Estimates of Genetic Parameter Contributing To Early Bulkiness of Yellow Root Cassava (Manihot Esculenta Crantz) Genotypes in Niger State, North Central Nigeria
Estimates of Genetic Parameter Contributing To Early Bulkiness of Yellow Root Cassava (Manihot Esculenta Crantz) Genotypes in Niger State, North Central Nigeria
Estimates of Genetic Parameter Contributing To Early Bulkiness of Yellow Root Cassava (Manihot Esculenta Crantz) Genotypes in Niger State, North Central Nigeria
ISSN No:-2456-2165
Abstract:- Genetic variability among different genotypes Keywords:- Genetic Variability, Root Bulkiness, Heritability.
for root yield component characteristics was studied in
Guinea Savannah Agroecological zones of Niger state to I. INTRODUCTION
determine its effect on early root bulkiness. Sixteen
parameters were evaluated in 420m2 at spacing of 1mx1m Cassava (Manihot esculenta Crantz) is a perennial shrub
in a randomized complete block design in three replicates. originated in the neotropics. Its most important product is the
Cassava genotypes were evaluated at 3 and 6 MAP (Month starchy roots used as a source of caloric energy by millions of
After Planting) to evaluate root bulkiness. REML/BLUP people, particularly in Sub-Saharan Africa (Stapleton 2012;
showed significant difference among genotypes for Norton 2014). Cassava is the fourth most important basic food
different harvesting periods for Harvest Index and fresh after rice, wheat, and maize worldwide, but is the second most
storage root yield (FSRY). Estimates of genetic variance important food staple in terms of calories consumed in sub-
for phenotypic (PCV) and genotypic coefficient of Saharan Africa (Cacamisi, 2010; Tarawali et al., 2012).
variation (GCV) were very close. PCV estimates were
higher than GCV and varied from 39% to 13% for root The crop is called Africa’s food insurance because it
weight and root size respectively. Broad sense heritability offers reliable yields even in the face of drought, low soil
estimates were high for FSRY and ranged from 81% to fertility, low intensity management and because of its
8% among root yield components. GCV estimates was resilience to face the effects of climate change (Burns et
higher for harvest index (34%) and least for number al.,2010). Late bulking cassava stay long on the farm
harvested (6.15%). Heritability was highest for fresh predisposing it to bush fires and animal invasion particularly
storage root yield (81%) and least for shoot weight (0%), during dry season especially in the northern part of the
Environmental coefficient of variation was least for country. Late bulking cultivars occupy land for extended
harvest index (HI) with 0.36 and shoot weight had the periods of time and consequently the land cannot be
highest coefficient of variation and the least being for effectively utilized for other crops and it is the single most
harvest index. Genotype IKN120036 performed best important factor responsible for rejection and abandonment of
among the genotypes with 3.61tha-1 and had the highest cassava cultivars in African countries (Okechukwu &
genetic gains in terms of selection criterion FSRY. FSRY Dixon,2009; Kamau et al., 2011). Farmers usually cultivates
and HI had higher heritability and were strongly local varieties with low yields and high yielding and early-
correlated (R= 0.61). Root number was not bulking varieties could only guarantee higher yields when
significant(P>0.05; R=-0.24) and negatively correlated harvested at 12 months (Nweke, 2004). As cassava has no
with FSRY. specific maturation period; therefore, harvest can take place as
soon as reasonable root yield has been formed. Farmers
where y is a vector of observations from plots for each cassava (σ 2 G x 100)/X where X is the phenotypic mean, and σ 2 G is
variety the genotypic variance (Asante & Dixon, 2002).
β and b are the fixed and random effect vectors Phenotypic Coefficient of Variation
respectively, e denotes the random error vector, and X is the Phenotypic coefficient of variation was calculated as the
incidence matrix of the fixed effects for the variety; Z the square of phenotypic variance component expressed as a
incidence matrix of random effects corresponding to percentage of mean as follows:
replication; and ε, the random residual variance when the
genotype and replication was considered fixed and random (σ 2 P x 100)/X where X is the phenotypic mean and σ 2
P is
respectively and vice-versa. The effect of MAP was evaluated the phenotypic variance (Asante & Dixon, 2002).
using combined analyses where genotype effect was
considered as fixed while MAP is random and genotype effect IV. RESULTS
was made random while MAP was fixed.
soil depths
b ~ N (0, G)
soil parameters 0-30cm
ε ~ N (0, R)
Cov [b, ε] = 0 Textural Class Sandy loam
V = ZGZ' + R PH 7.10
𝑌 𝑋𝐺
𝑅 I𝜎2R 0 ] Phosphorous(g/kg) 11.47
E=𝑅 = 0 ;Var =[
𝜀 0 𝐼𝜎2𝜀
𝜀 0
Carbon(g/kg) 8.56
The random effects are assumed to be distributed as µ
Nitrogen(g/kg) 0.74
MVN (0; G) and ε MNV (0; R) where MVN (U; V) means
Table 1:- Physicochemical properties of trial field
multivariate normal distribution with mean µ and variance-co-
variance matrix V (Piepho et al., 2008).
