NAAS Score 2020

                   5.36

UserOnline

Free counters!

Previous Next

Socio-Economic Characterization of Some Milk Value Chain Actors in the Vina Division- Producers, Collectors and Processors

Clemence Aggy Njehoya Youssouf Mfopit Mouliom Paul Marie-Désiré Ko Awono Kingsley Etchu Robert Domwa Akuro Andisson Choh Bella N. Siri
Vol 7(9), 196-204
DOI- http://dx.doi.org/10.5455/ijlr.20170710034812

The study was conducted to have an insight on the milk value chain in the Vina division. In each village, milk producers, collectors and processors were interviewed. The producers encountered had a relatively low level of education (73% were primary school leavers or had no formal education). Women were very poorly involved in the production and collection of milk (1.5%). The cattle breed mostly used in dairy production was Gudali. Only 42.8% of villages had milk collection points. Most of the milk collected was sold or consumed. Cattle were naturally grazed. The animals were only milked in the morning. The mean production per cow varied according to the breed: Goudali (2.47 liters), Holstein (6.6 liters) and cross-breeds (3.29 liters). The different milk products were- Curds (85.2%), pasteurized milk (52.9%), butter (14.7%), cheese (2.9%) and cream (2.9%) of transformers. There is a need for training at all levels of the chain.


Keywords : Bovine Cameroon Milk Value Chain

Introduction

In Cameroon, per capita annual consumption of milk is currently 14 kg. To satisfy current level of consumption, the country imports and milk estimated at more than 20 billion FCFA per year (CamAgro, 2017). Local breeds have fairly good beef characteristics. The local cattle stock thus satisfies almost half of the country’s demand for meat, the remainder being covered by the production of short-cycle species (sheep, goats, poultry etc.) and imports. On the other hand, the performance of dairy production remains very limited. Genetic improvement and herd management (feed and animal health) remain the focus of the Government (MINEPIA, 2011). Several development programmes have been set up and many research projects have been carried out in the Adamawa region to improve dairy production (Mbah et al., 1987 and Messine et al.,2007). Despite this, Cameroon has a production deficit of more than 170,000 tons per year (Abouame et al., 2003). In order to satisfy the demand for dairy products, the country imports enormous quantities of milk every year, resulting in a significant loss of foreign exchange (Tambi EN, 1991).

The Adamawa is an excellent area of the cattle production with more than 30% of the national production, hence, a zone of milk production. Bovine breeding provides wealth to families and the state, provided that it is well supported, supervised and accompanied in the process of its modernization. More specifically, the dairy sector is the one that deserves most attention because of its many implications in the national and family economy as well as in the country’s strategy to improve food security (ACDIC, 2006). Since the difference in consumption is made up by dairy imports, which are continually increasing, special attention needs to be given to the development of dairy production in the country. The diagnosis of the milk value chain has permitted to know the organization of the chain, its functioning, constraints and the level of adoption of innovations.

Materials and Method

Study Area

The Adamawa region is located at 1200m altitude with two seasons of almost equal duration: a rainy season that runs from May to October and a dry season that runs from November to April. Many breeders are still practicing semi- extensive management, but there are some ranches in which there is increasing desire to intensify production. The region is divided into five divisions, including the Vina that is the study area.

Sampling and Survey

The study used the Rapid Rural Appraisal technique. In each village, milk producers, collectors and processors were selected on a random basis and interviewed individually using a semi-structured questionnaire, developed according to the specific objectives of the study. Of the eight subdivisions in the vina division, seven were selected for this study for their dominance in dairy production. They are the subdivisions of Ngaoundere1, 2 and 3, Martap, Belel and Nyambaka. At least two villages were visited per subdivision. A total of 173 questionnaires were administered. The questionnaire provided information on cows and their feeding, milk production, collection, processing and preservation.

Statistical Analysis

The survey data were subjected to the descriptive analysis. The student t test and ANOVA were used for the comparison of variables using SPSS for windows version 15 software.

