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Heritability Analysis and Phenotypic Characterization of Spider Plant (Cleome gynandra L.) for Yield

Heritability Analysis and Phenotypic Characterization of Spider Plant (Cleome gynandra L.) for Yield Hindawi Advances in Agriculture Volume 2018, Article ID 8568424, 11 pages https://doi.org/10.1155/2018/8568424 Research Article Heritability Analysis and Phenotypic Characterization of Spider Plant (Cleome gynandra L.) for Yield 1 1 1 2 Ann Kangai Munene , Felister Nzuve, Jane Ambuko , and Damaris Odeny Department of Crop Science and Crop Protection, University of Nairobi, Kenya eTh International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Nairobi, Kenya Correspondence should be addressed to Ann Kangai Munene; wakaireann@gmail.com Received 30 November 2017; Revised 30 March 2018; Accepted 12 July 2018; Published 31 July 2018 Academic Editor: Mumtaz Cheema Copyright © 2018 Ann Kangai Munene et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Knowledge on phenotypic diversity among existing spider plant accessions is a milestone in the improvement of spider plant, which is a highly nutritious indigenous vegetable in Kenya. A study involving agronomic and morphological characterization of 49 spider plant accessions assembled from East and South Africa was carried out at the University of Nairobi Field Station for two seasons in a randomized complete block design with three replications. Phenotypic data was collected on growth habit, flower, petiole, leaf and stem colour, petiole, leaf and stem hairiness, number of leaves per plant, plant height, number of primary branches, leaf length and width, single leaf area, and chlorophyll content according to FAO descriptors with modifications. Data was analyzed using both DARwin sow ft are V6 and Genstat Version 14. We observed significant differences among the traits implying great genetic variability among the evaluated spider plant accessions. The high genetic variation was further validated using the Unweighted Pair Group Method with Arithmetic mean (UPGMA) clustering method with stem and flower colour as key traits. The 49-spider plant accessions were clustered into 2 major groups, each consisting of Kenyan and South African accessions. Stepwise regression revealed that plant height had the most influence on yield in terms of number of leaves per plant. We also observed high heritability for several traits including days to flowering (91%), number of leaves per plant (99%), plant height (99%), number of primary branches (94%), chlorophyll content (94%), and single leaf area (87%). Our results reveal the high genetic variation between dieff rent spider plant accessions, especially from dieff rent regions of Africa that could be further exploited to improve productivity in the plant. The high heritability of most of the yield related traits is promising for improving yield in the crop through direct selection. Coastal regions. The key counties producing the crop include 1. Introduction Kisii, Nyamira, Kericho, Migori, and Siaya [4]. Despite this Cleome gynandra, also knownas “Africanspider plant”, is wide adaptation and continued increase in production and among the most important traditional leafy vegetables widely consumption, there have been limited efforts towards its used in Africa [1]. It belongs to the family of Capparaceae. improvement. There is lack of critical information on the It is also an erect herbaceous annual herb that is mainly extent and structure of phenotypic variation crucial for the self-pollinated [2]. The plant is highly nutritive and con- breeding and conservation of spider plant [2, 5]. Genetic tains health promoting bioactive compounds important in diversity is particularly useful in characterizing individual combating malnutrition and reducing human degenerative accessions and cultivars, in detecting genetic materials with diseases. Spider plant is native to the Southern Africa, novel genes and thereby rescuing them from genetic erosion, Western Africa, Central Africa, Eastern Africa, and South and as a general guide, in selecting appropriate parents in breeding programs. Most of the genetic diversity observed in East Asia [3]. In South Africa, spider plant has been found to grow in the wild in KwaZulu-Natal, Free State, Northern spider plant in Kenya and South Africa has traditionally been Cape, Limpopo, and North West provinces [3]. In Kenya, the maintained by farmers in situ. This poses the risk of species plants are mainly found in Western, Rift Valley, Eastern, and extinction due to loss of natural habitat as humans continue 2 Advances in Agriculture to exploit and develop land, divert water o fl w, and change Table 1: List of Kenyan and South African spider plant accessions evaluated in the study. the environment. Secondly, as human population continues to increase, there is pressure on natural land being cleared Entry Accession no. Country of origin Region by human activity. The need for cultivation, conservation, ke 1 1 Kenya Siaya and characterization of spider plant remains imperative in ke 2 2 Kenya Bungoma maintaining the integrity of the genetic information and ke 3 3 Kenya Kakamega diversity. ke Mendelian analysis of discrete morphological traits can 4 4 Kenya Kitale ke be used to estimate genetic diversity in plants [6] and has 5 5 Kenya Mbale ke been successfully used in spider plant [5]. Some of the key 6 6 Kenya Bomet traits that have been used as a guide in selection for good ke 7 7 Kenya Busia genotypes in previous studies included high heritability traits ke 8 9 Kenya Marakwet such as days to flowering, plant height, and number of leaves ke 9 10 Kenya Kisumu per plant [7]. Omondi [7] observed that higher leaf yield, ke 1 11 Kenya Homabay plant uniformity, longer vegetative phase, late flowering, and ke 11 12 Kenya Nandi drought tolerance could form the best criterion in selection ke 12 13 Kenya Kakamega of good performing spider plant accessions. However, for ke an efficient crop improvement program, information on 13 14 Kenya Kisii ke estimates of heritability for these desirable traits must be 14 15 Kenya Mbale ke established [8]. Due to limited knowledge on the genetic 15 16 Kenya Meru variability, more research remains of the essence to elucidate sa 16 1959 South Africa Mpumalanga the genetic and phenotypic diversity of existing spider plant sa 17 1988 South Africa Mpumalanga accessions. u Th s, the main thrust of this study was to sa 18 2000 South Africa Mpumalanga understand the extent of phenotypic diversity and heritability sa 19 2232 South Africa Northern province of qualitative traits among 49 spider plant accessions assem- sa 2 2241 South Africa Northern province bled from Kenya and South Africa. Promising spider plant sa 21 2249 South Africa Northern province accessions can be utilized in various breeding programs and sa have the potential of enhancing its utilization while aiding to 22 2279 South Africa Northern province sa gfi ht hidden hunger in Kenya. 23 2289 South Africa Mpumalanga sa 24 2299 South Africa Mpumalanga ke 2. Materials and Methods 25 30316 Kenya Western ke 26 31990 Kenya Western 2.1. Plant Materials. The study used 49 spider plant acces- ke 27 31992 Kenya Western sions, mainly local landraces assembled from 3 sources: Gene ke 28 45426 Kenya Western bank of Kenya (25), Gene bank of South Africa (9), and ke 29 45446 Kenya Central Kenyan farmers’ landraces (15) (Table 1). ke 3 45451 Kenya Central ke 31 50259 Kenya Kisii 2.2. Experimental Design and Study Site. The experiments ke were carried out at the University of Nairobi’s Kabete Field 32 50264 Kenya Nyamira ke station (Nairobi, Kenya) for two seasons from March 2014 to 33 50265 Kenya Nyamira ke May 2014 and October 2014 to January 2015. The experiments 34 50273 Kenya Nyamira were laid out in a randomized complete block design with ke 35 50290 Kenya Nyamira ∘ 󸀠 three replications. Kabete Field station lies at 36 41 Eand ke 36 50296 Kenya Nyamira 01 15’S with an altitude of 1737 m above sea level. It receives an ke ∘ 37 50298 Kenya Nyamira average temperature of 23 Cwith a bimodal rainfall pattern ke 38 50299 Kenya Nyamira and an annual precipitation of 600 mm to 1800 mm. The soil ke 39 50307 Kenya Kisii type is well drained very dark reddish, brown to dark red ke 4 50319 Kenya Nyamira friable clay locally known as Kikuyu red clay loam with an ke average pH of 6.2 [9]. 