Livestock Research for Rural Development 24 (5) 2012 Guide for preparation of papers LRRD Newsletter

Citation of this paper

On-farm evaluation of dairy farming innovations uptake in northern Malawi

S F Tebug, S Chikagwa-Malunga* and S Wiedemann

Institute of Animal Breeding and Husbandry, Christian-Albrechts-University Kiel,
Olshausenstraße 40, D-24098 Kiel, Germany.   ;
* Luyanga Research Station, P.O. Box 59, Mzuzu, Malawi


The objective of this study was to evaluate and identify farm characteristics associated with adoption of common dairy innovations at farm level in the Northern region of Malawi. Concurrently, uptake of a regular farm recording scheme was assessed. One hundred and fifteen dairy farms were selected and included in the study. Data collection was based on individual interviews of farmers using a semi-structured questionnaire, visual inspection as well as individual farm records.

Most of the farmers (91.3%) practiced zero grazing while a minority supplemented protein (20.0 %) or minerals (11.3 %) to the animals. The number of dairy innovations practiced increased significantly (p = 0.0101) with increased number of extension visits made to farms during the previous year. Similarly, a significant (p = 0.000445) increment in average peak milk yield was observed with increased uptake of dairy innovations. On the contrary, the number of dairy innovations adopted were found to decrease significantly (p = 0.0294) with farmers’ experience in dairy farming. Moreover, about 69.5 % of farmers kept less than 4 out of the 6 records assessed. Lack of interest or failure to perceive the need for farm records were the major hindrance to its adoption. The results of this study suggest a need to increase dairy extension visits as well as on-farm training in order to improve on the adoption of dairy innovations.

Key words: adoption, dairy technologies, farm characteristics, records, smallholder dairy


Production and consumption level of milk and milk products in most African countries still lags behind that of western countries. In Malawi, the per capita milk consumption is estimated to be 4.5 – 6.0 kg (DAHLD 2005; FAO 2011). In response to this low milk consumption, the government of Malawi in collaboration with other stakeholders embarked on measures to increase milk production in the country by ensuring favourable conditions for importation and dissemination of improved dairy cattle breeds and innovations to farmers. As a result, dairy farmers in Malawi are organised into groups known as Milk Bulking Groups (MBGs) around the three major cities (Blantyre, Lilongwe and Mzuzu). These groups play salient roles including the dissemination of dairy innovations, facilitating access to information, and offering easy access to market through common milk collecting and cooling units. Consequently, most farmers receive information on basic aspects of dairy husbandry such as feeding techniques, health as well as reproductive management, and farm record keeping during training sessions and on-farm extension visits to these groups. These services are provided mainly by extension personnel from the Ministry of Agriculture and Food Security and from Non-Governmental Organisations (NGOs).

According to previous reports, this initiative has resulted in an increase in the average milk production from 2 - 4 litres per cow per day for the indigenous Malawi zebu breed (Mwale et al 1999) to 5 - 15 litres of milk per cow per day in improved dairy breeds (Agyemang and Nkhonjera 1990; Chagunda et al 2006; Tebug et al 2012). Similarly, an average annual increase in milk production of 1.1% was recorded between 1999 and 2009 at the national level (FAO 2011). However, this increase still lags behind the projected annual growth need of 4.0 % in order to attain the estimated per capita milk production of 30 kg for sub-Saharan Africa countries by the year 2020 (Delgado et al 1999). Hence, more effort is needed to improve milk production in the country.

