banana systems in sub-saharan africa

Banana Systems in the Humid Highlands of Sub-Saharan Africa

Enhancing Resilience and Productivity

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Banana Systems in the Humid Highlands of Sub-Saharan Africa

Enhancing Resilience and Productivity

Edited by

Guy Blomme

Bioversity International, Uganda

Piet van Asten

International Institute of Tropical Agriculture, Uganda

and

Bernard Vanlauwe

International Institute of Tropical Agriculture, Kenya

CABI is a trading name of CAB International

CABI CABINosworthy Way 38 Chauncey StreetWallingford Suite 1002Oxfordshire OX10 8DE Boston, MA 02111UK USA

Tel: +44 (0)1491 832111 Tel: +1 800 552 3083 (toll free)Fax: +44 (0)1491 833508 Tel: +1 617 395 4051E-mail: [email protected] E-mail: [email protected]: www.cabi.org

CAB International 2013. All rights reserved. No part of this publication may be reproduced in any form or by any means, electronically, mechanically, by photocopying, recording or otherwise, without the prior permission of the copyright owners.

A catalogue record for this book is available from the British Library, London, UK.

Library of Congress Cataloging-in-Publication Data

Banana systems in the humid highlands of Sub-Saharan Africa enhancing resilience and productivity / edited by Guy Blomme, Piet van Asten and Bernard Vanlauwe. p. cm. Includes bibliographical references and index. ISBN 978-1-78064-231-4 (alk. paper) 1. Bananas--Africa, Sub-Saharan. 2. Plantain banana--Africa, Sub-Saharan. I. Blomme, G. II. Asten, Piet van, 1972- III. Vanlauwe, B. (Bernard)

SB379.B2B3493 2013 634'.7720967--dc23

2013016574ISBN-13: 978 1 78064 231 4

Commissioning editor: Claire ParfittEditorial assistants: Emma McCann and Alexandra LainsburyProduction editor: Shankari Wilford

Typeset by SPi, Pondicherry, IndiaPrinted and bound in the UK by CPI Group (UK) Ltd, Croydon, CR0 4YY
www.cabi.org

The book evolved from an international conference that was organized by the Consortium for Improving Agriculture-based Livelihoods in Central Africa (CIALCA) and was held in Kigali, Rwanda, from 24 to 27 October 2011. The conference addressed the challenges and opportunities for agricultural intensification of the humid highland systems of sub-Saharan Africa.

CIALCA is a Consortium of the International Agricultural Research Centers (IARCs) and their national research and development partners that aims at close technical and administra-tive collaboration and planning in areas of common interest, thereby enhancing returns to the investments made by DGD, Belgium and accelerating impact at the farm level.

The cover photo of the book was taken by Concretedreams (Sophie Spillemaeckers and Ludovic Schweitzer).

CIALCA is coordinated by three CGIAR institutions: Bioversity International, the International Center for Tropical Agriculture (CIAT) and the International Institute of Tropical Agriculture (IITA) in collaboration with Belgian Universities and national agricultural research and develop-ment partners.

Financial contributions to the conference were made by:

Contributors xi

Preface xvii

Acknowledgements xix

PART 1: MUSA GERMPLASM DIVERSITY AND EVALUATION

1 Plantain Collection and Morphological Characterization in Democratic Republic of Congo: Past and Present Activities and Prospects 1 J.G. Adheka, D.B. Dheda, C. Sivirihauma, D. Karamura, E. De Langhe, R. Swennen and G. Blomme

2 Musa Germplasm Diversity Status across a Wide Range of Agro-ecological Zones in Rwanda, Burundi and Eastern Democratic Republic of Congo 8 W. Ocimati, D. Karamura, A. Rutikanga, C. Sivirihauma, V. Ndungo, J. Adheka, D.B. Dheda, H. Muhindo, J. Ntamwira, S. Hakizimana, F. Ngezahayo, P. Ragama, P. Lepoint, J.-P. Kanyaruguru, E. De Langhe, S.V. Gaidashova, A. Nsabimana, C. Murekezi and G. Blomme

3 Banana Genotype Composition along the UgandaDemocratic Republic of Congo Border: A Gene Pool Mix for Plantain and Highland Bananas 22D. Karamura, W. Ocimati, R. Ssali, W. Jogo, S. Walyawula and E. Karamura

4 Analysis of Farmer-preferred Traits as a Basis for Participatory Improvement of East African Highland Bananas in Uganda 30A. Barekye, P. Tongoona, J. Derera, M.D. Laing and W.K. Tushemereirwe

5 Agronomic Evaluation of Common and Improved Dessert Banana Cultivars at Different Altitudes across Burundi 37 M. Kamira, R.J. Crichton, J.-P. Kanyaruguru, P.J.A. van Asten, G. Blomme, J. Lorenzen, E. Njukwe, I. Van den Bergh, E. Ouma and P. Muchunguzi

Contents

vii

6 Growth and Yield of Plantain Cultivars at Four Sites of Differing Altitude in North Kivu, Eastern Democratic Republic of Congo 48 I. Sikyolo, C. Sivirihauma, V. Ndungo, E. De Langhe, W. Ocimati and G. Blomme

PART 2: NOVEL SEED SYSTEMS

7 Macropropagation of Musa spp. in Burundi: A Preliminary Study 58P. Lepoint, F. Iradukunda and G. Blomme

8 Challenges and Opportunities for Macropropagation Technology for Musa spp. among Smallholder Farmers and Small- and Medium-scale Enterprises 66E. Njukwe, E. Ouma, P.J.A. van Asten, P. Muchunguzi and D. Amah

9 Impact of Arbuscular Mycorrhizal Fungi on Growth of Banana Genotypes in Three Different, Pasteurized and Non-pasteurized Soils of Rwanda 72S.V. Gaidashova, A. Nsabimana, P.J.A. van Asten, B. Delvaux, A. Elsen and S. Declerck

10 Indigenous Arbuscular Mycorrhizal Fungi and Growth of Tissue-cultured Banana Plantlets under Nursery and Field Conditions in Rwanda 83 J.M. Jefwa, E. Rurangwa, S.V. Gaidashova, A.M. Kavoo, M. Mwashasha, J. Robinson, G. Blomme and B. Vanlauwe

PART 3: BANANA PESTS AND DISEASES

11 Development of ELISA for the Detection of Xanthomonas campestris pv. musacearum, the Causal Agent of BXW: Banana Xanthomonas Wilt 93G.V. Nakato, S.A. Akinbade, P. Lava Kumar, R. Bandyopadhyay and F. Beed

12 Systemicity and Speed of Movement of Xanthomonas campestris pv. musacearum in the Banana Plant after Garden Tool-mediated Infection 101 W. Ocimati, F. Ssekiwoko, M. Buttibwa, E. Karamura, W. Tinzaara, S. Eden-Green and G. Blomme

13 Use of DNA Capture Kits to Collect Xanthomonas campestris pv. musacearum and Banana Bunchy Top Virus Pathogen DNA for Molecular Diagnostics 109I. Ramathani and F. Beed

14 Banana Xanthomonas Wilt Management: Effectiveness of Selective Mat Uprooting Coupled with Control Options for Preventing Disease Transmission. Case Study in Rwanda and Eastern Democratic Republic of Congo 116 A. Rutikanga, C. Sivirihauma, C. Murekezi, U. Anuarite, V. Ndungo, W. Ocimati, J. Ntamwira, P. Lepoint and G. Blomme

viii Contents

Contents ix

15 Effect of Length of Fallow Period after Total Uprooting of a Xanthomonas Wilt-infected Banana Field on Infection of Newly Established Planting Materials: Case Studies from Rwanda and Eastern Democratic Republic of Congo 125 C. Sivirihauma, A. Rutikanga, C. Murekezi, G. Blomme, U. Anuarite, W. Ocimati, P. Lepoint and V. Ndungo

16 Distribution, Incidence and Farmer Knowledge of Banana Xanthomonas Wilt in Rwanda 131 G. Night, S.V. Gaidashova, A. Nyirigira, Theodomir Mugiraneza, A. Rutikanga, C. Murekezi, A. Nduwayezu, E. Rurangwa, Thierry Mugiraneza, F. Mukase, O. Ndayitegeye, W. Tinzaara, E. Karamura, W. Jogo, I. Rwomushana, F. Opio and D. Gahakwa

17 Xanthomonas Wilt Incidence in Banana Plots Planted with Asymptomatic Suckers from a Diseased Field Compared with Plots Using Suckers from a Disease-free Zone in North Kivu, Eastern Democratic Republic of Congo 138C. Sivirihauma, N. Ndungo, W. Ocimati and G. Blomme

PART 4: BANANA INTERCROPPING SYSTEMS

18 Coffee/Banana Intercropping as an Opportunity for Smallholder Coffee Farmers in Uganda, Rwanda and Burundi 144 L. Jassogne, A. Nibasumba, L. Wairegi, P.V. Baret, J. Deraeck, D. Mukasa, I. Wanyama, G. Bongers and P.J.A. van Asten

19 The Use of Trees and Shrubs to Improve Banana Productivity and Production in Central Uganda: An Analysis of the Current Situation 150 S. Mpiira, C. Staver, G.H. Kagezi, J. Wesiga, C. Nakyeyune, G. Ssebulime, J. Kabirizi, K. Nowakunda, E. Karamura and W.K. Tushemereirwe

20 Effect of Banana Leaf Pruning on Legume Yield in BananaLegume Intercropping Systems in Eastern Democratic Republic of Congo 158 J. Ntamwira, P. Pypers, P.J.A. van Asten, B. Vanlauwe, B. Ruhigwa, P. Lepoint and G. Blomme

21 A Comparative and Systems Approach to Banana Cropping Systems in the Great Lakes Region 166J. Van Damme, D. De Bouver, M. Dupriez, P.J.A. van Asten and P.V. Baret

22 Agronomic Practices for Musa across Different Agro-ecological Zones in Burundi, Eastern Democratic Republic of Congo and Rwanda 175 W. Ocimati, D. Karamura, A. Rutikanga, C. Sivirihauma, V. Ndungo, J. Ntamwira, M. Kamira, J.-P. Kanyaruguru and G. Blomme

PART 5: BANANA USE, POSTHARVEST AND NUTRITION

23 The Beer Banana Value Chain in Central Uganda 191A.M. Rietveld, S. Mpiira, W. Jogo, C. Staver and E.B. Karamura

24 Contribution of Bananas and Plantains to the Diet and Nutrition of Musa-dependent Households with Preschoolers in Beni and Bukavu Territories, Eastern Democratic Republic of Congo 202B.N. Ekesa, J. Kimiywe, M. Davey, C. Dhuique-Mayer, I. Van den Bergh and G. Blomme

PART 6: SURVEILLANCE, ADOPTION AND COMMUNICATING KNOWLEDGE

25 Processes and Partnerships for Effective Regional Surveillance of Banana Diseases 210 F. Beed, J. Kubiriba, A. Mugalula, H. Kolowa, S. Bulili, A. Nduwayezu, C. Murekezi, E. Sakayoya, P. Ndayihanzamaso, R. Mulenga, M. Abass, L. Mathe, B. Masheka, M. Onyango, E. Shitabule, V. Nakato, I. Ramathani and H. Bouwmeester

26 Adoption and Impact of Tissue Culture Bananas in Burundi: An Application of a Propensity Score Matching Approach 216E. Ouma, T. Dubois, N. Kabunga, S. Nkurunziza, M. Qaim and P.J.A. van Asten

27 Communication Approaches for Sustainable Management of Banana Xanthomonas Wilt in East and Central Africa 224W. Tinzaara, E. Karamura, G. Blomme, W. Jogo, W. Ocimati and J. Kubiriba

28 A Global Information and Knowledge Sharing Approach to Facilitate the Wider Use of Musa Genetic Resources 235N. Roux, M. Ruas and B. Lalibert

Index 241

x Contents

xi

Contributors

M. Abass, Ministry of Agriculture and Livestock (MAL), Lusaka, Zambia.J.G. Adheka, Laboratoire de Gntique, Amlioration des Plantes et Biotechnologies, Facult

des Sciences, Universit de Kisangani (UNIKIS), Kisangani, Democratic Republic of Congo. E-mail: [email protected]

S.A. Akinbade, International Institute of Tropical Agriculture (IITA), PMB 5320, Oyo Road, Ibadan, Nigeria. Present address: Irrigated Agriculture Research and Extension Center, Washington State University, Prosser, WA 99350, USA.

