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Xanthomonas Wilt of Banana (BXW) is a complex problem in the African Great Lakes Region that is affecting the livelihoods of millions of smallholder farmers. Since the first disease reports from Uganda and the Democratic Republic of Congo in 2001, BXW has been studied widely. The majority of these studies focus on the technological or biophysical dimensions, while aspects and influence of socio-cultural, economic and institutional dimensions only recently started to gain attention. This paper provides an in-depth analysis of the broader BXW problem using a systems perspective, with the aim to add to the understanding about reasons for poor uptake of appropriate disease management practices, and limited ability to prevent rather than control BXW in the region. We comprehensively describe and analyse the various problem dimensions, and determine relations with data, information, knowledge, and connectivity. Building on this, the paper explores and discusses entry-points for the use of Information and Communication Technologies (ICT) and citizen science tools to better address BXW in banana production systems.
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NJAS - Wageningen Journal of Life Sciences
journal homepage: www.elsevier.com/locate/njas
Research paper
Xanthomonas Wilt of Banana (BXW) in Central Africa: Opportunities,
challenges, and pathways for citizen science and ICT-based control and
prevention strategies
Mariette McCampbell
a,b,
, Marc Schut
a,b
, Inge Van den Bergh
c
, Boudy van Schagen
d
,
Bernard Vanlauwe
e
, Guy Blomme
f
, Svetlana Gaidashova
g
, Emmanuel Njukwe
h
, Cees Leeuwis
b
a
International Institute of Tropical Agriculture (IITA), Kacyiru, KG 563 Street #3, P.O. Box 1269, Kigali, Rwanda
b
Knowledge, Technology and Innovation Group, Wageningen University and Research, P.O. Box 8130, 6700 EW Wageningen, The Netherlands
c
Bioversity International, C/O KU Leuven, W. De Croylaan 42, P.O. Box 2455, 3001 Leuven, Belgium
d
Bioversity International, HK Pootstraat 10, 3906 WT, Veenendaal, The Netherlands
e
International Institute of Tropical Agriculture (IITA), c/o ICIPE, oThika Road, P.O. Box 30772, Nairobi, Kenya
f
Bioversity International, c/o ILRI, P.O. Box 5689, Addis Ababa, Ethiopia
g
Rwanda agriculture Board (RAB), P.O. Box 5016, KK 18 Ave, Kigali, Rwanda
h
International Institute of Tropical Agriculture (IITA), Quartier Kabondo, Rohero 1, Avenue 18 Septembre 10, Bujumbura, Burundi
ARTICLE INFO
Keywords:
ICT4Ag
Digital innovation
Environmental monitoring
Agricultural transformation
Systems analysis
Banana wilt disease
ABSTRACT
Xanthomonas Wilt of Banana (BXW) is a complex problem in the African Great Lakes Region that is aecting the
livelihoods of millions of smallholder farmers. Since the rst disease reports from Uganda and the Democratic
Republic of Congo in 2001, BXW has been studied widely. The majority of these studies focus on the techno-
logical or biophysical dimensions, while aspects and inuence of socio-cultural, economic and institutional
dimensions only recently started to gain attention. This paper provides an in-depth analysis of the broader BXW
problem using a systems perspective, with the aim to add to the understanding about reasons for poor uptake of
appropriate disease management practices, and limited ability to prevent rather than control BXW in the region.
We comprehensively describe and analyse the various problem dimensions, and determine relations with data,
information, knowledge, and connectivity. Building on this, the paper explores and discusses entry-points for the
use of Information and Communication Technologies (ICT) and citizen science tools to better address BXW in
banana production systems.
1. Introduction
Infectious crop diseases continue to cause large yield losses with
underestimated social and economic impacts in developing countries
(Vurro et al., 2010). Xanthomonas Wilt of Banana (BXW), caused by the
bacterium Xanthomonas campestris pv. musacearum,aects production
of all types of bananas, in all major production regions in East and
Central Africa (Tripathi et al., 2009). The disease is detrimental to
banana-based farming systems, due to easy spread, rapid in-plant de-
velopment, absence of resistant cultivars, and inevitable death of in-
fected plants (but not the whole physically interconnected mat due to
incomplete systemicity) in absence of disease resistant varieties
(Tripathi et al., 2009). Banana is an important source of livelihood for
millions of farmers, providing food and income, as well as playing an
important role in the social life of populations in the African Great
Lakes Region (i.e. Burundi, the Democratic Republic of the Congo,
Kenya, Rwanda, Tanzania, and Uganda) (Van Damme et al., 2014). For
example, 30% of the cultivated land in the region is occupied by banana
(Van Asten et al., 2004), and in a country like Rwanda banana con-
tributes to approximately 50% of the diet of 32% of the households
(Nkuba et al., 2015). Hence production declines not only impact
household income but also food and nutrition security, and social and
cultural wellbeing.
BXW is a complex problem that is rooted in a multitude of chal-
lenges, embedded and cross-cutting in six dierent system dimensions,
and has shown to be persistent and recurrent. Since the rst disease
reports from central Uganda and east DR Congo in 2001, BXW has been
studied widely. Most studies focus on the technological or biophysical
dimensions (Biruma et al., 2007;Shimwela et al., 2016;Tinzaara et al.,
2016) and cultural practices. Key practices are the originally
https://doi.org/10.1016/j.njas.2018.03.002
Received 31 August 2017; Received in revised form 8 March 2018; Accepted 8 March 2018
Corresponding author at: International Institute of Tropical Agriculture (IITA), Kacyiru, KG 563 Street #3, P.O. Box 1269, Kigali, Rwanda.
E-mail addresses: M.McCampbell@cgiar.org,mariette.mccampbell@wur.nl (M. McCampbell).
NJAS - Wageningen Journal of Life Sciences xxx (xxxx) xxx–xxx
1573-5214/ © 2018 The Authors. Published by Elsevier B.V. on behalf of Royal Netherlands Society for Agricultural Sciences. This is an open access article under the CC BY-NC-ND
license (http://creativecommons.org/licenses/BY-NC-ND/4.0/).
Please cite this article as: McCampbell, M., NJAS - Wageningen Journal of Life Sciences (2018), https://doi.org/10.1016/j.njas.2018.03.002
recommended Complete Mat Uprooting technology (CMU), and the
increasingly suggested Single Disease Stem Removal technology (SDSR)
(Box 1). CMU and SDSR should be combined/applied with other en-
dorsed practices, e.g. early removal of the male bud using a forked
stick, disinfection of tools, selection of clean planting material, in order
to be most eective. Aspects and impacts of the non-technological di-
mensions (i.e. socio-cultural, economic, institutional, and political)
only recently started to gain attention. Yet, addressing a complex pro-
blem like BXW requires an integrated approach with attention for both
technological and non-technological dimensions (Schut et al., 2014a).
In other words, a focus on solving individual (technological) challenges
will likely be ineective when failing to simultaneously understand and
address interrelationships with (non-technological/socio-cultural, eco-
nomic, institutional, and political) challenges, and the roles of dierent
actors, and dierent system levels.
As amplied by Cieslik et al. (2018) in this issue, opportunities to
collect and exchange data, information, and knowledge emerge from
the enhanced availability of mobile/smart phones, smart Information
and Communication Technologies (ICT), and internet in low and middle
income countries. Moreover, these innovations give prospect to resolve
communication and connectivity related challenges in rural areas. The
emergent robust, aordable and low maintenance sensing, data pro-
cessing, visualization and other ICT enabled features have also led to
growth in the number of so called citizen science initiatives (Buytaert
et al., 2014). Citizen science (also referred to as environmental or
participatory monitoring) was introduced by Irwin (1995) more than
two decades ago as a concept that enables active involvement of non-
scientists in research design, data collection and data interpretation
(Buytaert et al., 2014). Until now, most citizen science initiatives oc-
curred in high-income countries where volunteers engaged in mon-
itoring and reporting of environmental aspects (e.g. counting birds or
insects, monitoring spread of communicable diseases). However, si-
milar initiatives start to take oin developing countries too. Wagen-
ingen University and Researchs Environmental Virtual Observatories
for Connective Action (EVOCA) programme explores the potential of
such ICT-based citizen science platforms for tackling complex socio-
ecological problems in six case studies in Africa. The complex problem
of BXW that we focus on in this paper represents one of those case
studies.
In this paper, we contribute to two strategic gaps in the scientic
literature: (i) comprehensive understanding of both the technological
and non-technological BXW problem dimensions (ii) how problem di-
mensions are related to (the lack of) data, information, knowledge, and
connectivity. In doing so, the paper has three main objectives: (i) to
comprehensively describe and analyse BXW in the Great Lakes Region,
thereby contributing to a deeper understanding of the complex pro-
blem, (ii) to determine the potential role of data, information, knowl-
edge, and connectivity in addressing the problem, and (iii) to explore
whether and how citizen science and ICT-based platforms can con-
tribute to overcoming specic BXW problems in Central Africa.
The next section provides a short historical background on banana
farming and BXW in the Great Lakes Region (Section 2). A conceptual
and methodological framework is presented in Section 3. Thereafter,
the main characteristics of the BXW problem in the region are identied
and discussed per system dimension (Section 4). In Section 5, we ex-
plore how these characteristics are interlinked with data, information,
knowledge, and connectivity challenges. In the same section, we ana-
lyse how citizen science and ICT could oer appropriate intervention
mechanisms for the identied problem characteristics. Lastly, Section 6
provides a reection on our ndings and some practical recommenda-
tions.
2. Historical overview and gaps in our understanding of BXW and
its management in the Great Lakes Region
2.1. History, symptoms and spread of BXW
Bananas form an important staple crop in East and Central Africa.
Box 1
Description of managing BXW, the traditional and the alternative way.
The initial way: Complete Mat Uprooting (CMU)
Uprooting of an entire banana mat after diagnosis of BXW, even if only one plant in the mat shows symptoms, has long been the
recommended control BXW practice. Although very eective in removing most of the inoculum causing BXW, Complete Mat Uprooting
(CMU) is tedious, labour intensive, time consuming. A side-eect is that asymptomatic plants are removed too. It requires from farmers to
replace the removed mats with new planting material. This need makes CMU costly, further aggregated by high labour demand and long-
term impact on production. Moreover, for optimal impact, i.e. reduce risk of reinfection, CMU should be practiced by all infected farmers in
an area. Farmers are often reluctant to remove an entire banana mat when disease symptoms are minor and symptomless shoots could
potentially still bear an edible bunch. Nevertheless, Blomme et al. (2017) suggest that in regions with intensive, market-oriented banana
systems, where the goal is to eradicate BXW from the eld, CMU could be a preferred management option. In addition, CMU would be
applied where the disease appears for the rst time in a location and is still limited to a few mats. Unfortunately, CMU cannot guarantee
long term eradication of BXW, as there is always a risk of reinfection under small-scale farming conditions (Tinzaara et al., 2013).
The alternative way Single Diseased Stem Removal (SDSR)
Single Diseased Stem Removal (SDSR) technology is based on understanding that adjacent/physically attached shoots of an infected
mother stem/plant are often disease free. SDSR is a less intensive alternative to CMU. Continuous removal of symptomatic plants, cutting
them at soil level when observing rst symptoms, can drastically reduce inoculum levels and disease incidence over time (from up to 80%
to below 2% within 3 months, and below 1% within 510 months) (Blomme et al., 2017). Advantages of SDSR over CMU are low cost, and
simple and easy applicability. Additionally, farmers can individually control BXW in highland settings with highland type bananas [AAA-
EAH genome group] (van Schagen et al., 2016). This lessens need for collective action in AAA-EAH dominated systems in high elevation
settings, allowing for eective out-scaling of the technology by targeting individual households. Nevertheless, a collective approach is
preferable to prevent the incursion of inoculum from neighbouring infected farms. In lowland areas and in ABB dominated systems where
insect vector mediated transmission is rampant, early male bud removal should be rigorously applied too. With SDSR there is no need for
replanting and productivity of a BXW infected eld can be restored in a relatively short time with non-removed shoots that reach their
harvest stage. This makes SDSR a suitable management strategy for subsistence banana systems that target management of BXW at ac-
ceptable levels (< 1%) (Blomme et al., 2017). However, SDSR does not remove all inoculum and requires rigorous application for as long as
disease is present on or near a farm. Practice alongside other cultural management practices is critical (e.g. male bud removal, and tool
sterilization), making BXW management still knowledge and labour intensive and necessitating continuous training and extension eorts.
M. McCampbell et al. NJAS - Wageningen Journal of Life Sciences xxx (xxxx) xxx–xxx
2
Among the worldstop ten producers of cooking bananas, Uganda ranks
rst, and DR Congo holds the 8th position (FAO and FAOSTAT, 2014).
For production of dessert bananas Tanzania is the worlds 8th largest
producer, and Rwanda the 10th (FAO and FAOSTAT, 2014). More than
50% of Sub-Saharan Africas production takes place in the African Great
Lakes Region (Frison and Sharrock, 1998;Blomme et al., 2014). Ba-
nanas are of major economic importance in this region, forming an
important part of peoplesdaily diet and providing income and food
security to millions of smallholder households.
