Coffee Production Levels among Smallholder Farmers with and without Hanns. R. Neumann Stiftung Interventions in Rungwe and Mbeya Districts

This study examined and compared coffee production levels among smallholder farmers, those involved, and those not involved with Hanns R. Neumann Stiftung (HRNS) interventions since 2006. The study sample was selected using systematic and random sampling techniques, whereby 104 out of 413 respondents were selected from two wards and five villages within the HRNS intervention zone, as well as five villages without HRNS interventions; farmers in both groups being members of Umalila Agricultural Marketing Cooperatives (AMCOS) and Kyobo, Tutafika, and Ikuti AMCOS. The production levels were then compared for two samples in Mbeya and Rungwe Districts, respectively. Questionnaires, focus group discussions, and key informant interviews were used to collect primary data, which were complemented by secondary data from documentary reviews. Descriptive statistics, including frequencies, percentages, and means, were employed to analyse socio-economic characteristics and coffee production parameters. The study findings revealed that smallholder coffee farmers’ yields increased significantly with HRNS interventions, reaching 248.66 kg/ha, compared to 115.18 kg/ha for coffee farmers outside the HRNS intervention. The findings indicate that HRNS interventions have a positive impact on smallholder coffee farmers who are beneficiaries of the HRNS program. Thus, the findings highlight the critical significance of government assistance in sustaining such programs. The study recommends for sustained Tanzanian government support for HRNS-like interventions, such as the continual provision of quality seedlings, fertilizers, and extension services to enhance coffee production. This study contributes to the theoretical understanding of agricultural interventions by comparing smallholder farmers’ coffee production with and without HRNS interventions. It demonstrates the usefulness of HRNS in increasing yields, emphasizing the significance of focused interventions in coffee production.

Introduction

Coffee, the second most traded commodity in the world, plays a significant role in balancing trade between developed and developing countries [1]. The two dominant coffee varieties, Arabica and Robusta, comprise 99% of bean production, making up 70% and 30% of the consumption, respectively, [2], [3]. Countries that grow coffee, such as Brazil, Vietnam, Colombia, Indonesia, and Ethiopia, experience a significant economic impact, as highlighted by [4]. This lucrative $19 billion sector supports the basic needs of over 125 million people, with Arabica being the favoured coffee variety in East Africa [5].

Brazil, Indonesia, Vietnam, Columbia, and Costa Rica [6] are the leading coffee-producing countries in the world, while Ethiopia, Kenya, Uganda, Tanzania, Rwanda, Malawi, and Zambia are the leading coffee-producing countries in Africa. In Tanzania, both Arabica and Robusta coffee are cultivated with a preference for Arabica, while Uganda primarily produces Robusta coffee [7]. According to Killeen and Harper [8], low coffee production has been a major concern in coffee-growing regions across Central and South America, Africa, the Middle East, and Southeast Asia. The global average production of green coffee for small producers is around 0.55 metric tons (MT) per hectare (ha), which is below the recommended 1.5 metric tons per ha [9].

Coffee production is one of the major agricultural exports in Tanzania contributing significantly to the country’s foreign exchange revenues [10]. The revenue generated from coffee exports substantially bolsters the nation’s foreign currency reserves. This, in turn, benefits various industries, stimulates economic growth, and contributes to the overall prosperity of the economy [11], [12]. Additionally, as noted by the TCB [23] the coffee industry plays a crucial role in improving the lives of smallholder farmers and neighboring communities. On average, the coffee industry employs 22 million people, including 320,000 households [13]. Thus, the coffee industry in Tanzania not only significantly contributes to foreign exchange revenues and fostering economic growth but also plays a vital role in uplifting the lives of numerous smallholder farmers and communities.

Arabica coffee-producing regions in Tanzania. include Kilimanjaro, Arusha, Mbeya, Songwe, Ruvuma, Morogoro, Kigoma and Mara [14]. These areas have high elevation, reasonable rainfall patterns, optimal temperature, and fertile soils, which provide an ideal climate for the cultivation of Arabica coffee. The favorable climate contributes to the production of coffee with a unique flavours and is highly preferred in the world markets. While the aforementioned areas are famous for the production of Arabica coffee in Tanzania, Kagera region is famous for the production of Robusta coffee [15]. On average, smallholder coffee growers contribute 90% of the coffee produced in Tanzania [16].

