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Applied Biotechnology & Bioengineering

Research Article Volume 11 Issue 3

Analysis of determinates for the adoption of agricultural technologies by family farmers in the administrative post of OCUA, Northern Mozambique

Dalmildo Agostinho Máquina,1 Lérida Palmira Domingos Madeira Castiano,1 Bilde Agostinho Máquina,2 Adérito Jeremias Vicente da Silva3

1Department of Forestry and Wildlife, Forestry Engineer, Bilibiza Agrarian Institute, Mozambique
2Agricultural production department, Agricultural Engineer, Vale do Lúrio Polytechnic Institute, Mozambique
3Department of Agricultural Inputs, Forestry Engineer, Ministry of Agriculture and Rural Development, National Directorate of Commercial Agriculture, Mozambique

Correspondence: Dalmildo Agostinho Máquina, Master’s student in the Postgraduate Program in Agribusiness at UniLúrio Business School, (Forestry Engineering), Trainer at the Agrarian Institute of Bilibiza/Ocua, Department of Forestry and Wildlife, Mozambique, Tel +258 866158712

Received: February 09, 2024 | Published: June 19, 2024

Citation: Machine DA, Castiano LPDM, Machine BA, et al. Analysis of determinates for the adoption of agricultural technologies by family farmers in the administrative post of OCUA, Northern Mozambique. J Appl Biotechnol Bioeng. 2024;11(3):54-58. DOI: 10.15406/jabb.2024.11.00360

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Abstract

The adoption of new technologies in agriculture has attracted special attention in economic development because they offer the opportunity to substantially increase production and income. Therefore, the present research aims to analyze the potential factors for the adoption of agricultural technologies by farmers in the family sector in the Administrative Post of Ocua. To carry out the research, semi-structured interviews were carried out to collect information/data, which were then processed using Excel and SPSS software. The results show that around 73% adopt row cultivation using the compasses and density recommended for each type of crop, 54% use improved seeds, 52% apply some type of irrigation, 33% seed conservation, 32% use organic fertilizers, 34% use tractors and 21% capture and conserve rainwater on the farm. Regarding the determining factors for the adoption of different agricultural technologies, 91% point to Access to rural extension services, followed by Access to agricultural credit (89%) and membership in a farmer association (78%). Another significant part points to formal education at a rate of 53% and finally access to information on agricultural products at a rate of 42%. Access to credit, access to extension consultancy services and members of farmer associations are more likely to adopt new agricultural technologies.

Keywords: agrarian technologies, agriculture in the family sector and community

Introduction

Agriculture is the engine for economic growth and poverty reduction in developing countries such as those in Sub-Saharan Africa.1,2 It plays an important role in food and nutritional security, combating poverty, generating rural employment and reducing rural exodus.4–7 Therefore, increasing productivity and agricultural income is important in the fight against hunger and malnutrition, especially in rural regions of developing countries.3

Agriculture in Mozambique is still predominantly explored by rural populations on small farms that cultivate in an environment characterized by rainfed production and without a significant link with the market8#ref8,9 where within them, the production of food for consumption constitutes the main basis of the productive structure of the family sector,10 characterized by the use of rudimentary production techniques, intensive use of labor force, low level of capitalization and use of inputs, enabling the reduction of dependence on inputs and services that are difficult to access (extension) in local markets (Singo, 2020).11,12

Mozambican agriculture has low productivity.13 This situation contributes to the perpetuation of poverty in the country. In this sense, increasing agricultural productivity is considered one of the crucial actions for reducing poverty in Mozambique.14 Agricultural productivity growth is promoted by improved technologies, including improved seeds, fertilizers and control of water resources.15,16

The adoption of new technologies in agriculture has attracted special attention in economic development because the majority of the population in developing countries survives on subsistence agriculture and new technologies offer the opportunity to substantially increase their production and income.17 There are few studies that seek to explain the slow adoption of improved agricultural technologies in Mozambique. Bandiera and Rasul,.18 ; Langyintuo and Mekuria,.19 and Zavale et al.,20 are among the few researchers who have looked at the adoption of improved technologies in Mozambique.