BXW was rst reported in Ethiopia on enset (Ensete ventricosum), a
relative of banana, in 1968 (Yirgou and Bradbury, 1968) and hereafter
on banana in 1974 (Yirgou and Bradbury, 1974)(Fig. 1). BXW was
recognized as a thread for banana production in the entire region, but
remained conned to Ethiopia until rst outbreaks were observed in
Central Uganda in 2001 (Tushemereirwe et al., 2003). Since then BXW
has spread through to DR Congo (2001), Rwanda (2002), Tanzania,
Kenya (2005) and Burundi (2010) respectively (Karamura et al., 2005;
Niko et al., 2011;Tushemereirwe et al., 2003). Trans-boundary trans-
mission of the disease has been reported. For example, in Rwanda, BXW
was rst identied in the North-Western region around Rubavu district,
where local farmers mentioned seeing rst symptoms around
20022003. BXW most likely spread into Rwanda from DR Congos
Kivu region due to continuous exchange of people and goods across the
Rubavu-Goma border and the fact that rst outbreaks of BXW in DR
Congo were conrmed near this border in the Masisi region north of
Goma (Reeder et al., 2007).
Several governments took rigorous actions in an attempt to eradi-
cate BXW. For example, Uganda installed task forces assigned with the
mission to cut down and destroy infected plantations/elds, remove
male buds to prevent insect vector transmission, and control cutting of
bunches with non-sterilized tools (Tushemereiwe et al., 2006). These
types of interventions are rigorous and have had eect in reducing
disease incidence (Bouwmeester et al., 2016). However, the invasive
nature of uprooting entire plantations received little support from
farmers (Blomme et al., 2017). Although disease eradication has been
achieved in some sites, BXW has reached endemic status in other sites
where resurgence is observed after a period of control, often due to a
less rigorous application of control measures (Tinzaara et al., 2014).
Additionally, endemicity of BXW is sometimes attributed to lack of
awareness and knowledge about disease transmission, diagnosis, and
disease management by stakeholders across the value chain. Alter-
natively, reluctance of farmers to actively apply awareness and
knowledge due to the invasive/time-consuming nature of re-
commended practices can be a cause. As complete eradication of the
disease has proven dicult to achieve, the focus has shifted towards
development of strategies that use SDSR and complementary
approaches to reach a situation in which BXW is manageable and dis-
ease incidence minimized to economically acceptable levels.
2.2. Gaps in understanding the disease and its management
Since the rst reports of BXW in the Great Lakes Region in 2001,
there have been numerous publications analysing the disease. Initial
focus of academic literature was on improving understanding about the
diseases epidemiology and control (mainly building on existing
knowledge from banana bacterial wilts in Asia and Latin America), and
later on strategies to develop BXW resistant banana cultivars, mostly
through genetic engineering (Tripathi et al., 2009;Biruma et al., 2007).
This contributed to considerable progress in terms of knowledge about
the technological and biophysical dimensions of BXW, including disease
epidemiology, bio-engineering of resistant varieties and, updating/ne-
tuning cultural control practices. Based on increased understanding of
e.g. within plant and mat systemicity and disease spread/dissemination,
cultural control practices were developed and updated. The con-
centration on understanding the biophysical and technological dimen-
sions of the crop protection problem corresponds with ndings by Schut
et al. (2014c), who concluded that there is generally much less atten-
tion for other problem dimensions (e.g. socio-cultural (e.g. stakeholder
beliefs, or locally preferred practices), economic (e.g. costs of disease
management), and institutional (e.g. trade policies, or disease control
strategies)). Capturing the impact of these system dimensions, e.g. on
BXW transmission at farm and regional scales, as well as the role of
surveillance and control mechanisms, and their impact on combating
BXW (Tinzaara et al., 2016;Markham, 2009), becomes gradually more
important now that focus shifts from developing knowledge to devel-
oping suitable interventions. This includes investigating (i) diversity
among farmers, their production objectives and barriers for adopting
(BXW) technologies, (ii) eective strategies of information provision
and capacity development for farmers, (iii) information needs and
communication preferences to better understand and address con-
straints and challenges, and (iv) how multi-stakeholder processes can
support joint problem identication, analysis and collective action
(Schut et al., 2014c). This diagnostics paper does not oer such an
investigation, yet it conveys the importance of each problem dimension
by providing a comprehensive assessment of their contribution to the
persistence of BXW.
3. Conceptual and methodological framework
3.1. Conceptual framework
The conceptual framework for this study is rooted in three coherent
theoretical concepts that t the studys purpose: (i) systems perspective
on complex agricultural problems, (ii) ICT for agriculture and citizen
science, and (iii) theoretical understanding of data, knowledge, in-
formation, and connectivity. Each of these concepts responds to one of
the study objectives. We use systems perspective to frame our analysis
of BXW in Section 4. Theory on ICT for agriculture and citizen science
informs our assessment and discussion of potential contributions of ICT
in addressing BXW. Furthermore, the four intervention categories pre-
sented in the discussion section build on the notion that ICT for agri-
culture and citizen science are approaches for generating and ex-
changing various classes of content, as well as connecting people. The
concepts of data, knowledge, information, and connectivity ad-
ditionally help to perceive dierences between the categories.
3.1.1. Complex problems and systems perspectives
Complex agricultural problems are problems in the agricultural
domain that cannot be resolved but rather have to be managed.
Complex agricultural problems are typically unstructured, embedded in
the agricultural system and therefore persistent, relentless, and cross-
cutting (Weber and Khademian, 2014). BXW can be considered a
Fig. 1. Schematic overview of historical spread of Xanthomonas Wilt of Banana (BXW) in
the Great Lakes Region, with the year in which BXW was rst reported (map developed
based on data from Yirgou and Bradbury, 1974;Karamura et al., 2005;Niko et al., 2011;
Tushemereirwe et al., 2003;Yirgou and Bradbury, 1968;Castellani, 1939).
M. McCampbell et al. NJAS - Wageningen Journal of Life Sciences xxx (xxxx) xxx–xxx
3
complex problem as it too is persistent, unresolvable, and embedded
and cross-cutting in the banana system. BXW is rooted in a multitude of
challenges in various system dimensions (i.e. biophysical, technolo-
gical, social, cultural, economic, institutional, and political) (Markham,
2009), and as past experiences have shown that technology-based so-
lutions do not necessarily provide the full answer, an alternative ap-
proach, which is more integrated and knowledge-based, is required
(Markham, 2009). Addressing such problems rather requires colla-
boration between dierent actors (e.g. farmers, extensionists, re-
searchers), at dierent levels (e.g. local, regional, national) to address
challenges in dierent dimensions (e.g. social, economic, institutional)
(Schut et al., 2014d). Improving understanding of the interplay of
various system dimensions is important, given that current eorts to
out-scale interventions and technologies, which gave promising results
at local or farm level, mostly yield unsatisfying success rates (Tinzaara
et al., 2016). This associates with the notion that interventions aiming
to solve crop disease issues must be tailored to a specic crop pro-
duction system (Jogo et al., 2013), and that farmers should be oered
management options tting with their local and individual context
(Blomme et al., 2017).
3.1.2. ICT for agriculture and citizen science
With their strength to allow for co-creation of knowledge and joint
reection, contemporary ICTs oer immense potential for addressing a
variety of todays complex agricultural problems. For example, inter-
ventions in which contemporary ICTs such as mobile phones comple-
ment or replace face-to-face agricultural service delivery are increas-
ingly observed (FAO, 2017). As much as ICTs can be useful, they should
not be seen as a panacea for solving all complex agricultural problems,
or for providing all pieces of the puzzle that are required to manage
complex problems (Deichmann et al., 2016;Nelson, 2010).
Contemporary ICTs (e.g. mobile phones, tablets) are a key driver for
the recent boom in citizen science initiatives. Citizen science initiatives
focus on crowd-sourcing data from citizens, often in conjunction with
an online, ICT-based platform (Fradera et al., 2015). The term citizen
science represents (i) a science that assists the needs and concerns of
citizens and, (ii) a form of science developed and enacted by citizens
themselves. Most citizen science platforms aim to monitor the en-
vironment and foster collaborative research, learning, and action
(Cieslik et al., 2018). Citizen science emerged from the observed need
for an approach to enhance dialogue between scientic and citizen
groups, as well as to recognize the added value of building on expertise
and understandings possessed by citizen in decision making processes
(Irwin, 1995). Benets include increased awareness and knowledge,
and a more participatory and democratic research process for citizens,
while scientists prot from faster access to larger data sets for studying
complex problems at lower costs (Fradera et al., 2015). Identied
challenges with citizen science include the potential dierence between
who participates and the population targeted, reliability of data col-
lected, and communication of models developed based on citizen sci-
ence data (Buytaert et al., 2012).
3.1.3. Framing data, knowledge, information, and connectivity
Deployment of ICT tools and citizen science-based interventions in
agriculture are only useful when they mediate in generating and
sharing content or connecting people in the agricultural system. It has
been argued that ICT-based platforms can enhance connectivity be-
tween disassociated populations, enabling participatory monitoring
(collection and exchange of data), broad accessibility of information,
and dialogue about scientic-based models (knowledge creation)
(Jalbert and Kinchy, 2016). To further conceptualize this, we rst look
at the understanding of, and dierences between, data, information,
and knowledge. These have been described widely (Alavi and Leidner,
2001;Leeuwis and van den Ban, 2004;Acko, 1999) and the dierence
between the two concepts can be subtle (Alavi and Leidner, 2001;
Leeuwis and van den Ban, 2004). Given the scope of this paper we use
broader denitions of the three terms. In this study, we understand data
as raw facts and numbers from observations or measurements (for ex-
ample outputs from measurements of the number of banana mats in-
fected with BXW); information as processed or interpreted data made
tangible in useful descriptions (for example a message informing ex-
tensionists that 20% of all banana mats in a region are infected with
BXW and need to be managed with appropriate cultural control prac-
tices) that turn it into something that is accessible and actionable; and
knowledge as interpreted and personalized data and information (for
example the knowledge that with a 20% plant incidence rate SDSR is
the most eective management strategy for farmers operating in that
region) (Alavi and Leidner, 2001;Leeuwis and van den Ban, 2004;
Acko, 1999).
Knowledge is inuenced by and inuences for example mindset,
behaviour, and learning processes (Leeuwis and van den Ban, 2004). It
also informs peoples capacity to understand patterns to which they can
take action (Alavi and Leidner, 2001;Acko, 1999). Data, information,
and knowledge are connected through a forward ow: data is processed
into information, which is then assimilated into knowledge. A reverse
ow is possible too, when knowledge explains information and lters
and processes data (Heeks, 2018).
The dierence between information and knowledge is that the rst
entails processed data useful to its recipient, while the second ag-
gregates information to a higher level by assimilating it into a coherent
framework of understanding (Heeks, 2018). This brings us to the ad-
ditional description of knowledge as the sum of what has been per-
ceived, discovered and learned (6).
Alavi and Leidner (2001) make two important points to take into
account for exchanging information and knowledge that is actionable to
a receiver: (i) most information has little value to a user unless it goes
through a process of reection, enlightenment, or learning, and (ii)
knowledge is individual and to be useful for someone else it needs to be
expressed and communicated in such way to a receiver that it is in-
terpretable. This links with the notion that uncontextualized knowl-
edge, that is analysed and interpreted by experts and then projected
back to a locality, is likely inappropriate for utilization (Cieslik et al.,
2018;Leeuwis and van den Ban, 2004).
Lastly, we understand connectivity as the ability of and opportunity
for stakeholders to interact and collaborate, as well as to coordinate and
organize themselves (Bennett and Segerberg, 2012). Connectivity re-
lates to how people interact, and who interacts with who, and can
therefore inuence collection and exchange of data, information, and
knowledge. The absence of eective stakeholder collaboration and
connectivity can form a bottleneck for agricultural system development
(Schut et al., 2014a), is often related to heterogeneity in communities
and weak leadership and control arrangements, power imbalances and
information asymmetries (Poteete et al., 2010;Olson, 1965), and a
limiting factor to solving complex agricultural problems (Schut et al.,
2014b). For example, banana farmers excluded from interactions with
extension ocers and operating individually are more likely to lack
access to information about BXW management. According to Bennett
and Segerberg (2012) digital innovations foster opportunities for
communicative ways of organizing that do not rely on formal organi-
zational coordination but rather on self-organizing networks, thereby
creating new spaces of interaction that can be accessed by many. Cieslik
et al. (2018) argue that this may be of relevance in the context of en-
vironmental management in developing countries, hence for an agri-
cultural challenge like BXW.
3.2. Methodological framework
3.2.1. Study location
Although much of the data presented in this paper apply broadly
across the Great Lakes Region, we sometimes focus on specic BXW-
related issues in Rwanda. This is for three reasons. First, BXW has been
a recurring problem in Rwanda since the initial identication in 2002,
M. McCampbell et al. NJAS - Wageningen Journal of Life Sciences xxx (xxxx) xxx–xxx
4
Table 1
Overview of problem descriptions and causes per problem dimension.
