Genotype x environment interaction and stability analysis for yield and its components in selected cassava (manihot esculenta crantz) genotypes in southern tanzania

Journal of Biology, Agriculture and Healthcare www.iiste.org
ISSN 2224-3208 (Paper) ISSN 2225-093X (Online)
Vol.4, No.19, 2014
Genotype x Environment Interaction and Stability Analysis for
Yield and its Components in Selected Cassava (Manihot Esculenta
Crantz) Genotypes in Southern Tanzania
A.C. Kundy1* G.S. Mkamilo1 R.N.Misangu2
1.Naliendele Agricultural Research Institute, P.O. Box 509, Mtwara, Tanzania
2.Department of Crop Science and Production, Sokoine University of Agriculture, P.O.Box 3005
Morogoro Tanzania
*E-mail of the corresponding author: ackundya@hotmail.com
Abstract
The present investigation was carried out to study stability performance over three environments for root yield
and its components in twelve genetically diverse genotypes of cassava using a Randomized Complete Block
Design. The partitioning of (environment + genotype x environment) mean squares showed that environments
(linear) differed significantly and were quite diverse with regards to their effects on the performance of
genotypes for root yield and majority of yield components. Stable genotypes were identified for wider
environments and specific environments with high per se performance (over general mean) for root yield per
plant. The investigation revealed that the genotypes Kiroba (21.72 t ha-1) and NDL 2006/487 (19.5 t ha-1) were
desirable and relatively stable across the environments. Other genotypes NDL 2006/850 was suitable for
favourable situations, while genotypes NDL 2006/104 and NDL 2006/283 were suited to poor environments for
root yield.
Keywords: G X E Interaction, Stability Analysis, Cassava, Root Yield, Yield Components
1.0 Introduction
Cassava (Manihot esculenta Crantz) is from the family Euphobeaceae. It is among the most important root crops
worldwide and provides food for one billion people (Bokanga, 2001; Nuwamanya et al., 2009). It is an important
food crop in developing countries, and it is the fourth source of calories, after rice, sugar cane and maize
worldwide (Akinwale et al., 2010). The edible roots supply energy for more than 500 million people worldwide
(Ceballos et al., 2006). It is a perennial crop, native to America and grown in agro ecologies which differ in
rainfall, temperature regimes and soil types (Olsen and Schaal, 2001). Cassava constitutes an essential part of the
diet of most tropical countries of the world (Calle et al., 2005). In Africa the crop is the most important staple
food grown and plays a major role in the effort to alleviate food crisis (Hahn and Keyer, 1985).
The success of cassava in Africa, as a food security crop is largely because of its ability and capacity to yield
well in drought-prone, marginal wastelands under poor management where other crops would fail. Despite
cassava’s ability to grow in marginal areas (Mkumbira et al., 2003), large differential genotypic responses occur
under varying environmental conditions. This phenomenon is referred to as genotype x environment interactions
(G x E), which is a routine occurrence in plant breeding programmes. Recent studies on genotype by
environment interactions in some economic crops include the work by Akinyele and Osekita (2011), Sakin et al.,
(2011), Ngeve et al., (2005) and Kilic et al., (2009). Both the genotype and the environment determine the
phenotype of an individual. The effects of these two factors, however, are not always additive because of the
interaction between them. The large G x E variation usually impairs the accuracy of yield estimation and reduces
the relationship between genotypic and phenotypic values (Ssemakula and Dixon, 2007). G x E due to different
responses of genotypes in diverse environments, makes choosing the superior genotypes difficult in plant
breeding programmes. Traditionally plant breeders tend to select genotypes that show stable performance as
defined by minimal G x E effects across a number of locations and/or years. The term stability is sometimes used
to characterize a genotype which shows a relatively constant yield independent of changing environmental
conditions. On the basis of this idea, genotypes with a minimal variance for yield across different environments
are considered stable.
This study was therefore, designed to evaluate the influence of genotype (G), environment (E) and G x E
interaction on fresh root yield, root number, dry matter content, starch content, root size, plant height, number of
branches per plant, stem girth, harvest index, cassava mosaic disease and cassava brown streak disease of nine
(9) newly developed cassava genotypes across three agro-ecological zones of Southern Tanzania, namely;
Coastal low land (Naliendele-Mtwara), Masasi-Ruangwa plains (Mkumba-Nachingwea) and Makonde plateau
(Mtopwa-Newala).