Therefore, the present study aims to analyze the potential factors for the adoption of agricultural technologies by farmers in the family sector in the Administrative Post of Ocua. The study is important because of the possibility of identifying how family farmers from different PAO communities have reacted to the adoption of agricultural technologies.

Material and methods

Study area

The research location for this research was the localities of Mahipa, Ocua-sede, Samora Machel and Napuco of the Administrative Post of Ocua, district of Chiúre, province of Cabo Delgado circumscribed to the North with the district of Ancuabe, to the South with the province of Nampula through the Lúrio River to the East with the district of Mecufi and to the West with the districts of Namuno and Montepuez.21

The inhabitants of the PAO community are generally characterized by essentially rural origins. Agriculture is the dominant activity practiced manually on small family farms in a system of intercropping based on local varieties. The population uses various forest products in the construction of their homes.21

In these locations, the primary technologies used and the low crop yields, the main harvest is generally insufficient to cover basic food needs, which are only met through food aid, second harvest, non-agricultural income or other mechanisms of survival. During times of scarcity, families resort to a variety of survival strategies that include collecting wild fruits, selling firewood, charcoal, stakes, reeds, drinks, hunting and fishing.21

Data collection procedures

To obtain information from the communities, a questionnaire was prepared with open and closed questions, with a view to obtaining information on the subject to be researched through a survey (questionnaire survey). A questionnaire is a technique that aims to obtain information in a systematic and orderly manner about the population being studied and the quantitative variables that are the object of the study. Therefore, the questionnaire that was applied went through a testing stage, in a reduced universe, so that possible formulation errors could be corrected.

The questionnaire was designed to find answers to central questions such as:

  1. Socioeconomic information of research participants
  2. Main agricultural technologies adopted by local producers
  3. Main cultivation strategies and practices used
  4. Determinants of adoption and use of technologies by producers

Sample and sampling

The sample for this research was made up of farmers from the family sector residing in the Administrative Post of Ocua in the localities of Mahipa, Ocua-sede, Samora Machel and Napuco, who represented, in total, 100 families. The type of sampling used was non-probability convenience sampling. In this type of sampling, the constituents are people who are within reach of the researcher and willing to respond to the data collection instrument.22 From the perspective of Gil,.23 non-probabilistic convenience sampling constitutes the least rigorous of all types of sampling, which is why it is devoid of any statistical rigor. The researcher selects the elements he has access to, assuming that these may, in some way, represent the universe.

Procedure for data analysis

After data collection, they were checked, possible errors were corrected and validated. After validation, the data were subsequently coded and processed in a Microsoft Excel spreadsheet and in the Social Science Statistical Package, (SPSS) version 25, then grouped into tables and graphs of frequencies and percentages depending on the analysis requirements. After processing, the results obtained allowed us to give a general idea of ​​the current situation in the study area, in order to compare different positions of the respondents.

Results and discussions

Characterization of the socio-demographic and socioeconomic profile of producers

100 households were interviewed, 29% of which were headed by women and the remaining 71% by men. The table below presents the demographic characteristics of the families interviewed at the Administrative Post of Ocua (Table 1).

Education level

 

 

 

Frequencies

No level

Primary

Secondary

Absolute

32

50

18

Relative (%)

32%

50%

18%

Age group

Frequencies

18-29

30 to 50

≥ 50

Absolute

19

50

31

Relative (%)

19%

50%

31%

Number of individuals in households

Frequencies

≤ 4

5 to 7

≥ 7

Absolute

27

60

13

Relative (%)

27%

60%

13%

Table 1 Characterization of the socio-demographic profile

Analyzing the level of education in the families interviewed, it was observed that 32% of the population is illiterate. Around 50% of those interviewed have primary education, with the majority having attended up to seventh grade. A smaller proportion have education and attended secondary level, 18% having mostly attended up to the 10th grade, the others attended up to the 12th.

Regarding the age range of the interviewees, it was possible to observe that the majority of the population (50%) is adults, in an age range between 30 and 50 years old, followed by the elderly population (31%), over 50 years old. and finally the young population (19%) aged between 18 and 29 years old. Regarding the age range, Mário (2015), in a similar study, obtained the following results: in the range of 11 to 20 years with 5 producers, from 21 to 30 years with 44 producers, from 31 to 40 years with 67 producers, from 41 50 years ago 42 producers, and finally over 50 we have 11 producers.

