‘’EVALUATION OF AFRICAN TOMATO LANDRACES (SOLANUM LYCOPERSICUM) SUPPORTED MORPHOLOGICAL AND HUSBANDRY TRAITS’’

VOL 04 NO.02

DR. NASOD RIZAE; KEMJI, P.E; DODE K.O.

ABSTRACT

Crop a domesticated plant species which has developed largely adaptation to the natural and cultural environment in which it lives; therefore understanding and utilizing the genetic variation in tomato accessions area unit essential for raising the crop. The objective of this study was to characterize sixty-nine tomato landraces from the globe Vegetable Centre and therefore the National Gene bank of the African country to spot fascinating morphological and husbandry traits that could be used for tomato crop improvement. Field experiments were arranged to go into a randomized complete block style with 3 replicates at the University of Nairobi’s Kabete field station, Kenya, in 2014 and 2015. The principal component analysis showed that the first five components explained 78.4% of the total variation among the genotypes. Traits that contributed most to variability were the presence of inexperienced shoulder, fruit size, exterior fruit color, pubescence density, flower color, and fruit cross-section shape. Cluster analysis grouped the accessions into two major clusters. Cluster I contained sixty-three accessions whereas cluster II had six accessions. As the study was done on variance for quantitative traits indicated important variations among the accessions for single leaf area, soil plant analysis development, days to five hundredth flowering, days to maturity, the number of fruits per plant, fruit width, fruit length and fruit weight per plant. Fruit weight per plant ranged from 565.0 g to 2759.0 g per plant and showed a positive significant correlation with fruit length (r = 0.28) and fruit width (r = 0.30). The study showed the existence of wide genetic diversity among the tomato accessions so providing scope for future genetic improvement of the crop.

Keywords:-

 Diversity, Horticultural, Landraces ,Morphology, Tomato.

INTRODUCTION:-

 Tomato (Lycopersicon esculentum L.) is horticultural crop widely grown in Kenya (Musyoki et al., 2005). The crop is mainly grown for the domestic market and ranks second after potato (Horticultural Crops Development Authority, 2014). Alongside other nutrients, tomato fruit contains β-carotene, vitamin C and phenolic compounds, which offer many health benefits for the consumers (Martí et al., 2016). The production area under tomato has been on the increase in the country, and this could be attributed mainly to the increased demand for the crop. Between 2011 and 2013, the area under tomato increased by 16% from 20,584 ha to 23,866 ha. In the same period, the total volume produced increased by about 24% from 396,544 t to 494,037 t (Horticultural Crops Development Authority, 2014).

Despite this substantial improvement, tomato production has continued to face major setbacks. According to Maerere et al. (2006), some biotic and abiotic factors have been attributed to low yields and the increased cost of production. In their effort to control pests and diseases, farmers use pesticide products excessively with over 40 applications per season recorded in some tomato fields (Waiganjo et al., 2006). The low diversity among commercial tomato varieties has been identified as one of the major factors that predispose the crop to biotic and abiotic constrains (Osei et al., 2014).

Crop landraces have been used widely in breeding work and are always thought to harbor valuable traits lost among cultivated varieties and the exploitation of such traits increases research findings and knowledge of the genetic variability which facilitates breeding for wider geographic adaptability (Hanson et al., 2007). In Africa, there are large numbers of tomato landraces stored in gene banks whose phenotypic and genotypic traits are largely un documented. Knowledge of this diversity is important to broaden the genetic resource base for future tomato crop improvement programs. The current study aimed to evaluate and document the extent of phenotypic diversity among African tomato landraces.

MATERIALS AND METHODS

Description of the research site

The study was conducted during the short and long rains of 2014 and 2015, respectively, at the University of Nairobi’s Upper Kabete Field Station, Kenya. The site lies at an altitude of 1940 m above sea level and between latitude 10⁰14′20′S and 10⁰15′15 ′N and longitude 360⁰44′E to 360⁰45′E and receives bimodal rainfall averaging 1000 mm annually (Mburu, 1996). The long rains last from March to December. Mean monthly maximum and minimum temperatures are 23 °C and 12 °C, respectively (Siderius, 1976). The soils at the positioning area unit Venetian red clays superimposed dark and red clays and area unit classified as dirt nitisols that area unit deep, fertile, well-drained with thick acid top soils and have a cubic  structure that permits sensible root penetration and development; the clay minerals area unit preponderantly mineral (Karuku et al., 2012).

