AFRICA AGRICULTURE STATUS REPORT 2016

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• Logistics Management: Digital technology platforms are aggregating smallholder farmers in remote locations, making it easier for agribusinesses and processors to work with them, and subsequently ensuring reliability, quality and productivity of supply (GrowAfrica, 2015). With the use of mobile technologies to manage the business side of things—from establishing farmer contracts to making payments and sending receipts, agribusinesses are now able to cut down on both time and transportation costs which has made them more willing to work with remote farmers (Gustafson, 2016). The Zambia National Farmers Union (ZNFU), for example, launched an eTransport system known as Transzam. It is a web-based interactive information system which allows transport users to publicize availability of loads or cargo to a known destination and at preferred times of delivery to farmers and other transport users (Deloitte, 2012). Multiflower, a seed and cuttings exporter based in Arusha, Tanzania has also realized major savings in logistics from issuing mobile-based payments to its network of 3,500 outgrower farmers as show in Box 8.1. • Quality management: Farmers can now make more informed decisions about which inputs are better or cheaper to buy and when and where to best obtain them to improve their capacity to raise yields. Service providers are also able to aggregate data on the origin of products for input providers enabling traceability and discouraging counterfeit goods (World Bank, 2011). As in the case of MPedigree in Kenya and Uganda, for example, developed by the International Fertilizer Development Center (IFDC) in partnership with CropLife Africa-Middle East, CropLife Uganda and Kenya, farmers subscribed to the platform are able to quickly authenticate the origin and assess the quality of input products via a USSD code. Likewise, data validation processes and their role in quality assurance on the advice given to farmers can help determine and correct cases where the advice has significant health and market access implications as exemplified by the recommendations to use red list pesticides or the wrong pesticide– crop–pest combinations. Lessons on these using Plantwise plant clinic data are best used by national regulatory authorities to monitor country situations with pest and pesticides; this is only feasible where the authorities are proactively engaging in sharing and using agriculture related data. BOX 8.1: Multiflower realizing savings in logistics from mobile payments Multiflower, a seed and cuttings exporter based in Arusha, Tanzania, works with 3,500 out-growers and has close to US$1 million in annual revenue. The project embarked on a proof of concept pilot in 2013 where they issued loans totaling US$6,000 to 200 farmers and paid US$67,000 to 300 farmers via M-Pesa. Apart from providing each farmer with an additional and simple method for accessing credit, the switch from cash to digital payment also resulted in an average saving of US$10.75 in transport costs and 8 hours per payment per farmer with participating farmers saving a total of approximately 6,000 hours over the duration of the pilot. Source: McKay C, Buruku, B, 2016 Digital Agri-Based Financial Systems: The mobile phone has offered a powerful new channel to deliver affordable financial services to smallholder farmers, who have traditionally lacked access to training, finance, and market facilitation. SSA leads the way with over two-thirds of the world’s 100 million active mobile money users, and mobilebased financial services diversifying into credit, savings, merchant payments, and insurance (Masiyiwa, 2016). The developing world now has five times more mobile money agents than commercial banks (Masiyiwa, 2016). The flexible, low-cost and ubiquitous models made possible by mobile technology and the evidence base to guide their design have created a major opportunity to deliver real value to the poor and more specifically to smallholder farmers (Masiyiwa, 2016). Kenya still ranks highest when it comes to the level of financial inclusion among the rural population with 8 in 10 adults using mobile money services (Figure 8.4). This has been due to the country’s high-level commitment to financial inclusion with the Maya Declaration, Better Than Cash Alliance, and the Vision 2030 National Development Strategy, that has set out to reduce the population without access to finance from 85 percent to below 70 percent. (Villasenor, West, & Lewis, 2016). AFRICA AGRICULTURE STATUS REPORT 2016 177
Figure 8.4: Kenya leads the pack for increased access and use of affordable financial and digital technology services globally. Mexico 74 94 83 78 58 Nigeria 72 94 79 83 53 Kenya 84 89 83 94 78 Colombia 79 100 94 89 56 Turkey 72 89 79 67 64 Phillipines 76 100 94 100 42 100 73 KEY 94 58 Country Commitment % Mobile Capacity % Regulatory Environment % Adoption % 89 72 61 75 89 83 83 67 Brazil 78 94 83 100 50 Uganda 78 Rwanda 76 72 94 100 47 Indonesia 71 Chile 74 83 94 100 50 South Africa 78 Source: The 2016 Brookings Financial and Digital Inclusion Project Report 178 AFRICA AGRICULTURE STATUS REPORT 2016
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AFRICA AGRICULTURE STATUS REPORT 20
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FOREWORD Over the last decade, mill
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ACKNOWLEDGEMENTS The Africa Agricul
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ACRONYMS Africa Lead AAS AASR AATIF
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FMARD FSN FTF GACSA GAFSP GAIN GART
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SAKSS SBCC SCARDA SCM SDG SDI SI SM
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Introduction For decades, observers
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and changing food diets associated
