




































 Agricultural Science; Vol. 2, No. 1; 2020 
ISSN 2690-5396   E-ISSN 2690-4799 

https://doi.org/10.30560/as.v2n1p289 

289                             Published by IDEAS SPREAD 
 

Genetic Variability and Characters Association of Hot Pepper 
(Capsicum annuum L.) Genotypes Tested under Irrigation in Northern 

Ethiopia 
Fasikaw Belay1, Berhanu Abate2 & Yemane Tsehaye3 

1 Horticulture Department, Axum Agricultural Research Center, Axum, Ethiopia 
2 Hawassa University, School of Plant and Horticultural Sciences, Hawassa, Ethiopia 
3 Department of Crop and Horticultural Science, Mekelle University, Mekelle, Ethiopia 
Correspondence: Fasikaw Belay, Horticulture Department, Axum Agricultural Research Center, P.O. Box 230, 
Axum, Ethiopia. E-mail: fasikawbelay79@gmail.com 
 
Received: May 20, 2020   Accepted: June 9, 2020   Online Published: June 17, 2020 
 
Abstract 
Hot pepper production in most areas of Ethiopia especially in Tigray region is constrained by shortage of varieties, 
the prevalence of fungal and bacterial as well as viral diseases. Sixty-four hot pepper genotypes were evaluated to 
obtain the extent of genetic variability, association among characters. The experiment was laid out using 8x8 
simple lattice design at Axum Agricultural Research center in 2017/18. Data were collected for 19 agronomic 
characters and analysis of variance revealed significant differences (p<0.01) among the genotypes for all characters. 
Fruit yield ranged from 0.8 to 4.5 t ha-1 with a mean of 2.7 t ha-1. The genotypic coefficient of variation (GCV) 
and phenotypic coefficient of variation (PCV) ranged from 3.57and 3.84 for days to maturity to 42.4 and 42.9% 
for average single fruit weight. All the traits had moderate to very high broad sense heritability while genetic 
advance as percent of mean (GAM) ranged from 8.34 for days to maturity to 85% for average single fruit weigh. 
High heritability coupled with high GAM was obtained for average single fruit weight, fruit length, dry fruit yield 
per plant, fruit diameter and thousand seed weight reflecting the presence of additive gene action for the expression 
of these traits and improvement of these characters could be done through selection. Fruit yield per hectare had 
positive and highly significant phenotypic and genotypic correlations with dry fruit yield per plant, average single 
fruit weight, fruit pericarp thickness, thousand seed weight, fruit diameter and fruit length, but it had negative and 
highly significant genotypic and phenotypic correlations with days to maturity. Estimates of genotypic and 
phenotypic direct and indirect effects of various characters on fruit yield showed that dry fruit yield per plant, fruit 
pericarp thickness had the highest positive direct contribution to fruit yield indicating that selection based on these 
characters will improve fruit yield. In conclusion, the research results showed the presence of significant variations 
among genotypes for agro-morphology traits. Therefore, it is recommended further evaluation of genotypes or 
hybrids that exhibited highest yield, quality and disease resistance in subsequent breeding programs to improve 
the productivity of the crop. 
Keywords: vegetable crop, genetic correlation, additive gene, direct effect, genetic advance, heritability   
1. Introduction 
The genus Capsicum belongs to the family Solanaceace and it includes 30 species, including five domesticated 
and commercially cultivated species (C. annuum L., C. baccatum L., C. chinensis Jacq., C. frutescence L. and C. 
pubescence ) (Dagnoko et al., 2013). However, from the five-domesticated species of the genus C. annuum L. is 
the most widely cultivated species worldwide (Pickersgill, 1997).  It is the world’s most important vegetable after 
tomato and used as fresh, dried or processed products, as vegetables and spices or condiments (Berhanu et al., 
2011). Nutritionally, hot pepper like any other Capsicum species is rich in vitamin A and C, calcium, phosphorus 
and potassium. It has been reported that peppers are highly appreciated for their spicy flavor and nutritional value. 
Currently, it is produced in many parts of the country, because food is tasteless without hot pepper for most 
Ethiopians. The crop is also one of the important vegetables that serve as the source of income particularly for 
smallholder producers in many parts of rural Ethiopia (Berhanu et al., 2011; Shimeles, 2018).  Moreover, hot 
pepper contributes 40 - 60% to the household income (Shimeles, 2018). 



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According to CSA (2017) the national average yields of hot pepper are 6.3 t ha-1 for green pod and 1.8 t ha-1 for 
the dry pod, which is far below the dry pod yield (2.5-3.7 t ha-1) of improved varieties harvested at research fields 
of Ethiopia (MoANR, 2016) and world average yield of 3 - 4 t ha-1 (FAO, 2015). The productivity of the crop is 
low due to many limiting factors such as shortage of adapted high yielding varieties, using unknown seed sources 
and poor-quality seeds, poor irrigation system, lack of information on soil fertility, the prevalence of fungal and 
bacterial as well as viral diseases, lack of awareness on existing improved technologies and poor marketing system. 
In the past decades, diverse pepper genotypes (>300) were introduced from different regions of the world (Fekadu 
et al., 2008) adding to the diversity of the crop in Ethiopia. However, Ethiopia has less benefited from research 
activities although some research centers are working on hot pepper variety development, which mainly focused 
on adaptation and release of locally adapted varieties. For efficient and effective breeding work investigation and 
better understanding of the variability of existing genotypes is essential. Very few studies have been conducted on 
hot pepper genetic variability using morphological traits (Berhanu et al., 2011; Shimeles et al., 2016; Abrham et 
al., 2017 and Birhanu, 2017). 
Effectiveness of selection depends on the amount of variability, heritability and genetic advance, interrelations 
among themselves and genetic divergence present in the genetic material for yield and yield related characters. 
Hence, developing of varieties with the desired traits has a significant contribution to increase the yield of hot 
pepper in the region. Therefore, the first step in the development of varieties is assessing the genetic variability of 
available genotypes for the characters of interest. Similarly, information on the extent and nature of 
interrelationship among plant characters’ help formulating efficient index selection and the relative contribution 
of various components traits to yield (Singh, 1993). Besides, knowledge of the naturally occurring diversity in a 
population helps identify diverse groups of genotypes that can be useful for the breeding program. Greater the 
variability in a population, greater the chance for an effective selection of desirable types (Vavilov, 1951). 
Therefore, assessment of variability, association and heritability of traits in hot pepper genotypes in case of Central 
zone of Tigray agro-ecology is essential for planning an appropriate breeding strategy for genetic improvement of 
the crop. Hence, the present study was undertaken with the objectives to estimate phenotypic and genotypic 
variations, heritability and expected genetic advance of agronomically important traits in the hot pepper genotypes, 
to assess the extent of associations among yield and yield related traits and to identify the most yield predicting 
traits. 
2. Materials and Methods 
Experimental Site: The study was conducted under irrigation at Axum Agricultural Research Center (AxARC) 
experimental field, Mereb Lekhe District, in the central zone of Tigray, northern Ethiopia during 2017/18 cropping 
season. The site is located at about 1041 kms away from Addis Ababa and 67 km to the north of Aksum town, at 
14o 25’26” and 14o18’48” N latitude, and 38o 42’15” and 38o48’30” E longitude with an altitude of 1390 m.a.s.l. 
(Figure 1). The site is found in semi-arid tropical belt of Ethiopia with “kola” agro climatic zone and the rainy 
season is mono - modal concentrated in one season from late July to early September and receives from 400 - 600 
mm of rain fall per annum. The mean minimum and maximum temperatures ranged from 13.3 0C to 33.7 0C, 
respectively. The soil texture of the specific site of the study area is sandy clay loam textural class with bulk density 
of 1.7 g cm-3, very low in organic carbon (0.7%) with an alkaline pH of 8.2.   

 



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Figure 1. Geographical location of the study area showing Ethiopia, Tigray region, Mereb Leke District and 

specific location of the experimental site 
 
Experimental Materials: Sixty-three local hot pepper Ethiopian landraces along with one released variety Mareko 
fana as a check were used in this study. The landraces were collected from different agro-ecologies of varying 
altitude, rainfall, temperature, and soil type by the Ethiopian Biodiversity Institute (EBI), Shire Maitsebri 
Agricultural Research Center (SMARC) and Melkassa Agricultural Research Center (MARC). The accession 
numbers and source of the genotypes are shown in Table 1. 
Experimental Design: The experiment was laid out in 8x8 simple lattice design with two replications. The 
experimental materials were planted at Axum Agricultural Research Center main research site during 2017/2018 
cropping season under irrigation. Seeds of each hot pepper genotypes were sown in seed bed of 0.6 m2 (3 rows, 
0.2 m spacing between rows, 1m row length) during October 2017 to raise seedlings. Seedlings were transplanted 
to main field 48 days after seed sowing i.e. when the seedlings attained 15 cm height. Each genotype was planted 
in the main field in a plot size of 8.4m2 (2.8 m x 3 m). Each plot consisted of four rows of 3m length with inter 
and intra-row spacing of 0.7m and 0.3m, respectively, containing a total of 40 plants. Each incomplete block and 
replication was spaced 1 and 1.5 meters, respectively. The middle two rows were used for data collection leaving 
the two rows as borders. Fertilizer, Di-ammonium phosphate (DAP) as a source of Phosphorus was applied at the 
rate of 200 kg ha-1 during planting and nitrogen fertilizer was applied in the form of Urea at the rate of 150 kg ha-
1 in splits, half during transplanting and the rest as side dressing at 45 days after transplanting. Watering was made 
following furrow irrigation at 7days interval (AxARC, 2016) was used. Weeding, hoeing and other field 
management and crop protection activities were done as required. 
 