Effects of genotypes and harvest time on FSRY
Broad sense Heritability Estimates
Broad sense heritability (h2) of the all traits were 3 MAP 6 MAP
calculated according to the formula as described by Allard Genotype FSRY FSRY
(1960) as follow: h 2bs= [(σ 2 G) / (σ 2 P)] × 100, where: h2bs
= heritability in broad sense; σ 2 G = Genotypic variance; σ 2 P IBA070593(c) 2.16 2.17
= Phenotypic variance. IBA090525 2.00 1.89
IBA090581 2.59 2.32
Genetic Advance Estimates
Estimation of genetic advance Genetic advance (GA) IBA130818 0.98 0.89
was determined as described by Johnson et al., (1955): GA = IBA130896 2.16 2.17
K (σp) h2, where: K = the selection differential (K = 2.06 at
5% selection intensity); σp = the phenotypic standard deviation IBA141092 2.63 2.65
of the character; h 2 = broad sense heritability. The genetic IBA980581(c) 2.29 2.28
advance as percentage of the mean (GAM) was calculated as IKN120016 1.31 1.32
described by Johnson et al., (1955) as follow: GAM (%) =GA/
X * 100, where: GAM = genetic advance as percentage of the IKN120036 3.61 3.47
mean, GA = genetic advance, and x = grand mean of a TME419(c) 1.72 1.71
character. Table 2:- Mean performance of 10 yellow cassava genotypes
for FSRY at 3 and 6 MAP.
3 MAP 6MAP
GENOTYPE DSRY DSRY
IBA070593(c) 0.67 0.75
IBA090525 0.71 0.72
IBA090581 0.67 0.76
IBA130818 0.24 0.26
IBA130896 0.82 0.84
IBA141092 0.71 0.77
IBA980581(c) 0.86 0.87
IKN120016 0.51 0.53
IKN120036 0.99 1.06
TME419( c) 0.69 0.73
Table 3:- Mean performance of 10 yellow cassava genotypes for DSRY at 3 and 6 MAP.
3 MAP 6 MAP
Genotype HI HI
IBA070593(c) 0.34 0.38
IBA090525 0.52 0.49
IBA090581 0.44 0.45
IBA130818 0.11 0.12
IBA130896 0.31 0.33
IBA141092 0.56 0.6
IBA980581(c) 0.36 0.38
IKN120016 0.23 0.27
IKN120036 0.54 0.53
TME419( c) 0.34 0.38
Table 4:- Mean performance of 10 yellow cassava genotypes for Harvest Index at 3 and 6 MAP.
Identifying high yielding and early storage root bulking genotypes at 3 and 6 MAP in terms of HI.
6 MAP
3 MAP
Genotype HI Rank HI Rank
IBA070593(c) 0.30 6 0.38 5
IBA090525 0.50 3 0.49 3
IBA090581 0.40 4 0.45 4
IBA130818 0.10 10 0.12 10
IBA130896 0.30 8 0.33 8
IBA141092 0.60 1 0.60 1
IBA980581(c) 0.40 5 0.38 5
IKN120016 0.20 9 0.27 9
IKN120036 0.50 2 0.53 2
TME419( c) 0.30 6 0.38 5
Table 5:- Rank of 10 genotypes in 3 and 6 MAP using mean performance.