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Vol.4, No.19, 2014
Cassava being the second most important food crop after maize in Tanzania, it is however faced with production
constraints from pests, diseases, poor agronomic practices and inadequacy of extension services to farmers (Lema and
Hemskeerk, 1996; Msabaha et al., 1988). Low yield of cassava in the Southern zone of Tanzania is caused by
many factors, including diseases and pests. Halima (2005) found out that, the yield of cassava under farmers’
conditions was 5 – 10 t ha-1, whereas attainable yield under research conditions was above 20 t ha-1. Use of
local varieties which are susceptible to diseases and with poor genetic traits are among those factors contributing
to low yield. Efforts on screening for genotypes with high yield potential and tolerant to biotic and abiotic
stresses have been done, resulting in production of many improved genotypes, but farmers have not yet
benefited from these outcomes. This may be due to the fact that, the performance of such improved genotypes
has not been tested/evaluated for recommendations in different agro ecologies of the Southern zone (Banzigarer
and Cooper, 2001; Ceccarelli et al., 2003; Haugernd and Collinson, 1990; Witcombe, 1996; Baidu-Forson, 1997;
Morris and Bellon, 2004). There is a lack of information on the magnitude of G x E effect on yield and yield
components of improved cassava genotypes in the Southern zone of Tanzania.
The early growth and development of cassava depends very much on genetic and environmental factors. Most of
the community in the Southern zone depends on cassava crop as their main source of food. At Naliendele
Agricultural Research Institute (NARI) for example, many improved genotypes and few varieties have been
developed, but no recommendations for cassava varieties/genotypes have been made, with exception of one
variety, Naliendele. Naliendele variety was tolerant to Cassava Mosaic Disease (CMD) and Cassava Brown
Streak Disease (CBSD). In recent years, Naliendele variety has lost its trait for diseases resistance, CBSD &
CMD, which has caused a bad situation to the community of cassava dependent people. The newly developed
genotypes at NARI are now in final stages of breeding; therefore testing them and providing recommendations
of suitable ones to different agro ecologies was one step forward in solving the problem.
3.0 Materials and Methods
3.1 Experimental Sites and Materials
The experiment was conducted during the 2011/2012 cropping season in the Southern zone of Tanzania in three
agro ecologies. Coastal low land plains (in Mtwara urban) located at 10o 22'S and 40o 10'E, 120m above sea level;
Masasi-Ruangwa plains (in Lindi rural) located at 10o 20 ׳S and 38o46 ׳E, 465m above sea level and Makonde
plateau (in Mtwara rural) located at 10o 41'S 39o 23'E, 760m above sea level.
Nine newly improved cassava genotypes, one old improved variety (Naliendele as a control), one ex-Rufiji
variety (Kiroba) and 1 landrace (Albert) were used in this study (Table 1). Albert, was used both as a check and a
CBSD disease spreader. Limbanga was used as CMD disease spreader. Albert and Limbanga were planted
around the replications as a source of inoculum (spreader of the diseases) at all locations. The improved
genotypes were obtained from Naliendele Agricultural Research Institute - Mtwara, while the local ones were
from farmers’ fields.
Table 1: Cassava genotypes used in this study, their origin and status
Genotype Source Status
1 NDL 2006/104 NARI Tolerant to CBSD &CMD
10 NALIENDELE NARI Susceptible to CBSD &CMD and check
11 KIROBA Ex-Rufiji Tolerant to CBSD & CMD and check
12 ALBERT Farmers Local (Check in all sites)
3.2 Experimental design
A split-split plot experiment in a Randomized Complete Block Design (RCBD) was used to carry out the study.
Weeding regime as a crop management practice was used in each location, weeding once (W1) and weeding
twice (W2), in order to create micro environments for stability analysis. The experiment consisted of three
factors, location as main factor A, crop management (weeding regime) as sub factor B and genotype as sub-sub
factor C. Nine newly developed genotypes and three other varieties with three replications in each location
30

Vol.4, No.19, 2014
spaced at 1 m x 1 m, 4 rows planted with 7 plants per row and a plot size of 7m long and 4m wide were used.
3.3 Statistical Analysis
Indostat/Windostat version 8.5 and Genstat version 14 statistical softwares were used for analysis. Means of
treatments were compared using Duncan’s Multiple Range Test at 0.001 and 0.05 levels of significance.
4.0 Results and Discusion
4.1 Effect of locations on root yield and its components
4.1.1 Cassava root yield
The results from this studyshowed variations in cassava root yield among genotypes within and across locations.