Table 1. Hot pepper accessions tested under furrow irrigation in northern Ethiopia, their local name, area of 
collection, origin and sources 

NO. Accession 
Name 

Local Name  
 

Site of 
Collection 

Sources NO. Accession 
Name 

Local Name  
 

Site of 
collection 

Sources 

1 Acc-1 Berebere Hormat Raya Kobo Amhara 33 Acc-
229701 

Hulet Ejenese Misrak 
Gojam 

Amhara 

2 Acc-2 Berbere 
Aberegelle 

Tanqua 
Abergelle 

Tigray 34 Acc-
237528 

Enticho Ahferom Tigray 

3 Acc-3 Berebere 
Birisheleko 

Bure Amhara 35 Acc-9102 Achefer Mirab 
Gojam 

Amhara 

4 Acc-4 Felege Da’ero Mekelle Tigray 36 Acc-9094 Gooda Mirab 
Gojam 

Amhara 

5 Acc-5 Berebere Agew Ofla(Zata) Tigray 37 Acc-9098 Achefer Mirab 
Gojam 

Amhara 



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6 Acc-6 Berebere Dibdibo Ahferom Tigray 38 Acc-9104 Merwi Mirab 
Gojam 

Amhara 

7 Acc-7 Shamba 
berbereAdi 

Welkait Tigray 39 Acc-9099 Amestya Mirab 
Gojam 

Amhara 

8 Acc-8 Berebere korir Kilte 
Awulalo 

Tigray 40 Acc-9082 Meacha Mirab 
Gojam 

Amhara 

9 Acc-9 Berebere Tsalaiet  Kola 
Temben 

Tigray 41 Acc-9101 Achefer Mirab 
Gojam 

Amhara 

10 Acc-10 Berebere Agbe Abergelle Tigray 42 Acc-9086 Kudmie Mirab 
Gojam 

Amhara 

11 Acc-11 Laelay Dayu Alamata Tigray 43 Acc-
229696 

Dibata Metekel B/Gumz 

12 Acc-12 Berebere Hewane Walkait Tigray 44 Acc-9106 Bure 
Wemberma 

Mirab 
Gojam 

Amhara 

13 Acc-13 Abat Berebere Walkait Tigray 45 Acc-9007 Galioch Buare 
town 

Mirab 
Gojam 

Amhara 

14 Acc-14 Bora(Gemelo) Embalaje Tigray 46 Acc-9107 Guzamn Misrak 
Gojam 

Amhara 

15 Acc-15 Abat Berebere Welkait Tigray 47 Acc-28334 Abdigudina Illubabor Oromiya
16 Acc-16 Berbere Rama Mereb Leke Tigray 48 Acc-48 Berbere Alaba Alaba SNNPRS
17 Acc-28336 Durame Illubabor Oromiya 49 Acc-49 Tedele Guragae SNNPRS
18 Acc-

230800 
Bedeno Misrak 

Harerge 
Oromiya 50 Acc-

229694 
Mentawuha Metekel B/Gumz 

19 Acc-28337 Elammo  Illubabor Oromiya 51 Acc-51 Abeshigie Guragie SNNPRS
20 Acc-

229699 
Adet Misrak 

Gojam 
Amhara 52 Acc-52 Wegedadi Mirab 

Gojam 
Amhara 

21 Acc-
212912 

Kedida Gameala Kembata 
Alaba 

SNNPRS 53 Acc-9093 Solmeda Mirab 
Gojam 

Amhara 

22 Acc-9097 Achefer/Durbate Mirab 
Gojam 

Amhara 54 Acc-
229692 

Dinkara Agew Awi Amhara 

23 Acc-9084 Merawi Mirab 
Gojam 

Amhara 55 Acc-55 Debremarkos Misrak 
Gojam 

Amhara 

24 Acc-
229697 

Wonbera Metekel B/Gumz 56 Acc-56 Finote Selam Mirab 
Gojam 

Amhara 

25 Acc-
212913 

Humbo Semen 
Omo 

SNNPRS 57 Acc-57 Guragie 
Berebere 

Butajira SNNPRS

26 Acc-
229700 

Bibugn (Astero 
M.) 

Misrak 
Gojam 

Amhara 58 Acc-58 Berebere Merb Mereb 
Leke 

Tigray 

27 Acc-9085 Merawi Mirab 
Gojam 

Amhara 59 Acc-59 Adiha Local Abi Adi Tigray 

28 Acc-
230798 

Dogo Midi Jara Misrake 
Harerge 

Oromiya 60 Acc-23880 Meskele 
Kirstos 

Semien 
Gonder 

Amhara 

29 Acc-
230799 

Girawa Misrake 
Harerge 

Oromiya 61 Acc-61 Myweni Mereb 
Leke 

Tigray 

30 Acc-
236436 

Bako Tibe Mirab 
Shewa 

Oromiya 62 Acc-62 Berebere Hesea Mereb 
Leke 

Tigray 

31 Acc-
229698 

Dibate Metekel B/Gumz 63 Acc-63 Yeyeju 
Bereberie 

Woldia  Amhara 

32 Acc-
229698 

Dibate Metekel B/Gumz 64 Acc-64 Mareko fana 
(St. check) 

Melkassa Oromiya

SNNPRS = Southern Nation, Nationalities and People’s Regional State, B/Gumz = Benishangul-Gumz Regional State, Acc = accession 
 
Data collected: Seventeen quantitative characters were recorded on five randomly selected plants from the two 
middle rows of each plot by adopting descriptors list for hot pepper (IPGRI, 1995). 
Data Analysis: Data for quantitative characters were subjected to analysis of variances (ANOVA) for simple 
lattice design following procedures of SAS Version 9.2(SAS Institute Inc., 2010) to test the presence of significant 
differences among genotypes. Mean separations were estimated using Duncan Multiple Range Test (DMRT) at 5% 
probability levels.   
Variability among accessions was estimated using genotypic variances and coefficients of variations as suggested 
by Burton and De vane (1953) as: Genotypic Variance (σ2g) =   

Phenotypic variance (σ2p) = [σ2g + (σ2e/r)], Phenotypic coefficient of variation (PCV) = 𝒙 ∗ 100 , Genotypic 

coefficient of variation (GCV) =   𝒙 ∗ 100, Where, r = number of replication; MSg = mean square due to 



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genotypes and Mse = mean square of error, σ2p = phenotypic variance, σ2g = genotypic variance and �̅� = grand 
mean of the character under consideration. Both phenotypic coefficients of variation (PCV) and genotypic 
coefficients of variation (GCV) was categorized depending up on cut points suggested by Deshmukh et al. (1986) 
as low (<10%), moderate (10-20%) and high (>20%). 
Broad sense heritability (h2) of the all traits were calculated according to the formula as described by Allard (1960) 
as follow:  

h2
bs= [(σ2G) / (σ2P)] × 100, 

Where: h2
bs= heritability in broad sense; σ2G = Genotypic variance; σ2P = Phenotypic variance. According to Singh 

(2001) that heritability values ≥80% were very high, values from 60-79% were moderately high, values from 40-
59% were medium and values less than 40% were low. 
Genetic Advance (GA) for selection intensity (K) at 5%was computed according to Allard (1960) as given here:  

GA = K*σp*H2 
Where, GA = expected genetic advance, K = the standardized selection differential at 5% selection intensity (K = 
2.063), σp = is phenotypic standard deviation on mean basis and H2 = heritability in the broad sense. The genetic 
advance as percentage of population means (GAM) was also estimated with the methods described by Johnson et 
al. (1955). Genetic advance as % of mean (GAM) was computed as: GAM = ̅   ∗ 100 
Where, GA = Genetic advance under selection and �̅� = mean of the population. According to Johson et al. (1955) 
genetic advance as percent of mean was classified as low (<10%), moderate (10-20%) and high (>20%). 
Characters associations at genotypic and phenotypic levels were calculated from the genotypic and phenotypic and 
environmental covariance according to Singh and Chaundhary (1985). In Path analysis, total yield per hectare was 
taken as the resultant (dependent) variable while the rest of the characters were considered as casual (independent) 
variables. The direct and indirect effects of the independent characters on fruit yield per hectare were estimated by 
the simultaneous solution of the formula suggested by Dewey and Lu (1959). 
3. Results and Discussion 
Analysis of Variance (ANOVA) 
There were highly significant differences (P<0.01) among the tested genotypes for all characters studied indicating 
presence of adequate variability among genotypes (Table 2). This significant genetic variation among genotypes 
suggested that the genotypes were genetically diverse and it could be a good opportunity for breeders to select 
genotypes for trait of interest for variety development. This finding was in agreement with the findings of Berhanu 
et al. (2011), Nsabiyera et al. (2013), Birhanu (2017) and Shimeles (2018). 
Mean Performance of Genotypes: Genotypes had 57.5 to 76.5 days to flowering, 67.5 to 84.5 days to fruiting 
and 113.5 to133 days to maturity with a mean of 62.27, 75.78 and 122.6 days, respectively. The result showed a 
wide range of variations for days to flowering, fruiting and maturity. Similarly, Shimeles (2018) and Berhanu et 
al. (2011) reported the existence of wide genetic variation for those phenological characters on 49 and 20 hot 
pepper genotypes respectively. Acc-1 (113.5 days), Acc-49 (114.5 days) and Acc-57 (114 days) had significantly 
shorter days to maturity while Acc-5 (133 days), Acc-9 (130.5days) and Acc-59 (130.5days) had significantly 
delayed maturity. About 54.7% of the genotypes exhibited shorter number of days to maturity than the genotypes 
mean (122.6). Moreover, 25 genotypes were significantly earlier in maturity than the check variety (Mareko fana) 
that had the earliest days to maturity (Appendix Table 1). Most of the genotypes have also yield advantage over 
the early maturing check variety. Hence, there is an opportunity to select early maturing and high yielder genotypes 
better than the check variety (Mareko fana). 
The magnitude of genetic variability for plant height ranged from 37.1 (Acc-9097) to 66.5 cm (Acc-3) with average 
value of 53.29 cm. Genotypes codded as Acc-63, Acc-9007, Acc-8, Acc-212912, Acc-1, Acc-9, Acc-59, Acc-5 
and Acc-9102 had tall plant stature (59.4 - 65 cm), so can be used as parents in developing varieties with maximum 
plant height, as it may contribute to fruit yield.  
The minimum and maximum canopy diameter was exhibited by genotypes Acc-229697 and Acc-59, respectively. 
Genotypes Acc-59, Acc-15 and Acc-9101 have also yield advantage and can be used as parents in developing 
varieties with high canopy diameter over the check variety. However, Shimeles (2018) reported a wide range of 
40.9 - 76.6 cm for canopy diameter.  This wide range of variability may be attributed to differences in the materials 
test and /or may be due to the differences of in the testing environments. 
The fruit pericarp thickness of genotypes also ranged from 1.7 to 2.7 mm with an overall mean of 2.1 mm. The 
genotypes Acc-212912, Acc-212913, Acc-230798, Acc-236436, Acc-229698, Acc-16, Acc-11, Acc-48, and Acc-