Despite having a diverse Arabica and Robusta-rich coffee-producing regions, for the last six decades, Tanzania has been encountering notable fluctuations in her coffee production, a phenomenon attributed to many challenges as reported in previous literature. These challenges range from poor management practices employed by coffee farmers to the inadequacy of extension services provided to farmers [17]. Additionally, price fluctuations in the coffee market have also caused significant obstacles, affecting the economic stability of coffee production in the country [18]. The prevalence of persistent coffee diseases, contributing to the fluctuations of coffee yields, and impacting the overall health of coffee crops have been the major concern.

Additionally, the aging of coffee trees, affecting production presents another substantial challenge [12]. For example, the current average production of green coffee is 150–200 kg/ha, which is among the lowest compared to the world’s recommended production, which is 1.5 metric tons per ha. In Mbeya, the average production is 470 kg/ha, while in Rungwe, it is 237 kg/ha among smallholder coffee farmers [19], [20]. Therefore, these challenges necessitate the implementation of comprehensive strategies aimed at enhancing the resilience and sustainability of coffee production over a long time.

In addressing the challenges related to low coffee production, governments and non-government organizations have made various efforts [21], including providing extension services to coffee farmers, increasing coffee research, and advancing technology in cultivation, processing, and marketing [22]. Extension services play a crucial role in disseminating knowledge, best practices, and innovative techniques directly to the farming communities; coffee research boosts farmers’ knowledge of coffee plant biology, disease resistance, and climate adaptation. Thus, guidance on optimal cultivation methods, pest and disease management, and efficient resource utilization empower coffee farmers with the tools necessary to enhance their productivity [23]. In addition, advancements in technology form a critical component of the efforts to revitalize the coffee sector [24].

Hanns R. Neumann Stiftung (HRNS) is a German non-profit organization founded in 2005 with the mission of enhancing the living conditions and long-term economic sustainability of small-scale coffee farmers. This organization operates globally, spanning 18 countries, and is committed to achieving its goals through community-based initiatives, as highlighted by [25]. Hanns R. Neumann Stiftung (HRNS) began its operations in Tanzania in 2006 by initiating pilot projects in Southern Tanzania and expanded to Northern Tanzania in 2010. Committed to enhancing sustainability in coffee smallholder farmers, HRNS Interventions employs four key components: empowering farmers through knowledge transfer, nurturing farm management and gender equality, establishing efficient and inclusive Farmer Organizations (FOs), and promoting climate resilience [26]. Using the Farmer Field School (FFS) approach, HRNS Interventions addresses farming, economic, and social issues, with a strong focus on gender equality.

HRNS Interventions extension workers work in coffee zones involved in training farmers and government extension workers on good agricultural practices. These practices include weeding, mulching, pruning, controlling pests, preparing and using compost as an organic fertilizer, addressing climate change, and conserving soil [27]. To ensure a sustainable training process, HRNS Interventions has implemented a system of lead contact farmers who play a crucial role in assisting others in accessing extension services. Furthermore, HRNS Interventions have conducted specialized training on the propagation and multiplication of new coffee seedlings that are resistant to diseases, are drought resilient, and have high yielding capacity. The organization significantly emphasises training farmers on effective record-keeping practices related to coffee production. The organization also actively contributes to enhancing smallholder coffee farmers’ resources by providing them with improved seedlings. This integrated approach addresses training needs as well as focuses on the development and distribution of resilient and high-yielding coffee varieties to enhance the overall sustainability of coffee production. By fostering community-based approaches, HRNS Interventions aims to create a positive impact on the coffee production and socio-economic well-being of coffee farmers and ultimately contribute to the overall resilience and prosperity of coffee-producing communities worldwide. Through its multidimensional efforts, HRNS interventions exemplify a commitment to sustainable development and social responsibility within the global coffee industry.

Despite these efforts, the impact of non-government interventions, including HRNS Interventions on coffee production, has fuelled heated debates among scholars with two contesting groups, the proponents of and the opponents of HRNS Interventions on coffee production [9], [14], [28] The supporters argue that non-government interventions contribute significantly to increased productivity and improved coffee quality [29]. The initiatives such as training programs, access to modern farming techniques, and the provision of quality inputs are believed to elevate the overall production standards [30]. On the other hand, the opponents contend that there has been an insufficient increase in coffee production attributable to interventions by non-governmental organizations. They ascertain that contextual factors such as market dynamics, climate variability, limited technology adoption, social and labour challenges and training complexity limit the outcome of interventions implemented by non-governmental organizations [16].