D. Amah, International Institute of Tropical Agriculture (IITA), PMB 5320, Oyo Road, Ibadan, Nigeria. E-mail: [email protected]

U. Anuarite, Rwanda Agriculture Board (RAB), PO Box 5016, Kigali, Rwanda. E-mail: [email protected]

R. Bandyopadhyay, International Institute of Tropical Agriculture (IITA), PMB 5320, Oyo Road, Ibadan, Nigeria. E-mail: [email protected]

A. Barekye, African Centre for Crop Improvement, School of Agricultural Sciences and Agri-business, University of KwaZulu-Natal, P/Bag X01, Pietermaritzburg, 3209, South Africa and National Banana Research Programme, National Agricultural Research Organisation (NARO), PO Box 7065, Kampala, Uganda. E-mail: [email protected]

P.V. Baret, Earth and Life Institute, Universit Catholique de Louvain (UCL), Croix du Sud, 2 L7.05.14, 1348 Louvain-la-Neuve, Belgium. E-mail: [email protected]

F. Beed, International Institute of Tropical Agriculture (IITA), PO Box 7878, Kampala, Uganda. Present address: IITA, PO Box 34441, Dar es Salaam, Tanzania. E-mail: [email protected]

G. Blomme, Bioversity International, PO Box 24384, Kampala, Uganda. E-mail: [email protected]

G. Bongers, International Institute of Tropical Agriculture (IITA), PO Box 7878, Kampala, Uganda. E-mail: [email protected]

H. Bouwmeester, International Institute of Tropical Agriculture (IITA), PO Box 34441, Dar es Salaam, Tanzania. E-mail: [email protected]

S. Bulili, Maruku Agricultural Research Institute (ARI-Maruku), PO Box 127, Bukoba, Kagera, Tanzania. E-mail: [email protected]

M. Buttibwa, National Crops Resources Research Institute, National Agricultural Research Organisation (NARO), Namulonge, Uganda. E-mail: [email protected]

R.J. Crichton, Bioversity International, Parc Scientifique Agropolis II, 34397 Montpellier Cedex 5, France. E-mail: [email protected]

M. Davey, Katholieke Universiteit Leuven (KUL), Leuven, Belgium. E-mail: [email protected]

D. De Bouver, Earth and Life Institute, Universit Catholique de Louvain (UCL), Croix du Sud, 1348 Louvain-la-Neuve, Belgium. E-mail: [email protected]

S. Declerck, Earth and Life Institute, Mycology, Universit Catholique de Louvain (UCL), Croix du Sud, 2 bte L7.05.06, 1348 Louvain-la-Neuve, Belgium. E-mail: [email protected]

E. De Langhe, Laboratory of Tropical Crop Improvement, Katholieke Universiteit Leuven (KUL), Leuven, Belgium. E-mail: [email protected]

B. Delvaux, Universit Catholique de Louvain (UCL), 1348 Louvain-la-Neuve, Belgium. E-mail: [email protected]

J. Deraeck, Earth and Life Institute, Universit Catholique de Louvain (UCL), Croix du Sud, 2 L7.05.14, 1348 Louvain-la-Neuve, Belgium.

J. Derera, African Centre for Crop Improvement, School of Agricultural Sciences and Agribusi-ness, University of KwaZulu-Natal, P/Bag X01, Pietermaritzburg, 3209, South Africa.

D.B. Dheda, Laboratoire de Gntique, Amlioration des Plantes et Biotechnologies, Facult des Sciences, Universit de Kisangani (UNIKIS), Kisangani, Democratic Republic of Congo. E-mail: [email protected]

C. Dhuique-Mayer, La Recherche Agronomique pour le Dveloppement/Agricultural Research for Development (CIRAD), TA B-95/16, 73 rue Jean-Franois Breton, 34398 Montpellier Cedex 5, France. E-mail: [email protected]

T. Dubois, International Institute of Tropical Agriculture (IITA), PO Box 7878, Kampala, Uganda. E-mail: [email protected]

M. Dupriez, Earth and Life Institute, Universit Catholique de Louvain (UCL), 1348 Louvain- la-Neuve, Belgium. E-mail: [email protected]

S. Eden-Green, EG Consulting, 470 Lunsford Lane, Larkfield, Kent, ME20 6JA, UK. E-mail: [email protected]

B.N. Ekesa, Bioversity International, Plot 106, Katalima Road, PO Box, 24384, Kampala, Uganda. E-mail: [email protected]

A. Elsen, Soil Service of Belgium, 48 W. de Croylaan, 3001, Leuven, Belgium. E-mail: [email protected]

D. Gahakwa, Rwanda Agriculture Board (RAB), PO Box 5016, Kigali, Rwanda. E-mail: daphrose. [email protected]

S.V. Gaidashova, Rwanda Agricultural Board (RAB), PO Box 5016, Kigali, Rwanda. E-mail: [email protected]

S. Hakizimana, Institut de Recherche Agronomique et Zootechnique (IRAZ), Mashitsi, Burundi. E-mail: [email protected]

F. Iradukunda, Bioversity International, PO Box 1893, Bujumbura, Burundi and Universit du Burundi, Facult des Sciences Agronomiques, PO Box 2940, Bujumbura, Burundi. E-mail: [email protected]

L. Jassogne, International Institute of Tropical Agriculture (IITA), PO Box 7878, Kampala, Uganda and Earth and Life Institute, Universit Catholique de Louvain, Croix du Sud, 2 L7.05.14, 1348 Louvain-la-Neuve, Belgium. E-mail: [email protected]

J.M. Jefwa, Mycorrhizal Specialist, PO Box 0050-21872, Ngong Road, Nairobi, Kenya. E-mail: [email protected]

W. Jogo, Bioversity International, PO Box 24384, Kampala, Uganda. E-mail: [email protected]. Kabirizi, National Agricultural Research Organisation (NARO), PO Box 7065, Kampala, Uganda.N. Kabunga, International Food Policy Research Institute (IFPRI), PO Box 28565, Kampala,

Uganda. E-mail: [email protected]. Kagezi, National Agricultural Research Organisation (NARO), PO Box 7065, Kampala,

Uganda. E-mail: [email protected]

xii Contributors

Contributors xiii

M. Kamira, Bioversity International/CIALCA project, Bukavu, South Kivu, Democratic Republic of Congo. E-mail: [email protected]

J.-P. Kanyaruguru, Bioversity International/CIALCA project, PO Box 7180, Bujumbura, Burundi. E-mail: [email protected]

D. Karamura, Bioversity International, PO Box 24384, Kampala, Uganda. E-mail: [email protected]

E.B. Karamura, Bioversity International, P.O. Box 24384, Kampala, Uganda. E-mail: [email protected]

A.M. Kavoo, Jomo Kenyatta University of Agriculture and Technology (JKUAT), PO Box 62,000, 00200 Nairobi, Kenya.

J. Kimiywe, Kenyatta University (KU), PO Box 43844, 00100 Nairobi, Kenya.H. Kolowa, Ministry of Agriculture, Food Security and Cooperatives, PO Box 9192, Dar es

Salaam, TanzaniaJ. Kubiriba, National Banana Research Programme, Kawanda Agricultural Research Institute

(KARI), National Agricultural Research Organisation (NARO), PO Box 7065, Kampala, Uganda. E-mail: [email protected]

P. Lava Kumar, International Institute of Tropical Agriculture (IITA), PMB 5320, Ibadan, Nigeria. E-mail: [email protected]

M.D. Laing, African Centre for Crop Improvement, School of Agricultural Sciences and Agri-business, University of KwaZulu-Natal, P/Bag X01, Pietermaritzburg, 3209, South Africa.

B. Lalibert, Commodity Systems and Genetic Resources Programme, Bioversity Interna-tional, Parc Scientifique Agropolis II, Montpellier Cedex 5, 34397 France. E-mail: [email protected]

P. Lepoint, Bioversity International/CIALCA project, PO Box 7180, Bujumbura, Burundi. E-mail: [email protected]

J. Lorenzen, International Institute of Tropical Agriculture (IITA), PO Box 7878, Kampala, Uganda. E-mail: [email protected]

B. Masheka, Institut National pour lEtude et la Recherche Agronomique (INERA), Kinshasa, Democratic Republic of Congo.

L. Mathe, Universit Catholique du Graben (UCG), Butembo, North Kivu, Democratic Repub-lic of Congo. E-mail: [email protected]

S. Mpiira, Bioversity International, PO Box 24384, Kampala, Uganda and National Agricul-tural Research Organisation (NARO), PO Box 7065, Kampala, Uganda. E-mail: [email protected]

P. Muchunguzi, International Institute of Tropical Agriculture (IITA), BP 7878, Kampala, Uganda. E-mail: [email protected]

A. Mugalula, Ministry of Agriculture, Animal Industries and Fisheries (MAAIF), PO Box 34518, Kampala, Uganda.

Theodomir Mugiraneza, Centre for Geographic Information Systems and Remote Sensing, National University of Rwanda (NUR), PO Box 212, Huye, Rwanda.