Results and Discussion

Characteristics of the Producers

The producers were mainly of Fulanis (95.2%). They have a relatively low level of education (73% are primary school leavers or no formal educated). This will have a significant impact on the level of adoption of innovation in the domain. The main activity of these producers is livestock breeding (90.48%), which can be in pure farming systems (18.42%), associated with small-scale agriculture (64.91%), trade (13.16 %) or associated with others activities (03.51%). Their experience in the field of dairy production is largely varied- 60.16% have more than 10 years in the activity. But there is no significant relationship (p> 0.005) between milk production and producer experience. 79.2% of these breeders are members of producer associations. This is an asset since these organizations defend common interests such as sourcing for funding, negotiating for the delimitation of grazing areas. Table 1 summarizes some characteristics of producers.

Table 1: Producers characteristic

Parameters Proportions
Education Level
No formal education 28.12%
Primary 45.31%
Secondary 23.44%
University 03.13%
Producer Experience
1-5 years 13.01%
6-10 years 26.83%
> 10 years 60.16%
Type of Pasture
Improved pasture only 4%
Natural pasture only 26.40%
Natural & Improved 69.6%
Farmer Activities
Pure breeding 18.42%
With agriculture 64.91%
With trade 13.16%
Others 3.51%

Feeding

The main source of feeding is the natural pasture. Table 1 shows the distribution of milk producers according to the different types of grazing used. Livestock farmers use only improved feed for their animals represent 4%, while those that graze their animals naturally make up 26.4%. Finally, 69.60% of farmers use both types of grazing. These figures indicate that cattle farmers, especially dairy farmers, are aware of the innovation on improved grazing since many of them intended to genetically improve their animals as such cattle population can no longer depend on traditional management techniques. The fact that only 4% of them use them purely could be explained by the cost of setting up and maintaining an improved pasture. Ninety-eight (98.4%) of farmers provided food supplements; 96.7% of them gave the supplement once a day and the rest twice.

Milk Production

The cattle breed mostly used by breeders for dairy production is the Gudali. All the breeders keep it. Some 10.32% of these breeders also use crossbreeds obtained from crossing with exotic breeds (Holstein, Charolais, Brahman, Simmental); whereas 2.38% of them own some pure-bred exotic dairy cattle. The animals are milked once a day (in the morning). Milking is done mainly by the herdsmen (97.62%) and also by children (2.63%) for cows rearing around the household. These figures show that women have very little participation in the milk production. The average daily production per farmer and by rounding is statistically identical in all the boroughs except in Nyambaka (55.59 L /day) where it was higher (Table2).

Table 2: Milk production characteristics

Milk Production (L/day)
Bellel 14,12±1,76A
Martap 27,21±4,11A
Ngaoundéré 23,50±4,15A
Nganha 15,69±1,82A
Nyambaka 55,59±5.47B
Producer Categories
Small producer (<15L/day) 38.09%
Medium producer (16-25L/day) 22.22%
Large producer (26-40 L/day) 11.90%
Very large producer (>40L/day) 27.77%
Milk Destination
Consumption only 4%
Sale 1%
Processing 1%
Consumption + Sale 84%
Sale + Processing 2%
Consumption + Sale + Processing 8%

