Agriculture is the main means of livelihood in Africa. Wheat is one of the globally produced and marketed cereal crops which cover 15% of the total sowing areas of cereal crops in the world. This study focused on the analysis of factors affecting smallholder farmer’s participation in wheat cluster farming in Gasera District of Bale zone. A multi-stage sampling method was employed for this study. Simple random sampling technique was used to select 259 sample respondents in three selected Kebeles out of 24 total kebeles in the woreda. Primary data sources were generated using an interview schedule, five Focus Group Discussions, and eight key informant interviews. Besides, secondary data were obtained from literature and the Woreda Agricultural Office. Both descriptive statistics and econometric models were employed to analyze the collected data. The descriptive statistics results showed that from the total sampled households, 169 (65.3%) were participant and, 90 (34.7%) were non-participant smallholder farmers of wheat cluster farming technology. According to the probit regression model, education status, wheat land, livestock size, frequency of extension contact, credit access, availability of fair price, market information, agricultural input access, training access and membership in a cooperative had a positive influence on farmers’ decisions to participate in wheat cluster farming. Therefore, the local community, Woreda Agriculture Office and research institutes need to expand cluster farming technology to increase wheat production and policies aiming at increasing farmers’ awareness of producing wheat in cluster to increase yield of farmers.
| Published in | Plant (Volume 12, Issue 4) |
| DOI | 10.11648/j.plant.20241204.12 |
| Page(s) | 95-110 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Gasera Woreda, Cluster Farming, Cluster, Probit Model, Wheat
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APA Style
Sultan, O. (2024). Analysis of Factors Affecting Participation of Smallholder Farmers in Wheat Cluster Farming: The Case of Gasera District, Bale Zone, Oromia Region, Ethiopia. Plant, 12(4), 95-110. https://doi.org/10.11648/j.plant.20241204.12
ACS Style
Sultan, O. Analysis of Factors Affecting Participation of Smallholder Farmers in Wheat Cluster Farming: The Case of Gasera District, Bale Zone, Oromia Region, Ethiopia. Plant. 2024, 12(4), 95-110. doi: 10.11648/j.plant.20241204.12
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Download@article{10.11648/j.plant.20241204.12,
author = {Obsitu Sultan},
title = {Analysis of Factors Affecting Participation of Smallholder Farmers in Wheat Cluster Farming: The Case of Gasera District, Bale Zone, Oromia Region, Ethiopia
},
journal = {Plant},
volume = {12},
number = {4},
pages = {95-110},
doi = {10.11648/j.plant.20241204.12},
url = {https://doi.org/10.11648/j.plant.20241204.12},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.plant.20241204.12},
abstract = {Agriculture is the main means of livelihood in Africa. Wheat is one of the globally produced and marketed cereal crops which cover 15% of the total sowing areas of cereal crops in the world. This study focused on the analysis of factors affecting smallholder farmer’s participation in wheat cluster farming in Gasera District of Bale zone. A multi-stage sampling method was employed for this study. Simple random sampling technique was used to select 259 sample respondents in three selected Kebeles out of 24 total kebeles in the woreda. Primary data sources were generated using an interview schedule, five Focus Group Discussions, and eight key informant interviews. Besides, secondary data were obtained from literature and the Woreda Agricultural Office. Both descriptive statistics and econometric models were employed to analyze the collected data. The descriptive statistics results showed that from the total sampled households, 169 (65.3%) were participant and, 90 (34.7%) were non-participant smallholder farmers of wheat cluster farming technology. According to the probit regression model, education status, wheat land, livestock size, frequency of extension contact, credit access, availability of fair price, market information, agricultural input access, training access and membership in a cooperative had a positive influence on farmers’ decisions to participate in wheat cluster farming. Therefore, the local community, Woreda Agriculture Office and research institutes need to expand cluster farming technology to increase wheat production and policies aiming at increasing farmers’ awareness of producing wheat in cluster to increase yield of farmers.
},
year = {2024}
}
TY - JOUR T1 - Analysis of Factors Affecting Participation of Smallholder Farmers in Wheat Cluster Farming: The Case of Gasera District, Bale Zone, Oromia Region, Ethiopia AU - Obsitu Sultan Y1 - 2024/10/18 PY - 2024 N1 - https://doi.org/10.11648/j.plant.20241204.12 DO - 10.11648/j.plant.20241204.12 T2 - Plant JF - Plant JO - Plant SP - 95 EP - 110 PB - Science Publishing Group SN - 2331-0677 UR - https://doi.org/10.11648/j.plant.20241204.12 AB - Agriculture is the main means of livelihood in Africa. Wheat is one of the globally produced and marketed cereal crops which cover 15% of the total sowing areas of cereal crops in the world. This study focused on the analysis of factors affecting smallholder farmer’s participation in wheat cluster farming in Gasera District of Bale zone. A multi-stage sampling method was employed for this study. Simple random sampling technique was used to select 259 sample respondents in three selected Kebeles out of 24 total kebeles in the woreda. Primary data sources were generated using an interview schedule, five Focus Group Discussions, and eight key informant interviews. Besides, secondary data were obtained from literature and the Woreda Agricultural Office. Both descriptive statistics and econometric models were employed to analyze the collected data. The descriptive statistics results showed that from the total sampled households, 169 (65.3%) were participant and, 90 (34.7%) were non-participant smallholder farmers of wheat cluster farming technology. According to the probit regression model, education status, wheat land, livestock size, frequency of extension contact, credit access, availability of fair price, market information, agricultural input access, training access and membership in a cooperative had a positive influence on farmers’ decisions to participate in wheat cluster farming. Therefore, the local community, Woreda Agriculture Office and research institutes need to expand cluster farming technology to increase wheat production and policies aiming at increasing farmers’ awareness of producing wheat in cluster to increase yield of farmers. VL - 12 IS - 4 ER -
Agricultural Extension and Communication Research, Ethiopian Institute of Agricultural Research, Wondo Genet, Ethiopia
