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     American Journal of Agricultural Science, Engineering and Technology 
 

 
 ISSN: 2158-8104 (Online), 2164-0920 (Print), 2021, Vol. 5, Issue.2 

http://journals.e-palli.org 

 



     American Journal of Agricultural Science, Engineering and Technology 
 

 
 ISSN: 2158-8104 (Online), 2164-0920 (Print), 2021, Vol. 5, Issue.2 

http://journals.e-palli.org 

The American Journal of Agricultural Science, Engineering and Technology (AJASET) is 
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Published Media: ISSN: 2158-8104 (Online), 2164-0920 (Print).  

Frequency: 2 issues per year (January, July)  

Area of publication: Agricultural Science, Engineering and Technology. The subjects 
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     American Journal of Agricultural Science, Engineering and Technology 
 

 
 ISSN: 2158-8104 (Online), 2164-0920 (Print), 2021, Vol. 5, Issue.2 

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EDITORIAL BOARD 

 

Chief Editor 

Dr Mamun-Or-Rashid 

Professor, Dhaka University, Bangladesh 

 

Board Members  

Dr. Sumit Garg, IL, USA 

Professor Dr. James J. Riley, The University of Arizona, USA 

Dr. Ekkehard KÜRSCHNER, Agriculture Development Consultant, Germany 

Professor Dr. Rodriguez Hilda, USA 

Professor Dr. Michael D. Whitt, USA 

Professor Dr. Wael Al-aghbari, Yemen 

Professor Dr. Muhammad Farhad Howladar, Bangladesh 

Dr. Clement Kiprotich Kiptum, University of Eldoret, Kenya 

Professor Dr M Shamim Kaiser, Professor, Jahangirnagar University, Bangladesh 

Professor Dr Mohammad Shahadat Hossain, Chittagong University, Bangladesh 

 

Managing Editor 

Md. Roshidul Hasan 

Professor, Department of Computer Science and Information Technology,  
Bangabandhu Sheikh Mujibur Rahman Agricultural University, Bangladesh



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EVALUATION OF MORPHOLOGICAL CHARACTERS AND YIELD 

VARIABILITY OF SOME ELITE CASSAVA (MANIHOT ESCULENTA  CRANTZ) 

IN UYO, SOUTHEASTERN NIGERIA 

DOI: https://doi.org/10.5281/zenodo.5449188  

Udounang, P.I. 1*,  Ekwere, O.J.1 , Ofonime R.A. 1  

 

ABSTRACT 

Field experiment was carried out at Okigwe to evaluate some morphological traits and yield 

variablility of some elite cassava varieties with aim of making innovative recommendation to 

farmers. The experiment laid out in a complete block design, replicated three times. The 

treatments were six cassava varieties; TMS 30572, TME 419, TMS 98/0505, TMS 98/0581, 

TMS 01/1412 and local variety known as Obubit Okpo. Data collected from growth and yield 

were subjected to analysis of variances. Significant means were compares using least 

significant difference (LSD) at 5% probability level. Among the cassava varieties; TMS 

98/0581 had superiority over in four characters namely; leaf area, storage root length, storage 

root circumference and yield. Also TMS 01/1412 was superior in terms of number of leaves 

per plant and number of storage roots per plant while TME 419 was superior in terms of plant 

height. Since TMS 98/0581 had four major characters, it could be disseminated to farmers in 

Uyo, Akwa Ibom State, while the other varieties TMS 01/1412, and TME 419 which were 

superior in two and one characters respectively could be incorporated into breeding 

programme with TMS 98/0581 to produce hybrid varieties with higher yield for the study 

area.  

Keywords: Cassava, characters, breeding and yield. 

1 Department of Crop Science, Faculty of Agriculture, Akwa Ibom State University Obio 

Akpa Campus, Akwa Ibom State Nigeria. 

