Hostname: page-component-cd9895bd7-mkpzs Total loading time: 0 Render date: 2024-12-27T07:54:35.072Z Has data issue: false hasContentIssue false
  • English
  • Français

Dealing with farmers’ Ethnolinguistic differences when collecting crop diversity on-farm

Published online by Cambridge University Press:  28 March 2016

Joseph Ireri Kamau ,
Vanesse Labeyrie ,
Grace Njeri Njoroge ,
Anthony Kibira Wanjoya ,
Peterson Weru Wambugu ,
Zachary Kithinji Muthamia  and
Christian Leclerc
Joseph Ireri Kamau
Affiliation:
KALRO-Genetic Resources Research Institute, P.O. Box 30148-0100, Nairobi, Kenya
Vanesse Labeyrie
Affiliation:
CIRAD, UMR AGAP, F-34398 Montpellier, France
Grace Njeri Njoroge
Affiliation:
Jomo Kenyatta University of Agriculture & Technology, P.O. Box 62000-00200, Nairobi, Kenya
Anthony Kibira Wanjoya
Affiliation:
Jomo Kenyatta University of Agriculture & Technology, P.O. Box 62000-00200, Nairobi, Kenya
Peterson Weru Wambugu
Affiliation:
KALRO-Genetic Resources Research Institute, P.O. Box 30148-0100, Nairobi, Kenya
Zachary Kithinji Muthamia
Affiliation:
KALRO-Genetic Resources Research Institute, P.O. Box 30148-0100, Nairobi, Kenya
Christian Leclerc*
Affiliation:
CIRAD, UMR AGAP, F-34398 Montpellier, France
*
*Corresponding author. E-mail: christian.leclerc@cirad.fr
Get access Rights & Permissions [Opens in a new window]

Abstract

Identification and characterization of the farmers’ named crop varieties cultivated around the world is a major issue for conservation and sustainable use of plant genetic resources. Intraspecific diversity is strongly determined by farmers’ socio-cultural environment, but this has little been documented. In this paper, we tested, on a contact zone among three ethnolinguistic groups located on the Mount Kenya region, whether farmers’ socio-cultural differences have an impact on the morphological characteristics of the farmers’ named sorghum varieties. Eighteen qualitative morphological traits of the panicles were measured. We first compared the morphological diversity of the named varieties among ethnolinguistic groups using multivariate analysis of homogeneity of groups’ dispersion and tested their differentiation using permutational multivariate analysis of variance. Discriminant analysis of principal components was then used to categorize the morphological diversity without a priori, and this classification was compared with farmers’ local taxonomy (vernacular names) in the three ethnolinguistic groups. Our results show that some morphotypes are peculiar to some ethnolinguistic groups and that a morphotype can bear different variety names while the same variety name can be used to identify different morphotypes. Morphological differentiation that was explained by ethnolinguistic groups was higher for local landraces than for improved varieties. Our findings imply that socio-cultural diversity of farmers and the criteria they use to identify and maintain landraces need to be considered in studying and sampling crop diversity for in situ as well as for ex situ conservation.

