, L. (2020). A review of indigenous food crops in Africa and the implications for more sustainable and healthy food systems. Sustainability. 12:3493. doi: 10.3390/su12083493
Alemu, A. E., Mathijs, E., Maertens, M., Deckers, J., and Bauer, H. (2012). Vertical coordination in the local food chains: evidence from farmers'in ethiopia. Int. J. Econ. Finan. Stud. 4, 11–20.
Ali, E. B., Agyekum, E. B., and Adadi, P. (2021). Agriculture for sustainable development: A SWOT-AHP assessment of ghana's planting for food and jobs initiative. Sustainability. 13:628. doi: 10.3390/su13020628
Aliber, M., and Hall, R. (2012). Support for smallholder farmers in South Africa: Challenges of scale and strategy. Dev. South. Afr. 29, 548–562. doi: 10.1080/0376835X.2012.715441
Apind, B. O., Lagat, J. K., Bett, H. K., and Kirui, J. K. (2015). Determinants of small-holder farmers extent of market participation; case of rice marketing in ahero irrigation scheme, Kenya. J. Econ. Sustain. Develop. 6, 154–160. doi: 10.22004/AG.ECON.265572
Avocèvou-Ayisso, C., Sinsin, B., Adégbidi, A., Dossou, G., and Van Damme, P. (2009). Sustainable use of non-timber forest products: Impact of fruit harvesting on Pentadesma butyracea regeneration and financial analysis of its products trade in Benin. Forest Ecol. Manage. 257, 1930–1938. doi: 10.1016/j.foreco.2009.01.043
Bello, L. O., Baiyegunhi, L. J., and Danso-Abbeam, G. (2020). Productivity impact of improved rice varieties' adoption: case of smallholder rice farmers in Nigeria. Econ Innov New Technol. 30, 750–766. doi: 10.1080/10438599.2020.1776488
Boughton, D., Mather, D., Barrett, C. B., Benfica, R. S., Abdula, D., Tschirley, D., et al. (2007). Market participation by rural households in a low-income country: an asset based approach applied to Mozambique. Faith Econ. 50, 64–101.
Cameron, A. C., and Trivedi, P. K. (2005). Micro-Econometrics: Methods and Applications. Cambridge University Press. doi: 10.1017/CBO9780511811241
Cardoso, A. R., Fontainha, E., and Monfardini, C. (2010). Children's and parents' time use: empirical evidence on investment in human capital in France, Germany and Italy. Rev. Econ. Household. 8, 479–504. doi: 10.1007/s11150-010-9090-5
Chen, L., Guan, X., Zhuo, J., Han, H., Gasper, M., Doan, B., et al. (2020). Application of double hurdle model on effects of demographics for tea consumption in China. J. Food Quality. 2020:9862390. doi: 10.1155/2020/9862390
Christopher, A. J. (2017). Statistics as news: South African newspapers and the release of Community Survey 2016. Afr. J. Stud. 38, 85–103. doi: 10.1080/23743670.2017.1288646
Chukwukere, A. O., Jamalludin, S., and Nwosu, A. C. (2012). Farm-level determinants of agricultural commercialization. Int. J. Agric. Forest. 2, 1–5. doi: 10.5923/j.ijaf.20120202.01
De, N. N., Uchiyama, T., and Ohara, K. (2005). Vietnam agricultural extension: Its roles, problems and opportunities. Bull. Faculty Bioresour.-Mie Univ. 32, 79–94.