41 50325 Kenya Kisii ke 42 50326 Kenya Nyamira ke 2.3. Crop Husbandry. Pregermination for each accession was 43 50328 Kenya Nyamira done for 72 hours under treatment with 0.2% gibberellic ke 44 50330 Kenya Nyamira acid to break seed dormancy and enhance germination [10]. ke 45 50332 Kenya Kisii Each individual accession was planted by hand in two rows ke 46 50339 Kenya Nyamira comprising ten seeding holes per row (20 plants in a plot). ke 47 50353 Kenya Nyamira Row plots were 3 m in length with inter-row spacing of ke 48 50584 Kenya Nyamira 30 cm and intra-row spacing of 30 cm. Farmyard manure ke 49 50600 Kenya Kisii was applied to rows at the rate of 10.5 g/accession and mixed ke sa with soil at planting. Hand weeding was done throughout the =originated from Kenya; =originated from South Africa. Advances in Agriculture 3 Table 2: Character, descriptor, and codes used for characterization of qualitative traits in spider plant accessions. S/No. Character Descriptor and code 1Growthhabit Erect(2), semi-erect(4) and prostrate(6) 2 Flower colour White(1),purple(2) and pink(3) 3 Stem colour Green(1),pink(2),violet(3) and purple(4) 4 Stem hairiness Glabrous(1),weak/sparse(3),medium(5) and profuse(7) 5 Petiole colour Green(1),pink(2),violet(3) and purple(4), 6 Petiole hairiness Glabrous(1),weak/sparse(3),medium(5) and profuse(7) 7 Leaf colour Dark green(1) and light green(2), 8 Leaf hairiness Glabrous(1),weak/sparse(3),medium(5) and profuse(7) Source: Food and Agriculture Organization of the United Nations (FAO, 1995); numbers in brackets on the right-hand side are the corresponding descriptor codes listed in the FAO publication with modifications during the development of the list. experimental period. The experiment was conducted under Heritability in the broad sense was estimated as a ratio of rain-fed conditions with supplemental overhead irrigation genotypic variance to the phenotypic variance and expressed when required. in percentage [14] as per the following equation. 2.4. Data Collection and Analysis. There were two sets of data Heritability (𝐻 )=( ×100) (1) collected in the study, namely, qualitative (morphological) and quantitative (agronomic). where V is the genotypic variance and V is the phenotypic g p variance. 2.5. Qualitative Traits. Spider planttraitsthatwere consid- Genotypic variance (𝜎 𝑔 ) was derived by subtracting ered qualitative included growth habit, owe fl r colour, stem error mean sum of squares (EMS) from the genotypic mean colour, stem hairiness, petiole colour, petiole hairiness, leaf sum of squares (GMS) and divided by the number of colour, and leaf pubescence based on the list of modified spi- replications as given by the following equation. der plant descriptors [11] (Table 2). Three randomly selected plants were tagged per accession per replicate during crop 𝑆 𝜎 𝑔=𝑆𝑀𝐺− (2) growth, before ow fl ering. The data was subjected to DARwin 5.0 sowa ft re as described by Perrier and Jacquemoud-Collet where [12]. Euclidean distance matrix and hierarchical clustering analyses of Unweighted Pair Group Method of Arithmetic GMS is the genotype mean sum of squares, EMS is averaging were used to estimate dissimilarities among the the error mean sum of squares, and r is the number of accessions and results displayed in a dendrogram. This replications. was followed by the identification of the most significant descriptors contributing to most phenotypic variation among Phenotypic variance (𝜎 𝑝 ) was derived by adding genotypic the spider plant accessions through a stepwise regression variance with error variance as per the following equation. analysis. 2 2 2 (3) 𝜎 𝑝=𝜎 𝑒+𝜎 𝑔 2.6. Quantitative Traits. All the yield and yield related traits were considered quantitative, including days to 50% flower- 3. Results and Discussions ing, SPAD values, plant height, number of primary branches, leaf length, leaf width, single leaf area, and number of leaves 3.1. Qualitative Traits. There were three distinct o fl wer per plant. Using Genstat version 14 software as described colours displayed by the spider plant accessions: purple, by [13], the data was subjected to Analysis of Variance to pink, and white. Among these, the purple flower colour was establish any significance differences among the traits and to the most dominant among the Kenyan accessions at 49% obtain genotype means which were then separated using the (Table 3) while the most dominant flower colour among Fishers protected least significant differences (LSD) at P < the South African accessions was white. Most of the South 0.05. African accessions displayed a green stem with a green petiole To establish the relationship among the traits collected, a as opposed to the Kenyans accessions, which displayed two-tail correlation analysis was performed to estimate quan- purple stems and pubescence. Previous study by Masuka and titative relationships among the traits and also to identify Mazarura [15] reported that purple-stemmed plants tended those traits that could be of great signicfi ance in a spider plant to be more hairy (trichomes) than the green-stemmed plants. breeding program. Anthocyanins have been implicated as responsible for the 𝐸𝑀 𝑉𝑝 𝑉𝑔 4 Advances in Agriculture fi Table 3: Morphological descriptors recorded for the 49 eld grown spider plant accessions for the combined season. Entry Accession no. Origin Flower colour Stem colour Petiole colour Stem hairiness Petiole hairiness Leaf colour Leaf hairiness Growth habit 1 1 Kenya Purple Purple Green Profuse Medium dark green Medium Erect 2 2 Kenya White Purple Pink Profuse Medium light green Sparse Erect 3 3 Kenya Pink Purple Pink Profuse Medium dark green Sparse Erect 4 4 Kenya Pink Purple Pink Profuse Medium light green Medium Erect 5 5 Kenya White Purple Purple Profuse Profuse light green Profuse Erect 6 6 Kenya Pink Purple Pink Profuse Profuse dark green Medium Erect 7 7 Kenya Pink Purple Purple Profuse Medium dark green Medium Erect 8 9 Kenya White Purple Purple Profuse Profuse dark green Sparse Erect 9 10 Kenya Purple Purple Purple Medium Medium light green Sparse Erect 1 11 Kenya Pink Purple Purple Medium Medium dark green Medium Erect 11 12 Kenya Pink Purple Purple Profuse Medium light green Sparse Erect 12 13 Kenya Purple Purple Purple Medium Medium light green Sparse Erect 13 14 Kenya Purple Green Purple Profuse Profuse dark green Medium Erect 14 15 Kenya Pink Purple Purple Medium Sparse dark green Sparse Erect 15 16 Kenya Pink Purple Pink Medium Sparse light green Sparse Erect 16 1959 S. Africa Pink Purple Pink Profuse Medium light green Medium Erect 17 1988 S. Africa White Green Green Sparse Sparse light green Sparse Semi erect 18 2000 S. Africa White Green Green Glabrous Glabrous light green Glabrous semi erect 19 2232 S. Africa White Green Green Glabrous Glabrous dark green Glabrous Erect 2 2241 S. Africa White Green Pink Sparse Sparse light green Sparse Erect 21 2249 S. Africa White Green Pink Glabrous Glabrous light green Glabrous Erect 22 2279 S. Africa White Green Green Glabrous Glabrous light green Glabrous Semi erect 23 2289 S. Africa White Green Pink Medium Sparse dark green Sparse Erect 24 2299 S.Africa White Green Green Glabrous Sparse light green Glabrous Erect 25 30316 Kenya Purple Purple Purple Profuse Medium dark green Sparse Erect Advances in Agriculture 5 Table 3: Continued. Entry Accession no. Origin Flower colour Stem colour Petiole colour Stem hairiness Petiole hairiness Leaf colour Leaf hairiness Growth habit 26 31990 Kenya Purple green Green Medium Sparse light green Sparse Erect 27 31992 Kenya Pink purple Green Profuse Medium dark green Medium Erect 28 45426 Kenya Purple Purple Green Profuse Sparse dark green Sparse Erect 29 45446 Kenya White Purple Purple Profuse Medium dark green Sparse Erect 3 45451 Kenya Pink Purple Purple Profuse Profuse dark green Medium Erect 31 50259 Kenya Pink Purple Purple Profuse Medium dark green Sparse Erect 32 50264 Kenya Purple Purple Purple Profuse Medium dark green Sparse Erect 33 50265 Kenya Purple Purple Purple Profuse Medium dark green Medium Erect 34 50273 Kenya Purple Purple Purple Profuse Medium dark green Sparse Erect 35 50290 Kenya Purple Purple Purple Profuse Medium dark green Medium Semi erect 36 50296 Kenya Purple Purple Purple Profuse Medium dark green Medium Erect 37 50298 Kenya Purple Purple Purple Medium Sparse light green Sparse Semi erect 38 50299 Kenya Purple Purple Purple Profuse Medium dark green Sparse Erect 39 50307 Kenya Purple Purple Purple Medium Medium dark green Sparse Erect 4 50319 Kenya Purple Purple Purple Profuse Medium dark green Medium erect 41 50325 Kenya Pink Purple Purple Medium Medium dark green Sparse erect 42 50326 Kenya Purple Purple Purple Profuse Medium dark green Sparse erect 43 50328 Kenya Purple Purple Purple Profuse Medium dark green Sparse erect 44 50330 Kenya Purple Purple Purple Profuse Medium dark green Sparse erect 45 50332 Kenya Purple Purple Purple Profuse Medium dark green Medium erect 46 50339 Kenya Purple Purple Purple Profuse Medium dark green Sparse erect 47 50353 Kenya Purple Purple Purple Profuse Medium dark green Medium erect 48 50584 Kenya Purple Purple Purple Medium Medium dark green Sparse erect 49 50600 Kenya Purple Purple Purple Profuse Medium dark green Sparse erect 6 Advances in Agriculture stem pigmentation in most herbaceous plants [16] and have Kisii region grouped together suggesting some degree of also been widely studied for their potential medicinal value similarity in their morphological traits. Most of the Kenyan [17]. Although spider plants have been traditionally used farmers’ landraces clustered together based on their origin. There were major overlaps with the accessions assembled for medicinal purposes [18], the obvious contrast between South