EXPERIMENTAL TREATMENTS AND DESIGN

The study evaluated 69 tomato landraces (Table 1) sourced from the World Vegetable Centre and the National Genetic Resources in Kenya. These accessions were from Ethiopia (16), Morocco (15), Madagascar (14), South Africa (10), Egypt (3), Mauritius (3) Kenya (2), Tanzania (2), Zimbabwe (2), Nigeria (1) and Zambia (1). The accessions were planted in a randomized complete block design with three replications.

Table 1. List of the African tomato accessions evaluated in the study and their country of origin.

S/noAcc NameSpecies nameOriginS/noAcc NameSpecies nameOrigin
1GBK 050580S.lycopersicumKenya36VI006481-AS.lycopersicumZimbabwe
2GBK 050589S.lycopersicumKenya37VI006825S.lycopersicumEthiopia
3RV02114S.lycopersicumTanzania38VI006826S.lycopersicumEthiopia
4RV101884S.lycopersicumMadagascar39VI006827S.lycopersicumEthiopia
5RVI01885S.lycopersicumMadagascar40VI006828S.lycopersicumEthiopia
6RVI01887S.lycopersicumMadagascar41VI006832S.lycopersicumEthiopia
7RVI01888S.lycopersicumMadagascar42VI006833S.lycopersicumEthiopia
8RVI01896S.lycopersicumMadagascar43VI006837S.lycopersicumEthiopia
9RVI01983S.lycopersicumMadagascar44VI006838S.lycopersicumEthiopia
10RVI02098S.lycopersicumMadagascar45VI006840S.lycopersicumEthiopia
11RVI02100S.lycopersicumMadagascar46VI006841S.lycopersicumEthiopia
12RVI02102S.lycopersicumMadagascar47VI006842S.lycopersicumEthiopia
13RVI02104S.lycopersicumMadagascar48VI006847S.lycopersicumEthiopia
14RVI02107S.lycopersicumMadagascar49VI006848S.lycopersicumEthiopia
15RVI02109S.lycopersicumMadagascar50VI006864S.lycopersicumEthiopia
16RVI02111S.lycopersicumMadagascar51VI006865S.lycopersicumEthiopia
17RVI02112S.lycopersicumMadagascar52VI006869S.lycopersicumEthiopia
18VI005871S.lycopersicumMorocco53VI006881-BS.lycopersicumZimbabwe
19VI005872S.lycopersicumMorocco54VI006892S.lycopersicumSouth Africa
20VI005873S.lycopersicumMorocco55VI006972S.lycopersicumTanzania
21VI005874S.lycopersicumMorocco56VI007108S.lycopersicumSouth Africa
22VI005875S.lycopersicumMorocco57VI007539S.lycopersicumSouth Africa
23VI005876S.lycopersicumMorocco58VI007540S.lycopersicumSouth Africa
24VI005877S.lycopersicumMorocco59VI008098S.lycopersicumSouth Africa
25VI005878S.lycopersicumMorocco60VI008099S.lycopersicumSouth Africa
26VI005889-AS.lycopersicumEgypt61VI008234S.lycopersicumNigeria
27VI005895S.lycopersicumEgypt62VI008916S.lycopersicumSouth Africa
28VI005905S.lycopersicumMorocco63VI030375S.lycopersicumSouth Africa
29VI005986S.lycopersicumMorocco64VI030379S.lycopersicumMauritius
30VI005987S.lycopersicumMorocco65VI030380S.lycopersicumMauritius
31VI005988S.lycopersicumMorocco66VI030381S.lycopersicumMauritius
32VI005989S.lycopersicumMorocco67VI030852S.lycopersicumSouth Africa
33VI005990S.lycopersicumMorocco68VI035028S.lycopersicumSouth Africa
34VI005991S.lycopersicumMorocco69VI037948S.lycopersicumZambia
35VI006480S.lycopersicumEgypt    

S/no = serial number; Acc name = accession name.

Data collection and analysis

The qualitative traits studied consisted of stem color, growth type, pubescence density, foliage density, flower color, presence of a green shoulder, fruit shape, mature fruit color, fruit size, and fruit cross-sectional shape. The traits were evaluated based on the set standards for characters by the International Plant Genetic Resources Institute tomato descriptor (Darwin et al., 2003).