*Corresponding authors address: email; patunang@yahoo.com 

 

 

 

 

 

 

 



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INTRODUCTION 

Cassava (Manihot esculenta) is a very important root crop in the tropical and sub-tropical 

regions of the globe. It has been cultivated for several centuries, yet the yield is low. It is a 

key component of the diet of over 800 million people across several continents (El-Sharkawy, 

2012). About 70 million people drive more than 500 kcal per day from consuming cassava 

storage roots (Burns et al., 2011). In Nigeria, cassava is processed into different local diets 

such as garri, fufu or apu, abacha, akpu mmiri, adibo, etc (Ikeh 2017). Ikeh (2017) noted that 

cassava is a major dominant component crops in crop mixtures especially in southeastern 

Nigeria. Due to high demand of cassava product in local market, couple with its low yield, 

different cassava breeding programms has tend to proffer a solution on how to triple its yield.  

Plant breeding has the highest rate of return among the investment in agricultural research of 

which cassava has also benefited (Ceballos et al; 2012; Utomi, 2015). Bassey and Harry 

(2013) revealed that high and stable production of fresh storage roots is the key breeding 

objective in most cassava breeding projects. Ikeh (2017) indicated that productivity plays a 

major role in industrial uses of cassava, whether for starch, animal feed or bio-ethanol, 

whereas stability of production is fundamental in the regions where cassava is the main 

subsistence crop. Conventional breeding of cassava involves selection of out-performed 

parental genotypes for the characters or traits of interest, hybridizing them and conducting 

multi-stage offspring selections (Jennings and Iglesias, 2002; Ceballos et al; 2012; Bassey 

and Harry, 2013). This is often aimed at the accumulation of beneficial alleles and 

elimination of detrimental ones. High frequency genes of specific desirable characteristics, 

including yield components, yield stability, storage root quality and quantity, resistance to 

pests and diseases, to clearance to soil and climatic factors stresses, and good processing 

qualities are progressively accumulated through recurrent selection of cassava bred.  

Variability among cassava genotypes is a means of selecting for desirable traits which had led 

to significant progress in cassava improvement programme (Akinwale et al 2010; Ikeh 2017). 

Variation among varieties of cassava is not only genotypic in nature but influenced by the 

environment (Aina, 2007). The overall variability in cassava could be partitioned into 

heritable and non-heritable components with the use of suitable genetic parameters, such as 

coefficient of variation, heritability estimates, genetic advance and phenotypic variance for 

traits. (Bassey and Harry,2015; Utomi, 2015). Cassava varieties could be distinguished from 

one another by morphological characteristics such as leaf size, colour and shape of leaves, 

branching habits, plant height, colour of the stem, leaf area, storage root shape and colour etc. 



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Evaluation and morphological characterization of cassava varieties can by classify into 

morpho-types based on important agronomic traits. Characterization determines the 

expression of characters ranging determines the expression of characters ranging from 

morphological or agronomic features to seed protein or molecular marker (Engels and vassal, 

2003). Characterization is essential to provide information on the traits accessions, assuring 

the maximum utilization of the plants. According to Ezebiro et al (2013) cassava 

characterization can be carried out at any stage of the plants growth as long as there is 

sufficient number of materials to sample. Several attempts through field research have made 

in producing improved cassava varieties at different locations in Nigeria but due to various in 

both biotic and abiotic factors at different parts of the country sometimes the best performing 

cassava varieties in one region are not among the best in some other region. Therefore 

evaluation of cassava genotypes under this condition would help to identify those varieties 

that are adaptable to Okigwe local conditions for use by farmers and also s elect promising 

ones for production of hybrid varieties for the area.  

 

MATERIALS AND METHDOS 

The study was conducted at the National Cereals Research Institute (NCRI), Uyo Out-

Station, Akwa Ibom state, during the early and late planting season of 2017 between the 

months of March and December. The experimental site is situated between latitude 04o58' N 

and longitude 07o56'E and about 67 m above sea level. The area which lies within the humid 

tropical rainforest zone of southeastern Nigeria has average annual rainfall of about 2500 mm 

and mean monthly sunshine of about 3.14 hours. The mean annual temperature range is 

26°C- 28°C. Uyo has an annual mean relative humidity of 79% and evaporation rate of 2.6 

cm2. The rainfall pattern of Uyo is bimodal. Rain usually starts in mid- March and ends in 

Mid-November, with a short period of relative moisture stress in August traditionally referred 

to as “August Break” (Peters et al., 1989). Temperatures are generally highest in the months 

of February through April (Peters et al., 1989).The soil has been described as a typical acid 

soil. 