African and Kenyan accessions in their anthocyanin from the gene bank implying that they could have same content calls for more studies in order to elucidate the benefits genetic makeup. A study by K’opondo [5] has demonstrated a close relationship among spider plant genotypes following of the variations observed. Presence of trichomes, on the other hand, has been associated with insect resistance in the evaluation of the variability in seed proteins among them. several studies including soybean [19], pigeonpea [20], and In addition, this uniformity could also arise from the self- Brassicaceae [21]. Trichomes are considered a domestication pollination status of spider plant. However, more character- trait and are often more abundant in unadapted landraces ization needs to be done to validate such findings. The cluster analysis, which clearly grouped the accessions according to than in improved germplasm. The absence of trichomes in South African accessions may suggest that they have their geographical origin, suggests that crop improvement undergone much more intense selection cycles than the of spider plant could be achieved through exploiting the variation revealed. However, the current cluster analysis was Kenyan accessions, although more studies would need to be done to confirm this fact. done using morphological traits, which can be influenced Erect growth habit was more dominant and was observed by several environmental factors. There will be need to in 90% of the accessions as opposed to the semi-erect growth undertake a more detailed genetic analysis using molecular habit observed among 10% of the accessions. This observation markers to confirm the existence of genetic variation across agrees with earlier findings [22], which reported over 80% the different geographical regions. There is need for specific erect growth in the studied spider plant accessions. Other regional breeding efforts to target preferred traits [24, 25]. past research has also shown that majority of the spider plant morphotypes present an erect type of growth [5]. Growth 3.3. Quantitative Traits habit is crucial in vegetable breeding as reported in other indigenous vegetables [23]. Bushy growth habit results in 3.3.1. Analysis of Variance. Spider plant accessions showed significant differences (P <0.05) with no seasonal eeff ct for many small leaves arising from numerous shoots that are not a preference trait to producers while the erect growth habit all the traits, namely, days to 50% flowering, single leaf with only primary and secondary branches maximizes the area, leaf length and width, chlorophyll content, number of leaves per plant, number of primary branches, and plant leaf area. This implies that yield improvement in spider plant could be exploited through selection of genotypes exhibiting height (Table 4), implying the existence of variability for the erect growth habit and therefore large leaf size. Further respective traits among spider plant accessions. Accessions that exhibited longer days to 50% flowering also yielded more reports have suggested that, in mixed cropping, farmers could adopt the semi-erect type whereas the erect types are ideal for leaf count. Late o fl wering enables a plant to have a longer vegetative phase during growth period [7]. Past research intercrop adaptability [14]. has associated late flowering with increased leaf yield and 3.2. Cluster Analysis. Sufficient phenotypic variation was consequently early o fl wering as a limit to leaf yield in other indigenous vegetables [23]. This suggests that late flowering observed among the accessions as revealed by the cluster analysis (Figure 1). Two major clusters, namely, clusters 1 would be a good selection criterion for yield improvement in spider plant. and 2, were distinguished using the eight morphological Other traits that contributed to increased leaf count descriptors. Cluster 1 included 9 accessions of South African origin with an exception of one Kenyan accession 1959 while were plant height and number of primary branches. Kenyan accessions were taller than the South African accessions cluster 2 is comprised of 40 Kenyan accessions inclusive with plant height varying from 21 cm for accession 2249 to of one South African origin. Stem and petiole colour were the major traits that contributed to the Kenyan accession 113 cm for accession 50296. The Kenyan accessions performed better than South African genotypes for the number of leaves 31990 grouping together with the South African accessions per plant, number of primary branches, leaf length, leaf that were mainly green stemmed with green petiole. The exceptional South African accession grouped together with width, plant height, single leaf area, and chlorophyll content conforming to past research by Wasonga [22]. The best 5 the Kenyan accessions due to the purple stem colour and pro- fuse pubescence that were predominant among the Kenyan outstanding accessions with regard to yield related traits like 50% flowering, single leaf area, and number of leaves per plant accessions. This clearly revealed the differences in the genetic included Kenyan accessions: 3, 7, 45451, 50296, and South makeup of the accessions from the two regions. However, the South African accessions 2279 and 2000, which were African accession 2241 (Table 5). collected from the Northern Province, showed similarity in their phenotypic traits. Most of the Kenyan gene bank 3.3.2. Correlation among the Traits. Knowledge of the cor- accessions, namely, 50339, 50330, 50328, 50326, 50299, and relations among yield and the yield related traits is of 50273, from Nyamira region clustered closely together with considerable importance in crop improvement because it aids accession 30316 from Western region despite being collected in indirect selection [26]. There was positive and significant from dieff rent regions. Additionally, Kenyan accession 45451 correlation between leaf length, leaf width, and leaf area from central region and Kenyan accession 14 collected from with number of days to 50% o fl wering Table 6. This agrees Advances in Agriculture 7 Cluster 2 2249 Cluster 1 0 1 South African gene bank accessions Kenyan gene bank accession Kenyan farmer’s landraces Figure 1: Phenogram showing relationship among accessions characterized using morphological traits. with the findings of Kiebre et al. [27] who also reported number of the branches and the taller the plant, the higher a positive signicfi ant correlation between number of days the number of leaves. Single leaf area correlated positively to 50% flowering with leaf length and width. This further with leaf length, width, and days to 50% flowering at r = suggests that the late flowering genotypes could be selected 0.92, r = 0.88, and r = 0.21, respectively. As expected, the leaf area would be determined by its length and width suggesting for their big size, which is a crucial trait to the producers who regard leaf biomass as key in leafy vegetables production. the longer and wider the leaf, the bigger the leaf area. This There was a significant positive correlation between plant suggests leaf length and width as important traits in selecting height and number of primary branches conforming to the for vegetative yield in spider plant. results of Kiebre et al. [27] indicating the taller the plant, However, there was a nonsignificant negative correlation the more the number of primary branches. This is further between leaf size and leaf yield indicating the more the supported by the observed correlations, where yield in terms number of leaves in the plant, the smaller the leaves. Yield is of number of leaves per plant had a positive and signicfi ant influenced by complex soil plant interactions in many crops. correlation with plant height (r = 0.69) and number of In this study, the chlorophyll content measured in SPAD value primary branches (r = 0.63) implying that the higher the had a positive significant correlation with number of leaves 8 Advances in Agriculture Table 4 (a) Analyses of variance showing the mean squares for the agronomic traits in Cleome gynandra season one (April-July 2014). Source of variation d.f. DTF LL LW NPB NLPP PH SLA SPAD Rep 2 4.3 0.6 1.7 1.6 27.9 6.5 0.4 1 Genotype 48 34.7∗ 5.2∗ 16.3∗ 14.7∗ 6895.6∗ 2734.0∗ 8.1∗ 165.4∗ Residual 96 1 0.2 1.4 0.3 13.4 8.2 0.4 2.1 Total 146 (b) Analyses of variance showing the mean squares for the agronomic traits in Cleome gynandra season one (October-July 2014). Source of variation d.f. DTF LL LW NPB NLPP PH SLA SPAD Rep 2 5 0.5 0.5 0.4 1.5 3.2 0.6 3.6 Genotype 48 31.1∗ 5.1∗ 16.5∗ 11.9∗ 6961.3∗ 2723.8∗ 7.9∗ 139.5∗ Residual 96 0.8 0.1 0.5 0.5 17.6 6.4 0.2 4.3 Total 146 (c) Analyses of variance showing the mean squares for the agronomic traits in Cleome gynandra for the combined seasons. Source of variation d.f. DTF LL LW NPB NLPP PH SLA SPAD Rep 2 9.1 1 1.2 1.6 16 4.7 0.9 3.2 Genotype 48 64.6∗ 10.3∗ 32.6∗ 26.1∗ 13840.2∗ 5451.1∗ 15.9∗ 300.8∗ Season 1 161.6∗ 1.0∗ 4.1∗ 2.1∗ 54 33.4∗ 2.1∗ 4.8∗ Genotype Season 48 1.2 0.1 0.2 0.4 16.7 6.7 0.1 4.1 Residual 194 0.9 0.2 0.9 