The quantitative traits were: single leaf area, soil plant analysis development (SPAD), and days to 50% flowering, days to maturity, the number of fruits per plant, fruit length, fruit width fruit and fruit weight per plant. Days to flowering was recorded as the number of days from sowing to when 50% of the plants in each plot had flowered. A SPAD value was determined at the flower initiation stage on a fully expanded young leaf from three plants in each stand and averaged. This value was taken at flowering using a non-destructive, hand-held chlorophyll meter (SPAD-502; Minolta Camera Co. Ltd; Tokyo, Japan). Single leaf area was determined at flowering and calculated using leaf length and leaf width measurements following the formula of Rivera et al. (2007): SLA = 0.763L + 0.34W, where SLA is the single leaf area, L is the leaf length, and W is the leaf width. Days to maturity was recorded from sowing until 50% of plants had at least one ripened fruit. Fruit length and fruit width were measured at physiological maturity. Fruit length was recorded from stem end to blossom end while fruit width was recorded at the largest diameter of cross-sectioned fruits. The total number of fruits per plant was determined at physiological maturity and weighing was used to obtain the total fruit weight per plant.

Dissimilarities for qualitative traits were estimated based on Euclidean distance matrix and hierarchical clustering analyses using the unweighted pair group method of arithmetic averaging performed in the DARwin 6.0 software (available from http://darwin.cirad.fr/product.php). The MINITAB software package (version 18; Minitab Inc; State College, PA, USA) was used to perform multivariate-principal component analysis (PCA). The analysis was used to identify the most significant descriptors in capturing the qualitative variation within the accessions. Analysis of variance for quantitative traits was performed using the Genstat software package (version 15; Numerical Algorithms Group Ltd; Oxford, UK). Mean separation for a treatment that was significant was tested using Fisher’s protected least significant difference (LSD) test at p = 0.05.

RESULTS

QUALITATIVE TRAITS

Most of the study accessions had indeterminate growth type (68.1%) with only 31.9% being determinate (Table 2). Foliage density of 62.3% accessions was dense while 37.7% were intermediate. The study revealed that 98.5% of the accessions produced yellow flowers while white flowers were observed with only one accession. The majority of the accessions had a purple stem (91.3%) while only 8.7% were green. Stem hairiness was mainly intermediate for 65.2% accessions while 34.8% were dense.

Table 2. Qualitative variation at vegetative and flowering stages among the 69 tomato accessions.

        TraitObservationFrequencyPercentage
Growth typeDeterminate2231.9
 Indeterminate4768.1
Foliage densityDense4260.9
 Intermediate2231.9
 Sparse57.2
Flower colorWhite11.4
 Yellow6898.6
Stem colorGreen68.7
 Purple6391.3
Pubescence densityDense2434.8
 Intermediate4565.2    

A large proportion of the accessions recorded the presence of greening shoulder (79.7%) while only 20.3% showed uniform greening (Table 3). Fruit color at maturity indicated the predominance of red (95.6%) with only 4.4% of the accessions being yellow. Fruit shape varied being: round (66.7%), flattened (14.5%), highly rounded (5.8%), heart-shaped (4.4%), ellipsoid (2.9%), pyriform (2.9%) and cylindrical (2.9%). The shape of the fruit cross-section ranged being: round (85.51%), irregular (13.04%) and angular (1.45%). Fruit size varied being: very small (10.1%), small (17.4%), intermediate (42.0%), large (24.6%) and very large (42.0%).

Table 3. Qualitative variation in fruit characteristics among the 69 tomato accessions.

        TraitObservationFrequencyPercentage
Greening shoulderAbsent1420.3
 Present5579.7
Fruit colorRed6695.7
 Yellow34.3
Fruit shapeCylindrical22.9
 Ellipsoid22.9
 Flattened913.0
 Heartshaped34.3
 High rounded45.8
 Pyriform22.9
 Rounded4768.1
Fruit cross-section shapeAngular11.4
 Irregular913.0
 Round5985.5
Fruit sizeIntermediate2942.0
 Large1927.5
 Small1014.5
 Very large1115.9

Cluster analysis:- Cluster analysis identified two major clusters (Cluster I and II) as shown in Fig. 1. Cluster I had 63 accessions that were grouped into seven sub-clusters while cluster II had only six accessions all of which came from Madagascar. Accessions in clusters I and II all had purple and green stems, respectively. Sub-cluster ‘a’ had 17 accessions with the majority originating from South Africa and Madagascar. Most of the accessions in sub-cluster ‘b’ were from South Africa and Morocco while sub-cluster ‘c’ was dominated with accessions from Ethiopia. Sub-clusters‘d’, ‘e’, ‘f’ and ‘g’ had the least number of accessions evaluated grouped together. Sub-clusters, ‘d’, and ‘g’ had accessions from different origins while accessions from Morocco and Kenya dominated sub-clusters ‘e’ and ‘f’, respectively (see Fig. 2).

Fig. 1. Distribution of tomato accessions for first two principal components based on 10 qualitative traits.

Fig. 2. Unweighted pair-group method using arithmetic averages cluster analysis phenogram showing the relationships among the 69 tomato accessions.