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51 had thicker pericarp than the check variety. The highest fruit pericarp thickness was Acc-212912 (2.7 mm) 
which indicated that Acc-212912 should be given consideration for selection designed for the improvement of this 
trait. This is in agreement with the finding of Nsabiyera et al. (2013) and Shimeles (2018) who reported a wide 
range of variation for fruit pedicel length, fruit length and fruit diameter. Average single fruit weight varied from 
1.55 to 7.1 gm with a mean of 3.6 g. Acc-49, Acc-212912, Acc-61, Acc-1, Acc-11, Acc-212913 and Acc-229694 
depicted highest fruit weight per plant comparing to the check variety in that order.    
The genotypes exhibited significant variability in fruit number per plant which ranged from 14.75 to 55.5 with a 
mean of 31. The lowest number of fruits per plant was depicted by genotypes Acc-57, Acc-56, Acc-229698 and 
Acc-49, whereas the highest number of fruits per plant by genotypes Acc-5, Acc-2, Acc-59, Acc-229700, Acc-
212913, Acc-8 and Acc-229697. On the other hand, number of seeds per fruit ranged between 93 and 231 with a 
mean value of 139.1. The lowest number of seeds per fruit was counted for Acc-229697 and Acc-14, whereas the 
highest seeds per fruit for Acc-212912, Acc-3, Acc-48 and Acc-4 respectively. Accordingly, in the current study 
42 genotypes scored greater than 65% number of fruits per plant and 33 genotypes scored greater than 51% number 
of seeds per fruit as compared with the best performing check variety (Mareko fana) (Table 5). Similar results for 
number fruits per plant were reported by kadwey et al. (2015), Birhanu (2017), Kumari (2017) and Shimeles (2018).  
A wide range of variation was observed for 1000 seed weight among genotypes which ranged from 4 to 7.2g with 
a mean of 5.6g. Genotypes Acc-212913, Acc-58, Acc-229694, Acc-212912 and Acc-11 had high seed weight of 
7.2, 6.9, 6.9, 6.8 and 6.6 g while Acc-9085, Acc-9101, Acc-9099 and Acc-9086 had low 1000 seed weight of 4g 
each as compared to the check variety.  
Average dry fruit yield per plant ranged from 54 to 172.5g with an overall mean of 107.3g. The highest yield per 
plant was recorded from Acc-212913 (172.5g) and Acc-4 (168g) while Acc-13 (54.5 g), Acc-237528 (56 g) and 
Acc-9102 (64 g) produced lowest yield per plant as compared to the check variety. Similar results for dry fruit 
yield per plant were reported by kadwey et al. (2015), Rosmaina et al. (2016) and Shimeles (2018). 
 
Table 2. Mean squares of variance for 19 characters of 64 hot pepper genotypes evaluated at Mereb Lekhe in, 
2017/18 

Mean squares 
    Error    
Characters  

Replication(1) 
 
Treatments 
Adji (63) 

Blocks 
with  
in 
replication
(Adj)(14) 

Intra 
Block(49)

RCBD(63)  
R2 (%) 

 RE to  
RCBD 
(%) 

 
CV 
(%) 

DFL  8.508 27.51** 13.936 6.528 8.175 86.9 112.1 3.8 
DFR  0.008 30.17** 8.820 6.347 6.897 87.2 102.3 3.3 
DM  3.445 44.26** 6.222 5.856 5.937 91.2 100.1 2.0 
PH  526.500 62.76** 15.390 17.487 17.021 84.7 97.3 7.8 
CD  7.703 14.69** 3.318 3.550 3.499 86.9 98.6 5.0 
NPB 0.797 13.45** 1.100 1.117 1.113 94.6 99.7 15.0 
SD 1.144 3.37** 1.241 0.963 1.025 84.0 101.4 7.7 
FPL  0.054 0.79** 0.119 0.074 0.084 94.3 104.7 7.8 
FL  0.002 22.28** 0.426 0.407 0.411 98.7 100.0 7.8 
FD  1.533 49.14** 2.355 1.638 1.797 97.7 102.8 7.1 
FPT  0.918 0.13** 0.026 0.029 0.028 87.9 97.3 8.3 
FW  0.463 4.82** 0.144 0.187 0.177 97.3 95.0 11.9 
NFP 2.820 294.20** 8.135 4.555 5.351 98.9 107.0 6.9 
NSF 17.331 1453.86** 80.555 18.524 32.309 99.1 148.9 3.1 
TSW  0.538 1.50** 0.213 0.189 0.194 91.8 100.3 7.8 
DFYP 12.500 1741.51** 37.670 20.676 24.452 99.2 107.5 4.2 
MFY  1.304 0.81** 0.069 0.131 0.117 90.5 89.6 14.6 
UNMFY 0.008 0.01** 0.001 0.001 0.001 92.1 91.4 19.7 
TFY  1.533 0.82** 0.065 0.135 0.120 90.5 88.5 13.8 

*and** = significant at 5% and 1% probability level, respectively. Number in parenthesis represented degree of 
freedom adj =  adjusted treatment mean squares, RCBD = Randomized completed block design, RE to RCBD = 



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Relative efficiency to randomized completed block design CV = coefficient of variation, R2 (%) = coefficient of 
determination, DFL = days to 50% flowering, DFR = days to 50% fruiting, DM = days to maturity, PH = Plant 
height (cm), CD = canopy diameter (cm), number of primary branches per plant, SD = stem diameter (mm), FPL 
= fruit pedicel length (cm), FL = fruit length (cm), FD = fruit diameter (mm), FPT = fruit pericarp thickness (mm), 
FW = average single fruit weight (g), NFP = number of fruits per plant, NSF = number of seeds per fruit, TSW = 
thousand seed weight(g), DFYP = dry fruit yield per plant (g), MFY = marketable fruit yield (t ha-1), UNMFY = 
Unmarketable fruit yield (t ha-1) and TFY = total fruit yield (t ha-1). 
Marketable fruit yield per hectare ranged from 0.7- 4.3 t with an overall mean of 2.5 t ha-1. The highest marketable 
fruit yield per hectare was recorded for Acc-4, Acc-212913, Acc-212912, Acc-1, Acc-49, and Acc-50 while Acc-
9102, Acc-52, Acc-9099, Acc-9098, Acc-230798 and Acc-230799 gave the lowest yield as compared to the check 
variety (Appendix Table 2). Hence, there is an opportunity to select high yielding genotypes better than the check 
variety. Total fruit yield per hectare ranged from 0.83 to 4.6 t ha-1 which showed wide variation with a mean value 
of 2.7 t ha-1. The maximum yield was obtained from Acc-4 (4.6 t ha-1) followed by Acc-212912 (4.5 t ha-1), Acc-
212913 (4.3 t ha-1) and Acc-3 (4.3 t ha-1) (Appendix Table 2). Nearly, 43.8 % of the tested genotypes had fruit 
yields above the grand mean of genotypes. As compared with the best performing check variety (Mareko fana), 
54.6% of the genotypes had yield advantages. Most of these high yielding genotypes were also earlier in maturity 
than the check variety (Appendix Table 2). This wide range of variability of genotypes for most traits in the study 
indicated the high possibility for genetic improvement of traits under consideration.  
Phenotypic and Genotypic Variations: For all characters studied, the magnitude of environmental variance was 
lower than the corresponding genotypic variance (Table 3). This indicates that the genotypic component of 
variation was the major contributor to the total variation in the studied characters. Genetic variance ranged from 
0.05 for fruit pericarp thickness to 860.42 for dry fruit yield per plant while phenotypic variance values ranged 
from 0.07 to 870.76 for fruit pericarp thickness. The GCV ranged from 3.6% for days to maturity to 42% for 
average fruit weight. Similarly, PCV ranges from 3.8% for days to maturity to 42.9% for average fruit weight per 
plant. In general, the phenotypic coefficient of variation (PCV) was relatively higher than the corresponding 
genotypic coefficient of variation (GCV). The difference between PCV and GCV was narrow indicating little 
influence of environment on the expression of these characters and considerable amount of variation was observed 
for all the characters. The GCV and PCV values are normally categorized as low (<10%), moderate (10-20%) and 
high (>20%) as indicated by Deshmukh et al. (1986). High values of PCV and GCV indicated the existence of 
substantial variability for such characters and selection may be effective based on these characters.  
Average fruit weight had the highest GCV and PCV (42and 42.9%) followed by fruit length (40.3 and 40.7%), 
number of fruits per plant (38.9 and 39.2%), number of primary branches per plant (35.2% and 36.7%), dry fruit 
yield per plant (27.3 and 38.9%), fruit diameter (24.6 and 27.5%), total fruit yield (22 and 24.1%), number of fruits 
per plant (38.9 and 39.2%). Medium GCV and high PCV were observed for fruit pericarp thickness (11 and 12.4%), 
fruit pedicel length (17.2 and 18.1%), number of seeds per fruit (19.3 and 19.4%) and thousand seed weight (14.5 
and 15.6%). GCV and PCV were low for days to 50% flowering (7.3 and 7.8), days to 50% fruiting (6.9 and 7.3%) 
and days to maturity (5.2 and 5.4%), plant height (8.9 and 10.5%) and canopy diameter (6.3 and 7.2%). Similarly, 
Pujar et al. (2017) reported a relatively low GCV and PCV for days to flowering in 63 chilli genotypes. The high 
PCV and GCV are evident for the high variability that in turn offers good scope for selection.  
Similar finding was reported by Berhanu et al. (2011) indicating that days to flowering and days to maturity had 
low GCV and PCV values, while fruit weight, number fruits per plant, number of primary branches per plant had 
high GCV and PCV. Datta and Das (2013) reported high GCV and PCV with high heritability and GAM for fruit 
number per plant and fruit yield per plant.  Razzaq et al. (2016) reported high values of GCV and PCV for weight 
of red fruit (110 and 112%) and number of fruits per plant (85 and 86%). Shimeles et al. (2016) also reported high 
estimates of GCV and PCV for fruit weight, number of branches per plant and number of fruits per plant. In 
addition, similar findings were also reported by (Sharma et al., 2010; Janaki et al., 2015; Rosmaina et al., 2016; 
Sahu et al., 2016). 
Estimates of Heritability (h2) in broad Sense: In this study all the traits had moderate high to very high broad 
sense heritability in the range of 71.4 to 98.8% (Table 3) indicating that the traits studied were more influenced by 
genetic factors (Rosmaina et al., 2016). According to Singh (2001) heritability values greater than 80% considered 
as a very high, values from 60-79% as moderately high, values from 40-59% as medium and values less than 40% 
as low. Accordingly, the estimates of heritability of all traits in the current study were moderate to very high. The 
characters having very high heritability indicated relatively small contribution of the environmental factors to the 
phenotype and selection for such characters could be fairly easy due to high additive effect. 