The experiment site was manually prepared into ridges of 1m apart. The ridges were marked 

5m long and separated by 1m paths. Composite soil samples were collected at two soil depths 

(0-15cm and 15-30cm) using soil auger before planting. The soil samples were carefully put 

in polyethylene bags and labeled before being taken to the laboratory for analysis. At the 

laboratory, the soil samples were air dried, crushed and sieved through a 2.0mm mesh, and 



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labeled and stored for phyisco-chemical analysis. Soil pH was determined in water 1:2 (soil 

water ratio) using pH meter with glass electrode (Bates, 1954). Total nitrogen in the soil was 

determined by microkjeldahl digestion and distillation method (Ibia and Udo, 2009). Organic 

matter was determined by the dichromate wet oxidation method of walkley and Black (1934). 

Available P was determine by Bray-I method of Bray and Kurtz (1945). Exchangeable bases 

were extracted with neutral ammonium acetate solution. Calcium (Ca) and Magnesium (Mg) 

was determined in the extracts of EDTA titration of Jackson (1962), while potassium (K) and 

soium (Na) were determined by the use of flame photometer. Exchangeable acidity was 

extracted with 1mol of KCl solution, while exchangeable acidity was determined by titration 

with NaOH as described by Kamprath (1975). The exchangeable hydrogen was obtained by 

subtracting exchangeable aluminum from the exchangeable acidity. Effective cation 

exchange capacity (ECEC) was obtained by the summation of exchangeable cations and 

exchangeable acidity (Ibia and Udoh, 2009). 

The experimental design used was a randomized complete block design (RCBD) with three 

replications. Six cassava varieties used as treatments were; TMS 98/0505, TNS 98/0581, 

TME 419, TMS 01/1412, TMS 30572, with one local cultivar Ohu pam as check. The 

treatments (varieties) were randomly assigned to plots to eliminate bias. The six cassava 

varieties namely; TMS 98/0505, TMS 98/0581, TME 419, TMS 01/1412, TMS 30572, were 

obtained from the National Root Crops Research Institute (NRCRI) Umudike, Abia State, 

while Obubit Okpo (local cultivar) was obtained from Farmers field in Uyo Akwa Ibom 

State. The experimental area was 36m x 23 (828m2). There were 18 plots in the experimental 

area, each measured 5m x 5m and demarcated from one another by 1m paths. Similarly, each 

block was demarcated from one another by 2m. Planting was done on March, 2018 and 2019 

immediately after land preparation. Healthy stem cutting of 25cm long were planted in an 

incline position of 450 on the crest of ridges, at 1m intra and inter row spacing. Manual 

weeding was carried out at 1 and 5 months after planting with aid of a weeding hoe, followed 

by slashing at 8 months after planting. Fertilizer (NPK: 15:15:15) was applied 2 months after 

planting at 400kg/ha, using the ring application method.  The cassava storage roots were 

harvested at 12 months after planting.  

Data Collection  

Six (6) plants were randomly tagged within the next plots for data collections and the 

following growth and yield data were measured.  