Principal component analysis:- The first five components of the PCA explained 78.4% of total variations among the accessions, with the first two PCs contributing 40.7% (Fig. 1). PCA identified six traits, namely the presence of green shoulder, fruit size, exterior fruit color, pubescence density, flower color, and fruit cross-section shape as the main traits that contributed positively to PC1. However, the presence of green shoulder (0.414) and fruit size (0.336) contributed more positively to this PC compared to the rest of the traits. It was also observed that foliage density, growth type, stem color, and fruit shape had negative loadings to this component at −0.478, −0.445, −0.406 and −0.091, respectively (Table 4).

Table 4. Eigen values, proportion of variability and qualitative traits that contributed to the five principal components  in 69 tomato genotypes.

VariablePC1PC2PC3PC4PC5
Stem color−0.4060.2810.115−0.525−0.095
Flower color0.166−0.0540.661−0.1550.282
Growth type−0.4450.1910.1170.2020.400
Foliage density−0.480.0470.104−0.26−0.46
Pubescence density0.1780.256−0.193−0.5890.500
Green shoulder0.4140.006−0.135−0.277−0.018
Exterior fruit color0.232−0.0400.664−0.022−0.180
Fruit shape−0.091−0.5550.015−0.350−0.074
Fruit cross section shape0.0490.6310.1440.172−0.039
Fruit size0.3360.326−0.090−0.116−0.504
Eigen values2.4641.6091.5191.2970.947
% variation24.616.115.2139.5
Cumulative24.640.755.968.978.4                                   

Quantitative traits:-

Significant differences were observed for all the growth and fruit traits evaluated (Table 5, Table 6). Single leaf area was in the range 3.8–8.7 cm2 in accessions RV102107 and VI005895, respectively, while SPAD value ranged from 45.1 (VI030380) to 62.7 (VI030852) (Table 5). Days to flowering ranged between 39 d in accession VI005905 and 64 d in VI030375. Similarly, days to maturity ranged between 79.3 d and 127.3 d with accession VI005905 being the earliest to mature while accession VI030375 the latest. Accessions with the shortest and the longest fruit length recorded means of 3.3 cm (GBK 050580) and 11.9 cm (VI005986), respectively (Table 6). The average number of fruits per plant ranged from 8.3 (VI007539) to 442.8 (GBK 050580). Similarly, the mean fruit weight per plant ranged between 565.0 g (RVI02098 and VI006827) and 2759.0 g (VI006826). Correlation analysis among the quantitative traits showed that fruit weight per plant had a positive and significant association with fruit length (r = 0.28), fruit width (r = 0.30) and single leaf area (r = 0.16). However, the number of fruits per plant had a significant but negative correlation with days to maturity (r = −0.30), fruit length (r = −0.71) and fruit width (r = −0.66) (see Table 7).

Table 5. Quantitative Traits (mean ± SE) among the 69 tomato accessions.

