Socio-economic impacts and determinants of parasitic weed infestation in rainfed rice systems of sub-Saharan Africa

A.S. N'cho

Research output: Thesisinternal PhD, WU

Abstract

Keywords: rice; weed; weed management practices, adoption, impact, parasitic weeds; Rhamphicarpa fistulosa; Striga asiatica; Striga hermonthica, double hurdle model; multivariate probit, productivity, stochastic frontier analysis, data envelopment analysis, directional distance function, sub-Saharan Africa, Benin, Cote d’Ivoire, Tanzania.

Socio-economic impacts and determinants of parasitic weed infestation in

rainfed rice systems of sub-Saharan Africa

Simon A. N’cho

Abstract

Rice is an important strategic crop for food security in sub-Saharan Africa. However, its production is constrained by many biotic and abiotic stress. In rainfed rice systems, weeds and particularly parasitic weeds are among the most damaging constraints. The objective of this thesis was to identify factors affecting infestation of rice farms by parasitic weeds and to assess the economic and social impact of parasitic weeds on primary producers of rainfed rice systems in order to provide guidance for decision-making for rice farmers and policymakers aiming at developing strategies for coping with parasitic weeds. To achieve this objective, we first explored biophysical characters of the rice growing environment, farmers’ management practices, and socio-economic characteristics that affect the infestation of rice fields by parasitic weeds (PWs) and farmers’ ability to cope with the problem. A double hurdle model was used to analyses simultaneously the likelihood of occurrence and the severity of infestation of the PW. The findings suggest that farmers can cope with the PW as long as they are aware of the problem provided they have a good access and management capacity of production resources. Next, we examined weed management practices (WMPs) currently available to farmers and how PW infestation affect their choices for specific combinations of WMPs using a multivariate probit model. Findings indicate that farmers are more likely to adopt improved weed management practices or combined more WMPs when their fields are infested by PWs. Species-specific and country-specific approaches and technologies are require to address the PW problem. Then, we assessed the impact of parasitic weeds infestation on farmers’ productivity and examined how this problem and managerial factors prevent farmers from achieving optimal technical efficiency levels using a stochastic frontier analysis (SFA). PWs induce productivity losses ranging from 21% to 50%. Farmers seem to cope with PW through learning from experiencing PW problem. Finally, we estimated weeding labour inefficiencies using a Data Envelopment Analysis (DEA) with directional input distance function and a single truncated bootstrap regression to identify sources of inefficiencies. Results suggest that, farmers can save substantial (58% – 69%) weeding labour without reducing rice production. No evidence was found that the currently used manual weeding modalities were able to manage parasitic weeds efficiently. The main finding of this thesis is that in sub-Saharan Africa, PWs infestation has a negative impact on rainfed rice systems’ productivity and the use of production resources. However, these impacts can be reduced if farmers have a good access to production resources and manage them efficiently.

 

 

Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Wageningen University
Supervisors/Advisors
  • Oude Lansink, Alfons, Promotor
  • Mourits, Monique, Co-promotor
  • Rodenburg, J., Co-promotor
Award date1 Dec 2014
Place of PublicationWageningen
Publisher
Print ISBNs9789462571266
Publication statusPublished - 2014

Keywords

  • rice
  • agricultural production systems
  • crop production
  • weeds
  • parasitic weeds
  • striga hermonthica
  • striga asiatica
  • control
  • weed control
  • rainfed agriculture
  • economic impact
  • social factors
  • decision making
  • farmers
  • africa south of sahara
  • benin
  • cote d'ivoire
  • tanzania

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