Creative Education
2013. Vol.4, No.10A, 72-81
Published Online October 2013 in SciRes (
Copyright © 2013 SciRes.
Evaluating Human Resource Capacity for Crop Breeding in
National Programs in Africa and South and Southeast Asia
Ndeye Ndack Diop, Fredrick Okono, Jean-Marcel Ribaut
CGIAR Generation Challeng e Programme, Texcoco, México
Received August 29th, 2013; r evised September 29th, 2013; accepted October 6th, 2013
Copyright © 2013 Ndeye Ndack Diop et al. This is an open access article distributed under the Creative Com-
mons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, pro-
vided the original work is pr ope rly cited.
Plant breeders must keep abreast of the rapid evolution of new technologies, and also implement informa-
tion management strategies that efficaciously handle the ever growing amount of data required for effi-
cient integrated breeding. Updated training for breeders is critical to build relevant human resource capac-
ity, particularly in developing countries whose breeding programs suffer a lack of staff with diverse ex-
pertise. The CGIAR Generation Challenge Programme is leading such a capacity-building initiative. A
survey was conducted among course nominees to establish a baseline of breeder level of education,
knowledge and skills in analyzing data and their involvement in molecular breeding programs. The
breeders were mainly from three regions: West and Central Africa, East and Southern Africa, and South
and Southeast Asia, and also included a few participants from North Africa. Many of the breeders from all
the regions held or were working towards a PhD. Gender balance was low, principally in West and Cen-
tral Africa, where less than 15% of the breeders were women. Between 57% and 73% of the breeders
surveyed in the different regions were involved in molecular breeding projects at regional or international
level. The Use of multiple software tools by individual breeders for data analysis was low for breeders
from all the regions, with most using 1 - 3 packages. A lack of high data-analysis capacity will be a prob-
lem in an era where integration of genomics and phenotypic data in breeding programs is essential to effi-
ciently deliver improved cultivars.
Keywords: Training; Breeders; Developing Countries; Molecular Breeding
Integrated breeding approaches take advantage of all possible
tools and methodologies (from simple phenotyping to complex
genomic selection) to most efficiently achieved crop selection.
An overall decrease in the number of plant breeders and a lack
of the new skills required to conduct modern integrated breed-
ing are real challenges for crop improvement and food security
worldwide, but particularly in developing countries. In these
countries the challenge is even greater because staff reductions
require a breeder to compensate by mastering a diverse range of
skills and competencies. This shortage of staff is the result of a
freeze in recruitment in most breeding institutions in Sub-Sa-
hara Africa since the 1980s, after the implementation of the
structural adjustment policies of the International Monetary
Fund (IMF) and the World Bank (WB) that reduced public
investment in agricultural research. This further diminished the
human resource capacity of breeding programs that already had
too few trained breeders (Guimaraes et al., 2006), exacerbated
by limited funding to access modern tools and a general lack of
support from governments. This situation makes most breeding
programs in developing countries dependent on donors with
their particular research objectives, creating an increased de-
mand for short-term impact which is quite a challenge in plant
breeding (Ribaut et al., 2008). In developed countries on the
other hand, the overall number of plant breeders in the private
and public sectors has decreased concomitantly with decreased
numbers of students trained because breeding has been in in-
creasing competition with other disciplines such as genomics
and bioinformatics. In the public sector, this has resulted in the
replacement of retiring breeders by scientists involved in more
basic genetic studies (Gepts & Hancock, 2006). As a result, the
seed industry has become the main employer of plant breeders
to meet the needs of cultivar development. In the USA, these
breeders represent about 70% of all plant breeders because by
nature the seed business greatly depends on producing competi-
tive new cultivars (Bliss, 2007). However, this notion of de-
creasing numbers of breeders needs to be considered in the
context that a modern breeding team is composed of people
with different expertise. Huge progress has been made in field
management and analytical tools, so selection power in terms of
genetic gained efficiency and the number of plots per crop cy-
cle has increased significantly over the last decade. Such an
optimal breeding team is likely to be found in the private sector
and centers of the CGIAR (formally the Consultative Group on
International Agricultural Research) and in Advanced Research
Institutions (ARIs).