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Heritability alone provides no indication of the amount of genetic improvement that would result from selection 
of individual genotype. Hence, knowledge on heritability coupled with genetic advance is more useful. Genetic 
advance as percent of the mean (GAM) in this study ranged from 6.9% to 85% for days to maturity and average 
single fruit weight respectively (Table 6). According to Jonhson et al. (1955) the value of GAM is categorized as 
low (< 10%), moderate (10-20%) and high (> 20%). The highest GAM was recorded for average single fruit weight 
(85%), followed by fruit length (82.4%), number of fruits per plant (79.5%) and number of primary branches per 
plant (69.5%) indicating that these characters are governed by additive genes and selection will be rewarding for 
improvement of hot pepper for these traits. The least GAM was recorded for days to maturity (6.9 %), days to 50% 
fruiting (8.4%) and days to 50% flowering (8.7%). In the current result, moderately high heritability coupled with 
moderate GAM was observed for plant height (15.6%), canopy diameter (11.3%), stem diameter (15.1%) and fruit 
pericarp thickness (19.9%). These results agreed with the findings of earlier researchers (Janaki et al., 2015; 
Rosmaina et al., 2016; Birhanu, 2017; Kumari, 2017) who found high genetic advance as percent of mean for 
number of fruits per plant, average fruit weight, and number of primary branches per plant. Shimeles et al. (2016) 
also obtained high genetic advance as percent of mean for number of branches per plant. Similar findings were 
reported by earlier workers for some characters with moderate to high GCV, PCV, heritability and GAM estimates, 
for fruit yield per plant, fruit diameter, fruit length, average fruit weight, number of seeds per fruit and number of 
fruits per plant (Sharma et al., 2010; Sahu et al., 2016; Razzaq et al., 2016; Pujar et al., 2017). 
Generally, for characters like dry fruits yield per plant, number of fruits per plant, number of seeds per fruit, 
average single fruit weight, fruit diameter, fruit length and thousand seed weight with high GCV, heritability and 
GAM should be considered as reliable selection criteria for crop improvement in terms of yield and its components 
in hot pepper.  
Association of Characters: In most cases, the genotypic correlation coefficients were higher than the phenotypic 
correlation coefficient which indicates that the inherent association among various characters independent of 
environmental influence (Table 4). Total fruit yield per hectare showed positive and highly significant (P<0.01) 
genotypic and phenotypic correlations with dry fruit yield per plant (rg = 0.75 and rp = 0.70), average single fruits 
weight (rg = 0.52 and rp = 0.49), thousand seed weight (rg = 0.47 and rp = 0.41), fruit pericarp thickness (rg = 0.44 
and rp = 0.42), number of seeds per fruit (rg = 0.42 and rp = 0.39) and fruit diameter (rg = 0.37 and rp = 0.33). Total 
fruit yield also exhibited positive and significant (P<0.05) genotypic and phenotypic correlations with canopy 
diameter, stem diameter and fruit length (Table 4). The results imply that improvement of the characters could 
improve capacity to synthesize and translocate photosynthesis to the organ of economic value. 
This suggested that, improvement of those characters would result in a substantial increment on fruit yield that 
could be used in selection of genotypes for high fruit yield. Similarly, Abrham et al. (2017) and Shimeles (2018) 
reported higher genotypic correlation coefficients than the phenotypic ones, implying the inherent associations 
between various characters in Ethiopian Capsicums.   
Dry fruit yield per plant   had a highly significant association at both genotypic and phenotypic level with average 
single fruit weight (rg = 0.50, rp = 0.56), number of seeds per fruit (rg = 0.46, rp = 0.45) and thousand seed weight 
(rg = 0.43, rp = 0.40). These results agreed with the findings of earlier researchers (Kadwey et al., 2015; 
Chakrabarty and Aminul , 2017; Kumari et.al, 2017) indicating genotypic and phenotypic correlations between 
plant height, number of primary branches per plant, fruit length, fruit diameter, fruit pericarp thickness, fruit yield 
per plant, average fruit weight, number of fruit per plant, number of seeds per fruit and thousand seed weight. 
 
Table 3. Estimates of Range, Mean, Genotypic, Environmental and Phenotypic variances and Coefficient of 
variations, Heritability in broad sense, Genetic advance and Genetic advance as percentage of mean for 17 
characters of 64 hot Pepper genotypes at Mereb Lekhe in, 2017/18 

Characters Ranges Mean ± SEM σ2g σ2e σ2p GCV (%) PCV (%) h2 (%) GA GAM (%)
DFL 57.5-75.9 67.3±1.8 10.5 6.53 13.76 4.8 5.5 76.3 5.84 8.7 
DFR 67.5-84.5 75.7±1.8 11.9 6.35 15.09 4.6 5.1 79.1 6.33 8.4 
DM 113.5-133 122.6±1.7 19.2 5.86 22.13 3.6 3.8 86.8 8.42 6.9 
PH 37.1-66.5 53.3±3 22.6 17.49 31.38 8.9 10.5 72.1 8.34 15.6 
CD 32.4-43.4 37.4±1.3 5.6 3.55 7.34 6.3 7.3 75.8 4.24 11.3 
NPB 3.4-11.8 7.1±0.8 6.2 1.12 6.72 35.2 36.7 91.7 4.9 69.5 
SD 9.8-16.1 12.7±0.7 1.2 0.96 1.68 8.6 10.2 71.4 1.91 15.1 
FPL 2.3-4.7 3.5±0.2 0.4 0.07 0.39 17.2 18.1 90.6 1.17 33.9 
FL 4-2.8 8.2±0.5 10.9 0.40 11.14 40.3 40.7 98.2 6.76 82.4 



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FD 11.21-31 18±0.9 23.7 1.64 24.57 27.0 27.5 96.7 9.89 54.8 
FPT 1.7-2.7 2.1±0.1 0.1 0.03 0.07 10.9 12.4 77.7 0.41 19.9 
DFYP 53.96-173.6 107.3±3.2 860.4 20.68 870.76 27.3 27.5 98.8 60.15 56.0 
FW 1.55-7.1 3.6±0.3 2.3 0.19 2.41 42.0 42.9 96.1 3.08 85.0 
NFP 14.3-55.7 30.9±1.5 144.8 4.56 147.1 38.9 39.7 98.5 24.63 79.5 
NSF 90.66-233.6 139.1±3.1 717.7 18.52 726.93 19.7 19.4 98.7 54.91 39.5 
TSW 4-7.2 5.56±0.3 0.7 0.19 0.75 14.5 15.6 87.4 1.56 28.1 
TFY 0.8-4.5 2.7±0.3 0.3 0.14 0.41 22.1 24.1 83.6 1.11 41.5 

DFL = days to 50% flowering, DFR = days to 50% fruiting, DM = days to maturity, PH = plant height, CD = 
canopy diameter , NPB = number of primary branches per plant, SD = stem diameter, FPL= fruit pedicel length , 
FL = fruit length , FD = fruit diameter, FPT = fruit pericarp thickness, DFYP = dry red fruit yield per plant, FW = 
average fruit weight, NFP = number of fruits per plant, NSF = number of seeds per fruit, TSW = thousand seed 
weight and TFY = total fruit yield, SEM = standard error of the mean, σ2g = genotypic variance, σ2e = error 
variance, σ2p = phenotypic variance, PCV = phenotypic coefficient of variance, GCV = genotypic coefficient of 
variance, h2 = broad sense heritability, GA = genetic advance, GAM = genetic advance as percent of mean.  
 
