How did the federal government enable the nations leap in agricultural productivity?

2.1 Overview of agriculture in Commonwealth Africa

• Of the 54 countries in Africa, 19 are members of the Commonwealth. These are Botswana, Cameroon, The Gambia, Ghana, Kenya, Lesotho, Malawi, Mauritius, Mozambique, Namibia, Nigeria, Rwanda, Seychelles, Sierra Leone, South Africa, Swaziland, Uganda, United Republic of Tanzania and Zambia

• Agriculture is the backbone of the majority of the economies in Commonwealth Africa. On average, the sector employs 42.4 per cent of the population of Commonwealth Africa, and the agriculture, forestry, and fishing value accounts for 17 per cent of their GDP.[1]The percentage contribution to GDP is however varied among different African countries ranging from below 3 per cent in Botswana and South Africa to more than 50 per cent in Chad. This points to the diversified nature of the Commonwealth African economies.[2]

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  • 2.1 Overview of agriculture in Commonwealth Africa
  • 2.2 Systemic constraints to agriculture in Commonwealth Africa
  • 2.2.1 Climate vulnerability and agriculture productivity
  • 2.2.2 Access to finance and investment
  • 2.2.3 Market, trade and supply chain
  • 2.2.4 Women and youth in agriculture
  • 2.2.4 Initiatives to promote agriculture sector in Commonwealth Africa
  • Case study: impact of the covid-19 pandemic on the agriculture sector in Commonwealth Africa
  • 2.3 State of digital agriculture in Africa
  • 2.3.1 Digital agriculture innovations in Commonwealth Africa
  • Case study: featured frontier digital agricultural solution in Sub-Saharan Africa – (Uganda)
  • Farmer impact story: Featured Frontier Digital Agricultural Solution in Sub-Saharan Africa – (Uganda)
  • In summary: how digital innovations are being leveraged to solve the systemic constraints in agriculture
  • Featured Frontier digital technologies
  • 2.3.2 Data infrastructure for digitalisation of agriculture in Africa
  • 2.3.3 Business development for digitalisation of the agriculture in Africa
  • 2.3.4 Enabling environment for digitalisation of agriculture in Africa
  • 2.4 Policy recommendations to fast-track digitalisation of agriculture in Africa
  • 2.4.1 Digital innovations
  • 2.4.2 Data infrastructure
  • 2.4.3 Business development services
  • 2.4.4 Enabling environment
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• Between 30–60 per cent of all economic production among African Commonwealth countries is attributed to agriculture, with key crops grown being mainly categorised into garden and field crops.

• Agriculture is prioritised by most African Commonwealth countries; this is evident in The Comprehensive African Agricultural Development Programme (CAADP) which is an integral part of the New Partnership for Africa’s Development (NEPAD) that highlights the importance of the sector’s contribution to GDP.[3]

• Agricultural production in Commonwealth Africa is predominantly subsistence in nature and carried out in rural areas. Rural populations account for 58 per cent of the populations in Commonwealth Africa.

2.2 Systemic constraints to agriculture in Commonwealth Africa

2.2.1 Climate vulnerability and agriculture productivity

To show the level of vulnerability to climate shocks and readiness to respond to these shocks, the ND-GAIN Matrix is used. The matrix provides a visual tool for comparing the current state of climate vulnerability and readiness of different countries. Based on the matrix illustrated below, most of the Commonwealth Africa are very vulnerable to climate changes and possess a low level of readiness to respond to the impacts. These countries have a great need for investment to improve their readiness and great urgency for adaptation action.[4]

Agriculture in Sub-Saharan Africa is mainly rain-fed and highly vulnerable to climate change and variability. The frequency and severity of climate occurrences such as drought, floods, heat and cold stress have increased with negative impacts on agriculture and food security. Additionally, increasing temperatures and incidences of precipitation will have a direct impact on agriculture productivity. In both East and Southern and West and Central Africa, wheat and rice will be the most affected groups. Sorghum on the other hand appears to be the most resilient crop to the impacts of climate change in both regions.[5]

Source: University of Notre Dame Global Adaptation Index. Country Index Technical Report. https://gain.nd.edu/our-work/country-index/matrix/ 

Source: World Meteorological Organisation, State of Climate Change in Africa Report, 2019

2.2.2 Access to finance and investment

The agriculture sector in Africa is under-financed. The general observation is that the large portion of the financing needed for smallholder agriculture is unmet.Only 4 per cent of private sector credit is allocated to the sector.[6] This is despite the fact that the sector is a big contributor to the GDP (as compared to other regions) and largest employer of most of Africa’s economies. Below are the main factors that hinder financing to the agricultural sector.

Factors that hinder financing to the agriculture sector

• Smallholders lack proper records because they operate informally and on a small scale. The majority of the farmers on the African continent are smallholders operating at a subsistence level. Due to this, they possess informality characteristics that hinder them from attracting financing and investing. The trend in the African continent is geared towards financing and investing in businesses that operate formally, that is to say, have governing rules, structures and paperwork in place. Smallholders, SMEs and traders in the agricultural sector are largely in the informal sector and providers of finance do not view them as attractive for investor capital. Additionally, the lack of quality data, records and statistics on farming in developing countries including those in Africa makes an assessment of creditworthiness challenging for financial providers.
• Smallholder-level production is characterised by production risks that are linked to natural hazards such as droughts, floods, pests, diseases as well as volatility in commodity prices. The preference for financiers is to work with more predictable sectors.
• Although financing may be available, products may not be suitable for all types of agricultural activities. These activities have divergent needs with respect to amounts, risks and timing for disbursements. Agricultural value chains are unique, and financial products do not always respond to the risks and nuances within a given value chain. Within commercial banks, there is more support for structured and tight value chains (structures, processes and actors are known) in comparison to value chains that possess little to no structure.
• Smallholders lack the physical assets to harness as a guarantee/collateral for financing. This could be twofold: (1) the farmer lacks documentation for the land to offer as a loan guarantee or (2) the value of the land may be too low by virtue of the fact that they mainly live in rural areas or volatile in nature.

Below is a summary of the main sources through which smallholders access financing.

• In Africa, smallholders generally have limited access to financing. Informal sources and channels are the commonest ways through which financing is obtained. Smallholder communities rely on revolving-fund structures and community-based groups to access financing. However, the capital base for these structures is limited, which in turn limits the capital each smallholder is able to access.
• Blended finance models are being used to de-risk lending to the sector. This refers to the use of development finance and philanthropic funds to mobilise private capital flows for projects the private sector would usually shun. A key limitation with this model, from the experience of Africa, is that smallholders do not always qualify for these schemes. This is because the financial institutions that partner with development partners use their internal and typically commercial-driven criteria to assess loan applications, and based on these, smallholders are usually found ineligible.
• Internal value chain financing models are being used to reach smallholders. Internal value chain financing takes place between participants along the value chain based on their relationships. This usually takes the form of actors such as processors and aggregators financing smallholders (who could be part of their network of out-growers) with inputs such as seeds and fertilisers. Smallholders typically pay upon harvest and sale of produce.

Beyond smallholder farmers, other actors such as processors and Micro Small and Medium Enterprises (MSMEs) operating in the agriculture value chain also face financing difficulties.For MSMEs such as input dealers and traders, factors that limit them are not very different from those limiting smallholders. Just like smallholders, they neither keep records nor have the governance structures that are desired by providers of finance. For example, for MSMEs dealing in aggregation businesses, while trade finance products exist in the market and are available to agriculture traders, the products are under-utilised mainly because these companies are not formal and do not meet the requirements of commercial banks. In the case of larger processors and bigger businesses, though commercial banks are more willing to lend to them, the high cost of credit is a big deterrent from accessing finance.

2.2.3 Market, trade and supply chain

Smallholders have low bargaining power because they tend to access markets individually rather than collectively

Collective bulking is important because market information alone is not enough. In spite of knowledge about pricing and markets, farmers face other challenges such as lack of means to transport their commodities to markets. Though some farmer groups/cooperatives bulk, they are challenged by the fact that farmers are not always willing to wait for prolonged periods for produce to be sold at a favourable price. Access to affordable credit for farmers as they wait out the seasonal fluctuation of prices of agricultural produce is critical. Cooperatives also have a great need for working capital financing to purchase commodities from farmers at the time of bulking.