Thierry Mugiraneza, Rwanda Agriculture Board (RAB), PO Box 5016, Kigali, Rwanda. E-mail: [email protected]

H. Muhindo, Institut Facultaire des Sciences Agronomiques (IFA-Yangambi), PO Box 1232, Kisangani, Democratic Republic of Congo. E-mail: [email protected]

D. Mukasa, International Institute of Tropical Agriculture (IITA), PO Box 7878, Kampala, Uganda. E-mail: [email protected]

F. Mukase, Rwanda Agriculture Board (RAB), PO Box 5016, Kigali, Rwanda.R. Mulenga, Zambia Agricultural Research Institute (ZARI), Lusaka, Zambia.C. Murekezi, Rwanda Agriculture Board (RAB), PO Box 5016, Kigali, Rwanda. E-mail:

[email protected]. Mwashasha, Jomo Kenyatta University of Agriculture and Technology (JKUAT), Juja, PO

Box 62,000, 00200 Nairobi, Kenya.

xiv Contributors

G.V. Nakato, International Institute of Tropical Agriculture (IITA), PO Box 7878, Kampala, Uganda. E-mail: [email protected]

C. Nakyeyune, SSC Vi Agroforestry, PO Box 1732, Kampala, Uganda.P. Ndayihanzamaso, Institut des Sciences Agronomique du Burundi (ISABU), Avenue de la

Cathdrale, BP 795, Bujumbura, Burundi. E-mail: [email protected]. Ndayitegeye, Rwanda Agriculture Board (RAB), PO Box 5016, Kigali, Rwanda.V. Ndungo, Universit Catholique du Graben (UCG), Butembo, North Kivu, Democratic

Republic of Congo. E-mail: [email protected]. Nduwayezu, Rwanda Agriculture Board (RAB), PO Box 5016, Kigali, Rwanda.F. Ngezahayo, Institut de Recherche Agronomique et Zootechnique (IRAZ), Mashitsi, Burundi.

E-mail: [email protected]. Nibasumba, International Institute of Tropical Agriculture (IITA), PO Box 7878, Kampala,

Uganda; Earth and Life Institute, Universit Catholique de Louvain (UCL), Croix du Sud, 2 L7.05.14, 1348 Louvain-la-Neuve, Belgium; and Institut des Sciences Agronomique du Burundi (ISABU), Avenue de la Cathdrale, BP 795, Bujumbura, Burundi.

G. Night, Rwanda Agriculture Board (RAB), PO Box 5016, Kigali, Rwanda. E-mail: [email protected]

E. Njukwe, International Institute of Tropical Agriculture (IITA), BP 7878 Kampala, Uganda and IITA-CIALCA, Bujumbura, Burundi. E-mail: [email protected]

S. Nkurunziza, International Institute of Tropical Agriculture (IITA), PO Box 7180, Bujumbura, Burundi.

K. Nowakunda, National Agricultural Research Organisation (NARO), PO Box 7065, Kampala, Uganda. E-mail: [email protected]

A. Nsabimana, Kigali Institute of Science and Technology (KIST), PO Box 3900, Kigali, Rwanda. E-mail: [email protected]

J. Ntamwira, Institut National pour lEtude et la Recherche Agronomique (INERA), Mulungu Research Station, Bukavu, South Kivu, PO Box 2037 Kinshasa 1, Avenue de Cliniques, Kinshasa-Gombe, Democratic Republic of Congo and Bioversity International/CIALCA Project, Bukavu, South Kivu, Democratic Republic of Congo. E-mail: [email protected]

A. Nyirigira, Rwanda Agriculture Board (RAB), PO Box 5016, Kigali, Rwanda.W. Ocimati, Bioversity International, PO Box 24384, Kampala, Uganda. E-mail: w.ocimati@

cgiar.orgM. Onyango, Kenya Agricultural Research Institute (KARI), Nairobi, Kenya. E-mail: maonyango

[email protected]. Opio, Association for Strengthening Agricultural Research in Eastern and Central Africa

(ASARECA), Entebbe, Uganda. E-mail: [email protected]. Ouma, International Institute of Tropical Agriculture (IITA), PO Box 7180, Bujumbura,

Burundi. E-mail: [email protected]. Pypers, Tropical Soil Biology and Fertility Institute of the International Center for Tropical

Agriculture (TSBF-CIAT), PO Box 30677, Nairobi, Kenya. E-mail: [email protected]. Qaim, Georg-August University of Gttingen, 37073 Gttingen, Germany.P. Ragama, Kabarak University, Private Bag 20157, Kabarak, Kenya. E-mail: peragama55@

yahoo.co.ukI. Ramathani, International Institute of Tropical Agriculture (IITA), PO Box 7878, Kampala,

Uganda. E-mail: [email protected]. Rietveld, Bioversity International, PO Box 24384, Kampala, Uganda. E-mail: a.rietveld@

cgiar.orgJ. Robinson, Jomo Kenyatta University of Agriculture and Technology (JKUAT), Juja, PO Box

62,000, 00200 Nairobi, Kenya.N. Roux, Commodity Systems and Genetic Resources Programme, Bioversity International,

Parc Scientifique Agropolis II, Montpellier Cedex 5, 34397 France. E-mail: [email protected]

Contributors xv

M. Ruas, Commodity Systems and Genetic Resources Programme, Bioversity International, Parc Scientifique Agropolis II, Montpellier Cedex 5, 34397 France. E-mail: [email protected]

B. Ruhigwa, Institut Facultaire des Sciences Agronomiques (IFA-Yangambi), PO Box 1232 Kisangani, Democratic Republic of Congo. E-mail: [email protected]

E. Rurangwa, Rwanda Agriculture Board (RAB), PO Box 5016, Kigali, Rwanda. E-mail: [email protected]

A. Rutikanga, Bioversity International/CIALCA project, Kigali, Rwanda. E-mail: [email protected]

I. Rwomushana, Association for Strengthening Agricultural Research in Eastern and Central Africa (ASARECA), Entebbe, Uganda.

E. Sakayoya, Dpartement de la Protection des Vgteaux (DPV), BP 114, Gitega, Burundi.E. Shitabule, Kenya Plant Health Inspectorate Services (KEPHIS), Nairobi, Kenya.I. Sikyolo, Universit Catholique du Graben (UCG), Butembo, North Kivu, Democratic

Republic of Congo. E-mail: [email protected]. Sivirihauma, Universit Catholique du Graben (UCG), Butembo, North Kivu, Democratic

Republic of Congo and Bioversity International/CIALCA project, Butembo, North Kivu, Democratic Republic of Congo. E-mail: [email protected]

R. Ssali, National Agricultural Research Organisation (NARO), PO Box 7065, Kampala, Uganda.G. Ssebulime, Kyankwanzi District Local Government, PO Box 90, Kiboga, Uganda.F. Ssekiwoko, National Banana Research Programme, Kawanda Agricultural Research Insti-

tute (KARI), National Agricultural Research Organisation (NARO), PO Box 7065, Kampala, Uganda. E-mail: [email protected]

C. Staver, Commodity Systems and Genetic Resources Programme, Bioversity International, Parc Scientifique Agropolis II, Montpellier Cedex 5, 34397 France. E-mail: [email protected]

R. Swennen, Laboratory of Tropical Crop Improvement, Katholieke Universiteit Leuven (KUL), Leuven, Belgium. E-mail: [email protected]

W. Tinzaara, Bioversity International, PO Box 24384, Kampala, Uganda. E-mail: [email protected]

P. Tongoona, African Centre for Crop Improvement, School of Agricultural Sciences and Agri-business, University of KwaZulu-Natal, P/Bag X01, Pietermaritzburg, 3209, South Africa.

W.K. Tushemereirwe, National Banana Research Programme, Kawanda Agricultural Research Institute (KARI), National Agricultural Research Organisation (NARO), PO Box 7065, Kampala, Uganda. E-mail: [email protected]

P.J.A. van Asten, International Institute of Tropical Agriculture (IITA), BP 7878, Kampala, Uganda. E-mail: [email protected]

J. Van Damme, Earth and Life Institute, Universit Catholique de Louvain (UCL), Croix du Sud, 1348 Louvain-la-Neuve, Belgium. E-mail: [email protected]

I. Van den Bergh, Commodity Systems and Genetic Resources Programme, Bioversity International, Parc Scientifique Agropolis II, Montpellier Cedex 5, 34397 France. E-mail: [email protected]

B. Vanlauwe, International Institute of Tropical Agriculture (IITA), c/o ICIPE, PO Box 30772-00100, Nairobi, Kenya. E-mail: [email protected]

N. Vigheri, Bioversity International/CIALCA project, Butembo, North Kivu, Democratic Republic of Congo. E-mail: [email protected]

L. Wairegi, International Institute of Tropical Agriculture (IITA), PO Box 7878, Kampala, Uganda and CAB International, ICRAF Complex, PO Box 633-00621,Nairobi, Kenya. E-mail: [email protected]

S. Walyawula, National Agricultural Research Organisation (NARO), PO Box 7065, Kampala, Uganda.

I. Wanyama, International Institute of Tropical Agriculture (IITA), PO Box 7878, Kampala, Uganda. E-mail: [email protected]

J. Wesiga, Volunteer Efforts for Development Concern (VEDCO), PO Box 1244, Kampala, Uganda.

xvii

Preface

Banana Systems in the Humid Highlands of Sub-Saharan Africa: Enhancing Resilience and Productivity addresses issues related to intensification of banana-based cropping systems in the (sub)humid highland areas of Africa. Bananas are a staple food in the East African highlands, where they have some of the highest per capita consumption rates in the world. The crop is a permanent source of food and income throughout the year for millions of smallholder farmers. Its reliable and continuous production has spared the humid highland region from drought-induced famines that have plagued other areas in sub-Saharan Africa. Moreover, the permanent canopy cover and self-mulch of banana-based systems also prevent run-off and erosion in this hilly landscape. However, in times of rapid population growth, urbanization and increasing regional trade, actors in the private and public sector are particularly encouraging the production of easily tradable and storable dry foods such as maize. Bananas have further suffered from major pest and disease outbreaks over the past few years. Maintaining and enhancing the socio-economic and biophysical buffer function of banana-based systems has, therefore, become a formidable challenge that affects the livelihoods of millions of poor producers and consumers in the region.

This book brings together key contributions on banana-based systems that were pre-sented as part of an international conference that was organized by the Consortium for Improving Agriculture-based Livelihoods in Central Africa (CIALCA) and was held in Kigali, Rwanda, from 24 to 27 October 2011. The conference was entitled the Challenges and Opportunities for Agricultural Intensification of the Humid Highland Systems of sub- Saharan Africa. The information that is presented in the 28 chapters of the book is based on research carried out in the Great Lakes Region by CIALCA and partners, and is arranged in six sections. Part 1 covers banana germplasm, Part 2 innovative seed systems, Part 3 pests and diseases, Part 4 cropping systems, Part 5 postharvest use and nutrition, and Part 6 technology adoption and dissemination of knowledge. The book provides a valu-able resource for researchers, development actors, students and policy makers in agricul-tural systems and economics and in international development. It highlights and

addresses key challenges and opportunities that exist in maintaining and improving the vital buffer function that bananas provide in the agricultural systems of the humid high-lands of sub-Saharan Africa.