0.4 15.5 7.3 0.3 3.2 Total 293 ∗Significant at P<0.05, DTF: days to 50% flowering, SLA: single leaf area (cm ), LL: leaf length (cm), LW: leaf width (cm), NLPP: number of leaves per plant, NPB: number of primary branches, PH: plant height (cm), and SPAD: soil plant analysis development. per plant (r = 0.45), number of primary branches (r = 0.54), broad sense heritability were estimated for number of leaves and plant height (r = 0.59). This contradicts the findings of per plant, plant height at 99%, and SPAD value at 96%. [28] who reported negative correlations between chlorophyll Leaf width exhibited a moderately lower percentage at 78% readings with yield related traits except for plant height in followed by single leaf area and leaf length at 86% and 89%, beans. This positive significance correlation between SPAD respectively (Table 8). High heritability plays a great role in values and yield related traits calls for more studies to selection for crop improvement as the traits to be improved elucidate this phenomenon. Leaf yields may be improved depend immensely on their heritability and variability [27]. through selection of accessions that showed high leaf count In this study, the genotypic variance of all traits was higher than the environmental variance implying that much of the as well as large single leaf area. phenotypic variation among the accessions was attributed to variation in genotype as opposed to the environment. The 3.4. Stepwise Regression. The most importanttraitsthathave high estimates of heritability displayed in the study suggest a considerable effect on the dependant variable are verified that selection for yield improvement in spider plant could through a stepwise regression analysis. The traits selected be based on traits like number of leaves per plant and plant through the regression model can then be used as a selec- height. tion criterion for indirect selection in a breeding program [29]. A multiple linear regression analysis was calculated by 4. Conclusions and Recommendations considering the number of leaves as the dependent variable and other characters as the independent variables. Results of This study reported the existence of significant phenotypic regression analysis showed that plant height had a signicfi ant variation in Cleome gynandra as evidenced by the mor- influence on yield (R =46.7,Pvalue≤ 0.05) (Table 7). This phological characterization which clearly distinguished the implies that selection based on plant height will influence and accessions from the two regions. The new knowledge gener- increase vegetative yield in C. gynandra. This further agrees ated on the spider plant morphological structure could oeff r with other n fi dings by Nwangburuka et al. [30] in vegetable a great potential in developing relevant genetic and genomic C. olitorius where plant height was found to significantly resources for spider plant breeding programs. It is also clear increase leaf yield. that indirect selection for improved spider plant accessions could be based on the yield related traits like number of 3.5. Heritability Estimates for Yield and Yield Related Traits. leaves per plant, plant height, number of primary branches, The estimates of heritability in broad sense for all the traits and days to flowering which exhibited high heritability. This ranged from 78% to 99% (Table 8). High percentages of study recommends the complementation of morphological Advances in Agriculture 9 Table 5: Mean comparison of the quantitative traits of 49 spider plant accessions from Kenya and South Africa grown in the University of Nairobi Field at Kabete, for the two combined seasons. Entry Accession No. Origin DTF LL LW NPB NLPP PH SLA SPAD 1 1 Kenya 39.7 5.1 14.2 6.3 105 38.3 8.7 56.4 2 2 Kenya 45.7 6.4 11.5 5.7 58.8 31.5 8.8 57.6 3 3 Kenya 45.3 6.7 17 7 112.2 41 10.9 50.3 4 4 Kenya 43.8 5.2 13.8 7.5 75.8 36.7 8.7 56.9 5 5 Kenya 45.3 5 13.2 7.5 53.8 46.8 8.3 57.6 6 6 Kenya 39.7 5 11.7 7.5 57.2 47.8 7.8 56.9 7 7 Kenya 45 5.9 16 7.7 91.3 51.2 9.9 53 8 9 Kenya 45.5 6.2 14.3 6.5 94.3 39 9.6 56.6 9 10 Kenya 41.5 5.6 11.7 5.7 68 40.7 8.3 58.3 1 11 Kenya 45 3.6 10.6 5.5 100.5 40.1 6.3 56.8 11 12 Kenya 46 4.6 11.9 7.5 61 42.2 7.6 58.8 12 13 Kenya 37.8 5 13.1 6.2 64.8 38.3 8.3 55.9 13 14 Kenya 39.8 4.7 11.3 7.8 83.3 63.2 7.4 53.3 14 15 Kenya 38.7 3.7 9.3 5.7 55.7 37.8 6 46.7 15 16 Kenya 45.2 7.8 15.6 9 75.7 75.5 11.2 61.6 16 1959 S. Africa 43.8 5.8 12 6.7 89.2 34.3 8.5 54.3 17 1988 S. Africa 34.2 6.8 12.6 5.7 50.7 45.2 9.5 49.9 18 2000 S. Africa 32.8 6.5 13.6 4.2 19.7 30.8 9.6 53.1 19 2232 S. Africa 39.8 5.3 10 4.7 56 26.3 7.4 24.3 2 2241 S. Africa 45.3 7.8 15.4 7.8 41 42.3 11.2 44 21 2249 S. Africa 39.3 6.2 13.2 4.2 20.3 21.2 9.2 42.9 22 2279 S. Africa 53.2 6.3 12.3 6.7 23.2 22.1 9 39.6 23 2289 S. Africa 44 7.2 13.9 6.3 31.3 41.7 10.2 43 24 2299 S. Africa 40 5.1 9.8 7.3 78 30.3 7.2 43.7 25 30316 Kenya 37.7 5.9 10.3 10 146 83 8 57.1 26 31990 Kenya 41 5.7 13.2 8.5 109.3 91.3 8.8 55.4 27 31992 Kenya 42 8 11 9.2 201 91.7 9.9 59.5 28 45426 Kenya 43 7.4 11.5 10 97 97 9.5 58.4 29 45446 Kenya 42.3 8.8 13 8.3 68 111.7 11.1 57.3 3 45451 Kenya 47.7 7.2 16.1 9.2 247.5 109.3 10.9 53.9 31 50259 Kenya 44 5.7 10.6 9.2 182 101.3 7.9 58.1 32 50264 Kenya 40.2 4.4 10.5 11.7 172.2 108.8 6.9 60.8 33 50265 Kenya 44.3 5.5 11.6 10.3 78.7 92.2 8.2 60.1 34 50273 Kenya 40.3 5.1 9.5 8.7 92.8 89.7 7.1 57.5 35 50290 Kenya 40.3 4.8 10.4 9.3 105.2 93.2 7.1 62.2 36 50296 Kenya 40 10.5 18.3 10.7 109.5 113 14.2 57.9 37 50298 Kenya 40 4.4 7.9 11.5 140 82.7 6.1 59.5 38 50299 Kenya 41.7 4.8 9.4 10.5 101.3 99.8 6.9 58.9 39 50307 Kenya 40 6 12 8.3 140.7 93.8 8.7 58.4 4 50319 Kenya 40.3 6.2 12.5 9.5 101 77.8 9 62.5 41 50325 Kenya 40 6.8 12.1 10 94.8 95 9.3 57.9 42 50326 Kenya 44.3 5.6 11.1 12.5 165.8 101.2 8.1 57.5 43 50328 Kenya 40.2 5.4 8.6 8.7 96.5 75.7 7.1 58.6 44 50330 Kenya 39.8 5.7 10.4 9.8 172 104.3 7.8 60.8 45 50332 Kenya 40.5 4.2 8.8 9.2 115.8 110.5 6.2 62.5 46 50339 Kenya 42.7 5.2 12.8 12.5 149.8 101.7 8.3 61.6 47 50353 Kenya 42.3 4.5 8.4 11 146.8 86 6.3 57.8 48 50584 Kenya 39.7 4.8 9.8 9.7 88.8 78.7 7 57.9 49 50600 Kenya 38.8 5.9 8.8 9.5 78.8 98.8 7.5 56.2 Mean 41.8 5.8 12 8 97 68.4 8.5 55.1 LSD 1.5 .7 1.6 1 6.3 4.4 .9 2.9 (p< . 5) CV % 2.2 7.4 8.1 7.8 4 4 6.5 3.3 DTF: days to 50% flowering, SLA: single leaf area (cm ), LL: leaf length (cm), LW: leaf width (cm), NLPP: number of leaves per plant, NPB: number of primary branches, PH: plant height (cm), and SPAD: soil plant analysis development. 10 Advances in Agriculture Table 6: Correlation in combined seasons. DTF LL LW NPB NLPP PH SLA SPAD DTF - LL 0.12∗ - LW 0.28∗∗ 0.62∗∗ - NPB 0.09 0.02 -0.20∗∗ - NLPP 0.1 -0.01 -0.11 0.63∗∗ - PH -0.07 0.16∗ -0.19∗ 0.82∗∗ 0.69∗∗ - SLA 0.21∗∗ 0.92∗∗ 0.88∗∗ -0.08 -0.06 0.01 - SPAD -0.04 -0.07 -0.11 0.54∗∗ 0.45∗∗ 0.59∗∗ -0.1 - ∗ implies significance difference at P <0.05;∗∗ implies significance difference at p <0.001 (2-tailed), DTF- days to 50% flowering, SLA- single leaf area (cm ), LL- leaf length (cm), LW- leaf width (cm), NLPP- number of leaves per plant, NPB- number of primary branches, PH- plant height (cm), SPAD- soil plant analysis development. Table 7: Stepwise regression analysis of the 7 evaluated traits. Step Variable Partial R square Adjusted R square F-test 1 Plant height 0.48 0.47 43.00∗ ∗Significant at p ≤ 0.05 y = 1.102x + 21.947, y = number of leaves per plant, and x = plant height. Table 8: Estimates of yield and yield related components of 49 spider plant accessions. Traits VE VG VP HBS (%) Season 1 1.0 11.2 12.2 91.8 DTF Season 2 1.0 10.1 11.1 91.0 Season 1 0.2 1.7 1.9 89.3 LL Season 2 0.2 1.7 1.9 89.3 Season 1 1.4 5.0 6.4 78.0 LW Season 2 1.4 5.3 6.7 79.2 Season 1 0.3 4.8 5.1 94.1 NPB Season 2 0.3 3.8 4.1 92.7 Season 1 13.4 2294.1 2307.5 99.4 NLPP Season 2 13.4 2314.6 2328.0 99.4 Season 1 8.2 908.6 916.8 99.1 PH Season 2 8.2 905.8 914.0 99.1 Season 1 0.4 2.6 3.0 86.5 SLA Season 2 0.4 2.6 3.0 86.5 Season 1 2.1 54.4 56.5 96.3 SPAD Season 2 2.1 45.1 47.2 95.5 VE = environmental variance, VG = genotypic variance, VP = phenotypic variance, HBS = broad sense heritability, NLLP = number of leaves per plant, NPB = number of primary branches, LL = leaf length, LW = leaf width, PH = plant height, SLA = single leaf area, and SPAD = soil plant analysis development. characterization with the use of molecular markers for paper is part of the M.S. thesis entitled “Genetic Characteri- germplasm characterization and genetic diversity since they zation and Nutrition Analysis of Eastern and South African are under little influence from the environment. Cleome gynandra (Spider Plant) Accessions” submitted to the University of Nairobi towards achievement of an M.S. degree Conflicts of Interest in plant breeding and biotechnology. The authors declare no conflicts of interest regarding the References publication of this paper. [1] R. R. Schippers, “African indigenous vegetables: an overview of the cultivated species,” 2000. Acknowledgments [2] J.A.Chweya and N. A.Mnzava, Cat’s whiskers. gynandra L.: The authors would like to acknowledge the University of Promoting the conservation and use of underutilized and neglect- Nairobi for the opportunity to undertake the research. This ed crops,vol.11, 1997. Advances in Agriculture 11 [3] Department of Agriculture Forestry and Fisheries (DAFF), wild relative C. scarabaeoides,” Euphytica,vol. 145, no. 3, pp. Cleome, Resource Centre, Pretoria, South Africa. 247–257, 2005. [4] HCDA, Horticulture Data 2011-2013 Validation Report,Horti- [21] U. Alahakoon, J. Adamson, L. Grenkow, J. Soroka, P. 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Heritability Analysis and Phenotypic Characterization of Spider Plant (Cleome gynandra L.) for Yield