Poor post-harvest handling practices limits the marketability of agricultural produce

Smallholder-level post-harvest handling is characterised by the following:

• Poor storage techniques that emanate from the fact that it is costly to not only set up but also maintain product standards in storage.
• Lack of post-harvest handling equipment such as refrigerators, solar dryers and tarpaulins which lead to poor quality control.
• Limited capacity and resources to conduct value addition.

Poor infrastructure particularly the road network to markets is a challenge for smallholder farmers that are predominantly based in rural areas

The situation is worst in African countries where roads become almost impassable during the rainy season. Farmers that have diversified livelihoods (better income standing) can access better markets because they can use investments or extra resources to transport to better markets

Limited access to market information

Linked to access to the market is the access to information on extension, inputs and advisory services. There is currently information asymmetry. That is, farmers are not always able to access information about possible off-takers and markets. When farmers have timely and reliable information at the current and projected trends in the market, they are able to wait for better prices in the market and even make informed discussions about the length of the period and cost of storage of agricultural produce

2.2.4 Women and youth in agriculture

Agriculture is a critical sector for women in Africa; 43 per cent of employed women in the Commonwealth countries in Africa are employed in the agriculture sector. Within the agriculture sector, women engage in primary production activities such as tending family land and production of food crops. There is limited access to land for women in Commonwealth Africa. Only 2.38 per cent of women in 11 of the 19 African countries that are members of the Commonwealth own land either alone or jointly. Broadly speaking, women have less access to finance and financial resources than men because the primary form of collateral that is required by financial institutions is land, and yet ownership among women is very low.

In rural Sub-Saharan Africa, the youth typically engage in the same agricultural activities as their parents.The nature of their contribution is through the provision of labour on farms. Some youth also rent land from parents and relatives to grow their own crops. A common theme from key informant interviews is that young people are not necessarily interested in agriculture. They would rather partake in informal trade where earnings are more frequent and regular. When employed in agriculture, their preference is to engage in off-farm activities related to agriculture as well as other sectors such as service and trade which have shorter cash conversion cycles than the traditional growing of crops or rearing of animals.

Table 2.1: Proportion of women in agriculture

Source: Most recent estimates from the World Bank Indicator Database.
*Where N/A is used, data is not available.

2.2.4 Initiatives to promote agriculture sector in Commonwealth Africa

Set-up of special agro-economic zones: Most countries have identified regions of high agricultural potential as targets for streamlined agricultural investment. This has been followed by the set-up of specialised agro-economic zones based on output potential. These zones are hotspots for attracting investors with relaxed tax regulations and improved infrastructure while also making farming more productive for the smallholder farmer.

By setting up special economic zones, there would be an increased investment into the sector in a particular area. This would trickle down into increased access to markets for farmers.

Incentive packages to attract investors: Private sector funding is needed to make advances in infrastructural development and fast-track agricultural mechanisation and commercialisation of the sector. Putting in place incentives that attract investors has the potential to increase growth in the sector, create market for smallholders and even provide an avenue through which smallholders are able to access better-quality inputs. This initiative is cross-cutting in solving several of the systemic constraints.

Case study: impact of the covid-19 pandemic on the agriculture sector in Commonwealth Africa

Impact of the COVID-19 Pandemic

• Price volatility: The outbreak of COVID-19 in the region caused sudden price hikes of food commodities. This was partially a result of panic-buying by consumers who were uncertain about the impact that the pandemic would have on the prices of food crops.[8]
• Reduction in demand: Government-imposed lockdown restrictions left a significant proportion of the population out of employment with no regular sources of income. Limited disposable income forced consumers to significantly cut expenditure on all items. For the food sector, this resulted in decreased purchases with most households prioritising expenditure on only essential food items.
• Disruptions to food supply chains: Restrictions on travel in-country and across borders created heavy queues across border points for trucks transporting among others, agricultural produce, agro-inputs, etc. Several countries also set up mandatory testing locations at border crossings which created delays for truck drivers and other providers of cargo logistics services. This coupled with freight disruptions in major agro-exporting countries such as China resulted in price fluctuations for agro-inputs and products.
• Limited mobility of extension service providers: In a survey conducted by the Sasakawa Africa Association on 433 key actors in African agriculture,[9] several farmers reported the inability of agricultural extension service providers in accessing farms to provide needed support.

Responses in light of COVID-19 Outbreak

Surge in e-commerce Marketplaces

Despite the negative impacts caused by the novel COVID-19, it has accelerated digital transformations in different African countries. Some of such interventions in Commonwealth African countries include the following:

• In Uganda, United Nations Capital Development Fund (UNCDF) and SafeBoda Uganda announced a partnership to provide an e-commerce platform aimed at initially connecting 800 market vendors to households in need of market supplies via the SafeBoda transportation network in Uganda.[10] SafeBoda is a ride-hailing mobile application that is present in Uganda, Kenya and Nigeria. One of the core offerings of the platform is an e-commerce platform that connects MSMEs to consumers.
• The United Nations Development Program (UNDP) and JUMIA Uganda partnered to link market vendors with consumers online.[11]

Government policy interventions

• Farming activities were allowed to go on during the lockdown in countries such as South Africa, Uganda and Kenya among others.
• In March 2020, the Nigerian Government with the support of research institutes led by the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) launched the Seed Support Initiative[12] to supply farmers with improved seeds such as sorghum, pearl millet, cowpea and rice in a bid to tackle the impact of the pandemic on the country’s agricultural system.
• The Central Bank in Kenya issued policies that required mobile money providers to waive transactional charges on transactions less than $10 which account for 80 per cent of the country’s mobile money transactions. This was done to facilitate and promote e-commerce platforms and mobile payment options following the outbreak.[13] This helped promote e-commerce agricultural payments during the pandemic.

2.3 State of digital agriculture in Africa

2.3.1 Digital agriculture innovations in Commonwealth Africa

Use cases of digital agriculture solutions in Commonwealth Africa

• Digital agriculture solutions in Commonwealth Africa predominantly provide market linkages (52 per cent) and crop-based pre advisory (60 per cent) services.[14]
• The digital solution mapping reveals that despite the region having significant logistical challenges particularly the transportation and storage of agricultural inputs and produce,[15] very few of the mapped digital solutions in this region were found to have a logistics and supply chain solution in their value proposition.
• From the systemic constraints affecting agriculture, there is a gap in the availability of solutions providing or related to financial access and solutions (only 26 per cent of mapped solutions in Commonwealth Africa) provide financial access and insurance. Part of the reason smallholders find it hard to access financing is the lack of attractive collateral options. Land is the primary form of collateral, and yet less than 20 per cent of the land in sub-Saharan Africa is formally registered.[16]Due to this gap, there is a need for solutions that provide alternative credit scoring.