Problem
dimension
Biophysical Technological Socio-cultural Economic Institutional Political
Description of
the
problem
Relatively small genetic variability
of banana (mostly ABB and AAA-
AE) in a densely populated region
in combination with an
environment that is suitable for
insect vector transmission
Costly, time consuming and
complicated process to unravel
disease epidemiology, screen
genepool for resistance, develop
transgenic varieties, and develop
and update control practices
Poor targeting of diverse smallholder
farmers who base decisions on their
direct cost-benet ratio
(Cost) Inecient control and
prevention of BXW by farmers
and extension services
(including e.g. labour, time,
access to in- and outputs)
Diversity in policies and their
implementation and
performance in the African
Great Lakes Region
Top-down nature of the
agricultural sector in general and
extension services in particular
(in Rwanda) and/or ineective
formal organization of extension
services
Causing
challenges
Lack of BXW-resistant cultivars
(Tripathi et al., 2009)
(Long-distance) disease
transmission through airborne
(insect) vectors, bats and birds,
and contaminated planting
material (Tinzaara et al., 2013;
Blomme et al., 2014)
Resurgence of BXW after a
period of control due to
continued vector pressure and
reduced control intensity
(Tinzaara et al., 2013)
Absence of BXW-resistant
(transgenic) cultivars (Tinzaara
et al., 2016)
Insucient understanding of
disease epidemiology (Tinzaara
et al., 2016)
Low availability of clean plant
material
Single Disease Stem Removal
(SDSR) technology does not
remove all inoculum (Tinzaara
et al., 2016)
Farmers not enough involved in
nding solutions with positive cost-
benet ratio (Mwangi and Nakato,
2009)
Awareness campaigns and trainings
not targeted to vulnerable farmer
groups (e.g. women, youth)
(Blomme et al., 2014)
Low adoption of control
technologies limiting sustainability
of disease control eorts
(Ndayihanzamaso et al., 2016)
Low farmer awareness of BXW
(Ndayihanzamaso et al., 2016)
Limited attention for inuence of
gender roles on adoption of control
and prevention strategies in the
household (Blomme et al., 2017).
E.g. gender roles can limit womens
decision making/agency/access to
information
Insect-vector transmission
susceptible Pisang Awakor
Kayinja(ABB) variety culturally
popular among smallholder farmers
(Nkuba et al., 2015)
Lack of collective action among
farmers and other stakeholders
No accurate predictive
system for early disease
diagnosis and action
(Bouwmeester et al., 2016)
Lack of reliable data on
economic losses (Vurro
et al., 2010)
Cumbersome and expensive
nature of traditional
management techniques
(e.g. Complete Mat
Uprooting (CMU) (Blomme
et al., 2017)
Often lack of income
generating alternatives that
majority of farmers can rely
one when banana
production is reduced
Priority setting for
continuous investment
lacking in small number of
farmers with o-farm jobs
(Okech et al., 2005)
Fundamental research
expensive, time consuming
and complex
Absence of appropriate
institutional frameworks
for policy guidance and
byelaws (e.g. on quarantine
measures) (Tinzaara et al.,
2013)
Low buy-in of technologies
due to unknown interests
and incentives for
stakeholders (Mwangi and
Nakato, 2009;Kubiriba
et al., 2012)
Ineective surveillance
methods leading to
untimely actions (Tinzaara
et al., 2016)
Dierences in the
institutional environment
in various Great Lakes
countries (Vurro et al.,
2010)
Lack of a working formal
seed system (Tinzaara
et al., 2013)
Lack of adequate knowhow
and sensitization about
BXW among extensionists
and other stakeholders
along the value chain
(Tinzaara et al., 2013)
Lack of participatory and
demand driven approach
(Nkuba et al., 2015;Kubiriba
et al., 2012)
Inadequate mobilization and
sensitization of key
stakeholders (Tinzaara et al.,
2016)
National level political actors
determine allocation of funds
and eorts for crop extension
services (Cioo et al., 2016)
M. McCampbell et al. NJAS - Wageningen Journal of Life Sciences xxx (xxxx) xxx–xxx
5
despite attempts to control it. Ocials in the Ministry of Agriculture
and Animal Resources articulated existence of keen interest for in-
novations providing a lasting solution (Ministry of Agriculture, personal
communication, July 2017). Second, Rwanda has the most ambitious
objectives for use of ICT in rural and agricultural transformation in the
African Great Lakes Region. The country proles itself as the ICT hub in
Africa and adopted several policies and strategies to enhance the use of
ICT among which the National ICT for Rwandan Agriculture Strategy
(Ministry of Agriculture and Animal Resources, 2016). Third, Rwanda is
the main focus country of the EVOCA case study that was the entry-
point for our diagnostics study.
3.2.2. Data collection and analysis
Data for this qualitative paper were gathered through various
methods: literature and secondary data review, scoping eld visits,
semi-structured interviews, and semi-structured group interviews. The
methodsfocus on BXW was stronger than on ICT and citizen science in
response to our research objectives. This mixed approach was appro-
priate since it (i) allowed for a broad assessment of scientic and eld
level knowledge and understanding about BXW, (ii) provided the ne-
cessary input to unravel the research problem across all system di-
mensions both technologically and socially in Section 4, and (iii) sup-
ported development of suitable pathways for interventions in Section 5.
More specically, Table 1 in Section 4was developed based on review
of literature and secondary data, while Table 2 in Section 5.1 emerged
from synthesizing information from Section 4and linking this with the
data, information, knowledge and connectivity concepts as laid out in
the conceptual framework.
First, literature and secondary data were reviewed. For the BXW,
banana systems, and citizen science related literature snowball sam-
pling was used, tracing references in articles to identify additional re-
levant peer-reviewed articles and grey-literature. Advancements in
understanding of technological and biophysical aspects, that led to
changing/ne-tuned ideas about appropriate BXW control strategies,
and recently developed interest for social aspects were considered.
Therefore, recent publications (from 2015 to 2017) were consulted rst
and supported identication of older relevant publications. ICT for
agriculture related literature was purposively selected from a set of
articles retrieved through search queries in Web of Science, Scopus and
CAB-abstract. Selection took place based on relevance in relation to the
study objectives. Catering for developments in the research eld, focus
was on recent publications (after 2007). Second, scoping visits to ba-
nana production areas in Rwandas Eastern Province (Kayonza District,
2 areas visited) and Southern Province (Kamonyi District, 1 area vis-
ited) took place between January and June 2017, and Burundis
Muyinga District (August 2017, 2 areas visited). Sampling was purpo-
sive, based on presence of existing projects from IITA (CIALCA, in
Rwanda) and Bioversity International (DFAP-AMASHIGA, in Burundi).
Third, aforementioned visits facilitated semi-structured interviews in
Rwanda. We purposively selected 2 lead farmers who represented
members of a banana innovation platform in Kayonza, covering ex-
periences with BXW, disease incidence in the area, and management
strategies. Fourth, four semi-structured group interviews were orga-
nized with in total approximately 50 smallholder farmers (mixed male,
female, age) in Muyinga, Burundi, focusing on experiences with dif-
ferent control strategies and use of mobile technologies. These inter-
views asked a regular set of questions used by project staduring
routine visits with the addition of questions about mobile technology by
the researcher.
4. Results: unravelling dimensions of the BXW problem
This section unravels the dierent dimensions of BXW as a complex
problem and identies dierent challenges under each of the six system
dimensions. Table 1 summarizes for each dimension a problem de-
scription and characteristics that are discussed in detail in adjacent
paragraphs. We build on ndings and interpretations from scientic
literature and secondary data, and supplement by input retrieved from
eld visits and focus group discussions.
4.1. Biophysical dimension
Biophysical characteristics refer to issues of biological nature that
may or may not be controlled. Roughly, edible bananas are divided into
four categories, each with their own varieties and purposes: (i) dessert
(sweet yellow banana, eaten ripe), (ii) cooking (unripe green bananas
for cooking, also known as matoke), (ii) plantain (for cooking and
frying), and (iv) juicing (also called beer banana, used for production of
local brews) (Vurro et al., 2010). Another means of categorization is in
dierent subgroups: East African highland cooking and brewing culti-
vars (AAA-EA), exotic brewing, dessert and roasting types (AB, AAA,
AAB, ABB) and hybrids (Nkuba et al., 2015). No resistant cultivars have
been identied (Tripathi et al., 2009), and the locally popular and
widely spread ABB cultivars (Pisang Awakor Kayinja)are particularly
prone to insect vectored transmission of Xcm (BXW) (Nkuba et al.,
2015). This cultivar is particularly common in non-commercial, low-
management areas further which adds to risk for disease transmission.
Susceptibility of banana to BXW and infection risk are intensied by the
large and, especially in Rwanda, densely populated banana growing
areas in the Great Lakes Region. Dierent vectors for BXW transmission
are: airborne (insects, bats, or nectar sucking and fruit pulp eating
birds), contaminated garden tools, infected planting material and
browsing animals. Especially airborne vectors are a typical biophysical
challenge. The Great Lakes region is specically suitable for this type of
transmission (Mwangi and Nakato, 2009), due to for example insect
favourable climatological conditions and, the aforementioned human
population density and pressure on land. The resulting lowered ability
to predict and control disease spread claries why BXW can suddenly
pop-up in previously unaected areas.
BXW symptoms appear as early as 34 weeks (Tripathi et al., 2009)
and up to 16 months (Ocimati et al., 2013) after infection, depending
on conditions. Recent studies conrmed that BXW does not necessarily
infect or cause symptoms in all shoots physically attached to an infected
(mother) plant in a mat, a condition that is referred to as incomplete
systemicity (Ocimati et al., 2015). Symptoms of BXW are progressive
yellowing, withering and necrosis of leaves; fruits that rapidly and
prematurely ripen and show internal browning; shrivelling/rotting
male owers and bracts, stem and bunches; withering and rotting of the
entire plant (Biruma et al., 2007).
The lack of BXW resistant cultivars necessitates use of cultural
management practices. Survival of the inoculum on tools used in such
practices and presence of e.g. free roaming animals (Tinzaara et al.,
2013;Blomme et al., 2014) increases the complexity to prevent trans-
mission within elds and over (long) distances. Biophysical character-
istics impact chances of BXW resurgence after a disease-free period.
Tendency is to reduce rigour after incidence levels reduced sig-
nicantly, while in fact continuous eld monitoring and application of
appropriate management practices are needed (Tinzaara et al., 2013).
This makes ghting BXW labour intensive both nationally and locally
however. Our discussions with farmers showed that farmers indeed
tend to reduce monitoring practices when disease pressure is low,
especially for elds further away from the homestead. Additionally,
farmers critiqued impact of neighbours who fail to appropriately
maintain their bananas and thereby increase disease infection risks.
4.2. Technological dimension
Technological characteristics relate to the role technological ad-
vances play in solving agricultural issues. For example, technological
advances like improved diagnostics, disease management strategies,
and generally improved agronomic practices can all reduce risk of
major disease outbreaks. Research on BXW led to improved diagnostics
M. McCampbell et al. NJAS - Wageningen Journal of Life Sciences xxx (xxxx) xxx–xxx
6
and increased knowledge about epidemiology, as well as the develop-
ment of dierent technologica options for e.g. diagnostics, management
and control. These options however face limitations, e.g. SDSR does not
completely remove inoculum and CMU is labour intensive and requires
replanting of uprooted mats.
Absence of BXW resistant cultivars forms a, partially, technical issue
too. Eorts to develop transgenic cultivars with resistance are in an
advanced stage, however not yet to the point of marketability.
Additionally, transgenic cultivars are (1) only available for some pop-
ular cultivars, and (2) not or limitedly acceptable within existing re-
gional bio-control policies. Also, clean planting material is perceived as
expensive while its availability is low. Correspondingly, we observed
that farmers mostly sourced unscreened material (i.e. suckers/lateral
shoots) from own or neighbouring farms, a practice posing the risk of
disease spread/(re)introduction (Tinzaara et al., 2013).
4.3. Socio-cultural dimension
Socio-cultural challenges are mostly the result of common one-size-
ts-all approaches that insuciently respect needs and interests of di-
verse groups of farmers. Despite advances made, the epidemiological
knowledgeability of extensionists and farmers is still insucient to
address the problem eectively (Tinzaara et al., 2016). For example,
our interviews with trained farmers in Burundi revealed that some still
struggled with recognizing the disease. Also, not all respondents ap-
plied regular or proper tool disinfection mostly due to limited aware-
ness of the most appropriate practice. Incomplete knowhow/under-
standing and subsequent suboptimal implementation of appropriate
control and prevention strategies leads to new and resurging BXW
epidemics.
Farmers of dierent gender, age and socio-economic groups pursue
dierent livelihood strategies to ensure food, income and nutrition se-
curity, and face dierent land, labour and other resource constraints
(Klapwijk et al., 2014). Information about and access to markets forms
an output constraint (Okello et al., 2012). Smallholder, including ba-
nana-based, farming systems are thus diverse and complex. For ex-
ample, van Damme et al. (2013) found three distinct categories of ba-
nana producers in the Great Lakes Region based on characteristics such
as land-size and productivity. Analysis of the largest group of farmers,
those with medium-sized farms, showed additional heterogeneity (e.g.
in number of crops and crop management practices) which the authors
attributed to varying risk coping strategies. This contributes to system
resilience but impedes rapid transitions towards increased productivity
(van Damme et al., 2013). Next to typologies based on farming system
and livelihood characteristics, it is useful to dierentiate according to
the willingness of a farmer to invest and change practices. Hence,
Silver bulletsolutions to production constraints are an illusion given
the systems complexity (Giller et al., 2011), and thus technologies and
service provisions like awareness campaigns and trainings, need to
target the specic challenges and opportunities of vulnerable farmer
groups (Blomme et al., 2017;Blomme et al., 2014).