Guy BlommeBioversity International, Uganda

Piet van AstenInternational Institute of Tropical Agriculture, Uganda

Bernard VanlauweInternational Institute of Tropical Agriculture, Kenya

xviii Preface

xix

Special thanks go to Michael Bolton (consultant under contract to Bioversity International) and to David Turner (Associate Professor, Honorary Research Fellow, School of Plant Biology Faculty of Natural and Agricultural Sciences, The University of Western Australia) for their contributions to the scientific editing of all the chapters.

Acknowledgements

CAB International 2013. Banana Systems in the Humid Highlands of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe) 1

AbstractThe collection and morphological characterization of Musa spp. (bananas and plantains) started during the 1950s in the Democratic Republic of Congo (DR Congo) at the Institut National pour lEtude Agronomique du Congo (INEAC) Yangambi Research Station, where 56 plantain cultivars were established in a collection. Unfortunately, that collection no longer exists as a result of years of social unrest and instability in the region. Collection and characterization restarted in 2005 at the University of Kisangani (UNIKIS) within the framework of a UNIKIS/Bioversity International-led project funded by the Gatsby Charitable Foundation. From January 2005 to May 2007, three missions were carried out by UNIKIS to collect plantain cultivars in different parts of Oriental Province and recover major parts of the extinct plantain collection of INEAC Yangambi. A total of 65 plantain cultivars were collected in the framework of the Gatsby-funded project. From 2009 to 2012, nine MSc students, working with a PhD student, carried out collection work in 66 territories of Oriental, North Kivu, South Kivu, Maniema, Katanga, Eastern Kasai, Western Kasai, Bandundu and Equateur provinces. The per-centage of forest cover, and to a lesser extent province size, were positively linked to plantain diversity. Katanga, which is the second largest surveyed province and has savannah-type ecology had the lowest number of plan-tain cultivars. The highest plantain diversity was observed in forest zones across the Congo Basin. These com-prise Oriental Province, where 69 plantain cultivars were recorded, followed by Equateur, with 60 cultivars, and Maniema, with 31 cultivars. Lower plantain diversity was recorded in the provinces where savannah ecologies predominate (Bandundu (25 cultivars), Western Kasai (22), Eastern Kasai (21), South Kivu (14), North Kivu (11) and Katanga (8)). Several putative new plantain cultivars were recorded. The highest cultivar diversity was observed within the French plantain clone set, followed by the False Horn and the Horn clone sets. Nevertheless, False Horn and Horn plantain take up the largest proportion of the production landscape owing to their short cycle duration and the marketability of some of their cultivars (e.g. Libanga Likale, Libanga Lifombo or Lokusu, which has large fruit). In-depth synonymy studies are needed and synonymy reconciliation between cultivars of the defunct INEAC Yangambi collection and the current UNIKIS collection is ongoing. In addition, agronomic, postharvest and molecular aspects of characterization should be considered as a means of enhancing the knowledge, use and conservation of Musa diversity across DR Congo.

1 Plantain Collection and Morphological Characterization

in Democratic Republic of Congo: Past and Present Activities and Prospects

J.G. Adheka,1* D.B. Dheda,1 C. Sivirihauma,2 D. Karamura,3 E. De Langhe,4 R. Swennen4 and G. Blomme3

1Universit de Kisangani (UNIKIS), Democratic Republic of Congo; 2Universit Catholique du Graben (UCG), Butembo, Democratic Republic of Congo; 3Bioversity International, Kampala, Uganda;

4Katholieke Universiteit Leuven (KUL), Belgium

* E-mail: [email protected]

2 J.G. Adheka et al.

1.1 Introduction

Bananas (Musa spp.) and plantains (a parti cular subgroup of Musa spp. Musa AAB) are key components of food security in the Democratic Republic of Congo (DR Congo), which pro-duces 1.57 million t/year of these foods (FAOSTAT, 2010), particularly in Oriental province, which covers a large part of the Congo Basin. For example, Tshopo District, Oriental Province, produced 444,435 t of plan-tain in 2009. Plantains are mainly cultivated at lower elevations in the Congo Basin, while the eastern Congolese highlands along the Albertine Rift Valley are considered as a meeting place of East African highland banana (Musa spp. AAA-EA) and plantain (Musa AAB) cultivation.

Musa (especially plantain and AAA-EA) cultivars were established during the 1950s in collections at four research stations of the Institut National pour lEtude Agronomique du Congo (INEAC) Yangambi (Oriental), Bambesa (Oriental), Lubarika (South Kivu) and Mulungu (South Kivu). Characterization of the wide variety of plantain cultivars in the Congo Basin started at INEAC Yangambi and, by 1960, 56 plantain cultivars had been collected and characterized by Edmond De Langhe. However, social unrest, civil war and political instability prevented work on Musa characteri-zation for several decades afterwards, and none of these early Musa collections still exists. Nevertheless, studies of these collections had led to a series of publications, especially for plantain, which revealed that humid Africa is the major secondary centre of diversity for both groups of Musa (Dheda et al., 2011). Still, the Musa collection missions carried out by INEAC scientists only covered part of Oriental Province and it was thus assumed that only samples rep-resenting a part of the wide plantain diversity that existed had been collected.

In 2005, funds were obtained from the Gatsby Charitable Foundation to start a University of Kisangani (UNIKIS)/Bioversity International-led project on Plantain in the Eastern Congo Basin. The objectives of the project were: (i) to (re-)collect in Oriental Province part of this unique set of plantain cultivars; (ii) to establish and maintain the cultivars in a field collection at UNIKIS; (iii) to duplicate the collection in vitro; and

(iv) to back up this plantain material at the International Transit Centre (ITC), Leuven, Belgium for subsequent virus indexing/clean-ing and exchange for possible future use.

From January 2005 to May 2007, four col-lection missions were carried out by UNIKIS to collect plantains in Oriental Province and to recover major parts of the extinct plantain col-lection of INEAC Yangambi. The missions took place in: Tshopo around Kisangani and Yangambi; Ituri around Kilo, close to the bor-der with Uganda; Haut Uele around Wamba, close to the border with Sudan; and Bas Uele close to the border with the Central African Republic. A total of 65 plantain cultivars were collected in the framework of the Gatsby pro-ject. A minimum set of morphological descrip-tors was recorded for each new plantain cultivar and a minimum set of photographs was taken (De Langhe, 1961; Tezenas du Montcel et al., 1983; Swennen, 1990; Daniells et al., 2001). The majority of the plantain cultivars characterized had a medium plant size (65%), with giant plan-tains making up 20%, dwarf plantains, 12%, and semi-dwarf plantains, 3%. No dwarf or semi-dwarf cultivars had been observed in West Africa (Dheda et al., 2011). Likewise, many of the 56 plantain cultivars collected dur-ing the 1950s in the eastern Congo basin, DR Congo, and more particularly in Tshopo District, Oriental Province, did not seem to exist in West Africa, where over 110 plantain culti-vars had been collected (De Langhe, 1961; Tezenas du Montcel et al., 1983; Swennen, 1990).

Further collaboration between UNIKIS, Universit Catholique du Graben (UCG, DR Congo), Bioversity-CIALCA (Consortium for Improving Agriculture-based Livelihoods in Central Africa) and Katholieke Universiteit Leuven (KUL, Belgium) was established in 2009 to boost Musa collection, characterization and conservation work in DR Congo. Since 2009, a team of nine MSc students and one PhD stu-dent have carried out Musa germplasm collec-tion and morphological characterization work in nine provinces (Oriental, North Kivu, South Kivu, Maniema, Katanga, Eastern Kasai, Western Kasai, Bandundu and Equateur). The MSc students each carried out their work in a specific province, while the UNIKIS PhD stu-dent (20112014) is currently analysing the combined data from all the provinces surveyed. An important aspect of this work comprises the

Plantain Collection and Characterization in the Congo 3

comparison of the 56 plantain cultivars col-lected by INEAC in the 1950s and the UNIKIS plantain collection. As different ethnic groups use different names for a particular cultivar, synonymy work is an important aspect of the ongoing Musa germplasm research. In addition, maps will be made depicting the diversity of plantain cultivars and the geographical distri-bution of the most common plantain cultivars.

1.2 Materials and Methods

Since 2009, Musa germplasm surveys have been carried out in nine provinces and 66 ter-ritories (five territories in, respectively, Katanga, Eastern Kasai, Western Kasai and Bandundu provinces; six territories in, respec-tively, Maniema, North Kivu and South Kivu; 14 territories in Equateur; and 19 territories in Oriental). Three villages in which Musa pro-duction systems dominated were selected in each territory. Where only one main road was present within a territory, villages were selected at 50 km intervals. If several road axes were present, a village was selected on each axis.

In each selected village, a focus group discussion was conducted with a group of at least 30 men, and with a separate group of 30 women, to establish a list of all banana and plantain cultivars grown and known by farm-ers. The presence of each listed cultivar was verified by UNIKIS/UCG staff/students and descriptor data were subsequently collected for each new cultivar using the Bioversity International banana descriptor guidelines (IPGRI-INIBAP/CIRAD, 1996). A minimum

set of digital photographs (e.g. entire plant with bunch, close-up of the inflorescence) (Kepler and Rust, 2006) was also taken of a mature plant for each new cultivar. Three vis-ibly healthy sword suckers of each putative new cultivar were collected for subsequent establishment at the UNIKIS and UCG Musa collections, and additional morphological characterization will be carried out on these at maturity. Diagnostic surveys were also conducted with ten households, each with at least 30 plantain mats per village. Overall, a total of 198 villages and 1980 households were surveyed, and the following informa-tion was collected: the most widely grown Musa cultivars, the name of each cultivar in the local dialect, the meaning of this name, the origin of each cultivar, its positive and negative traits and its use.

1.3 Results and Discussion

The total number of Musa cultivars grown varied by province, with highest diversity observed in Oriental, Equateur, North Kivu, Maniema and South Kivu (Tables 1.1 and 1.2). Most of the larger provinces had a higher num-ber of Musa cultivars, as is the case for Oriental Province which ranked first in size and Equateur which ranked second (Table 1.3). The size of a province is, however, not the only fac-tor that influenced banana and plantain div-ersity in DR Congo provinces. The percentage of forest cover is also highly related to plantain diversity (Table 1.3). Plantains clearly dominate the production landscape in the Congo basin

Table 1.1. Number of cultivars of Musa spp.: for cooking and beer (East African highland banana, AAA-EA subgroup); for dessert use (AAA, ABB subgroups); and plantain (AAB subgroup) in nine provinces in Democratic Republic of Congo.