3MAP 6MAP
GENOTYPE EBI% FSRY FSRY
IBA070593(c) 120.00 6.00 5.00
IBA090525 100.00 7.00 7.00
IBA090581 100.00 3.00 3.00
IBA130818 100.00 10.00 10.00
IBA130896 83.00 5.00 6.00
IBA141092 100.00 2.00 2.00
IBA980581(c) 100.00 4.00 4.00
IKN120016 100.00 9.00 9.00
IKN120036 100.00 1.00 1.00
TME419( c) 100.00 8.00 8.00
Table 6:- Early Bulking percentage of 10 yellow cassava genotypes based on FSRY at 3 and 6 MAP
GENOTYPE DMC DSRY FSRY HI INNCOL NOHAV RTNO RTWT SC STWT VIGOR CMDS PLPCOL
IBA070593(c) 31.36 0.67 2.16 0.34 1.00 1.00 9.67 1.13 16.37 9.67 3.00 3.00 0.00
IBA090525 36.20 0.71 2.00 0.52 1.00 1.33 10.33 1.95 23.40 11.00 1.80 6.33 0.00
IBA090581 28.15 0.67 2.59 0.44 1.00 1.33 10.33 2.52 14.26 11.00 3.26 5.67 0.00
IBA130818 24.64 0.24 0.98 0.11 1.00 1.67 7.00 0.72 10.05 8.33 5.29 5.00 0.00
IBA130896 28.35 0.82 2.16 0.31 1.00 1.67 11.00 2.30 25.51 10.33 4.88 5.00 0.00
IBA141092 26.98 0.71 2.63 0.56 1.67 1.33 10.67 3.09 12.86 11.00 4.84 3.67 0.00
IBA980581(c) 37.61 0.86 2.29 0.36 1.00 2.00 12.33 2.82 24.80 13.00 4.84 5.67 0.00
IKN120016 38.60 0.51 1.31 0.23 1.00 1.33 10.67 1.35 26.21 8.00 4.69 4.33 0.00
IKN120036 28.25 0.99 3.61 0.54 1.00 1.00 7.00 2.70 12.86 12.00 2.05 4.33 0.00
TME419( c) 40.11 0.69 1.72 0.34 1.00 1.33 10.67 1.65 27.62 10.00 3.38 6.33 0.00
GrandMean 33.02 0.69 2.14 0.38 1.07 1.40 9.97 2.02 19.39 10.43 3.81 4.93 0.00
SE 3.88 0.15 0.46 0.07 0.11 0.28 2.80 0.58 4.35 1.22 1.45 0.76 0.00
CV 16.62 23.25 21.03 23.95 13.98 28.17 39.74 39.40 31.75 11.94 53.86 21.79 0.00
Table 7:- Mean performance of traits at 3 and 6 MAP
FSRY
3 MAP 6MAP
Yield component Correlation Coeff. (R) P-Value
Root Size 0.41 0.0060** 0.0066**
Shoot weight -0.11 ns ns
Root Number -0.24 ns ns
Harvest Index 0.61 0.0018** <0.0001***
Storage Root Diameter 0.26 0.0219* ns
Root Weight 0.57 ns 0.0017**
Dry Matter Content -0.3 ns ns
Table 8:- Pearson correlation coefficient of some selected yield component trait.
*, **, *** Significant at 0.05, 0.01 and 0.001 probability levels, respectively
3 MAP
Range 6 MAP
Character Mean CV Min Max Genotype Error Genotype Error
df=9 df=20 df=9 df=220
FSRY 2.14 21.03 0.98 3.61 2.14** 1.70 2.09** 1.68
HI 0.38 23.95 0.11 0.56 0.38** 0.36 0.39*** 0.37
ns
NOHAV 1.4 28.17 1.00 2.00 1.4 1.39 1.93** 1.90
ns
RTNO 9.97 39.74 7.00 12.33 9.97 9.97 13.77ns 11.86
ns
RTWT 2.02 39.4 0.72 3.09 2.02 1.71 2.82** 1.90
ns
STWT 3.81 53.86 1.80 5.29 3.81 3.81 4.48ns 3.40
Table 9:- Range, mean, coefficient of variation of traits evaluated at 3 and 6 MAP.
*, **, *** Significant at 0.05, 0.01 and 0.001 probability levels, respectively
Genotype P u+g G%
IKN120036 3.61 4.05 6.02
IBA141092 2.63 3.07 4.38
IBA090581 2.59 3.03 4.32
Table 11:- Genetic gains of top three genotypes.
This study revealed that shoot weight (Stwt) had zero Fresh storage root yield (fsry) had the highest heritability
heritability and genotypic coefficient of variation (GCV) values of 81%. Heritability among traits ranges from 81% to
which implies that its phenotypic expression is not due to its 0% for fsry and stwt (Shoot weight) respectively. High
genetic component but as result of the environmental heritability is an indication of less environmental influence in
influence (Table 10). A greater difference between phenotypic the observed variation (Eid, 2009).