The mean root yield across locations ranged from 7.32 – 21.72 t ha-1. However the analysis for root yield
revealed that, Kiroba and NDL 2006/487 were identified as superior yielding genotypes across the locations
(Table 4). NDL 2006/487 showed wider adaptability across the locations, while Kiroba showed instability in root
yield performance. This implies that NDL 2006/487 can be grown in any of the three locations, while Kiroba is
favourable for Nachingwea site (Figures 1 – 4). The superiority for these treatments existed probably because
these two varieties had consistently high number of roots per plant across the locations and furthermore the two
genotypes were less affected by diseases. These results agree with previous study by Ntuwurunga et al., (2001),
who reported that, cassava root yield increases as plant root number increases. Variation among locations on root
yield was observed on NDL 2006/850 and NDL 2006/738 and therefore regarded as unstable genotypes. Stable
genotype, for root yield, across the locations were NDL 2006/438 and NDL 2006/741, although the latter
recorded lower yields across the locations.
Figure 1: b–values against roots per plant mean values
KEY:
1 = Albert, 2 = Kiroba, 3 = Naliendele, 4 = NDL 2006/030, 5 = NDL 2006/104, 6 =NDL 2006/283, 7 = NDL
2006/438, 8 = NDL 2006/487, 9 = NDL 2006/738, 10 = NDL 2006/741, 11 = NDL 2006/840, 12 = NDL
2006/850.
A = Albert, B = Kiroba, C = Naliendele, D = NDL 2006/030, E = NDL 2006/104, F =NDL 2006/283, G =
NDL 2006/438, H = NDL 2006/487, I = NDL 2006/738, J = NDL 2006/741, K = NDL 2006/840, L = NDL
2006/850.
31
Figure 2: S2d values against b – values for
roots per plant

Vol.4, No.19, 2014
Figure 3: b–values against root yield mean values. Figure 4: S2d values against b–values for root
Table 2: Stability parameters for root yield and some of its componets.
Variable Code Genotype Mean b -value b-1 Rank S2d Rank R2
Roots per plant 1 A Albert 4.8794 0.018 -0.982 12 2.9678 *** 10 0.0001
2 B Kiroba 4.5889 0.377 -0.623 11 1.5177 *** 9 0.0882
3 C Naliendele 5.9350 1.529 0.529 9 5.7994 *** 12 0.3049
4 D NDL 2006/030 5.4678 1.162 0.162 2 3.2922 *** 11 0.3056
5 E NDL 2006/104 4.6378 1.569 0.569 10 1.0116 *** 6 0.708
6 F NDL 2006/283 4.4889 1.290 0.290 4 1.1990 *** 8 0.5846
7 G NDL 2006/438 3.6706 1.107 0.107 1 1.0104 *** 5 0.5473
8 H NDL 2006/487 3.4628 1.163 0.163 3 1.1862 *** 7 0.5358
9 I NDL 2006/738 3.6911 0.524 -0.476 7 0.9309 *** 4 0.226
10 J NDL 2006/741 3.5983 0.508 -0.492 8 0.7180 *** 3 0.2557
11 K NDL 2006/840 4.1861 1.429 0.429 6 0.4565 *** 2 0.7989
12 L NDL 2006/850 4.0600 1.360 0.360 5 0.3718 ** 1 0.8085
4.3888 1.003 0.003 6.5 1.7051 6.5 0.4303
Root size 1 A Albert 0.2372 0.1360* -0.864 5 -0.004 8 0.0515
2 B Kiroba 0.2194 0.0790* -0.921 9 -0.0049 11 0.0462
3 C Naliendele 0.2428 0.177 -0.823 4 0.0009 3 0.0211
4 D NDL 2006/030 0.2522 0.088 -0.912 6 0.0014 5 0.005
5 E NDL 2006/104 0.3417 2.342 1.342 10 0.0447 *** 12 0.3242
6 F NDL 2006/283 0.2356 1.213 0.213 3 -0.0022 6 0.6617
7 G NDL 2006/438 0.2306 -0.07 -1.07 8 -0.0027 7 0.0076
8 H NDL 2006/487 0.2244 0.059 -0.941 7 0.0012 4 0.0023
9 I NDL 2006/738 0.2556 3.1910* 2.191 11 0.0004 2 0.8831
10 J NDL 2006/741 0.2656 3.2500* 2.25 12 -0.0001 1 0.8963
11 K NDL 2006/840 0.2739 0.887 -0.113 1 -0.0042 9 0.7347
12 L NDL 2006/850 0.2783 0.806 -0.194 2 -0.0046 10 0.7599
0.254775 0.68775 0.0131667 6.5 -0.0017091 6.5 0.3661
Root yield 1 A Albert 7.3211 1.962 0.962 12 50.28 *** 0.4827
2 B Kiroba 21.7223 1.7311 0.7311 9 45.86 *** 9 0.3152
3 C Naliendele 11.454 1.2832 0.2832 6 102.93 *** 12 0.8113
4 D NDL 2006/030 8.9501 1.2612 0.2612 5 91.45 *** 11 0.7105
5 E NDL 2006/104 12.8924 0.9971 -0.0029 1 5.87*** 4 0.591