ProvinceAAA-EA cooking

AAA-EA beer

AAA, ABB dessert

AAB plantain Total

Bandundu 1 0 6 25 32Eastern Kasai 4 0 7 21 32Equateur 2 0 6 60 68Katanga 5 0 9 8 22Maniema 2 2 5 31 40North Kivu 17 9 11 11 48Oriental 8 2 7 69 86South Kivu 10 7 9 14 40Western Kasai 3 0 5 22 30


Table 1.2. Name, local synonym and clone set (type) of the five most widely spread cultivars of the plantain subgroup (AAB) in nine provinces of Democratic Republic of Congo.

Province Name Local synonym Clone set

Bandundu Egbe-O-mabese I Moasi False HornIkpolo Rouge Mbuli HornLibanga Likale Ntsila False HornLitete Mimbuka FrenchLokusu Nkombe Horn

Eastern Kasai Chwachwa Ateta False HornEgbe-O-mabese I Kalunga mbumba False HornIkpolo Rouge Makonda bianza HornLibanga Likale Makondji mampadji False HornLokusu Makonda Horn

Equateur Egbe-O-mabese I Mbuli False HornLibanga Likale Embanga False HornLibanga type C Mogbokuma False HornLitete Lolipili FrenchLokusu Mopanza Horn

Katanga Boofo Noire Kanyongolo FrenchIkpolo Rouge Konde HornLibanga Lifombo Kamatadji False HornLibanga Likale Kabuzigonde False HornLokusu Gondelilume Horn

Maniema Chwachwa Sombi FrenchEgbe-O-mabese I Mogogo False HornIkpolo Rouge Mbudji HornLibanga Likale Abholo False HornLokusu Mogomba Horn

North Kivu Kotina Kikothina False HornMusilongo Munzabo FrenchNguma Nguma FrenchVuhindi Vuhindi FrenchVulambya Nyalambya French

Oriental Amakake Kanamusungudile False HornChwachwa Ayele FrenchLibanga Lifombo Kasombo False HornLibanga Likale Ambulu False HornLitete Losau French

South Kivu Boofo Noire Namasolu FrenchChwachwa Lubinja FrenchIkpolo Rouge Chibulanana HornLibanga Likale Ngange False HornLokusu Musisa Horn

Western Kasai Chwachwa Djeke tokoleke FrenchEgbe-O-mabese I Yemba too False HornLibanga

LibokoikoiEtshuma kawelo French

Libanga type C Shenga dikondo False HornLokusu Lokoma Horn

(Oriental, Maniema, the northern parts of the two Kasai provinces, Bandundu and Equateur), but not in Katanga (which ranks second in size but has savannah-type ecology) or in the eastern highland regions. In addition, the

coexistence of different Musa genome groups contributes to a higher overall cultivar number as, for example, in the Kivu provinces where AAA-EA, dessert (AAA, ABB) Musa spp. and plantains (AAB) are all cultivated.


The five most important plantain cultivars in each province are well known (Table 1.2). However, across DR Congo there are about 450 ethnic groups speaking about 200 different languages (WFP et al., 2009). It is, therefore, to be expected that different plantain names exist for a given cultivar (especially if this cultivar is geographically widespread) and that syno-nyms can occur within a province or between provinces if different ethnic groups are pre-sent. As a result, the total number of plantain cultivars may have to be adjusted once all in-depth morphological characterization and description work is completed. Initial survey results indicate that plantain diversity is high-est in Oriental Province (69 cultivars), followed by Equateur (60), Maniema (31), Bandundu (25), Western Kasai (22), Eastern Kasai (21), South Kivu (14), North Kivu (11) and Katanga (8). Primary forest dominates in the provinces with the highest plantain diversity (Table 1.3). Plantain cultivation and diversity are low in the eastern highlands and the savannah zones of southern Kasai or Katanga. Plantain is more widely grown in the hot and humid climates in lowland regions at 0750 m above sea level (masl). An exception is the plantain cultiva-tion system in Mutwanga, North Kivu (1049 masl), where high yields are obtained owing to excellent, volcanic derived soils and a favourable microclimate. The plantain culti-var Vuhembe is cultivated on a farm at Ndihira, North Kivu (2172 masl), which dem-onstrates the exceptional adaptation of this cultivar to high altitude and thus low temper-ature conditions.

Plantains are a staple food for the majority of ethnic groups in the forest

zones of DR Congo (Sebasigari, 1985). In this region, green or ripe plantain is cooked or both cooked and pounded. Pounded plantain is often mixed with cassava. Ripe plantain is also fried in oil, while plantain flour is used for making dough or fritters (Bakelana and Muyunga, 1998). In some isolated villages of Tshopo District, Oriental Province, beer is prepared from fermented plantain and sold in order to maximize income. In the highlands of North and South Kivu, the landscape is mostly occu-pied by East African highland bananas (AAA-EA), while cassava and maize domi-nate in the savannah regions of southern Katanga, southern Kasai and southern Bandundu.

The plantain cultivars Ikpolo Rouge, Libanga Likale and Lokusu dominate the plantain landscape across the provinces that have been surveyed (Table 1.2) and the Horn and False Horn clone sets are the most common (Table 1.2). In accordance with past observations (Adheka, 2010; Dheda et al., 2011), the predominance of False Horn and Horn plantains can be explained by their short cycle duration and high market demand. All plantain cultivars with large hands (i.e. Horn and False Horn clone sets) are commonly called Ambulu (i.e. great banana) in the local mar-kets. None the less, the diversity of the Horn and False Horn plantain clone sets is over-shadowed by the diversity in French types (Table 1.4). It is postulated that the False Horn and Horn types evolved from French clones through mutation, resulting in a grad-ual reduction of the male inflorescence parts.

Table 1.3. The relative importance of forest cover in relation to Musa diversity in provinces of Democratic Republic of Congo. Sources: SPIAF (1995); Ministre de Plan (2004, 2005a,b); Bikumu (2005); PNUD (2009).

Province Total area (km2) Forest cover (%) No. Musa cultivars No. plantain cultivars

Bandundu 295,658 40.6 32 25Eastern Kasa 168,216 59.4 32 21Equateur 403,293 99.7 68 60Katanga 496,865 2.0 22 8Maniema 132,250 75.0 40 31North Kivu 59,631 30.0 48 11Oriental 503,239 73.5 86 69South Kivu 56,128 30.0 40 14Western Kasa 156,967 25.5 30 22


1.4 Conclusion

This chapter gives a general overview of plan-tain diversity across DR Congo. Initial results from the nine provinces surveyed show that primary forest dominates in those with the highest plantain diversity (3169 plantain cul-tivars). Plantain cultivation and diversity are low in the eastern highlands (North and South Kivu) and in the savannah zones of southern Bandundu, eastern and western Kasai and Katanga (825 plantain cultivars). In addition, the plantain production landscape across the nine provinces is dominated by False Horn and Horn clone sets. Nevertheless, the diver-sity of the Horn and False Horn plantain clone sets is overshadowed by the diversity of the French clone set.

In-depth synonymy work is now needed to pinpoint similar cultivars across ethnic group boundaries or across provinces. In addition, maps of cultivar diversity and geographical

distribution could pinpoint sites where muta-tion may have taken place. Moreover, agro-nomic, postharvest and molecular aspects of characterization should be considered in the future in order to enhance the knowledge and improve the use and conservation of Musa diversity across DR Congo.

Acknowledgements

We would like to thank the Directorate General for Development (DGD), Belgium for funding this research through the CIALCA project and the KUL-led VLIR-UOS project for contributing to this work. UNIKIS, Kisangani and UCG, Butembo, North Kivu are gratefully acknowledged for their crucial technical support. Finally, the help of the farmers of the nine provinces of DR Congo who provided the information used in this study is also gratefully acknowledged.

Table 1.4. Number of plantain cultivars by clone set observed across the nine provinces in Democratic Republic of Congo. French plantain has a male bud and persistent bracts on the rachis; False Horn plantain has some bracts at the end of rachis but no male bud; Horn plantain has no male bud, no bracts and a short rachis.

Plantain clone set

Province French False Horn Horn Total

Bandundu 14 7 4 25Eastern Kasai 10 8 3 21Equateur 36 18 6 60Katanga 2 2 4 8Maniema 21 6 4 31North Kivu 8 2 1 11Oriental 45 18 6 69South Kivu 10 2 2 14Western Kasai 11 7 4 22

References

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Bakelana, K. and Muyunga, T. (1998) La production de bananes et de bananes plantain en Rpublique Dmocratique du Congo. In: Picq, C., Four, E. and Frison, E.A. (eds) Bananas and Food Security, Les productions Bananires: Un Enjeu conomique Majeur pour la Scurit Alimentaire, International Symposium, Douala, Cameroon, 1014 November 1998. International Network for the Improvement of Banana and Plantain (INIBAP), Montpellier, France, pp. 103112.


Bikumu, F. (2005) La Problmatique du Dficit nergtique dans la Sous Rgion des Grands-Lacs Africains. Rapport de lInstitut Interculturel dans la Rgion des Grands Lacs, Goma, Democratic Republic of Congo.

Daniells, J., Jenny, C., Karamura, D. and Tomekpe, K. (2001) Musalogue: a Catalogue of Musa Germplasm Diversity in the Genus Musa. International Network for the Improvement of Banana and Plantain (INIBAP), Montpellier, France.

De Langhe, E. (1961) La taxonomie du bananier plantain en Afrique Equatoriale. Journal dAgriculture Tropicale et de Botanique Applique 8, 418453.

Dheda, D.B., Nzawele, B.D., Roux, N., Ngezahayo, F., Vigheri, N., De Langhe, E., Karamura, D., Picq, C., Mobambo, P., Swennen, R. and Blomme, G. (2011) Musa collection and characterization in central and eastern DR Congo: a chronological overview. Acta Horticulturae 897, 8794.

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Kepler, A. and Rust, F. (2006) Simmonds Scoring, a Pictorial Review, Technical Advisory Group (TAG) Workshop, Cameroun, 29 May3 June, 2006.

Ministre de Plan (2004) Monographie de la Province de Maniema. Unit de Pilotage du Processus DSRP [Document de la Stratgie de Rduction de la Pauvret], Kinshasa, Democratic Republic of Congo.

Ministre de Plan (2005a) Monographie de la Province de Nord Kivu. Unit de Pilotage du Processus DSRP [Document de la Stratgie de Rduction de la Pauvret]. Kinshasa, Democratic Republic of Congo.

Ministre de Plan (2005b) Monographie de la Province de Sud Kivu. Unit de Pilotage du Processus DSRP [Document de la Stratgie de Rduction de la Pauvret]. Kinshasa, Democratic Republic of Congo.

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Sebasigari, K. (1985) Aperu sur la culture du bananier et ses problmes dans la Communaut Economique des Pays des Grands Lacs (CEPGL). In: Kirkby, R.A. and Ngendahayo, D. (eds) Banana Production and Research in Eastern and Central Africa. Proceedings of a Regional Workshop held in Bujumbura, Burundi, 1417 December 1983. Publication No. IDRC-MR114e [available in English and French], International Development and Research Centre, Ottawa, Canada, pp. 1228.