s/nACC.NO.SLASPADDTFDTM
1GBK 0505804.7 ± 0.154.0 ± 0.550.5 ± 0.992.5 ± 0.3
2GBK 0505894.3 ± 0.153.5 ± 0.444.0 ± 0.9109.8 ± 0.5
3RV021144.4 ± 0.150.8 ± 0.549.0 ± 0.691.2 ± 0.5
4RV1018846.1 ± 0.152.8 ± 0.249.7 ± 0.8122.0 ± 0.6
5RVI018855.2 ± 0.252.2 ± 0.551.2 ± 0.698.2 ± 0.7
6RVI018878.1 ± 0.253.4 ± 0.354.5 ± 0.4102.0 ± 1.0
7RVI018885.6 ± 0.258.1 ± 0.362.3 ± 1.0116.7 ± 0.7
8RVI018966.5 ± 0.255.6 ± 0.353.8 ± 0.6113.3 ± 0.6
9RVI019837.1 ± 0.255.8 ± 0.261.5 ± 0.4113.3 ± 0.4
10RVI020986.6 ± 0.160.4 ± 0.442.0 ± 0.6120.5 ± 1.0
11RVI021006.1 ± 0.157.9 ± 0.442.0 ± 0.7112.3 ± 0.7
12RVI021025.7 ± 0.151.4 ± 0.242.7 ± 0.4116.7 ± 0.8
13RVI021046.8 ± 0.255.2 ± 0.452.2 ± 0.7109.2 ± 1.0
14RVI021073.8 ± 0.152.8 ± 0.340.3 ± 0.692.8 ± 0.9
15RVI021095.6 ± 0.351.3 ± 0.541.8 ± 0.6103.5 ± 1.3
16RVI021114.3 ± 0.151.1 ± 0.339.8 ± 0.5114.2 ± 1.2
17RVI021125.1 ± 0.156.6 ± 0.649.3 ± 0.4113.3 ± 0.9
18VI0058715.3 ± 0.154.8 ± 0.548.8 ± 0.892.7 ± 0.9
19VI0058725.8 ± 0.249.9 ± 0.452.7 ± 0.594.2 ± 0.9
20VI0058735.3 ± 0.345.9 ± 0.453.2 ± 0.6112.7 ± 0.7
21VI0058745.8 ± 0.152.3 ± 0.457.2 ± 0.5104.2 ± 1.1
22VI0058756.3 ± 0.356.7 ± 0.349.5 ± 0.6101.0 ± 1.0
23VI0058765.4 ± 0.251.9 ± 0.645.7 ± 0.696.0 ± 1.0
24VI0058775.5 ± 0.254.4 ± 0.351.0 ± 0.781.8 ± 0.6
25VI0058784.8 ± 0.157.1 ± 0.457.5 ± 0.6114.5 ± 0.8
26VI005889A5.6 ± 0.257.9 ± 0.440.7 ± 0.7113.8 ± 0.9
27VI0058958.7 ± 0.256.1 ± 0.440.8 ± 0.7108.5 ± 0.8
28VI0059054.1 ± 0.251.2 ± 0.237.5 ± 0.979.3 ± 0.7
29VI0059865.9 ± 0.251.4 ± 0.459.8 ± 0.6119.5 ± 0.8
30VI0059875.5 ± 0.352.6 ± 0.449.5 ± 0.6114.5 ± 0.8
31VI0059885.8 ± 0.251.4 ± 0.545.5 ± 0.6105.7 ± 0.7
32VI0059894.5 ± 0.250.9 ± 0.549.5 ± 0.9109.3 ± 0.7
33VI0059906.5 ± 0.258.8 ± 0.251.0 ± 0.6115.0 ± 1.0
34VI0059915.1 ± 0.155.3 ± 0.253.8 ± 0.7112.0 ± 1.1
35VI0064805.2 ± 0.156.7 ± 0.450.0 ± 0.797.8 ± 1.1
36VI006481-A4.0 ± 0.154.6 ± 0.354.3 ± 0.6114.3 ± 0.9
37VI0068256.2 ± 0.161.4 ± 0.553.2 ± 0.692.5 ± 1.0
38VI0068266.6 ± 0.158.5 ± 0.453.5 ± 0.6111.3 ± 1.4
39VI0068274.4 ± 0.251.4 ± 0.253.2 ± 0.5105.2 ± 0.7
40VI0068284.7 ± 0.155.3 ± 0.153.5 ± 0.694.8 ± 1.0
41VI0068324.5 ± 0.154.0 ± 0.349.3 ± 0.5114.7 ± 1.3
42VI0068337.5 ± 0.151.3 ± 0.151.8 ± 0.796.8 ± 0.7
43VI0068375 ± 0.357.0 ± 0.255.0 ± 0.6104.3 ± 0.8
44VI0068385.5 ± 0.150.0 ± 0.145.3 ± 0.7108.3 ± 0.8
45VI0068405.7 ± 0.256.2 ± 0.353.7 ± 1.088.7 ± 1.1
46VI0068415.4 ± 0.152.8 ± 0.555.0 ± 0.4118.0 ± 1.9
47VI0068425.8 ± 0.257.9 ± 0.453.8 ± 0.789.2 ± 0.9
48VI0068475.5 ± 0.151.1 ± 0.451.8 ± 0.7116.2 ± 0.5
49VI0068485.3 ± 0.254.8 ± 0.447.3 ± 0.7103.7 ± 1.1
50VI0068644.8 ± 0.151.5 ± 0.451.3 ± 0.8101.5 ± 0.8
51VI0068655.1 ± 0.154.6 ± 0.451.7 ± 0.793.3 ± 0.7
52VI0068696.8 ± 0.146.9 ± 0.352.8 ± 0.8103.2 ± 0.9
53VI006881-B5.5 ± 0.148.6 ± 0.754.7 ± 0.8109.2 ± 0.7
54VI0068924.6 ± 0.251.3 ± 0.361.2 ± 1.2108.2 ± 0.6
55VI0069725.1 ± 0.153.3 ± 0.452.0 ± 0.6108.7 ± 0.3
56VI0071084.8 ± 0.154.5 ± 0.239.0 ± 0.4113.3 ± 0.7
57VI0075396.4 ± 0.152.3 ± 0.354.2 ± 1.3114.7 ± 0.5
58VI0075405.6 ± 0.256.4 ± 0.356.7 ± 0.5118.8 ± 0.6
59VI0080986.8 ± 0.356.1 ± 0.258.5 ± 0.9119.2 ± 0.4
60VI0080994.5 ± 0.153.0 ± 0.450.2 ± 0.6105.0 ± 0.6
61VI0082346.0 ± 0.255.6 ± 0.338.2 ± 0.294.8 ± 0.4
62VI0089165.3 ± 0.254.0 ± 0.550.3 ± 0.7115.3 ± 0.7
63VI0303756.5 ± 0.260.8 ± 0.363.8 ± 1.1127.3 ± 0.6
64VI0303795.7 ± 0.251.4 ± 0.351.5 ± 0.8100.3 ± 0.7
65VI0303805.7 ± 0.345.1 ± 0.548.0 ± 0.5106.3 ± 0.5
66VI0303814.4 ± 0.348.1 ± 0.450.8 ± 0.5109.8 ± 0.6
67VI0308528.5 ± 0.362.7 ± 0.460.0 ± 0.4115 ± 0.5
68VI0350285.3 ± 0.253.6 ± 0.449.3 ± 0.591.5 ± 0.6
69VI0379484.4 ± 0.158.7 ± 0.449.5 ± 0.691.2 ± 0.8
 Lsd(p < 0.01)0.51**1.01**1.85**2.31**