6 F NDL 2006/283 10.8811 0.934 -0.066 2 9.53 *** 7 0.8354
7 G NDL 2006/438 20.6121 0.2581 -0.7419 10 5.68 *** 3 0.3361
8 H NDL 2006/487 17.5331 0.2132 -0.7868 11 4.73 *** 2 0.6896
9 I NDL 2006/738 13.4734 0.4687 -0.5313 7 3.61 *** 1 0.7849
10 J NDL 2006/741 8.9362 0.4553 -0.5447 8 5.88 *** 5 0.2161
11 K NDL 2006/840 13.0732 1.261 0.261 4 12.00 *** 8 0.1957
12 L NDL 2006/850 14.1722 1.2132 0.2132 3 7.77 *** 6 0.6545
13.4092 1.0031 0.003175 6.5 28.7992 6.5 0.5519
32
yield.
KEY:
1 = Albert, 2 = Kiroba, 3 = Naliendele, 4 = NDL 2006/030, 5 = NDL 2006/104, 6 =NDL 2006/283, 7 = NDL
2006/438, 8 = NDL 2006/487, 9 = NDL 2006/738, 10 = NDL 2006/741, 11 = NDL 2006/840, 12 = NDL
2006/850.
A = Albert, B = Kiroba, C = Naliendele, D = NDL 2006/030, E = NDL 2006/104, F =NDL 2006/283, G =
NDL 2006/438, H = NDL 2006/487, I = NDL 2006/738, J = NDL 2006/741, K = NDL 2006/840, L = NDL
2006/850.

Vol.4, No.19, 2014
Generally the trend for the root yield (Figure 5) was not consistent with increase in altitude, as the yields were
higher at Nachingwea located 465 masl, followed by the yields at Naliendele located at 120 masl and lastly
Mtopwa which is located at relatively high altitudes 760 masl. These results are in agreement with observations
by Ntawurunga and Dixon, (2010) that experienced the same trend of root yield at different altitudes. This is
because cassava performs better in mid altitudes, as compared to low and high altitudes where temperatures are
very high and very low respectively (Ntawurunga, 2000). Therefore the differences in yield among the three
locations could be due to differences in temperature; where at Mtopwa site the temperatures are relatively low
and therefore the rate of growth and root filling needs longer time for the crop to attain its optimum yield, while
at Naliendele the temperatures are very high to an extent that both plant growth and root expansion are retarded.
However selecting the best performing genotypes and locating them to the most suitable locations remains a
necessary criterion for the best yield results.
45.00
40.00
35.00
30.00
25.00
20.00
15.00
10.00
5.00
Figure 5: Effects of location on cassava root yield (t ha-1) grown at Naliendele (low altitude),
Nachingwea (mid altitude) and Mtopwa (high altitude)
The variety Kiroba was on average considered as the best for root yield across the three locations and
specifically for Nachingwea (Table 4), while genotype NDL 2006/487 was more suitable for Naliendele and
Mtopwa. Based on these results therefore, Nachingwea was the most suitable location for cassava root yield
production, as this location had suitable conditions for cassava growth and development (Appendix 1). The
weather data agrees partially (in this season), with optimum conditions for cassava growth and production as
those suggested by (Nassar and Ortiz, 2007).
The performance of yield and yield components at all locations were below the expected ones (Kundy et al.,
2014) as most of the newly selected genotypes were expected to yield about 18 t ha-1 and above. Mkamilo
et al., (2010) in unpublished research reports, reported that, these genotypes when tested in Advanced Yield
Trials, had root yields ranging between 18 - 25 t ha-1. This low performance may be attributed to the weather
conditions that prevailed during the cropping season 2011/2012 (Appendix 1), which was not optimum. These
results do not conform to the optimum conditions for cassava growth and development. According to Nassar and
Ortiz, 2007, cassava performs better in low land tropics requiring a warm temperature (24°C – 27°C), moist
climate and rainfall between 1000mm – 1500mm per annum.
