Determinants of Maize (<i>Zea mays L.</i>) Varietal Turnover in Ethiopia

Guta Bukero

doi:doi:10.11648/j.ijaas.20230901.15

| Peer-Reviewed

Determinants of Maize (Zea mays L.) Varietal Turnover in Ethiopia

Guta Bukero

Published in International Journal of Applied Agricultural Sciences (Volume 9, Issue 1)

Received: 2 September 2022 Accepted: 14 September 2022 Published: 27 February 2023

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

While many smallholder farmers all over the developing countries have benefited from the introduction of first-generation green revolution cultivars that replaced lower-yielding landraces, adoption of second and third-generation cultivars offering improvements in yield, output quality, and stress resistance seems now to be occurring at a much slower pace. Most varietal adoption and impact assessment studies in the past have relied on farmers’ responses at household level surveys to estimate these indicators. Such method of ‘farmer elicitation’ to estimate varietal adoption can be fairly accurate in a setting where farmers are mostly planting seeds freshly purchased or acquired from the formal seed market as certified or truthfully labeled seed, and the seed system is well-functioning and effective in monitoring the quality and genetic identity of varieties being sold by the seed suppliers. Thus, this study focused on varietal turnover by calculating an index of the weighted average age of varieties grown by farmers in a given year (measured in years since release) and factors affecting this varietal turnover, using a recently collected DNA fingerprinting dataset. Secondary data from the household survey data collected by Central Statistical Agency were used in the analysis. The multiple linear regression models were used in identifying determinants of maize cultivars varietal turnover. Econometric results indicate that, Farmers’ experience in growing maize affects WA weakly and statistically significant and positive. This implies that more experienced farmers are refusing to change their varieties as they are small holders and so risk averse. Family size being positively affecting varietal turnover also implies that if the decision to cultivate a new variety requires consensus among key family members who are involved in farming, then idea generation and making decision may become more difficult and taking time, causing households to forgo varietal turnover in order to avoid disagreement.

Published in	International Journal of Applied Agricultural Sciences (Volume 9, Issue 1)
DOI	10.11648/j.ijaas.20230901.15
Page(s)	21-30
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), 2023. Published by Science Publishing Group

