ABSTRACT
Seventy-two Jatropha curcas clonal accessions, collected from different parts of India, were grown in randomized block design and evaluated for 13 characters. These showed significant differences in growth, yield and seed characteristics, except for number of primary branches per plant. The accessions AFRI-35, AFRI-52 and AFRI-56 showed above mean value for 12 growth, fruit and seed yield characters except for number of primary branches, seed width and seed thickness. Accessions AFRI-12, AFRI-20, AFRI-21 and AFRI-39 showed above mean value for 11 traits. All the growth traits except for number of primary branches were positively correlated with fruit and seed yield. The magnitude of genotypic correlation coefficient (rg) was higher than their corresponding phenotypic coefficient of correlations (rp) for almost all the growth and yield characters, indicating the strong genetic linkage among all the characters. Kernel oil percentage was positively correlated with 20-seed weight and seed/kernel ratio. Seed/kernel ratio and oil percentage were negatively and non-significantly correlated with seed length and width. Principal component analysis revealed that plant height, collar diameter, number of secondary branches, crown diameter, fruit yield, seed yield, 20-seed weight, seed length, seed width, seed thickness, S/K ratio and oil percentage could be used as characters to distinguish the germplasm entries. K-means clustering revealed that trees from different geographic regions were grouped together in a cluster as well as trees from the same geographical area were placed in different clusters, suggesting that geographical diversity did not go hand in hand with genetic diversity. In addition, clustering identified promising accessions with favourable traits for future establishment of elite Seedling Seed Orchard (SSO) and Clonal Seed Orchard (CSO) for varietal and hybridization programmes.
Key words: Biodiesel, clustering, genetic variation, growth performance, principal component analysis.
The increased prices of petroleum products coupled with depletion of fossil fuel reserves and compulsion to reduce greenhouse gas emission, have evoked worldwide interest in searching for alternative sources of raw material for fuels (Mohapatra and Pande, 2010). Biodiesel, bio-ethanol and biomass gasification are the three major bio-energy and fast developing options which have huge potential in India to develop as renewable energy sources, where investment made would be economical (Parikh and Walia, 2002; Mishra, 2009). Bio-energy generated from bio-fuels constitute a suitable renewable energy source that may help to cope up with rising energy prices and offer new livelihood opportunities to farmers and rural communities around the world (Hazell and Pachauri, 2006; Rao et al., 2009). In recent years Jatropha curcas L., a perennial plant belonging to the family Euphorbiaceae has received considerable attention from researchers as a non-edible tree-born oil-seed crop (Tiwari et al., 2007; Das et al., 2010). It is a native of tropical Central America and is domesticated widely in Africa and Asia due to its ability to grow in varied climatic zones of tropical and subtropical regions particularly in marginal lands (Rao et al., 2008). J. curcas is a prominent species with a wide variety of uses: seeds, leaves and bark used in traditional medicine and for veterinary purpose (Heller, 1996) and oil as an insecticidal agent, in preparation of soap, candle, by-product glycerine and as germination promoter (Ginwal et al., 2005; Nabil and Yasser, 2012; Sharma et al., 2012). It is a highly promising species as bio-diesel crop of short gestation period, hardy nature, high quality oil contents and wide adaptability compared to most other non-edible oil yielding species. The seeds of J. curcas contain about 35 to 40% of non-edible oil (Keith, 2000). The magnitude of genetic variability present in base population of any crop species is pivotal to crop improvement; however, no species simultaneously performs best in respect to its all attribute (Vongadow and Bredenkamp, 1992; Raje and Rao, 2000; Idahosa et al., 2010). Considering the vast semi-wild distribution of J. curcas in different parts of India, there exists considerable genetic variability which can be exploited for potential economic yield (Pant et al., 2006; Rao. et al., 2008). Detection and exploitation of natural genetic variability in J. curcas