Innovations geared towards improving livestock productivity have been reported to be partly or not adopted. In Ethiopia for example, the level of technology adoption by smallholder farmers was reported as unsatisfactory (Mekonnen et al 2010). Nell and Schwalbach (2002) also observed a poor adoption of veterinary medication geared towards preventing external parasites of sheep and goats in Qwaqwa, South Africa. Previous studies show variation in the level of adoption of different dairy technologies across space and time. For example, Chagunda et al (2006) observed a positive and significant relationship between farmers’ participation in dairy recording and herd size in the Central Region of Malawi. Other authors identified gender, educational level, access to capital, farm inputs and access to market as determinants to adoption of dairy technologies in Kenya, Cameroon, and Tanzania (Baltenweck et al 2006; Nchinda and Mendi 2008; Mekonnen et al 2010). Considering the current focus of dairy management in Malawi on dairy cattle breed improvement and dissemination of dairy innovations to farmers, assessing adoption and determinants of the current dairy innovations could generate valuable information for improving dairy development initiatives in the country. Hence, this paper reports on the assessment of farm-level adoption of common dairy innovations, their association with farm and farmer’s characteristics as well as peak milk production with probable reasons for low adoption of farm records in Malawi.

Materials and methods

Farm selection

The study was carried out in the Northern Region of Malawi between December 2010 and June 2011. A two-stage cluster sampling approach was used. All MBGs constituted the primary units while individual farmers made up the secondary units. At each stage, random sampling was used. A total of 115 farms out of the 684 registered dairy farms in Mzuzu Agriculture Development Division were included in this study.

Data collection

Each participating farm was visited and face-to-face interviews with farm owners were conducted. Data were collected using a semi-structured and pre-tested questionnaire, visual on-farm observations as well as farm records. The questionnaire included information on farm and farm owner’s characteristics, number and means of acquisition of animals, training sessions attended, number of visits made to the farm by extension personnel, type of farm records and peak milk yield during the most recent lactation. Farm records assessed included daily milk production, health or veterinary treatments, breeding, milk sales and feeding records. Farmers with less than four farm records (<50 % of records included in the study) were further asked to give reasons for keeping few records on their farms. In order to avoid variation of obtained data between investigators, data were collected by the same team consisting of the principal investigator and dairy extension personnel.

For every innovation studied (n=9), dairy farmers were categorized as adopters or non-adopters at individual level. Classification of seven innovations was obtained as a choice between two alternatives (adoption or non-adoption of innovation). Uptake of milking practices and farm record keeping were classified with a cut-off point of 50% for the total number of milking practices or farm record categories studied (n=6 ).

The sum of all innovations adopted per farmer was used to categorise farmers into low, medium and high adopters at overall level (<4, 4-6, >6 innovations adopted).

Data analysis

Data obtained were analyzed using Microsoft Excel 2007 (Microsoft Corp) and R statistical software (R Development Core Team (2011)). Descriptive statistics such as means, standard errors of means (SEM) and percentages were generated. Pearson’s correlation coefficient (r) was used to measure the strength of the association between the number of innovations adopted and farm as well as farmers characteristics. A one-way analysis of variance followed by pairwise t test were used to assess the difference between mean peak milk yield and the three groups of farmers by level of adoption of dairy innovations.


Farm characteristics

A total of 74 (64.3 %) farms were headed by women. Thirty six (31.3 %) farmers acquired at least one animal (usually a heifer or a cow) using family resources while the rest of the farms acquired all their cattle through external funds in the form of loans. Ninety four (81.7 %), 19 (16.5 %) and 2 (1.7 %) farmers had attempted or completed primary, secondary and tertiary education, respectively.  Maize brand (husks of maize separated from the maize flour by sifting) was provided to animals in all farms, usually during milking. Table 1 summarises the means of some farm characteristics included in this study.

 Table 1: Mean, standard error of mean (SEM), minimum and maximum  values of some dairy farmers’ and farm characteristics (n=115)







Age of farm owner, years






Experience in dairy farming, years






Parity of Cows






Herd size






Peak milk yield, l/cow/day






Adoption of common dairy innovations studied

Description of dairy innovations considered in this study, their frequencies of adoption and rank are presented in Table 2. Overall, 49.5% of all innovations considered were adopted per farm. Stall feeding and drying of cows two months before calving were the most adopted innovations, whereas provision of protein and mineral supplements were least adopted.