Current farmer involvement in the search for innovations with po-
sitive cost-benet ratio is limited (Mwangi and Nakato, 2009). This may
impact local awareness about BXW and understanding of disease se-
verity and spread (Tinzaara et al., 2016;Tinzaara et al., 2013) despite
the many campaigns aiming to inform farmers. The result is disease
transmission through, for example, non-disinfected farm tools or
browsing domestic animals (Tripathi et al., 2009). Moreover, in-
formation provision about disease transmission, spread and control is
ambiguous, inducing beliefs that BXW cannot be controlled eectively
(Ndayihanzamaso et al., 2016). The resultant is low adoption of control
and prevention technologies, limited collective action, late disease di-
agnosis, and ultimately poor sustainability of disease control eorts
(Ndayihanzamaso et al., 2016).
Literature makes note of other persisting mindset issues and, indeed,
during our scoping eld visits and group interviews many of following
challenges came to the surface. Farmers largely base decisions about
disease control mechanisms on the economic risk involved, i.e. the es-
timated cost of controlling BXW needs to outweigh the estimated cost of
losing the crop (Gent et al., 2013). In addition, perceptions of control
technique eectiveness determine adoption decisions (Blomme et al.,
2017). For BXW this mindset proves problematic as initial symptoms
are mild with limited impact on plant mat productivity. Farmers are
hence hesitant to quickly act as benets of traditional control me-
chanisms, such as CMU, have no short-term visibility (Blomme et al.,
2017), while the eort required to apply them and the negative trade-
os are immediately visible. Additionally, the perception exists that
individual eorts are ineective due to the high chance of reinfection if
neighbours do not manage their elds (Blomme et al., 2017). Hence,
most interventions have a curative control character and are im-
plemented when disease manifestation and crop losses are visible in a
large portion of a eld.
The lack of considering gender issues when designing and dis-
seminating interventions to control BXW is problematic as technology
uptake aects and is aected by gender relations (Blomme et al., 2017).
For example, gender roles inuence success of management practices
such as SDSR. Blomme et al. (2017) discuss potential conicts between
male (usually managing the perennial banana) and female (usually
managing annual (inter) crops) household members during the appli-
cation of SDSR. This is the case when SDSR is practiced during the
growth period of the intercropped annual crop, which can then be
disrupted/damaged by people walking in the eld for monitoring or
cutting and falling of (especially large) diseased stems. Consequently,
annual cropping seasons should be considered when planning SDSR
activities, for example by the removal of all visibly diseased plants
before onset of the annual cropping season as to match labour demand
by men and women, and limit movement in the eld during the growth
period of annual crops.
4.4. Economic dimension
Economic characteristics relate to the devastating impacts of BXW
on household food, nutrition and income security, and the inecient
attempts to prevent and control it. From a scientic point of view,
fundamental research is expensive, time consuming and complex.
Economic impact and thus return on investment are not fully under-
stood (Biruma et al., 2007), though its impact on food security is likely
substantial. Accurate data on the short- and long-term economic impact
of BXW are limited and mostly assumption based (Vurro et al., 2010;
Nkuba et al., 2015). However, without eective control BXW certainly
causes yield losses up to 100% (Nkuba et al., 2015) especially in ABB-
dominated production systems. The initial control measure to drasti-
cally reduce eld inoculum levels (CMU) is cumbersome as it is time
and labour intensive, and therefore expensive. Also, replanting is in-
advisable before 6 months of fallowing (Blomme et al., 2014) and,
adding time until rst bunch production (approx. 18 months), pro-
duction losses entail about 24 months. All along householdsfood, in-
come and nutrition security are disrupted. Understandably, farmer
willingness to control BXW with such cost-ineective techniques is low
(Blomme et al., 2017). Additionally, lack of sucient strategies/timely
intervention approaches to prevent large-scale, and severe outbreaks
induce unnecessary high control costs both locally, nationally, and re-
gionally. Although SDSR technology is more farmer friendly, it still
requires signicant time and labour investments, especially in the in-
itial application phase with high incidence levels. Consequently,
farmers may perceive reason to opt for more economic coping strate-
gies, e.g. switching other crops. Lastly, a dichotomy exists between
farmers with and without o-farm income generating activities. The
rst has low motivation for continuous investment in banana man-
agement as it is not the main source of income. In group interviews this
was mentioned as a concern and nuisance. The latter lacks room for
nancial manoeuvre both for managing the crop and when BXW aects
M. McCampbell et al. NJAS - Wageningen Journal of Life Sciences xxx (xxxx) xxx–xxx
7
the production while bananas provide an important income source.
4.5. Institutional dimension
Institutional challenges relate to the diverse appearances and per-
formance of the institutional environment in the Great Lakes Region
that aect ability to implement BXW control and prevention strategies
at scale. Appropriate frameworks, guiding policies and byelaws (e.g.
quarantine measures) are largely absent (Tinzaara et al., 2013). The
institutional situation moreover diers per country (Vurro et al., 2010)
complicating potential for and willingness to engage in regional action.
Trans-boundary pathogen transmission is dicult to prevent since
both banana produce and planting material travel across borders
without restraint. Additionally, surveillance methods are ineective
(Tinzaara et al., 2016), due to a common lack of organization, reg-
ularity or accuracy. Although Rwanda currently conducts a country-
wide BXW mapping exercise, the absence of national and regional
strategies and collaborations for continuous surveillance and interven-
tion decreases ability to forecast disease spread. This aects potential
for timely disease diagnosis and action, thereby impacting infection
rates and crop yields. Interventions hence largely have a curative
character due to limited research and developments for BXW preven-
tion, and absence of predictive early-warning systems for BXW spread/
resurgence hotspots (Bouwmeester et al., 2016) to inform governments
about targeted investments.
Extension services, including those for control and prevention of
pests and diseases, in the Great Lakes Region are generally the re-
sponsibility of national agricultural research institutes. Research and
(extension) service providers have a role in nding solutions that can
increase development of and access to agricultural services by all
farmers (Poulton et al., 2010). Continuous interaction between farmers
and service providers to make extension services more demand-driven,
inclusive, and widely available can contribute to increasing benets
from rural development for all farmer categories. However, Govern-
ment extension systems are often incapable to provide farmers with
adequate support. Traditional extension services are usually expensive,
ineective or both, and more ecient extension models are required to
improve this situation (Kabunga et al., 2011).
Indeed, we observed that Rwandas Twigire Muhinzi extension
programme aims to follow an approach that is demand-drive and par-
ticipatory. Yet, Cioo et al. (2016) noted that local actors, like sector
and district agronomists, who assumedly are the most important pro-
viders of such demand-driven extension services often lack budgetary
and decisional autonomy, and instead rely on top-down decisions and
actions that may or may not match local realities. Although our primary
data did not capture it, the nature of Rwandas agricultural system tells
that this issue may apply here too.
An important challenge in the ght against BXW is the lack of
healthy planting material. This is both a technological, socio-cultural,
and an institutional constraint. The lack of a working formal seed-
system forms an obstacle for reestablishment of uprooted elds. In
absence of sucient high-quality planting material from micro- (tissue
culture) or macro-propagation (suckers or suckers-derived plantlets),
farmers rely on unregulated sources. The socio-cultural practice to
obtain planting material free of cost rather than purchasing it ag-
gregates the issue. Most farmers source suckers from their own elds
(60%) or neighbouring elds (30%) (Tripathi et al., 2009) thereby
risking obtainment of BXW contaminated planting material (Tinzaara
et al., 2013), a habit that was conrmed by farmers during group in-
terviews.
4.6. Political dimension
Political characteristics result from top-down structures in some of
the Great Lakes countries (e.g. Rwanda), and lack of collaboration and
coordinated eorts between key stakeholders within and across
dierent levels. Additionally, mobilization and sensitization of stake-
holders along the value chain is inadequate (Tinzaara et al., 2016). The
result is that current capacities and eorts to out-scale interventions
and technologies often have unsatisfying results.
Most extension services still have a strong top-down, linear, and
technological orientation, and focus on the development, transfer,
adoption and diusion of crop (protection) technologies to farmers
(Schut et al., 2014b). This despite the alleged shift of extension services
towards a more systemic and participatory approach. A bottleneck is
that decisions about fund allocation and priority crops are made by
political actors at national level, thereby limiting agenda-setting and
bargaining power of local actors.
The lack of participatory and demand-driven approaches (Van Asten
et al., 2004;Kubiriba et al., 2012;Nkuba et al., 2015) results in poor
understanding of local agro-ecological and socio-economic context and
related challenges, and has caused low adoption of technologies by
farmers and relatively low buy-in of governments in scaling BXW pre-
vention and control measures. The result is low stakeholder awareness
about the BXW problem and its impact, with negative impact on in-
terest for participation and investment in collective control and pre-
vention initiatives. This translates in lack of regional mechanisms for
surveillance and monitoring, and limited collaboration between stake-
holders in the dierent aected countries (Tinzaara et al., 2013). This
on the one hand complicates introduction of suitable regional institu-
tional frameworks, and on the other hand prevents scaling of eective
control strategies.
5. Analysis and discussion
5.1. The role of data, information, knowledge, and connectivity in
overcoming BXW
The previous section presented an extensive series of ndings based
on our review of the literature, and interactions with farmers and ba-
nana experts. These provide a starting point to analyse how BXW
challenges are related to data, information, knowledge, and con-
nectivity constraints, and how ICT and citizen science can play a role in
overcoming such BXW challenges (Table 2).
Relationships with knowledge and connectivity dominate, while
data and information score lower. This conrms not necessarily the
absence of data or information, but rather their relevance and relia-
bility, as well as inclusive access form an issue (Bruce, 2016;Walsham,
2017). Regardless of some successful intervention approaches (e.g.
through the use of Farmer Field Schools in Uganda (Tinzaara et al.,
2016;Kubiriba et al., 2012)), communication related problems are
present for BXW. Concerning data, we see limitations in the amount of
reliable and up-to-date data about disease diusion patterns, severity of
outbreaks, and eect of control measures, as well as socio-economic
and socio-cultural data that could feed into farmer decision-making
tools and an early warning system. Development of informed policies
and prevention strategies is also hindered by the absence of large-scale
accurate data. Another data problem is the missing link between data
collection and action-oriented research. The diversity of stakeholders
causes two problems that we link to information. Firstly, the use of one-
size-ts all approaches results in a lack of actionable information,
customized to the perceptions, practices, and resources of diverse target
groups. Secondly, available information is not up-to-date (e.g. about
current disease incidence) nor adapted to the local context (e.g. on use
of preferred cultural management practices), fails to link technological
and socio-economic data, and therefore either inaccessible or non-
useful for various target groups. Knowledge problems include gaps in
understanding of long- and short-term disease impact, and poor
awareness of both the problem and suitable solutions for BXW by
farmers and extension agents, causing negligence to take timely action.
Additionally, both horizontal (between farmers, and between extension
agents) and vertical (across value chain, and across innovation system)
M. McCampbell et al. NJAS - Wageningen Journal of Life Sciences xxx (xxxx) xxx–xxx
8
exchange of information that is translatable into actionable knowledge
is limited. Absence of connections and collaborations between stake-
holders at all levels is a cross-cutting problem that prevents eective
exchange of data, information, and knowledge.
5.2. The potential of citizen science and ICT-based tools for overcoming
data-, information, knowledge- and connectivity-related BXW challenges
Based on our ndings we have developed four dierent intervention
pathways: (1) data for prevention of new outbreaks, (2) information for
BXW control, (3) knowledge for enhanced capacity to act timely and
inuence decision making and, (4) connectivity for connective action.
These pathways build on the impression that citizen science and ICT
enabled collection of data, exchange of information and knowledge,
and stakeholder connectivity could positively contribute to addressing
BXW. In summary, large scale data from citizen science would support
timely diagnosis of new and recurrent/re-emerging (i.e. resurgence)
disease outbreaks. Information exchanged through a digital platform
could help farmers and extensionists to make decisions about actionable
control strategies. Knowledge developed by engaged stakeholders can
enhance capacity to act timely and increase dialogue. Lastly, con-
nectivity between stakeholders would allow building of self-organized
networks.