This ongoing debate underscores the complexity of interventions in the coffee sector and emphasizes the importance of evidence-based research to generate knowledge for informed decision-making and policy formulation. Therefore, the current study was conducted to determine the contribution of HRNS Interventions in coffee production among smallholder coffee farmers. To understand the contribution of the intervention, the study involved smallholder coffee farmers both with and without HRNS intervention program. The inclusion in the study of farmers with and those without HRNS Interventions who are members of Umalila Agricultural Marketing Cooperatives (AMCOS) and Kyobo, Tutafika, Ikuti (AMCOS) in Mbeya and Rungwe, respectively, ensures a holistic understanding of the varied dynamics at play within the coffee farming sub-sector.

Theoretical Framework

In comparing coffee production with and without HRNS Interventions, the Resource-Based View (RBV) theory served as a theoretical framework. The RBV theory is traditionally applied to business scenarios; it posits that external interventions act as valuable resources in enhancing agricultural productivity. This perspective suggests that unique and valuable resources, such as supportive interventions, can yield sustainable competitive advantages, manifested here as increased coffee production. By employing the RBV framework, the study delves into the distinctive resources and capabilities introduced by HRNS Interventions, shedding light on the mechanisms that contribute to observed differences in coffee production between the conditions. This theoretical approach not only facilitates the interpretation of statistical findings but also provides a comprehensive understanding of the underlying factors and resources influencing variations in agricultural outputs.

Methodology

Description of the Study Area

This study was conducted in Mbeya and Rungwe districts, as indicated in Fig. 1. The HRNS Interventions organization has been implementing its intervention in two coffee-producing districts of the Mbeya Region since 2006; thus, it was imperative to select these districts for study. Mbeya District is located between latitudes 7° and 9° S and longitudes 33° and 35° E with Iringa Region to the east, Rungwe and Ileje Districts to the south, Mbozi District to the west, and Chunya District to the northwest of Mbeya District. The average annual temperature ranges from 12 °C and 30 °C. Rungwe District Council is situated between latitudes 8° 30′ East at 9° 30′ South of the Equator and Longitudes. 33′ and 34′ east of Greenwich Meridian. The district borders Kyela District in the south, Ileje District in Songwe Region to the west, and Kyela District to the east. The climate condition of Mbeya District is a function of altitude. The mean annual rainfall ranges from 650 mm to 2700 mm. Rungwe District is mountainous, with Rainfall averages ranging from 900 mm in the lowland areas to 2700 mm in the highlands. Temperature is generally modest and ranges from 180 °C to 250 °C throughout the year. The major food crops grown in Mbeya and Rungwe Districts include Irish potatoes, pyrethrum, maize, beans, paddy, citrus, bananas, avocado, coffee, mango, groundnuts, and vegetables.

Fig. 1. Map of Mbeya and Rungwe Districts showing the location of the study area. Source: Google Map, 2023.

Research Design

The study employed a cross-sectional design, allowing data collection at a single point in time to draw conclusions. Additionally, the design allows the use of various analytical techniques, including mixed methods for data collection and analysis of the relationships between dependent and independent variables [31]. The study was conducted in Mbeya and Rungwe Districts of Tanzania’s Mbeya Region. These districts were selected because they are the main coffee-producing areas in the region and have received HRNS Interventions. Furthermore, the study respondents constituted members of Umalila Agricultural Marketing Cooperatives (AMCOS) and Kyobo, Tutafika, Ikuti (AMCOS) in Mbeya and Rungwe, respectively, comprising both those under HRNS Interventions and those outside these interventions.

Study Population

The study population comprised smallholder coffee farmers within the designated study area, encompassing both those who benefited from HRNS Interventions and those who did not. This inclusive approach aimed to capture a comprehensive understanding of the impact of HRNS Interventions on coffee production.