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Copyright © 2018 Ann Kangai Munene et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Hindawi Advances in Agriculture Volume 2018, Article ID 8568424, 11 pages https://doi.org/10.1155/2018/8568424 Research Article Heritability Analysis and Phenotypic Characterization of Spider Plant (Cleome gynandra L.) for Yield 1 1 1 2 Ann Kangai Munene , Felister Nzuve, Jane Ambuko , and Damaris Odeny Department of Crop Science and Crop Protection, University of Nairobi, Kenya eTh International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Nairobi, Kenya Correspondence should be addressed to Ann Kangai Munene; wakaireann@gmail.com Received 30 November 2017; Revised 30 March 2018; Accepted 12 July 2018; Published 31 July 2018 Academic Editor: Mumtaz Cheema Copyright © 2018 Ann Kangai Munene et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Knowledge on phenotypic diversity among existing spider plant accessions is a milestone in the improvement of spider plant, which is a highly nutritious indigenous vegetable in Kenya. A study involving agronomic and morphological characterization of 49 spider plant accessions assembled from East and South Africa was carried out at the University of Nairobi Field Station for two seasons in a randomized complete block design with three replications. Phenotypic data was collected on growth habit, flower, petiole, leaf and stem colour, petiole, leaf and stem hairiness, number of leaves per plant, plant height, number of primary branches, leaf length and width, single leaf area, and chlorophyll content according to FAO descriptors with modifications. Data was analyzed using both DARwin sow ft are V6 and Genstat Version 14. We observed significant differences among the traits implying great genetic variability among the evaluated spider plant accessions. The high genetic variation was further validated using the Unweighted Pair Group Method with Arithmetic mean (UPGMA) clustering method with stem and flower colour as key traits. The 49-spider plant accessions were clustered into 2 major groups, each consisting of Kenyan and South African accessions. Stepwise regression revealed that plant height had the most influence on yield in terms of number of leaves per plant. We also observed high heritability for several traits including days to flowering (91%), number of leaves per plant (99%), plant height (99%), number of primary branches (94%), chlorophyll content (94%), and single leaf area (87%). Our results reveal the high genetic variation between dieff rent spider plant accessions, especially from dieff rent regions of Africa that could be further exploited to improve productivity in the plant. The high heritability of most of the yield related traits is promising for improving yield in the crop through direct selection. Coastal regions. The key counties producing the crop include 1. Introduction Kisii, Nyamira, Kericho, Migori, and Siaya [4]. Despite this Cleome gynandra, also knownas “Africanspider plant”, is wide adaptation and continued increase in production and among the most important traditional leafy vegetables widely consumption, there have been limited efforts towards its used in Africa [1]. It belongs to the family of Capparaceae. improvement. There is lack of critical information on the It is also an erect herbaceous annual herb that is mainly extent and structure of phenotypic variation crucial for the self-pollinated [2]. The plant is highly nutritive and con- breeding and conservation of spider plant [2, 5]. Genetic tains health promoting bioactive compounds important in diversity is particularly useful in characterizing individual combating malnutrition and reducing human degenerative accessions and cultivars, in detecting genetic materials with diseases. Spider plant is native to the Southern Africa, novel genes and thereby rescuing them from genetic erosion, Western Africa, Central Africa, Eastern Africa, and South and as a general guide, in selecting appropriate parents in breeding programs. Most of the genetic diversity observed in East Asia [3]. In South Africa, spider plant has been found to grow in the wild in KwaZulu-Natal, Free State, Northern spider plant in Kenya and South Africa has traditionally been Cape, Limpopo, and North West provinces [3]. In Kenya, the maintained by farmers in situ. This poses the risk of species plants are mainly found in Western, Rift Valley, Eastern, and extinction due to loss of natural habitat as humans continue 2 Advances in Agriculture to exploit and develop land, divert water o fl w, and change Table 1: List of Kenyan and South African spider plant accessions evaluated in the study. the environment. Secondly, as human population continues to increase, there is pressure on natural land being cleared Entry Accession no. Country of origin Region by human activity. The need for cultivation, conservation, ke 1 1 Kenya Siaya and characterization of spider plant remains imperative in ke 2 2 Kenya Bungoma maintaining the integrity of the genetic information and ke 3 3 Kenya Kakamega diversity. ke Mendelian analysis of discrete morphological traits can 4 4 Kenya Kitale ke be used to estimate genetic diversity in plants [6] and has 5 5 Kenya Mbale ke been successfully used in spider plant [5]. Some of the key 6 6 Kenya Bomet traits that have been used as a guide in selection for good ke 7 7 Kenya Busia genotypes in previous studies included high heritability traits ke 8 9 Kenya Marakwet such as days to flowering, plant height, and number of leaves ke 9 10 Kenya Kisumu per plant [7]. Omondi [7] observed that higher leaf yield, ke 1 11 Kenya Homabay plant uniformity, longer vegetative phase, late flowering, and ke 11 12 Kenya Nandi drought tolerance could form the best criterion in selection ke 12 13 Kenya Kakamega of good performing spider plant accessions. However, for ke an efficient crop improvement program, information on 13 14 Kenya Kisii ke estimates of heritability for these desirable traits must be 14 15 Kenya Mbale ke established [8]. Due to limited knowledge on the genetic 15 16 Kenya Meru variability, more research remains of the essence to elucidate sa 16 1959 South Africa Mpumalanga the genetic and phenotypic diversity of existing spider plant sa 17 1988 South Africa Mpumalanga accessions. u Th s, the main thrust of this study was to sa 18 2000 South Africa Mpumalanga understand the extent of phenotypic diversity and heritability sa 19 2232 South Africa Northern province of qualitative traits among 49 spider plant accessions assem- sa 2 2241 South Africa Northern province bled from Kenya and South Africa. Promising spider plant sa 21 2249 South Africa Northern province accessions can be utilized in various breeding programs and sa have the potential of enhancing its utilization while aiding to 22 2279 South Africa Northern province sa gfi ht hidden hunger in Kenya. 23 2289 South Africa Mpumalanga sa 24 2299 South Africa Mpumalanga ke 2. Materials and Methods 25 30316 Kenya Western ke 26 31990 Kenya Western 2.1. Plant Materials. The study used 49 spider plant acces- ke 27 31992 Kenya Western sions, mainly local landraces assembled from 3 sources: Gene ke 28 45426 Kenya Western bank of Kenya (25), Gene bank of South Africa (9), and ke 29 45446 Kenya Central Kenyan farmers’ landraces (15) (Table 1). ke 3 45451 Kenya Central ke 31 50259 Kenya Kisii 2.2. Experimental Design and Study Site. The experiments ke were carried out at the University of Nairobi’s Kabete Field 32 50264 Kenya Nyamira ke station (Nairobi, Kenya) for two seasons from March 2014 to 33 50265 Kenya Nyamira ke May 2014 and October 2014 to January 2015. The experiments 34 50273 Kenya Nyamira were laid out in a randomized complete block design with ke 35 50290 Kenya Nyamira ∘ 󸀠 three replications. Kabete Field station lies at 36 41 Eand ke 36 50296 Kenya Nyamira 01 15’S with an altitude of 1737 m above sea level. It receives an ke ∘ 37 50298 Kenya Nyamira average temperature of 23 Cwith a bimodal rainfall pattern ke 38 50299 Kenya Nyamira and an annual precipitation of 600 mm to 1800 mm. The soil ke 39 50307 Kenya Kisii type is well drained very dark reddish, brown to dark red ke 4 50319 Kenya Nyamira friable clay locally known as Kikuyu red clay loam with an ke average pH of 6.2 [9]. 