Keywords

DNA Fingerprinting, Varietal Turnover, Age of Varieties

References

[1]	Abate Tsedeke, Shiferaw Bekele, Menkir, A., Wegary Dagne, Kebede, Y., Tesfy, K., Menale Kassie, Bogale, G., Tadesse, B., Keno, T. (2015). Factors that transformed maize productivity in Ethiopia. Food Security, 7 (5): 965-981.
[2]	Asfaw, A. and Admassie, A. (2004). The role of education on the adoption of chemical fertilizer under different socioeconomic environments in Ethiopia. Journal of Agricultural Economics, 30: 215-228.
[3]	Brennan, J. P. and Byerlee, D. (1991). The rate of crop varietal replacement on farms: measures and empirical results for wheat. Plant Varieties and Seeds, 4: 99–106.
[4]	Bruce, E. H. (2014). Econometrics. Department of Economics, revised January 3, 2014. University of Wisconsin, 1-387.
[5]	Chilot Yirga, Dawit Alemu, Oruko, L., Kefyalew Negisho and Taxler, G. (2016). Tracking the Diffusion of Crop Varieties Using DNA Fingerprinting. Research Report 112.
[6]	Dixon, J., Nalley, L., Kosina, P., Larovere, R., Hellin, J. and Aquino, P. (2006). Adoption and economic impact of improved wheat varieties in the developing world. Journal of Agricultural Science, 144: 489–502.
[7]	Feder G., Just, R. E. and Zilberman, D. (1985). Adoption of agricultural innovations in developing countries: A survey. Economic Development and Cultural Change, 33 (2): 255-298.
[8]	Feder, G. and O’mara, G. T. (1981). Farm size and the diffusion of green revolution technology. Economic Development and Cultural Change, 30: 59–76.
[9]	Heisey, P. and Mwangi, W. (1993). An overview of measuring research impacts assessment. In Impacts on Farm Research. Proceedings of a Net workshop on Impacts on Farm Research in Eastern Africa (In edition: Heisey, P. and Waddington, S.): 28–36.
[10]	Karlan, D., Osei, R., Osei-Akoto, I. and Udry, C. (2014). Agricultural decisions after relaxing credit and risk constraints. The Quarterly Journal of Economics, 129: 597–652.
[11]	Krishna V. V., Spielman, D. J., and Veettil, P. C. (2015). Exploring the supply and demand factors of varietal turnover in Indian wheat. Journal of Agricultural Science, 154: 258–272.
[12]	Langyintuo, A. and Mulugeta Mekuria (2008). Assessing the influence of neighborhood effects on the adoption of improved agricultural technologies in developing agriculture. African Journal of Agricultural Research, 2 (2): 151-169.
[13]	Langyintuo, A. S. and Mulugeta Mekuria (2005a). Accounting for neighborhood influence in estimating factors determining the adoption of improved agricultural technologies. Selected Paper prepared for presentation at the American Agricultural Economics Association Annual Meeting, Providence, Rhode Island, July 24-27, 2005.
[14]	Maredia, M., and Reyes, B. (2015). Agriculture in an Interconnected World. International Conference of Agricultural Economists. Universita Degli Studi Di Milano, August 8-14.
[15]	Mose, L. O., Onyango, L., Rono, S., Kute, C. and Ruto, C. R. (2000). “Factors that influence the adoption of organic and inorganic fertilizers in maize and kales in north rift valley region of Kenya.”In Participatory Technology Development for Soil Management. Proceeding of 2nd Scientific Conference of Soil management and Legume Research Network Projects. Mombasa, 384-392.
[16]	Polson, R. A. and Spencer, D. S. C. (1991). The technology adoption process in subsistence agriculture: the case of cassava in South Western Nigeria. Agricultural Systems, 36: 65-77.
[17]	Salasya, B., Mwangi, W., Mwabu, D. and Diallo, A. (2007). Factors influencing adoption of stress-tolerant maize hybrid (WH 502) in Western Kenya. African Journal of Agricultural Research, 2 (10): 544-551.
[18]	Wanyoike, F. N., Karugia, J. T. and Kimenye, L. N. (2000). “A gender Differentiated Analysis of Adoption of Improved Fodder trees (Caliandra calothyrsus) by Smallholder Farmers in Embu district.” In Collaborative and Participatory Research for Sustainably Improved livelihoods. Proceedings of 7th Biennial Scientific Conference. KARI Headquaters, Nairobi: 215-219.

Cite This Article

Plain Text BibTeX RIS

APA Style

Guta Bukero. (2023). Determinants of Maize (Zea mays L.) Varietal Turnover in Ethiopia. International Journal of Applied Agricultural Sciences, 9(1), 21-30. https://doi.org/10.11648/j.ijaas.20230901.15

Copy | Download

ACS Style

Guta Bukero. Determinants of Maize (Zea mays L.) Varietal Turnover in Ethiopia. Int. J. Appl. Agric. Sci. 2023, 9(1), 21-30. doi: 10.11648/j.ijaas.20230901.15

Copy | Download

AMA Style

Guta Bukero. Determinants of Maize (Zea mays L.) Varietal Turnover in Ethiopia. Int J Appl Agric Sci. 2023;9(1):21-30. doi: 10.11648/j.ijaas.20230901.15