Sampling Procedure and Sample Size

The sampling framework included farmers within HRNS Intervention project zones, ensuring a purposive selection that accounted for the distinct characteristics of the intervention areas. This study involved 104 respondents, strategically sampled from a larger pool of 413 smallholder coffee farmers. Employing a combination of systematic and random sampling methods, 52 respondents were selected from HRNS Interventions beneficiaries using systematic sampling, while another 52 were randomly chosen from non-HRNS beneficiaries who were members of Umalila Agricultural Marketing Cooperatives (AMCOS) and Kyobo, Tutafika, Ikuti (AMCOS) in Mbeya and Rungwe Districts [32], respectively. Two specific wards, Isuto and Ikuti, were purposively selected from a total of 36 wards. The criteria used to select the respondents included smallholder coffee farmers either working or not working under the HRNS program. Five villages out of fourteen were selected. About ten respondents were chosen from each of the three villages, while 2 respondents came from each of the two villages, eleven respondents were selected from among the HRNS beneficiaries using systematic sampling. Five villages out of fourteen were selected. About ten respondents were chosen from each of three villages, while eleven respondents were selected from each of the two villages among the non-HRNS beneficiaries using random sampling with the aid of a table of random numbers. This sampling technique was adopted to ensure a representative and balanced sample, allowing for a comparative analysis of coffee production outcomes between HRNS Interventions beneficiaries and non HRNS Interventions beneficiaries, thereby facilitating a comprehensive evaluation of the organization’s impact within the coffee farming sub-sector. The sample size in Table I was calculated using the formula by Kothari [33] as follows:

where n is the sample size, N is the sampling frame/population size, Z is the standard value at a given confidence level, that is, 1.96 (confidence interval at 95%), p is the sample proportion (0.1), q equals to 1-p, and e is the sampling acceptable error, i.e., 0.05.

(1) $$\begin{array}{r}n=\frac{Z^2\cdot p\cdot q\cdot N}{e^2(N-1)+Z^2\cdot p\cdot q}\end{array}$$

Table I. SAmpling Matrix

District	Ward	Village	Sample for with HRNS interventions	Sample for without HRNS interventions
Mbeya	Isuto	Isuto	7	7
		Mlowo	6	6
		Idiwili	5	6
		Shisonta	3	4
		Shitete	5	3
Rungwe	Ikuti	Ikuti	7	7
		Kyobo juu	5	6
		Kyobo	4	6
		Lumbe	5	3
		Lyenje	5	4
		Total	52	52

The proportional sample size for each village was calculated by using the formula as proposed by Kothari [33], as shown in the Table I.

(2) $$\begin{array}{r}n=n/NxS\end{array}$$

Data Collection Procedures

The study collected both primary and secondary data. Primary data were collected through questionnaires, focus group discussions, and key informant interviews, while secondary data were obtained from relevant literature sources such as journals and band baseline surveys. Questionnaires was used to collect primary data from 104 respondents, including smallholder coffee farmers with or without HRNS Interventions who are members of Umalila Agricultural Marketing Cooperatives (AMCOS) and Kyobo, Tutafika, Ikuti (AMCOS) in Mbeya and Rungwe Districts respectively. A checklist was used for key informants and focus group discussions.

Focus Group Discussion and Key Informant Participants

Sixteen focus group discussions (FGDs) were conducted, each comprising eight participants, including four women and four men. Respondents were selected based on their coffee farming experience, age, and sex. Priority was given to those who had at least three years of experience in the coffee sector. Purposive sampling was used to select key informants from the coffee sector. Key informants were interviewed using predetermined questions. Key informants included the TaCRI Zone Manager, two AMCO leaders, one Coffee Inspector from Mbeya and Rungwe Districts, an experienced coffee farmer, and the Manager of the zone from the Tanzania Coffee Board.

Validity and Reliability

The questionnaire was subjected to experts to ensure its validity and reliability. These include lecturers in the Department of Agricultural Extension and community development and statisticians. The questionnaire was also pretested by a small group of smallholder coffee farmers near the study area before the actual data collection. Subsequently, adjustments were made to incorporate comments from experts to ensure the validity and reliability of the instruments to be used. Reliability plays a vital role in refining and establishing effective measurement tools, thereby enhancing the credibility of study results [34]. It indicates the degree to which research instruments consistently yield accurate results [35].

On the other hand, a test is considered reliable if repeated measurements produce the same results under consistent conditions. To ensure test-retest reliability, instruments such as questionnaires were administered to 10 respondents to assess clarity. By administering the same test or measure to the same respondents twice, consistency over time can be evaluated, thus ensuring the assessment of reliability. In this study, the same questionnaire was applied to a sample group of five respondents from Ikuti and Isuto Wards after a specific time, typically using intervals of 1–2 weeks for the test-retest method, maintaining consistency in the research approach.

Data Analysis

Quantitative data were entered into SPSS version 25. Descriptive statistics, including frequency, percentages, and means, were used to report smallholder farmers’ socio-economic characteristics and the coffee production parameters. The respondents were selected based on their involvement in the coffee cultivation. Key informants for focus group discussions (FGDs) were selected from the two farming communities using purposive sampling. The study employed multiple data collection tools, including checklists for key informants and focus group discussions.