5.2.1. Data-related interventions: citizen science and ICT for prevention of
new BXW outbreaks
Current eorts to manage BXW are mostly targeting control of the
disease after it has been diagnosed in a farm or area. Adoption of
preventive measures such as male bud removal, and tool sterilisation
has been limited. More successful results have been obtained by task-
forces that surveyed an area for disease outbreaks and enforced rig-
orous action when disease was diagnosed. However, such measures
meet farmer reluctance for impracticability (Blomme et al., 2014) and
are reported as too costly to be sustainable for smallholders
(Tushemereiwe et al., 2006). Yet, the need for monitoring does not end
with the control of BXW in a region given the high risk of resurgence
and continuation of surveillance activities is critical. Thus, there is need
for cost-ecient and eective interventions that enhance the ability to
identify disease outbreaks early on thereby reducing necessity to con-
trol severe outbreaks in a late(r) stage. A system in which citizen sci-
ence and ICT tools are used to crowd-source environmental data (e.g.
about disease spread, incidence and severity), and that links existing
(scientic) data with eld level observations from farmers and exten-
sion service providers could be helpful here, possibly combined with
historical and real-time data from satellite images or collected by
drones. In such a system, farmers would play a leading role, sharing
data (e.g. on location, BXW incidence and severity) that can support
real-time monitoring and prediction of disease spread and incidence
that would then provide decision support to farmers about accurate
management strategies, to extensionists about hotspots for monitoring
and training, and governments about where to focus investments.
5.2.2. Information-related interventions: reliable and real-time data to
improve BXW control
Citizen science and ICT tools can support better access to informa-
tion and in a far timelier manner, as well as increase meaningfulness
and interpretability of information. This can positively aect farmer
decision-making, and in turn be a rst step towards improved tech-
nology adoption rates, more sustainable disease control, and increased
prevention. Farmers base decisions on local conditions, and this needs
to be considered when providing farmers with decision support (Wood
et al., 2014). For example, enforcing the practice of CMU to control
BXW spread in a region where bananas are mostly grown as a sub-
sistence crop resulted in farmers rejecting/poorly adopting the practice
due to its expensive and cumbersome nature (Blomme et al., 2014;
Tushemereiwe et al., 2006). Albeit from a scientic perspective CMU
may be the preferred technology for most eective disease eradication
(or reduction in overall eld inoculum level), technologies like SDSR
could be more appropriate in a specic farming context and therefore
better meet farmer needs and demands resulting in better uptake and
Table 2
Linkages between challenges in each dimension and data, information, knowledge, and connectivity.
Problem dimension Type of problem where ICT and citizen science can support
Specic BXW related challenges Data related
problems
Information related
problems
Knowledge related
problems
Connectivity related
problems
Biophysical Long distance transmission through variety of
vectors
√√ √ √
Resurgence after period of control √√ √ √
Technological Absence of resistant (transgenic) cultivars √√
Insucient epidemiologic understanding √√
Low availability of clean plant material √√
SDSR technology leaves some inoculum
Socio-cultural Farmers not involved in nding solutions √√
Campaigns and trainings not inclusive √√
Low adoption of control technologies √√
Low farmer awareness of the disease √√
No attention for gender √√
Economic No accurate predictive system √√ √ √
Lack of reliable data on economic losses √√ √ √
Cumbersome and expensive nature of traditional
management techniques
Institutional Absence of appropriate institutional frameworks √√ √
Ineective surveillance methods √√ √ √
Dierent institutional environments
No formal seed system
Lack of disease knowhow at institutional level √√
Stakeholder incentives and interests unknown √√ √
Political Inadequate mobilization of key actors at all levels
National level policy actors determine allocation
of funds and activities
M. McCampbell et al. NJAS - Wageningen Journal of Life Sciences xxx (xxxx) xxx–xxx
9
impact. Digital innovations may support gathering and assessing ap-
propriate information and control strategies for a specic farmer in a
specic locality. For example, app or SMS based services could be
combined with more conventional forms of communication used in the
banana system to gather, process, and exchange information relevant to
individual farmers or farmer communities. Experiments with the use of
mobile phones for multiway interaction between science and practice
for the control of BXW in Uganda showed opportunities for more cost-
eective disease control and surveillance in the region (Nakato et al.,
2016). This is promising given the lack of strong national and regional
surveillance and monitoring mechanisms necessary for management of
BXW (Tinzaara et al., 2014). Other examples of existing initiatives that
provide farmers and extensionists with a tool for rapid diagnostics and
control advice on crop pests and disease diagnosis are PEATs Plantix
and Penn State Universitys PlantVillage. Examples of crop specic tools
are Africa Rices Rice Advice, and ICAR-National Rice Research In-
stitutesRiceXpert. Thus, we observe opportunities to for example
provide decision-support on suitable BXW control strategies to dierent
groups of farmers, including those who normally have diculties to
access information, such as women. This could include sensitizing
farmers about risks of locally sourced plant material or, providing in-
formation about locally available clean seed resources. Bringing to-
gether all information needed for informed decision-making enhances
the reliability and consistency of that information for farmers or other
end-users.
5.2.3. Knowledge-related interventions: enhanced knowledge, knowhow
and capacity to act and inuence
Knowledge is critical for addressing complex problems as they are
intertwined with peoplesactions and processes of change (Leeuwis and
van den Ban, 2004). Not knowledge about BXW as such is key, but
rather knowledge that can enhance the capacity of stakeholders in
terms of understanding, dening and strategizing the broad range of
existing and new challenges for addressing BXW. This also builds on
stakeholder perceptions and beliefs about eective BXW management
(Blomme et al., 2017;Blomme et al., 2014).
However, for knowledge to become actionable it needs to be in-
terpretable, something dicult to achieve with one-size-ts-all
knowledge. ICT and citizen science could support here, integrating local
and scientic knowledge and experiences. A suitable intervention
would be the introduction of a digital platform (based on existing di-
gital technologies and platforms such as WhatsApp, SMS, and
Unstructured Simplied Service Data (USSD)) to exchange data, in-
formation, knowledge and expertise. Integration with a wide variety of
digital technologies and platforms makes the platform inclusive for a
larger variety of stakeholders. This way ICT and citizen science can
enhance availability, accessibility, accuracy, and actionability of the
knowledge and knowhow needed to make informed decisions at in-
dividual, household and institutional levels by assembling existing
knowledge and translating it into new knowledge that is adjusted to the
needs and context of its user. Additionally, it allows for collection of
scientic and practical evidence of BXWsspread and impact (e.g. data
on crop and economic losses) that can convince policy makers to en-
gage in national and regional action.
5.2.4. Connectivity-related interventions: connective action among
stakeholders
Although newer management practices such as SDSR make in-
dividual level control of BXW very eective under certain conditions
(e.g. at highland sites with AAA-EA type bananas), stakeholder colla-
boration and connectivity remain an important bottleneck when aiming
for BXW prevention rather than control. General absence of well-
functioning networks providing assistance in monitoring, surveying and
controlling crop diseases in developing countries results in incomplete
data and provides a hurdle to eective disease control and prevention
(Vurro et al., 2010). Hence, there is a need for scientists and farmers to
collaborate and turn available information into relevant, actionable
farming knowledge (Bruce, 2016). This especially for knowledge-in-
tensive agricultural problems, like BXW, that require intensive training
and extension eorts and close collaboration between trainers and
learners (Kabunga et al., 2011).
Experimentation with new forms of social mechanisms and ex-
change of contextualized information through ICT and citizen science
provides an entry-point for engaging farmers in research and develop-
ment activities, creating opportunities for targeted, multi-way, multi-
level interaction. Citizen science and ICT can enhance such multi-way
information exchange by collecting the feedback from farmers to the
research community that can shape new research questions and im-
prove service delivery to farmers (Kindred, 2015;Phillipson et al.,
2012). Additionally, ICT provides opportunities for more inclusive
services that benet a larger number and broader variety of stake-
holders (Bruce, 2016), and can support improved understanding and
communication about best-bet practices according to science, and best-
t practices following farmerscontext. Already some banana technol-
ogies stem from such a participatory, collective approach (e.g. SDSR
and cost-eective macro-propagation). Although face-to-face interac-
tions with experts will still be needed, citizen science and ICT can en-
able, complement, or accelerate these approaches.
6. Conclusions
This paper contributes to a deeper understanding about BXW in the
Great Lakes Region by unravelling this complex agricultural problem.
We found that the BXW epidemic/constraint is a resultant of numerous
challenges across various system dimensions and is not only caused by
biophysical and technological challenges. Identied challenges se-
quentially link with data, information, knowledge, and stakeholder
connectivity challenges. This nding has largely been neglected in
studies and interventions this far, potentially contributing to meagre
results of eorts to control existing and prevent new or recurrent dis-
ease outbreaks. Literature on ICT and citizen science innovations sug-
gests that these could potentially be put to eective deployment for
addressing such information and communication related challenges.
Related to this we identied four action pathways: (1) Data-related
interventions: Citizen science for BXW prevention (e.g. involving
farmers to collect large scale data on disease transmission patterns); (2)
Information-related interventions: Reliable and real-time data to im-
prove disease control (e.g. sharing personal(ized) and contextualized
information to facilitate translation into applicable knowledge); (3)
Knowledge-related interventions: Enhanced knowledge, knowhow and
capacity to act and inuence (e.g. establishing a digital platform for
sharing of expertise on knowledge-based interventions) and (4)
Connectivity-related interventions: Collective action among stake-
holders (e.g. creation of a virtual platform for connective action).
Citizen science and ICT innovations based on these pathways are
likely more cost-ecient and have an ability to reach larger groups of
farmers than current extension services and interventions for disease
management. However, ICTs nor citizen science alone will oer the
panacea to a longstanding agricultural problem like BXW.
Alternatively, they should be considered useful new modalities that
support tackling such problems. We recommend that research and de-
velopment eorts to address BXW in the Great Lakes Region should not
primarily focus on the development of new tools and applications.
Instead the focus should be on the identication of best-t options for
combining face-to-face interactions with ICT and citizen science-based
innovations for problem solving.
Acknowledgements
This research was undertaken as part of the CGIAR Research
Program on Roots, Tubers and Bananas (CRP RTB) and supported by
the CGIAR Fund Donors (http://www.cgiar.org/about-us/our-funders/
M. McCampbell et al. NJAS - Wageningen Journal of Life Sciences xxx (xxxx) xxx–xxx
10
). Funding was provided by the Deutsche Gesellschaft fur Internationale
Zusammenarbeit (GIZ) on behalf of the German Federal Ministry for
Economic Cooperation and development (BMZ). The research was im-
plemented in collaboration with the Consortium for Improving
Agricultural Livelihoods in Central Africa (CIALCA) which is funded by
the Belgian Directorate General for Development Cooperation and
Humanitarian Aid (DGD).
References
Acko, R.L., 1999. From data to wisdom. Ackos Best His Class. Writings Manag. John
Wiley & Sons, New York, pp. 170172 (Accessed 31 August 2017).
Alavi, M., Leidner, D.E., 2001. Review: knowledge management and knowledge man-
agement systems: conceptual foundations and research issues. MIS Q. 25, 107. http://
dx.doi.org/10.2307/3250961.
Bennett, W.L., Segerberg, A., 2012. The logic of connective action. Inf. Commun. Soc. 15,
739768. http://dx.doi.org/10.1080/1369118X.2012.670661.
Biruma, M., Pillay, M., Tripathi, L., Blomme, G., Abele, S., Mwangi, M., Bandyopadhyay,
R., Muchunguzi, P., Kassim, S., Nyine, M., Turyagyenda, L., Eden-Green, S., 2007.
Banana Xanthomonas wilt: a review of the disease, management strategies and future
research directions. Afr. J. Biotechnol. 6, 953962. http://www.academicjournals.
org/AJB.
Blomme, G., Jacobsen, K., Ocimati, W., Beed, F., Ntamwira, J., Sivirihauma, C.,
Ssekiwoko, F., Nakato, V., Kubiriba, J., Tripathi, L., Tinzaara, W., Mbolela, F., Lutete,
L., Karamura, E., 2014. Fine-tuning banana Xanthomonas wilt control options over
the past decade in East and Central Africa. Eur. J. Plant Pathol. 139, 265281. http://
dx.doi.org/10.1007/s10658-014-0402-0.
Blomme, G., Ocimati, W., Sivirihauma, C., Vutseme, L., Mariamu, B., Kamira, M., van
Schagen, B., Ekboir, J., Ntamwira, J., 2017. A control package revolving around the
removal of single diseased banana stems is eective for the restoration of
Xanthomonas wilt infected elds. Eur. J. Plant Pathol. 149, 385400. http://dx.doi.
org/10.1007/s10658-017-1189-6.
Bouwmeester, H., Heuvelink, G.B.M., Stoorvogel, J.J., 2016. Mapping crop diseases using
survey data: the case of bacterial wilt in bananas in the East African highlands. Eur. J.
Agron. 74, 173184. http://dx.doi.org/10.1016/j.eja.2015.12.013.
Bruce, T.J.A., 2016. The CROPROTECT project and wider opportunities to improve farm
productivity through web-based knowledge exchange. Food Energy Secur. 5, 8996.
http://dx.doi.org/10.1002/fes3.80.
Buytaert, W., Baez, S., Bustamante, M., Dewulf, A., 2012. Web-based environmental si-
mulation: bridging the gap between scientic modeling and decision-making.
Environ. Sci. Technol. 46, 19711976. http://dx.doi.org/10.1021/es2031278.