4.1.2 Plant height
At Nachingwea, genotypes had the tallest cassava plants as compared to the two locations. This could be due to
the fact that Nachingwea had good rainfall and optimum temperatures (Appendix 1) which had favoured plant
growth compared to Naliendele and Mtopwa. Genotype NDL 2006/850 had the highest plant height across the
locations and also gave highest plant heights at Nachingwea and Mtopwa. Plants with high heights do not
33
0.00
Naliendele
Mtopwa
Nachingwea

Vol.4, No.19, 2014
guarantee high yields as plant height is not among the main factors contributing to yield (Ntawurunga et al.,
2001). Also this is supported in this experiment whereby Kiroba had low to medium plant heights, but with high
to highest root yields. The overall mean number of plant height was 144.9 cm. These results are within the range
of cassava plant height of 100 to 400 cm (Ekanayake et al., 1997; Tan and Cock, 1979).
4.1.3 Number of branches per plant
This variable showed significant variations within and across locations. Nachingwea had many plants with many
branches per plant compared to other sites. High number of plants with high number of branches at Nachingwea
was supported by the good moisture availability (Appendix 1), which favoured both vegetative growth and root
yield. The number of branches per plant varied from 1.15 to 4.17 in the three locations. This differed a little bit
from the results obtained by Villamayor, (1983) in research done at Philippines’ Root Crop Research and
Training Center, where number of branches per plant ranged between 1.6 and 2.0. The overall highest number of
branches per plant was recorded on the treatment Kiroba. High number of branches per plant is not an indicator
for high root yield, as the correlation between number of branches per plant was positive non – significant
(0.0947). To support this, NDL 2006/487 had the lowest number of branches per plant within and across the
locations, however it was among the best yielders; whereas NDL 2006/741 had higher numbers of branches per
plant, but it was the least yielder, indicating that selection for high yield would require other parameters apart
from number of branches per plant.
4.1.4 Stem girth
This parameter showed significant variations within and across locations. Naliendele had many plants with wider
stem girths compared to the other two locations. The widest value of plant stem girth was recorded on Naliendele
variety at Naliendele site. Higher plant stem girths at Naliendele could be contributed by the moderate moisture
content, as compared to Mtopwa and Nachingwea, experienced during plant growth (Appendix 1). The stem
girth ranged between 2.79 and 6.17 cm. This agrees with study done by Ikeh et al., (2012), who reported that
cassava stem girths ranged between 3.10 and 5.80 cm. Stem girth had positively and highly significant
correlation with yield (r = 0.481**) indicating that, improvement of stem girth will also improve root yield. This
agrees with findings by Ntawurunga et al., (2001), who reported that, stem girth is among the main yield
components contributing to root yield.
4.1.5 Number of roots per plant
Based on this study, it was observed that the mean number of roots per plant varied significantly within and
across locations. Nachingwea had plants with many roots compared to other locations. The differences may have
been caused by distribution of rainfall and temperature in these locations. Nachingwea received more rainfall as
compared to Naliendele and Mtopwa. Furthermore, the temperatures for Nachingwea during the 2011/2012
cropping season (Appendix 1), favoured growth and development of cassava and hence many roots per plant.
Number of roots per plant varied from 1.63 to 10.03. These results were below the number of roots per plant
obtained by Cock, (1985) at CIAT, which were in the range of 5 to 20 roots per plant. This remarkable difference
between these two experiments may be due to different environmental conditions. The sites under this study are
in dry environments, and according to Cock, (1979), fewer storage roots are formed in drier environments.
Kiroba, NDL 2006/438 and NDL 2006/487 gave better performance at Nachingwea, indicating that, these three
genotypes were suitable in that location for good number of roots per plant and ultimately high yields. This
variable had a positively and highly significant correlation with yield (0.7053***).
4.1.6 Root size per plant
Mean weight in kilograms of roots revealed significant variations within and across locations. Nachingwea had
the highest mean weight of roots per plant compared to other sites. In this study, across the locations root size
ranged between 0.19 kg and 0.38 kg, which agrees with study conducted by Alfredo, (1997), who reported that
weight of a single cassava root varied from 0.17 to 2.35 kg. Albert, NDL 2006/283, NDL 2006/438, and NDL
2006/487 appeared to be stable in terms of performance with respect to this character and had average to high
values. These genotypes had (b -1) values of 0.213, -1.07 and 0.941 respectively as an indication of their stability.