Characteristics of sampled digital agriculture solutions in Africa

• More solutions focus on the crop than the livestock sector. Of the assessed 140 solutions, 60 per cent had a crop-based pre-harvest advisory component, while only 6 per cent had an animal-based pre-harvest advisory component.
• Most of the solutions on the market come in the form of mobile applications. For the majority of the assessed solutions, mobile applications were included in their delivery means. Only 8 per cent of assessed solutions used USSD as a primary delivery medium.
• Along the agriculture value chain, most solutions are targeted at farmers as opposed to other actors in the value chain like traders, aggregators, input dealers and processors. The mapping exercise, most solutions are developed and targeted at actors at the production level of the value chain. This could be explained by the development actors’ push to close the gap on farmer data, knowledge and service delivery at the farmer level.
• Digital solutions in Commonwealth Africa are predominantly funded by the private sector. Sixty-six per cent of the solutions are pioneered by private entities, 29 per cent by Governments and the remaining 5 per cent by partnerships between development actors and private entities. It should however be noted that many digital solutions, though not directly run by development actors, are in many cases supported by development agencies with initial funding and technical support. The role of the Government entities in the development and deployment of digital agricultural solutions may need to be greatly enhanced. None of the sampled 140 digital agricultural solutions in the region used data from state-run repositories like national farmers’ registries and Government provided soil and weather data. The critical lesson to note is the transformative potential that data collected and managed by state agencies can have on the development and provision of digital solutions
• Most of the solutions in Commonwealth Africa have two or less service offerings. Sixty per cent of the assessed 140 solutions have two service offerings or less, while the remaining 40 per cent have bundled product offerings (more than two offerings in one).[17]

Case study: featured frontier digital agricultural solution in Sub-Saharan Africa – (Uganda)

M-omulimsa[18] is an agricultural solutions provider that leverages a wide array of technologies, from mobile applications to a USSD service to provide a wide variety of digital solutions that among others include provision of index-based agricultural solutions to farmers, linking farmers to extension agents, connecting farmers to inputs providers and credit from a wide variety of lending entities.[19]

Value proposition summary

• USSD solution for farmers without internet connections.
• The solution offers an android application for android devices.
• The solution provides mobile-based extension services.
• The solution provides lending and alternative finance options for smallholder farmers in Uganda.

Product offering details

General outreach – M-Omulimisa is an agriculture technology company that leverages mobile phone technology to improve the livelihoods of smallholder farmers in Uganda. Although its service is available to all farmers across the country, the solution is mainly focused on Northern districts of; Apac, Lira, Kole, Oyam, Alebtong, Dokolo, Agago and Nwoya. The solution offers a variety of ICT-based agriculture services including e-extension, agriculture insurance, agricultural loans and inputs distribution to support smallholder farmers to improve their access to information and services needed to sustainably increase productivity and income.

Response to climate variability and the national extension services gap – Uganda like many Sub-Saharan African countries has been greatly impacted by climate change. By 2016,[20]Uganda had been ranked by the International Institute for Sustainable Development in the 20 most vulnerable to the adverse effects of climate change. The M-Omulimsa digital solution provides a USSD-based digital solution in the region that facilities provide access to weather index-based crop insurance to more than 13,314 registered crop farmers. The food and agriculture organisation recommends a farmer extension officer ratio of one to five hundred farmers. It should however be noted that Uganda lags critically behind this benchmark with an estimated 5,000 farmers per subcounty extension worker.[21] In addition, with an estimated adult illiteracy rate of 30 per cent, the role of extension works in the region cannot be over-emphasised. M-Omulimsa steps into the extension services gap in the country by providing a USSD application to link rural farmers to the country to Government provided extension works that would others be unable to reach them.

Smallholder farmer impact – Since its establishment in 2016, M-Omulimisa has gone on to register over 20,000 farmers from 23 different districts in Uganda. The service has also received and responded to more than 12,000 questions in ten different local languages across the country. The service also has 325 registered extension officers but only about 100 are actively engaged in responding to farmers’ questions. The service has also commenced the distribution of inputs to farmers, by forming partnerships with seed distribution companies for example the NALWEYO SEED Company (NASECO) from which farmers can buy directly through the platform. This provides farmers with the opportunity to conveniently access affordable high-quality agricultural inputs.

Farmer impact story: Featured Frontier Digital Agricultural Solution in Sub-Saharan Africa – (Uganda)

For many years, Emily Akallu’s [22] family suffered the harsh and frequent realities of dependence on rain-fed agriculture, as the weather patterns become less predictable due to the adverse effects of climate change. Her lengthy experience in the growing of soybeans in her home district of Alebtong did little to improve her fortunes arising mostly from the growing of low-yielding varieties, lack of capital for expansion among other financing constraints faced by farmers. Since March 2019, the private company M-Omulimisa has developed innovative mobile-phone-based solutions that help farmers like Emily in rural northern Uganda access favorably priced inputs such as seeds and fertiliser. It has also provided a credit facility for the farmers to enable them to access farm inputs on credit at the start of the cropping season.

The advent of the mobile phone and the subsequent other innovations have brightened the chances of the rural farmers like Emily and indeed millions of people in Northern Uganda by enabling them to access critical inputs into their gardens and repay at the end of the cropping season. Now, M-Omulimisa, one of the numerable ICT-driven start-ups, is behind the sense of relief among several rural farmers in Alebtong. The company uses an application called M-Omulimisa and village agents to work with farmers and help them procure affordable high-quality inputs. The farmers can also access a bank of frequently asked questions that have been answered by state-provided government extension agents that offer solutions to farmer queries. Akallu praised the innovation noting that the lending option allows them to invest without having cash. “I have received free seeds (literally) and am ready to plant, my family is happy,” Akallu excitedly said. Studies by the Bank of Uganda and other financing entities in Uganda have concluded that access to finance especially by smallholder farmers is a critical hindrance to the adoption of commercial farming by millions of Ugandan households.

Hence, the slow migration of smallholder farmers from subsistence agriculture to more commercial farming practices. With the majority of Ugandan farmers still shackled to rain-fed subsistence farming. The importance of access to trained extension agents for smallholder farmers like Akallu becomes even more important. The M-Omulimisa[23] platform, with support from the Sasakawa Africa Association (SAA) and the Japanese Government, has also been a vital link for farmers to extension agents in the wake of the COVID-19 pandemic. According to Roseline Nyamutale, the country manager of Sasakawa Global, extension services provided by e-extension platforms, like M-Omulimisa, that have a team of qualified extension agents, who will share vital farming knowledge through question-and-answer interactions with farmers help bridge the extension gap many farmers are facing in the wake of Government instituted travel restrictions to reduce the spread of the COVID-19 pandemics in the country.

The extension services offered access to look at all challenges in the agriculture value chain. But the focus will be mainly on the promotion of food security and nutrition crops, such as iron-rich beans, Vitamin A-rich sweet potatoes, and vegetables so that farmers can not only be food-secure but also produce nutritious food for their households.

Digital technologies (smart technologies) in Commonwealth Africa

The application of smart farming techniques and methods is still low in Africa. This section highlights some notable cases of the application of various smart farming methods in the region.

1. Deployment of the AI assistant plant detection algorithm Nuru. Nuru is an Artificially Intelligent crop disease detection algorithm that has been developed with the UN FAO, CGIAR, and other publicly funded institutions.[24] As an AI-enabled assistant, Nuru has learned to diagnose multiple diseases in Cassava, fall armyworm infections in African maize, potato disease, and wheat disease. It is also diagnosing spotted lanternfly pests.
   The Nuru project expects to radically transform pest and disease monitoring by using artificial intelligence (AI), advanced sensor technology, and crowdsourcing to connect the global agricultural community to smallholders. It aims to increase the effectiveness of farm-level advice by leveraging democratisation of AI, miniaturisation of technology allowing affordable deployment, and the development of massive communication and money exchange platforms. These platforms, including M-Pesa, allow rural extension to scale as a viable economic model enabling last-mile delivery in local languages.
2. Soil property detection with the use of machine learning. In many countries in the region, soil attribute mapping for farmers has not been done at a national level largely due to the cost and technical complexity involved. New digital images/maps of farmland have been developed by the African Soil Information Service that have the ability to tell precisely what is required to support better decision-making. Additionally, data about distribution of soil properties have been available since 2014. The maps are maintained by the Africa Soil Information Service (AfSIS), with input from scientists from International Centre for Research in Agroforestry (ICRAF).
3. Unmanned aerial vehicles. Aerobotics, a technology company based in Africa, has developed drones with the following use cases:
   • The farm uses drones for aerial monitoring of orchards in South Africa. The farm also provides service offerings to crop insurance providers to enable the determine premiums and also access crop damages before effecting insurance proceeds.[25]
   • The solution uses custom software to develop diagnostic maps created by processing the captured images during flight.
   • The solution also enables the interpretation of the data to facilitate decision-making. This is through activities like measuring the health of the vegetation on the farms to make accurate inferences regarding the health of farmer crops.
4. Crop disease detection with the aid of AI models. In Ghana, one of the notable uses of artificial intelligence models has been the crop disease detection algorithm used by the Okuafo AI foundation.[26] The Okuafo AI deployed using an Android application to detect pest infections and disease on crops. On the detection of crop illness, the application recommends scientifically proven courses of action with the use of an animated video. It also provides an option for farmers to contact regional crop authorities and report on the incidence of crop disease and pest outreaches.
5. Livestock management with radio frequency chips. The Jaguza farm management operating platform developed in Uganda supports the management and visualisation of farm management data, displays animal information and also supports working routines to record all the important events that happen throughout the day as they happen.[27] Some advantages that it offers include:
   • An insemination, heat, vaccination, pregnancy check, or health treatment schedule that is well documented and can be used to accurately record every action in real time.
   • Farmers can track the movement and health of animals using radio frequency chips.
   • The solution also leverages the open-source library by google called tensor flow that facilitates the generation of automated recommendations for farm actions.