Genotypic path coefficient analysis: In this study, the result of genotypic path coefficient analysis showed that 
dry red fruit yield per plant (0.46) had the highest positive direct effect on total fruit yield per hectare followed by 
fruit pericarp thickness (0.37), number of primary branches per plant (0.31), canopy diameter (0.2), thousand seed 
weight (0.18), average single fruit weight (0.16), fruit pedicel length and stem diameter (0.11), while negative 
direct effect was observed for days to maturity (-0.21), fruit length (-0.2), fruit diameter (-0.15) and days to 50% 
flowering (- 0.08) while, days to 50% fruiting, plant height and number of seeds per fruit had very little positive 
direct effect on fruit yield per hectare though it exhibited significant and positive association with fruit yield (Table 
5).This indicates the true relationship between these characters as a good contributor to fruit yield. 
Similarly, Shimeles (2018) reported that direct influence of pericarp thickness on fruit yield was very high and 
positive and its indirect influence through fruit diameter was also positive. However, pericarp thickness showed 
high negative indirect effect on number of fruits per plant. Generally, based on the genotypic path analysis of 
agronomic characters which showed positive direct effects on fruit yield per hectare were: dry fruit yield per plant, 
fruit pericarp thickness, average single fruit weight, number of primary branches per plant, canopy diameter and 
number of seeds per fruit. This result agrees with that of Kumari (2017).  
In conclusion, the present study confirmed the existence of enormous genetic variability among the hot pepper 
germplasm for various important morphological traits. Hence there is an opportunity to exploit these traits in order 
to develop genotypes that perform better than the existing varieties for the future pepper improvement program. 
 
Table 4. Estimates of genotypic (above diagonal) and phenotypic (below diagonal) correlation coefficient for 17 
characters of 64 Hot pepper genotypes tested under irrigation in northern Ethiopia 

Traits DFL DFR DM PH CD NPB SD FPL FL FD FPT DFYP FW NFP NSF TSW TFY 

DFL 1.00 0.79** 0.58** 

0.48*

* 0.26* 0.40* 0.49** -0.25* -0.30* -0.26* -0.31* 

-

0.12ns -0.29* 0.31* -0.11ns 

-

0.22ns 

-

0.08ns 

DFR 0.72** 1.00 0.72** 

0.41*

* 0.22ns 0.54** 0.47** -0.34* 

-

0.45** 

-

0.44** 

-

0.44** 

-

0.18ns 

-

0.46** 0.43** 

-

0.24ns 

-

0.33** 

-

0.13ns 

DM 0.54** 0.62** 1.00 0.29* 0.32** 0.66** 0.39** 

-

0.45** 

-

0.69** 

-

0.60** 

-

0.60** 

-

0.33** 

-

0.65** 0.55** 

-

0.33** 

-

0.47** -0.28* 

PH 0.37** 0.31** 0.26** 1.00 0.18ns 0.11ns 0.73** 0.07ns 0.04ns 0.03ns 0.00ns 0.06ns 0.09ns 0.13ns 0.14ns 0.09ns 0.20ns 

CD 0.25** 0.18** 0.31** 0.20* 1.00 0.39** 0.41** 

-

0.23ns -0.27* 

-

0.24ns 

-

0.23ns 0.07ns 

-

0.16ns 0.35** 

-

0.04ns 

-

0.01ns 0.28* 

NPB 0.34** 0.47** 0.61** 

0.12n

s 0.37** 1.00 0.31* 

-

0.58** 

-

0.73** 

-

0.62** 

-

0.60** -0.11ns 

-

0.63** 0.70** -0.26* 

-

0.48** 

-

0.02ns 

SD 0.38** 0.37** 0.31** 

0.61*

* 0.36** 0.27** 1.00 
-

0.08ns 

-

0.06ns -0.11ns 

-

0.16ns 0.10ns 

-

0.07ns 0.38** 0.07ns 0.09ns 0.26* 

FPL 

-

0.24** 

-

0.32** 

-

0.39** 

0.06n

s -0.19* 

-

0.52** 

-

0.09ns 1.00 0.59** 0.60** 0.52** 0.15ns 0.51** 

-

0.51** 0.35** 0.26* 0.19ns 

FL 

-

0.27** 

-

0.41** 

-

0.64** 

0.03n

s 

-

0.25** 

-

0.69** 

-

0.05ns 0.56** 1.00 0.72** 0.67** 0.27* 0.80** 

-

0.66** 0.30* 0.62** 0.25* 

FD 

-

0.24** 

-

0.40** 

-

0.56** 

0.02n

s -0.22* 

-

0.59** 

-

0.09ns 0.57** 0.70** 1.00 0.84** 0.37** 0.79** 

-

0.70** 0.60** 0.47** 0.37** 

FPT 

-

0.26** 

-

0.36** 

-

0.50** 0.11ns -0.19* 

-

0.52** 

-

0.07ns 0.40** 0.58** 0.74** 1.00 0.38** 0.74** 

-

0.56** 0.49** 0.49** 0.44** 



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DFY

P -0.12 

-

0.17** 

-

0.32** 

0.05n

s 0.07ns 

-

0.10ns 0.09s 0.15ns 0.26** 0.37** 0.34** 1.00 0.57** 0.06ns 0.46** 0.43** 0.75** 

FW 

-

0.26** 

-

0.42** 

-

0.61** 

0.08n

s 

-

0.15ns 

-

0.60** 

-

0.05ns 0.49** 0.77** 0.77** 0.64** 0.56** 1.00 

-

0.60** 0.54** 0.63** 0.52** 

NFP 0.27** 0.37** 0.52** 

0.12n

s 0.31** 0.67** 0.34** 

-

0.48** 

-

0.65** 

-

0.68** 

-

0.49** 0.06ns 

-

0.58** 1.00 
-

0.40** -0.30* 0.04ns 

NSF -0.09 

-

0.22** 

-

0.31** 

0.14n

s 

-

0.03ns 

-

0.25** 0.08ns 0.33** 0.30** 0.59** 0.43** 0.45** 0.52** 

-

0.40** 1.00 0.19ns 0.42** 

TSW -0.22* 

-

0.32** 

-

0.40** 

0.09n

s 0.03ns 

-

0.41** 0.06ns 0.23** 0.58** 0.46** 0.46** 0.40** 0.59** 

-

0.28** 0.17ns 1.00 0.47** 

TFY 

-

0.06ns 

-

0.15ns 

-

0.25** 

0.23*

* 0.23* 

-

0.02ns 0.25** 0.18* 0.23** 0.33** 0.42** 0.70** 0.49** 0.06ns 0.39** 0.41** 1.00 

Note: ns= non Significance *and **=significant at 5% and 1% probability levels, respectively. DFL=days to 50 
percent flowering, DFR= Days to 50 percent fruiting, DM = days to maturity, PH = plant height, CD = canopy 
diameter, NPB= Number of primary branches per plant, SD= Stem diameter, FPL= Fruit pedicel Length, FL= 
Fruit length, FD= Fruit diameter, FPT = Fruit pericarp thickness, DFYP= Dry fruit yield per plant, FW= Average 
single fruit weight, NFP=Number of Fruit per plant, NSF= Number of seeds per fruit, TSW= Thousand seed weight, 
TFY= Total fruit yield. 
 
Table 5. Estimates of direct (bold and diagonal) and indirect effect (off diagonal) of different characters on fruit 
yield of 64 hot pepper genotypes at genotypic level at Mereb Lekhe (northern Ethiopia) in, 2017/18. 