In developing countries, breeding teams will most likely be
composed of the main breeder and several technicians for
whom the numbers will vary depending on availability of re-
sources. However, the breeders still have to perform efficient
conventional selection which is the basis of any breeding activ-
ity—that includes a good understanding of field experimental
designs, phenotyping screening methodologies and statistics—
but also have some understanding of how to integrate new ge-
nomics approaches in their breeding program to deliver culti-
vars most efficiently. The breeding and biotechnology capacity
in developing countries was assessed through a survey (Gui-
maraes et al., 2006; Guimarães et al., 2007) and updated infor-
mation is available in the online database of the Global Part-
nership Initiative for Plant Breeding Capacity Building (GIPB)
“Plant Breeding and Related Biotechnology Capacity Assess-
ments” at (ve-
rified 27 Aug. 2013). In this reported survey the use of bio-
technologies in breeding was only just the beginning, with dif-
ferent levels of capacity among the 12 countries surveyed, of
which three in fact had no biotechnologists in 2001. Updated
data from the GIPB database showed that the number of bio-
technologists had increased in most countries with only a lim-
ited number of countries that did not report any biotechnolo-
The limited skills of breeding teams in developing countries
can still be a bottleneck in the integration of molecular markers
into plant breeding strategies—now recognized as an effective
way to enhance crop improvement in the 21st century (Moose
& Mumm, 2008). Often described as “molecular breeding”
(MB), this usually includes marker-assisted selection (MAS),
marker-assisted backcrossing (MABC), marker-assisted recur-
rent selection (MARS) and genome wide selection (GWS) (Ri-
baut et al., 2010). MB is widely used for crop improvement and
cultivar development in developed countries, especially in
breeding programs in private-sector seed companies. Gene
discovery and knowledge of marker-trait associations have
even greater potential for developing new cultivars that can
face challenges of biotic and abiotic stresses while maintaining
high yields. Understanding the genetic basis of complex traits
and the pyramiding of favorable alleles for native traits will
likely be the basis of new opportunities for crop improvement
(Bliss, 2007; Varshney et al., 2012) and the next “green revolu-
One constraint to the use of MB in developing countries has
been limited genomics resources for most tropical crops, in-
cluding legumes, dry land cereals and clonal crops. However,
this constraint is being overcome by research investment in
developing genomic resources for crops often considered “or-
phans” (Raju et al., 2010; Varshney et al., 2010; Gautami et al.,
2012). Most staple crops in developing countries now have
adequate genomic resources for meaningful genetic studies and
most MB applications (Ribaut et al., 2010). The use of single-
nucleotide polymorphism (SNPs) markers in high-throughput
genotyping systems has contributed to a significant drop in
prices per data point (Delannay et al., 2012).While poor infra-
structure and lack of trained personnel have previously limited
adoption of MB, the falling prices for genotyping have made
outsourcing such services cost effective and reduced the need to
perform genotyping in expensive individual in-house laborato-
ries. This has increased access to genotypic data for a large
number of scientists, regardless of their background in molecu-
lar studies and laboratory experience. The challenge has hence
shifted from data acquisition to equipping breeders with suffi-
cient knowledge and tools to analyze important data from the
field and laboratories for use in cultivar development.
With these developments, today’s breeders face the challenge
of understanding how to take advantage of ever-expanding new
knowledge, spanning from marker–trait associations, quantita-
tive trait loci (QTL) mapping, genomics and gene discovery to
its use in breeding programs to increase genetic gain—all while
delivering cultivars to farmers in a timely manner. Updated
training on newly-developed technologies and their application
in breeding is required to allow practicing breeders to take full
advantage of this data revolution. New generations of breeders
coming out of colleges similarly require the essential knowl-
edge, skills and practical exposure in these fields to prepare
themselves for the challenges they will face very early in their
careers (Gepts & Hancock, 2006; Bliss, 2007; Repinski et al.,
2011). In addition to their breeding expertise they require
working knowledge of experimental design, advanced statisti-
cal methods, phenotyping methodologies and genotype-by-
environment (G × E) interactions (Morris et al., 2006; Delannay
et al., 2012). This is even more challenging in developing
countries because the lack of staff and resources requires them
to cover a wider range of activities. Fortunately, with the out-
sourced laboratories, breeders do not have to add laboratory
skills to their already long list of requisite expertise. They only
need to give breeding value to results they obtain from out-
sourced service providers.
To facilitate adoption of MB in the public sector, and espe-
cially in developing countries, the GCIAR Generation Chal-
lenge Programme (GCP,; verified 27
Aug. 2013) is leading the Integrated Breeding Platform initia-
tive (IBP,; verified 27 Aug. 2013)
(Delannay et al., 2012; Ribaut et al., 2013). This will enable
accelerated variety development using marker technologies—
from simple gene or transgene introgression to gene pyramiding
and complex MARS and GWS projects. The initiative has three
main components: the web portal—a gateway for the tools,
manuals, breeding materials, crop databases and breeding ser-
vices; the Integrated Breeding Workflow System (IBWS)—an
integrated software system for managing breeding logistics,
data, analyses, simulation and decision making through a user
friendly interface; and a brokerage of molecular marker labora-
tory services and capacity development activities (Delannay et
al., 2012).
The program of plant breeding capacity-building reported
here is an integral component of the IBP initiative, the goal
being to train 180 scientists working on the nine GCP target
crops (bean, cassava, chickpea, cowpea, groundnut, maize, rice,
sorghum and wheat) plus pigeonpea and soybean. These are
important crops in the three main target regions: West and Cen-
tral Africa (WCA), East and Southern Africa (ESA) and South
and Southeast Asia (SSEA). The training program will provide
access to modern tools to design and more efficiently manage
breeding experiments and better analyze genotypic and phenol-
typic data generated by their projects. The program will also
help to prepare breeders to meet challenges of managing infor-
mation and data central to MB, as this takes root and becomes
an integral part of crop improvement programs in the target
countries. Participants will acquire a comprehensive under-
standing of activities right from the initiation of an MB project,
through identification of target traits and markers correlated to
the breeding objective, to utilization of molecular markers.
Ultimately, they will gain the expertise needed to use molecular
markers efficiently and when needed in their programs.
The objective of this paper is to provide information on
breeding capacity in the public sector mainly in Sub-Saharan
Copyright © 2013 SciRes. 73
Africa (SSA) and South and South-East Asia (SSEA). In addi-
tion to the information obtained from the GIPB database, this
paper reports on the level of education, knowledge and exper-
tise in data analysis and MB application within their breeding
programs by a broad group of 367 scientists who applied to
attend the Integrated Breeding Multi-Year Course (IB-MYC).