Buytaert, W., Zulkai, Z., Grainger, S., Acosta, L., Alemie, T.C., Bastiaensen, J., De
Bièvre, B., Bhusal, J., Clark, J., Dewulf, A., Foggin, M., Hannah, D.M., Hergarten, C.,
Isaeva, A., Karpouzoglou, T., Pandeya, B., Paudel, D., Sharma, K., Steenhuis, T.,
Tilahun, S., Van Hecken, G., Zhumanova, M., 2014. Citizen science in hydrology and
water resources: opportunities for knowledge generation, ecosystem service man-
agement, and sustainable development. Front. Earth Sci. 2, 121. http://dx.doi.org/
10.3389/feart.2014.00026.
Castellani, E., 1939. Su un marciume dellensete. Lagricoltura Colon 33, 297300.
Cieslik, K., Leeuwis, C., Dewulf, A., Feindt, P., Lie, R., Werners, S., Van Wessel, M., Struik,
P., 2018. Addressing socio-ecological development challenges in the digital age:
environmental virtual observatories for connective action. NJASWageningen J. Life
Sci. 120.
Cioo, G.D., Ansoms, A., Murison, J., 2016. Modernising agriculture through a new Green
Revolution: the limits of the Crop Intensication Programme in Rwanda. Rev. Afr.
Polit. Econ. 43, 277293. http://dx.doi.org/10.1080/03056244.2016.1181053.
Deichmann, U., Goyal, A., Mishra, D., 2016. Will digital technologies transform agri-
culture in developing countries? Agric. Econ. 47, 2133. http://dx.doi.org/10.1111/
agec.12300.
FAO, FAOSTAT, 2014. http://www.fao.org/faostat/en/#home. (Accessed 15 January
2018).
FAO, 2017. The Future of Food and Agriculture: Trends and Challenges. FAO, Rome.
http://www.fao.org/publications/card/en/c/d24d2507-41d9-4ec2-a3f8-
88a489bfe1ad/.
Fradera, R., Slawson, D., Gosling, L., Lakeman-Fraser, K., Makuch, P., Makuch, Z.,
Madani, K., Martin, K., Slade, R., Geoghegan, H., Moat, A., Haklay, M., 2015.
Explorinig the Nexus Through Citizen Science. https://www.researchgate.net/
publication/291356316_Exploring_the_Nexus_through_citizen_science.
Frison, E., Sharrock, S., 1998. The economic, social and nutritional importance of banana
in the world. In: Banan. Food Secur. Proc. an Int. Symp. Douala, Cameroon. p. 2135.
Gent, D.H., Mahaee, W.F., McRoberts, N., Pfender, W.F., 2013. The use and role of
predictive systems in disease management. VanAlfen, N.K. (Ed.), Annu. Rev.
Phytopathol., vol. 51, 267289. http://dx.doi.org/10.1146/annurev-phyto-082712-
102356.
Giller, K.E., Tittonell, P., Runo, M.C., Van Wijk, M.T., Zingore, S., Mapfumo, P., Adjei-
Nsiah, S., Herrero, M., Chikowo, R., Corbeels, M., 2011. Communicating complexity:
integrated assessment of trade-os concerning soil fertility management within
African farming systems to support innovation and development. Agric. Syst. 104,
191203. http://www.sciencedirect.com/science/article/pii/S0308521X10000934.
(Accessed 14 January 2018).
Heeks, R., 2018. Information and Communication Technology for Development (ICT4D),
1st ed. Routledge, Abingdon, New York. https://www.routledge.com/Information-
and-Communication-Technology-for-Development-ICT4D/Heeks/p/book/
9781138101814. (Accessed 13 January 2018).
Irwin, A., 1995. Citizen Science: A Study of People, Expertise and Sustainable
Development. http://dx.doi.org/10.1177/017084069701800109.
Jalbert, K., Kinchy, A.J., 2016. Sense and inuence environmental monitoring tools and
the power of citizen science. J. Environ. Policy Plan. 18, 379397. http://dx.doi.org/
10.1080/1523908X.2015.1100985.
Jogo, W., Karamura, E., Tinzaara, W., Kubiriba, J., Rietveld, A., 2013. Determinants of
farm-level adoption of cultural practices for banana Xanthomonas Wilt control in
Uganda. J. Agric. Sci. 5. http://dx.doi.org/10.5539/jas.v5n7p70.
Kabunga, N.S., Dubois, T., Qaim, M., 2011. Information Asymmetries and Technology
Adoption The Case of Tissue Culture Bananas in Kenya, Courant Res. Cent. Poverty,
Equity GrowthDiscuss. Pap. https://ideas.repec.org/p/got/gotcrc/074.html.
(Accessed 5 June 2017).
Karamura, E., Osiru, M., Blomme, G., Lusty, C., Picq, C., 2005. Developing a regional
strategy to address the outbreak of banana Xanthomonas wilt in East and Central
Africa. In: Proc. Banan. Xanthomonas Wilt Reg. Prep. Strateg. Dev. Work. INIBAP,
Montpellier, Kampala (Uganda). pp. 3639.
Niko, N., Ndayihanzamaso, P., Lepoint, P., 2011. First report of Banana Xanthomonas
Wilt (Xanthomonas campestris pv. musacearum) in Burundi. Institut des Sciences
Agronomiques du Burundi, BP 795, Bujumbura. Burundi.
Kindred, D., 2015. Eective exchange between practice and research-using farmer net-
works to enable researchers to learn. Assoc. Appl. Biol. Energy Secur. Conf. Knowl.
Exch. from Res. to Food Supply Chain. University of Lancaster, Lancaster, U.K.
Klapwijk, C.J., Bucagu, C., Van Wijk, M.T., Udo, H.M.J., Vanlauwe, B., Munyanziza, E.,
Giller, K.E., 2014. The One cow per poor family programme: current and potential
fodder availability within smallholder farming systems in southwest Rwanda. Agric.
Syst. 131, 1122. http://dx.doi.org/10.1016/j.agsy.2014.07.005.
Kubiriba, J., Karamura, E.B., Jogo, W., Tushemereirwe, W.K., Tinzaara, W., 2012.
Community mobilization: a key to eective control of banana xanthomonas wilt. J.
Dev. Agric. Econ. 4, 125131. http://dx.doi.org/10.5897/JDAE11.098.
Leeuwis, C., van den Ban, A.W., 2004. Knowledge and perception. In: van den Ban, A.W.
(Ed.), Commun. Rural Innov. Rethink. Agric. Ext., 3rd ed. Blackwell Science, Oxford,
pp. 94116.
Markham, R., 2009. Managing diseases and pests of banana: the way ahead? Acta Hortic.
828, 417427.
Ministry of Agriculture and Animal Resources, 2016. National ICT4RAg Strategy
(20162020), Kigali. http://www.minagri.gov.rw/leadmin/user_upload/
documents/policies_and_strateg/ICT4RAg_STRATEGIC_PLAN_2016-2020_nal__
nal__3_.pdf. (Accessed 9 June 2017).
Mwangi, M., Nakato, V., 2009. Key factors responsible for the xanthomonas wilt epidemic
on banana in East and Central Africa. Acta Hortic. 828, 395404. http://dx.doi.org/
10.17660/ActaHortic.2009.828.41.
Nakato, G.V., Beed, F., Bouwmeester, H., Ramathani, I., Mpiira, S., Kubiriba, J., Nanavati,
S., 2016. Building agricultural networks of farmers and scientists via mobile phones:
case study of banana disease surveillance in Uganda. Can. J. Plant Pathol. 38,
307316. http://dx.doi.org/10.1080/07060661.2016.1230149.
Ndayihanzamaso, P., Niko, N., Niyongere, C., Bizimana, S., Nibasumba, A., Lepoint, P.,
Tinzaara, W., Kaboneka, S., Sakayoya, E., Jogo, W., Mugiraneza, T., Karamura, E.,
2016. Distribution, incidence and farmers knowledge of banana Xanthomonas wilt in
Burundi. Afr. J. Agric. Res. 11, 36153621. http://dx.doi.org/10.5897/AJAR2016.
11210.
Nelson, C., 2010. Dont mourn, organize. J. Int. Dev. 22, 674692. http://dx.doi.org/10.
1002/jid.1719.
Nkuba, J., Tinzaara, W., Night, G., Niko, N., Jogo, W., Ndyetabula, I., Mukandala, L.,
Ndayihazamaso, P., Niyongere, C., Gaidashova, S., Rwomushana, I., Opio, F.,
Karamura, E., 2015. Adverse impact of banana Xanthomonas Wilt on farmerslive-
lihoods in Eastern and Central Africa. Afr. J. Plant Sci. 9, 279286. http://dx.doi.org/
10.5897/AJPS2015.1292.
Ocimati, W., Ssekiwoko, F., Karamura, E., Tinzaara, W., Eden-Green, S., Blomme, G.,
2013. Systemicity of Xanthomonas campestris pv. musacearum and time to disease
expression after inorescence infection in East African highland and Pisang Awak
bananas in Uganda. Plant Pathol. 62, 777785. http://dx.doi.org/10.1111/j.1365-
3059.2012.02697.x.
Ocimati, W., Nakato, G.V., Fiaboe, K.M., Beed, F., Blomme, G., 2015. Incomplete systemic
movement of Xanthomonas campestris pv. musacearum and the occurrence of latent
infections in xanthomonas wilt-infected banana mats. Plant Pathol. 64, 8190.
http://dx.doi.org/10.1111/ppa.12233.
Okech, S.H.O., Gaidashova, S.V., Gold, C.S., Nyagahungu, I., Musumbu, J.T., 2005. The
inuence of socio-economic and marketing factors on banana production in Rwanda:
results from a participatory rural appraisal. Int. J. Sustain. Dev. World Ecol. 12,
149160. http://dx.doi.org/10.1080/13504500509469626.
Okello, J.J., Kirui, O., Njiraini, G.W., Gitonga, Z.M., 2012. Drivers of use of information
and communication technologies by farm households: the case of smallholder farmers
in Kenya. J. Agric. Sci. 4, 111124. http://search.ebscohost.com/login.aspx?direct=
true&db=lah&AN=20123048386&site=ehost-live.
Olson, M., 1965. Logic of Collective Action: Public Goods and the Theory of Groups
(Harvard Economic Studies v. 124). Harvard University Press.
Phillipson, J., Lowe, P., Proctor, A., Ruto, E., 2012. Stakeholder engagement and
knowledge exchange in environmental research. J. Environ. Manage. 95, 5665.
http://dx.doi.org/10.1016/j.jenvman.2011.10.005.
Poteete, A.R., Janssen, M., Ostrom, E., 2010. Working Together: Collective Action, the
Commons, and Multiple Methods in Practice. Princeton University Press.
Poulton, C., Dorward, A., Kydd, J., 2010. The future of small farms: new directions for
services, institutions, and intermediation. World Dev. 38, 14131428. http://dx.doi.
org/10.1016/j.worlddev.2009.06.009.
Reeder, R.H., Muhinyuza, J.B., Opolot, O., Aritua, V., Crozier, J., Smith, J., 2007.
M. McCampbell et al. NJAS - Wageningen Journal of Life Sciences xxx (xxxx) xxx–xxx
11
Presence of banana bacterial wilt (Xanthomonas campestris pv. musacearum) in
Rwanda. Plant Pathol. 56, 1038. http://dx.doi.org/10.1111/j.1365-3059.2007.
01640.x.
Schut, M., Klerkx, L., Rodenburg, J., Kayeke, J., Hinnou, L.C., Raboanarielina, C.M.,
Adegbola, P.Y., van Ast, A., Bastiaans, L., 2014a. RAAIS: rapid appraisal of agri-
cultural innovation systems (Part I). A diagnostic tool for integrated analysis of
complex problems and innovation capacity. Agric. Syst. 132, 111. http://dx.doi.org/
10.1016/j.agsy.2014.08.009.
Schut, M., Rodenburg, J., Klerkx, L., van Ast, A., Bastiaans, L., 2014b. Systems approaches
to innovation in crop protection. A systematic literature review. Crop Prot. 56,
98108. http://dx.doi.org/10.1016/j.cropro.2013.11.017.
Schut, M., Rodenburg, J., Klerkx, L., van Ast, A., Bastiaans, L., 2014c. Systems approaches
to innovation in crop protection. A systematic literature review. Crop Prot. 56,
98108. http://dx.doi.org/10.1016/j.cropro.2013.11.017.
Schut, M., van Paassen, A., Leeuwis, C., Klerkx, L., 2014d. Towards dynamic research
congurations: a framework for reection on the contribution of research to policy
and innovation processes. Sci. Public Policy 41, 207218. http://dx.doi.org/10.
1093/scipol/sct048.
Shimwela, M.M., Ploetz, R.C., Beed, F.D., Jones, J.B., Blackburn, J.K., Mkulila, S.I., van
Bruggen, A.H.C., 2016. Banana xanthomonas wilt continues to spread in Tanzania
despite an intensive symptomatic plant removal campaign: an impending socio-
economic and ecological disaster. Food Secur. 8, 939951. http://dx.doi.org/10.
1007/s12571-016-0609-3.
Tinzaara, W., Karamura, E.B., Blomme, G., Jogo, W., Ocimati, W., Rietveld, A., 2013.
Why sustainable management of Xanthomonas Wilt of Banana in East and Central
Africa has been elusive. Acta Hortic. 986, 157164. http://apps.webofknowledge.
com/full_record.do?product=WOS&search_mode=GeneralSearch&qid=1&SID=
Q2P32sLOEzbx67QXjO7&page=1&doc=5.