Keywords

cultural diversityFarmers’ variety naming systemKenyamorphological diversityPGR conservationsampling strategysorghum
Type
Research Article
Information
Plant Genetic Resources , Volume 15 , Issue 5 , October 2017 , pp. 400 - 408
Copyright
Copyright © NIAB 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Anderson, MJ (2001) A new method for non-parametric multivariate analysis of variance. Austral Ecology 26: 32–46.Google Scholar
Anderson, MJ (2006) Distance-based tests for homogeneity of multivariate dispersions. Biometrics 62: 245–253.CrossRefGoogle ScholarPubMed
Anderson, MJ, Ellingsen, KE and McArdle, BH (2006) Multivariate dispersion as a measure of beta diversity. Ecology Letters 9: 683–693.Google Scholar
Barnaud, A, Deu, M, Garine, E, McKey, D and Joly, HI (2007) Local genetic diversity of sorghum in a village in Northern Cameroon: structure and dynamics of landraces. Theoretical and Applied Genetics 114: 237–248.Google Scholar
Barth, F (1969) Ethnic Groups and Boundaries. The Social Organization of Culture Difference. Long Grove, Illinois: Little, Brown & Co.Google Scholar
Boster, JS (1986) Exchange of varieties and information between Aguaruna Manioc cultivators. American Anthropologist 88: 428–436.Google Scholar
Brush, SB (1995) In situ conservation of landraces in centers of crop diversity. Crop Science 35: 346–354.CrossRefGoogle Scholar
Brush, SB (2000) Genes in the Field: on-Farm Conservation of Crop Diversity. Ottawa, Canada: IDRC.Google Scholar
Camberlin, P, Boyard-Michaud, J, Philippon, N, Baron, C, Leclerc, C and Mwongera, C (2014) Climatic gradients along the windward slopes of Mount Kenya and their implication for crop risks. Part 1: climate variability. International Journal of Climatology 34: 2136–2152. doi: 10.1002/joc.3427 Google Scholar
de Wet, JMJ (1978) Systematics and evolution of Sorghum (Gramineae). American Journal of Botany 65: 477–484.Google Scholar
Harlan, J and de Wet, JMJ (1972) A simplified classification of cultivated sorghum. Crop Science 12: 172–176.CrossRefGoogle Scholar
IPGRI (1993) Descriptors for Sorghum [Sorghum bicolor (L.) Moench]. Rome, Italy: IBP-GR/ICRISAT.Google Scholar
Jaetzold, R, Schmidt, H, Hornetz, B and Shisanya, C (2007) Farm Management Handbook of Kenya (2nd edition), vol.II, part C East Kenya. Natural Conditions and Farm Management Information. Nairobi: Ministry of Agriculture.Google Scholar
Jombart, T (2008) adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics 24: 1403–1405.CrossRefGoogle Scholar
Jombart, T, Devillard, S and Balloux, F (2010) Discriminant analysis of principal components: a new method for the analysis of genetically structured populations. BMC Genetics 11: 94.Google Scholar
Labeyrie, V, Deu, M, Barnaud, A, Calatayud, C, Buiron, M, Wambugu, P, … Leclerc, C (2014a) Influence of ethnolinguistic diversity on the sorghum genetic patterns in subsistence farming systems in Eastern Kenya. PLoS ONE 9: e92178. doi: 10.1371/journal.pone.0092178 CrossRefGoogle ScholarPubMed
Labeyrie, V, Rono, B and Leclerc, C (2014b) How social organization shapes crop diversity: an ecological anthropology approach among Tharaka farmers of Mount Kenya. Agriculture and Human Values 31: 97–107.Google Scholar
Leclerc, C and Coppens d'Eeckenbrugge, G (2012) Social organization of crop genetic diversity. The GxExS interaction model. Diversity 4: 1–32. doi: 10.3390/d401001 Google Scholar
Leclerc, C, Mwongera, C, Camberlin, P and Moron, V (2014) Cropping system dynamics, climate variability, and seed losses among East African smallholder farmers: a retrospective survey. Weather, Climate and Society 6: 354–370. doi: 10.1175/WCAS-D-13-00035.1 Google Scholar
Lewis, MP, Simons, GF and Fennig, CD (2009) Ethnologue: Languages of the World. (Vol. 9). Dallas, Texas: SIL international.Google Scholar
Middleton, J and Kershaw, G (1965) The Central Tribes of the North-eastern Bantu: The Kikuyu, Including Embu, Meru, Mbere, Chuka, Mwimbi, Tharaka, and the Kamba of Kenya. London: International African Institute.Google Scholar
Mokuwa, A, Nuijten, E, Okry, F, Teeken, B, Maat, H, Richards, P and Struik, PC (2013) Robustness and strategies of adaptation among farmer varieties of African rice (Oryza glaberrima) and Asian rice (Oryza sativa) across West Africa. PloS ONE 8: e34801.Google Scholar
Mokuwa, A, Nuijten, E, Okry, F, Teeken, B, Maat, H, Richards, P and Struik, PC (2014) Processes underpinning development and maintenance of diversity in rice in West Africa: evidence from combining morphological and molecular markers.Google Scholar
Mwongera, C, Boyard-Michaud, J, Baron, C and Leclerc, C (2014) Social process of adaptation to environmental changes: how Eastern African societies intervene between crops and climate. Weather, Climate and Society 6: 341–353. doi: 10.1175/WCAS-D-13-00034.1 Google Scholar
Nuijten, E and Almekinders, CJ (2008) Mechanisms explaining variety naming by farmers and name consistency of rice varieties in the Gambia. Economic Botany 62: 148–160.Google Scholar
Oksanen, J, Kindt, R, Legendre, P, O'Hara, B, Stevens, MHH, Oksanen, MJ and Suggests, M (2015) The vegan package. Community Ecology Package version 2.3-0. http://CRAN.R-project.org/package=vegan Google Scholar
Perales, HR, Benz, BF and Brush, SB (2005) Maize diversity and ethnolinguistic diversity in Chiapas, Mexico. Proceedings of the National Academy of Sciences of the United States of America 102: 949–954.CrossRefGoogle ScholarPubMed
Pressoir, G and Berthaud, J (2004) Population structure and strong divergent selection shape phenotypic diversification in maize landraces. Heredity 92: 95–101.Google Scholar
Quiros, C, Brush, SB, Douches, DS, Zimmerer, KS and Huestis, G (1990) Biochemical and folk assessment of variability of Andean cultivated potatoes. Economic Botany 44: 254–266.Google Scholar
Rabbi, IY, Geiger, HH, Haussmann, BI, Kiambi, D, Folkertsma, R and Parzies, HK (2010) Impact of farmers’ practices and seed systems on the genetic structure of common sorghum varieties in Kenya and Sudan. Plant Genetic Resources 8: 116–126.CrossRefGoogle Scholar
Smale, M and Jayne, TS (2003) Maize in Eastern and Southern Africa: “seeds” of success in retrospect. EPTD Discussion 97: 1–87.Google Scholar
Smale, M, Byerlee, D and Jayne, T (2011) Maize Revolutions in Sub-Saharan Africa. World Bank Policy Research Working Paper Series 5659: 1–32.Google Scholar
Team, RC (2014) R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. 2012. ISBN 3-900051-07-0.Google Scholar
Xie, Y (2013) knitr: a general-purpose package for dynamic report generation in R. R Package Version 1: 1–11.Google Scholar
Supplementary material: Image

Kamau supplementary material S1

Kamau supplementary material

Download Kamau supplementary material S1(Image)
Image 78.4 KB
Supplementary material: Image

Kamau supplementary material S2

Kamau supplementary material

Download Kamau supplementary material S2(Image)
Image 126.5 KB
Supplementary material: Image

Kamau supplementary material S3

Kamau supplementary material

Download Kamau supplementary material S3(Image)
Image 70.7 KB
Supplementary material: Image

Kamau supplementary material S4

Kamau supplementary material

Download Kamau supplementary material S4(Image)
Image 70.2 KB
Supplementary material: Image

Kamau supplementary material S5

Kamau supplementary material

Download Kamau supplementary material S5(Image)
Image 85.8 KB
Supplementary material: Image

Kamau supplementary material S6

Kamau supplementary material

Download Kamau supplementary material S6(Image)
Image 94.5 KB
Supplementary material: File

Kamau supplementary material S7

Kamau supplementary material

Download Kamau supplementary material S7(File)
File 544.8 KB