It was observed that most families (60%) have a number of households ranging from 5 to 7 individuals. A value that can be considered high, compared to the average for households in other rural communities in Africa and the world in general. This is probably due to the fact that in Mozambique the birth rate is very high, especially in rural areas.

The results of this research are in accordance with the census carried out by MAE19 and studies carried out by INE and MISAU.24,25 The high birth rates observed in Mozambique are related to poverty and high illiteracy rates.24 According to Ribeiro,.26 Mozambique has an estimated population of 22.4 million inhabitants, 70% of whom live in rural areas and approximately 75% depend on agriculture, forestry and fishing.

Analyzes carried out allow us to conclude that the greater the number of households, the larger the area of ​​the farm, as the greater the labor force for agricultural production and other activities, given that the population depends on agricultural production for survival, the same fact it was also found by (Nube, 2013;).27

In relation to the economic activities carried out, the data show that 100% of those interviewed dedicate themselves to agriculture as their main activity. In turn, 62% dedicate themselves to agriculture as their main activity. Therefore, the remaining “non-beneficiaries” who practice agriculture as a complementary activity, indicated commerce (19%), casual employment (11%) and provision of services in the public service (8%) as their main activities.

Main agricultural activities practiced by households

Regarding the main agricultural and livestock activities practiced by PAO AFs, the results show that all families practice agriculture and around 59% practice livestock. In relation to activities related to the exploitation of forest resources, the percentages vary from 52% for the collection of wild fruits and other non-timber products, 20% for the production and sale of charcoal and less than 10% for the cutting and sale of stakes and firewood.

Characteristics of the family’s agricultural activities

In relation to time in agricultural activity (Table 2), it appears that most interviewees have dedicated themselves to the activity for more than 10 years.

Time in agriculture(years)

Absolute frequency (fi)

Relative frequency (fri)

Up to 5

21

21%

5 to 10

37

37%

10 to 15

25

25%

More than 15 years

17

17

Total

12

100%

Table 2 Time in agricultural activity

According to Karam,.28 family sector farmers can be considered those farmers who generally have a life path that is reproduced materially, socially and culturally in rural areas.

Regarding the size of the farms, respondents indicate that 15% of family farmers interviewed practice agriculture in areas smaller than 1 hectare, 40% in areas ranging from 1 to 2 hectares, and 32% have areas ranging from 2 to 5 hectares. and 14% in areas equal to or greater than 5 hectares as shown in the figure below (Figure 1).

Figure 1 Size of family farmers’ farms.
Source: Authors (2022).

It was found that there are more farmers practicing agriculture in medium areas (1 to 2ha and 2 to 5ha) than larger areas, as found by Reis,.29 According to the same author. The lack of production areas larger than 5ha is partly due to the lack of land for farming and, on the other hand, soil degradation. The findings described above are in line with what was described by MINAG,.30 when it states that the family sector cultivates an average area of ​​2 ha. The results are in line with Sitoe,.10 when he states that the agrarian sector in Mozambique is essentially made up of the family sector and in rural areas of Mozambique, family farming is made up essentially of small farms (cultivating less than 5 ha).

The results on the main crops practiced by the AFs of the villages surveyed in the PAO show that the main crops, in terms of number of families that cultivated, are the following: Corn, which was cultivated by around 99% of AFs, cowpeas (77% ), jugo beans (39%), pumpkin (27%), peanuts (70%), sorghum (52%), millet (52%) and cucumber (51%).

Main cultivation strategies and practices used

Table 3 presents the number of Family Farmers who applied each of the 15 agricultural practices surveyed.