Characters DFL DFR DM PH CD NPB SD FPL FL FD FPT DFYP FW NFP NSF TSW rg 

DFL -0.08 0.06 -0.12 0.031 0.053 0.12 0.05 -0.03 0.06 0.04 -0.11 -0.06 -0.05 -0.006 -0.001 -0.04 -0.08 

DFR -0.06 0.08 -0.15 0.027 0.045 0.16 0.05 -0.05 0.09 0.07 -0.16 -0.08 -0.07 -0.008 -0.002 -0.06 -0.13 

DM -0.05 0.06 -0.21 0.019 0.066 0.20 0.04 -0.06 0.14 0.09 -0.22 -0.15 -0.10 -0.010 -0.003 -0.09 -0.28* 

PH -0.04 0.03 -0.06 0.065 0.037 0.03 0.08 0.01 -0.01 0.00 0.00 0.03 0.02 -0.002 0.001 0.02 0.20 

CD -0.02 0.02 -0.07 0.012 0.205 0.12 0.04 -0.03 0.05 0.04 -0.09 0.03 -0.03 -0.006 0.000 0.00 0.28* 

NPB -0.03 0.04 -0.14 0.007 0.080 0.31 0.03 -0.08 0.14 0.09 -0.22 -0.05 -0.10 -0.013 -0.002 -0.09 -0.02 

SD -0.04 0.04 -0.08 0.047 0.085 0.10 0.11 -0.01 0.01 0.02 -0.06 0.05 -0.01 -0.007 0.001 0.02 0.26* 

FPL 0.02 -0.03 0.10 0.005 -0.047 -0.18 -0.01 0.13 -0.12 -0.09 0.19 0.07 0.08 0.009 0.003 0.05 0.19 

FL 0.02 -0.04 0.15 0.003 -0.056 -0.22 -0.01 0.08 -0.20 -0.11 0.25 0.12 0.13 0.012 0.003 0.11 0.25* 

FD 0.02 -0.04 0.13 0.002 -0.049 -0.19 -0.01 0.08 -0.14 -0.15 0.31 0.17 0.13 0.013 0.006 0.09 0.37 

FPT 0.02 -0.04 0.13 0.000 -0.048 -0.18 -0.02 0.07 -0.13 -0.13 0.37 0.18 0.12 0.010 0.005 0.09 0.44** 

DFYP 0.01 -0.01 0.07 0.004 0.014 -0.03 0.01 0.02 -0.05 -0.06 0.14 0.46 0.09 -0.001 0.004 0.08 0.75** 

FW 0.02 -0.04 0.14 0.006 -0.034 -0.19 -0.01 0.07 -0.16 -0.12 0.27 0.26 0.16 0.011 0.005 0.12 0.52** 

NFP -0.02 0.03 -0.12 0.009 0.072 0.21 0.04 -0.07 0.13 0.10 -0.21 0.03 -0.10 -0.018 -0.004 -0.06 0.04 

NSF 0.01 -0.02 0.07 0.009 -0.008 -0.08 0.01 0.05 -0.06 -0.09 0.18 0.21 0.09 0.007 0.010 0.04 0.42** 

TSW 0.02 -0.03 0.10 0.006 -0.001 -0.15 0.01 0.04 -0.12 -0.07 0.18 0.20 0.10 0.006 0.002 0.18 0.47** 

Residual effect = 0.50 *and ** = significant at 5% and 1% probability levels, respectively. DFL = days to 50% 
flowering, DFL = days to 50%fruiting, DM = days to maturity, PH = plant height, CD = canopy diameter, NPB = 
number of primary branches per plant, SD = stem diameter, FPL = fruit pedicel length, FL = fruit length, FD = 
fruit diameter, FPT = fruit pericarp thickness, DFYP = dry fruit yield per plant, FW = average single fruit weight, 
NFP = number of fruit per plant, NSF = number of seeds per fruit, TSW = thousand seed weight and rg = genotypic 
coefficient of correlation. 
 
Conflict of Interests 
The authors have not declared any conflict of interests. 
Acknowledgements 
The authors grateful appreciate the Tigray Agricultural Research Institute (TARI) and Axum Agricultural 
Research Center (AxARC) for funding the project. It is also time to thank the staff of Horticulture case team in 
core process of Horticulture and plant sciences for the execution of the experiment. 
 



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Appendix 1. Mean values for phenological and morphological characters of 64 hot pepper genotypes evaluated 
under irrigation at Mereb Lekhe (northern Ethiopia) in 2017/18. 

No. Genotypes DFL DFR DM PH CD NPB SD
1 Acc-1 65g-m 72i-p 113.5p 60a-e 39.5a-j 5.75n-s 16ab

2 Acc-2 68c-k 79a-g 126b-g 52.8c-m 41.1a-g 11a-d 13.2c-j

3 Acc-3 70.5a-h 79.5a-f 122.5d-l 66.5a 40.5a-h 6.3k-p 14.9a-e

4 Acc-4 64i-n 74e-o 116m-p 46.3j-o 40.2a-i 11a-d 12.65d-m

5 Acc-5 74a-c 81a-d 133a 59.5a-f 40.4a-h 11.75ab 14.4a-f

6 Acc-6 71a-g 82.5ab 128.5a-c 54.3c-m 34.9j-o 9.8a-g 13.5c-h

7 Acc-7 65g-m 77.5b-j 126.5b-f 53.3c-m 38.3b-l 7.2h-o 13c-l

8 Acc-8 68.5c-k 77.5b-j 127.5a-d 60.7a-d 42.9ab 10a-f 15.25a-c

9 Acc-9 75.5ab 80a-e 130.5ab 60a-e 37.7c-m 11.6ab 13.85a-g

10 Acc-10 69.5b-j 81a-d 123.5d-k 55.4b-l 37.6d-m 10.9a-e 14.4a-f

11 Acc-11 69.5b-j 76.5b-l 113.5p 54.8b-m 33.1m-o 5.6n-s 13.05c-k

12 Acc-12 67d-m 78b-i 127b-e 57.3a-h 42a-d 11.8a 11.1h-o

13 Acc-13 65g-m 74.5e-n 117.5l-p 51.5d-m 33.85l-o 5.4n-s 11.7g-o

14 Acc-14 73a-d 78b-i 129a-c 53.5c-m 42.3a-c 11.5a-c 15a-d

15 Acc-15 70.5a-h 77.5b-j 126b-g 54.1c-m 43.3a 6.3k-p 13.3c-j



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16 Acc-16 65.5f-n 74.5e-n 121.5e-m 56.2b-j 36.45g-o 4.8o-s 12.9c-m