S/no = serial number; ACC NO = accession number; SLA = single leaf area (cm2); SPAD = soil plant analysis development; DTF = days to 50% flowering; DTM = days to maturity; ** = highly significant.

Table 6. Quantitative fruit traits (mean ± SE) among the 69 tomato accessions.

s/nACC.NO.FLFWNFPPFWPP
1GBK 0505803.3 ± 0.01.9 ± 0.1442.8 ± 4.61212.0 ± 18.0
2GBK 0505893.9 ± 0.02.4 ± 0.0230 ± 2.4571.0 ± 9.0
3RV021144.8 ± 0.13.0 ± 0.0107.7 ± 1.4618.0 ± 14.3
4RV1018845.5 ± 0.13.2 ± 0.0135.0 ± 3.41143.0 ± 48.4
5RVI018858.9 ± 0.05.4 ± 0.042.7 ± 1.22351.0 ± 67.6
6RVI018877.4 ± 0.84.3 ± 0.347.7 ± 1.21636.0 ± 64.0
7RVI018887.3 ± 0.04.4 ± 0.019.7 ± 1.1789.0 ± 44.3
8RVI018969.4 ± 0.25.6 ± 0.028.7 ± 1.21719.0 ± 39.9
9RVI0198310.2 ± 0.15.0 ± 0.036.0 ± 0.62186.0 ± 24.0
10RVI020988.2 ± 0.14.4 ± 0.013.0 ± 0.9565.0 ± 44.0
11RVI021009.1 ± 0.15.8 ± 0.118.8 ± 0.81325.0 ± 63.2
12RVI021026.3 ± 0.14.0 ± 0.135.0 ± 1.3802.0 ± 43.3
13RVI0210410.2 ± 0.07.1 ± 0.120.3 ± 0.81210.0 ± 40.7
14RVI0210710.5 ± 0.16.0 ± 0.127.2 ± 1.32638.0 ± 160.5
15RVI021097.7 ± 0.45.0 ± 0.365.2 ± 1.91857.0 ± 70.9
16RVI021116.8 ± 0.55.8 ± 0.143.0 ± 0.61124.0 ± 48.8
17RVI021126.2 ± 0.13.3 ± 0.197.7 ± 1.7934.0 ± 51.4
18VI0058719.3 ± 0.36.1 ± 0.529.8 ± 0.72674.0 ± 69.4
19VI0058729.0 ± 0.35.6 ± 0.324.0 ± 1.01427.0 ± 67.0
20VI0058737.3 ± 0.04.5 ± 0.023.2 ± 1.91202.0 ± 124
21VI0058748.5 ± 0.35.8 ± 0.228.7 ± 0.82253.0 ± 74.2
22VI0058759.9 ± 0.36.9 ± 0.225.7 ± 0.81727.0 ± 51.1
23VI00587610.4 ± 0.47.3 ± 0.528.0 ± 1.72108.0 ± 106.7
24VI00587710.1 ± 0.06.9 ± 0.131.7 ± 0.62222.0 ± 36.4
25VI0058788.5 ± 0.15.3 ± 0.114.3 ± 0.8763.0 ± 53.4
26VI005889A8.0 ± 0.15.7 ± 0.119.0 ± 0.9816.0 ± 34.5
27VI0058959.3 ± 0.27.6 ± 0.226.7 ± 0.61613.0 ± 39.6
28VI0059053.5 ± 0.02.2 ± 0.038.5 ± 1.11203.0 ± 36.9
29VI00598611.9 ± 0.17.4 ± 0.011.0 ± 0.61018.0 ± 53.4
30VI0059878.6 ± 0.25.7 ± 0.125.3 ± 0.81052.0 ± 21.7
31VI0059888.8 ± 0.36.0 ± 0.247.3 ± 2.01823.0 ± 93.1
32VI0059895.0 ± 0.13.2 ± 0.1145.7 ± 2.3871.0 ± 31.0
33VI0059908.9 ± 0.15.4 ± 0.121.7 ± 1.51020.0 ± 68.9
34VI0059917.5 ± 0.54.6 ± 0.434.3 ± 0.41253.0 ± 15.0