Producers with high level of education (university), have the highest production, although the difference is not significant (p> 0.05). This is probably due to the size of these producers. The average quantity of milk produced per cow varied according to the breed- Gudali (2.47 liters), Holstein (6.6 liters) and crossbreeds (3.29 liters). The difference in production between breeds is statistically significant (p <0.005). These values are higher than those reported by the Ministry in- charge of Animal Husbandry (MINEFI-DSCN, 1999), which stated a daily production ranging from 0.85 to 1 liter per cow in the dry season and 1.5 to 2 liters in the rainy season. Bayemi et al. (2005) reported a production of 11.4 l/day for Holstein and 373 kg of milk per lactation period for Gudali. This confirms that the Gudali is less dairy productive. On the other hand, the poor performance observed with Holstein may be due to the livestock management system which is not yet able to maintain animals of high performances (Tawah et al., 1998). The production obtained is indicative of the level of performance of the livestock management systems in which animals evolve. Considering all the health problems of exotic breed, maintaining traditional livestock management systems can only be justified if breeds used for dairy production are local breeds. The frequency of milking can also have an impact on the amount of milk produced daily. Milking is done each morning because of the nutritional status of the cows and their calves. Indeed, cows were rarely in stall. During the day, they go to graze and return in the evening to breastfeed the little ones which remained tied. A part of their energy is thus expended in the walking. The amount of water consumed is generally uncontrolled.

Daily quantities of milk produced vary from one farmer to another according to the number of cows. Thus, producers can be classified as small scale producers (less than 15 L/day), medium scale producers (16-25 L/day), large scale producers (26-40 L/day) and very large scale producers (more than 40 L/day). Table 2 shows the repartition of different types of producers according to the daily quantity of milk produced. Small producers are the most numerous; they represent 35% of the surveyed producers. They are followed by very large producers (30%), followed by medium producers (25%) and finally large producers (10%). In order to increase milk production so that the impact of this increase is perceptible, the programmes should first target small scale producers and also very large producers. Dairy production contributes significantly to the income of livestock farmers. Indeed, a study on the dairy economy in the Adamawa region showed that the monthly profit of a milk producer would be 45,326 Fcfa (Ngoma S, 2013). This gives an annual profit of more than 500,000 Fcfa.

In the dry season, milk production decreases due to inadequate/poor forage and the drying up of water points. It is the contrary in Senegal, where the sector is better organized during this period, when agro-pastoralists are not involved in agricultural activities (John Libbey, 2002). This result is a consequence of the stalling of animals during this period, which rather increases the production. A change in the management of natural resources is therefore necessary. This includes, for example, the storage of hay for the dry season and the construction of water points for the animals. But so far, dairy farmers continue to manage their farms semi-extensively. Majority complained that they did not have the means to make these improvements. According to producers, the main ways to improve dairy herds are selection (89.26%) and cross-breeding with dairy exotic breeds (10.74%) by the means of artificial insemination or use of exotic bulls. Enough work has already been done on crossbreeding local with exotic dairy breeds as cited in the present paper. These studies have recommended upon the use of F1 progeny (Bayemi et al., 2005). Milk produced is either sold, consumed or processed. The Table 2 shows that the main destinations for milk are consumption and sale. Cumulatively, 11% of the producers are also processors. These figures indicate that the majority of producers do not process their product; this creates a real problem when the raw milk is not sold. About 96% of the breeders consume the milk they produce, while 93% of them also sell the milk produced. The situation here is different from that observed in Senegal where 80% of milk produced in rural areas is destined for self-consumption (John Libbey, 2002). The average price of milk is 280.85 FCFA per liter in the rainy season and 405.35 FCFA in the dry season. Thus the season influences significantly (p <0.0001) the price of milk.

Case of Collectors

Collectors are traders who go to collect milk from producers’ farms and transport it to urban centers. To make it easier for farmers to sell their produce regularly, some government projects have financed the construction of milk collection centers. Unfortunately, these centers function as shops and not as places for collecting and preserving milk until it is processed. Forty-two percent (42.8%) of villages have milk collection points which, of these points are well constructed. The most frequent means of transport is the motorcycle (71.43%) of collectors. After the milking, the breeders take the quantity of milk destined for self-consumption and the rest is sent to the collection centers. Regardless of the season, collection is done once a day. The containers are plastic cans with narrow opening which often make effective cleaning a problem. Some 30% of collectors obtained less than 100 liters of milk per day during the rainy season, while 53% succeeded to have between 100 and 300 liters per day; only 15% had more than 300L/day. In the dry season, 69% of collectors had less than 100L of milk per day, 15% got between 100 and 300L, and 15% collected more than 300L. Milk collection takes place until 12:00 AM and delivery begins at 2:00 PM. The time taken to collect milk and deliver it, can affect the quality of the milk on delivery, especially since collectors do not have any preservative and collection centers either. Average delivery prices in the rainy season and in the dry season are 354 Fcfa and 700 Fcfa respectively. This makes a profit margin of 54F/liter in the rainy season and 200F/liter in the dry season. This highlights the need to improve supply during the dry season.