Copy | Download

@article{10.11648/j.ijaas.20230901.15,
  author = {Guta Bukero},
  title = {Determinants of Maize (Zea mays L.) Varietal Turnover in Ethiopia},
  journal = {International Journal of Applied Agricultural Sciences},
  volume = {9},
  number = {1},
  pages = {21-30},
  doi = {10.11648/j.ijaas.20230901.15},
  url = {https://doi.org/10.11648/j.ijaas.20230901.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijaas.20230901.15},
  abstract = {While many smallholder farmers all over the developing countries have benefited from the introduction of first-generation green revolution cultivars that replaced lower-yielding landraces, adoption of second and third-generation cultivars offering improvements in yield, output quality, and stress resistance seems now to be occurring at a much slower pace. Most varietal adoption and impact assessment studies in the past have relied on farmers’ responses at household level surveys to estimate these indicators. Such method of ‘farmer elicitation’ to estimate varietal adoption can be fairly accurate in a setting where farmers are mostly planting seeds freshly purchased or acquired from the formal seed market as certified or truthfully labeled seed, and the seed system is well-functioning and effective in monitoring the quality and genetic identity of varieties being sold by the seed suppliers. Thus, this study focused on varietal turnover by calculating an index of the weighted average age of varieties grown by farmers in a given year (measured in years since release) and factors affecting this varietal turnover, using a recently collected DNA fingerprinting dataset. Secondary data from the household survey data collected by Central Statistical Agency were used in the analysis. The multiple linear regression models were used in identifying determinants of maize cultivars varietal turnover. Econometric results indicate that, Farmers’ experience in growing maize affects WA weakly and statistically significant and positive. This implies that more experienced farmers are refusing to change their varieties as they are small holders and so risk averse. Family size being positively affecting varietal turnover also implies that if the decision to cultivate a new variety requires consensus among key family members who are involved in farming, then idea generation and making decision may become more difficult and taking time, causing households to forgo varietal turnover in order to avoid disagreement.},
 year = {2023}
}

Copy | Download

TY  - JOUR
T1  - Determinants of Maize (Zea mays L.) Varietal Turnover in Ethiopia
AU  - Guta Bukero
Y1  - 2023/02/27
PY  - 2023
N1  - https://doi.org/10.11648/j.ijaas.20230901.15
DO  - 10.11648/j.ijaas.20230901.15
T2  - International Journal of Applied Agricultural Sciences
JF  - International Journal of Applied Agricultural Sciences
JO  - International Journal of Applied Agricultural Sciences
SP  - 21
EP  - 30
PB  - Science Publishing Group
SN  - 2469-7885
UR  - https://doi.org/10.11648/j.ijaas.20230901.15
AB  - While many smallholder farmers all over the developing countries have benefited from the introduction of first-generation green revolution cultivars that replaced lower-yielding landraces, adoption of second and third-generation cultivars offering improvements in yield, output quality, and stress resistance seems now to be occurring at a much slower pace. Most varietal adoption and impact assessment studies in the past have relied on farmers’ responses at household level surveys to estimate these indicators. Such method of ‘farmer elicitation’ to estimate varietal adoption can be fairly accurate in a setting where farmers are mostly planting seeds freshly purchased or acquired from the formal seed market as certified or truthfully labeled seed, and the seed system is well-functioning and effective in monitoring the quality and genetic identity of varieties being sold by the seed suppliers. Thus, this study focused on varietal turnover by calculating an index of the weighted average age of varieties grown by farmers in a given year (measured in years since release) and factors affecting this varietal turnover, using a recently collected DNA fingerprinting dataset. Secondary data from the household survey data collected by Central Statistical Agency were used in the analysis. The multiple linear regression models were used in identifying determinants of maize cultivars varietal turnover. Econometric results indicate that, Farmers’ experience in growing maize affects WA weakly and statistically significant and positive. This implies that more experienced farmers are refusing to change their varieties as they are small holders and so risk averse. Family size being positively affecting varietal turnover also implies that if the decision to cultivate a new variety requires consensus among key family members who are involved in farming, then idea generation and making decision may become more difficult and taking time, causing households to forgo varietal turnover in order to avoid disagreement.
VL  - 9
IS  - 1
ER  -

Copy | Download

Author Information

Guta Bukero

Ethiopian Institute of Agricultural Research, Wondo Genet Agricultural Research Centre, Shashemene, Ethiopia

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Guta Bukero. (2023). Determinants of Maize (Zea mays L.) Varietal Turnover in Ethiopia. International Journal of Applied Agricultural Sciences, 9(1), 21-30. https://doi.org/10.11648/j.ijaas.20230901.15

Copy | Download

ACS Style

Guta Bukero. Determinants of Maize (Zea mays L.) Varietal Turnover in Ethiopia. Int. J. Appl. Agric. Sci. 2023, 9(1), 21-30. doi: 10.11648/j.ijaas.20230901.15

Copy | Download

AMA Style

Guta Bukero. Determinants of Maize (Zea mays L.) Varietal Turnover in Ethiopia. Int J Appl Agric Sci. 2023;9(1):21-30. doi: 10.11648/j.ijaas.20230901.15