S. no

Cultivation strategies

Frequency

Percentage

1

Fertilizer application

11

11%

2

Manure application

21

21%

3

Compost preparation and application

23

23%

4

Application of synthetic pesticides

22

22%

5

Preparation and application of natural pesticides

4

4%

6

Crop rotation

79

79%

7

Mulch

72

72%

8

Use of cover crops

53

53%

9

Minimum tillage

42

42%

10

Use of improved varieties

57

57%

11

Intercropping with forest/fruit trees found on farms

60

60%

12

Improved fallow using fast-growing, drought-tolerant species

37

37%

13

Rainwater collection and conservation on the farm

21

21%

14

Row cultivation using the calipers and recommended density for different crops

89

89%

15

Use of land preparation practice for cultivation through the slash and burn system

54

54%

Table 3 The number of family farmers who applied each of the 15 agricultural practices surveyed

Main agricultural technologies adopted by local producers

To improve production and productivity, the SDAE and other partners linked to agriculture have carried out technical assistance activities in matters of using new production technologies and the subsidized sale of inputs has begun. Farmers are technically assisted in matters of sowing, demonstration and consolidation of measures, seed density per hole, phytosanitary control, harvest monitoring and product storage, among others (Table 4).

Technologies

Frequency

Percentage

Row cultivation using the recommended compasses and density for each type of crop

73

73%

Use of tractors

24

24%

Use of improved seeds

54

54%

Use of organic fertilizers

32

32%

Use of some type of irrigation

52

52%

Seed conservation

33

33%

Rainwater collection and conservation on the farm

21

21%

Table 4 Main agricultural technologies adopted

Regarding the agricultural technologies incorporated by producers, most of the interviewees 73% mention row cultivation using the compasses and density recommended for each type of crop, 54% indicate the use of improved seeds, 52% refer to the application of some type irrigation, 33% mention seed conservation, 32% mention the use of organic fertilizers, the use of tractors with a percentage of 24% and finally the capture and conservation of rainwater in the farm with a rate of 21%.

In almost every place in the world where the process of agricultural transformation has been documented, growth in agricultural productivity is promoted by improved agricultural technologies, including improved seeds, fertilizers, and control of water resources.15,16

Determinants of the adoption and use of agricultural technologies by PAO producers

The Figure below presents the main factors that determine the adoption of agricultural technologies by farmers in the Administrative Post of Ocua (Figure 2).

Figure 2 Factors determining the adoption of different agricultural technologies.
Source: Authors (2022).

Regarding the determining factors for the adoption of different agricultural technologies, it is possible to observe in the figure above that the majority of farmers, 91% point out Access to rural extension services, followed by Access to agricultural credit (89%) and membership in some association. farmers (78%). Another significant part points to formal education at a rate of 53% and finally access to information on agricultural products at a rate of 42%.

Regarding access to extension services, Pattanak et al. (2003) cited by Lopes31 argue that access to public/private extension services plays an important role in the adoption of new technologies because producers are exposed to information about new technologies by extension agents (through group discussions, demonstrations field reports and other sources of information) tend to adopt new technologies.

Most studies carried out in the country indicated that access to extension services had a positive response to adoption.32–34 Artur35 argues that increasing crop productivity requires efforts in several directions, which means that new technologies and knowledge must be developed and introduced and, for this, the existence of a strong research and extension service is important and also involves education. and training producers in various areas.

The lack of access to agricultural credit negatively affects the adoption rate of new technologies. Therefore, it is a prominent variable and favorable to adoption. It is therefore argued that producers with credit restrictions are unlikely to be interested in investing in new technologies and typically allocate a considerable part of their capital to traditional technologies. Most studies indicate that there are influences from differentiated access to credit and the adoption of technologies.36,37

Regarding membership in farmers' associations, Sitoe and Sitole38 state that farmers' associations are extremely useful in reducing information asymmetries and empowering their members to negotiate prices for agricultural products and inputs. According to Come,14 in Mozambique the percentage of agricultural holdings with farmers affiliated to associations is extremely low.