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CAB International 2013. Banana Systems in the Humid Highlands 8 of Sub-Saharan Africa (eds G. Blomme, P. van Asten and B. Vanlauwe)

AbstractMusa (bananas and plantains), an important food and income crop in the east and central African Great Lakes countries (Rwanda, Burundi and the Democratic Republic of Congo (DR Congo)), has suffered declines in production and diversity over the past 20 years. The loss in cultivar diversity is mainly attributed to land pres-sure, agricultural intensification, market demands, pests and diseases and civil unrest. Knowledge on the cur-rent Musa cultivar diversity across Rwanda, Burundi and eastern DR Congo will provide valuable information to breeders and taxonomists. This study assessed the on-farm and community level Musa germplasm diversity across different districts of Rwanda and Burundi, and across the South and North Kivu provinces of eastern DR Congo. Spatial diversity was computed using cultivar richness and the GiniSimpson index of diversity. A total of 92 cultivars was recorded across the surveyed regions, with the highest number of cultivars observed in Rwanda and lowest in North Kivu. The mean number of cultivars across households varied from seven to eight. North Kivu had the highest diversity index, suggesting a more even distribution of plant populations among cultivars. For example, the two most predominant cultivars occupied 35% of the land area in North Kivu, 44% in Rwanda, 61% in Burundi and 70% in South Kivu. In addition, only 26% of the cultivars had a GiniSimpson score greater than zero, i.e. were more uniformly spread and widely adapted. Hence, 74% of the cultivars, especially those with no cultural significance, are prone to genetic erosion; ex situ conservation would

2 Musa Germplasm Diversity Status across a Wide Range of Agro-ecological Zones in Rwanda, Burundi and Eastern

Democratic Republic of Congo

W. Ocimati,1* D. Karamura,1 A. Rutikanga,2 C. Sivirihauma,3 V. Ndungo,3 J. Adheka,4 D.B. Dheda,4 H. Muhindo,5 J. Ntamwira,6 S. Hakizimana,7

F. Ngezahayo,7 P. Ragama,8 P. Lepoint,9 J.-P. Kanyaruguru,9 E. De Langhe,10 S.V. Gaidashova,11 A. Nsabimana,12 C. Murekezi11 and G. Blomme1

1Bioversity International, Kampala, Uganda; 2Bioversity International, Kigali, Rwanda and Higher Institute for Agriculture and Animal Husbandry (ISAE);

3Universit Catholique du Graben (UCG), Butembo, Democratic Republic of Congo; 4University of Kisangani (UNIKIS), Democratic Republic of Congo; 5Institut

Facultaire des Sciences Agronomiques (IFA-Yangambi), Kisangani, Democratic Republic of Congo; 6Institut National pour lEtude et la Recherche Agronomique (INERA), Mulungu Research Station, Bukavu, Democratic Republic of Congo;

7Institut de Recherche Agronomique et Zootechnique (IRAZ), Mashitsi, Burundi; 8Kabarak University, Kabarak, Kenya; 9Bioversity International, Bujumbura, Burundi;

10Katholieke Universiteit Leuven (KUL), Belgium, 11Rwanda Agricultural Board (RAB), Kigali, Rwanda; 12Kigali Institute of Science and Technology, Rwanda

* E-mail: [email protected]

Musa Germplasm Status across Agro-ecological Zones 9

2.1 Introduction

Bananas and plantains (Musa spp.) are impor-tant staple and income-generating fruit crops for millions of people in the tropical and subtropical regions of the world (Ssebuliba et al., 2005; Robinson and Galn Saco, 2010). The countries of the Great Lakes region of East and Central Africa, including Rwanda, Burundi and the Democratic Republic of Congo (DR Congo) rank among the top banana and plantain producers in the world, with annual production estimated at 2.75 million tonnes (Mt) in Rwanda, 0.13 Mt in Burundi and 1.57 Mt in DR Congo (FAOSTAT, 2010). In addition, the crop ranks first in overall produc-tion in Rwanda and second in Burundi and DR Congo (FAOSTAT, 2010). The Musa crop is grown across a wide range of agro-ecologies and provides an important ecological func-tion. The large banana leaves, a widespread super ficial root system and mulch obtained from old leaves and harvested plants protect the soil against erosion (Baragengana, 1985). The banana crop covers 23% of the total culti-vated landscape (Mpyisi et al., 2000) and is grown by 90% of households (Lassoudire, 1989) in Rwanda, whereas in Burundi approxi-mately 17% of the landscape is devoted to it. Much lower soil erosion levels have been reported in plots with bananas compared with plots with annual crops (Lufafa et al., 2003).

The Great Lakes region of East Africa, of which Rwanda, Burundi and DR Congo are part, constitutes one of the secondary cen-tres of Musa diversity and especially for the East African highland bananas (Musa spp. AAA-EA subgroup) (Karamura et al., 2004; Dheda et al., 2011). Despite the great impor-tance of the crop, its yield and diversity have been declining over the past decades (Rishirumuhirwa, 1997; Baijukya and de Steenhuijsen Piters, 1998; Woomer et al., 1998; MINECOFIN, 2001; Karamura et al., 2004). Loss in cultivar diversity is mainly attributed

to land pressure, pests and diseases, agricul-tural intensification, market demands and civil unrest (Okech et al., 2002, 2005; Nsabimana and van Staden, 2005; Ndungo et al., 2008). For example, in Rwanda, civil unrest led to the near complete staff turnover of the Rwandan Banana Programme, loss of archived informa-tion (Okech et al., 2002, 2005) and confusion in the nomenclature of cultivars (Nsabimana and van Staden, 2005). The recent drive for on-farm conservation of genetic resources (Brush, 1995; Bellon et al., 1997; Bretting and Duvick, 1997; Fowler and Hodgkin, 2004) is hampered by the need for food security and agricultural intensification that results in the selection and promotion of a few of the more productive cul-tivars for which there is a high market demand. Adequate knowledge of existing cultivar diversity is lacking in the Great Lakes region of Central Africa (De Langhe, 2004).

Knowledge of Musa genetic diversity and the geographical spread of banana and plan-tain cultivars will provide valuable informa-tion to breeders and taxonomists (Swennen and Vuylsteke, 1987). Knowledge of the cur-rent cultivar diversity and synonyms is there-fore urgently needed to formulate strategies for the conservation of threatened cultivars with good/promising yield/marketing or breeding qualities. Consequently, this study assessed on-farm and community Musa germ-plasm diversity and cultivar synonyms across Rwanda, Burundi and the South and North Kivu provinces of eastern DR Congo. It is envisaged that the information generated will provide a baseline and a precursor for a more detailed germplasm characterization study using descriptors for banana (IPGRI-INIBAP/CIRAD, 1996; Dadzi and Orchard, 1997).

2.2 Materials and Methods

A Musa germplasm survey was carried out in different agro-ecologies of Rwanda, Burundi

maintain these. Beer and cooking bananas dominate the Musa landscape. However, plantains gain importance in North Kivu, especially in the regions bordering the humid Congo basin and in Mutwanga at the foothills of the Rwenzori mountain chain. The predominance of the AAA-EA highland banana subgroup can be attrib-uted to the predominantly mid to high altitudes (>1500 masl) found in these regions. Mid to high altitudes support East African highland banana cultivars, while humid lowlands support the growth of plantains.

10 W. Ocimati et al.

and eastern DR Congo (North Kivu and South Kivu) in 2007. In Rwanda, five districts representing different agro-ecologies were selected along a transect from Rusizi, border-ing Lake Kivu (Western Province), to Kirehe District (Eastern Province) at the border with Tanzania. Three provinces were selected in Burundi, namely, Cibitoke in the north-west, Kirundo in the north and Gitega in the central region. In eastern DR Congo, four represent-ative and key banana-growing localities were selected in both North and South Kivu. The sampled localities included Maboya, Mangodomu, Munoli and Mutwanga in North Kivu, and Burhale, Kabamba, Luhihi and Lurhala in South Kivu. The survey site selection criteria included biophysical and socio-economic characteristics (e.g. wealth status and land holding size), access to mar-kets and the presence of local farmers organi-zations and non-government organizations (NGOs) that have an interest in banana pro-duction and the capacity to disseminate gen-erated knowledge.

The on-farm germplasm survey activi-ties were to build on Participatory Rural Appraisal (PRA) and baseline surveys that were conducted in the same provinces in 2006 (CIALCA, 2008). Whereas the PRA and baseline surveys were solely based on infor-mation derived through focus group discus-sions and household interviews, the on-farm germplasm surveys took a step further to quantifying farming systems through actual field measurements. In each region, farms with at least 50 banana mats were identified. In Rwanda, a total of 118 farmers/farms were sampled, while 132 farms were sam-pled in Burundi. In the North and South Kivu provinces of DR Congo, 30 farms were randomly sampled per locality, giving a total of 120 farmers/farms per province.

The list of cultivars, their names and uses were recorded for each farm surveyed. Data were also collected on the synonyms of each cultivar. Regional/national scien-tists from the Institut de Recherche Agro-nomique et Zootechnique (IRAZ) in Burundi, the Rwandan Agricultural Board (RAB) in Rwanda, the Universit Catholique du Graben (UCG) in North Kivu and the Institut National pour lEtude et la Recherche

Agronomique (INERA) in South Kivu veri-fied Musa cultivar names obtained during the farmer interviews.

Cultivar spatial diversity was calculated using the proportional area of the cultivars grown by farmers (Smale et al., 2003; Gauchan, 2004). The number of mats per identified Musa cultivar in each of the household farms sam-pled was counted, summed and expressed as a percentage of the total mats for all the cultivars in each country or region. Cultivar spatial diver sity was computed using two indices: cultivar richness, which is diversity of order zero, and the GiniSimpson index of diversity using an order of diversity of two (Jost, 2006). These indices can help to determine which populations to target for conservation (to maximize diversity) or for demonstrating the services that are provided by diversity (Gauchan et al., 2005).

Cultivar richness, which is the number of cultivars in a region, is completely insensitive to cultivar frequencies (Jost, 2006). It gives as much weight to those cultivars that are repre-sented by very few plants as to those cultivars that are represented by many plants (Jost, 2006; Dyke, 2008; Colwell, 2009). The cultivar richness (D, order of diversity zero) was com-puted as:

D Ssi =1 Pi 0 (2.1)

where cultivar i comprises the proportion Pi of the total individuals in a community of S cultivars.

The GiniSimpson index (1 D) takes account of the number of individuals of each cultivar as well as the number of cultivars within a community (Gauchan et al., 2005; Jost, 2006). If the order of diversity in the GiniSimpson index is zero, then the index is the cultivar richness (Jost, 2006). Values of order of diversity less than one favour rare cultivars and those above one favour the more common cultivars. The Simpson Index, D, with an order of diversity of two, was calculated as:

D = Si {ni(ni1)}/(N(N 1)) (2.2)

where ni is the number of individuals of cul-tivar i and N is total number of individuals of all cultivars.