is the need of the hour to deliver the best genotypes from the working germplasm collections to meet the immediate requirement of the growers. The first step in this process is selection criteria, which is, the retention of desired genotypes and elimination of undesirable ones. Once the selection criterias are clarified, the next is to choose a proper system of selection. Selection index maximizes genetic gain in a desired direction and is usefully applied to develop better cultivars with target traits (Ceron-Rojas et al., 2006). In a population under selection for quantitative characters, gene frequencies are altered and these are further modified by the mating systems that may be utilized to advance the selected individuals to the next generation (Chopra, 2000). Ginwal et al. (2005) reported variability of J. curcas from central India limited to seed source, morphology, germination and seedlings growth. Kaushik et al. (2007) reported divergence in seed oil traits of J. curcas in 24 locally collected accessions Srivastava et al. (2011) mentioned the paucity of date on growth performance and yield of J. curcas. One important limitation for selection for improvement is the extent of diversity present in the germplasm. Quantitative characters such as yield and its determinants exhibit substantial degree of interaction with the environment thus it is imperative to analyse the variability present in the germplasm and partition it into genotypic, phenotypic nature. Release of high yielding cultivars is impossible without ascertaining the magnitude of variation present in the available germplasm, interdependence of growth pattern with yield, extent of environmental influence on these factors, heritability and genetic gain of the materials (Rao et al., 2008). The potentiality of plants for optimum yield (seed yield and oil percentage) is dependent both on environmental and genotypic factor. The knowledge of genetic variation/diversity would be useful for selection especially when the desired ideo type is yet to be defined due to its wide adaptability. Knowledge of genetic variation for attributes viz: branching pattern, female to male flower ratio, pest resistance, drought hardiness and yield attributes in germplasm of Jatropha is of great significance in tree improvement programmes and particularly for selection of genotypes having more seed yield and oil content (Burely et al., 1984; Voncarlowitz, 1986, Wen et al., 2012; Ndir et al., 2013). Basha and Sujatha (2007) indicated modest levels of genetic variation in the Indian germplasm based on random amplified polymorphic DNA (RAPD) and inter simple sequence repeat (ISSR) markers. Reddy et al. (2007) reported 8 to 10% (AFLP; Amplified Fragment Length polymorphism; genetic fingerprinting technique) and 14 to 16% (RAPD) polymorphism in 23-selected provenances from 300 collections. Randae et al. (2008) reported a wide diversity in 12 germplasm of J. curcas through molecular markers. Sakaguchi and Somabi (1987) studied 40 genotypes of J. curcas from different places in Thailand. Mahajen et al. (2009) reported significant variation in oil content of J. curcas for Uttarakhand States of India. In the present investigation the magnitude of genetic variability is quantified in terms of morphological traits present in the existing base population (72 J. curcas clonal accessions) collected from different regions of India (Map 1) and to identify important yield attributing characters to provide useful information for developing improved high yielding J. curcas genotypes for establishment of elite seedling seed orchard (SSO) and clonal seed orchard (CSO) with favorable traits for future plantation and breeding programmes.
MATERIALS AND METHODS
Experimental site
Experiment was conducted at the experimental site of Arid Forest Research Institute, Jodhpur (AFRI) (24° 40´ N and longitude 71° 15´ E), India. The experimental site was flat, had loamy sand soil. The soil pH was 7.8 (recorded by digital pH meter) and organic matter content in the soil was about 0.25% (analyzed at laboratory level). The average annual rainfall of the region during the study period from 2007 to 2010 ranged between 139.2 mm in 2010 to 321.2 mm in 2007. Average number of rainy days annually is 10 to 15 and maximum temperature goes as high as 49oC in summer and drops to 0°C in winter (source: metrological database of CAZRI (Central Arid Zone Research Institute, Jodhpur).