Copy | Download

@article{10.11648/j.ijaas.20230901.15,
  author = {Guta Bukero},
  title = {Determinants of Maize (Zea mays L.) Varietal Turnover in Ethiopia},
  journal = {International Journal of Applied Agricultural Sciences},
  volume = {9},
  number = {1},
  pages = {21-30},
  doi = {10.11648/j.ijaas.20230901.15},
  url = {https://doi.org/10.11648/j.ijaas.20230901.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijaas.20230901.15},
  abstract = {While many smallholder farmers all over the developing countries have benefited from the introduction of first-generation green revolution cultivars that replaced lower-yielding landraces, adoption of second and third-generation cultivars offering improvements in yield, output quality, and stress resistance seems now to be occurring at a much slower pace. Most varietal adoption and impact assessment studies in the past have relied on farmers’ responses at household level surveys to estimate these indicators. Such method of ‘farmer elicitation’ to estimate varietal adoption can be fairly accurate in a setting where farmers are mostly planting seeds freshly purchased or acquired from the formal seed market as certified or truthfully labeled seed, and the seed system is well-functioning and effective in monitoring the quality and genetic identity of varieties being sold by the seed suppliers. Thus, this study focused on varietal turnover by calculating an index of the weighted average age of varieties grown by farmers in a given year (measured in years since release) and factors affecting this varietal turnover, using a recently collected DNA fingerprinting dataset. Secondary data from the household survey data collected by Central Statistical Agency were used in the analysis. The multiple linear regression models were used in identifying determinants of maize cultivars varietal turnover. Econometric results indicate that, Farmers’ experience in growing maize affects WA weakly and statistically significant and positive. This implies that more experienced farmers are refusing to change their varieties as they are small holders and so risk averse. Family size being positively affecting varietal turnover also implies that if the decision to cultivate a new variety requires consensus among key family members who are involved in farming, then idea generation and making decision may become more difficult and taking time, causing households to forgo varietal turnover in order to avoid disagreement.},
 year = {2023}
}

Copy | Download

TY  - JOUR
T1  - Determinants of Maize (Zea mays L.) Varietal Turnover in Ethiopia
AU  - Guta Bukero
Y1  - 2023/02/27
PY  - 2023
N1  - https://doi.org/10.11648/j.ijaas.20230901.15
DO  - 10.11648/j.ijaas.20230901.15
T2  - International Journal of Applied Agricultural Sciences
JF  - International Journal of Applied Agricultural Sciences
JO  - International Journal of Applied Agricultural Sciences
SP  - 21
EP  - 30
PB  - Science Publishing Group
SN  - 2469-7885
UR  - https://doi.org/10.11648/j.ijaas.20230901.15
AB  - While many smallholder farmers all over the developing countries have benefited from the introduction of first-generation green revolution cultivars that replaced lower-yielding landraces, adoption of second and third-generation cultivars offering improvements in yield, output quality, and stress resistance seems now to be occurring at a much slower pace. Most varietal adoption and impact assessment studies in the past have relied on farmers’ responses at household level surveys to estimate these indicators. Such method of ‘farmer elicitation’ to estimate varietal adoption can be fairly accurate in a setting where farmers are mostly planting seeds freshly purchased or acquired from the formal seed market as certified or truthfully labeled seed, and the seed system is well-functioning and effective in monitoring the quality and genetic identity of varieties being sold by the seed suppliers. Thus, this study focused on varietal turnover by calculating an index of the weighted average age of varieties grown by farmers in a given year (measured in years since release) and factors affecting this varietal turnover, using a recently collected DNA fingerprinting dataset. Secondary data from the household survey data collected by Central Statistical Agency were used in the analysis. The multiple linear regression models were used in identifying determinants of maize cultivars varietal turnover. Econometric results indicate that, Farmers’ experience in growing maize affects WA weakly and statistically significant and positive. This implies that more experienced farmers are refusing to change their varieties as they are small holders and so risk averse. Family size being positively affecting varietal turnover also implies that if the decision to cultivate a new variety requires consensus among key family members who are involved in farming, then idea generation and making decision may become more difficult and taking time, causing households to forgo varietal turnover in order to avoid disagreement.
VL  - 9
IS  - 1
ER  -

Copy | Download