The Simpson Index, D, assesses the probabi lity that two randomly selected


individuals (i.e. order of diversity two) from a site will belong to the same cultivar (Simpson, 1949). In a complementary way, the GiniSimpson index (1 D) is the probability that two independent samples will yield individu-als belonging to different cultivars (Frosini, 2004). The GiniSimpson index, with D calcu-lated using Eqn 2.2, indicates greater diversity as the index value approaches 1.0. The index assumes values between 0 and (S 1)/S (almost exactly normalized between 0 and 1 for large values of S) (Frosini, 2004). For exam-ple, if a location contains 15 cultivars with 100 mats of each cultivar, then the cultivar richness is 15 and the GiniSimpson index is 0.96, indicating high diversity in the popula-tion. If, in contrast, one of the 15 cultivars has 10,000 mats, and the others only 100 each, then the richness remains unchanged but the value of 1 D falls to 0.23, indicating a less diverse population. The software GenStat (11th edition) from VSN International (2008) was used to calculate the Simpson index, and also to compute the analysis of variance, means and standard errors for the household level cultivar richness. The Microsoft Excel package was used to generate figures.

2.3 Results and Discussion

2.3.1 Musa cultivar richness

A total of 92 Musa cultivars was recorded across all the study areas (North and South Kivu in eastern DR Congo, Burundi and Rwanda) (Table 2.1). Rwanda ranked highest with 42 cultivars, followed by South Kivu with 32, Burundi with 31 and finally North Kivu with 30. Of these cultivars, only five (Gisukari (AAA), Intuntu (AAA-EA), Kamaramasenge (AAB), Pisang awak (ABB) and Yangambi Km5 (AAA)) were widely grown across the four regions. Another nine cultivars were grown in at least three regions; ten cultivars were grown in at least two regions, while the remaining 68 cultivars were grown in only one region (Table 2.1).

In Rwanda, the beer cultivars Intuntu (AAA-EA, 33% of mats), Yangambi Km5 (AAA, 11%), Umuzibwe (AAA-EA, 7%) and

Pisang awak (ABB, 7%) dominated the banana landscape. In Burundi, Intuntu (31%), Igisahira gisanzwe (AAA-EA cook-ing, 30%) and Igipaca (AAA-EA beer, 9%) dominated the landscape. In North Kivu, Vulambya (AAA-EA cooking, 22%), Nguma (AAB plantain, 13%), Intuntu (10%), Pisang awak (8%) and Mukingiro (AAA-EA beer, 7%) dominated the landscape while Ishika/Nshikazi (AAA-EA beer, 62%) and Kamaramasenge (AAB dessert, 7%) domi-nated in South Kivu (Table 2.1).

The number of Musa cultivars on each farm across the four regions varied from one to 15. The average population of household/farm cultivars was relatively large, varying from 7.9 cultivars in North Kivu Province to 6.7 in South Kivu Province (Fig. 2.1). High diversity has also been reported among sub-sistence farmers for other crops: for example, up to 12 types of maize were found on farms in Chiapas, Mexico (Bellon and Brush, 1994) and 26 distinct types of potato on farms in the Andes of South America (Quiros et al., 1990). Some of this diversity is preserved to spread the potentially limiting requirements of labour at planting and to spread the harvests so as to minimize the hunger gap that occurs between harvests (Pickersgill, 2000). Farmers also mix cultivars to avoid complete crop losses due to biotic and abiotic constraints as mixtures contain cultivars with different lev-els of resistance (Ortega, 1997). Cultivar mix-tures also offer a variety of tastes, flavour, texture, colours and uses to the farmers.

2.3.2 The GiniSimpson index of diversity

The GiniSimpson index varied from 0.60 in South Kivu to 0.91 in North Kivu. Rwanda had an index of 0.87 and Burundi an index of 0.80 (Fig. 2.2). This indicates that North Kivu, despite having the lowest cultivar rich-ness (30) has a more even population distri-bution between cultivars. For example, the two predominant cultivars in North Kivu occupied 35% of the Musa landscape com-pared to 44% in Rwanda, 61% in Burundi and 70% in South Kivu.


Table 2.1. Musa cultivars recorded in the four study regions (Rwanda, Burundi and North Kivu and South Kivu in Democratic Republic of Congo), their respective genome groups (subgroups), main use, mat coverage (%) and comparison of the GiniSimpson index of diversity of the cultivars across the study regions. Dashes () indicate that the cultivar was not detected in this location in this survey. The data were collected during a Musa germplasm survey in 2007. In the main use column, M is multiple use, B is beer, C is cooking, D is dessert and P is plantain.

Cultivar nameGenome group Use

Musa mat coverage (%)GiniSimpson index (1 D)Burundi Rwanda North Kivu South Kivu

Bakungu AAA-EA C 0.17 0.00Barabeshya AAA-EA C 5.20 2.23 0.49Buhake AAA-EA B 0.82 0.00Bulengere AAA-EA C 0.07 0.00Bushoki AAA-EA C 0.02 0.00Butembo AAB P 0.01 0.00Cibula nana AAB P 0.07 0.00Cindege AAA D 1.25 0.00FHIA hybrida Tetraploid M 0.03 0.00Gisubi ABB B 1.40 0.02 0.09Gisukari AAA D 0.20 0.10 0.20 2.82 0.39Goma AAB P 0.01 0.00Gros Michel AAA D 1.50 2.20 1.06 0.81Icyerwa AAA-EA C 1.31 0.16 0.60Igifysi AAA-EA B 0.01 0.00Igihonyi AAA-EA B 0.70 0.00Igihuna AAA-EA B 0.10 0.00Igipaca AAA-EA B 9.20 0.00Igisahira gisanzwe AAA-EA C 30.4 0.00Igisahira namwezi AAA-EA C 0.01 0.00Igisahira Uganda AAA-EA C 0.01 0.00Ikingurube AAA D 0.52 1.60 0.70Ikiyove AAA-EA B 2.20 0.00Imporogoma AAA-EA C 0.05 0.00Inabukumu AAA-EA B 0.20 0.00Incakara AAA-EA C 1.90 0.00Indundi AAA-EA C 0.02 0.00Ingagara AAA-EA C 0.20 0.00Ingaju AAA-EA C 3.70 0.00Ingenge AAA-EA C 0.80 2.30 0.42 0.71Ingumba AAA-EA C 0.40 0.00Injagi AAA-EA C 1.30 0.00Intembe AAA-EA B 0.20 0.00Intobe AAA-EA C 1.10 0.01 0.18Intokatoke AAA-EA B 5.60 0.00Intutsi AAA-EA C 0.90 0.00Intutu AAA-EA B 31.0 33.0 9.84 4.64 0.66Inyabupfunsi AAA-EA C 0.01 0.00Inyabutembe AAA-EA C 0.40 0.00Inyamunyo AAA-EA C 0.50 0.00Inyonya AAA-EA C 0.20 0.00Isanzi AAB P 0.05 0.00Isha AAA-EA B 3.30 0.02 0.01 0.03Ishika AAA-EA B 0.30 62.2 0.01Kafukama AAA-EA C 0.08 0.00


Table 2.1. Continued.

Cultivar nameGenome group Use

Musa mat coverage (%)GiniSimpson index (1 D)Burundi Rwanda North Kivu South Kivu

Kamaramasenge AAB D 1.70 1.70 4.66 7.39 0.70Kampala AAA B 1.10 0.00Kashulye AAA-EA B 0.11 0.00Kingulungulu AAB P 0.41 0.00Kintu AAA-EA C 0.17 0.00Kisamunyu AAA-EA C 2.32 0.00Kisubi Katarina ABB B 2.42 0.00Kithavwira AAA-EA C 0.18 0.00Kitika sukari kikuhi 1 AAA D 0.44 0.00Kitika sukari kikuhi 2 AAA D 0.48 0.00Kitika sukari kiri AAA D 5.62 0.00Kiware AAA-EA C 2.33 0.00Kotina/Kikotina AAB P 1.20 0.00Malaya AAA D 0.50 3.50 0.29Mbwazirume AAA-EA C 2.61 1.20 0.10 0.62Mujuba AAA-EA C 2.20 2.90 1.40 0.76Mukingiro AAA-EA B 7.15 0.00Munyamimba AAA-EA B 0.04 0.00Musheba AAB P 1.14 0.00Musilongo AAB P 3.40 0.00Muzuzu AAB P 0.01 1.1 0.01 0.26Ndaminya

mughendiAAA-EA C 0.18 0.00

Ngorya AAA-EA B 0.01 0.00Nguma AAB P 13.0 4.6 0.41Nshungurhi AAB P 0.01 0.00Nyakitembe AAA-EA C 0.30 0.11 5.58 0.16Nyiramabuye AAA-EA B 1.90 0.00Nzirabahima AAA-EA C 1.10 0.07 0.00Nzirabahima

plantainAAB P 0.81 0.77

Nzirabushera AAA-EA C 0.01 0.10 1.10 0.33Nzovu AAA-EA B 0.01 0.00Pisang awak ABB B 3.00 6.90 7.62 0.03 0.67Pome AAB D 0.01 0.00Poyo AAA D 0.01 4.46 0.27 0.14Rugamba AAA D 0.02 0.00Rumaripfa AAA-EA C 0.80 0.00Sanza moja AAB P 1.1 0.01 0.18Sila AAA-EA C 0.10 0.00Umugumira AAA-EA B 0.05 0.00Umuzibwe AAA-EA B 7.22 0.00Vuhethera AAB P 0.16 0.00Vuhindi AAB P 1.16 0.00Vukamatha-yira AAA-EA C 0.12 0.00Vukelekele AAB P 0.05 0.00Vulambya cooking AAA-EA C 22.0 0.00Walungu 16 AAB P 0.01 0.00Yangambi Km5 AAA B 5.80 11.0 5.93 3.61 0.74

aFHIA, Fundacion Hondurea de Investigacin Agricola.


Across the study region, only 24 cultivars (26%) had a GiniSimpson index greater than zero (Table 2.1). This suggests that only a small portion of the 92 cultivars were uni-formly spread. Some of the 68 cultivars with a low GiniSimpson index, especially those with little country-specific importance and with low cultural significance, are at a great risk of genetic erosion.

These findings have important implica-tions for conservation. Values below the aver-age GiniSimpson index (i.e. the dominance of one or few cultivars, with much of the rich-ness held in low frequencies) suggest above-average richness for a given evenness while values above the average index indicate a comparatively more even distribution of cul-tivars (Jarvis et al., 2008). It is further argued

abbc

c

a

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

9.0

Burundi Rwanda North Kivu South Kivu

No.

cul

tivar

s/h

ouse

hold

Regions

Fig. 2.1. Number of Musa cultivars grown per household across Burundi, Rwanda and the eastern Democratic Republic of Congo (North and South Kivu provinces). Data were obtained during a germplasm survey carried out in 2007. Columns with the same letters did not differ significantly at P = 0.05. Vertical bars are standard errors.

