|
Field
Intervention (Public)
|
Before
Intervention at the milk collection center level: To make relevant quality parameters visible at the level of the milk collection centers, we focus on a technological intervention. In close collaboration with DDA, we install digital lactoscans at a random sample of milk collection centers. These can be used to test milk samples of individual farmers or traders that supply to the milk collection centers to establish quality of incoming milk, as well as to test samples from the milk tankers when milk is picked up by traders or processors.
To provide information to dairy farmers on the parameters and characteristics that processors are looking for and how farmers can produce milk that adheres to these standards, we use a short engaging video that demonstrates the inputs and practices that can be used to increase milk quality.
|
After
To make relevant quality parameters visible at the level of the milk collection centers, we focus on a technology bundle. In close collaboration with DDA, we install milk analyzers at a random sample of milk collection centers. These can be used to test milk samples of individual farmers or traders that supply to the milk collection centers to establish quality of incoming milk, as well as to test samples from the milk tankers when milk is picked up by traders or processors. Milk analyzers show butter fat, solid non-fats, added water, temperature of milk, protein content, and corrected lactometer coefficient. Taking a sample is non-destructive and takes about 30 to 50 seconds depending on the temperature of the milk. The milk analyzers will be delivered with clear Standard Operating Procedure advising MCCs and MCC staff will be trained. We collaborate with the DDA to set up a system to monitor the milk analyzers and its use. In particular, DDA technicians will visit treatment MCCs at set periods. We also set up a hotline that MCCs can contact in case of problems with the milk analyzers. We also make sure that, over the course of the project, equipment is adequately cleaned and calibrated. In addition to the milk analyzers, the MCC level treatment also consists of a digitized system to keep track of milk quantity and quality delivered to the MCC. To do so, we developed a custom Android application that MCCs can use to register farmers that deliver milk. For these farmers, MCC managers can then record milk deliveries, including quantities delivered and price agreed, as well as a range of quality parameters that can be read from milk analyzer, such as butter fat and protein content. The application can also provide MCC managers with simple reports, such as the average butter fat (weighted by quantities supplied) over a different period (today, yesterday, last week, last two weeks and custom data range). Reports by farmer are also possible, such that MCC managers can determine the total sum to be paid to a farmer for milk delivered in the last 14 days. The application, which is pre-installed on a Samsung galaxy tab A7 with sim-card for mobile internet, backs up data in the cloud, but is designed following an off-line first principle as some MCCs may not have coverage. Finally, for the MCC intervention, we also developed a poster to be displayed at MCCs informing farmers that the MCC now has a milk analyzer that can determine milk quality for free. The poster was designed by a local artist.
To provide information to dairy farmers on the parameters and characteristics that processors are looking for and how farmers can produce milk that adheres to these standards, we use a short engaging video that demonstrates the inputs and practices that can be used to increase milk quality. The use of video has been found to increase technology adoption in different settings, although the effectiveness also depends on a range of design attributes (Spielman et al., 2021). The ability to depict role models in videos seems important to increase both aspirations of the person targeted, as well as creating an enabling environment for adoption in that it may challenge world views and stereotypical thinking (Riley, 2019; Lecoutere et al., 2020).
To provide information to dairy farmers on the parameters and characteristics that processors are looking for and how farmers can produce milk that adheres to these standards, we use a short engaging video that demonstrates the inputs and practices that can be used to increase milk quality. To design the video based extension intervention, we first identified the top five practices and inputs that are known to raise butter fat and Solid Non Fats in milk. This was done through consultations of experts. We found the top 5 practices and inputs were: selection of breed and genetic potential, selection of grasses for high-quality forage, best practice in silage and hay making, correct mixing and dosage of feed, and feed supplements like Methionine and Lysine. To make the information intervention more actionable, we also provide farmers with some free inputs (1 kg of Chloris Gayana also known as Rhodes grass). The video will be screened a first time during baseline data collection and a second time just before the distribution of the milk analyzers. We also developed an appealing handout that summarizes some of the main points from the video using cartoons drawn by a local artist.
|
|
Field
Intervention (Hidden)
|
Before
To make relevant quality parameters visible at the level of the milk collection centers, we focus on a technological intervention. In close collaboration with DDA, we install digital lactoscans at a random sample of milk collection centers. These can be used to test milk samples of individual farmers or traders that supply to the milk collection centers to establish quality of incoming milk, as well as to test samples from the milk tankers when milk is picked up by traders or processors.
To provide information to dairy farmers on the parameters and characteristics that processors are looking for and how farmers can produce milk that adheres to these standards, we use a short engaging video that demonstrates the inputs and practices that can be used to increase milk quality. The use of video has been found to increase technology adoption in different settings, although the effectiveness also depends on a range of design attributes (Spielman et al., 2021). The ability to depict role models in videos seems important to increase both aspirations of the person targeted, as well as creating an enabling environment for adoption in that it may challenge world views and stereotypical thinking (Riley, 2019; Lecoutere et al., 2020).
To design the video based extension intervention, we first identified the top five practices and inputs that are known to raise butter fat and Solid Non Fats in milk. This was done through consultations of experts. We found the top 5 practices and inputs were: selection of breed and genetic potential, selection of grasses for high-quality forage, best practice in silage and hay making, correct mixing and dosage of feed, and feed supplements like Methionine and Lysine. To make the information intervention more actionable, we also provide farmers with some free inputs (feed supplements and/or seed for eg Napier grass).
|
After
|