In summary: how digital innovations are being leveraged to solve the systemic constraints in agriculture

Use of index-based insurance in African Countries in the Commonwealth Countries

Even though an estimated 60 per cent of the Sub-Saharan Africa population are smallholder farmers, less than 3 per cent of these farmers have crop insurance schemes. There are private sector initiatives that provide insurance solutions to smallholders. One notable example is the Credit Suisse backed agritech start-up Pula.[28] Pula is an agricultural insurance and technology company that designs and delivers innovative agricultural insurance and digital products to help smallholder farmers endure yield risks, improve their farming practices, and bolster their incomes over time. Pula’s innovative tech-based business model for insurance is said to be helping millions of smallholder farmers manage their risks while boosting productivity and entrepreneurial thinking. To date, Pula claims to have insured 3.4 million farmers across Africa (Nigeria, Rwanda, Uganda and Tanzania).

In the livestock value chains, notable public–private partnerships have also occurred in some Commonwealth countries to provide agricultural index-based insurance to pastoralists. A Kenyan example to this regard is the Kenya Livestock Insurance Program (KLIP). Recognising the need to strengthen the ability and quality of drought management in Kenya, in 2014, the Ministry of Agriculture, Livestock, and Fisheries – with support from the International Livestock Research Institute (ILRI) and the World Bank Group launched a livestock insurance scheme targeting vulnerable pastoralists.[29] The Kenya Livestock Insurance Program (KLIP) targets vulnerable pastoralists whose livelihoods are entirely dependent on livestock. KLIP has been developed as a public-private partnership where the Government creates the enabling conditions, including premium support, and the insurance companies focus on service delivery, including insurance product development and paying claims to the insured beneficiaries.

The key feature of the novel insurance scheme is the use of satellite data to generate an index for grazing conditions so that payments are triggered early in the drought when conditions fall below a certain critical level. The index-based system also ensures timely payouts to pastoralists, which help herders keep more livestock alive. To date, the Government of Kenya through KLIP has insured an estimated 30,000 vulnerable households with total premiums of US$5 million, and insurance companies have paid claims amounting to US$7.2 million to about 100,000 people.

Snapshot on how digital is being used to enhance agricultural productivity

Current digital agriculture solutions that are designed to increase the productivity of smallholders focus on the provision of advisory service. Other emerging solutions focus on mechanisation and access to quality inputs. Examples of solutions tackling agricultural productivity are Hello Tractor mobile app[30] (for farmers to rent tractors) and Tesitoo[31] (in the Gambia for farmers to access inputs).

Snapshot on how digital is being used to tackle climate change

Digital solutions that have been designed to respond to the effects of climate mainly provide weather forecast solutions and weather forecast advisory. Examples in this space include Agricloud[32] providing targeted weather forecast in South Africa and M-Omulimisa[33]USSD solution in Uganda providing farmers remote access to extension agents.

Snapshot on how digital is being used to solve market, trade and supply chain constraints

Digital solutions solving the markets trade and supply chain issues are mainly focused on enabling farmers aggregate their crop produce, and in some cases also offer digital product traceability solutions. Examples in this space are Maziwa plus[34] offering a milk bulking solution for farmers in Kenya, and Cropchain mobile app[35] offering an integrated agricultural supply chain management platform that allows organisations to manage everything in the agricultural supply chain from out-grower schemes, logistics, traceability to digital trading, quality assurance and data analytics.

Snapshot on how digital is being used to solve financing and investment constraints in agriculture

Solutions offered include digital lending platforms that connect farmers to a wide range of lenders. Some solutions provide alternative credit scoring methods for farmers. Examples of solutions include the FarmDrive[36] mobile application Kenya that provides alternative credit scoring for farmers and Agropay[37] in Ghana providing alternative financing sources in Ghana.

Snapshot on how digital is being used to facilitate youth involvement in agriculture

With the increasingly youthful demographic in the region, there is a significant void of mobile applications with youth engagement as a focus in the digital agriculture space. Although solutions do not directly target the youth as a beneficiary category, many solution providers are keen on youth participation. The youth are typically used as on-ground agents that profile farmers. They therefore provide an interface between farmers and digital solution use. This arises because the youth are more tech-savvy and are likely to have knowledge regarding the effective use of mobile technologies.

Snapshot on how digital is being used to facilitate women involvement in agriculture

Despite the growing consensus of a gender digital divide in the region, limited mobile applications and initiatives are primarily focused on dealing with the inclusivity question. One of the few initiatives is in the form of some financial institutions requiring spousal consent before a loan is given against any form of family collateral. Some applications also require next of kin details to be provided at registration.[38]

Featured Frontier digital technologies

1. KaiOS

As revealed by the region's solutions mapping, many of the assessed digital solutions use mobile applications as their primary delivery medium. With an estimated smartphone penetration rate of about 50 per cent of all mobile connection in 2020,[39] several potential users of digital solutions in Kenya are excluded simply by the fact that they cannot afford a smartphone. KaiOS provides a bridge between a feature phone and smartphone, by enabling the development of devices that are not as expensive as the typical smartphones but are not as a feature limited as ordinary feature phones.

KaiOS is a mobile operating system, based on Linux, for keypad feature phones. The primary features of KaiOS are support for 4G LTE E, VoLTE, GPS and Wi-Fi; with HTML5-based apps and longer battery life to non-touchscreen devices with optimised user interface, less memory and energy consumption. It also features over-the-air updates.[40] A dedicated app marketplace (KaiStore) enables users to download mobile applications, update current applications, and browse available alternatives. Some services are preloaded as HTML5 applications, including Facebook and YouTube. As of 1 April 2020, there were more than 500 apps in the KaiStore. The mobile operating system is comparatively lightweight on hardware resource usage and can run on devices with just 256 megabytes (MB) of memory. This mobile operating system provides for the development of solutions that do not have the feature limitations of feature phones, while not being as cost-prohibitive as smartphones. Currently, KaiOS supports 4G connections and is projected to support 5G by 2022 at a cost of less than $15 per device. This operating system in effect greatly lowers the barriers of mobile connectivity by enhancing affordability.[41]

2. The Huawei rural star

Sixty-seven per cent of the world's population that are not covered by mobile broadband are in Africa. One of the main barriers of mobile broadband coverage in the region is the high cost of establishing telecommunication masts. The Huawei rural star provides a means to relower this cost. The Huawei Rural star is a comprehensive rural mobile broadband solution supporting 2G, 3G and 4G connectivity and with non-line-of-sight wireless technology that allows multi-hop to backhaul. Its lightweight design uses poles nine to 24 meters tall instead of complex 40-meter towers. This significantly reduces operator capital and Operating expenditure.

The rural star can also be deployed without the need for concrete foundations, further reducing roll-out cost and complexity, and has been designed to function using solar power. The rural star has been successfully deployed in several rural and remote locations, some of which have been profiled in previous GSMA case studies. This includes deployment in partnership with MTN in Ghana and with Safaricom in Kenya. It is a strong and increasingly proven solution for delivering mobile broadband to those hardest to reach. The rural star has been successfully deployed in several rural and remote locations, for example, in Ghana[42] by the mobile network operator (MNO) – MTN and in Kenya[43]by the mobile network operator Safaricom. The device effectivity lowers the establishment costs of mobile broadband networks, hence effectively enabling mobile network operators to build out their networks much faster and in a more cost-effective manner.