This suggests that, these genotypes had wider adaptability in terms of root size. Genotype NDL 2006/741
appeared to be unstable with inconsistent performance from one location to another with a (b -1) value of 2.25
(Table 2).
4.1.7 Harvest Index
With respect to harvest index, genotypes varied significantly within and across locations. The highest harvest
index was obtained from Kiroba at Naliendele, while the overall highest harvest was obtained on NDL 2006/738.
This highest value of harvest index at Naliendele, probably may be due to low rainfall (Appendix 1) received in
34

Vol.4, No.19, 2014
this area, and therefore made the accumulation of water in the shoots to be low; which resulted to low shoot
weight, low total weight and hence high harvest index. With respect to Kiroba having the highest harvest index
at Naliendele, this may be due to the short and reduced aerial parts of Kiroba, which was 116 cm tall with
average of 7 roots per plant as compared to NDL 2006/850 (144 cm tall) with average of 4 roots per plant. The
harvest index values ranged between 0.57 and 0.84. This was in contrast with what was observed by Joseph et al.,
(2011) who reported a range of 42.33 – 54.54 % in hybrids (crosses) and 14.30 – 37.83 % in parents of those
crosses. This big difference in harvest index probably has been contributed by variations in genetical traits, as
harvest index in cassava is little affected by the environment and is a good indicator of the potential performance
of a genotype across agro-ecological zones (Kawano, 1990).
4.2 Effect of locations on cassava major diseases on the Cassava Genotypes
4.2.1 Cassava brown streak disease
Significant variations were observed among the treatments at all locations. The highest disease incidence and
severity were observed at Nachingwea on the variety Albert. The higher occurrence of the disease in
Nachingwea compared to other locations can be due to location specific problem, as Nachingwea is known to be
one of the high pressure disease areas in southern Tanzania (Hillocks, 1997). Albert was a stable susceptible
variety which consistently recorded the highest disease incidences and severities across the locations. Probably,
this is due to the genetical make up of this variety, which is highly susceptible to CBSD, as this disease is also
transmitted through dissemination of infected planting materials. Other treatments that showed significant effect
on this disease were Naliendele at Nachingwea and NDL 2006/283 at Naliendele sites.
4.2.2 Cassava mosaic disease
Based on the results of this study, it was observed that the mean CMD varied significantly within and across
locations. Nachingwea had the highest disease incidence and severity recorded on the genotype NDL 2006/741.
The highest incidences and severity at Nachingwea is probably due to location as disease spread between plants
is by whitefly and can be rapid in some areas with high occurrence of this vector (Hillocks and Thresh, 2000).
NDL 2006/741 was susceptible across the locations as it was consistently affected by the CMD. Genotypes
Naliendele (at Naliendele and Nachingwea), NDL 2006/104 (at Naliendele) and NDL 2006/840 (at
Naliendele) also showed significant disease symptoms. The observed differences in CMD incidence and severity
among the genotypes could be due to genetic differences. This is because according to Hillocks and Thresh
(2000), the variations between cassava lines/genotypes diseases are inherited from planting materials and hence,
genetically controlled. This suggests that, for the tolerant newly developed genotypes, there is a room for using
them both directly for cassava root production and or using them in breeding programs as parents.
Table 3: Summary of location effects for the different variables
35
Location
RY
D PHT
BP
L
SG
H
RP
L
RT
Z HI
CBI
%
CB
S
CMI
%
CM
S
NE
C
DM
%
STH
%
PTN
%
Naliende
le
11.
62
136.
04
2.7
2
5.2
5
4.7
8
0.2
1
0.6
5
10.9
7
1.2
4
21.5
3
1.4
1
1.6
0
36.7
5
20.3
6 0.67
Mtopwa
8.1
0
96.8
9
2.4
9
3.3
7
3.2
1
0.2
5
0.6
5
11.8
9
1.3
0 8.34
1.1
9
1.3
1
37.9
2
21.2
1 0.88
Naching
wea
18.
18
158.
00
2.7
5
4.5
9
5.1
8
0.3
1
0.7
6
11.7
9
1.2
5
11.6
0
1.3
0
1.5
1
38.2
2
21.4
7 0.78
Mean
12.
63
130.