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Establishment percentage was done at first months after panting. This was calculated as the 

number of established stands over total number of planted stands in a plot and expressed in 

percentage. Cassava height was obtained by measuring tagged plants from the ground level to 

terminal point of the plants 3, 6 and 9 months after planting (MAP). Leaf areas were 

determined by measuring the length of each lobe and width of all the leaf lobes of each 

tagged plant. The means for length of all the leaf lobes and the sum of width of all leaf lobes 

were multiplied and the product was further multiplied by a correction factor of 0.74 

(Hammer, 1980). Number of leaves per plant was determined by physical counting of all 

functional leaves of tagged cassava plants. Number of harvested tubers per plant was done by 

counting all the cassava tubers produced by each plant and of all the tagged plants in each 

plot and the means recorded for each variety. The length of storage roots harvested from 

sample cassava plants was measured from the proximal to distal and using a flexible 

measuring tape in centimeter. The circumference of storage roots determine by measuring 

circumference of storage were of cassava plants with the aid of flexible measuring tape in 

centimeter at the middle portion of the storage root. Fresh storage root yield per plant was 

weighed with the aid of top load weighing balance in kilograms and converted the yield in 

tonnes per hectare.  

Data Analysis  

Data of all growth characters and yield components were subjected to analysis of variance 

with aid of sensate significant means were compared using the least significant difference at 

5% probability level.   

 

RESULTS AND DISCUSSION 

The physicochemical properties of the soil obtained from the experimental site are shown in 

Table 1. The result showed that the soil was slightly acidic with low cation exchange capacity 

(CEC) and suffered from multi-nutrient deficiencies. The soil may be classified as sandy 

loam. For intensive cultivation of the soil, appropriate soil management techniques were 

adopted to improve the nutrient status and general soil conditions. The fertilizer (NPK 

15:15:15) was applied at two months after planting at the rate of 400kg/ha and all the cassava 

genotypes received equal treatments.  

The result of establishment percentage as influenced by cassava genotypes showed no 

significant differences (P0.05). All the cassava genotypes had higher establishment 

percentage and ranged between 95.00% in TMS 98/0581 to 100% recorded for the following 



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varieties; TMS 01/1412, TME 419 and Obubit Okpo in 2018/2019 cropping season and range 

of 99-100% in 2019/2020. Subsequent differences (P0.05) were observed following plant 

height among the cassava varieties in all the months under investigation (Table 3). TME 419 

variety was the tallest plant in all the sampled months; 95.40, 176.77 and 215.98 cm in 

2018/2019 while height of 101.20, 182.80 and 220.88 cm was recorded in 2019/2020 season, 

at 3.6 and 9 MAP respectively. TMS 98/0581 was the shortest variety in both cropping 

seasons; 51.08, 83.40 and 125.31cm in 2018/2019 whereas 53.92, 91.30 and 133.71cm were 

recorded in 2019/2020 cropping seasons. 

The result showed significant differences (P0.05) among the cassava varieties for number of 

leaves per plant in all the months under study (Table 4). TMS 01/1412 had highest number of 

leaves per plant; 98.25, 281.16 and 325.12 in 2018/2019. The following number of leaves per 

plant 101.22, 306.33 and 359.48 was recorded in 2019/2020 cropping season at 3.6 and 

9MAP, respectively. TME 419 had the least number of leaves per plant; 71.55, 139.08 and 

188.41 in 2018/2019 while 68.50, 143.92 and 200.60 leaves per plant was recorded in 

2019/2020 cropping season. Obubit Okpo which was the local variety had significant higher 

number of leaves compared to TME 419 and TMS 98/0571. Significant differences (P0.05) 

were observed among the cassava genotypes for leaf area (Table 5). Leaf area of all the 

cassava genotypes evaluated increased from 3 MAP to 6 MAP and started declined at 9 MAP 

to MAP. In all the cassava varieties evaluated, TMS 98/0581 had the largest leaf area for all 

the months under investigations, followed by TMS 01/1412 while TMS 98/0505 had the least 

leaf area in all the months under investigation. Number of cassava tubers per plants varied 

significantly (Table 6). The result showed that TMS 01/1412 produced significant highest 

number of storage roots per plants; 10.25 and 9.82 in 2018/2019 and 2019/2020 cropping 

years, followed by TMS 98/0581, with 8.50 and 8.75, respectively. TMS 30572 had lowest 

number of storage root plants 4.80 and 5.20 respectively. Length of tubers per plant differed 

significantly (P0.05) among the cassava varieties sampled. TMS 98/0581 had significant 