An Independent Samples T-Test was used to assess whether there were statistically significant variations in the levels of coffee production between smallholder coffee farmers receiving and those not receiving HRNS Interventions, even though both are members of Umalila Agricultural Marketing Cooperatives (AMCOS) and Kyobo, Tutafika, Ikuti (AMCOS) in Mbeya and Rungwe Districts, respectively. Likewise, content analysis was utilized to analyse qualitative data. The analysis involved content transcription and coding to obtain themes.

Results and Discussion

Social Economic Characteristics

This section presents the percentage distribution of the respondents across various background variables, including age, sex, education, marital status, farm size, and years of farming experience, based on the respondents’ responses.

Sex of the Respondents

The findings in Table II underscore a notable gender disparity among the respondents, with approximately 87% and 83% with and without HRNS Interventions, respectively, being males and the remaining 13% and 17% females, with and without HRNS Interventions, respectively, being females. This demographic distribution suggests a traditional gender-based division of labour in the predominantly agricultural communities in Mbeya and Rungwe districts. Historically, females have been primarily associated with the cultivation of food crops such as maize and beans, often geared towards fulfilling family nutritional needs [11].

Table II. Socio-Economic Characteristics of the Smallholder Coffee Farmers

Variable	With HRNS interventions (n = 52)		Without HRNS Interventions (n = 52)
	n	%	n	%
Sex of the respondents
Male	45	87	43	83
Female	7	13	9	17
Marital status
Marriage	49	94	50	96
Divorce			1	2
Single			1	2
Widow/Widower	3	6
Education level
Primary school	52	100	51	98
Secondary school			1	2
Age of the respondents
20–50	29	56	31	60
51–70	23	44	21	40
Household size
1–4	16	31	17	32
5–8	32	61	31	60
9+	4	8	4	8
Total land size
≤2	7	13	7	13
3–10	41	79	41	79
11–18	3	6	3	6
19–25	1	2	1	2
Land size under coffee
≤2	42	81	42	81
3–5	9	17	9	17
11+	1	2	1	2
Farming years’ experience
1–5	17	33	19	37
6–10	5	10	12	23
11–15	1	2	7	13
16–20	4	7	6	12
21–25	25	48	8	15

Marital Status of the Respondents

The findings in Table II indicate the marital status of the interviewed farmers, with a substantial 94% and 96% of those with and without HRNS interventions, respectively, being married. Additionally, 2% represent single individuals, and 6% are widows/widowers among those with and without HRNS interventions, respectively. Furthermore, 2% of those without HRNS interventions are divorced; this finding indicates that the majority, comprising 9%, among those without HRNS interventions are married. This implies that coffee production attracts more married couples with different social and economic commitments. The commitments include providing food for family members, improving housing, children’s education, clothes, and access to better health care. On the other hand, this suggests that community members with varying marital statuses were involved in smallholder farmers’ coffee production, mostly because coffee was essential to their daily needs. Smallholder coffee farmers need money for a variety of economic, social, and cultural reasons. Growing coffee is one way these requirements might be met [36].

Education Level of Respondent

The study’s findings in Table II reveal a striking educational pattern among the respondents in the study area. An overwhelming 100% of farmers with HRNS intervention have primary education, while 98% of farmers without HRNS Interventions have attained only a basic level of education, predominantly at the primary level, with a mere 1% having secondary education. This educational profile suggests the prevalence of a predominantly low-skilled workforce in the agricultural sector in the studied region [37]. When considering the adoption of HRNS intervention and its potential impact on coffee production, the limited educational attainment of the farmers becomes a critical factor.

Effective implementation of HRNS intervention practices may require tailored educational programs and extension services to ensure widespread understanding and successful adoption of HRNS intervention technologies among the predominantly primary-educated farmers. Focusing on practical and accessible methods of disseminating information about sustainable coffee practices can enhance the likelihood of adoption, leading to increased productivity in coffee cultivation [21]. This finding underscores the importance of considering education level when designing and implementing interventions to ensure that the dispensed technologies are accessible and beneficial to the target farming community.