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Burundi Rwanda North Kivu

South Kivu

Total

Gin

iS

imps

on in

dex

(1

D)

Regions

Fig. 2.2. GiniSimpson indices of diversity of Musa cultivars assessed during a germplasm survey in 2007. Regions covered included Burundi, Rwanda and the North Kivu and South Kivu provinces of eastern Democratic Republic of Congo. Vertical bars are jackknife standard errors.


by Jarvis et al. (2008) that high dominance, with much of the richness held at low fre-quency, signals a management strategy for diversity maintained as an insurance to meet future environmental changes, social and economic needs. In contrast, an even fre-quency distribution of cultivars shows that farmers are selecting cultivars to meet a diversity of specific current needs and pur-poses. Dyke (2008) argues that when a com-munity is dominated by only one or a few species, it may be that the rarer species are at risk of disappearing from the site. The more common species might even be part of the problem if their behaviour is detrimental to the less abundant species. In addition, a dis-tribution pattern in which one or a few spe-cies are far more abundant than all others may indicate that the habitat lacks a sufficient diversity of structure, patchiness or resources to allow many species to exist together (Dyke, 2008). For example, some Musa cultivars, such as Mbwazirume, an AAA-EA cooking cultivar, have been reported not to withstand competition in mixed cultivar plots, while AAA-EA beer types thrive well at high alti-tudes (> 1500 m) that do not always support AAA-EA cooking types and especially plan-tains (D. Karamura, Kampala, Uganda, 2011, personal communication).

2.3.3 Cultivar distribution by use

Beer cultivars generally dominate the Musa landscape in the study regions, except in North Kivu (see Fig. 2.3). In Rwanda, beer cul-tivars occupy about 67% of the banana land-scape, followed by cooking cultivars (22%), dessert bananas (10%) and plantains, which cover only a meagre 1%. In Burundi, beer cul-tivars occupy about 57%, of the Musa land-scape, cooking cultivars about 38%, dessert cultivars about 4% and plantains are absent. In South Kivu, beer cultivars also ranked highest in importance (75% of Musa grown), followed by dessert bananas (16%), plan-tains (6%) and cooking cultivars (5%). North Kivu, in contrast to the other three regions, had all the cultivar groups much more evenly distributed; cooking bananas

ranked top at about 35%, followed by beer cultivars (34%), plantains (20%) and dessert cultivars at about 11%.

The dominance of beer cultivars in the study region could be attributed to the relatively high altitudes that favour the growth of beer cultivars (D. Karamura, Kampala, Uganda, 2011, personal communication). The altitudes of the sampled communities varied from 1553 to 1992 m above sea level (masl) in South Kivu, from 1310 to 1706 masl in Rwanda and from 1130 to 1609 masl in Burundi. Beer bananas are also considered to be more toler-ant of adverse growing conditions and low levels of management, and are better suited to regions with low market access, because the beer produced has a longer shelf life than bunches of bananas (Gaidashova et al., 2005). In contrast, in North Kivu (9691733 masl), cooking cultivars and plantains occupy sub-stantial proportions of the Musa landscape. This can be attributed to the great variation in the Musa agro-ecologies in North Kivu, with its mid-altitude areas that support the produc-tion of AAA-EA cooking cultivars and low humid altitude areas where plantains are grown (Fig. 2.3). The plantains in North Kivu are mainly cultivated in the regions bordering the humid Congo Basin and in Mutwanga at the foothills of the Rwenzori mountain chain.

2.3.4 Musa cultivar synonyms

In this study, 41 Musa cultivars had several alternative names (synonyms) (Table 2.2) within a region/country and across the dif-ferent regions/countries. The cultivar names given are those commonly used across the region or among farmers, and so less widely used names were taken as synonyms. For example, the cultivar Gisukari had three synonyms in both Burundi and Rwanda, but 13 synonyms in eastern DR Congo (North and South Kivu). Similarly, the cultivars Kamara masenge and Yangambi Km5 also had a large number of synonyms, especially in DR Congo. The presence of numerous names and synonyms in different lan-guages, dialects and countries is a common problem confronting banana taxonomists


Mangodumu

Kabamba

DRC

North Kivu

Uganda

Rwanda

Tanzania

BurundiDRC

South Kivu

kmN

Banana germplasm

0

Burhala

KarongiRuhango

Bugesera

Kirundo

Kirehe

Lurhala

Rusizi

Cibitoke

Gitega

12.5 25 50

Beer

Maboya

Munoli

Cooking

Dessert

Plantain

Luhihi

Mutwanga

Fig. 2.3. Musa cultivar distribution by use across four regions in central Africa (Rwanda, Burundi and North Kivu and South Kivu, Democratic Republic of Congo). Data were collected during a banana germplasm survey in 2007.

M

usa Germ

plasm S

tatus across Agro-ecological Z

ones 17

Table 2.2. Cultivar names of Musa spp. and their synonyms in Burundi, Rwanda and eastern Democratic Republic of Congo (DR Congo).

Synonyms

Cultivar name Burundi Rwanda DR Congo (North Kivu, South Kivu)

Cibula nana Horn PlantainCindege Dwarf Cavendish, Kitika Kikuhi, Kitika sukari kikuhiGisubi Igisubi Kisubi, Ney PovanGisukari Red Banana, Ikisukari,

Ikinyarwanda gisanzweIgisukari, Igihushwamuhoro,

Ikiziramuhoro

Red Banana Buganda mweupe, Cisukari, Cisukari mweupe, Bumpavu, Sukumba, Mugombozi, Kisukari, Cisukari Rouge, Cuduku, Cingurube ceka, Ikirisirya, Gisukari green

Icyerwa Icywera-ntoya NyambururuIgihuna Chihuna, IgihuniIkingurube (Dwarf

Cavendish)Ikinyangurube, Petite Naine,

Grande NaineIkingurube maraya

Inabukumu Intobe beer variantIndundi IncakaraIngagara Ingagara Ntabawali, Kiwari, Muhuna Binyoko, Ndabaware, MawareIngenge Ingege, Nyabutembe Nyaghenge, Pakuma, Kagenge, Ngenge, Kisamunyu ya

mufupiIntutu Igitsiri, Makara Inkara, Insiri, Igishumbu Tundu, NdunduIsha Umushya, Insha Isha Nsha, InshaIshika Ishika Magizi, Nshikazi, NshikaKamaramasenge Mabunga, Kalole, Sukarindizi, Kamela, Manzaka na mukari,

Kamela ya Rwanda, Cimera, Kamela munene, Vandiward, Cinyaburungu, Kamela Buganda

Kampala Madame, PrataKashulye NakashuliyeKisamunyu CinamunyuKisubi Katarina BluggoeKithavwira Kitawira KithavwiraKitika sukari kikuhi 1 Dwarf CavendishKitika sukari kikuhi 2 Dwarf CavendishKitika sukari kiri Dwarf CavendishKiware Ndabaware, Maware, Ngagara

Continued

18 W

. Ocim

ati et al.

Table 2.2. Continued.

Synonyms

Cultivar name Burundi Rwanda DR Congo (North Kivu, South Kivu)

Malaya Ikimaraya Cingulube, Cindege ya munene, Cindege ya Rwanda, Giant Cavendish

Mujuba Mudjuva, Igisahira namujuba, Inamujuba

Mukingiro Mazizi, Magizi ordinaireMuzuzu Imuzuzu Umuzuzu, Umushaba1=

False Horn plantain, Umushaba 2 = French plantain

Mzuzu

Nguma Baguma, MagondiNyakitembe Mitoke Kitika, Kitoke, MatokeNyiramabuye ImbotabotaNzirabahima plantain AsomboNzirabahima InzirabahimaNzirabushera Indyabarangira MutsimawuburoSanza moja Cibula nana 2 mains, Cibirangondo, Sanza mbili, Chanjo

mbili, Kingalu, Sanza tatu, Angalwa, KingalwaUmuzibwe Umuzibo, InyamakureVuhethera VuheteraVuhindi Ayaya, Mayaya, Kinamutobisa, KimanzobonzoVukelekele Makelelele, MakelekeleVulambya cooking Malambya, Nyalambya, Edidi, CinyamunyuYangambi Km5 Kanuka, Tembo, Indaya,

IngameDepre, Kanuka, Tembo, Kagame, Buganda, Nakasimbu,

Bukere, Kamela, Nakabusimbu, Kaganda, Kamira simbu, Kisubi mangango


and horticulturists (Valmayor et al., 2000). For example, in Rwanda, population migrations before and during the 1994 genocide led to the disappearance or renaming of some of the cultivars (Nsabimana and van Staden, 2005), thus creating confusion in their nomencla-ture. A more exhaustive and systemic study on synonyms in the region is recommended, using this study as a reference to complement/supplement the new study. Knowledge of synonyms is helpful in reducing/prevent-ing wasteful duplication in basic studies on banana cultivars and will also promote regional understanding, communication, and banana trade and commerce (Valmayor et al., 2000).

2.4 Conclusion

The distribution pattern (richness and index of diversity) of Musa cultivars demonstrated in this study indicates that some of the agro- ecologies in the study region lack sufficient diversity. Despite the relatively large number of cultivars of each farm or household (seven to eight) and high richness, some cultivars dominated the landscape, especially in South Kivu. For example, despite having 32 culti-vars, only two occupied 74% of the banana landscape in South Kivu; moreover, only 18 cultivars (19% of the total) had a GiniSimpson index above zero. Given that on-farm conservation is often hampered by the need

for food security and by agricultural intensi-fication, which both result in the selection and promotion of a few of the more productive cultivars, ex situ conservation, especially for cultivars with low cultural or market value, would maintain them. Further studies on cul-tivar interactions within the different agro-ecologies are needed. This study revealed the dominance of beer cultivars in all the regions except North Kivu where cooking cultivars predominate and plantains occupy a fair share of the Musa landscape. There was a strong alti-tude effect on cultivar distribution, with beer cultivars more prevalent at high altitudes and plantains in the humid low altitude regions.

Acknowledgements

The Belgian Directorate General for Devel-opment, which provided the necessary funds for this study, is gratefully acknowledged. The Institut de Recherche Agronomique et Zootechnique in Burundi, the Rwandan Agricultural Board, the Universit Catholique du Graben in North Kivu, DR Congo and the Institut National pour ltude et la Recherche Agronomique in South Kivu are also acknowl-edged for their crucial role in data collection and verification of synonyms. The authors also gratefully acknowledge the help of the farmers who provided the information for the study from the localities that were surveyed across the three countries.

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