Dlamini-Mazibuko, B. P., Ferrer, S., and Ortmann, G. (2019). Factors affecting the choice of marketing outlet selection strategies by smallholder farmers in Swaziland. Afr. J. Sci. Technol. Innov. Develop. 11, 569–577. doi: 10.1080/20421338.2018.1554323
Donkor, E., Onakuse, S., Bogue, J., and de los Ríos Carmenado, I. (2018). Determinants of farmer participation in direct marketing channels: a case study for cassava in the Oyo State of Nigeria. Span. J. Agric. Res. 16:3. doi: 10.5424/sjar/2018162-12076
Gautam, Y., and Andersen, P. (2016). Rural livelihood diversification and household well-being: Insights from Humla, Nepal. J. Rural Stud. 44, 239–249. doi: 10.1016/j.jrurstud.2016.02.001
Gitz, V., Meybeck, A., Lipper, L., Young, C. D., and Braatz, S. (2017). Climate change and food security: risks and responses. Food and Agriculture Organization of the United Nations (FAO) Report. http://www.fao.org/3i5188e/i5188e.pdf (accessed March 11, 2021).
Hailua, G., Manjureb, K., and Aymutc, K. M. (2015). Crop commercialization and smallholder farmerslivelihood in Tigray region, Ethiopia. J. Dev. Agric. Econ. 7: 314–322. doi: 10.5897/JDAE2015.0649
Heckman, J. J. (1976). The common structure of statistical models of truncation, sample selection and limited dependent variables and a simple estimator for such models. In: Annals of economic and social measurement. NBER. Vol. 5, p. 475–492.
Hill, R. V., and Vigneri, M. (2014). Mainstreaming gender sensitivity in cash crop market supply chains. In: Gender in Agriculture. Springer. p. 315–341. doi: 10.1007/978-94-017-8616-4_13
Hlatshwayo, S. I., Ngidi, M., Ojo, T., Modi, A. T., Mabhaudhi, T., and Slotow, R. (2021). A typology of the level of market participation among smallholder farmers in South Africa: limpopo and mpumalanga provinces. Sustainability. 13, 7699. doi: 10.3390/su13147699
Hlongwane, J. J., Ledwaba, L. J., and Belete, A. (2014). Analyzing the factors affecting the market participation of maize farmers: a case study of small-scale farmers in greater Giyani Local Municipality of the Mopani District, Limpopo Province. Afri. J. Agric. Res.. 9, 895–899. doi: 10.5897/AJAR12.1896
Ingabire, C., Mshenga, M. P., Langat, K., Bigler, C., Musoni, A., Butare, L., et al. (2017). Towards commercial agriculture in Rwanda: understanding the determinants of market participation among smallholder bean farmers. Afri. J. Food Agric. Nutr. Develop. 17, 12492–12508. doi: 10.18697/ajfand.80.16825
Karaan, M., Ham, C., Aithal, A., Franzel, S., Moombe, K., Akinnifesi, F., et al. (2006). Baseline marketing surveys and supply chain studies for indigenous fruit markets in Tanzania. Zimbabwe and Zambia.
Key, N., Sadoulet, E., and Janvry, A. D. (2000). Transactions costs and agricultural household supply response. Am. J. Agric. Econ. 82, 245–259. doi: 10.1111/0002-9092.00022
Khapayi, M., and Celliers, P. R. (2016). Factors limiting and preventing emerging farmers to progress to commercial agricultural farming in the King William's Town area of the Eastern Cape Province, South Africa. South African J. Agric. Exten. 44, 25–41. doi: 10.17159/2413-3221/2016/v44n1a374
Komarek, A. (2010). The determinants of banana market commercialisation in Western Uganda. Afri. J. Agric. Res. 5, 775–784. doi: 10.5897/AJAR2021.15494
Kyaw, N. N., Ahn, S., and Lee, S. H. (2018). Analysis of the factors influencing market participation among smallholder rice farmers in magway region, central dry zone of Myanmar. Sustainability. 10:4441. doi: 10.3390/su10124441
Lehohla, P. (2016). Community Survey 2016 Agricultural Households. Pretoria: Statssa. Available Online at: https://www.statssa.gov.za/publications/03-01-05/Presentation_CS2016_Agricultural_Households.pdf
Lubungu, M., Chapoto, A., and Tembo, G. (2012). Smallholder farmers participation in livestock markets: the case of zambian Farmers. p. 66.