3. Gen Cell 4

System cell site power is one of the most critical issues facing rural connectivity. Without a dependable power supply solution, cell sites cannot operate. Half of Sub-Saharan Africa and a third of Southeast Asia do not have access to power, and in some cases, the lack of a cost-effective electricity supply (or energy storage option) is the main barrier to expanding the rural network coverage. Rural sites are rarely connected to reliable on-grid power supplies, relying instead on two expensive industrial-grade diesel generators: often one for day-to-day operation and another for backup.[44] These require frequent and ongoing maintenance, including monthly visits for refuelling.

The diesel fuel powering the cell site can be contaminated by dirt or water and is often stolen, requiring some sites to provide security guards and infrastructure to protect supplies. Transporting diesel to more remote sites can also be challenging and expensive due to the remoteness of rural cell tower sites. In many cases, these costs can make rural infrastructure roll-out prohibitively expensive and, in the long run, ultimately drive up the cost of mobile broadband connections for rural users. By effectively reducing reliance on electricity grids, the GenCell lowers the operating expenses of the mobile network operators enabling them to lower the cost of mobile broadband connections for rural users. In addition, its faculties greater network coverage and roll out of the networks beyond areas not covered by the electricity grid and hence enables the narrowing of the broadband coverage gap, especially in rural areas.

2.3.2 Data infrastructure for digitalisation of agriculture in Africa

Digital agriculture data infrastructure consists of “data for content” and “data on users (digital identities)”. The “data content” refers to data sets and data products derived from reliable soil maps, agronomic, weather, farm and market data. “Digital identities” on the other hand refer to data on users such as farmers, traders, consumers, research networks, extension networks, financial institutions, cooperatives and other actors in the agriculture value chain.

Data for content

Table 2.2:Content data for digital solutions

Data on users

Primary identifiers for farmers: The presence of state-issued unique identifiers for farmers provides a critical first step in building of the data rails on which future customised data products can run. Across Africa, 69 per cent of adults have at least one primary identifier document. However, the spread of identifiers is not uniform with Southern Africa having as high as 91 per cent, and Central Africa and West Africa having approximately at 62 per cent.[48]

Primary identifiers for farmer land parcels: The next most critical set of unique identifiers are land-related identifiers. Most land in Sub-Saharan Africa has no registration, that is to say, ownership or user rights are known or documented. This finding is also underpinned by the World Bank[49] that identifies that only 10 per cent of Sub-Saharan Africa’s rural land is formally registered. The remaining 90 per cent of the land remains largely undocumented and informally administered.

2.3.3 Business development for digitalisation of the agriculture in Africa

Emerging pricing models for digital agriculture solutions on the market

The following pricing models are currently being explored by providers on the market

1. Installment payments: This involves farmers paying for digital solutions, through periodic (daily or monthly) installments rather than lumpsum payments. A prime example is the USSD crop insurance solution provided by Ensibuuko in Uganda that allows farmers to pay for seasonal insurance in several periodic installments in amounts that are easier.[50]
2. Subscription models: This involves farmers having to pay subscription fees to access certain services. From the experience of development actors working with solution providers, this model is harder to sustain because farmers have to incur many transaction costs. The model works best in more established markets where agriculture is commercially driven. An example of this type of digital solution is the Agri Bora digital solution in Kenya, which provides farm remote sensing solutions for farmers at a fee.[51]
3. Outright transaction fees are particularly for digital marketplaces. In this case, digital solutions are paid for either by individual farmers or by Farmer Cooperatives. An example in this case includes the Maziwa plus application for dairy farmers in Kenya where cooperatives make payments for their members to use the digital solution.[52]
4. Commission models – Developers earn commissions from either selling agricultural inputs to farmers or enabling farmers to sell their products to consumers or agricultural produce aggregators. Examples in this case include The AgroMarket Day mobile application that connect farmers to input dealers and earns a commission from each transaction processed.[53]

2.3.4 Enabling environment for digitalisation of agriculture in Africa

Technology-related enablers

1. Access to telephone (mobile devices) that can be used to access internet and non-internet-based solutions

Table 2.3: Mobile cellular subscriptions (per 100 people)

Source: Author computations from the World Bank indicator database.[54]

For the most part, mobile devices can reach and be sold even to the most remote of locations in Africa. The challenge is the ability of smallholders to afford and use functional mobile devices. In addition, mobile devices come with a cluster of implied expenses like charging and frequent purchase of broadband connectivity. For those who have access, another challenge lies with the quality of devices. That is, the quality of devices that end up in the hands of smallholders is not always of the best. A limitation of the devices that smallholders own is that they are not always compatible with applications that provide solutions targeting them. That is to say, most smallholders can only afford feature phones, yet most digital solutions targeting smallholders are distributed as web and mobile applications.

Additionally, the affordability of 4G-enabled devices remains a key barrier to smartphone adoption. In many countries in SSA, taxes on mobile ownership alone constitute up to 7 per cent of income for the bottom 20 per cent of the earners.[55] This effectively means that many of the low-income earners are kept out of the region’s thriving internet economy. This percent value due to sector- specific taxes makes the initial cost of mobile device acquisition and continual use prohibitively high.

2. Penetration of smartphone devices: The GSMA[56] estimates that smartphone adoption continues to rise rapidly in the region, reaching 50 per cent of total connections in 2020, as cheaper devices have become available. Alternative smartphone financing models are also gaining traction. In some cases, these models are facilitated by the partnerships between mobile network operators like Safaricom and multinational conglomerates like Google, allowing low-income consumers to pay for 4G devices in daily installments. It is further estimated that over the next 5 years, the number of smartphone connections in Sub-Saharan Africa will almost double to reach 678 million by the end of 2025, with an estimated adoption rate of 65 per cent. Penetration of smartphones enhances the consumption of advanced digital agriculture solutions, for example, those that involve the streaming of multimedia.

3. Network coverage: Mobile network coverage is very important for the adoption of digital technologies. Without network connectivity, internet and non-internet-based solutions are unable to work. In Africa, mobile network providers typically quote high proportions of coverage in a country. However, the quoted coverage is for the part of the country that is thought to be potential viable markets. Areas that are very rural and remote typically lack coverage, and where available, the network connection is very poor.[57]

4. Internet and related infrastructure that enables access to digital solutions and technologies: Compared to other regions, Commonwealth Africa has low proportions of people using the internet, that is, 30 per cent versus 43 per cent in the Pacific, 50 per cent in Asia, 64 per cent in Caribbean and Americas, and 88 per cent in Europe. Within Commonwealth Africa, the usage of the internet varies from a low of 7 per cent in Nigeria to 64 per cent in Mauritius and 59 per cent in Seychelles.[58]

Table 2.4: Individuals using the internet (% of the population)

Part of the reason for the low usage of the internet in Commonwealth Africa is the high cost of the internet. The Alliance for Affordable Internet defines affordable mobile data as the kind that costs not more than 2 per cent of a consumer's monthly income.[59] Most people living in Commonwealth African countries are charged an average of 7.1 per cent of their monthly salary for a gigabyte (GB) of mobile data. This is more than 3.5 times the affordable threshold.[60] This could hence explain the paradox that a region with a 75 per cent

population living in areas covered by mobile broadband only has less than 30 per cent of the mobile subscribers with internet connections.

As shown below, the average cost of internet in Commonwealth Africa is comparatively higher than all other regions of the Commonwealth.

Non-technology-related enablers for digitalisation in Africa

1. Youthful regional demography: Youthful demographic brackets are the largest numbers of early technology adopters. The United Nations estimates that Sub-Saharan Africa has the largest growing youth population in the world. In the last couple of decades, the youth population in the region has grown by over 70, is expected to grow by over 17 per cent in the next 5 years and nearly double by 2050.