Age of the Respondent

The study’s findings in Table II reveal that among respondents, 56% and 60% of those with and without HRNS intervention, respectively, fall in the age range of 20–50. Conversely, 44% and 40% of those with and without HRNS intervention, respectively, fall in the age range of 51–70. Notably, the majority (60%) of farmers among those without HRNS interventions belong to the economically active age group of 20–50 years. This demographic composition implies that the study area highlights a substantial workforce in the prime of their economic productivity, particularly suited for engaging in agricultural activities such as coffee farming [38].

Farm Size

The findings in Table II indicate that, on average, respondents reported owning 3–10 ha of land, with 79% having HRNS interventions and 79% without HRNS Interventions. Additionally, there is an average allocation of ≤2 ha of land, 81% having with HRNS interventions and 81% without HRNS interventions for coffee production. This suggests that farmers in the study area possess additional land beyond what is utilized for coffee cultivation.

The observation by Olana Jawo et al. [39] and Wanbua et al. [40] emphasized the positive correlation between larger land holdings and increased agricultural production becomes relevant in this context. Farmers with substantial land resources are better positioned to allocate larger areas to coffee cultivation, potentially leading to higher yields. In the context of HRNS Interventions, the presence of extra land offers the opportunity to implement sustainable agricultural practices without compromising the main crop’s yield. The surplus land provides a favourable environment for the adoption of HRNS interventions technologies, allowing farmers to experiment with innovative approaches through diversifying and optimizing their agricultural strategies. Thus, ample land holdings ultimately contribute to increased coffee production in the studied region.

Farming Years’ Experience in Coffee Production

The findings in Table II highlight the diverse range of levels of experience among the surveyed farmers. Notably, 48% and 15% of farmers with and without HRNS Interventions, respectively, reported having experience of 21–25 years in coffee cultivation. Additionally, 7% and 12% of farmers with and without HRNS Interventions, respectively, reported an experience of 16–20 years, 2% and 13% reported an experience of 11–15 years, 10% and 13% reported an experience of 6–10 years, and 33% and 37% reported an experience of 1–5 years. The preponderance of farmers with a relatively high experience level of 21–25 years is 48%. The findings in Table II highlight the diverse range of experience levels among the surveyed farmers. Notably, 48% and 15% of farmers with and without HRNS Interventions, respectively, reported an experience of 21–25 years in coffee cultivation.

Additionally, seven and twelve of farmers with and without HRNS Interventions, respectively, reported an experience of 16–20 years, 2% and 13% reported an experience of 11–15 years, 10% and 13% reported an experience of 6–10 years, and 33% and 37% reported an experience of 1–5 years. The preponderance of farmers with a relatively high experience level of 21–25 years is 48%. This implies that years of farming experience help farmers develop excellent functional abilities in understanding the relationship between inputs and outputs and make wise decisions when selecting inputs.

This developed knowledge enables farmers to choose and apply inputs wisely, maximizing the effectiveness and productivity of their farming techniques [41]. The variety of knowledge, which has been accumulated over a long time, is a valuable resource for promoting sustainable agricultural management and making wise choices [42]. Consequently, the chances of farmers increasing their coffee yields are higher for those with farming experience of over an extended period. Farmers’ farming experience also has a significant contribution in enabling them to make better decisions that reduce crop disaster in terms of quantity and quality. Also, HRNS interventions can significantly improve the farming experience in coffee production [27]. The organization plays a crucial role in providing knowledge, resources, and assistance to farmers.

Coffee Production among Famers with and without HRNS Intervention

Coffee Production Trend from 2017 to 2021

The group statistics highlight a substantial difference in the average coffee production between the two groups—those with and those without HRNS interventions (Table III). With HRNS interventions, the mean of coffee production stands at 248.66 kg, with a relatively higher standard deviation of 304.35. In contrast, without HRNS Interventions, the mean production is notably lower at 115.19 kg, followed by a lower standard deviation of 98.03. This stark contrast in both mean and variability underscores the potential impact of HRNS interventions on coffee production. The larger standard deviation without intervention suggests a more variable outcome, while the higher mean with HRNS interventions indicates a substantial and consistent increase in coffee production. These findings further emphasize the effectiveness of HRNS interventions in positively influencing coffee production outcomes.

