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Crop–livestock integration in smallholder farming systems of Goromonzi and Murehwa, Zimbabwe

Published online by Cambridge University Press:  26 October 2018

Siyabusa Mkuhlani Open the ORCID record for Siyabusa Mkuhlani [Opens in a new window] ,
Walter Mupangwa ,
Neil MacLeod ,
Lovemore Gwiriri ,
Isaiah Nyagumbo ,
Godfrey Manyawu  and
Ngavaite Chigede
Siyabusa Mkuhlani*
Affiliation:
CIMMYT Southern Africa Regional Office, 12.5 km Peg Mazowe Road, Mt Pleasant, Harare, Zimbabwe
Walter Mupangwa
Affiliation:
CIMMYT Southern Africa Regional Office, 12.5 km Peg Mazowe Road, Mt Pleasant, Harare, Zimbabwe
Neil MacLeod
Affiliation:
CSIRO Agriculture and Food, St Lucia, Queensland4072, Australia
Lovemore Gwiriri
Affiliation:
Centre for Agroecology, Water and Resilience, Coventry University, Priory Street, CoventryCV15FB, UK
Isaiah Nyagumbo
Affiliation:
CIMMYT Southern Africa Regional Office, 12.5 km Peg Mazowe Road, Mt Pleasant, Harare, Zimbabwe
Godfrey Manyawu
Affiliation:
International Livestock Research Institute, c/o CIMMYT Southern Africa Regional Office, Harare, Zimbabwe
Ngavaite Chigede
Affiliation:
Chibero Agricultural College, P. Bag 901, Norton, Zimbabwe
*
Author for correspondence: Siyabusa Mkuhlani, E-mail: siyabusa@gmail.com
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Abstract

Poor productivity in smallholder farming systems has necessitated research on the potential of crop–livestock integration to sustainably improve productivity. The study hypothesized that improvement in individual agronomic and livestock systems and synergistic utilization of by-products of either system increases productivity, profitability and integration. Smallholder farming households were classified into: old and resource endowed (OR); part time (PT); and young, risk-taking and enthusiastic (YRE) following a survey conducted in Murehwa and Goromonzi districts of Zimbabwe. Crop–livestock systems’ integration scenarios were developed for each farmer category. Expression of crop–livestock integration in physical terms, e.g., kg ha−1, can be complex and confounding, hence the expression of integration in monetary values. Baseline scenario results indicate that OR had the highest crop–livestock integration of $3981 compared with PT and YRE despite OR having the lowest manure usage compared with PT and YRE farmers. Moreover, OR had the least legume yields of <800 compared with 3530 kg ha−1 in YRE farmers. Subsequent crop–livestock integration scenarios increased maize grain yields by at least 50%, thus increasing profitability to $1210, $3230 and $3100 yr−1 for mucuna, cowpea and groundnut, respectively. Total income increased by 135, 132 and 101% translating to $9880, $2960 and $6290 yr−1 in OR, PT and YRE farmers, respectively. Crop–livestock integration therefore has the potential to improve smallholder crop and livestock productivity, variable with socio-economic status.

Keywords

Crop–livestock productivityfarm household typologyprofitabilitysimulation modelingsmallholder farming systems
Type
Research Paper
Information
Renewable Agriculture and Food Systems , Volume 35 , Issue 3 , June 2020 , pp. 249 - 260
Copyright
Copyright © Cambridge University Press 2018

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