17 Acc-28336 70b-i 79a-g 127b-e 58.4a-g 39.3a-j 9.2b-i 12.8d-n

18 Acc-230800 68.5c-k 77b-k 121.5e-m 56.1b-k 39.2a-j 9c-j 12.25f-o

19 Acc-28337 66f-n 77b-k 120.5g-m 54.3c-m 35.6i-o 3.6rs 12.75d-n

20 Acc-229699 65.5f-n 75.5c-m 124.5c-i 54.6c-m 36.9f-o 11.8a 12.75d-n

21 Acc-212912 70.5a-h 78.5a-h 120h-n 60.1a-e 41a-g 8.4e-m 14.9a-e

22 Acc-9097 61m-o 72i-p 123.5c-k 37.1o 39a-k 6.3k-p 11i-o

23 Acc-9084 57.5o 68op 122.5d-l 53.5c-m 36h-o 8.8d-k 12.65d-m

24 Acc-229697 68c-k 77b-k 124c-j 50.1e-m 32.4o 9.7a-h 11.75g-o

25 Acc-212913 64i-n 71.5j-p 119.5i-o 55.8b-k 41.5a-e 3.9q-s 13.9a-g

26 Acc-229700 66.5e-m 78.5a-h 125.5b-h 50.9d-m 33.5m-o 8.7d-l 13.35c-i

27 Acc-8995 70.5a-h 77b-k 128.5a-c 52.8c-m 39.1a-j 11a-d 12.6d-n

28 Acc-9085 67.5d-l 75d-m 120h-n 46.3j-o 35.1j-o 6.6j-p 10.75k-o

29 Acc-230798 64i-n 71.5i-p 116.5l-p 47.6h-m 35.1k-o 3.7rs 11i-o

30 Acc-230799 72.5a-e 79a-g 126b-g 52.7c-m 38.9a-k 7.8f-n 11.8g-o

31 Acc-236436 67d-m 77.5b-j 125.5b-h 55.5b-l 33.2m-o 5.25n-s 12.2f-o

32 Acc-229698 62.5k-o 70.5l-p 118k-p 49.5f-m 35j-o 3.6rs 12.25f-o

33 Acc-229701 63.5j-o 71k-p 117l-p 37.5no 37.5d-n 9.7a-h 10.4no

34 Acc-237528 71a-g 80a-e 127.5a-d 47.1h-m 35.2j-o 9.7a-h 10.9j-o

35 Acc-9102 64.5h-m 72.5h-p 124.5c-i 59.4a-g 35j-o 6.7i-p 13.65b-g

36 Acc-9094 71.5a-f 76.5b-l 122.5d-l 50.4d-m 34.4k-o 7.05i-p 12.25f-o

37 Acc-9098 63.5j-o 78b-i 127.5a-d 54c-m 37.6d-m 8.6d-l 12.9c-m

38 Acc-9104 63.5j-o 77.5b-j 127b-e 45.7k-o 41.6a-e 10.5a-e 12.25f-o

39 Acc-9099 70.5a-h 79a-g 128.5a-c 46.8i-o 35.1j-o 8.7d-l 12.75d-n

40 Acc-9082 67d-m 74e-o 119i-p 52c-m 36.1h-o 5.25n-s 12.5e-n

41 Acc-9101 67d-m 71.5j-p 122d-l 57.3a-h 43.1a 7.7f-n 13.35c-i

42 Acc-9086 70b-i 80a-e 129a-c 52.7c-m 42.5ab 7.3g-o 13.2c-j

43 Acc-229696 73a-d 82.5ab 127.5a-d 55.3b-m 36.6g-o 7.7f-n 13.6c-g

44 Acc-9106 66f-n 80a-e 122.5d-l 51.8d-m 35.55i-o 8.7d-l 12.35f-n

45 Acc-9007 70b-i 77.5b-j 129a-c 60.8a-c 35.9h-o 8.6d-l 14a-g

46 Acc-9107 71.5a-f 76.5b-l 126b-g 52.7c-m 37e-o 5o-s 12.05f-n

47 Acc-28334 64.5h-m 70.5l-p 122.5d-l 50.7d-m 33.9l-o 4.6p-s 13.2c-j

48 Acc-48 61.5l-o 67.5p 117l-p 47.7h-m 37.25e-n 3.6rs 10.55m-o

49 Acc-49 63.5j-o 67.5p 114.5n-p 45.3l-o 39a-k 3.5s 10.75k-o

50 Acc-229694 65.5f-n 74.5e-n 117l-p 56.2b-j 37.5d-n 3.5s 13.55c-g

51 Acc-51 68c-k 74.5e-n 119.5i-o 57.5a-g 33.3m-o 3.6rs 12.75d-n

52 Acc-52 66.5e-m 77b-k 121.5e-m 47.3h-m 37.5d-n 3.4s 11.85g-o

53 Acc-9093 62.5k-o 68.5n-p 119i-p 54.1c-m 32.95no 6.4l-q 11.6g-o

54 Acc-229692 67d-m 73.5f-p 118.5j-p 51.6d-m 36.2h-o 3.9q-s 12.3f-n

55 Acc-55 65g-m 69.5m-p 117l-p 52.5c-m 37e-o 4q-s 12.3f-n

56 Acc-56 68.5c-k 71.5j-p 116.5l-p 56.1b-k 35.55i-o 5.5n-s 11.6g-o

57 Acc-57 64i-n 72.5h-p 114p 47.2h-m 36h-o 3.5s 10.6l-o

58 Acc-58 69c-j 73g-p 119.5i-o 51.6d-m 37.5d-n 3.5s 12.3f-n

59 Acc-59 75.5ab 81.5a-c 130.5ab 59.6a-f 43.4a 10.1a-f 16.05a

60 Acc-23880 63.5j-o 72.5h-p 120h-n 49g-m 35.6i-o 5.9m-s 10.9j-o

61 Acc-61 60.5no 70.5l-p 118k-p 44.9m-o 36h-o 3.6rs 9.85o

62 Acc-62 62.5k-o 74e-o 120h-n 56.8a-i 33.3m-o 3.95q-s 11.95g-n

63 Acc-63 76.5a 84.5a 126b-g 65ab 37.4d-n 6.2l-r 13.7a-g

64 Acc-64 66f-n 76.5b-l 121f-m 62.3a-c 35j-o 3.6rs 13.7a-g

 Mean 62.27 75.68 122.6 53.29 37.38 7.1 12.7
 CV (%) 3.8 3.3 2 7.8 5 15 7.7

Means followed by the same letter in the same column are not significantly different. CV (%) = coefficient of 
variation, DFL = days to 50% flowering, DFR = days to 50% fruiting DM = days to maturity, PH = plant height, 
CD = canopy diameter, NPB = number of primary branches per plant, SD = stem diameter.  
 
Appendix 2. Mean performance for fruit yield and fruit characteristics of 64 hot pepper genotypes evaluated at 
Mereb Lekhe (northern Ethiopia) in, 2017/18 

No. Genotypes  FPL FL FD FPT FW NFP NSF TSW DFYP MFY UNMY TFY 

1 Acc-1 4.05a-g 16.75a 23.25d-f 2.3a-g 6.6a-c 26j-m 136.5n-p 6.55a-d 128.5e 3.25c-d 0.125qr 3.38bc 

2 Acc-2 2.67o-t 6.2o-u 11.21x 1.7k 2.41p-u 53.15ab 105.3wx 5.8c-j 106i-l 2.67c-j 0.24e-m 2.91c-j 

3 Acc-3 4.1a-f 11e-j 29.4ab 2.3a-g 6.3a-d 19.25o-r 221b 6.45a-e 167.5ab 3.855ab 0.41a 4.27a 

4 Acc-4 2.8n-t 7.52no 18.72k-m 2.3a-g 2.95k-r 34.6e 188d 5.8c-j 168ab 4.34a 0.21i-r 4.55a 

5 Acc-5 3.4g-n 4.56v-x 15.14p-v 1.85h-k 2.185q-u 55.5a 111u-w 5.7d-j 105.5i-l 2.85c-h 0.29c-i 3.14c-f 



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6 Acc-6 2.32t 5.08s-x 15.11o-v 1.7k 3.7h-m 44.3c 147.4j-m 6.5a-d 143cd 2.465c-m 0.16l-r 2.63c-n 

