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Frontiers of Agricultural Science and Engineering

ISSN 2095-7505

ISSN 2095-977X(Online)

CN 10-1204/S

Postal Subscription Code 80-906

Front. Agr. Sci. Eng.    2020, Vol. 7 Issue (4) : 418-426    https://doi.org/10.15302/J-FASE-2020358
RESEARCH ARTICLE
Innovative agricultural extension value chain-based models for smallholder African farmers
Bidjokazo FOFANA1(), Leonides HALOS-KIM1, Mercy AKEREDOLU1, Ande OKIROR1, Kebba SIMA1, Deola NAIBAKELAO1, Mel OLUOCH1, Fumiko ISEKI2
1. Sasakawa Africa Association, Gurd Sholla, Daminarof Building, Addis Ababa 1000, Ethiopia
2. Sasakawa Africa Association, Sasakawa Peace Foundation Building, Tokyo 105-0001, Japan
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Abstract

The value chain extension strategy of Sasakawa Africa Association focuses on improving the capacity of national agricultural extension systems and follows various thematic areas along the value chain to address key challenges accountable for low income households and poverty in Africa. Farmer learning platform is a model designed to increase crop productivity and encompasses demonstration plots where technological packages demonstrated significantly outperformed other technology plots in crop productivity and average profit margins. Enterprise-oriented production, postharvest and trading centers are value adding models designed to improve the effectiveness of extension and adoption of postharvest and agricultural processing technologies by producers. The use of the above along with necessary capacity building has facilitated the development of profitable business linkages of smallholder farmers with financial institutions and reliable market opportunities. The community association trader-trainer model is a market-oriented business approach applied in combination with other extension models. In 2018, 297 community-based commodity association trader-trainers were mobilized and capacitated to improve farmer group dynamics and developed collective input and output access and cluster aggregation centers at community level where various agricultural produces were mobilized and collectively aggregated, and valued at about 3.9 million USD. The supervised enterprise project model is an innovative agricultural extension model developed along with above models for capacity development of extension agents and transfer of technologies to smallholder farmers. Over 6000 supervised enterprise projects have been introduced into 27 universities in 12 African countries for training front-line extension officers and extension delivery to farming communities.

Keywords crop productivity      extension      farmer      grain yield      income      model     
Corresponding Author(s): Bidjokazo FOFANA   
Just Accepted Date: 12 August 2020   Online First Date: 15 September 2020    Issue Date: 06 November 2020
 Cite this article:   
Bidjokazo FOFANA,Leonides HALOS-KIM,Mercy AKEREDOLU, et al. Innovative agricultural extension value chain-based models for smallholder African farmers[J]. Front. Agr. Sci. Eng. , 2020, 7(4): 418-426.
 URL:  
https://academic.hep.com.cn/fase/EN/10.15302/J-FASE-2020358
https://academic.hep.com.cn/fase/EN/Y2020/V7/I4/418
Fig.1  Sasakawa Africa Association value chain concept encompassing production, postharvest and agricultural processing along with group dynamics toward facilitating smallholder farmer access to input and output markets; technology adoption plot (TAP); technology option plot (TOP); women assisted demonstrations (WADs); community demonstration plots (CDPs); production technology plots (PTPs), village savings and loan association (VSLA); postharvest and trading center (PHTC)
Fig.2  Sasakawa commodity association trader-trainer business model: commercial linkages among business actors. Commodity association trader and trainer (CAT).
Crop CDPs TAPs CPs Average LSD (5%)
Ethiopia
Maize 5539 4858 3573 4657 355
Wheat 5160 4160 2603 3974 230
Barley 4841 3438 2388 3556 440
Sorghum 4180 3295 2554 3343 393
Teff 2519 2048 1737 2101 64
Nigeria
Rice 6148 5505 4269 5307 133
Maize 4823 4272 2438 3844 69
Groundnut 1317 1017 897 1077 45
Tab.1  Crop grain yields (kg·ha1) in community demonstration plots (CDPs) as compared with technology adoption plots (TAPs) and community practices (CPs); least significant difference values (LSD) at 5% probability, Ethiopia (n = 384) and Nigeria (n = 420), 2018
Priority crop CDPs MAPs TAPs CPs LSD (5%)
Rice 6148 5786 5505 4269 133
Maize 4823 4984 4272 2438 69
Groundnut 1317 1393 1017 897 45
Tab.2  Average grain yields (kg·ha1) of priority crops in the farmer learning platforms comprising community demonstration plots (CDPs), technology adoption plots (TAPs), model adoption plots (MAPs) and community practices (CPs), Nigeria, 2018
Variable CDPs MAPs TAPs CPs
Rice
Grain yield/(kg·ha1) 6148 5786 5505 4269
Production costs (NN·ha1) 181300 176175 165407 197635
Revenue/(NN·ha1) 737760 694320 660600 512280
Profit/(NN·ha1) 556460 518145 495193 314645
Cost benefit ratio 3.07 2.94 2.99 1.59
Internal rate of Return (%) 206.93 194.11 199.38 59.21
Maize
Grain yield/(kg·ha1) 4823 4984 4272 2438
Production costs/(NN·ha1) 185200 150175 143000 101098
Revenue/(NN·ha1) 409955 423640 363120 207230
Profit/(NN·ha1) 224755 273465 185969 106132
Cost benefit ratio 1.21 1.82 1.30 1.05
Internal rate of Return (%) 21.36 82.09 30.05 4.98
Tab.3  Average grain yield (kg·ha1) and economics of priority crops in the farmer learning platforms comprising community demonstration plots (CDPs), technology adoption plots (TAPs), model adoption plots (MAPs) and community practices (CPs), Nigeria, 2018
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