Tinzaara, W., Karamura, E., Kubiriba, J., et al., 2014. The banana Xanthomonas wilt
epidemic in east and central Africa: current research and development eorts. 1114
Int. Hortic. Congr. Hortic. Sustain. Lives, Livelihoods Landscapes 267274. https://
www.actahort.org/books/1114/1114_36.htm. (Accessed 14 January 2018).
Tinzaara, W., Karamura, E.B., Kubiriba, J., Ochola, D., Ocimati, W., Blomme, G.,
Ssekiwoko, F., 2016. The banana Xanthomonas wilt epidemic in east and central
Africa: current research and development eorts. Acta Hortic. 1114, 267274. http://
dx.doi.org/10.17660/ActaHortic.2016.1114.36.
Tripathi, L., Mwangi, M., Aritua, V., Tushemereirwe, W.K., Abele, S., Bandyopadhyay, R.,
2009. Xanthomonas wilt: a threat to banana production in East and Central Africa.
Plant Dis. 93. http://dx.doi.org/10.1094/PDIS-93-5-0440.
Tushemereirwe, R., Kangire, W., Smith, A., Ssekiwoko, J., Nakyanzi, F., Kataama, M.,
Musiitwa, D., Karyaija, C., 2003. An outbreak of bacterial wilt on banana in Uganda.
InfoMusa 12, 68. http://c3project.iita.org/Doc/BXWuganda.pdf. (Accessed 31
August 2017).
Tushemereiwe, W.K., Okaasai, O.O., Kubiriba, J., Nankinga, C., Muhangi, J., Odoi, N.,
Opio, F., 2006. Status of banana bacterial wilt in Uganda. Afr. Crop Sci. J. 14, 7782.
http://dx.doi.org/10.4314/acsj.v14i2.27913.
Van Asten, P.J., Gold, C., Okech, S.H., Gaidashova, S., Tushemereirwe, W., De Waele, D.,
2004. Soil quality problems in East African banana systems and their relation with
other yield loss factors. InfoMusa 13, 2025. https://lirias.kuleuven.be/handle/
123456789/175191.(Accessed 12 January 2018).
van Damme, J., Ansoms, A., Baret, P.V., 2013. Agricultural innovation from above and
from below: confrontation and integration on Rwandas hills. Afr. A. (Lond.)
108127. http://dx.doi.org/10.1093/afraf/adt067.
Van Damme, J., Ansoms, A., Baret, P.V., 2014. Agricultural innovation from above and
from below: confrontation and integration on Rwandas Hills. Afr. A. (Lond.) 113,
108127. http://dx.doi.org/10.1093/afraf/adt067.
van Schagen, B., Blomme, G., Ocimati, W., Bagula, J.N., 2016. Simple, Safe, Sure A New
Approach for Manging Banana Wilt in Highland Zones of South Kivu, DR Congo.
http://www.cialca.org/leadmin/Cialca-uploads/documents/publications/
technical-publications/SDSR_brief_South_Kivu_English_-_Final.pdf. (Accessed 15
January 2018).
Vurro, M., Bonciani, B., Vannacci, G., 2010. Emerging infectious diseases of crop plants in
developing countries: impact on agriculture and socio-economic consequences. Food
Secur. 2, 113132. http://dx.doi.org/10.1007/s12571-010-0062-7.
Walsham, G., 2017. ICT4D research: reections on history and future agenda. Inf.
Technol. Dev. 1102, 124. http://dx.doi.org/10.1080/02681102.2016.1246406.
Weber, E.P., Khademian, A.M., 2014. Wicked problems, knowledge capacity builders in
network challenges, settings and collaborative. Public Adm. Rev. 68, 334349.
http://dx.doi.org/10.1111/j.1540-6210.2007.00866.x.
Wood, B.A., Blair, H.T., Gray, D.I., Kemp, P.D., Kenyon, P.R., Morris, S.T., Sewell, A.M.,
2014. Agricultural science in the wild: a social network analysis of farmer knowledge
exchange. PLoS One 9, e105203. http://dx.doi.org/10.1371/journal.pone.0105203.
Yirgou, D., Bradbury, J.F., 1968. Bacterial wilt of enset (Enset ventricosum) incited by
Xanthomonas musacearum sp. n. Phytopathology 58, 111112.
Yirgou, D., Bradbury, J.F., 1974. A note on wilt of banana caused by the enset wilt or-
ganism Xanthomonas musacearum. East Afr. Agric. For. J. 40 (1), 111114. http://
www.tandfonline.com/doi/abs/10.1080/00128325.1974.11662720?journalCode=
teaf20. (Accessed 31 August 2017).
M. McCampbell et al. NJAS - Wageningen Journal of Life Sciences xxx (xxxx) xxx–xxx
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... On the other hand, studies present challenges hindering extension systems from delivering to their full potential. For example, farmers' natural and socioeconomic settings (Bernet et al., 2001), farmers' heterogeneity (Hammond et al., 2020), the complexity of agricultural systems (McCampbell et al., 2018), institutional settings (Lamprinopoulou et al., 2014), limited resources, the capacity of extension agents, and stakeholders from different backgrounds needing to cooperate (Esparcia, 2014) are listed, among others, as bottlenecks of extension services delivery. ...
... We used the case of banana Xanthomonas wilt (BXW) to collect information about extension visits, BXW management training, and the information source. BXW is a fast-spreading banana disease that is easily transmitted, has no cure after infection, and can cause 100% farm-level yield losses (McCampbell et al., 2018). In Rwanda, the value of the losses due to BXW in 2015 was estimated at USD 2.95 million (Nkuba et al., 2015). ...
... Case selection, sampling, and data collection For this study, I used the case of advisory services provided to farmers on how to deal with BXW disease in Rwanda. This is an effective case with which to study the effectiveness of extension delivery for two reasons: (i) bananas are very important to Rwanda and (ii) BXW is an aggressive, fast-spreading disease resulting in 100% yield loss (McCampbell et al., 2018). Thus, advisory on how to deal with BXW is of utmost relevance for both farmers and the government. ...
Article
To determine whether a farmer’s accessibility predicts the delivery of extension services, this study used banana Xanthomonas wilt (BXW) disease-management advisory as a typical case with which to collect extension-delivery information from 690 farmers, distinguished by their respective accessibility. Cost–distance analysis was applied to define each farmer’s accessibility. The results revealed that a farmer’s accessibility does not predict extension delivery to that farmer in all forms of the examined extension parameters. Significant factors contributing to the delivery of extension services included BXW incidence and membership in Twigire Muhinzi groups. Given the results of this paper, I argue that the nature of the advisory and the type of farmers’ networks are more predictive factors than physical proximity. The findings of this study support the argument that the group-based extension approach is more effective; therefore, the Twigire Muhinzi initiative is recommended as a suitable model for delivering agricultural advisory services. The absence of a significant association between extension delivery and distance (accessibility) suggests that extension agents do not follow the first-reached, first-served rule but instead follow the problem-solving-based approach.
... For instance, a case study in Central Africa explores Xanthomonas Wilt of Banana (BXW) disease, one of the most devasting bacterial diseases in African cultivars which remains in the soil for months. McCampbell et al. (2018), who analysed challenges, opportunities, and pathways for working with citizens in this initiative, stated how CS supports BXW prevention (e.g., farmers collecting large scale data on disease transmission) and connectivity-related interventions such as collective actions taken by stakeholders to control the disease. CS is proposed as a cost-efficient tool that reaches larger groups of farmers than current extension services and interventions for disease management (McCampbell et al., 2018). ...
... McCampbell et al. (2018), who analysed challenges, opportunities, and pathways for working with citizens in this initiative, stated how CS supports BXW prevention (e.g., farmers collecting large scale data on disease transmission) and connectivity-related interventions such as collective actions taken by stakeholders to control the disease. CS is proposed as a cost-efficient tool that reaches larger groups of farmers than current extension services and interventions for disease management (McCampbell et al., 2018). ...
Article
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A fifty-four per cent of the global population is estimated to live disconnected from the natural environment. Furthermore, a large majority of our community unknown how significant is the soil in their life, e.g. the provider of food, energy and medicine, etc. Strengthening this connection is one relevant action toward Soil Security, referred to as "Soil Connectivity". Citizen Science (CS) improves soil connectivity by increasing citizens awareness and making them collect scientific data. Unfortunately, an indicator of soil connectivity increases is difficult to estimate. Here, we provide a review of fifty-five soil CS initiatives worldwide to collect information such as experts' motivation for starting these projects, technologies being used, and participants' profiles. Our findings show three main trends that citizen soil initiatives tend to follow: those linking soil to human health (e.g. lead, food quality, antibiotics), those focused on future-proofing and education, and those focused on soil health (degradation) and productivity (agriculture). In addition, simplifying scientific technicalities and methods, maintaining communication with participants, and acknowledging contributions are critical factors in crowdsourcing soil research.
... Smallholder farmers can benefit from ICTs, especially Internet infrastructure and mobile phones, which provide farmers with opportunities to easily access technological innovations, extension services, markets, and essential weather information (Debsu et al. 2016). From this perspective, it is argued that the use of mobile phone-based ICT platforms is also a potential way to reorganize and facilitate formal agricultural extension by delivering relevant, timely, and cost-effective information (Duncombe, 2016;McCampbell et al. 2018;Schut et al. 2016) and improve communication among farmers in the context of informal knowledge sharing networks (Vouters, 2017). ...
... Therefore, farm heterogeneity has a profound implication on farm households' efficiency and needed policy interventions. On one hand, the one-size-fits-all scaling approach, in which technologies are packed in one adoption package regardless of particular compatibility and risk aversion imposed by particular contexts of these diverse (heterogeneous) farms, is increasingly questioned (Cleary & Van Caenegem, 2017;McCampbell et al. 2018;Find Your Feet 2012). On the other hand, policies and measurements cannot be designed on an individual basis alone. ...
Article
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Information and communications technologies (ICTs) play a key role in improving agricultural production, enhancing socio-ecological resilience, and mitigating rural poverty. However, the use of ICTs for agricultural development among smallholder farmers, especially in the least developed countries, still lags behind. It is therefore critical to understand distinct attitudes among heterogeneous smallholder farmers that determine use of ICTs, such as mobile phones. Moreover, data-driven empirical studies on the use of mobile phones in smallholder settings are still scarce. We bridge this knowledge gap by evaluating the link between the use of mobile phones and various farming types of smallholder farmers in Rwanda. Using the principal component and cluster analysis, we analyzed 690 banana farming households across eight of the 10 major agro-ecological zones of Rwanda and developed a typology of banana farms. We identified three distinct farm types based on a combination of various farmer characteristics and farm operations and endowments, namely the beer banana, livestock-based, and the cooking banana farm types. These farm types clearly differ in terms of ownership and use of both basic and smart mobile devices. Farmers in the cooking banana farm type are far more likely to own and use smart mobile phones than in other types. Regression results further indicated that farm type, gender, and education have significant correlations with the perceived usefulness of mobile phones in agriculture. Major barriers to using ICT-based agricultural services were 1) low awareness of the existence of ICT services, 2) limited availability of ICT services, 3) lack of technical know-how, 4) relatively high prices of ICT devices, and 5) low levels of ICT literacy. This empirical study provides strategically important insights for the transition to digital agriculture in the context of smallholder farming systems.
... We then apply these theoretical insights to a specific case to see how these different forms of proximity influence the diffusion of knowledge, specifically knowledge about a banana disease in Rwanda. This banana disease, banana Xanthomas wilt (BXW) is a fast-spreading crop disease that threatens the livelihood of banana growers (McCampbell et al., 2018). ...
Article
CONTEXT Social networks play an important role in the diffusion of knowledge, and farmers draw on their personal networks to enhance their adaptive capacity to shocks. Different forms of proximity have been long recognized as important factors in knowledge and information exchanges. However, the specific roles and their interactions in agricultural knowledge and innovation systems (AKISs) are still far from clear. In this study, we investigate the underlying forces that drive tie formation within the knowledge-sharing networks of banana farmers in four different villages in Rwanda. OBJECTIVE Our study has three objectives: First, we discuss the importance of various types of proximities in AKIS research. Second, we empirically contribute to how different forms of proximity influence the way knowledge diffuses in formal and informal networks by studying a plant disease's management. Finally, we discuss our findings' relevance for targeted interventions to help rural communities transition to greater resilience. METHODS We review different proximity concepts and adapt them for use within an AKIS context. We then apply this framework to assess the proximity effects on the advice-seeking networks of banana farmers in four purposefully chosen villages in Rwanda. We used a structured questionnaire to collect social network information about the management of banana Xanthomonas wilt (BXW), from all banana growers (N = 491) in these four villages. We distinguished the informal advice networks among farmers from the official government extension system—the formal advice network. We employed exponential random-graph models to assess the determinants of the networks we observed, especially geographical, cognitive and social proximity indices. RESULTS AND CONCLUSIONS We found that geographical proximity significantly affects knowledge exchange within larger villages' informal advice networks; but not in smaller villages, where both cognitive and social proximities play substantial roles. We argue that farmers are socially closer in smaller communities where geographical distance does not matter, and that geographical distance only starts to matter after a certain community size threshold is reached. SIGNIFICANCE We provide solid empirical evidence to help plan targeted interventions toward greater resilience for rural communities. We argue that properly integrating informal social networks can result in more effective knowledge exchange within AKISs, enhancing their resilience.