Materials and Methods
Description of the Training
The IB-MYC technical training program was started to train
a purpose-selected group of potential IBP users over a three-
year period (2012-2014 for the first cohort). This consisted of
two weeks of face-to-face training per year, imparting progres-
sively more complex skills and providing post-training evalua-
tion and support to help overcome implementation challenges
and ensure long-term and sustainable adoption. The IB-MYC
follows a modular approach based on the sequential steps of an
integrated breeding project. The informatics tools and services
of the IBP project provide and support practical elements of the
course, and the trainees are an integral part of the Platform
development process by providing real-life field testing and
feedback. Hence, at the end of the three-year period, the train-
ees are expected to have a high proficiency in both conven-
tional and molecular breeding methodologies in general, as well
as use of the IBP informatics tools and services developed and
customized to support MB in their particular environments and
circumstances. Simultaneously, trainees will establish commu-
nities of practice (CoPs) that provide peer-to-peer technical
support under the oversight of the trainers, incorporating men-
toring, exchange of information and breeding materials, and
collective problem-solving. Establishing CoPs among student
breeders for evaluating and reflecting on their experience in
plant breeding is recommended by Repinski et al. (2011).
The IB-MYC ( e,
verified 27 Aug. 2013) training covers three core areas: mo-
lecular breeding (MB), data management (DM) and data analy-
sis and statistics (DAS). The MB section focuses on imparting
knowledge of breeding methodologies that use molecular mark-
ers. Instruction includes why, how and when to use the different
methodologies. The DM module examines how breeders can
efficiently access relevant information generated by themselves
and other scientists. It addresses management of germplasm,
population, phenotypic and genotypic data, and on the use of
crop information databases in breeding programs. The DAS
module covers analysis of phenotypic data generated from sin-
gle and multiple environments including G × E interactions,
estimation of genetic variance parameters, and analysis of ge-
notypic data and detection of QTLs in single and multiple en-
vironment setting. It also covers experimental design, and how
to select one based on the research objectives.
Nomination Procedures
A call was sent in early 2012 to all GCP collaborators re-
questing nomination of candidates working on GCP’s nine
target crops (bean, cassava, chickpea, cowpea, groundnut,
maize, rice, sorghum and wheat) and two other important crops,
pigeonpea and soybean, a request for nominations was also sent
to other networks such as the Africa Rice Breeding Task Force,
the African Centre for Crop Improvement (ACCI), the West
African Centre for Crop Improvement (WACCI), the GIPB and
Rothamsted International African Fellowship Programme (AFP)
Alumni in order to reach outside the extended GCP community.
The list of nominees was shared with regional organizations in
WCA (CORAF/WECARD—Conseil ouest et centre africain
pour la recherche et le développement agricoles/West and Cen-
tral African Council for Agricultural Research and Develop-
ment) and ESA (ASARECA—Association for Strengthening
Agricultural Research in Eastern and Central Africa) to ensure
inclusion of their key partners.
The primary target of the program was breeders and crop
improvement scientists from developing countries in SSA and
SSEA that were carrying out research activities and research
data analysis. These included senior, middle-level and upcom-
ing breeders/scientists. Nominees who held an MSc degree in
plant breeding, plant genetics, biotechnology, molecular boil-
ogy, bioinformatics or biometrics were preferred, but holders of
a BSc in an appropriate field, were also accepted for the train-
ing program if they were the primary researcher/breeder on
their program.
Survey Procedures and Selection Process
A survey was administered to the 367 nominees with a dual
purpose: 1) to assess their knowledge of basic statistical meth-
ods and 2) to select candidates with comparable levels of
knowledge so as to have as uniform a group of trainees as pos-
sible. The survey was designed to determine what training they
had received in the last five years, the nature of their research
activities, the statistical concepts and procedures they knew and
used, their computer proficiency—specifically their proficiency
in Microsoft Excel (spreadsheet software) and Microsoft Ac-
cess (database software), and their understanding of basic ex-
perimental design and data analysis software packages. The
survey also requested general data about their country, em-
ployer, level of education and gender. They were asked to clas-
sify the activities they were engaged in, by choosing from
breeding, field and lab activities, physiology, agronomy, data
analysis and project management. The trainers involved in the
program selected the best candidates, basing their selection on
an assessment of each individual candidate.
Who Was Considered a Breeder?
Any scientist working in breeding-related fields such as
evaluation of material, development of lines, management of
germplasm, genetic enhancement, genetic diversity, and MB
and marker-trait association studies was considered to be a
breeder. More upstream areas like physiology and gene discov-
ery were considered to be “crop improvement” rather than
breeding per se. Scientists collaborating on projects with an
MB component, regardless of whether or not they contributed
to the genotypic data analysis, were considered as involved in
MB. This differs from the definition of biotechnologists as
reported on the GIPB database which excludes them from the
count of breeders. Thus in this study we focused on breeders
that were using biotechnology tools to achieve their breeding
Scope of the S t udy
This study focused on Africa and SSEA. In WCA, 13 coun-
tries where there was ongoing work on eight of GCP’s target
crops (bean, cassava, cowpea, groundnut, maize, rice, sorghum
Copyright © 2013 SciRes.
and wheat) and soybean were included in the selection process:
Benin, Burkina Faso, Cameroon, Cote d’Ivoire, Democratic
Republic of Congo, Ghana, Guinea, Liberia, Mali, Niger, Nige-
ria, Senegal and Sierra Leone. In ESA, 12 countries where there
was ongoing work on all 11 targeted crops of the present study
were included—Burundi, Ethiopia, Kenya, Malawi, Mauritius,
Mozambique, Rwanda, South Africa, Tanzania, Uganda, Zam-
bia and Zimbabwe. In SSEA, 11 countries with ongoing work
on eight of the target crops (bean, chickpea, groundnut, maize,
pigeonpea, rice, soybean, wheat) were covered—Bangladesh,
China, India, Indonesia, Laos, Myanmar, Nepal, Pakistan,
Philippines, Thailand and Viet Nam. In this last training group
we also included a few nominees from North Africa (NA)
recommended by other networks included in the nomination
process. They were from three countries (Algeria, Morocco and
The survey was sent to all 367 nominees, with the most
complete information received for 327 nominees. The response
rate was highest in ESA (88.3%), followed by SSEA and NA
(81.1%), and then WCA with the lowest response (78.9%).