Table 2:  Description, frequency, and ranking of dairy innovations included in the study




Number of farms

Number of adopters (%)




Stall feeding

stall feeding only

free or semi grazing


105 (91.3)


Dry period

two months before calving

irregular periods


90 (80.4)


Milking practices**

more than three

less than three


66 (57.4)


Sale of milk

to farmers organisation only

to farmers organisation and public


58 ( 50.4)


Stable sanitation day of farm visit

clean and dry stables floors

dirty or wet floors


51 (44.3)


Farm records on day of visit

more than three

less than three


35 (30.4)


Breeding methods

AI*** only

AI and bulls


26 (22.6)


Protein supplement

regular use

no or no regular use


23 (20.0)


Mineral supplement

regular use

no or no regular use


13 (11.3)

*Cows in three farms in the first lactation

**  Milking  practices include: (1)washing of hands with soap, (2) washing the teat before milking, (3) drying the udder after washing, (4) use of a single towel per cow, (5) use of milk salve or lubricant and (6) post milking teat dipping

***Artificial insemination

 The number of innovations adopted was positively correlated with average peak milk yield per farm (p = 0.000445), number of extension visits to the farm in the last year (p = 0.0101), but negatively correlated to farm experience (p<0.0294; Table 3). Mean peak milk yield was significantly higher (p< 0.05) in high adopters compared to the other two levels (Table 4).

Table 3: Correlation coefficients between and within farm characteristics and innovations adopted (N=115)










Farmer owners’ experience in dairy farming









Age of farm owner









Education Level









Number of farm visits









Number of cattle









Peak milk yield (litres/day)









Number of innovations adopted








*: P <0.05,  **: P <0.01


Table 4: Frequency distribution of farmers and mean peak milk yield as per their overall adoption level of dairy innovations

Adoption level

(No. of adopted innovations)

No. of farmers (%)

Peak milk yield (l/day/cow)



Low (less than 4)

42 (36.5)

11.14 a


Medium (4 to 6)

61 (53.1)

12.83 a


High (more than 6)

12 (10.4)

16.17 b


a,b means in the same column without common letters are significantly different (p <0.05)

 Reasons for low adoption of dairy farm record keeping

About  69.5% of the farmers included in the study kept less than four out of the six record categories assessed. The most frequent records were breeding records, records on extension visits  made to farms, and veterinary records (Table 5). Various reasons were given for the low adoption of farm records keeping (Table 6). Many farmers (47.5 %) had no interest or gave no reason to keep few farm records while a significant number (15.0%) did not have recording skills or no formal education.

Table 5. Description and frequency of farm records at day of farm visit (n=115)

Farm records


No. of farms (n, %)


Calving dates, breeding dates, dates of pregnancy diagnoses, heat dates

93 (80.9)

Extension visits

Date, name, purpose and comments and signature of visitor

91 (79.1)


Date, name or symptom of health problem, treatment administered

53 (46.09)

Milk production

Date, cow name or number and quantity of milk produced

46 (40%)

Milk sales

Milk delivery dates and quantity, date and quantity of milk sold on the farm

16 (13.9)


Dates, type, and quantity of feed

2 (1.73)


Table 6.  Main reasons for keeping only few farm records (n= 80)




No interest or see no benefit of keeping farm records



No clear reason



Lack of recording skills or no formal education



Recording is tiresome and boring



Busy with other activities



No recording materials (mainly books and pens)



Discouraged because of poor market



Discouraged because of poor animal health (mastitis, abortion, East Coast Fever)



Discouraged because of low milk yield



*multiple reasons were recorded




The distribution of dairy farms in the present study was in favour of women. This observation was different from the situation in the Central Region of Malawi and Dejen” district, Ethiopia (Chagunda et al 2006; Mekonnen et al 2010). The uptake and implementation of new dairy farming techniques have generally been reported to be higher in male than female headed smallholder dairy farms (Mekonnen et al 2010; Mama 2010). According to Koehler-Rollefsen (2001), women prefer low input, low output but less disease susceptible traditional breeds to improved ones  which may account for the decrease in adoption of innovations with farming experience. Furthermore, this study revealed that a higher percentage of dairy animals were acquired in the form of loans.  This reflects the presence of many NGOs in the region. The activities of these NGOs are oriented toward poverty alleviation and improvement of food security among the poorest and most vulnerable groups in communities through provision of improved dairy cattle and extension services (Goyder and Mang’anya 2009). Hence, the need to increase the motivation of farmers to adopt basic innovations in dairy farming can not be underestimated.