2. Changing education levels of the farming population: 52 Per cent of Africa’s total workforce is expected to have at least a secondary education by 2030 (versus 36 per cent in 2010).[62]This matters because the educated population is more likely to have the digital literacy skills to make effective use of digital agricultural solutions. Literate farmers are more likely to be effectively used hand-held internet appliances, read device user manuals and install plant data sensors correctly in the field. Noteworthy is the fact that the inability to read and write does not inhibit mobile phone ownership. Illiterate users still make up a sizable share of mobile phone owners in the region. Illiteracy despite the pre-stated facts reduces the users’ ability to make the most of developed digital agricultural solutions.

3. Existence of mobile network-friendly policies: Mobile Network Operator-friendly policies: In some parts of Commonwealth Africa, the policy environment is being made more mobile connectivity friendly specifically for mobile network operators to enable them effectively expand with minimal regulatory hurdles. In Nigeria, for example,[63] several state governments have reduced right-of-way fees for laying fibre-optic cables by up to 95 per cent to enable the efficient and timely rollout of network infrastructure. Policies like these lower the capital expenditure costs for the mobile network operators which supports the enhancement of coverage for mobile broadband connections.

5. The rise of alternative financing models for model devices: Alternative financing for mobile devices: Alternative financing arrangements are also a great enabler for digitalisation of agriculture in the region. The success of the mobile-enabled Pay-As-You-Go model for the provision of affordable home solar equipment, agricultural equipment and other household assets has brought to light the opportunity to make variants of mobile devices accessible to more rural consumers through similar financing schemes. This form of financing for mobile devices reduces the initial cost of entry barrier for many of the rural poor.[64] The daily rather than monthly payment options reflect the financial culture and abilities of many smallholder farmers in the region; many of whom earn a daily wage and can only afford smaller payments on a regular basis than one-time complete payments.

Technology related barriers for digitalisation in Africa

1. Poor infrastructure: Less than 35 per cent of rural SSA is connected to national electricity grids.[65] This effectively means that mobile broadband operators have increased operating expenditure to run and maintain the much-needed mobile broadband networks that facilitate farmers’ access to mobile internet. The result is a higher cost of connectivity (internet) for the final consumers. Additionally, the majority of the roads in Commonwealth Africa are not paved (shown in the table below). Poor road network is more so common in rural hard-to-reach areas, where agriculture is concentrated. For this reason, mobile network operators are disincentivised from setting up in such areas.

Table 2.5: Roads paved (% of total roads) by country in selected Commonwealth countries

Source: World Bank Database.[66]

Where country data have not been provided, there is no data available in the mentioned database

2. Absence of updated regulation: The current rules and regulations being used by many Governments in SSA were developed in the late 1990s and early 2000s.[67] The pioneering laws and policies made little or no mention of emerging digital technologies such as big data and analytics, blockchain, the Internet of Things, robotics, machine learning, artificial intelligence, unmanned aerial vehicles and privacy-related complications of dealing with farmer data with a wide range of unique identifiers.

3. Fragmented and heterogeneous agricultural terrain: A technical limiter of the implementation of many digital agriculture solutions, especially those that rely on aerial imagery, is the inbuilt natural complexities of the agricultural layout in SSA. This includes among others a very heterogenous and highly intercropped farming system and a culture of subsistent rain-fed agriculture. Heterogeneous nature of farming systems and poor and unavailable crop yield databases limits the ability of the agriculture sector to leverage big data and remote sensing technologies.[68] This arises from the fact that aerial imagery-based remote sensing farm solutions are best applied to large homogeneous farming systems and systems that avail data.

4. Uncoordinated roll out of digital solutions: The digital agriculture space in SSA is characterised by duplication of scattered knowledge, products and solutions.[69] This effectively wipes out the subsequent economies of scale that would have resulted from the large-scale application of uniformly coordinated solutions and services.

5. Absence of robust accelerator programmes: From the deep dive done into the literature review, robust and well-coordinated accelerator programmes are absent. These programmes are typically important because they facilitate the effective coordination and absorption of talent into well-created capacity-building programmes. The technical and regulatory environments in the region remain far from ideal to facilitate the digitalisation of agriculture, based on the GSMA Mobile Connectivity Indices for Commonwealth Africa. For most of the farmers in Sub-Saharan Africa, mobile devices are the primary access media for the consumption of digital agricultural solutions. The GSMA mobile connectivity index is an elaborate quantitative rank of technological and non-technological attributes that facilitate the use of mobile devices to consume digital services.

This index has been detailed in the annex and footnote below

Source: Author computations from the World Bank indicator database[70]

The GSMA mobile connectivity Index[71] measures the enablers of mobile internet connectivity. This index provides an aggregated quantifiable measure for selected indicators enablers of mobile connectivity. These indicators are Infrastructure – the availability of high-performance mobile internet network coverage; Affordability – the availability of mobile services and devices at price points that reflect the level of income across a national population; Consumer readiness – citizens with the awareness and skills needed to value and use the internet, and a cultural environment that promotes gender equality; Content – the availability of online content and services accessible and relevant to the local population.

2.4 Policy recommendations to fast-track digitalisation of agriculture in Africa

2.4.1 Digital innovations

Gaps (factors limiting innovation and scalability in digital agriculture)

• From the mapping of solutions in the region, most of the products on the market rely on the internet. This is a major limitation given the smallholders often do not have access to the internet and the devices they own are not compatible with channels like “App” and “Web”. Additionally, most developers lack financing to scale up.
• Most developers lack the knowledge to run successful businesses. There is a gap in articulating value propositions, raising funding, developing business plans, day-to-day management among others.

Table 2.6: Recommendation for African countries to increase investment in digital agriculture innovations

2.4.2 Data infrastructure

Gaps in the data infrastructure required for digitalisation of agriculture to thrive

• Absence of state-run soil and weather data Application Programming Interfaces (APIs). This means that state-collected data resources are excluded from many of the region's digital solutions.
• Absence of robust national agri-statistical national data sets. Many of the countries in the region do not have national agri-statistical data infrastructure. This means that many digital solutions are not aligned with the market.
• Absence of robust linkages between land and person identifiers. Despite the roll-out of national identity schemes in many Commonwealth African countries, the different identifiers in Africa are not linked. This hence limits the transformative power that existent data can have in the creation of relevant digital solutions for farmers in the region.
• Fragmentation of data. There is a lot of data on the sector that is collected by different development partners and government bodies. However, this data is not always used (or re-used) for further production of information that would feed into decision-making.

Table 2.7: Recommendation for African Countries to increase investment in data infrastructure

2.4.3 Business development services

Gaps (factors hindering the flow of financing to digital innovations in agriculture)

• Existence of a significant number of largely subsistent farmers. More than 60 per cent of the population of Sub-Saharan Africa is smallholder farmers. Financial institutions are not willing to finance smallholders because they lack the required collateral and proper records.
• Low state-provided expenditure on government research and development into smart farming. Government expenditure on agriculture innovations has been critically low. There is also limited evidence of several large-scale private sector investments in smart farming and digital innovations research in the region.

Table 2.8: Recommendation for African countries to increase investment business development

2.4.4 Enabling environment

Gaps in Africa’s enabling environment for digitalisation

• Existing laws are not always aligned with the fast pace of technology evolution – The current rules and regulations being used by many Governments in Sub-Saharan Africa were developed in the late 1990s and early 2000s. The pioneering laws and policies made little or no mention of emerging digital technologies such as big data and analytics, blockchain, the Internet of Things, robotics, machine learning, artificial intelligence, unmanned aerial vehicles and the privacy-related complications of dealing with farmer data with a wide range of unique identifiers.
• Existence of a significant number of rural households that cannot afford mobile broadband – In Sub-Saharan Africa, the poorest 20 per cent on average would need to spend more than 16 per cent of their monthly income on 1 gigabyte of data. This hence means the cost of connectivity is prohibitively high for a typical rural-based subsistent smallholder farmer.[82] The high cost of mobile broadband connections locks out a significant number of potential consumers of digital agriculture solutions.
• Existence of a significant broadband coverage gap – Only 24–37 per cent of farms of less than 1 hectare in size are served by third-generation (3G) or 4G services. This eliminates the people in these areas from the pool of potential consumers of solutions that are reliant on the internet.
• Existence of a large percentage of the population uncovered by mobile network coverage – Although access has been slowly rising, only 42.8 per cent of the population in Africa had access to electricity in 2016, far less than any other developing region. More than 600 million people in Africa live without electricity, including more than 80 per cent of those residing in rural areas. This hence means that mobile network operators in these areas have to incur higher costs to set up as they must include more expensive power alternatives for mobile sites, consequently making connections in these areas prohibitively expensive.