Some respondents did not however complete all sections.
GIPB Database
The online GIPB database was used as an information source
for the numbers of breeders and biotechnologists in each coun-
try involved in our study. The most recent information was
used. In most cases this was from 2004 or 2005, but in some
cases was from 2001, 2003 and 2007. The 2001 information
was mostly for ESA.
Breeding Capacity of the National Programs
In WCA, we collected data on 95 nominees. They were cho-
sen based on nomination by their team, project or program
member. They represented 18.7% of the total number of breed-
ers and biotechnologists reported in the GIPB database for this
region. Their level of education varied from BSc to PhD and
included MSc and PhD students (Table 1). Most students were
actually staff members serving at their national institutions,
working while simultaneously pursuing their either had an MSc
or were working towards a PhD. The number of MSc students
was low and just one scientist only had a BSc degree. Data
from the GIPB database collected during 2001-2007 indicated
about 23% of the breeders were BSc level, raising the possibil-
ity that the BSc-level scientists were not nominated, had moved
to other positions or were not interested in learning new tech-
nologies. More than 71% of the 95 WCA nominees were in-
volved in MB projects (Table 2). This was high for the given
sample, as compared to the GIPB database that identified only
25% of the study subjects in the same region as biotechnolo-
In ESA, 137 scientists were nominated, representing 19.6%
of the breeders and biotechnologists in the region according to
the GIPB database. Their level of education spanned BSc to
PhD (Table 1). The number of BSc holders was particularly
high (11.7%), and they were mostly in senior positions. This
proportion of BSc holders was however still low compared to
the 42.5% reported in the GIPB database. The high number of
BSc holders nominated for training compared to WCA could be
partially explained by the fact that more than half of the breeder
Table 1.
Number of nominees with highest level of education for IB-MYC
training in the three regions targeted: WCA, ESA and SSEA and NA.
The missing data represents nominees that completed the survey but did
not fill all the fields.
Highest degree WCA ESA SSEA & NA
PhD 43 32 46
PhD students 21 34 3
MSc 26 36 24
MSc students 3 6 0
BSc 1 16 9
Missing data 1 13 13
Table 2.
Number of breeders involved in MB projects in the three targeted re-
gions WCA, ESA and SSEA & NA. The missing data represents data
not filled on the survey.
Involvement in MB WCA ESA SSEA & NA
Yes 66 79 69
No 24 51 25
Missing data 5 7 1
population in Ethiopia and Zimbabwe are at BSc level. As a
consequence the number of PhD-level breeders nominated was
low (23%). More than 50% of the nominees held an MSc or
were undertaking a PhD program. The GIPB database showed
that 37.5% of breeders in the region had an MSc degree. The
higher percentage of PhD holders in addition to the lower per-
centage of MSc- and BSc-level breeders could be a sign of
breeders getting more education. This is reflected in the per-
centage of MSc and PhD students (a total of 29.2%). More than
half (57.7%) of the scientists were involved in MB projects
(Table 2), which was very high given the 10.2% of biotech-
nologists reported in the GIPB database.
From SSEA and NA regions, 95 scientists were nominated.
They represented 4.1% of the community of breeders and bio-
technologists as reported in the GIPB database. Among the
nominees that responded to the survey (86.3%), about half
(48.4%) were PhD holders (Table 1). The number of PhD stu-
dents was low (3.1%), while 25.2% had an MSc and 9.4% a
BSc, with most of the BSc holders being from the Philippines.
The GIPB database showed that in the Philippines there were
many more breeders with a BSc than an MSc, and few had a
PhD. In India and Bangladesh, many breeders held an MSc.
The GIPB database did not include data on India but showed
that more than half of the breeders in Bangladesh (62.3%) had
an MSc. This status was well reflected in the sample of the
present study. The percentage of breeders collaborating in MB
projects was 72.6% (Table 2); while according to the GIPB
database survey biotechnologists represented just 20.4% in the
countries of our nomination, excluding data from two major
players in the region: China (biotechnologist data) and India
(both types of data).
Gender Representation
Female nominees were very few in Sub-Saharan Africa
Copyright © 2013 SciRes. 75
Copyright © 2013 SciRes.
(15.8% in WCA and 21.9% in ESA), but reached 26.3% in
SSEA and NA (Table 3(a)). After the selection process the
proportions were 14.8% in WCA, 18% in ESA and 33.3% in
SSEA & NA. Although selection did not include any gen-
der-based quotas, shortlisted women candidates were given
preference when making up the target number of workshop
participants. Only in the SSEA and NA group was there an
increase (of 7%) in the proportion of women after selection.
The proportion of trainees from SSA declined after selection by
1% and 3.9% in WCA and ESA, respectively. Countries were
also assessed based on the number of female nominees. Among
the countries with the highest number of nominations (17 to 41),
China had the highest female representation (41.1%) followed
by Kenya (30.3%); while Ethiopia and Mali had the lowest
(15% and 11.1%, respectively) (Table 3(b)). In the group of
countries that nominated 6 to 14 scientists, Ghana and Malawi
had the highest number of female nominees balance (30.7% and
30%, respectively), while Bangladesh and Senegal had the
lowest (7.7% and 7.1% women, respectively). Although there
were no data to support this, the percentage of female partici-
pants per region may reflect the proportions of scientists who
are women in each region; highest in SSEA and NA, followed
by ESA, with the lowest proportion in WCA nominations).
Data Analysis Software Proficiency
The level of proficiency in Microsoft Access and the number
of software packages used by individual respondents to analyze
data were among the questions asked in the survey to help
evaluate the capacity of the group to analyze scientific data.