7 Acc-7 3.73d-j 11.2d-i 15.36o-t 1.82i-k 2.92k-r 29.3f-k 118.8s-v 6b-i 83.5o-q 1.9i-o 0.13p-r 2j-o 

8 Acc-8 3.05k-r 4.39wx 12.01v-x 1.95f-k 2.235q-u 50.9ab 138.5m-o 5.9b-j 102.5j-l 2.88c-h 0.2i-r 3.1c-g 

9 Acc-9 2.65o-t 6.49o-t 14.06p-x 1.85h-k 2.205q-u 31.5e-h 116.5t-v 4.6l-p 63.5t-v 2.02h-n 0.25e-l 2.27f-o 

10 Acc-10 3.25i-o 10.25h-l 12.4t-x 1.9g-k 1.55u 52.9ab 110u-w 5.1h-n 118.5e-h 2.56c-l 0.14o-r 2.7c-m 

11 Acc-11 4.25a-e 14.5b 23.1d-f 2.25b-h 6.325a-d 23.4l-p 145.5k-n 6.6a-d 126.5e 2.64c-j 0.12r 2.8c-l 

12 Acc-12 2.67o-t 4.41wx 12.89s-x 1.85h-k 2.21q-u 31.25e-i 109.5vw 4.2n-p 87o-q 2.37d-m 0.22h-n 2.59c-n 

13 Acc-13 2.75n-t 8.23mn 16.03o-r 1.94f-k 2.75l-s 26.3i-m 110.2u-w 5.35f-m 54.5v 1.63m-o 0.16l-r 1.78n-p 

14 Acc-14 2.52r-t 5.25t-x 12.94s-x 1.75jk 2.51n-u 43.15cd 94y 5.4e-l 86o-q 2.56d-l 0.24f-n 2.79c-k 

15 Acc-15 3l-s 7n-p 12.6t-x 1.8i-k 2.38p-u 42.6cd 105.3wx 6.7a-d 82p-s 1.865j-o 0.23f-n 2.095i-o 

16 Acc-16 4.2a-f 9.15lm 19.72g-l 2.45a-d 4.82fg 32.6e-g 158.1g-i 6.1b-h 150c 3.84ab 0.225f-p 4.1ab 

17 Acc-28336 4.2a-f 4.4wx 13r-x 1.7k 3.175k-r 41.1cd 143k-n 4.7k-p 128e 2.415d-m 0.16l-r 2.58c-n 

18 Acc-230800 2.75n-t 6.55o-s 11.94wx 1.9c-k 3.395j-p 24.3l-n 118.7s-v 6b-i 78.5q-s 2.49c-m 0.175j-r 2.7c-n 

19 Acc-28337 3.73d-j 7.03n-p 18.9j-n 2.13c-j 3.75h-l 19o-r 173.9e 4.9j-p 83.5o-q 2.42d-m 0.15m-r 2.57c-n 

20 Acc229699 3.25i-o 4.165wx 23.8de 2.36a-f 3.58h-m 42.9cd 149.9i-l 4.1op 159.5b 3.07b-f 0.125qr 3.19c-e 

21 Acc212912 4.25a-e 9.56j-m 31a 2.7a 6.82ab 19.6n-r 231a 6.8a-c 163ab 4.16a 0.33a-e 4.49a 

22 Acc-9097 4.5a-c 6.38o-u 16.8l-q 1.9g-k 1.815s-u 17.9qr 101.1w-y 5.7d-j 61.5uv 2.125g-n 0.125qr 2.25f-o 

23 Acc-9084 2.53q-t 5.25s-x 11.91wx 1.75jk 1.61tu 42cd 125.2rs 5.1h-n 82.5o-r 1.9i-o 0.23f-n 2.13h-o 

24 Acc-229697 3.8d-j 4.95v-x 14.91o-w 2e-k 1.82s-u 52ab 93y 4p 83.5o-q 2.125g-n 0.315b-f 2.44d-o 

25 Acc-212913 3l-s 9.5k-m 18.63k-n 2.35a-f 5.98b-d 49.9b 118.3s-v 7.2a 172.5a 4.18a 0.14n-r 4.32a 

26 Acc-229700 3.57f-m 5.45q-x 11.855wx 1.7k 2.23q-u 54.9a 128.1p-s 5.4e-l 160b 2.425c-m 0.22g-q 2.7c-n 

27 Acc-8995 2.55p-t 4x 12.82t-x 1.85h-k 2.45p-u 43.65cd 176e 5.2g-m 99l-n 2.14g-n 0.38a-c 2.52c-o 

28 Acc-9085 3.2j-p 4.5wx 11.86wx 1.75jk 2.31q-u 45.3c 120r-u 4.9j-p 127.5e 1.825j-o 0.115r 1.94k-p 

29 Acc230798 3.94b-h 10.73f-k 27.75bc 2.35a-f 3.935g-k 18.5p-r 142.35k-n 6.3a-f 72.5r-t 1.73k-o 0.115r 1.845l-p 

30 Acc-230799 2.95m-t 5.3r-x 14.93o-w 1.95f-k 2.24q-u 31.6e-h 95.5y 5.2g-m 100k-n 1.675l-o 0.16l-r 1.79m-p 

31 Acc-236436 3.02l-r 6.45o-u 17.64k-o 2.69a 2.61m-u 33.8ef 99.3xy 6.3a-f 87o-q 2.29f-m 0.16l-r 2.45e-o 

32 Acc-229698 3.35h-n 12.2d-f 23.25d-f 2.35a-f 4.35f-j 15.1r 142.5k-n 6.3a-f 138d 2.78c-i 0.115r 2.9c-j 

33 Acc-229701 3.05k-r 4.05wx 12.1u-x 1.85h-k 2.125r-u 52.25ab 126.7q-s 4.9j-p 126e 2.56c-l 0.21h-r 2.77c-k 

34 Acc-237528 2.29t 4.93u-x 15.12o-u 2.05d-k 2.36p-u 30.3e-j 144.5k-n 4.4l-p 56v 1.7l-o 0.35a-d 2.04j-p 

35 Acc-9102 3.9c-i 6.1o-v 16.96l-p 1.95f-k 2.435p-u 26.9h-m 151.2i-k 4.3m-p 64t-v 0.7p 0.13p-r 0.83q 

36 Acc-9094 2.3t 6.9n-q 19.23i-m 1.8i-k 2.63m-t 24.5k-n 150.3i-l 4.7k-p 98l-n 2.08h-m 0.165l-r 2.25f-o 

37 Acc-9098 3l-s 5.3r-x 11.84wx 1.85h-k 2.22q-u 39d 123.5r-t 5.4e-l 80.5q-s 1.71k-o 0.35a-d 2.1i-p 

38 Acc-9104 2.75n-t 5.2s-x 15.19o-u 1.8i-k 2.31q-u 28.2g-l 110.8u-w 4.9j-p 79q-s 2.065h-n 0.265d-j 2.33e-o 

39 Acc-9099 3.1k-r 4.3wx 12.2u-x 1.8i-k 2.235q-u 22.1m-q 150.4i-l 4p 64t-v 1.395n-p 0.26d-k 1.66op 

40 Acc-9082 3.95b-h 6.8o-r 21.75e-j 2.1d-k 2.72l-s 24l-o 139m-o 5.3f-m 89.5n-q 2.53c-l 0.175j-r 2.71c-l 

41 Acc-9101 3.19j-q 4.3wx 12.84t-x 1.75jk 2.245q-u 42.9cd 170.1ef 4.1op 84o-q 2.555c-l 0.155l-r 2.71c-l 

42 Acc-9086 4a-h 5.4r-x 17.82k-o 1.99e-k 2.57m-u 42.2cd 137.9m-p 4.1op 99l-n 2.4d-m 0.39ab 2.79c-k 

43 Acc229696 2.35st 4.18wx 12.79s-x 1.75jk 2.71l-s 42.5cd 99.7xy 4.3m-p 92m-p 2.1g-n 0.31b-g 2.41d-o 

44 Acc-9106 4.04a-g 6.51o-t 16.54m-q 1.95f-k 2.235q-u 32e-g 138.9m-o 4.4l-p 71.5s-u 2.1h-m 0.13p-r 2.21g-o 

45 Acc-9007 3.69d-k 4.22wx 15.9n-s 1.75jk 2.495n-u 31.3e-i 156h-j 5i-o 115f-i 2.035h-n 0.37a-c 2.4d-o 

46 Acc-9107 4.6ab 10.97e-k 23.88de 2.25b-h 3.21k-q 16.6r 128.9o-r 5.2g-m 82.5o-r 2.41d-m 0.125qr 2.53c-o 

47 Acc-28334 4.25a-e 14.7b 25.24cd 2.4a-e 6b-d 19.6n-r 186.8d 5.7d-j 120e-h 2.6c-k 0.125qr 2.73c-l 

48 Acc-48 4.25a-e 11.4d-i 25.18cd 2.57ab 5.77c-e 19o-r 200.9c 5.7d-j 121.5e-g 2.57c-l 0.13p-r 2.7c-m 

49 Acc-49 4.3a-d 12.5c-e 25.1cd 2.4a-e 7.1a 15.2r 142.3l-n 6b-i 144cd 2.865c-h 0.2i-r 3.1c-g 

50 Acc-229694 4.27a-e 13.78bc 24.56de 2.35a-f 6.19a-d 17.6qr 139.3mn 6.9ab 112g-j 2.92c-h 0.115r 3.03c-h 

51 Acc-51 3.9c-i 12.5c-e 29.45ab 2.55a-c 5.32d-f 18.75pr 166.4e-g 6.3a-f 105.5i-l 2.14g-n 0.16l-r 2.3e-o 

52 Acc-52 3.2j-p 12.65cd 19.4h-m 2.21b-i 4.37f-j 15.6r 142.8k-n 5.4e-l 82.5o-r 1.1op 0.115r 1.2pq 

53 Acc-9093 3.625e-l 11.32d-i 20.54f-k 2.15b-j 6.27a-d 24.1l-o 145k-n 6.8a-c 140.5cd 3.34bc 0.115r 3.43bc 

54 Acc-229692 3.84c-j 12.45c-e 18.92j-n 2.2b-i 3.175k-r 27.9g-l 125.4r-t 6.8a-c 81.5p-s 2.795c-i 0.17k-q 3c-i 

55 Acc-55 4.65a 11.68d-h 22.43d-g 2.25b-h 4.585f-h 19o-r 152i-k 5.4e-l 93m-o 2.47c-m 0.12r 2.59c-n 

56 Acc-56 4.02a-g 11.6d-h 22.35d-h 2.2b-i 4.98ef 14.85r 138m-p 6.7a-d 100k-n 2.22f-n 0.14n-r 2.36d-o 

57 Acc-57 3.95b-h 11.27d-i 21.97e-i 2.25b-h 5.79c-e 14.75r 174.4e 6.5a-d 167.5ab 3.1b-f 0.165l-r 3.26b-d 

58 Acc-58 3.925c-h 9.93i-l 19.75g-l 2.2b-i 4.47f-i 18.3p-r 161.4f-h 6.9ab 138.5d 2.83c-h 0.14n-r 2.97c-i 

59 Acc-59 2.42r-t 5.62r-w 13.7q-x 1.8i-k 2.61m-u 53.5ab 139m-o 6.2a-g 125ef 2.49c-m 0.3c-h 2.78c-k 

60 Acc-23880 3.86c-i 11.18d-i 22.2d-h 2.15b-j 4.58f-h 15.2r 135.3n-q 6.6a-d 112.5g-j 2.515c-m 0.125qr 2.64c-n 

61 Acc-61 2.9n-t 11.85d-g 22.68d-g 2.3a-g 6.7a-c 16.2r 145.4k-n 5.7d-j 161b 2.995c-g 0.16l-r 3.16c-f 



as.ideasspread.org   Agricultural Science Vol. 2, No. 1; 2020 

 303       Published by IDEAS SPREAD 
 

62 Acc-62 4.5a-c 12.05d-f 18.48k-n 2.2b-i 6.1b-d 19.6n-r 140.5l-n 6.6a-d 105i-l 3.245b-e 0.165l-r 3.41bc 

63 Acc-63 4a-h 10.4g-l 13.27r-x 2.05d-k 3.46j-o 30.6e-j 128.4p-s 4.4l-p 110h-k 2.43c-m 0.125qr 2.56c-o 

64 Acc-64 3.94b-h 10.28h-l 19.71g-l 1.95f-k 3.5i-n 19.25o-r 137.9m-p 5.7d-j 80q-s 2.35e-m 0.185j-r 2.54c-o 

 Mean 3.5 8 18 2.1 3.6 31 139.1 5.6 107.3 2.48 0.19 2.67 

 CV (%) 7.8 7.8 7.1 8.3 11.9 6.9 3.1 7.8 4.2 14.6 19.7 13.8 

Means followed by the same letter in the same column are not significantly different. CV (%) = coefficient of 
variation, FPL = fruit pedicel length, FL = fruit length, FD = fruit diameter, FPT = fruit pericarp thickness, FW = 
average single fruit weight, NFP = number of fruits per plant, NSF = number of seeds per fruit, DFYP=dry fruit 
yield per plant, MFY = marketable fruit yield, UNMFY = Unmarketable fruit yield, TFY = total fruit yield. 
 
Copyrights 
Copyright for this article is retained by the author(s), with first publication rights granted to the journal. 
This is an open-access article distributed under the terms and conditions of the Creative Commons Attribution 
license (http://creativecommons.org/licenses/by/4.0/). 
 
















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    /NLD (Gebruik deze instellingen om Adobe PDF-documenten te maken die zijn geoptimaliseerd voor prepress-afdrukken van hoge kwaliteit. De gemaakte PDF-documenten kunnen worden geopend met Acrobat en Adobe Reader 5.0 en hoger.)
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    /ENU (Use these settings to create Adobe PDF documents best suited for high-quality prepress printing.  Created PDF documents can be opened with Acrobat and Adobe Reader 5.0 and later.)
  >>
  /Namespace [
    (Adobe)
    (Common)
    (1.0)
  ]
  /OtherNamespaces [
    <<
      /AsReaderSpreads false
      /CropImagesToFrames true
      /ErrorControl /WarnAndContinue
      /FlattenerIgnoreSpreadOverrides false
      /IncludeGuidesGrids false
      /IncludeNonPrinting false
      /IncludeSlug false
      /Namespace [
        (Adobe)
        (InDesign)
        (4.0)
      ]
      /OmitPlacedBitmaps false
      /OmitPlacedEPS false
      /OmitPlacedPDF false
      /SimulateOverprint /Legacy
    >>
    <<
      /AddBleedMarks false
      /AddColorBars false
      /AddCropMarks false
      /AddPageInfo false
      /AddRegMarks false
      /ConvertColors /ConvertToCMYK
      /DestinationProfileName ()
      /DestinationProfileSelector /DocumentCMYK
      /Downsample16BitImages true
      /FlattenerPreset <<
        /PresetSelector /MediumResolution
      >>
      /FormElements false
      /GenerateStructure false
      /IncludeBookmarks false
      /IncludeHyperlinks false
      /IncludeInteractive false
      /IncludeLayers false
      /IncludeProfiles false
      /MultimediaHandling /UseObjectSettings
      /Namespace [
        (Adobe)
        (CreativeSuite)
        (2.0)
      ]
      /PDFXOutputIntentProfileSelector /DocumentCMYK
      /PreserveEditing true
      /UntaggedCMYKHandling /LeaveUntagged
      /UntaggedRGBHandling /UseDocumentProfile
      /UseDocumentBleed false
    >>
  ]
>> setdistillerparams
<<
  /HWResolution [2400 2400]
  /PageSize [612.000 792.000]
>> setpagedevice