31
2.6
5
4.4
0
4.3
9
0.2
6
0.6
9
11.5
5
1.2
6
13.8
2
1.3
0
1.4
7
37.6
3
21.0
1 0.78
Where: RYD = Root yield, PHT = Plant height, BPL = Branches per plant, SGH = Stem girth, RPL =
Roots per plant, RTZ = Root size, HI = Harvest index, CBSI% = Cassava brown streak disease
incidence, CBS = Cassava brown streak disease severity, CMI = Cassava mosaic disease incidence,
NEC = Root necrosis, DM% = Dry matter, STH = Starch and PTN = Protein

Vol.4, No.19, 2014
Table 4: Means for root yield in cassava genotypes at Naliendele, Mtopwa and Nachingwea locations
Genotype Naliendele Mtopwa Nachingwea
ALBERT 5.00h 4.71f 12.23efg
KIROBA 14.11dc 10.56c 40.48a
NALIENDELE 16.00b 5.33f 12.87ef
NDL 2006/030 12.72ed 5.17f 8.97g
NDL 2006/104 11.22fe 5.83ef 9.06g
NDL 2006/283 11.42e 8.02d 13.20e
NDL 2006/438 14.40c 12.83b 14.61e
NDL 2006/487 19.02a 14.02a 19.45d
NDL 2006/738 9.77gf 10.15c 20.50d
NDL 2006/741 8.92g 8.22d 9.63fg
NDL 2006/840 4.71h 6.78e 12.33efg
NDL 2006/850 12.17e 5.55f 24.80c
Overall mean 11.62 8.10 18.18
s.e 1.32 0.98 0.91
c.v. (%) 11.40 12.10 5.00
Means with the same superscript letter(s) in the same column are not significantly different (P ≤ 0.05) following
separation by Duncan’s Multiple Range Test.
Table 5: Means for yield and growth parameters in cassava genotypes under combined analysis
Genotype PHT BRP STG RTP RTS HI RTY
ALBERT 134.20bc 2.93bcd 4.12ef 3.64fgh 0.24bcd 0.67bc 7.32g
KIROBA 116.90ef 3.71a 4.85a 7.03a 0.28bcd 0.73ab 21.72a
NALIENDELE 123.40de 2.86cd 4.27def 5.24c 0.20d 0.67bc 11.40e
NDL 2006/030 126.30d 2.80cde 4.07f 3.33h 0.22cd 0.68abc 8.95f
NDL 2006/104 130.20cd 2.97bc 4.59bc 3.52gh 0.19d 0.67abc 8.71f
NDL 2006/283 137.80ab 2.48efg 4.37cde 4.17de 0.25bcd 0.69abc 10.88e
NDL 2006/438 143.40a 2.51efg 4.32def 5.83b 0.22cd 0.71abc 18.61c
NDL 2006/487 138.80ab 1.22h 4.71ab 4.37d 0.22cd 0.60d 19.50b
NDL 2006/738 129.20cd 2.59def 4.43cd 3.89efg 0.38a 0.74a 13.47d
NDL 2006/741 112.60f 3.24b 4.35cde 3.81efg 0.23cd 0.66c 8.93f
NDL 2006/840 126.40d 2.21g 4.28def 3.77efg 0.33ab 0.68abc 7.94fg
NDL 2006/850 144.90a 2.28fg 4.87a 4.07def 0.30abc 0.71abc 14.17d
Overall mean 130.32 2.65 4.44 4.39 0.25 0.68 12.63
s.e 10.36 0.48 0.36 0.59 0.13 0.08 1.49
c.v. (%) 8.00 18.10 8.10 13.40 12.10 11.90 11.80
Key: PHT = Plant height (cm), BRP = Number of branches per plant, STG = Stem girth (cm), RTP = Number
of roots per plant, RTS = Root size (kg), HI = Harvest index and RYD = Root yield (t ha-1).