longest tubers, 45.60cm and 44.20m by TME 419 with 44.20 and 43.18cm. TMS 30577 

recorded the shortest storage root; 30.81 and 33.10 cm respectively. The result showed the 

circumference of tubers differed significantly among the cassava genotypes (P0.05). The 

largest tuber circumference was recorded for TMS 98/0581, 21.88cm and 22.30cm followed 

by 20.40cm and 22.18cm recorded in TME 419 in both cropping seasons. TMS 30572 had 

the least storage root circumference; 15.33 and 15.25cm in 2018/2019 and 2019/2020 

respectively.  



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Fresh tuber yield of cassava genotypes differed significantly (P0.05). The genotype TMS 

98/0581 recorded the highest fresh storage root yield of 39.25t/ha and 41.50t/ha followed by 

TME 419 with 38.60t/ha and 39.01t/ha while the lowest fresh storage root yield in all the 

cassava varieties recorded for TMS 30527 with yield of 25.15t/ha and 24.58t/ha in both 

years.  

 

Discussion  

The result showed that number of leaves and leaf are of cassava genotype different 

significantly (P0.05), cassava varieties that produced higher number of leaves at certain 

stages of growth. In this study, higher number of leaves seems to correlate with increase in 

photosynthetic in cassava. For example, the varieties TMS 98/0581, TMS 01/1412, TME 419 

with higher number of leaves per plant and leaf area also produced higher fresh storage root 

yield (t/ha), while TMS 30572 98/0505 and Obubit Okpo with lower number of leaves per 

plant produced lower fresh storage root yields (t/ha). Higher storage yield observed for some 

varieties showed that the plants had powerful source (leaves) and sink capacity roots. This 

observation agrees with the earlier report by IITA (1990) and El-stairway (2008) that number 

of leaves may influence crop yield. Similarly, leaf area increased as number of leaves also 

increased. Also number of leaf and leaf area decreased considerably under adverse 

environmental conditions such as the appearance of dry season. This was observed at 9MAP 

which agrees with the observation of Fermont (2009) that leaf area index increases as the 

number and size of individual leaves increased reaching a peak of 4 to 6 MAP. However, in 

this study an association could be established between leaf area and number of leaves per 

plants, and fresh tuber yields (t/ha) of cassava. This observation was in line with the report of 

Bassey and Harry (2013).  The varieties TMS 01/1412, TMS 98/0581 and TMS 419 with 

highest number of leaves and largest leaf areas also produced highest storage root yields. This 

result also agrees with Fermont (2009); Ikeh 2017 and IITA (1990) that tuber yields is 

determined by certain growth characteristics such as number of leaves, leaf area and plant 

habit.  

 

Table 1.  Soil physico-chemcial properties of the experimental site before planting 

Soil parameter 0-15 cm  Soil depth. 

pH 5.50 

Electric conductivity (ds/m) 0.035 

Organic matter (%) 1.58 



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Total nitrogen (%) 0.07 

Available p (mg/kg) 42.30 

Exchangeable bases (cmo1/kg)  

Ca 2.12 

Mg 1.08 

Na 0.06 

Exchangeable  2.20 

Acidity (cmol/kg)  

ECEC (Cmol/kg) 5.46 

Particle size analysis (%)  

Sand 86.50 

Clay 4.80 

Silt  8.70 

Soil textural class Loamy soil 

  

Table 2: Sprouting percentage of cassava varieties 

Cassava Varieties  2018/2019 2019/2020 

TMS 98/0505 98.00 100.00 

TIMS 98/0581 95.00 99.00 

TME 419 100.00 100.00 

TMS 30572 96.00 100.00 

TMS 01/1412 100.00 100.00 

Ohu Pam 100.00 100.00 

LSD (p<0.05) Ns Ns 

* Ns = Not significant  

 

Table 3: Cassava height as influenced by varieties 

 