41 50325 Kenya Kisii ke 42 50326 Kenya Nyamira ke 2.3. Crop Husbandry. Pregermination for each accession was 43 50328 Kenya Nyamira done for 72 hours under treatment with 0.2% gibberellic ke 44 50330 Kenya Nyamira acid to break seed dormancy and enhance germination [10]. ke 45 50332 Kenya Kisii Each individual accession was planted by hand in two rows ke 46 50339 Kenya Nyamira comprising ten seeding holes per row (20 plants in a plot). ke 47 50353 Kenya Nyamira Row plots were 3 m in length with inter-row spacing of ke 48 50584 Kenya Nyamira 30 cm and intra-row spacing of 30 cm. Farmyard manure ke 49 50600 Kenya Kisii was applied to rows at the rate of 10.5 g/accession and mixed ke sa with soil at planting. Hand weeding was done throughout the =originated from Kenya; =originated from South Africa. Advances in Agriculture 3 Table 2: Character, descriptor, and codes used for characterization of qualitative traits in spider plant accessions. S/No. Character Descriptor and code 1Growthhabit Erect(2), semi-erect(4) and prostrate(6) 2 Flower colour White(1),purple(2) and pink(3) 3 Stem colour Green(1),pink(2),violet(3) and purple(4) 4 Stem hairiness Glabrous(1),weak/sparse(3),medium(5) and profuse(7) 5 Petiole colour Green(1),pink(2),violet(3) and purple(4), 6 Petiole hairiness Glabrous(1),weak/sparse(3),medium(5) and profuse(7) 7 Leaf colour Dark green(1) and light green(2), 8 Leaf hairiness Glabrous(1),weak/sparse(3),medium(5) and profuse(7) Source: Food and Agriculture Organization of the United Nations (FAO, 1995); numbers in brackets on the right-hand side are the corresponding descriptor codes listed in the FAO publication with modifications during the development of the list. experimental period. The experiment was conducted under Heritability in the broad sense was estimated as a ratio of rain-fed conditions with supplemental overhead irrigation genotypic variance to the phenotypic variance and expressed when required. in percentage [14] as per the following equation. 2.4. Data Collection and Analysis. There were two sets of data Heritability (𝐻 )=( ×100) (1) collected in the study, namely, qualitative (morphological) and quantitative (agronomic). where V is the genotypic variance and V is the phenotypic g p variance. 2.5. Qualitative Traits. Spider planttraitsthatwere consid- Genotypic variance (𝜎 𝑔 ) was derived by subtracting ered qualitative included growth habit, owe fl r colour, stem error mean sum of squares (EMS) from the genotypic mean colour, stem hairiness, petiole colour, petiole hairiness, leaf sum of squares (GMS) and divided by the number of colour, and leaf pubescence based on the list of modified spi- replications as given by the following equation. der plant descriptors [11] (Table 2). Three randomly selected plants were tagged per accession per replicate during crop 𝑆 𝜎 𝑔=𝑆𝑀𝐺− (2) growth, before ow fl ering. The data was subjected to DARwin 5.0 sowa ft re as described by Perrier and Jacquemoud-Collet where [12]. Euclidean distance matrix and hierarchical clustering analyses of Unweighted Pair Group Method of Arithmetic GMS is the genotype mean sum of squares, EMS is averaging were used to estimate dissimilarities among the the error mean sum of squares, and r is the number of accessions and results displayed in a dendrogram. This replications. was followed by the identification of the most significant descriptors contributing to most phenotypic variation among Phenotypic variance (𝜎 𝑝 ) was derived by adding genotypic the spider plant accessions through a stepwise regression variance with error variance as per the following equation. analysis. 2 2 2 (3) 𝜎 𝑝=𝜎 𝑒+𝜎 𝑔 2.6. Quantitative Traits. All the yield and yield related traits were considered quantitative, including days to 50% flower- 3. Results and Discussions ing, SPAD values, plant height, number of primary branches, leaf length, leaf width, single leaf area, and number of leaves 3.1. Qualitative Traits. There were three distinct o fl wer per plant. Using Genstat version 14 software as described colours displayed by the spider plant accessions: purple, by [13], the data was subjected to Analysis of Variance to pink, and white. Among these, the purple flower colour was establish any significance differences among the traits and to the most dominant among the Kenyan accessions at 49% obtain genotype means which were then separated using the (Table 3) while the most dominant flower colour among Fishers protected least significant differences (LSD) at P < the South African accessions was white. Most of the South 0.05. African accessions displayed a green stem with a green petiole To establish the relationship among the traits collected, a as opposed to the Kenyans accessions, which displayed two-tail correlation analysis was performed to estimate quan- purple stems and pubescence. Previous study by Masuka and titative relationships among the traits and also to identify Mazarura [15] reported that purple-stemmed plants tended those traits that could be of great signicfi ance in a spider plant to be more hairy (trichomes) than the green-stemmed plants. breeding program. Anthocyanins have been implicated as responsible for the 𝐸𝑀 𝑉𝑝 𝑉𝑔 4 Advances in Agriculture fi Table 3: Morphological descriptors recorded for the 49 eld grown spider plant accessions for the combined season. Entry Accession no. Origin Flower colour Stem colour Petiole colour Stem hairiness Petiole hairiness Leaf colour Leaf hairiness Growth habit 1 1 Kenya Purple Purple Green Profuse Medium dark green Medium Erect 2 2 Kenya White Purple Pink Profuse Medium light green Sparse Erect 3 3 Kenya Pink Purple Pink Profuse Medium dark green Sparse Erect 4 4 Kenya Pink Purple Pink Profuse Medium light green Medium Erect 5 5 Kenya White Purple Purple Profuse Profuse light green Profuse Erect 6 6 Kenya Pink Purple Pink Profuse Profuse dark green Medium Erect 7 7 Kenya Pink Purple Purple Profuse Medium dark green Medium Erect 8 9 Kenya White Purple Purple Profuse Profuse dark green Sparse Erect 9 10 Kenya Purple Purple Purple Medium Medium light green Sparse Erect 1 11 Kenya Pink Purple Purple Medium Medium dark green Medium Erect 11 12 Kenya Pink Purple Purple Profuse Medium light green Sparse Erect 12 13 Kenya Purple Purple Purple Medium Medium light green Sparse Erect 13 14 Kenya Purple Green Purple Profuse Profuse dark green Medium Erect 14 15 Kenya Pink Purple Purple Medium Sparse dark green Sparse Erect 15 16 Kenya Pink Purple Pink Medium Sparse light green Sparse Erect 16 1959 S. Africa Pink Purple Pink Profuse Medium light green Medium Erect 17 1988 S. Africa White Green Green Sparse Sparse light green Sparse Semi erect 18 2000 S. Africa White Green Green Glabrous Glabrous light green Glabrous semi erect 19 2232 S. Africa White Green Green Glabrous Glabrous dark green Glabrous Erect 2 2241 S. Africa White Green Pink Sparse Sparse light green Sparse Erect 21 2249 S. Africa White Green Pink Glabrous Glabrous light green Glabrous Erect 22 2279 S. Africa White Green Green Glabrous Glabrous light green Glabrous Semi erect 23 2289 S. Africa White Green Pink Medium Sparse dark green Sparse Erect 24 2299 S.Africa White Green Green Glabrous Sparse light green Glabrous Erect 25 30316 Kenya Purple Purple Purple Profuse Medium dark green Sparse Erect Advances in Agriculture 5 Table 3: Continued. Entry Accession no. Origin Flower colour Stem colour Petiole colour Stem hairiness Petiole hairiness Leaf colour Leaf hairiness Growth habit 26 31990 Kenya Purple green Green Medium Sparse light green Sparse Erect 27 31992 Kenya Pink purple Green Profuse Medium dark green Medium Erect 28 45426 Kenya Purple Purple Green Profuse Sparse dark green Sparse Erect 29 45446 Kenya White Purple Purple Profuse Medium dark green Sparse Erect 3 45451 Kenya Pink Purple Purple Profuse Profuse dark green Medium Erect 31 50259 Kenya Pink Purple Purple Profuse Medium dark green Sparse Erect 32 50264 Kenya Purple Purple Purple Profuse Medium dark green Sparse Erect 33 50265 Kenya Purple Purple Purple Profuse Medium dark green Medium Erect 34 50273 Kenya Purple Purple Purple Profuse Medium dark green Sparse Erect 35 50290 Kenya Purple Purple Purple Profuse Medium dark green Medium Semi erect 36 50296 Kenya Purple Purple Purple Profuse Medium dark green Medium Erect 37 50298 Kenya Purple Purple Purple Medium Sparse light green Sparse Semi erect 38 50299 Kenya Purple Purple Purple Profuse Medium dark green Sparse Erect 39 50307 Kenya Purple Purple Purple Medium Medium dark green Sparse Erect 4 50319 Kenya Purple Purple Purple Profuse Medium dark green Medium erect 41 50325 Kenya Pink Purple Purple Medium Medium dark green Sparse erect 42 50326 Kenya Purple Purple Purple Profuse Medium dark green Sparse erect 43 50328 Kenya Purple Purple Purple Profuse Medium dark green Sparse erect 44 50330 Kenya Purple Purple Purple Profuse Medium dark green Sparse erect 45 50332 Kenya Purple Purple Purple Profuse Medium dark green Medium erect 46 50339 Kenya Purple Purple Purple Profuse Medium dark green Sparse erect 47 50353 Kenya Purple Purple Purple Profuse Medium dark green Medium erect 48 50584 Kenya Purple Purple Purple Medium Medium dark green Sparse erect 49 50600 Kenya Purple Purple Purple Profuse Medium dark green Sparse erect 6 Advances