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Table 1.2: Population growth of sel
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Figure 1.4: Changes in annual agric
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already occurring (Headey & Jayne,
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lease of customary land without the
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Hence, the pattern of trade illustr
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Table 1.4: Changes in farm structur
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of the pathway to food and nutritio
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Jayne, T. S., Chamberlin, J., Traub
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KEY MESSAGES ONE CAADP is an unpara
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Figure 2.1.Overview of the CAADP Im
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level. The success of ReSAKSS is be
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agricultural potential, alternative
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Table 2.1: Trends in selected CAADP
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poverty fell faster during this per
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expenditure (research, extension, i
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Table 2.4. Average annual change in
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captures the individual pathways of
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MA also has to be underpinned by lo
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References African Union. (2014). M
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Meenakshi, J.V., Johnson, N.L., Man
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KEY MESSAGES ONE TWO THREE FOUR Afr
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GDP declined by 1.4 percent in 2009
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from political violence, terrorism,
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interpretation is implied, this obs
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Differences in the African pattern
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Table 3.5: Trends in types of emplo
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that would likely affect the contri
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c. Concentration of farm structure
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a. Invest in education to upgrade t
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These could include policy measures
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References African Center for Econo
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Giller, K. E., Rowe, E. C., de Ridd
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Ndung’u, N. S. (2016). Viewpoint:
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World Bank. (2015). World developme
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KEY MESSAGES ONE Although sustainab
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BOX 4.1: Components of Sustainable
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of the world. These authors also re
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Further, Locatelli et al. (2008) ha
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Climate and Weather Variability The
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Resilience of livelihoods is determ
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While acknowledging successes of SI
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Entry Points For Sustainable Intens
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BOX 4.4: The CSA Compendium: A scie
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Successful interventions include fo
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Open data combined with agricultura
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According to Tshibaka (2014), evide
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References Abdulai, A., & Delgado,
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Enfors, E. (2013). Social-ecologica
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Lipper, L., Thornton, P., Campbell,
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Toulmin, C., Leonard, R., Brock, K.
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KEY MESSAGES ONE In SSA, sustainabl
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Figure 5.1: Poverty traps framework
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Cereal Yield/Kilogram Per Hectare F
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Table 5.2: Correlation between fact
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Table 5.3: Farmer use of improved i
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Figure 5.9: Agricultural research s
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association is found for cereal out
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AGRA’s Experience The observation
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Increase access to affordable crop
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Sheahan, M., & Barrett, C. B. (2014
Page 139 and 140: KEY MESSAGES ONE Smallholder farmer
Page 141 and 142: transformation in Africa. The achie
Page 143 and 144: from agribusiness actors to smallho
Page 145 and 146: season, maize prices could be 270 p
Page 147 and 148: critical challenges and the solutio
Page 149 and 150: Limited access and high cost of acc
Page 151 and 152: of onion production in northern Gha
Page 153 and 154: Conclusions This chapter presents t
Page 155 and 156: Collins, D., Morduch, ,. J., Ruther
Page 157 and 158: Minot, N. (2014). Food price volati
Page 159 and 160: Weatherspoon, D. D., & Reardon, T.