The results of this study revealed that stall feeding and implementation of a pre-calving dry period of two months were adopted by the majority of farmers. Most farmers also implemented more than three basic milking practices. However, more practices will be needed in the future to improve hygienic standard of milk and milk products, thereby lifting their market value in the study region. Protein and mineral supplements were rarely given. Farmers who supplemented protein to animals mainly used soy bean or commercial dairy meal while mineral supplements were in the form of commercial mineral blocks. Unavailability and high cost of these supplements were the main reasons for low adoption which agrees with results of  Banda et al (2011) and  Tebug et al (2012). The use of leguminous plants as a protein supplement was not a common practice in the study area.  However, one farmer reported providing dry Sesbania grandiflora  leaves on regular bases with a corresponding average peak milk yield of 27 litres per cow per day in his farm. Although the quantities of leguminous plants used were available at the time of the survey, Paterson et al. (1999) reported that 3 kg of fresh Calliandra calothyrsus  had the same effect on milk yield as had 1 kg of dairy meal at normal production levels. The same authors estimated that planting of about 500 trees could produce enough fodder to supplement one dairy cow for a complete lactation. Therefore, leguminous plants as a protein supplement could be promoted to complement soy bean and commercial dairy meal as a tool to increase milk production in the region.

It was shown that an increased number of on-farm visits by dairy extension workers is strongly associated with increased numbers of adopted dairy innovations. In a study to explain the diffusion of crossbred-cow technology adoption in Tanzania, Abdulai and Huffman (2005) also found that farmers’ adoption of the new technology was influenced inter alia by farmers contact with extension agents. Further, peak milk production is reported to closely related and could be used to predict to 305-day production or lactation yield in dairy cattle and buffaloes (Collier et al 1975; Banda 1998; Hamid et al 2003). Although less than half the number of farmers included in our study kept milk production records, peak milk yield in the current or previous lactation was easier to recall. However, the actual average peak milk yield could be higher since it was not uncommon for farmers to leave one udder quarter for the calf to suckle after milking is completed. The significant increment in peak milk yield with increased number of innovations adopted concurs with the results of Mekonnen et al (2010) in Ethiopia. The latter reported a significantly higher level of milk yield with higher level of adoption of dairy technologies regardless of the breed of cow owned by smallholder dairy farmers. Therefore, increasing the frequency of dairy extension visits with technical back-up would be a very valuable tool to increase adoption of dairy innovation and subsequently, milk production.

Farm records play a central role in all animal actions aimed at improving productivity, efficiency and management of cattle farming systems ( Howard and Cranfield 1995; Silver 2006). All farmers included in this study had attended training sessions on various aspect of dairy farming including farm record keeping. Amongst the various reasons for low number of records kept, lack of interest or failure to perceive the need for farm records was predominant. This finding agrees with Adesina and Baidu-Forson (1995) who confirmed the theory that farmers’ perceptions of technology characteristics significantly affect their uptake decision. Nell and Schwalbach (2002) further illustrated that medication technologies aimed at treatment of visible external parasites of sheep and goats was highly adopted as opposed to prophylactic treatment because these parasites were not visible. Learning from this experience, a need exists to explain or make the impact of dairy technologies more visible to dairy farmers.



Authors are thankful to World University Service of Canada (Malawi Office) and Veterinarians Without Boarders Canada for their financial support during data collection phase. The assistance of the staff of Mzuzu Agriculture Development Division, R B Nyirongo and farmers’ participation during data collection is also highly appreciated. Special thanks to W A Abia who provided valuable help in the manuscript preparation.


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Received 15 January 2012; Accepted 14 March 2012; Published 7 May 2012

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