... In most smallholder farming systems, the use of smart devices remains relatively low, but the high interest in smart digital tools constitutes a viable entry point for innovation among stakeholders, including farmers (McCampbell et al. 2018). Therefore, various smart apps are emerging for the diagnosis, surveillance, and control of pests and diseases in RT&B crops. ...
Chapter
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This chapter provides the first comprehensive review of digital tools and technologies available for the identification, monitoring, and control of pests and diseases, with an emphasis on root, tuber, and banana (RT&B) crops. These tools include systems based on identification keys, human and artificial intelligence-based identification based on smart applications, web interfaces, short messages services (SMS), or combinations thereof. We also present ideas on the use of image recognition from smartphones or unmanned aerial vehicles (UAVs) for pest and disease monitoring and data processing for modeling, predictions, and forecasting regarding climate change. These topics will be presented in the context of their current development and future potential but also the challenges, limitations, and innovative approaches taken to reach end users, particularly smallholder farmers, and achieve impacts at scale. Finally, the scope and limitation of private sector involvement demonstrates the need of publicly funded initiatives to maximize sharing of data and resources to ensure sustainability of unbiased advice to farmers through information and communication technology (ICT) systems.
... This finding explicitly supports claims made by Turner et al. (2020, p. 159) whereby the role of 'actors mobilising resources to transform power relations among platform actors' was found to be of importance in changing power dynamics. We show, in support of existing literature examining how and why 'working separately' from 'government' and 'science' may be optimal for an industry stakeholder/s given existing systemic perspectives, that it is still possible to move toward a model whereby 'working together' is prioritised (Berkes, 2009;Clapp et al., 2018;McCampbell et al., 2018). ...
Article
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We report on qualitative social research conducted with stakeholders in a local agricultural knowledge and advice network associated with a collaborative water quality monitoring project. These farmers, advisors and researchers allude to existing social dynamics, technological developments, and (more general) social evolution which is analysed against a novel analytical framework. This framework considers notions of power, social capital, and trust as related and dynamic, forming the basis of our contribution to knowledge. We then probe the data to understand perceived impacts of the collaborative project and social interaction associated with this research project, which involved cutting edge automated and frequent water quality monitoring that allowed for near real-time access to data visualisation displayed via a bespoke mobile or web 'app' (1622WQ). Our findings indicate that a multi-faceted approach to assessing and intervening based on consideration of multiple social dimensions holds promise in terms of creating conditions that allow for individual and group learning to encourage changes in thinking required to result in improved land management practice.
... Between 2002Between -2005, the disease caused a cumulative economic loss of 61.1 million dollars by the country, mainly affecting EAHB, 'Matooke' (AAA-EAHB genome) and the 'Kayinja' beer banana (ABB genome) ). According to McCampbell et al. 2018, the disease is also of prominent importance in neighboring banana producing countries, namely: Burundi, Kenya, the Democratic Republic of Congo, Rwanda, and Tanzania. ...
Article
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Several initiatives by the Government of Uganda, Research Institutes and CGIAR centers have promoted the use of tissue culture (TC) banana technology as an effective means of providing clean planting material to reduce the spread of Banana Xanthomonas wilt (BXW) but its uptake is still low. We examine factors that constrain uptake of tissue culture banana planting materials in central Uganda by considering the cultural context of banana cultivation. Data were collected using eight focus group discussions involving 64 banana farmers and 10 key informant interviews and subjected to thematic analysis. Results showed that banana cultivars in the study communities were important for food, cultural practices and medicine. Cultivars supplied through TC were based on commercial considerations focusing on market value and household income and insufficient attention was given to their cultural importance. Farmers regard banana from TC planting material to be incompatible with their tastes and preferences for traditional food and drinks, culture and medicine. Furthermore, the plantlets are perceived as complicated to use, and farmers report requiring more knowledge and information on how to plant and maintain the plantlets on-farm. In these aspects, TC planting material does not align with cultural values linked to societal welfare. Future efforts aimed at controlling pests and diseases would benefit from more location-specific and holistic approaches that integrate cultural dimensions alongside planting material hygiene, quality and vigor.
... In Rwanda, Banana is one of the important staple crops for food and nutritional security in the country, and it supports household livelihood as a source of income [35]. However, Banana production is threatened by the Banana Xanthomonas Wilt (BXW), an infectious crop disease that can cause up to 100% yield loss per infected stand [36,37], and spatially explicit data about areas of banana production are generally outdated or non-existent. The identification and delineation of cropland area is a critical first step towards targeting, controlling, and preventing crop-specific diseases, such as BXW, nationally. ...
Article
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Crop monitoring is crucial to understand crop production changes, agronomic practice decision-support, pests/diseases mitigation, and developing climate change adaptation strategies. Banana, an important staple food and cash crop in East Africa, is threatened by Banana Xanthomonas Wilt (BXW) disease. Yet, there is no up-to-date information about the spatial distribution and extent of banana lands, especially in Rwanda, where banana plays a key role in food security and livelihood. Therefore, delineation of banana-cultivated lands is important to prioritize resource allocation for optimal productivity. We mapped the spatial extent of smallholder banana farmlands by acquiring and processing high-resolution (25 cm/px) multispectral unmanned aerial vehicles (UAV) imageries, across four villages in Rwanda. Georeferenced ground-truth data on different land cover classes were combined with reflectance data and vegetation indices (NDVI, GNDVI, and EVI2) and compared using pixel-based supervised multi-classifiers (support vector models-SVM, classification and regression trees-CART, and random forest–RF), based on varying ground-truth data richness. Results show that RF consistently outperformed other classifiers regardless of data richness, with overall accuracy above 95%, producer’s/user’s accuracies above 92%, and kappa coefficient above 0.94. Estimated banana farmland areal coverage provides concrete baseline for extension-delivery efforts in terms of targeting banana farmers relative to their scale of production, and highlights opportunity to combine UAV-derived data with machine-learning methods for rapid landcover classification.
Chapter
This study examines the socio-economic effects of information and communication technologies (ICT) in Africa by region. Analysis-based data from countries in five regions of Africa show that the contribution of ICTs to socio-economic indicators varies according to the type of ICT and the region where these technologies are used. For example, Internet usage is prominent in the Middle, East, and North Africa, while telecommunication technologies are at the forefront in South, East, North, and West Africa. The study, therefore, contributes to the formation of policies according to the regional dynamics of the continent. Besides, this study argues that, contrary to the study performed by Njoh (2018) for the African continent, IC technologies can be effective on HDI with different types of ICT according to the regional dynamics of the continent. The result of this study is that using ICT alone does not adequately support development. Therefore, IC technologies should also be used in sectors such as agriculture, health, and education. Digital transformation in the agriculture sector can be a significant factor in solving the food problem facing the continent. Mobile phones and Internet use in the agricultural field can enable farmers to learn about new agricultural techniques and to use agricultural areas more efficiently. In healthcare, mobile phones and the Internet can enable these services to reach even remote regions of the continent. In education, the integration of IC technologies – especially the Internet and computers – can support human capital by ensuring that education reaches all levels of society equally and quickly. The use of IC technologies in these three sectors is the most effective way for Africa to achieve its sustainable development goals.
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Climate change, (a) biotic stresses and environmental degradation are adversely affecting the sustenance of farming communities in Africa. Addressing such challenges requires effective collective action and coordination among stakeholders, which often prove difficult to achieve. Timely and context-specific information on relevant environmental dynamics holds considerable promise to overcome these problems. This paper investigates the role of citizen science in facilitating knowledge co-creation and sharing between academia, development actors and users in developing country contexts. In our approach, we focus on information sharing platforms (known as Environmental Virtual Observatories, EVOs) and their potential to facilitate adaptive decision-making in six rural case-study areas in Africa. We complement the existing theory on EVOs with a focused exploration of the connective function of ICT-enabled multi-stakeholder exchange. We propose that increased connectivity may enable new forms of collective action (labelled ‘connective action’), relevant to addressing socio-ecological challenges. Along these lines, this paper presents the theoretical and conceptual grounding of a research program that aspires to develop Environmental Virtual Observatories for Connective Action (EVOCAs) and to explore their potential for improved crop, water, livestock and disease management in rural Africa.
Article
Xanthomonas campestris pv. musacearum, the causal agent of Xanthomonas wilt of banana (XW), does not infect or cause symptom development in all physically attached shoots in an infected mat. Incomplete/partial systemicity and latent infections often occur. The single diseased stem removal (SDSR, the removal of only symptomatic plants) technique depends on these observations. The SDSR technique, as an alternative or complementary practice to complete mat uprooting (CMU) for XW control, was evaluated at eight XW pilot sites in eastern Democratic Republic of Congo as a novel control option. This technique is low-cost, simple and easily applicable. Within one month, XW plant incidence at the experimental sites declined to below 10%, while within three and 10 months declined to below 2% and 1%, respectively. Restoration of banana plots was observed even in plots that initially had over 80% plant disease incidence. CMU removes a larger portion of the inoculum in a field but is very tedious, time consuming and costly in terms of labour and lost production, due to the premature cutting of symptomless plants that potentially could bear a bunch. CMU can potentially prevent further spread when XW appears for the first time on a farm or location. The choice of CMU relative to SDSR also depends largely on farming objectives. CMU can be carried out in intensive and market-oriented production systems, whose ultimate target is eradication, for example, in South-Western Uganda. In contrast, SDSR is more appealing to subsistence-oriented production, such as in eastern DR Congo, Burundi or central Uganda, whose target is more oriented towards management/control. SDSR can be suggested where access to clean planting material is difficult, thus could be recommended to a very large percentage of small-scale farmers in the currently affected banana-based production systems in east and central Africa.
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Research on the use of ICTs for international development, or information and communication technology for development (ICT4D) research, has a history going back some 30 years. The purpose of this paper is to take stock of the ICT4D research field at this important juncture in time, when ICTs are increasingly pervasive and when many different disciplines are involved in researching the area. The paper first provides some reflections on the history of the field broken down into three phases from the mid-1980s to the present day. This is followed by a detailed discussion of future research agenda, including topic selection, the role of theory, methodological issues and multidisciplinarity, and research impact. ICT4D research started largely in the academic field of information systems but it is concluded that the future lies in a multidisciplinary interaction between researchers, practitioners, and policy-makers.
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Research on the use of ICTs for international development, or ICT4D research, has a history going back some thirty years. The purpose of this paper is to take stock of the ICT4D research field at this important juncture in time, when ICTs are increasingly pervasive and when many different disciplines are involved in researching the area. The paper first provides some reflections on the history of the field broken down into three phases from the mid-1980s to the present day. This is followed by a detailed discussion of future research agenda including topic selection, the role of theory, methodological issues and multi-disciplinarity, and research impact. ICT4D research started largely in the academic field of information systems but it is concluded that the future lies in a multi-disciplinary interaction between researchers, practitioners and policy makers.
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Mobile phones and the internet have significantly affected practically all sectors of the economy and agriculture is no exception. Building on a recent World Bank flagship report, this article introduces a concise framework for describing the main benefits from new information and communication technologies. They promote greater inclusion in the broader economy, raise efficiency by complementing other production factors, and foster innovation by dramatically reducing transaction costs. The article reviews the recent literature on corresponding technology impacts in the rural sector in developing countries. Digital technologies overcome information problems that hinder market access for many small-scale farmers, increase knowledge through new ways of providing extension services, and they provide novel ways for improving agricultural supply chain management. While there are many promising examples of positive impacts on rural livelihoods—or “digital dividends”—these have often not scaled up to the extent expected. The main reason is that technology can always only address some, but not all of the barriers faced by farmers in poorer countries.
Article
Banana Xanthomonas wilt (BXW), caused by the recently introduced pathogen Xanthomonas campestris pv. musacearum (Xcm), is a limiting factor for banana production in Kagera, Tanzania. A region-wide eradication campaign was initiated in 2013. The objectives were to gain insight into the spatial and seasonal occurrences of BXW and into field management practices. In 2015, 135 smallholder farmers were interviewed about BXW and management practices, and their farms were assessed for incidence of the disease. BXW incidence per ward in 2014, obtained from extension offices, and space-time cluster analysis was performed with SaTScan. BXW clusters were detected during rainy but not during dry seasons. These results agreed with the information provided by farmers that the highest incidence of BXW occurred during rainy seasons. Farmers recalled that BXW incidence increased exponentially between 2011 and 2013 but decreased steeply after 2013, coincident with the start of the BXW eradication campaign. However, pathogen transmission continued due to inconsistent sterilization of field tools and exposure of Xcm to rain. Fields of poor farmers are at greatest risk because they borrow tools and are unable to impose some recommended management practices. After the appearance of BXW in individual farms, the number of banana bunches consumed per family per month decreased significantly from 13.1 to 6.4 with a corresponding increase in areas planted to cassava and maize. Based on these findings, we suggest refining the BXW management recommendations, in particular limiting the cutting of BXW-affected plants to dry periods and sterilizing farm tools in fire.