Collection of plantation material
In the present study a representative set of clonal material in the form of stem cuttings of 72 accessions of J. curcas from different geographical regions of India were evaluate for genetic variation and cluster analysis. The collection of the clonal material in the form of stem cutting ranged from latitude 10.0°46' to 32°02'N and longitude 72.0° 45' to 95.0° 1'E (Table 1). The selection were made on phenotypic assessment of characters of economic interest, that is, plant height, number of primary and secondary branch, branching pattern, crown spread, girth, fruit and seed yield. Clonal material in the form of stem cuttings was raised to saplings under nursery conditions and when plants were 4-months old were used for planting. Care was taken to avoid trees infested with pests and diseases.
Plantation at experimental site
The plants were planted in the pits of 45 cm3 filled with mixture of FYM (farm yard manure): sand: soil in 1:1:1 ratio at 3 x 3 m spacing in randomized block design (RBD) having three replicates. Each replicate consisted of one plant propagated by stem cuttings of single mother plant. The plantation was done in July to August 2007. Plants were irrigated immediately after planting. Further, the irrigation was done at 15-days interval in summer and 30-days interval in winter. Mortality was replaced with new plants up to six month.
Data measurements
Measurements were taken in August 2010 for plant height (cm), collar diameter (cm), number of primary branches, number of secondary branch, crown diameter (cm). Fruit were collected and seed were harvested from five to eight picking of dried black fruits at 15 to 20 days interval from July to November in 2010; these were weighed and expressed as yield (g) per plant. Seed characteristics were analysed after separating seeds from the fruit, cleaned and stored in muslin cloth bags at ambient conditions (26°C and 55% RH). All seed lots were dried in hot air oven at 60°C till constant weight. The 20-seeds weight (g) were determined by using calibrated electronic balance to the nearest 0.01 g), seed/kernel ratio (S/K ratio) was calculated in order to determine the proportion of seed coat and length (mm), width (mm) and thickness (mm) of seed was recorded with digital calliper to the nearest 0.01 mm as per ISTA, (1976). For estimate oil content three replicates for each
seed lot were used, 20 g of kernel were ground and powdered before placing in Soxhlet apparatus and were extracted with petroleum ether (60°C) for six hours without interruption by heating it at 60±5°C over water bath. Oil content was calculated on percentage basis. In the present investigation the data of 2010 have been analysed.
Statistical analysis
Data were subjected to analysis of variance by using SPSS (version 8.0; SPSS Inc.). Linear correlation coefficients were calculated at both genotypic (rg) and phenotypic (rp) levels among the studied traits, as described by Mode and Robinson (1959). The estimated studied traits mean were subjected to a principal component analysis (PCA) to investigate the dimensionality of studied data sets in test population and to identify new meaningful underlying variables under particular growth environment. Non-hierarchical (K-means) Euclidian cluster analysis was done for growth and yield traits and seed characters in planted J. curcas accessions separately.
Variability in growth and yield attributes
Significant variation at p<0.01 in the mean value was observed in plant height, collar diameter, number of secondary branches, crown diameter, fruit yield and seed yield. Number of primary branch showed non-significant variation among all the tested accessions of J. curcas (Table 2). Maximum mean plant height 272.50 cm was recorded in AFRI-39 followed by 267.50 cm in AFRI-35, while minimum was 90.00 cm in accession AFRI-16. The maximum collar diameter 11.49 cm was in AFRI-35 closely followed by 11.15 cm in AFRI-9. The high degree of variability with regard to the number of secondary branch was observed as AFRI-7 had 22.00 secondary branches followed by 21.00 in (AFRI-9, AFRI-12 and AFRI-43), which were almost five times compared to the lowest rank series 4.00 in (AFRI-16, AFRI-28 and AFRI-63). Crown diameter ranged from 62.50 cm in AFRI-23 to 260.00 cm in AFRI-35. The recorded data pertaining to fruit and seed yielding parameters showed significant variation among the accessions. Out of 72 tested accessions only 65 seeded after a period of 36 month. Among the seeded plants fruit and seed yield was minimum 30.00 and 22.00 g in accessions AFRI-50 and varied up-to 1586.00 and 812.50 g in AFRI-32, respectively. Out of 72 accessions only 21 and 23 accessions expressed significant higher fruit and seed yield per plant, respectively over general mean.