Across the three groups “low level” of proficiency in Access
was 62.1% in WCA and SSEA and NA and 73% in ESA (Ta-
ble 4(a)). The difference between ESA and the other two re-
gions much higher in ESA (40.1%) than in WCA (27.4%) and
in SSEA and NA (25.3%) (Table 4(b)). The ESA region had
the lowest number of scientists using two different software
packages (24.1%), followed by WCA (27.4%) and SSEA and
NA (32.6%). The latter had the smallest proportion of scientists
using three software packages (11.6%) compared to ESA
(15.3%) and WCA (16.8%). The number of scientists dropped
with each additional software package increase within the range
of 4 - 8 packages. In ESA, the maximum number of software
packages used was five, but reached eight in WCA and SSEA
& NA. In WCA, scientists using a high number of software
packages (six and eight) were biometricians and breeders, re-
spectively, while in SSEA and NA they were all breeders. In
the latter region they were mostly PhD holders but some were
Table 3.
(a) Gender representation of nominees within the three regions WCA, ESA and SSEA & NA; (b) Gender representation of nominees per country.
Total represents all nominees per country.
Gender representation WCA ESA SSEA & NA
Males 79 107 70
Females 15 29 25
Missing data 1 1 0
Country list Total Female Country list Total Female Coun try list Total Female
Benin 3 1 Burundi 1 0 Algeria 2 2
Burkina Faso 6 1 D. R. Congo 1 0 Bangladesh 1 3 1
Cameroon 3 1 Ethiopia 20 3 China 17 7
Cote d'Ivoire 5 0 Kenya 33 10 India 41 7
Ghana 13 4 Malawi 10 3 Indonesia 2 0
Guinea 1 0 Mauritius 1 1 Laos 1 0
Liberia 1 0 Mozambique 12 2 Morocco 2 2
Mali 18 2 Rwanda 1 0 Myanmar 1 1
Niger 4 0 South Africa 5 1 Nepal 3 0
Nigeria 26 5 Tanzania 30 6 Pakistan 1 0
Senegal 14 1 Uganda 11 2 Philippines 8 2
Sierra Leone 1 0 Zambia 2 1 Thailand 2 2
Zimbabwe 10 1 Tunisia 1 0
Viet Nam 1 0
Table 4.
(a) Level of proficiency in Access of the nominees in the three t argeted
regions; (b) Number of software packages of data analysis used by the
nominees in the three reg ion s.
Proficiency in Access WCA ESA SSEA & NA
Low 59 100 59
Average 10 16 13
Advanced 3 2 2
Missing data 23 19 21
Number of software packages WCA ESA SSEA & NA
1 26 55 24
2 26 33 31
3 16 21 11
4 3 9 3
5 2 3 2
6 1 - 3
7 - - 2
8 1 - 1
Missing data 20 16 18
MSc and BSc holders; in WCA they were all PhD holders.
Higher levels of education seemed to be a factor in increased
level of sophistication in analyzing data.
Number of Activities Carried Out
The number and the type of activities carried out by the
nominees were assessed through the survey and were catego-
rized into Agronomy, Breeding, Data analysis, Field, Lab,
Physiology and Project management activities. The information
was provided by 82.1% of respondents in WCA to 89.7% in
ESA (Table 5(a)). In WCA, 80.8% of respondents identified
breeding among their activities compared to 87.8% and 91.6%
in ESA and SSEA and NA respectively. Data analysis and Field
activities were the next two categories most important among
the activities identified by survey participants ranging from
69.2% to 83.7% across the three regions. Physiology was the
least pursued activity ranging from 19.2% to 29.6% in WCA
and SSEA & NA, respectively, compared to 26.8% in ESA.
Lab activities were in the range of 53.8% - 60.5% in the three
regions. Agronomy was less counted in SSEA and NA (28.4%)
compared to 50% and 58.5% in WCA and ESA regions, re-
spectively. Project management was less counted in WCA
(26.9%) than in ESA and SSEA and NA (49.6% and 48.1%,
respectively). The number of activities per nominee ranged
from one to all seven (Table 5(b)). In WCA most nominees
had carried out 3 - 4 activities, representing 20.5% and 30.8%,
respectively. Scientists carrying out one type of activity were
12.8%, while those carrying out all seven categories were low
(1.3%). In ESA, most nominees carried out 4 - 5 categories of
activities (27.6% and 20.3%, respectively). There were more
nominees carrying out all seven activities than those carrying
Table 5.
(a) Type of activities carried out by the nominees in the three regions;
(b) Number of activities among the seven categories carried out per no-
minee in the three regions.
Agronomy activities 39 72 23
Breeding activities 63 108 74
Data analysis 54 100 66
Field activities 57 103 61
Lab activities 42 68 49
Physiology activities 15 33 24
Project management 21 61 39
Missing data 17 14 14
Number of activities WCA ESA SS EA & NA
1 10 8 5
2 5 10 11
3 16 12 12
4 24 34 17
5 12 25 21
6 10 18 5
7 1 16 10
out only one (13% and 6.5%, respectively). In SSEA and NA
the trend was very similar to ESA with 21% and 26% carrying
out four and five activities, respectively, 12.3% all seven activi-
ties and 6.2% only one activity. In ESA and SSEA and NA
where there were more BSc-level nominees, they carried out up
to seven activities in ESA and six in SSEA & NA. Comparison
cannot be made with WCA as only one nominee was BSc level.