Cassava varieties  

2018/2019 

Months after planting 

2019/2020 

Months after planting 

3 6 9 3 6 9 

TMS 98/0505 62.14 121.81 163.50 58.60 128.90 170.09 

TIMS 98/0581 51.08 83.40 125.31 53.92 91.30 133.71 

TME 419 95.40 176.77 215.98 101.20 182.80 220.88 

TMS 30572 60.19 102.50 138.80 65.11 118.16 145.12 

TMS 01/1412 70.33 152.61 193.25 71.06 169.44 201.82 

Ohu Pam 64.20 148.00 176.70 65.22 156.18 183.14 

LSD (p<0.05) 3.40 5.25 6.81 4.77 5.28 4.80 

 



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Table 4: Number of leaves per plant 

Cassava varieties  2018/2019 

Months after planting 

2019/2020 

Months after planting 

3 6 9 3 6 9 

TMS 98/0505 80.50 258.30 285.06 77.51 233.01 262.48 

TIMS 98/0581 78.60 208.36 202.40 92.18 199.43 216.75 

TME 419 71.55 129.08 188.41 68.50 143.92 200.60 

TMS 30572 52.13 192.30 215.22 59.20 201.40 227.73 

TMS 01/1412 98.25 281.16 325.12 101.22 306.33 359.48 

Ohu Pam 65.48 182.42 205.31 70.60 188.41 250.19 

LSD (p<0.05) 2.87 5.57 9.25 2.92 4.22 6.62 

 

Table 5: Leaf Area of Cassava as Influenced by Varieties 

 

Cassava varieties  

2018/2019 

Months after planting 

2019/2020 

Months after planting 

3 6 9 3 6 9 

TMS 98/0505 120.40 130.22 125.60 125.39 137.44 135.22 

TIMS 98/0581 185.20 198.39 191.16 192.50 201.20 201.01 

TME 419 180.41 193.09 188.20 185.21 198.25 190.41 

TMS 30572 116.50 119.28 110.88 108.99 120.82 112.30 

TMS 01/1412 178.33 180.70 180.20 172.66 193.49 190.00 

Ohu Pam 129.81 142.24 140.01 133.80 158.08 151.26 

LSD (p<0.05) 4.25 5.29 3.33 2.71 5.75 5.39 

 

Table 6: Yield and yield Components of cassava as Influenced by Varieties 

 

 

 

 

Cassava 

varieties  

2018/2019 2019/2020 

Number 

of storage 

root/ plant 

Storag

e root 

length 

(cm) 

Circumfer

ence of 

storage 

root 

Storag

e root 

yield 

(t/ha) 

Number  

of  

storage  

root/ 

plant  

Storage 

root 

length 

(cm) 

Circumfere

nce of 

storage 

root 

Storage 

root yield 

(t/ha) 

TMS 98/0505 6.22 31.60 16.71 3250 6.01 33.11 15.80 29.60 

TIMS 98/0581 8.50 45.60 21.88 39.25 8.76 44.20 22.30 41.50 

TME 419 7.20 44.20 20.40 38.60 8.50 43.18 22.18 39.01 

TMS 30572 4.80 30.81 15.33 25.15 5.20 33.10 15.25 24.58 

TMS 01/1412 10.25 38.29 20.11 35.50 9.82 40.61 21.09 37.52 

Ohu Pam 7.55 36.95 18.55 33.09 6.31 35.20 17.88 32.55 

LSD (p<0.05) 2.58 3.18 2.88 3.48 2.16 2.27 2.40 3.91 



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CONCLUSION 

Based on the result findings, the following conclusions were drawn: The TMS 01/1412, TMS 

98/0581, and TME 419 which produced the highest storage root yields above the local variety 

(Obubit Okpo) could be disseminated to local farmers in Uyo.  Also Obubit Okpo which 

produced higher number of storage roots, be longer tubers and larger storage circumference 

when compares to TMS 98/0505, and TMS 30572 could be incorporated into breeding 

programmes involving the high yielding types (TMS 01/1412, TMS 98/0581, TME 419) to 

produce high yielding varieties for the area.  

 

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