in Agriculture stem pigmentation in most herbaceous plants [16] and have Kisii region grouped together suggesting some degree of also been widely studied for their potential medicinal value similarity in their morphological traits. Most of the Kenyan [17]. Although spider plants have been traditionally used farmers’ landraces clustered together based on their origin. There were major overlaps with the accessions assembled for medicinal purposes [18], the obvious contrast between South African and Kenyan accessions in their anthocyanin from the gene bank implying that they could have same content calls for more studies in order to elucidate the benefits genetic makeup. A study by K’opondo [5] has demonstrated a close relationship among spider plant genotypes following of the variations observed. Presence of trichomes, on the other hand, has been associated with insect resistance in the evaluation of the variability in seed proteins among them. several studies including soybean [19], pigeonpea [20], and In addition, this uniformity could also arise from the self- Brassicaceae [21]. Trichomes are considered a domestication pollination status of spider plant. However, more character- trait and are often more abundant in unadapted landraces ization needs to be done to validate such findings. The cluster analysis, which clearly grouped the accessions according to than in improved germplasm. The absence of trichomes in South African accessions may suggest that they have their geographical origin, suggests that crop improvement undergone much more intense selection cycles than the of spider plant could be achieved through exploiting the variation revealed. However, the current cluster analysis was Kenyan accessions, although more studies would need to be done to confirm this fact. done using morphological traits, which can be influenced Erect growth habit was more dominant and was observed by several environmental factors. There will be need to in 90% of the accessions as opposed to the semi-erect growth undertake a more detailed genetic analysis using molecular habit observed among 10% of the accessions. This observation markers to confirm the existence of genetic variation across agrees with earlier findings [22], which reported over 80% the different geographical regions. There is need for specific erect growth in the studied spider plant accessions. Other regional breeding efforts to target preferred traits [24, 25]. past research has also shown that majority of the spider plant morphotypes present an erect type of growth [5]. Growth 3.3. Quantitative Traits habit is crucial in vegetable breeding as reported in other indigenous vegetables [23]. Bushy growth habit results in 3.3.1. Analysis of Variance. Spider plant accessions showed significant differences (P <0.05) with no seasonal eeff ct for many small leaves arising from numerous shoots that are not a preference trait to producers while the erect growth habit all the traits, namely, days to 50% flowering, single leaf with only primary and secondary branches maximizes the area, leaf length and width, chlorophyll content, number of leaves per plant, number of primary branches, and plant leaf area. This implies that yield improvement in spider plant could be exploited through selection of genotypes exhibiting height (Table 4), implying the existence of variability for the erect growth habit and therefore large leaf size. Further respective traits among spider plant accessions. Accessions that exhibited longer days to 50% flowering also yielded more reports have suggested that, in mixed cropping, farmers could adopt the semi-erect type whereas the erect types are ideal for leaf count. Late o fl wering enables a plant to have a longer vegetative phase during growth period [7]. Past research intercrop adaptability [14]. has associated late flowering with increased leaf yield and 3.2. Cluster Analysis. Sufficient phenotypic variation was consequently early o fl wering as a limit to leaf yield in other indigenous vegetables [23]. This suggests that late flowering observed among the accessions as revealed by the cluster analysis (Figure 1). Two major clusters, namely, clusters 1 would be a good selection criterion for yield improvement in spider plant. and 2, were distinguished using the eight morphological Other traits that contributed to increased leaf count descriptors. Cluster 1 included 9 accessions of South African origin with an exception of one Kenyan accession 1959 while were plant height and number of primary branches. Kenyan accessions were taller than the South African accessions cluster 2 is comprised of 40 Kenyan accessions inclusive with plant height varying from 21 cm for accession 2249 to of one South African origin. Stem and petiole colour were the major traits that contributed to the Kenyan accession 113 cm for accession 50296. The Kenyan accessions performed better than South African genotypes for the number of leaves 31990 grouping together with the South African accessions per plant, number of primary branches, leaf length, leaf that were mainly green stemmed with green petiole. The exceptional South African accession grouped together with width, plant height, single leaf area, and chlorophyll content conforming to past research by Wasonga [22]. The best 5 the Kenyan accessions due to the purple stem colour and pro- fuse pubescence that were predominant among the Kenyan outstanding accessions with regard to yield related traits like 50% flowering, single leaf area, and number of leaves per plant accessions. This clearly revealed the differences in the genetic included Kenyan accessions: 3, 7, 45451, 50296, and South makeup of the accessions from the two regions. However, the South African accessions 2279 and 2000, which were African accession 2241 (Table 5). collected from the Northern Province, showed similarity in their phenotypic traits. Most of the Kenyan gene bank 3.3.2. Correlation among the Traits. Knowledge of the cor- accessions, namely, 50339, 50330, 50328, 50326, 50299, and relations among yield and the yield related traits is of 50273, from Nyamira region clustered closely together with considerable importance in crop improvement because it aids accession 30316 from Western region despite being collected in indirect selection [26]. There was positive and significant from dieff rent regions. Additionally, Kenyan accession 45451 correlation between leaf length, leaf width, and leaf area from central region and Kenyan accession 14 collected from with number of days to 50% o fl wering Table 6. This agrees Advances in Agriculture 7 Cluster 2 2249 Cluster 1 0 1 South African gene bank accessions Kenyan gene bank accession Kenyan farmer’s landraces Figure 1: Phenogram showing relationship among accessions characterized using morphological traits. with the findings of Kiebre et al. [27] who also reported number of the branches and the taller the plant, the higher a positive signicfi ant correlation between number of days the number of leaves. Single leaf area correlated positively to 50% flowering with leaf length and width. This further with leaf length, width, and days to 50% flowering at r = suggests that the late flowering genotypes could be selected 0.92, r = 0.88, and r = 0.21, respectively. As expected, the leaf area would be determined by its length and width suggesting for their big size, which is a crucial trait to the producers who regard leaf biomass as key in leafy vegetables production. the longer and wider the leaf, the bigger the leaf area. This There was a significant positive correlation between plant suggests leaf length and width as important traits in selecting height and number of primary branches conforming to the for vegetative yield in spider plant. results of Kiebre et al. [27] indicating the taller the plant, However, there was a nonsignificant negative correlation the more the number of primary branches. This is further between leaf size and leaf yield indicating the more the supported by the observed correlations, where yield in terms number of leaves in the plant, the smaller the leaves. Yield is of number of leaves per plant had a positive and signicfi ant influenced by complex soil plant interactions in many crops. correlation with plant height (r = 0.69) and number of In this study, the chlorophyll content measured in SPAD value primary branches (r = 0.63) implying that the higher the had a positive significant correlation with number of leaves 8 Advances in Agriculture Table 4 (a) Analyses of variance showing the mean squares for the agronomic traits in Cleome gynandra season one (April-July 2014). Source of variation d.f. DTF LL LW NPB NLPP PH SLA SPAD Rep 2 4.3 0.6 1.7 1.6 27.9 6.5 0.4 1 Genotype 48 34.7∗ 5.2∗ 16.3∗ 14.7∗ 6895.6∗ 2734.0∗ 8.1∗ 165.4∗ Residual 96 1 0.2 1.4 0.3 13.4 8.2 0.4 2.1 Total 146 (b) Analyses of variance showing the mean squares for the agronomic traits in Cleome gynandra season one (October-July 2014). Source of variation d.f. DTF LL LW NPB NLPP PH SLA SPAD Rep 2 5 0.5 0.5 0.4 1.5 3.2 0.6 3.6 Genotype 48 31.1∗ 5.1∗ 16.5∗ 