The photo above is of Samuel Miringu and his family, posing with Graham Benton of LishaBora Hydroponics. The photo was taken after completion of a product trial with fodder added to his cow's diets, during which time, his milk improved to give him an additional 20% profit.
Having spent half my life growing up in Saskatchewan, a province known for its agricultural industry, I will admit that I honestly didn’t know very much about dairy farming prior to coming to Kenya. In fact, I felt like an absolute moron when I interviewed a farmer based on the milk production data I had trended and realized I didn’t even know the number of months a cow is pregnant for, an important fact to know considering its impacts to lower a cow’s milk production significantly prior to the birth! It’s 9 months, by the way.
Regardless, I felt myself a fast learner and believed I could extract enough information to make my five months in Kenya worthwhile to the farmers I met along the way. In order to understand the situation more clearly, I trended each farmer’s milk production data for the year and then subsequently interviewed them to understand causes for fluctuations. Although the farmers were diligent in keeping their monthly milk cards, I was fortunate enough to be able to pull their production data from Fresha’s database so long as the farmer was present when I requested the information. Fresha is a dairy co-operative that works with the thousands of zero-grazing dairy farmers within the Githunguri region[1,2].
I’ve given an example of what the milk production trend might look like, given one farmer’s data in Figure 1.
As evident in Figure 1, there are significant changes in total milk production throughout a given year. In particular, Samuel experienced a complete loss in milk production from January to end of April of this year, in which he and his family suffered nearly 4 months due to dry season effects and the fact that their only cow was pregnant. What small amounts of milk the cow was able to produce were consumed by the family and therefore were not recorded by Fresha’s milk tracking. You can see that prior to January, the milk production had trended down due to pregnancy impacts. At the end of April, his cow delivered and his milk production shot up. Then in June, Samuel acquired a second cow to produce milk.
During the year, Samuel changed his feeding regime. In June, he was feeding a combination of dairy meal, maize germ, bran, and pollard; however, due to availability of feeds (available for purchase through the co-operative), he slowly transitioned to feeding only dairy meal, in which each cow eventually received only 4 kg of dairy meal per day with various amounts of Napier grass and corn stalks added (total mass was unknown during the interview).
Samuel’s average milk production is taken from June, onward as it was felt that an unfair bias would be given once fodder was introduced, to overstate the impact of fodder relative to other impacts such as pregnancy and climate (for example, if the entire year were accounted for, Samuel’s average milk production would look something like this: 4.3 kg milk/day +/- 3.9 kg milk, and changing to feeding fodder alone would look to be the hero in this case with a >60% milk production increase; we know this would be a wrong interpretation of the data).
On the other end of the spectrum is Joseph, a farmer with 4 cows currently being milked, and several small calves. He is able to feed a combination of dairy meal, maize germ, and bran to his cows, in which he feeds double the total feed amount than Samuel, for a daily total of 8 kg of feed per cow with 20 kg of Napier grass and corn stalks. He also pays a local veterinarian to service his cows and on the day I arrived to consult with Joseph, the veterinarian joined me for the consultation. Horns were removed by the vet from one cow with a wire piece, and the vet then proceeded to estimate the weight of each cow through visualization alone. The vet and I then discussed the potential harmful impacts of feeding the cows fodder, including the potential for diarrhea which would then show a decrease in overall milk production, as well as arthritis (I was told this could be remedied through an injection to the cow in the order of 800 KES).
Joseph’s milk production is trended in Figure 2, below. As evident by the graph, he is able to achieve significantly higher production volumes as well as consistency relative to Samuel, likely attributed to his feeding regime, ability to afford proper healthcare for his cows, and ability to counteract seasonal effects through better water storage and purchasing power.
I was excited to see that Joseph was able to obtain over 16 kg/cow daily milk production! Whereas most farmers were somewhere between 9-10 kg/cow daily milk produced, Joseph was well above average.
Immediately, I thought my role as farmer consultant extraordinaire should simply be to guide the other farmers to do exactly as Joseph was doing. Essentially, they should increase their total mass of feed per cow and diversify their feeds accordingly.
As you should know, it is very rare that when a Westerner such as myself perceives something as easy, is it truly the case. I’ve come to realize that as a developing country, Kenyan farmers have many struggles that were outside my understanding until I truly had a chance to crunch the microeconomics of small-holder dairy farmers.
Tables 1 and 2 give a short summary of the dairy farmers I’ve tracked since we started trialing impact of fodder to the overall milk production. Note, some farmers have been omitted from this list due to missing information and the desire to show the data in as clear a fashion as possible (obviously there are limitations to any method of data collection, specifically when interviewees can forget exact timelines, for example, a cow birth or feed change).
As well, you will remark that there is only a small list of farmers given in Table 1. In LishaBora’s small and growing state, we’d love to reach out to more farmers but our production capacity is limited as are our resources to continue growing. I will very shamelessly add our GoFundMe link here, in the event someone would care to donate. Now, with fundraising aside, let’s get back to the data.
*Where the amount of Napier grass was unknown, 20 kg/day per cow was assumed. Here, Napier grass is stated but other high-cellulose containing plants can be applied including corn stalks.
**Mashisha is fermented barley taken from the brewing process and fed to cows. Its availability is highly variable as other farmers will at times wait up to 2 days for mashisha and travel long distances only to find there is none available.
*Profit given in Kenyan shillings (1 USD is approximately 100 Kenyan shillings, KES).