The formal education of the head of the household has a consistently positive relationship to most technology adoption decisions. The effect is strong for high levels of education. Having completed at least five years of schooling indicates completion of first grade primary education. The completion of at least primary education implies a greater inclination to adopt new technologies than a low level of education, or zero.36

Access to information on the prices of agricultural products is essential for reducing information asymmetries between farmers, consumers and intermediaries. This has the potential to improve market efficiency.14 Information asymmetry is one of the factors that cause market failures. This is particularly relevant in the case of Mozambique where agricultural production is mostly small-scale, a situation that results in the farmer having weak bargaining power to negotiate the price of products. Under these conditions, the farmer has no other option than to accept the price determined by the retailer, which is often low.14,39–42

Conclusion

The agricultural technologies incorporated by producers in the communities studied are: row cultivation using the compasses and recommended density for each type of crop, use of improved seeds, the application of some type of irrigation, seed conservation, the use of organic fertilizers, the use of tractors and the capture and conservation of rainwater on the farm (control of water resources)

Access to credit, access to extension consultancy services and members of farmer associations are more likely to adopt new agricultural technologies.

The findings regarding credit are particularly strong and robust. The difficulty in accessing credit seems to be one of the biggest constraints for the adoption of technology. Being a member of an association also appears to positively influence adoption decisions through the dissemination of improved information.

The results also indicate the positive impacts of extension contact on the adoption of new technologies. The role of extension becomes stronger when household heterogeneity is recognized through the use of the panel data model.

Acknowledgments

None.

Conflicts of interest

Authors declare that there is no conflict of interest.

Funding

None.