coefficient of variation (PCV) and GCV is an indication of
greater degree of environmental control (Chikezie et al., Heritability Estimates
2016). Conversely, in similar study conducted by Rodrigo de The ability to express a particular trait as a result of
Souza et al (2016), they reported high genotypic coefficient of genetic component and phenotypic reliability in predicting its
variation and low heritability for shoot weight. It will be breeding value is provided by estimates of heritability
therefore suggested that the traits be studied in multi (Ndakauba et al., 2015). Heritability values for traits studied
environmental trial such as to accurately detect if the ranges from 81% to 0% for fsry and stwt respectively. Traits
manifestation of the traits is as a result of genotype or fsry having the highest heritability value of 81% shows that
environment. This then revealed that the highest coefficient of there is considerable genetic variation in the traits to warrant
variation value exhibited by the traits was influenced the selection for the best genotypes. Thus, such traits can be given
environment. Low heritability may be an effect of high more attention for the purpose of improvement (Chikezie et
environmental coefficient of variation which shows on low al., 2016). Heritability alone does not provide effective means
value of genetic gains (Rodrigo de Souza et al., 2016). of selection, genetic advance for the traits should be
considered (Ullah et al., 2012).
Coefficient of variation for fresh storage root yield was
21.03% and this affect selection as a result of genetic In this study, high heritability was observed with high
variability. This was similar to the coefficient of variation genetic advance over mean for fresh storage root yield and dry
obtained for fresh storage root yield in study conducted by storage root yield which is an implication of genotypic effect
Neto et al (2013) when 10 cassava genotypes were evaluated. rather than environmental influence which implies that the
genotypes will maintain their performance in any
Significant difference was observed in harvest index environment.
(HI) at different harvesting periods of 3 and 6 months after
planting (MAP) among genotypes (Table 4). This shows effect For traits such as the harvest index and root size which
of genetic variation and possibility of genetic gains. This was had higher heritability with low genetic advance over means is
similar to result obtained by Rodrigo de Souza et al (2016) an indication of environmental influence and this shows that
Heritability and genetic gain for Root number (Rtno) is VI. CONCLUSION
zero with 9.97% and 0% for PCV and GCV respectively.
There was no significance difference (P>0.005) among the Fresh storage root yield(fsry) and Harvest Index (HI) can
genotypes for the traits (Table 11). This is an indication that be considered as a good criterion for selection regarding root
the Rtno is influenced by the environments and not due to yield since fsry and HI showed a high heritability and both
genotype. It shows that the traits have non heritable were highly significant at P<0.01 with less environmental
component of phenotypic variance. However, Bareto & influence. Varying root size traits manifestation for each of the
Resende (2010) identified lower values of heritability (0.18%) genotypes was as a result of environmental influence which
and GCV (19.3%) for root number with genetic gains varying means that the environment has effect on the genotyic
from 26.4% to 32.85 with selection of best five genotypes. performance.
Also, Oliveria et al (2015) identified medium heritability of
0.51% and moderate GCV of 33.6% for root number and Root number and fresh storage root yield traits can be
genetic gains which varied from 16.1% to 33.8% for the 10 improved by direct crossing among selected genotypes.
best genotypes. Crossing have been successfully used in genetic breeding
programs of cassava (Ceballos et al., 2004).
The zero genetic gains were probably due to no
significant difference among the genotypes for root number Genetic Gain of 3 Best Genotypes
traits which implies that there is no genetic variation among Genetic gains varied from 6 to 4% considering the
the genotypes. As reported by Rodrigo de Souza et al (2016) selection of the three best genotypes when compared with the
that lower genetic gains for root number was as a result of an general mean of the population (Table 11)
effect of lower genetic variation among genotypes for root
number. The low environmental coefficient of variation RECOMMENDATION
(ECV) of 9.97% this was similar to what was reported by
Rodrigo de Souza et al (2016) where they observed ECV Genotype IKN120036 had the highest FSRY value of
value for Rtno to be to be below 30%. 3.61t/ha at both 3 and 6 MAP, therefore made genotype
IKN120036 the best genotype of all genotype. Genotype
Root weight has moderate heritability value of 49% has IKN120036 had the highest genetic gains in terms of FSRY.
possibility for improvement. Cassava root traits with moderate However, to confirm that the genotype had the best gene
heritability values can be improved base on their phenotypic expression for the trait FSRY used as a selection criterion, the
performances (Aina et al., 2007). trial should be repeated over a long period of time length such
as to confirm the accuracy and the reliability of the genetic
HI shows high level of heritability (80%) as also gain base on the trait.
confirmed by Kawano et al (1989) which implies less
environmental influence on the traits. Aina et al., (2007) also LIMITATION
found higher values of heritability of 57% in their studies.
Similar result was obtained by Ojulong et al., (2008) when For adaptation and stability of the genotypes across
they obtained moderate heritability for HI traits from the different location other than Niger state, phenotypic evaluation
analyses 979 genotypes from International Institute of trials and analyses will have to be conducted in multiple
Tropical Agriculture in their studies. environments.