Table 2.9: Recommendation for African countries to create an enabling environment for digitalisation to thrive

In conclusion, the most undeveloped pillar in the region is data infrastructure. This is despite the role that the pillar plays in unlocking inclusive innovations and reducing the cost for providers of digital solutions. Developing and investing in this pillar would thus put in place the rails for digitalisation to thrive. In developing the right data infrastructure, governments in the region ought to collect universal data and set up interlinked identifiers in tandem with other infrastructure.

The following are necessary for the recommendations to yield results.

1. Strong implementation. That is, policies need to be backed by clear strategic and implementation plans: For the policy recommendations to have an impact, there is a need for strategic plans that stipulate specific strategic objectives and well-defined activities whose execution would realise the desired impact. Additionally, as part of the process of developing the strategic plan, the capacity of the ICT and other Government Ministries to execute the plan would have to be assessed. Based on this assessment, recommendations on capacity building needs must be made. As part of the process of developing the strategic plan, proper monitoring and evaluation framework has to be in place. This monitoring and evaluation programme would include baselines, midlines and endlines. This would be to ensure that there is the tracking of the performance against the strategic plan at activity, output, outcome and impact levels.

The above has been clearly spelt out because though the African region has policies, there is a significant gap when it comes to implementation and monitoring.

1. Capacity building at a policy level is required. Capacity building of key decision-makers is necessary to empower them to make rules and regulations that are responsive to the fast-paced nature of technology innovations. Capacity building could be through the following:
   • Facilitating benchmark visits to other Commonwealth countries where laws on technology are updated.
   • Working with training partners that would carry out a capacity gap assessment and thereafter develop targeted training programmes.
   • Identification of a capacity-building partner to develop and rollout the relevant capacity building programme.
   • There is a need to use an integral programming approach that involves different ministries as opposed to using only the ICT ministry.

Having an empowered pool of policy and regulation actors would equally have trickle-down effects on policies that are passed.

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[1] Author Computations for Commonwealth countries in Africa done using raw data from World Bank.

[2] FAO and OECD, 2016, OECD – FAO Agricultural Outlook 2016–2025, Special Focus: Sub-Saharan Africa, OECD Publishing Paris. http://www.fao.org/3/I5778E/I5778E.pdf

[3] Xinshen, D., P. Hazell, D. Resnick and J. Thurlow (2006). The Role of Agriculture in Development: Implications for Sub-Saharan Africa, NW Washington DC. https://ageconsearch.umn.edu/record/55405/files/dsgdp29.pdf

[4] Chen, C., I. Noble, J. Hellmann, J. Coffee, M. Murillo and N. Chawla (2015). University of Notre Dame Global Adaptation Index. Country Index Technical Report. https://gain.nd.edu/our-work/country-index/matrix/

[5] World Meteorological Organization, 2019, State of Climate Change in Africa Report. https://library.wmo.int/doc_num.php?explnum_id=10421

[6] Computations for Commonwealth countries in Africa done using raw data from World Bank indicator database.

[7] The World Bank, World Bank indicator database. Data retrieved on August 8, 2021. Available from https://data.worldbank.org/indicator/SL.AGR.EMPL.FE.ZS

[8] Sasakawa Africa Association (2020). COVID-19’s impact on agriculture systems in Africa. https://globalagriculturalproductivity.org/covid-19s-impact-on-agriculture-systems-in-africa/

[9] Mishra, A. (2020). Africa and COVID19: Impact, Response, and Challenges to Recovery. https://www.orfonline.org/research/africa-and-covid19-impact-response-and-challenges-to-recovery-74209/

[10] Kentenyingi, R. (2020). UNCDF and SafeBoda, with support from SIDA, launch e-commerce platform for home delivery amid COVID-19. https://www.uncdf.org/article/5577/uncdf-and-safeboda-with-support-from-sida-launch-an-e-commerce-platform-for-home-delivery-amid-covid-19

[11] UNDP (2020). COVID-19: UNDP, JUMIA. Uganda partner to link market vendors with consumers online. https://www.ug.undp.org/content/uganda/en/home/presscenter/pressreleases/2020/covid-19--undp--jumia-uganda-partner-to-link-market-vendors-with.html

[12] CGIAR (2020). Reducing COVID-19 Impact on Agriculture: Nigerian farmers to receive improved seeds. https://reliefweb.int/report/nigeria/reducing-covid-19-impact-agriculture-nigerian-farmers-receive-improved-seeds

[13] Toewallace, C. and C. Shuaihua (2021). For farmers in Africa to recover from COVID-19, bridge the last mile. https://blogs.worldbank.org/nasikiliza/farmers-africa-recover-covid-19-bridge-last-mile

[14] In this classification, digital agriculture solutions enabling the provision of extension services by linking rural smallholder farmers to extension service providers solution providers are assessed differently from the solutions that provide direct pre-harvest crop advisory for farmers like access to information regarding planting routines, inputs and more.

[15] Mpagalile, J. (2015). Firm-level logistics systems for the Agrifood sector in sub-Saharan Africa: Report based on appraisals in Cameroon, Ghana, Uganda and the United Republic of Tanzania. http://www.fao.org/3/i5017e/i5017e.pdf

[16] Toulmin, C. (2005). Securing land and property rights in sub-Saharan Africa: the role of local institutions. https://www.sciencedirect.com/science/article/abs/pii/S0264837708000811

[17] In our classification, the word bundled was used to refer to digital solutions that has more than two service offerings in their value propositions.

[18] http://omulimisa.org/m-omulimisa/login (accessed on July 14, 2021).

[19] Echeverría, D., A. Terton and A. Crawford (2016). Review of Current and Planned Adaptation Action in Uganda. https://www.iisd.org/publications/review-current-and-planned-adaptation-action-uganda

[20] Dobermann, A. and A. Nelson (2013). Solutions for Sustainable Agriculture and Food Systems. https://irp-cdn.multiscreensite.com/be6d1d56/files/uploaded/TG07-Agriculture-Report-WEB.pdf

[21] Food rights Alliance Uganda (2019). State of food and nutrition we need.

[22] Twinamatsiko, J. (2019). ICT tools make life better for farmers. http://www.sunrise.ug/news/201907/ict-tools-make-life-better-for-farmers.html

[23] Nandudu, P. (2020). Pandemic-hit farmers turn to digital solutions. https://www.newvision.co.ug/articledetails/88907

[24] CGIAR (2019). Plant village Nuru: AI For Pest & Disease Monitoring. https://bigdata.cgiar.org/inspire/inspire-challenge-2017/pest-and-disease-monitoring-by-using-artificial-intelligence/

[25] https://www.aerobotics.com/ (accessed on July 14, 2021).

[26] https://okuafofoundation.org/ (accessed on July 14, 2021).

[27] https://jaguzafarm.com/support/ (accessed on July 14, 2021).

[28] Credit Suisse (2019) Pioneers of Progress: Pula. https://www.credit-suisse.com/microsites/empowering-entrepreneurs/lite-en/episodes/pula.html?t=944_0.2810058384998777

[29] The World Bank. (2018). Kenya’s Pastoralists Protect Assets from Drought Risk with Financial Protection. https://www.worldbank.org/en/news/feature/2018/11/05/kenyas-pastoralists-protect-assets-from-drought-risk-with-financial-protection

[30] https://hellotractor.com/ (accessed on July 3, 2021).

[31] http://www.tesitoo.com/ (accessed on July 3, 2021).

[32] https://agricloud.ro/ (accessed on July 3, 2021).

[33] https://m-omulimisa.com/ (accessed on July 3, 2021).