36

Vol.4, No.19, 2014
Table 6: Means for CBSD incidence, CBSD severity, CMD incidence and CMD severity at Naliendele,
37
Mtopwa and Nachingwea locations
CBS
DI
CBS
DS
CM
DI
CM
DS
Genotype
Nalien
dele
Mtop
wa
Nachin
gwea
Nalien
dele
Mtop
wa
Nachin
gwea
Nalien
dele
Mtop
wa
Nachin
gwea
Nalien
dele
Mtop
wa
Nachin
gwea
ALB
ERT
96.67a
93.33
a
100.00a 2.90a 2.97a 3.00a 0.00e 0.00c 1.67c 1.00d 1.00c 1.00c
KIROBA 0.00c 0.17b 0.00d 1.00c 1.01b 1.00d 0.00e 0.00c 0.00c 1.00d 1.00c 1.00c
NALIENDE
0.00c 0.00b 33.21b 1.00c 1.00b 1.84b 83.33b 0.00c 32.52b 2.67b 1.00c 1.80b
LE
NDL
2006/030
0.00c 4.17b 0.00d 1.00c 1.17b 1.00d 26.31d 0.00c 0.00c 1.00d 1.11c 1.00c
NDL
2006/104
0.00c 4.17b 0.00d 1.00c 1.17b 1.00d 0.00e
3.00b
c
4.56c 1.00d 1.00c 1.04c
NDL
2006/283
35.03b 0.00b 0.00d 1.96b 1.00b 1.00d 0.00e 0.00c 2.38c 1.00d 1.04c 1.11c
NDL
2006/438
0.00c
16.67
b
0.00d 1.00c 1.33b 1.00d 0.00e 2.08bc 2.22c 1.00d 1.00c 1.28c
NDL
2006/487
0.00c 0.00b 0.00d 1.00c 1.00b 1.00d 0.00e 0.00c 0.00c 1.00d 1.00c 1.00c
NDL
2006/738
0.00c 8.33b 0.00d 1.00c 1.42b 1.00d 31.66c 0.00c 0.00c 1.54c 1.00c 1.00c
NDL
2006/741
0.00c 7.50b 0.00d 1.00c 1.18b 1.00d 93.00a
87.50
a
95.83a 2.48a 2.87a 3.17a
NDL
2006/840
0.00c 4.17b 0.00d 1.00c 1.23b 1.00d 24.08d 0.00c 0.00c 1.35c 1.29b 1.00c
NDL
2006/850
0.00c 4.17b 8.33c 1.00c 1.13b 1.13c 0.00e 7.5 0.00c 1.00d 1.00c 1.00c
Overall
mean
10.97 11.89 11.79 1.24 1.30 1.25 21.53 8.34 11.6 1.41 1.19 1.30
s.e 1.95 2.34 3.99 0.07 0.33 0.11 3.43 2.01 2.44 0.18 0.14 0.24
c.v.
17.8 25.50 23.80 5.70 19.70 8.50 15.90 30.10 28.30 13.00 11.70 18.60
(%)
5.0 Conclusion and Recommendations
Among the genotypes used in this study, variety Kiroba and genotype NDL 2006/487, showed high mean root
yield, and were not significantly affected by diseases. Furthermore, variety Naliendele and genotype NDL
2006/438, although significantly affected by diseases, had high mean root yields at Naliendele and Nachingwea
respectively. This showed that these varieties are tolerant to diseases. Furthermore Kiroba, Naliendele, NDL
2006/487 and NDL 2006/438 were stable over the environments and therefore can be used in the breeding
programs for the development of high yielding stable genotypes over different environments for future use.
For cassava root yield production, it is recommended to grow Kiroba at Nachingwea and genotype NDL
2006/487 to be grown at Naliendele and Mtopwa sites where they performed best. For future G x E experiments,
it is recommended to employ the aspect of seasons or years in order to have reliable and precise information on
given varieties or genotypes. Also, further investigations on G x E interactions at important crop growth stages
for yield, yield components and biochemical profiles would help to develop strategies that integrate traditional
plant breeding with modern molecular marker based selection for tailoring cassava genotypes/cultivars for higher
yield and target environments.
6.0 Aknowledgements
We acknowledge the Government of Tanzania through Agricultural Sector Development Program (ASDP) for
funding this study. We thank the farmers involved in this study for both their time and information. We also
thank all who reviewed this paper and provided valuable advice. Finally, we thank staff members of Roots and
Tuber Crops Research Sub program at NARI for their assistance in the field work.
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Appendix 1:Rainfall and temperature data recorded at different locations during 2011/12 cropping season
Rainfall (mm) Temperature (°C)
Month Naliendele Mtopwa Nachingwea Naliendele Mtopwa Nachingwea
January 216.3 257.5 240.9 28.2 22 24.84
February 81.4 136.5 113.5 29.9 23.3 25.52
March 260.3 347.3 297.8 28.8 21.7 24.9
April 84.4 98.4 108.5 28.7 20 24.8
May 63.3 7.5 98.1 29 19.4 24.1
June 3.9 0 11 28.3 18.9 25.4
July 13.5 3 0 28.5 20 25.6
August 6.3 12.5 1.2 28.7 22 24.9
Total 729.4 862.7 870
39

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