Table III. Coffee Production Trends from 2017 to 2021 are Compared in kg/ha Among Farmers with and without HRNS Interventions

Variance	n	Year	Minimum	Maximum	Mean	Standard deviation
Average production with HRNS (kg/ha)	52	2017–2021	24.28	1,618.78	248.66	304.35
Average production without HRNS (kg/ha)	52	2017–2021	10.12	404.69	115.19	98.03
kg/ha with HRNS	52	2017	3.46	230.86	35.46	43.47
kg/ha with HRNS	52	2018	3.38	225.06	34.57	42.37
kg/ha with HRNS	52	2019	3.57	238.11	36.58	44.83
kg/ha with HRNS	52	2020	6.79	452.87	69.57	85.26
kg/ha with HRNS	52	2021	7.08	471.88	72.49	88.84
kg/ha without HRNS	52	2017	1.44	57.72	16.43	13.73
kg/ha without HRNS	52	2018	1.41	56.26	16.01	13.38
kg/ha without HRNS	52	2019	1.49	59.53	16.94	14.15
kg/ha without HRNS	52	2020	2.83	113.22	32.23	26.92
kg/ha without HRNS	52	2021	2.95	117.97	33.58	28.05

T-Test Results for Coffee Production among Farmers with and without HRNS Interventions

The findings in Table IV indicate that independent samples t-test was employed to examine the differences in the average coffee production between two groups: farmers with and without HRNS interventions. Levene’s test for equality of variances revealed a significant difference (F = 6.213, p = 0.014), indicating unequal variances. Considering equal variances, the t-test indicated a significant disparity in mean coffee production between the two groups (t = 2.843, df = 102, p = 0.005), with a mean difference of 317.172 kg (95% CI = 95.857 to 538.487). When equal variances were not assumed, the significant difference persisted (t = 2.889, df = 61.850, p = 0.005), with a similar mean difference (317.172 kg) and a slightly narrower confidence interval (97.730 to 536.614). These results highlight the practical and statistical significance of HRNS interventions, affirming that coffee production is notably higher when HRNS Interventions are implemented.

Table IV. T-Test Analysis of Coffee Production

Description	Levene’stest for equality of variance		T-test for equality means
Average production (kg)	F	Sig	t	df	Sig (2-tailed)	Mean difference	Std error difference	95 confidence interval of the difference
								Lower	Upper
Equal variance assumed	6.213	0.014	2.843	102	0.005	317.172	111.552	95.73	95.73
Equal variance not assumed			2.889	61.85	0.005	317.172	109.772	97.73	536.614

One Extension Officer during Key Informant Interview (KII) reported that the efforts of HRNS have significantly bolstered coffee production since their involvement began in 2012. The presence of HRNS has played a pivotal role in the sustained growth of coffee production over the years. These achievements are attributable to a range of interventions focusing on sound agricultural practices, including soil conservation, proper utilization of farm inputs, addressing market dynamics, and the provision of essential resources such as coffee seedlings to farmers. Each of these components has played a significant role in fostering increased coffee yields over time. (KII, Rungwe District, March 15, 2023).

In a Key Informant Interview (KII), one manager from Kenya highlighted that the efforts of the NGO are making a significant impact. Similarly, Abilla [43] reported: “Many farmers have learned how to use and assess fertilizers more efficiently as a result of various training programs, while others have adopted new farming management methods, resulting in increased production. Most farmers’ yields have grown significantly as a result of the effects of such training; also, the overall quality has greatly improved. Furthermore, some have moved to new agricultural practices and established their own nurseries to raise seedlings, using the knowledge taught to them” (page 60).

Factors Contributing to Success of HRNS Interventions

The study aimed to comprehensively understand the factors contributing to the success of HRNS interventions in increasing coffee production among participating farmers. Study findings in Table V reveal that a majority of farmers reported significant benefits from the interventions. Accordingly, 52% of farmers noted improved access to high-quality coffee seeds and seedlings, while 38% highlighted the acquisition of knowledge on good agricultural practices. Moreover, 8% of farmers reported gaining access to loans for essential inputs such as fertilizers, pesticides, seeds, and seedlings. Notably, 42% of farmers indicated that they had improved their coffee production by using proper knowledge on the optimal use of farm inputs. These findings suggest that HRNS interventions were successful in facilitating easier access to superior coffee seedlings and seeds, emphasizing the critical role of seed quality in influencing yields and overall production. As highlighted by Tadesse et al. [44], farmers recognize the significance of accessing improved, early maturing, and disease-resistant coffee varieties as key strategies for boosting coffee production. On the other hand, in Tanzania, some coffee varieties have the potential of yielding 3000 kg/ha, which is equivalent to 7410 kg/ha for improved varieties.