[34] Lemtukei, P. (2020). Maziwaplus – Providing solutions for Kenyan dairy farmers. https://www.cta.int/en/blog/all/article/maziwaplus-providing-solutions-for-kenyan-dairy-farmers-sid0d81a0fd9-8cd0-4899-aeaa-8f843f45beb1 (accessed on July 14, 2021).

[35] https://cropchain.co/features (accessed on July 14, 2021).

[36] https://farmdrive.co.ke/ (accessed on July 14, 2021).

[37] https://agropay.online/ (accessed on July 14, 2021).

[38] OCED (2019) Bridging The Digital Gender Divide Include, Upskill, Innovate. https://www.oecd.org/digital/bridging-the-digital-gender-divide.pdf

[39] Huawei (2017) The Digital Divide Challenge in Rural Kenya. https://www.huawei.com/ke/cases/ke/cases-remote-communities-in-kenya

[40] Wireless carriers and original equipment manufacturers (OEMs) typically use over-the-air updates to deploy firmware and configure phones for use on their networks over Wi-Fi or mobile broadband.

[41] Key informant interview with Pierre Marole the Strategic Partnership Manager at KaiOS Technologies.

[42] Global System for Mobile Communications (2020). The mobile Economy Sub-Saharan Africa.

[43] Global System for Mobile Communications (2018). Huawei: MTN Ghana – Safaricom.

[44] Global System for Mobile Communications (2019). Closing the Coverage Gap. How Innovation Can Drive Rural Connectivity.

[45] https://openweathermap.org/ retrieved on October 12, 2020.

[46] Shining a light below the surface: Mapping soil properties in Africa, 2013. https://cgspace.cgiar.org/rest/rest/bitstreams/eefff3ed-972b-4b26-8dfc-60ffe0f9e120/retrieve

[47] Minae, S., D. Baker and J. Dixon (2008). Status of Farm Data Systems and Farmer Decision Support in Sub-Saharan Africa. Rome: FAO.

[48] The World Bank (2019) Sub-Saharan Africa Series: Identification. Financial Inclusion and Development in Sub-Saharan Africa.

[49] Toulmin, C. (2009) Securing land and property rights in Sub-Saharan Africa: the role of local institutions.

[50] https://ensibuuko.com/products/insurance (accessed on July 14, 2021).

[51] https://agribora.com/ (accessed on July 14, 2021).

[52] Lemtukei, P. (2020) Maziwaplus – Providing solutions for Kenyan dairy farmers. https://www.cta.int/en/blog/all/article/maziwaplus-providing-solutions-for-kenyan-dairy-farmers-sid0d81a0fd9-8cd0-4899-aeaa-8f843f45beb1 (accessed on July 14, 2021).

[53] http://www.agromarketday.com/ (accessed on July 14, 2021).

[54] The World Bank, World Bank indicator database. Data retrieved on August 8, 2021. Available from https://data.worldbank.org/indicator/IT.CEL.SETS.P2

[55] Google, International Finance Corporation of the World Bank Group, 2020. Economy Africa. Africa's $180 billion internet economy future.

[56] Global System for Mobile Communications, 2020. The mobile Economy Sub-Saharan Africa.

[57] Key informant interview with a Financial Inclusion and Consumer Protection Expert(Agriculture Value Chains).

[58] The Alliance for Affordable Internet, Alliance for Affordable internet 2018. Data retrieved on August 8, 2021. Retrieved from https://a4ai.org/extra/mobile_broadband_pricing_gnicm-2018Q4

[59] The World Bank, World Bank indicator database. Data retrieved on August 8, 2021. Retrieved from https://data.worldbank.org/indicator/IT.NET.USER.ZS

[60] International Telecommunication Union, 2020, The affordability of ICT services 2020.

[61] In the interpretation of these data, high per capita gross national incomes should also be factored in. These could, for example, explain the island countries having considerably higher percentages of their individuals connected to the internet, possibly as a result of the higher per capita GNIs.

[62] Global System for Mobile Communications. (2020). Powering Youth Employment through the Mobile Industry in Sub-Saharan Africa by 2025.

[63] The World Economic Forum. (2017). The Future of Jobs and Skills in Africa.

[64] Global System for Mobile Communications (2020). The mobile Economy Sub-Saharan Africa 2020.

[65] The Trading Economics, World Bank indicator database. Data retrieved on August 8, 2021. Retrieved from https://tradingeconomics.com/country-list/roads-paved-percent-of-total-roads-wb-data.html

[66] Global System for Mobile Communications (2020). Mobile connectivity in Sub-Saharan Africa: 4G and 3G connections overtake 2G for the first time. https://www.gsma.com/mobilefordevelopment/blog/mobile-connectivity-in-sub-saharan-africa-4g-and-3g-connections-overtake-2g-for-the-first-time/

[67] Wahab, I. et al. (2018). Remote Sensing of Yields: Application of UAV Imagery-Derived NDVI for Estimating Maize Vigor and Yields in Complex Farming Systems in Sub-Saharan Africa.

[68] Baumüller, H. and B.K. Addom (2020). The enabling environments for the digitalisation of African agriculture. https://www.ifpri.org/publication/enabling-environments-digitalization-african-agriculture 

[69] Key informant interview with Financial Inclusion and Consumer Protection Expert.

[70] Global System for Mobile Communications (2020) Mobile Connectivity Index – methodology. https://www.gsma.com/r/wp-content/uploads/2020/09/GSMA-Mobile-Connectivity-Index-Methodology-2020.pdf

[71] The Global System for Mobile Communications, GSMA mobile connectivity index data. Data retrieved on August 8, 2021. Retrieved from https://www.mobileconnectivityindex.com/

[72] Connell, D. (2021). Is the UK’s flagship industrial policy a costly failure?. https://www.jbs.cam.ac.uk/wp-content/uploads/2021/05/cbr-report-uk-flagship-industrial-policy-2021.pdf

[73] Daily Bangladesh (2020) Farmers to get money from selling goods at home. https://www.daily-bangladesh.com/english/Farmers-to-get-money-from-selling-goods-at-home/42358

[74] Harper Adams University (2016). New innovation hub for agricultural technology to be built at Harper Adams University. https://www.harper-adams.ac.uk/news/202795/new-innovation-hub-for-agricultural-technology-to-be-built-at-harper-adams-university

[75] Organisation for Economic Co-operation and Development (2019). Digital Opportunities for Better Agricultural Policies. https://doi.org/10.1787/571a0812-en

[76] Global System for Mobile Communications (2019). Mobile technology for rural climate resilience: The role of mobile operators in bridging the data gap.

[77] Statistics Canada (2021). The 2021 Census of Agriculture – Frequently asked questions. https://www.statcan.gc.ca/eng/statistical-programs/document/3438_D4_V3

[78] Food and Agriculture Organization (2015). The economic lives of smallholder farmers.

[79] Food and Agriculture (2015). Organization Piloting livestock traceability using blockchain technology: the case of Jiwaka province. http://www.fao.org/asiapacific/perspectives/digital-villages/png-dvi/ar (accessed on July 14, 2021).

[80] Press Trust of India (2021) FDI in computer software, hardware jumps threefold to $26.14 bn: DPIIT data. https://www.business-standard.com/article/economy-policy/fdi-in-computer-software-hardware-jumps-threefold-to-26-14-bn-dpiit-data-121053000467_1.html

[81] Invest in China (2021) Yangling Agriculture High-Tech Industrial Demonstration Zone. https://investinchina.chinadaily.com.cn/s/201905/21/WS5ce3c108498e079e680214f3/yangling-agriculture-high-tech-industrial-demonstration-zone.html

[82] Global System for Mobile Communications (2020). The state of mobile internet connectivity 2020.

[83] United Nations Conference on Trade and Development (2021). The technology report 2021.

[84] Global System for Mobile Communications (2020). The mobile economy Sub-Saharan Africa.

[85] United Nations Conference on Trade and Development (2021). The technology report 2021.

[86] Global System for Mobile Communications (2020). The mobile economy Sub-Saharan Africa.

[87] Statistics Canada (2021) The 2021 Census of Agriculture – Frequently asked questions. https://www.statcan.gc.ca/eng/statistical-programs/document/3438_D4_V3

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