Mabhaudhi, T., Chimonyo, V. G., Chibarabada, T. P., and Modi, A. T. (2017). Developing a roadmap for improving neglected and underutilized crops: a case study of South Africa. Front. Plant Sci. 8:2143. doi: 10.3389/fpls.2017.02143
Mahlangu, S. A. (2014). Production and commercialisation potential of indigenous leafy vegetables: Case study of Capricorn District in the Limpopo Province, South Africa (Unpublished Doctoral Thesis, University of Limpopo). Available Online at: http://hdl.handle.net/10386/1332
Martey, E., Al-Hassan, R. M., and Kuwornu, J. K. (2012). Commercialization of smallholder agriculture in Ghana: a Tobit regression analysis. Afri. J. Agric. Res. 7, 2131–2141. doi: 10.5897/AJAR11.1743
Mather, D., Boughton, D., and Jayne, T. S. (2013). Explaining smallholder maize marketing in southern and eastern Africa: the roles of market access, technology and household resource endowments. Food Policy. 43, 248–266. doi: 10.1016/j.foodpol.2013.09.008
Meemken, E. M., and Bellemare, M. F. (2020). Smallholder farmers and contract farming in developing countries. Proc. Nat. Acad. Sci. 117, 259–264. doi: 10.1073/pnas.1909501116
Minot, N., and Sawyer, B. (2016). Contract farming in developing countries: Theory, practice, and policy implications. Innovation for inclusive value chain development: successes and challenges. Washington DC (USA): IFPRI. p. 127–158.
Mthembu, N. N. (2013). Exploring characteristics of farming systems in former labour tenant communities: the case of Ncunjane and Nkaseni in Msinga. [dissertation/master's thesis]. [Western Cape]: University of Chicago
Nwafor, C. U., and van der Westhuizen, C. (2020). Prospects for commercialization among smallholder farmers in South Africa: a case study. J. Rural Soc. Sci. 35:2. Available online at: https://egrove.olemiss.edu/jrss
Ochieng, J., Knerr, B., Owuor, G., and Ouma, E. (2016). Commercialisation of food crops and farm productivity: evidence from smallholders in Central Africa. Agrekon. 55, 458–482. doi: 10.1080/03031853.2016.1243062
Ojo, T., and Baiyegunhi, L. (2020). Determinants of climate change adaptation strategies and its impact on the net farm income of rice farmers in south-west Nigeria. Land Use Policy. 95:103946. doi: 10.1016/j.landusepol.2019.04.007
Ojo, T., Baiyegunhi, L., and Salami, A. (2019). Impact of credit demand on the productivity of rice farmers in South West Nigeria. J. Econ. Behav. Stud. 11, 166–180. doi: 10.22610/jebs.v11i1(J).2757
Papke, L. E., and Wooldridge, J. M. (1996). Econometric methods for fractional response variables with an application to 401 (k) plan participation rates. J. Appl. Econom. 11, 619–632. Available Online at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=225108
Pawlak, K., and Kołodziejczak, M. (2020). The role of agriculture in ensuring food security in developing countries: considerations in the context of the problem of sustainable food production. Sustainability. 12:5488. doi: 10.3390/su12135488
Rapsomanikis, G. (2015). The economic lives of smallholder farmers: An analysis based on household data from nine countries. Food and Agriculture Organization of the United Nations, Rome. Available online at: http://www.fao.org/3/i5251e/i5251e.pdf (accessed May 26 2021).
Reyes, B., Donovan, C., Bernsten, R. H., and Maredia, M. K. (2012). Market participation and sale of potatoes by smallholder farmers in the central highlands of Angola: A Double Hurdle approach. (No. 1007-2016-79774).