There were more breeders at a BSc level in ESA than in the
other regions. Some were senior breeders who had probably
begun their career before MSc and PhD levels became a re-
quirement for scientists in their respective countries. The high
level of BSc holders in the African breeding community has
been reported previously, although the numbers have decreased
to the benefit of MSc and PhD levels between 1985 and 2001 in
both WCA and ESA (Guimaraes et al., 2006). The decrease
was attributed to more people pursuing higher degrees, as indi-
cated by the fact that in 2012 most of the MSc and PhD stu-
dents participating in IB-MYC training program were staff
members of their national institutions. There were more nomi-
nations by institutions in ESA such as Ethiopia, Kenya and
Tanzania than in WCA. In fact nomination in ESA was done at
the level of the institution and not the program as in WCA. The
large numbers of nominations could be related to the high
number of breeders in these institutions; as reported in the
GIPB database, which showed that Ethiopia had the highest
number of breeders (408) followed by Kenya (63)—while
Copyright © 2013 SciRes. 77
Tanzania was not surveyed in the GIPB database. Therefore the
level of capacity needed in these countries could be much larger
than in countries with fewer breeders. In SSEA and NA, despite
approximately half of the breeders holding a PhD degree, there
were still a substantial number at the BSc level. The breeding
capacity was much greater (according to the GIPB database)
with an average number of breeders per million inhabitants (MI)
of 3.06, ranging from .9 in Bangladesh to 9.7 in Algeria, but
excluding China, India, Indonesia and Viet Nam. Breeding
capacity was 2.76 breeders per MI in ESA, with the lowest
capacity in Uganda (.9) and the largest in Ethiopia (5.6). WCA
had the least capacity among the three regions (2.03 breeders
per MI) with Mali having the highest (3.4) and Senegal the
lowest (1). The higher capacity in SSEA and NA in terms of
number and level of education of the breeders could explain a
lesser need in capacity strengthening hence the low level of
nominations for IB-MYC.
The percentage of breeders with PhDs in WCA was almost
double that in ESA in both case studies (i.e. nominations for
IB-MYC and the GIPB database). Our survey showed that the
percentages of PhD students, MSc holders and MSc students
were very similar in both regions. It seems that a higher level of
educational attainment (PhD), by enhancing the level of tech-
nical sophistication of the breeder, has been a factor in SSA in
increasing the involvement of the breeders in MB activities.
Female representation was low in our study and likely re-
flects the low representation of women in crop science in gen-
eral. Repinski, et al. (2011) found female representation of
16.9% compared to an average of 21.3% in the present study in
the three regions. In a subset of the study of Repinski et al.
(2011) that reported only on people working in the private sec-
tor, female representation was even lower at one out of 27 par-
ticipants in the final round of the survey (Miller et al., 2011).
The low representation of women in science in general (science,
technology, engineering and mathematics—STEM) is a well-
known problem not only in developing countries, but was also
reported 10 years ago in industrialized countries around the
world (Blickenstaff, 2005). Although updated data was not
found to support this idea, it seems the level of women in sci-
ence and especially in biology-related subjects and plant
breeding has improved in recent years.
Level of education of users did not seem to be related to use
of software packages like MS Access. For BSc through to PhD
holders, trainees had used it, although not many considered
their level of proficiency as “Advanced”. In contrast, the num-
bers of software packages used to analyze data seemed to be
more linked to the education level of trainees. Most BSc-level
breeders, regardless of their region, and in some cases senior
breeders, were only using one software package. A high level
of sophistication in data analysis, as represented by numbers of
software packages used, was dependent on level of education.
Improving knowledge of statistics and experimental design is
particularly important in national programs, as in most cases
they do not have access to an in-house biometrician to provide
guidance on experimental design before setting up experiments
and on analysis after the cropping season. In WCA, for instance,
due to lack of funding, most such scientific positions were
eliminated or not replaced after scientists had left. As a result a
disproportionately large reduction in research capacity and
efficiency was experienced by many developing countries
(Morris et al., 2006). Looking at the different categories of
activities breeders were carrying out, more than 80% of nomi-
nees in all regions were carrying out three or more activities
regardless of their level of education. This shows breeders in
the three regions are managing several aspects of their breeding
programs to counteract the lack of adequate staff as well as the
lack of specialized expertise. The BSc-level scientists carrying
out project management in ESA and SSEA and NA are most
probably senior breeders, as the present study showed that they
existed in larg e n umbers these two regions.
In view of the increasing complexity of skills and data that
breeders need for integrated breeding, recent attempts have
defined what an ideal breeding training program should look
like through inputs provided by breeders from the public and
private sectors in developed countries, but also the public sector
in newly industrialized and developing countries (Gepts &
Hancock, 2006; Bliss, 2007; Repinski et al., 2011). The most
prominent categories were practical breeding, experimental
design, scientific communication, analytical aptitude, field
work, statistics and data management. Some of these categories
are covered in the IB-MYC training, such as breeding method-
ologies, experimental design, data analysis, statistics and data
management. The latter is one of the major components of the
IBP initiative after it was realized that there were few informa-
tion systems (IS) in breeding that integrated a database of
germplasm information, phenotypic data and a complete ana-
lytical pipeline (Ribaut et al., 2013). This kind of database is
widely used in human disease as reviewed by (Thorisson et al.,
2009). Central databases for breeding exist for each of the crops
of interest for CGIAR centers. They should include pedigree
information of the germplasm, phenotypic information covering
several years and locations, agronomic traits they carry and in
some case s related genotyp ic information. The centers have the
responsibility to maintain, curate and populate them and they
are at various stages in terms of information content. The IBP
initiative is providing the cyber-infrastructure to link the large
amount of available information. This will allow access to the
data through query tools, and also facilitate analysis and breed-
ing decisions via various analytical and decision support tools.