**Min. and max. number of cows is used to describe farmer income as the number is highly variable throughout the year due to pregnancy and/or illness (perhaps an oversimplification but important to describe nonetheless).
Results from Tables 1 and 2 indicate that the average farmer has 2 – 3 cows, and depending on the feeding regime, will profit between $4.50 – $7.00 USD/day (excluding non-feed related agricultural costs). When we consider that the average in this case is being skewed by Boniface and Joseph’s data, it is more appropriate to speak in terms of median values. The median farmer in fact has 2 – 3 cows and the profit is more accurately described as between $2.00 – $5.00 USD/day.
To draw a correlation on amount of feed used relative to production volumes, I’ve graphed the results and depicted them below in Figure 3.
First, let me acknowledge right now that I don’t know if the trend should be exponential, linear, whatever. Additionally, it would be wrong to interpret these results to mean that simply more feed is the solution to more profit, as quality of feed will play a large role (i.e. the percentage of protein, fat, carbohydrates, base minerals, relative to cellulose, etc.). Amount of water available to the cow, and other high-cellulose plants used for roughage will impact these numbers as well. In truth, there are a whole wack of influencers to total milk production.
The point is, when you compare the amount of feed to dairy cows in Kenya versus Canada, you will determine that there are several reasons why the average farmer in Kenya might produce around 9-10 kg milk/cow relative to Canadian dairy farmers who produce around 29 kg milk/cow daily[3,4]. Aside from feed, Canadian farmers have access to some of the best genetics for breeding cows. Whereas in Kenya, many farmers in the Githunguri region have now recognized the value of Friesian genetics (those big, beautiful, black and white cows!), some are still breeding with the lesser quality Guernsey and Jersey breeds[5,6]. Not only genetics, but tailoring a cow’s feed to ensure it gets the ideal amount of protein, fat, vitamins, etc. has allowed farmers in Canada to optimize milk production. In order to tailor a cow’s diet, you need to be able to analyze the inputs and adjust feed ratios accordingly. Many farmers in Canada will employ nutritionists to design a health regimen and will send samples of their crops to be analyzed for nutritional value. That, in combination with veterinarian support and consistent feeds puts Canadian dairy farmers at the forefront of the dairy industry.
It seems like a simple solution, doesn’t it? It’s not.
There are several hurdles a Kenyan farmer will have to overcome in order to bring himself into a better economic position. These hurdles are as follows:
1. Access to consistent, quality dairy feeds
2. Understanding on how to prepare for and withstand environmental impacts such as drought to limit their consequences
3. Lowered risk aversion to new opportunities
Despite these hurdles, there are systems in place that have helped farmers in the Githunguri region to sustain themselves. In particular, the large dairy co-operative, Fresha, has helped to ensure access to feeds while also providing a regular income to farmers through milk sales.
Yet, consider this scenario: as a dairy co-operative, the farmers in Githunguri are paid and subsequently buy all of their feeds on the same day. On the 10th of the month, the farmers receive their share of the money from their milk sales from the previous month, and at that same time, they buy all of their feed required for the upcoming month. The price of the milk they sell is dictated by the market (Fresha, in this case, as Fresha buys the milk to be processed). The farmers then have the remaining money after purchasing feeds to live off of for the current month.
To determine how easily a farmer producing with 4 kg/day feed concentrates can increase to 8 kg/day, consider scenario 1, below:
The feed purchasing and monthly payment regime employed by Fresha is one meant to help farmers as it forces them to plan for the month ahead and helps ensure that regardless the financial issues that pop up over that month, they will have sufficient feed to continue to produce milk. As good as it may be for sake of consistency of feed to maintain production, it does not help a farmer to improve his economic situation as 55 KES/day per cow (or 110 KES/day if we were to assume each farmer has on average 2 cows milking at any one time out of the 3) is simply not enough money to live on.
Money aside, a farmer must look to the month ahead and assess his risks that will impart on his ability to produce milk. Impact of climate, illness, food scarcity, and other costs such as education fees will all take from the farmer’s pocket. Thus, it seems a risky decision for many farmers to invest more to their cow’s belly than their own.
Consider Scenario 2, where a farmer makes a lesser investment to increase their feed from 4 kg/day to 6 kg/day per cow.
Given the above, we see that the relative cost is only 37 shillings per day per cow. Yet, that is a 38% increase in cost still. Even if it does pay off and mean that cows are able to produce more milk, that farmer must wait a month to see any of the money back. For the farmer, it’s a difficult choice to make, especially given that feed quality has long been scrutinized as not being to standard.
In a 2013 study by SNV Kenya/Netherlands Development Organization as part of the Kenya Market-led Dairy Programme (KMDP), in which numerous varieties of dairy feeds were tested for their compliance against standards set by the Kenya Bureau of Standards (KEBS), 8 out of 32 high quality dairy meals and 15 out of 46 ordinary diary meals were found to be below standard. Maize germ and wheat brans were found to be even less likely to meet compliance (in the case of maize germ, 100% were found to be below standard) . Would a farmer risk purchasing feed on the off-chance that this month, feed producers were more likely to produce lower-quality feed?
This story will be continued in the next installment blog post as Part 2.
Fresha dairy farmers cooperative and farmer interviews:
Canadian farming numbers:
Freshian genetics – KLBO:
Kenyan dairy feed quality report:
Kenyan Bureau of Standards (KEBS):