Sebatta, C., Mugisha, J., Katungi, E., Kashaaru, A., and Kyomugisha, H. (2014). Smallholder farmers' decision and level of participation in the potato market in Uganda. Modern Econ. 5, 12. doi: 10.4236/me.2014.58082
Shackleton, C. M., and Shackleton, S. E. (2006). Household wealth status and natural resource use in the Kat River valley, South Africa. Ecol Econ. 57, 306–317. doi: 10.1016/j.ecolecon.2005.04.011
Shackleton, C. M., Shackleton, S. E., and Cousins, B. (2001). The role of land-based strategies in rural livelihoods: the contribution of arable production, animal husbandry and natural resource harvesting in communal areas in South Africa. Develop. Southern Afr. 18, 581–604. doi: 10.1080/03768350120097441
Sigei, G., Bett, H., and Kibet, L. (2014). Determinants of market participation among small-scale pineapple farmers in Kericho County, Kenya. [dissertation/master's thesis]. [Egerton]: Egerton University. doi: 10.5296/ijrd.v2i2.6237
Sinyolo, S., Mudhara, M., and Wale, E. (2017). The impact of social grant dependency on smallholder maize producers' market participation in South Africa: application of the double-hurdle model. South Afri. J. Econ. Manage. Sci. 20, 1–10. doi: 10.4102/sajems.v20i1.1474
Siziba, S., Nyikahadzoi, K., Diagne, A., Fatunbi, A. O., and Adekunle, A. A. (2011). Determinants of cereal market participation by sub-Saharan Africa smallholder farmer. J. Agric. Environ. Stud. 2, 180–193.
Statistics South Africa (2019). General Household Survey. Statistical Release P0318. Statistics South Africa: Pretoria. Available online at: https://www.statssa.gov.za/publications/P0318/P03182019.pdf
Strasberg, P. J., Jayne, T. S., Yamano, T., Nyoro, J. K., Karanja, D. D., and Strauss, J. (1999). Effects of agricultural commercialization on food crop input use and productivity in Kenya (No. 1096-2016-88433). [dissertation]. [East Lansing]: Michigan State University.
Tafesse, A., Goshu, D., Gelaw, F., and Ademe, A. (2020). Commercialization of moringa: evidence from southern ethiopia. Cogent Econ. Finance. 8:1783909. doi: 10.1080/23322039.2020.1783909
Tirivayi, N., Knowles, M., and Davis, B. (2016). The interaction between social protection and agriculture: a review of evidence. Global Food Security. 10, 52–62. doi: 10.1016/j.gfs.2016.08.004
Von Loeper, W., Musango, J., Brent, A., and Drimie, S. (2016). Analysing challenges facing smallholder farmers a conservation agriculture in South Africa: a system dynamics approach. South Afr. J. Econ. Manage. Sci. 19, 747–773. doi: 10.4102/sajems.v19i5.1588
Wooldridge, J. (2012). Panel Data Models With Heterogeneity and Endogeneity. Cham: Institute for Fiscal Studies. Available Online at: https://ifs.org.uk/docs/wooldridge%20session%204.pdf
Keywords: smallholder farmers, indigenous crops, household commercialization index, double-hurdle fractional response model, South Africa
Citation: Zondi NTB, Ngidi MSC, Ojo TO and Hlatshwayo SI (2022) Factors Influencing the Extent of the Commercialization of Indigenous Crops Among Smallholder Farmers in the Limpopo and Mpumalanga Provinces of South Africa. Front. Sustain. Food Syst. 5:777790. doi: 10.3389/fsufs.2021.777790
Received: 15 September 2021; Accepted: 16 December 2021;
Published: 25 January 2022.
Edited by:Ping Zhu, Royal Observatory of Belgium, Belgium
Reviewed by:Paul Christiaan Struik, Wageningen University and Research, Netherlands
Kikuko Shoyama, National Research Institute for Earth Science and Disaster Resilience (NIED), Japan
Copyright © 2022 Zondi, Ngidi, Ojo and Hlatshwayo. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Nonkululeko Thandeka Brightness Zondi, firstname.lastname@example.org