References

  1. Aref F. Farmers' participation in agricultural development: The case of fars province, Iran. Indian Journal of Science and Technology. 2011;4(2):155–158.
  2. Cunguara B, Garrett J. The Agrarian Sector in Mozambique: Situational analysis, constraints and opportunities for agrarian growth. Document presented at the Dialogue on the Promotion of Agrarian Growth in Mozambique. 2011.
  3. Ponguane S, Mucavele N. Determinants of agricultural technology adoption in Chókwè District, Mozambique. Munich Personal RePEc Archive. 2018.
  4. Food and Agriculture Organization of the United Nations – FAO. Manual of annual statistics and selection of agriculture and food indicators. 2000.
  5. United States Agency for International Development – ​​USAID. Private Investment in the Agriculture sector in Mozambique. Nathan Associates, Mozambique. 2008.
  6. Rural Mutual Aid Association – ORAM. Mutual aid organizations and Network of organizations for food security. The Impact of Agrarian Policy in Mozambique. 2010.
  7. Mosca J. Family farming in Mozambique: Ideologies and policies. Mozambique. 2014.
  8. World Bank. Mozambique Agricultural Development Strategy: Stimulating Smallholder Agricultural Growth, Agriculture, Environment, and Social Development Unit Country, Department 2, Maputo. 2010.
  9. Remane MA. Multifunctionality of family farming in the district of Chibuto. Dissertation to obtain a Master's degree in Rural Development. Maputo. 2014.
  10. Sitoe TA. Family farming in Mozambique: Rural development strategies. Maputo. 2005.
  11. Mucapana CA. Allocation of productive resources in the family sector: case report in the districts of Dondo, Nhamatanda, Gondola and Manica. Course culmination work to obtain a degree in Agronomy. Maputo. 2002.
  12. Moura J De S, Rosário NM. The role of rural financial services in promoting the development of family farming: Case of the 25 de Setembro Cooperative in the district of Boane, Mozambique. Society and Territory Natal. 2016;28(2):42–56.
  13. Marassiro M, Oliveira M, Pereira G. Family farming in Mozambique: Characteristics and challenges. Research Society and Development. 2021;10(6):e22110615682.
  14. Come SF. The dynamics of the adoption of agricultural technologies in Mozambique: analysis of the period 2002 to 2020. Research Society and Development. 2021;10(10):e332101018691.
  15. Johnston BF, P Kilby. Agriculture and structural transformation: economic strategies in late-developing countries. International Affairs. New York: Oxford University Press. 1975;52(1):101–102.
  16. Gabre-Madhin E, Johnston B. Accelerating Africa's structural transformation: Lessons from Asia. AgEcon. New Science, New York. 2002.
  17. Jorge AA. Impact of the Local investment fund on the adoption of agricultural technologies: Case of the District of Boane (2006-2011). Dissertation to obtain a Master's degree in Educational Extension. 2013.
  18. Bandiera O, Rasul I. Social networks and technology adoption in Northern Mozambique. The Economic Journal. 2006;116(514): 869–902.
  19. Langyintuo AS, M Mekuria. Accounting for neighborhood influence in estimating factors determining the adoption of improved agricultural technologies. Paper presented at the American Agricultural Economics. 2005.
  20. Zavale H, Mabaya E, Christy R. Adoption of improved maize seed by smallholder farmers in Mozambique. Department of Applied Economics and Management. Ithaca, New York: Cornell University; 2005:14853–7801.
  21. Ministry of State Administration – MAE. Profile of the district of Chiúre Province of Cabo Delgado. Maputo. 2005.
  22. Laville C, Dionnne JA. Construction of Knowledge: research methodology manual in human sciences. Porto Alegre: Artes Médicas Sul Ltda; Belo Horizonte: UFMG; 1999. 337 p.
  23. Gil A. Social research methods. 6. São Paulo: Atlas; 2008.
  24. National Statistics Institute – INE. Multiple Indicator Survey 2008. Maputo: National Statistics Institute; 2009.
  25. Ministry of Health – MISAU. Demographic Health Survey 2003, Ministry of Health, Maputo. 2005.
  26. Ribeiro A. Natural resource management policy in Mozambique: an overview. University of Liverpool; 2001.
  27. Landry J, Chirwa P. Analysis of the potential socio-economic impact of establishing plantation forestry on rural communities in Sanga district, Niassa province, Mozambique. Land Use Policy. 201128(3):542–551.
  28. Karam, KFA. Woman in organic agriculture and new ruralities. Feminist Studies Florianópolis. 2004;12(1):303–320.
  29. Reis SJC. Traditional agro-forestry practices above 1000 m altitude in the villages of Nhamombe, Chua and Chinhamazizi in the Locality of Penhalonga. Final Project, department of forestry engineering, Eduardo Mondlane University. Maputo. 2011.
  30. Ministry of Agriculture – MINAG. National Investment Plan for the Agrarian Sector (PNISA). Republic of Mozambique. 2012.
  31. Lopes H. Adoption of improved maize and common bean varieties in Mozambique. MSc Thesis, Michigan State University, Michigan. 2010.
  32. Cunguara B, Garrett J, Donovan C, et al. Situational analysis, constraints and opportunities for agrarian growth in Mozambique. Research Report N073P. Maputo, Mozambique: Directorate of Economy, Ministry of Agriculture. 2013.
  33. Mazuze F. Analysis of adoption of orange-fleshed sweet potatoes: The case study of Gaza province in Mozambique. MSc Thesis, Michigan State University. Michigan. 2004.
  34. Cavane E, Donovan C. Determinants of adoption of improved maize varieties and chemical fertilizers in Mozambique. Journal of International Agricultural and Extension Education. 2011;18(3):5–22.
  35. Arthur, L. Why the last remains the last: Reframing Mozambican green revolution in the 21st Century. African Crop Science Conference Proceedings. Uganda. 2012;10:287–294.
  36. Uaiene R. Determinants of agricultural technology adoption in Mozambique. Discussion papers No 67E. Maputo: National Directorate of Studies and Policy Analysis, Ministry of Planning and Development. 2009.
  37. Rauniyar G, Goode F. Managing green revolution technology: An analysis of a differential practice combination in Swaziland. Economic Development and Cultural Change. The University of Chicago. 1996;44(2):413–437.
  38. Sitoe T, Sitole A. Determinants of farmer's participation in farmers' associations: Empirical evidence from Maputo Green Belts, Mozambique. Asian Journal of Agricultural Extension Economics Sociology. 2019;37(1):1–12.
  39. Marconi MA, Lakatos EM. Fundamentals of Scientific methodology. 5. São Paulo: Atlas; 2003.
  40. Mário S das D. Study of the contribution of family sector agriculture to the socioeconomic development of the Homoíne District, Chindjinguir. 2014.
  41. Cloud T. Socio-economic impact of forest plantations in Mozambique - a case study of Niassa province. Master's Dissertation in Forestry Engineering, Agricultural Sciences Sector, Federal University of Paraná. Curitiba. 2013.
  42. Singer P. Is it possible to bring development to poor communities? Text for discussion. Brasilia. 2004.
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