The choice of the parents using all available information in-
cluding pedigree, traits and performance in different environ-
ments will be a key factor in making significant progress in a
breeding program (Sun et al., 2011). IB-MYC is providing
trainees with the knowledge to create their own breeding data-
bases and also integrate information provided by the crop lead
center or CGIAR center responsible for their research crop.
Other important training areas are statistics, experimental de-
sign and data analysis. They can have important impacts on
performance prediction and breeding outcome (Sun et al., 2011).
The need for statistical and related field knowledge was among
the important suggestions made by scientists surveyed in the
public sector of developed, newly industrialized and developing
countries who generally do not have access to statistical con-
sultants, unlike the situation in the private sector (Repinski et
al., 2011).
The large number of scientists in SSEA and NA collaborat-
ing on an MB project was expected. Their countries are invest-
ing substantially in technology and research and development,
and are self-reliant in most aspects of marker technologies (Ri-
baut et al., 2010). They are classified in Tier-1 and Tier-2,
countries considered to be aware of the importance of MB, with
some application of marker technologies. It was however sur-
prising that in WCA, where most countries are classified in
Tier-3 (countries struggling to sustain their breeding programs),
Copyright © 2013 SciRes.
the number of scientists involved in MB was as high as in
SSEA and NA. This confirms the dramatic change reported
between 1985 and 2001 in the use of biotechnology tools in that
region (Guimaraes et al., 2006). During the same period, the
number of biotechnologists probably increased in the USA even
though the real count was available only after 2001 (Bliss,
2007). This shows that the trend in using biotechnology in ag-
ricultural sciences occurred all around the world even though
the level of involvement might differ. This was facilitated by
the contribution of several donors, mainly private foundations
that promoted the use of technology including biotechnologies
(Ribaut et al., 2008). They have contributed to promotion and
use of molecular markers at different levels in Africa and Asia.
The fewer breeders involved in MB reported in ESA confirmed
a previous report (Guimaraes et al., 2006), although these au-
thors also mentioned they had evidence of more biotechnology
research and related development underway in ESA. From our
sampling it is clear that enthusiasm for MB is still lowest in
ESA—despite countries like Ethiopia, Kenya, Malawi, South
Africa, Uganda and Zambia having at least half of their nomi-
nees with some level of involvement in MB. Indeed, countries
like Malawi, Mozambique and Zambia that had one or no bio-
technologists in 2001 are now carrying out MB projects.
It is important to establish the level of integration of MB in
national programs, beyond the collaboration some scientists
would have in MB projects with CGIAR centers and ARIs. As
previously mentioned, in recent years the research objectives of
the donors had driven activities in national breeding programs.
If given the opportunity, would national partners be ready to
carry out their own MB breeding project? The GCP as part of
its mission to promote adoption of MB has been providing re-
sources for high-throughput genotyping to national programs in
developing countries through the Genotyping Support Services
(GSS) program. Grant recipients were initially competitively
selected, but in 2011 GCP made a restricted call to give the
opportunity to its national partners already collaborating on MB
projects involving international partners to carry out a small
MB project alongside their bigger GCP-funded project. This
was to overcome difficulties most breeders from developing
countries would encounter in obtaining funding to carry out
high-throughput genotyping, and to provide an opportunity to
breeders exposed to MB to further extend their experience by
applying the technologies to other components of their breeding
program that might not capture the attention of donors. Most of
the targeted breeders were managing phenotyping projects in-
volving international teams. The genotyping was being done or
coordinated by institutions they were partnering with, such as
the CGIAR centers and ARIs. Projects supported by GSS
needed to involve QTL identification, MAS or MABC. The
partners were in SSA, except one that is based in India. How-
ever, after almost two years very few have completed their
projects and some have not yet started despite several remind-
ers and a threat to cut funding. The Indian partner was the first
to complete their project while the partners from Burkina Faso,
Kenya, Mali and Nigeria are at different stages. Projects from
partners in Mozambique, Niger, Senegal and Tanzania seem not
to have sustained the initial interest in view of the delay in
submitting samples. Can this situation be explained as reluc-
tance to apply modern breeding technologies? Probably not, as
all the breeders to whom the opportunity was offered are in-
volved in MB to a certain extent. This could be more linked to
the difficulty for people to change the way they do things. In
the adoption of new technologies, people’s mindset and reluc-
tance to get out of their comfort zone remain a major bottleneck
anywhere in the world. Excluding Burkina Faso and Mali, all
countries that had completed or advanced in their sample sub-
mission for genotyping (India, Kenya and Nigeria) are Tier-2
countries as defined (Ribaut et al., 2010). They are known to be
using and applying biotechnology techniques in their breeding
programs (Morris et al., 2006; Ribaut et al., 2010). Most coun-
tries that have not submitted their samples are mostly Tier-3—
they are developing countries with limited resources for breed-
ing activities. The funding limitation for a prolonged period of
time must have negatively impacted on the capacity of the sci-
entists to integrate new technologies and bring them out of their
comfort zone as previously described. Burkina Faso and Mali
are amongst the few developing countries where transgenic
crops are being tested, Bt-cotton in their case. This may explain
why they are eager to use marker technologies despite being
Tier-3 countries.
The role and activities of plant breeders are evolving rapidly.
In developed countries, breeders coordinate a team where dif-
ferent crop improvement specialists collaborate. However, in
developing countries many breeders are isolated, with limited
access to specialists, and have to rely on their own knowledge
and skills (Repinski et al., 2011) to overcome the shortage of
complementary professionals. Historical declines in funding for
agricultural research and capacity building (Morris et al., 2006),
which was in part the result of the structural adjustment policies,
resulted in the weakening of national programs. However, some
donors are changing their strategies and are funding important
programs in SSA that will make a difference. Among them, the
Bill and Melinda Gates Foundation is funding major projects
where CGIAR centers and ARIs are working with national pro-
grams to apply molecular markers in their breeding programs.