Table V. Multiple Responses on the Reasons Contributed to Increased Coffee Production ‘with HRNS Interventions (n = 52)

Variable	Frequency	Percentage (%)
Provision of improved coffee seeds and seedlings	27	52
Provision of knowledge on proper use of farm inputs	22	42
Accessibility of loans for inputs	4	8
Provision of knowledge on GAP on coffee	20	38

Findings from focus group discussions (FGDs) conducted in Mbeya Districts “shed light on the impact of HRNS interventions on coffee production. Participants unanimously reported a notable increase in coffee yield after the implementation of HRNS initiatives. Key factors, including the distribution of superior coffee seedlings, the adoption of best practices in utilizing farm inputs, educational outreach on effective agricultural techniques, and the meaningful engagement of both genders in coffee cultivation, are associated with an increase in coffee production. These findings highlight the relevance of the approach employed by HRNS, which has evidently contributed to tangible improvements in coffee production among the farmers surveyed (FGDs, Mbeya District, March 28, 2023).

In their study on NGO operations in Yemen, Al-Najjar et al. [45] revealed the findings on the efforts on empowering farmers to enhance coffee production. The authors reported that using targeted interventions, farmers were provided with improved coffee seedlings alongside comprehensive training sessions aimed at refining their agricultural practices. “By offering support in both the provision of high-quality seedlings and capacity-building activities, the program sought to catalyse sustainable improvements in coffee yields” (page 6).

During Key Informant Interview, the Zonal Manager of the Tanzania Coffee Board “Emphasized the pivotal role of Arabica coffee seeds sourced from TaCRI Mbimba in HRNS Interventions in Mbeya and Rungwe Districts. These seeds are renowned for their superior quality and resilience, forming a cornerstone of the initiative. Implemented in collaboration with lead farmers in designated wards, the initiative encompasses comprehensive training sessions covering such topics as climate change adaptation, soil conservation techniques, gender equality in agricultural practices, and the optimized utilization of farm inputs such as fertilizers and pesticides” (Mbeya, March 15, 2023).

Similarly, another study, [46] disclosed that extension agents believe that the extension efforts of non-governmental organizations (NGOs) are more successful than those of the public sector because the former category typically focuses on smaller geographic areas.

In the context of coffee production, HRNS interventions provide farmers with valuable resources such as high-quality seedlings and knowledge on best practices, which are rare and not easily imitated by competitors. Therefore, these interventions contribute to the competitive advantage of participating farmers by enhancing their resource base and ultimately improving their coffee production.

Conclusion and Recommendations

Conclusion

This study aimed to assess the impact of Hanns. R. Neumann Stiftung (HRNS) interventions on the improvement of coffee production among smallholder coffee farmers in Mbeya and Rungwe Districts. The findings reveal that HRNS interventions have a significant positive impact on coffee production among the beneficiary smallholder farmers, as evidenced by significantly higher coffee yields compared to their non-beneficiary smallholder counterparts. Key factors contributing to this success include the provision of improved coffee seedlings, effective guidance on the proper utilization of farm inputs, dissemination of information on optimal agronomic practices for coffee production, and the active involvement of women in the coffee cultivation process. These outcomes underscore the crucial role of HRNS interventions in fostering sustainable and productive coffee farming practices, thereby contributing to the overall growth of the coffee sector in the studied districts.

Recommendations

Based on the research findings, the study recommends the strengthening and promotion of extension interventions by Hanns. R. Neumann Stiftung (HRNS) to smallholder coffee farmers in the coffee industry. The Tanzanian Government should ensure the provision of farming subsidies, including continuous access to quality coffee seedlings and farm inputs. Collaboration with the private sector partners or solely government efforts should be prioritized to ensure widespread access to these essential resources for increased coffee production.

Limitation of the Study

The current study experienced notable limitations that external factors, such as variations in weather conditions, market dynamics, or changes in government policies, could affect coffee production independently of HRNS Interventions. The study also relies on a cross-sectional design, capturing a snapshot of information at a specific point in time, which may not fully capture the dynamic nature of agricultural practices and outcomes.

Areas for Future Research

Future research in this domain could explore the long-term sustainability and scalability of HRNS interventions through longitudinal studies to track the impact of HRNS interventions on coffee production outcomes. Finally, a comparative analysis across different regions and farming communities could help identify variations in the impact of HRNS Interventions considering diverse agro ecological conditions and socio-economic contexts. Future studies might also focus on the role of technology adoption in HRNS Interventions programs, exploring how digital tools and precision agriculture could further optimize coffee production practices.