Case of Processors

Processors are represented by “dairy-restaurant” and home processing units. 26.4% of dairy-restaurants belong to GIC, and 73.53% to individuals. All transformers are of Fulani ethnic group. 42.2% of processors did not take processing as their main activity. An important majority (70%) of the processors had primary school education and 5.8% did not attend school. Processors are less grouped together than producers. This may make them more vulnerable to the difficulties they encounter in carrying out their trade. Fifty-eight percent (58%) of processors had less than 3 employees, while only 12% employed more than 5 persons. The number of employees is surely linked to the quantity of products processed and sold. It can be deduced that these processing companies are very small, which suggests the possibility of extension in the dairy processing sector. Only 39% of the processors were members of processors association, which suggests more work needs to be done in the structuring of the sector, to enhance its capability to better defend its rights and interests. About 23.5% of processors produced their own raw material (milk) which they received between 7 am and 3 pm. Seventy-six percent (76%) of processors tested the quality of the milk before buying, either by heating (58%) or visual observation (41.6%).

The products present in Ngaoundere market were designated by the generic term “kossam” which means milk in Fulani language. Depending on the type of transformation, specific terms are as follows (Kameni et al., 1999, Essomba et al., 2005)-

  1. Biraadam: raw milk, fresh, unfermented, non-skimmed;
  2. Kindirmu: which means “heavy milk”; It is whole milk, heated then curd;
  3. Penndidam: “acid” fermented milk, made from skimmed, heated and fermented biraadam;
  4. Dakéré: Mixture of fermented milk and cassava semolina;
  5. Leebol: it’s fresh butter;
  6. Yogurt: in Ngaoundere, industrial yogurt and semi-industrial yoghurt are distinguished. Both are marketed under the name of Kossam. The taste and consistency (firmer in general) are different from the kindirmou or penndidam crafted, due to different ferments.

The products sold by the processors are pasteurized milk (Biraadam), 52.9%, curds (Kindirmu, 85.2%, butter (Leebol) 14.7%, cheese and cream by 2.9% of transformers. These are the same products that Kameni et al. (1999) have reported except for the cream which is a new product, requested either because of the proliferation of bakeries or because of the evolution of consumer tastes. Two of these products are most preferred by customers: pasteurized milk and yogurt. Majority (76.45%) of transformers processed less than 100L/day, while 23.5% processed more than 100L/day. These values are better understood when one recalls that the majority of processors use less than 03 employees in their activity.

The equipments used are rudimentary and consists of pots, buckets, cans, plastic bottles. The processing methods were still artisanal and only 29% of processors have been trained for this work. This has a significant influence on the handling and presentation of these products. Considering the sensitivity of dairy products, it is important that particular emphasis be placed on the training of transformers in the hygiene and quality of products. Some 40.7% of transformers stopped their activities in the dry season due to the scarcity and high price of milk. Those who have enough money continue by using imported powdered milk. In the rainy season, there is an abundance of fresh milk causing some 15% of producers to lose milk which could be transformed locally into powder and used in the dry season. Unfortunately, local transformers do not have the technology.

Constraints

The milk value chain members were facing many constraints. The most important are genetic, nutrition, health, infrastructures and formations. Constraints to milk chain are listed in Table 3.