These projects explain the high numbers of scientists involved
in MB projects in SSA, especially those working on legumes
(bean, chickpea, cowpea, groundnut, pigeonpea and soybean),
cassava, maize and sorghum. In recent years the WB has initi-
ated two major projects, the West Africa and the East Africa
Agricultural Productivity Programs (WAAPP and EAAPP,
respectively). Their goal is to stimulate and accelerate adoption
of improved technologies in the top agricultural commodity
priority areas of participating countries that are aligned with the
top agricultural commodity priorities of the sub-region. These
programs cover research, the training of breeders, and infra-
structure improvement. The IB-MYC program fits perfectly
with such donor efforts to improve the capacity of national
programs. It is providing a knowledge update on key areas
including genetics, genomics, statistics, experimental design,
data management and phenotyping methodologies to enable
breeders to harness the potential of MB in the near future. It
aligns with updated training initiatives that were developed in
the USA in recent years to enhance expertise of plant breeders
such as the University of California-Davis Plant Breeding Aca-
demy (; verified 27 Aug. 2013) that has
trained breeders in the USA, Europe and Asia. In June 2013,
UC-Davis launched the African Plant Breeding Academy in
collaboration with the African Union’s New Partnership for
Africa’s Development (NEPAD) initiative and the African
Orphan Crops Consortium. Their training program is organized
Copyright © 2013 SciRes. 79
Copyright © 2013 SciRes.
in six one-week sessions over two years while IB-MYC is six
two-week sessions over three years. The important element in
such continuous programs is the possibility to follow up with
trainees and determine how they are integrating the knowledge
and skills acquired in their day-to-day activities. In case they
are not doing this, it is then possible to understand the difficul-
ties they are encountering and help them to overcome them.
Two more training courses should be mentioned: the “Plant
Breeding for Drought Tolerance” course
(; verified 27 Aug. 2013) offered
by Colorado State University and the “Partnership for Research
and Education in Plant Breeding and Genetics” offered by Pur-
due University (Miller et al., 2011). All these initiatives will
enhance the capacity of breeders not only from developed
countries but also developing and newly industrialized coun-
tries where the demand for highly trained skilled breeders is
increasing rapidly. Challenges will however remain on how to
ensure that conventional breeders in developing countries will
take full advantage of the genomic era and go beyond their
comfort zone by integrating marker technology and the use of
more powerful statistical packages in their breeding programs
to better serve the farmers in their regions. An additional chal-
lenge will be concerted action by all actors (GCP as training
organizer and sponsor, regional organizations ASARECA and
CORAF/WECARD, National programs) to ensure greater visi-
bility of the SSA trainees in their institutions and regions after
they have completed the course. This would enable them to
benefit from additional resources (such as from EAAPP and
WAAPP) to fully put into practice knowledge and skills ac-
quired from IB-MYC to enhance their breeding programs.
The authors thank all the GCP collaborators that contributed
to the design of the training program, for selecting the candi-
dates and for designing the survey: Ibnou Dieng (Africa Rice),
Theresa Fulton (Cornell University), Marcos Malosetti (Wa-
geningen University and Research Centre, WUR), Chikelu Mba
(Food and Agriculture Organization, FAO), Fred van Eeuwijk
(WUR) and GCP team members Xavier Delannay, Graham
McLaren, Arllet Portugal, Mark Sawkins and Hamer Paschal.
We are thankful to C. Mba of GIPB for providing email con-
tacts of the GIBP network of breeders. We are thankful to Aida
Martinez of GCP for administering the survey via SurveyMon-
key® and all the support she provided afterwards in extracting
and compiling data from it. We appreciate the critical review
and comments provided by Fred Bliss of University of Califor-
nia Davis. The authors thank the nominees who responded to
the survey for providing us with the valuable information pre-
sented here. We thank our main donors: the Bill and Melinda
Gates Foundation, the CGIAR Fund, the European Commission
and the Swiss Agency for Development and Cooperation.
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Abbreviations and Acronyms
ACCI: African Centre for Crop Improvement,
AFP: African Fellowship Programme,
ARIs: Advanced Research Institutions,
ASARECA: Association for Strengthening Agricultural Re-
search in Eastern and Central Africa,
CoPs: communities of practice,
CORAF/WECARD: Conseil Ouest et Centre Africain Pour
la Recherche et le Développement Agricoles/West and Central
African Council for Agricultural Research and Development,
DAS: Data Analysis and Statistics,
DM: Data Management,
EAAPP: East Africa Agricultural Productivity Programs,
ESA: East and Southern Africa,
GCP: Generation Challenge Programme,
GIPB: Global Partnership Initiative for Plant Breeding Ca-
pacity Building,
GSS: Genotyping Support Services,
GWS: Genome Wide Selection,
IB-MYC: Integrated Breeding Multi-Year Course,
IBP: Integrated Breeding Platform,
IBWS: Integrated Breeding Workflow System,
IS: Information Systems,
MABC: Marker-Assisted Backcrossing,
MARS: Marker-Assisted Recurrent Selection,
MAS: Marker-Assisted Selection,
MB: Molecular Breeding,
MI: Million Inhabitants,
MS: Microsoft,
NA: North Africa,
QTL: Quantitative Trait Loci,
SNPs: Single-Nucleotide Polymorphism,
SSA: Sub-Saharan Africa,
SSEA: South and Southeast Asia,
WAAPP: West Africa Productivity Progra ms,
WACCI: West African Centre for Crop Improvement,
WB: World Bank,
WCA: West and Ce nt ral Africa,
WUR: Wageningen University and Research Centre.
Copyright © 2013 SciRes. 81