11.9∗ 6961.3∗ 2723.8∗ 7.9∗ 139.5∗ Residual 96 0.8 0.1 0.5 0.5 17.6 6.4 0.2 4.3 Total 146 (c) Analyses of variance showing the mean squares for the agronomic traits in Cleome gynandra for the combined seasons. Source of variation d.f. DTF LL LW NPB NLPP PH SLA SPAD Rep 2 9.1 1 1.2 1.6 16 4.7 0.9 3.2 Genotype 48 64.6∗ 10.3∗ 32.6∗ 26.1∗ 13840.2∗ 5451.1∗ 15.9∗ 300.8∗ Season 1 161.6∗ 1.0∗ 4.1∗ 2.1∗ 54 33.4∗ 2.1∗ 4.8∗ Genotype Season 48 1.2 0.1 0.2 0.4 16.7 6.7 0.1 4.1 Residual 194 0.9 0.2 0.9 0.4 15.5 7.3 0.3 3.2 Total 293 ∗Significant at P<0.05, DTF: days to 50% flowering, SLA: single leaf area (cm ), LL: leaf length (cm), LW: leaf width (cm), NLPP: number of leaves per plant, NPB: number of primary branches, PH: plant height (cm), and SPAD: soil plant analysis development. per plant (r = 0.45), number of primary branches (r = 0.54), broad sense heritability were estimated for number of leaves and plant height (r = 0.59). This contradicts the findings of per plant, plant height at 99%, and SPAD value at 96%. [28] who reported negative correlations between chlorophyll Leaf width exhibited a moderately lower percentage at 78% readings with yield related traits except for plant height in followed by single leaf area and leaf length at 86% and 89%, beans. This positive significance correlation between SPAD respectively (Table 8). High heritability plays a great role in values and yield related traits calls for more studies to selection for crop improvement as the traits to be improved elucidate this phenomenon. Leaf yields may be improved depend immensely on their heritability and variability [27]. through selection of accessions that showed high leaf count In this study, the genotypic variance of all traits was higher than the environmental variance implying that much of the as well as large single leaf area. phenotypic variation among the accessions was attributed to variation in genotype as opposed to the environment. The 3.4. Stepwise Regression. The most importanttraitsthathave high estimates of heritability displayed in the study suggest a considerable effect on the dependant variable are verified that selection for yield improvement in spider plant could through a stepwise regression analysis. The traits selected be based on traits like number of leaves per plant and plant through the regression model can then be used as a selec- height. tion criterion for indirect selection in a breeding program [29]. A multiple linear regression analysis was calculated by 4. Conclusions and Recommendations considering the number of leaves as the dependent variable and other characters as the independent variables. Results of This study reported the existence of significant phenotypic regression analysis showed that plant height had a signicfi ant variation in Cleome gynandra as evidenced by the mor- influence on yield (R =46.7,Pvalue≤ 0.05) (Table 7). This phological characterization which clearly distinguished the implies that selection based on plant height will influence and accessions from the two regions. The new knowledge gener- increase vegetative yield in C. gynandra. This further agrees ated on the spider plant morphological structure could oeff r with other n fi dings by Nwangburuka et al. [30] in vegetable a great potential in developing relevant genetic and genomic C. olitorius where plant height was found to significantly resources for spider plant breeding programs. It is also clear increase leaf yield. that indirect selection for improved spider plant accessions could be based on the yield related traits like number of 3.5. Heritability Estimates for Yield and Yield Related Traits. leaves per plant, plant height, number of primary branches, The estimates of heritability in broad sense for all the traits and days to flowering which exhibited high heritability. This ranged from 78% to 99% (Table 8). High percentages of study recommends the complementation of morphological Advances in Agriculture 9 Table 5: Mean comparison of the quantitative traits of 49 spider plant accessions from Kenya and South Africa grown in the University of Nairobi Field at Kabete, for the two combined seasons. Entry Accession No. Origin DTF LL LW NPB NLPP PH SLA SPAD 1 1 Kenya 39.7 5.1 14.2 6.3 105 38.3 8.7 56.4 2 2 Kenya 45.7 6.4 11.5 5.7 58.8 31.5 8.8 57.6 3 3 Kenya 45.3 6.7 17 7 112.2 41 10.9 50.3 4 4 Kenya 43.8 5.2 13.8 7.5 75.8 36.7 8.7 56.9 5 5 Kenya 45.3 5 13.2 7.5 53.8 46.8 8.3 57.6 6 6 Kenya 39.7 5 11.7 7.5 57.2 47.8 7.8 56.9 7 7 Kenya 45 5.9 16 7.7 91.3 51.2 9.9 53 8 9 Kenya 45.5 6.2 14.3 6.5 94.3 39 9.6 56.6 9 10 Kenya 41.5 5.6 11.7 5.7 68 40.7 8.3 58.3 1 11 Kenya 45 3.6 10.6 5.5 100.5 40.1 6.3 56.8 11 12 Kenya 46 4.6 11.9 7.5 61 42.2 7.6 58.8 12 13 Kenya 37.8 5 13.1 6.2 64.8 38.3 8.3 55.9 13 14 Kenya 39.8 4.7 11.3 7.8 83.3 63.2 7.4 53.3 14 15 Kenya 38.7 3.7 9.3 5.7 55.7 37.8 6 46.7 15 16 Kenya 45.2 7.8 15.6 9 75.7 75.5 11.2 61.6 16 1959 S. Africa 43.8 5.8 12 6.7 89.2 34.3 8.5 54.3 17 1988 S. Africa 34.2 6.8 12.6 5.7 50.7 45.2 9.5 49.9 18 2000 S. Africa 32.8 6.5 13.6 4.2 19.7 30.8 9.6 53.1 19 2232 S. Africa 39.8 5.3 10 4.7 56 26.3 7.4 24.3 2 2241 S. Africa 45.3 7.8 15.4 7.8 41 42.3 11.2 44 21 2249 S. Africa 39.3 6.2 13.2 4.2 20.3 21.2 9.2 42.9 22 2279 S. Africa 53.2 6.3 12.3 6.7 23.2 22.1 9 39.6 23 2289 S. Africa 44 7.2 13.9 6.3 31.3 41.7 10.2 43 24 2299 S. Africa 40 5.1 9.8 7.3 78 30.3 7.2 43.7 25 30316 Kenya 37.7 5.9 10.3 10 146 83 8 57.1 26 31990 Kenya 41 5.7 13.2 8.5 109.3 91.3 8.8 55.4 27 31992 Kenya 42 8 11 9.2 201 91.7 9.9 59.5 28 45426 Kenya 43 7.4 11.5 10 97 97 9.5 58.4 29 45446 Kenya 42.3 8.8 13 8.3 68 111.7 11.1 57.3 3 45451 Kenya 47.7 7.2 16.1 9.2 247.5 109.3 10.9 53.9 31 50259 Kenya 44 5.7 10.6 9.2 182 101.3 7.9 58.1 32 50264 Kenya 40.2 4.4 10.5 11.7 172.2 108.8 6.9 60.8 33 50265 Kenya 44.3 5.5 11.6 10.3 78.7 92.2 8.2 60.1 34 50273 Kenya 40.3 5.1 9.5 8.7 92.8 89.7 7.1 57.5 35 50290 Kenya 40.3 4.8 10.4 9.3 105.2 93.2 7.1 62.2 36 50296 Kenya 40 10.5 18.3 10.7 109.5 113 14.2 57.9 37 50298 Kenya 40 4.4 7.9 11.5 140 82.7 6.1 59.5 38 50299 Kenya 41.7 4.8 9.4 10.5 101.3 99.8 6.9 58.9 39 50307 Kenya 40 6 12 8.3 140.7 93.8 8.7 58.4 4 50319 Kenya 40.3 6.2 12.5 9.5 101 77.8 9 62.5 41 50325 Kenya 40 6.8 12.1 10 94.8 95 9.3 57.9 42 50326 Kenya 44.3 5.6 11.1 12.5 165.8 101.2 8.1 57.5 43 50328 Kenya 40.2 5.4 8.6 8.7 96.5 75.7 7.1 58.6 44 50330 Kenya 39.8 5.7 10.4 9.8 172 104.3 7.8 60.8 45 50332 Kenya 40.5 4.2 8.8 9.2 115.8 110.5 6.2 62.5 46 50339 Kenya 42.7 5.2 12.8 12.5 149.8 101.7 8.3 61.6 47 50353 Kenya 42.3 4.5 8.4 11 146.8 86 6.3 57.8 48 50584 Kenya 39.7 4.8 9.8 9.7 88.8 78.7 7 57.9 49 50600 Kenya 38.8 5.9 8.8 9.5 78.8 98.8 7.5 56.2 Mean 41.8 5.8 12 8 97 68.4 8.5 55.1 LSD 1.5 .7 1.6 1 6.3 4.4 .9 2.9 (p< . 5) CV % 2.2 7.4 8.1 7.8 4 4 6.5 3.3 DTF: days to 50% flowering, SLA: single leaf area (cm ), LL: leaf length (cm), LW: leaf width (cm), NLPP: number of leaves per plant, NPB: number of primary branches, PH: plant height (cm), and SPAD: soil plant analysis development. 10 Advances in Agriculture Table 6: Correlation in combined seasons. DTF LL LW NPB NLPP PH SLA SPAD DTF - LL 0.12∗ - LW 0.28∗∗ 0.62∗∗ - NPB 0.09 0.02 -0.20∗∗ - NLPP 0.1 -0.01 -0.11 0.63∗∗ - PH -0.07 0.16∗ -0.19∗ 0.82∗∗ 0.69∗∗ - SLA 0.21∗∗ 0.92∗∗ 0.88∗∗ -0.08 -0.06 0.01 - SPAD -0.04 -0.07 -0.11 0.54∗∗ 0.45∗∗ 0.59∗∗ -0.1 - ∗ implies significance difference at P <0.05;∗∗ implies significance difference at p <0.001 (2-tailed), DTF- days to 50% flowering, SLA- single leaf area (cm ), LL- leaf length (cm), LW- leaf width (cm), NLPP- number of leaves per plant, NPB- number of primary branches, PH- plant height (cm), SPAD- soil plant analysis development. Table 7: Stepwise regression analysis of the 7 evaluated traits. Step Variable Partial R square Adjusted R square F-test 1 Plant height 0.48 0.47 43.00∗ ∗Significant at p ≤ 0.05 y = 1.102x + 21.947, y = number of leaves per plant, and x = plant height. Table 8: Estimates of yield and yield related components of 49 spider plant accessions. Traits VE VG VP HBS (%) Season 1 1.0 11.2 12.2 91.8 DTF Season 2 1.0 10.1 11.1 91.0 Season 1 0.2 1.7 1.9 89.3 LL Season 2 0.2 1.7 1.9 89.3 Season 1 1.4 5.0 6.4 78.0 LW Season 2 1.4 5.3 6.7 79.2 Season 1 0.3 4.8 5.1 94.1 NPB Season 2 0.3 3.8 4.1 92.7 Season 1 13.4 2294.1 2307.5 99.4 NLPP Season 2 13.4 2314.6 2328.0 99.4 Season 1 8.2 908.6 916.8 99.1 PH Season 2 8.2 905.8 914.0 99.1 Season 1 0.4 2.6 3.0 86.5 SLA Season 2 0.4 2.6 3.0 86.5 Season 1 2.1 54.4 56.5 96.3 SPAD Season 2 2.1 45.1 47.2 95.5 VE = environmental variance, VG = genotypic variance, VP = phenotypic variance, HBS = broad sense heritability, NLLP = number of leaves per plant, NPB = number of primary branches, LL = leaf length, LW = leaf width, PH = plant height, SLA = single leaf area, and SPAD = soil plant analysis development. characterization with the use of molecular markers for paper is part of the M.S. thesis entitled “Genetic Characteri- germplasm characterization and genetic diversity since they zation and Nutrition Analysis of Eastern and South African are under little influence from the environment. 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