Page 161 and 162: KEY MESSAGES ONE Access to finance
Page 163 and 164: esources into agriculture. This in
Page 165 and 166: Table 7.1: Indicative investments t
Page 167 and 168: technical knowledge about products.
Page 169 and 170: continue to experience inadequate a
Page 171 and 172: Box 7.1: GAFSP: Country Examples Rw
Page 173 and 174: Private Equity Association, total p
Page 175 and 176: drawing down assets, and 25 percent
Page 177 and 178: equires: recognition of the critica
Page 179 and 180: Policy Recommendations This review
Page 181 and 182: Meyer, R. L. (2015, March). Financi
Page 183 and 184: KEY MESSAGES ONE The African contin
Page 185 and 186: Figure 8.1: Mobile phone based serv
Page 187 and 188: high input costs, and a disconnecte
Page 189: available through less high-tech de
Page 193 and 194: years and higher quality seeds are
Page 195 and 196: CASE STUDY FieldLook South Sudan in
Page 197 and 198: Rationale behind rapid adoption •
Page 199 and 200: CASE STUDY Eastern Africa Farmer Fe
Page 201 and 202: many others have none or have strin
Page 203 and 204: the strategic adoption of ICT with
Page 205 and 206: To address constraints to improving
Page 207 and 208: References Accenture. (2015). Digit
Page 209 and 210: Gustafson, S. (27.1.2016). The Digi
Page 211 and 212: Wolfenson K. D. (2013). Coping with
Page 213 and 214: KEY MESSAGES ONE A guided evolution
Page 215 and 216: een registered over the last decade
Page 217 and 218: the AIS paradigm at policy and prog
Page 219 and 220: Box 9.2: Rwanda - A Phoenix Rising
Page 221 and 222: other supportive partners (tertiary
Page 223 and 224: Table 9.2: SSA AR4D funding through
Page 225 and 226: (e.g., NARIs, universities, NGOs, F
Page 227 and 228: Table 9.3: Number of extension agen
Page 229 and 230: the whole farm whereas the field sc
Page 231 and 232: approach, organizational or system
Page 233 and 234: CASE STUDY Regional Universities Fo
Page 235 and 236: CASE STUDY African Network for Agri
Page 237 and 238: CASE STUDY FAO—Tropical Agricultu
Page 239 and 240: Bizimana, C. (2014). Rwanda’s Ach
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Rwanda. Retrieved from http://www.m
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World Bank. (2007). Project Apprais
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KEY MESSAGES ONE The poverty rate a
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Table 10.1: Number of undernourishe
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Figure 10.6: Stunting in children u
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Why single out nutrition matters? A
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BOX 10.1: The 7 Malabo Declaration
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Reducing post-harvest losses FAO es
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BOX 10.4: Growing trend towards a m
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References African Union. (2015). T
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Schmidt, R. H., & Rodrick, G. E. (2
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“Africa is simply tired of being
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2025, tripling intra-African trade,
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towards agricultural transformation
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While agricultural research generat
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258 AFRICA AGRICULTURE STATUS REPOR
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Technical Notes The following conve
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Madagascar 72.6 72.3 72.1 71.8 71.2
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Madagascar 2.81 -15.28 6.54 2.19 1.
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Madagascar 351.1 337.2 332.9 323.7
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Madagascar 2,020 1,967 2,202 2,354
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Madagascar 86.0 84.2 87.3 91.8 103.
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Mali .. .. 52.0 15.7 17.5 31.1 22.5
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Madagascar -0.0053 -0.0075 0.0073 -
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Malawi 401.9 405.1 437.2 438.9 511.
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Madagascar 0.2 0.3 0.4 0.5 0.6 0.6
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Madagascar 0.9 1.0 1.6 1.9 2.8 5.6
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Liberia .. .. .. .. .. .. .. .. ..
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Liberia 2.0 1.9 1.8 1.7 1.5 1.3 1.5
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