35VI0064805.6 ± 0.23.7 ± 0.1125.8 ± 2.81718.0 ± 171.6
36VI006481-A6.9 ± 0.14.5 ± 0.0192.3 ± 0.81223.0 ± 17.2
37VI0068254.3 ± 0.12.2 ± 0.1146.8 ± 1.9622.0 ± 10.8
38VI0068267.7 ± 0.25.8 ± 0.240.5 ± 1.02759.0 ± 58.9
39VI00682710.6 ± 0.57.7 ± 0.231.5 ± 1.11637.0 ± 75.3
40VI0068283.8 ± 0.22.1 ± 0.0237.2 ± 2.6565.0 ± 23.7
41VI0068325.3 ± 0.13.2 ± 0.1115.5 ± 1.02341.0 ± 59.7
42VI0068335.5 ± 0.23.6 ± 0.154.8 ± 1.3954.0 ± 42.6
43VI0068378.4 ± 0.03.9 ± 0.064.8 ± 1.21777.0 ± 36.9
44VI0068387.9 ± 0.03.6 ± 0.123.8 ± 0.6812.0 ± 17.1
45VI0068405.6 ± 0.13.9 ± 0.2129.3 ± 1.21101.0 ± 10.4
46VI00684111.1 ± 0.57.6 ± 0.112.3 ± 0.71606.0 ± 90.9
47VI0068425.1 ± 0.13.2 ± 0.1162.2 ± 1.72125.0 ± 145.2
48VI0068479.2 ± 0.16.0 ± 0.115.8 ± 0.61018.0 ± 37.6
49VI0068485.4 ± 0.13.3 ± 0.1106.5 ± 2.01433.0 ± 105.4
50VI0068645.6 ± 0.13.5 ± 0.191.7 ± 0.81258.0 ± 41.6
51VI0068655.0 ± 0.14.1 ± 0.4126.5 ± 1.12477.0 ± 26.2
52VI0068695.2 ± 0.23.2 ± 0.1104.3 ± 0.81409.0 ± 9.6
53VI006881-B9.3 ± 0.46.1 ± 0.213.3 ± 0.81114.0 ± 66.0
54VI0068924.9 ± 0.02.4 ± 0.0102.7 ± 1.0887.0 ± 37.0
55VI0069727.0 ± 0.12.7 ± 0.1108.5 ± 1.11192.0 ± 30.0
56VI0071085.9 ± 0.23.8 ± 0.289.8 ± 1.11416.0 ± 25.1
57VI00753911.1 ± 0.27.4 ± 0.08.3 ± 0.4663.0 ± 36.5
58VI00754010.4 ± 0.17.4 ± 0.110.8 ± 0.51323.0 ± 61.9
59VI0080987.7 ± 0.14.5 ± 0.041.8 ± 0.71175 .0 ± 42.2
60VI0080998.4 ± 0.15.5 ± 0.053.2 ± 1.01269.0 ± 23.4
61VI0082347.5 ± 0.14.5 ± 0.148.2 ± 0.51369.0 ± 22.1
62VI0089167.3 ± 0.14.5 ± 0.065.7 ± 1.31589.0 ± 95.2
63VI03037510.1 ± 0.05.2 ± 0.130.7 ± 0.61841.0 ± 45.7
64VI0303798.9 ± 0.56.0 ± 0.117.3 ± 0.61110.0 ± 29.9
65VI0303807.0 ± 0.44.3 ± 0.353.5 ± 1.12115.0 ± 74.4
66VI0303817.5 ± 0.24.3 ± 0.242.0 ± 0.91539.0 ± 38.4
67VI03085210.2 ± 0.26.3 ± 0.149.2 ± 0.51941.0 ± 17.4
68VI0350286.3 ± 0.33.4 ± 0.128.0 ± 1.0881.0 ± 49.2
69VI0379483.6 ± 0.12.1 ± 0.1212.7 ± 0.71222.0 ± 24.5
 LSD(p < 0.01)0.69**0.48**3.96**182.69**

S/no = serial number; ACC NO = accession number; FL = fruit length; FW = fruit width; NFPP = number of fruits per plant; FWPP = fruit weight per plant (g); LSD = least significant difference; ** = highly significant.