Table 3: Constraints to milk chain

Actors Constraints
Producers Lack of improved forage pasture (Brachiaria sp, stylosanthes sp)
Low nutritive value of traditional grasses
Inadequate pasture management and supplementation
Low productivity of local breeds
Unavailability of good dairy breeds
High susceptibility of exotic dairy breeds to Ticks and tick-borne diseases
High prevalence of diseases like brucellosis, FMD and Gastrointestinal parasites
High costs of veterinary products
Collectors Limited quantity of milk in dry season
Long distance between production area and urban centres
Bad state of roads
Containers which do not permit effective cleaning
Processors Limited quantity of milk in dry season
Electricity
Conservation and packaging
Lack of modern equipment and technical know-how

Conclusion

The milk value chain is made up of producers at the base, collectors, and transformers. Each of these links in the chain plays an important role in the sustainability of the value chain. Local breed performances are low. There is need to increase production through genetic improvement and above all, the improvement of the production system from semi- extensive to semi- intensive or intensive. There is also the need for training of stakeholders at all levels of the chain for better performance and marketing.

References

  1. Abouame S, Ekue F, Fondoun JM, Messine O, Poné K, Ngwa A, Fotso JM, Njakoi H, Sofa J. 2003. In : Rapport national sur les ressources zoo génétiques des animaux d’élevage du Cameroun. 109p
  2. ACDIC (Association citoyenne de défense des intérêts collectifs). 2006. In : Filière laitière au Cameroun. 69 p.
  3. Bayemi PH, Bryant MJ, Perera BMAO, Mbanya JN, D Cavestany D and Webb EC. 2005. Milk production in Cameroon: A review. Livestock Research for Rural Development. Vol 17. Art. #60. www.lrrd.org/lrrd17/6/baye17060.htm
  4. CamAgro. 2017. Filière lait. www.camagro.cm
  5. Essomba JM, Dury S, Edjenguèlè M, Bricas N. 2005. In : La consommation des produits laitiers à Ngaoundéré au Cameroun : l’émergence des MPE. Ressources vivrières et choix alimentaires dans le bassin du lac Tchad. Pp458.
  6. John Libbey 2002. Production laitière périurbaine et amélioration des revenus des petits producteurs en milieu rural au Sénégal. Cahiers Agricultures. 11, 4: 251-7
  7. Kameni A, Mbanya NJ, Nfi A, Vabi M, Yonkeu S, Pingpoh D, Moussa C. 1999. Some aspects of the peri-urban dairy system in Cameroon. International journal of technology, 52, 2:63-67
  8. Mbah DA, Mbanya J. and Messine O. 1987. Performance of Holsteins, Jerseys and their zebu crosses in Cameroon: preliminary studies. Sci. Tech. Rev., Agron. and Anim. Sci. 3, 2: 115-126.
  9. Messine O, Schwalbach LJM, Mbah DA, Ebangi AL. 2007. Non-genetic Factors Affecting Gestation Length and Postpartum Intervals in Gudali Zebu Cattle of the Adamawa Highlands of Cameroon. TROPICULTURA, 25, 3 : 129-133.
  10. MINEFI-DSCN. 1999. In : Annuaire statistique du Cameroun 1998. Ministère de l’Économie et des Finances – Direction de la Statistique et de la Comptabilité nationale. Yaoundé.
  11. MINEPIA. 2011. Document de stratégie du sous-secteur de l’élevage, des pêches et des industries animales. 125pp.
  12. Ngoma S. 2013. APESS, Etude des chaines de valeur au Cameroun, rapport d’analyse. 43p
  13. Tambi EN. 1991. Dairy production in Cameroon: growth, development, problems and solutions. World Animal Review (67): 38-48.
  14. Tawah CL, Mbah D A, Messine O and Enoh MB. 1998. Effects of genotype and environment on milk production and reproduction of improved genotypes from the tropical highlands of Cameroon. Proceedings of the 6th World Congress on Genetics Applied to Livestock Production, Armidale, NSW, Australia, pp.11-16.
Full Text Read : 1593 Downloads : 388
Previous Next

Open Access Policy

Close