Table 7. Correlation table for the quantitative traits among the 69 accessions.

 DTFDTMFLFWNFPPSLAFWPPSPAD
DTF       
DTM0.24**      
FL0.20**0.35**     
FW0.090.27**0.90**    
NFPP−0.02−0.30**−0.71**−0.66**   
SLA0.23**0.30**0.49**0.43**−0.37**  
FWPP0.04−0.20**0.28**0.30**−0.13*0.16* 
SPAD0.100.32**0.24**0.21**−0.12*0.28**0.066

DTF = days to 50% flowering; DTM = days to maturity; FL = fruit length; FW = fruit width; NFPP = number of fruits per plant; SLA = single leaf area (cm2); FWPP = fruit weight per plant (g); SPAD = soil plant analysis development; ** = highly significant.

DISCUSSION:-

From the Dendrogram, it was not possible to group all the tomato accessions from the same collection sites or location into their specific groups, but it was clear that most of the study accessions are quite related. It is also likely that continuous recycling of tomato seeds by farmers and selections leading to massive segregation have contributed to the wide phenotypic variability of the tomato crop. However, stem color clearly separated the accessions into two major clusters, being those with a purple stem and those with a green stem.

Significant differences were observed among the 69 accessions for all the quantitative traits evaluated. This was in agreement with the findings of Kumar et al. (2013) who reported significant variation in days to maturity, the number of fruits per plant and average fruit weight among tomato accessions. Several authors have shown a relationship between SPAD value and the nitrogen content in plant leaves (Sexton and Carol, 2002; Wang et al., 2004). This implies that accessions with high SPAD values have higher levels of nitrogen. Variations in the current study could have been attributed to the differences in genetic and environmental conditions from which the accessions were obtained. This was expected since different genotypes perform differently in the same environment (Blay et al., 1999).

The positive and significant association of fruit weight with leaf area showed that plants with a large leaf area tend to have higher yields compared to those with a smaller leaf area. Similar findings were reported by Wali and Kabura (2014). This may be explained by the greater number of photosynthetic products available for partitioning to fruit production in plants with large leaf area. Similarly, fruit weight, which is a function of fruit size, had a predictably positive and significant association with fruit length and fruit diameter. Similar findings were reported by Islam et al. (2010). The authors concluded that yield had a significant positive correlation with fruit diameter.

The significant but negative correlations observed for a number of fruits per plant with days to maturity, fruit length and fruit width could be explained by the fact that with the increased number of days to 50% fruit maturity, the yield decreased, and this demonstrated that early maturing cultivars had higher yields than late maturing cultivars. Similarly, the number of fruits per plant had a significant correlation with fruit weight per plant (r = −0.13) because the accessions which had the highest numbers of fruits per plant had relatively small-sized fruits.

In summary, the variation observed in this study provides a potential source of genetic diversity for tomato crop improvement. However, a comparatively high level of similarity was also revealed among accessions from the same region for most of the characters studied. This suggests avoiding the use of material with a similar genetic background, as well as avoiding resource use on materials with the least relevant traits.

ACKNOWLEDGMENTS

Support for this research was provided by the United States Agency for International Development through the Partnerships for Enhanced Engagement in Research (PEER) program Sub-Grant Number: PGA–2000003426. The authors thank Dr. Tsvetelina Stoilova of the AVRDC- World Vegetable Center in Arusha , Tanzania for the provision of the bulk of the tomato seeds.

REFERENCES

1 S. Peralta Tomatoes in the Galapagos Islands: morphology of native and introduced species of Solanum section Lycopersicon.

2 J.P SIbuaaTomato as a source of carotenoids and polyphenols targeted to cancer prevention.

3 B.J Kibaaki & Abdul HazwuCorrelation studies in tomato ( Lycopersicon lycopersicum L . Karst) as affected by mulching and cultivar during the heat period in the semi-arid region of Nigeria.

AUTHOR AFFILIATION

DR. NASOD RIZAE

 KEMJI P.E

 DODE K.O.

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