Variability in seed characters
Table 2 revealed that from 72 studied accessions only 65 were seeded so the seed characteristic study was restricted to these seed yielded accessions only. Analysis of components of total variability in the germplasm indicated significant difference among the accessions for all the seed characteristic traits. Highest 20 seed weight was noticed 12.80 g in AFRI-3 nearly followed by 12.72 and 12.65 g in AFRI-31 and AFRI-30, respectively.
Whereas lowest 20 seed weight was observed 5.87 g in AFRI-63 closely followed by 5.88 g in AFRI-64 accession. The highest seed/kernel ratio and oil % was shown by accession AFRI-30 which had 0.81 and 57.32%, respectively while the lowest was showed by AFRI-6 with the value of 0.31 and 27.43%, respectively. Thirty accessions expressed significantly higher values over general mean of oil percent. Maximum seed length was observed 17.63 mm in AFRI-32 closely followed by 17.53 mm in AFRI-51 and minimum was 13.11 mm in AFRI-48. Seed width ranged from 9.24 mm in AFRI-22 to 11.51 mm in AFRI-30 accession which was closely followed by 11.46 mm in AFRI-40. Maximum seed thickness was observed 8.74 mm in AFRI-3 and minimum 7.10 mm in AFRI-28 accessions.
Table 3 showed positive association of correlation coefficient among different growth and yield traits. For growth and yield traits phenotypic correlation and genotypic correlation ranged from 0.087 to 0.978 (rp) and 0.100 to 1.00 (rg). Plant height and collar diameter exhibited significant correlation with all growth and yield traits at both phenotypic level and genotypic level. Number of primary branch exhibit higher r value for genotypic correlation (rg) than phenotypic correlation (rp) with number of secondary branch, crown diameter, fruit yield and seed yield. At phenotypic level its exhibited positive significant correlation only with number of secondary branch and crown diameter (it was 0.335 and 0.268, respectively). Number of secondary branch exhibited positive significant correlation with crown diameter, fruit yield and seed yield at both level. Crown diameter showed positive significant correlation with fruit and seed yield at both level. The maximum correlation coefficient for both rp and rg was observed between fruit and seed yield at both level with 0.978(rp) and 1.002(rg). Data in Table 3 revealed that seed yield showed higher values of genotypic correlation for all parameters (that is, plant height, collar diameter, number of primary branch, number of secondary branch, crown diameter and fruit yield) compared to phenotypic correlation.
Table 4 showed the correlation coefficient between various seed characteristics here it ranged from -0.048 (seed length with oil % on kernel basis) to 0.682 (Seed width with seed length) of rp and -0.039 (Seed length with seed/kernel ratio) to 0.715 (Seed kernel ratio with 20-seed weight) of rg. 20 seed weight exhibited a significant positive correlation at p<0.01 with seed/kernel ratio, oil %, seed length and seed thickness at both phenotypic and genotypic level whereas there was no significant positive correlation between seed width and 20-seed weight. High rg value of 20 seed weight with seed/kernel ratio and oil % observed than rp. Seed/kernel ratio showed positive significant correlation only with oil percent at phenotypic and genotypic level. Positive value of r was registered
between seed/kernel ratio and seed thickness without any significance at phenotypic and genotypic level. There was non-significant negative correlation between seed/kernel ratio and seed length and width. Non significant negative correlation was also observed between oil % and seed length, width and thickness at phenotypic and genotypic levels. Seed length exhibited highly significant positive correlation value of rp with seed width and seed thickness but also exhibited low level of genotypic correlation between them. Seed width showed significant positively correlation with seed thickness at rp level but poorly associated at rg level.
Principal component analysis
Table 5 revealed that the first principal component explained 36.15% of the total variation and dominated by plant height (0.876), crown diameter (0.862), collar diameter (0.838) and number of secondary branches (0.831). The coefficient of the second PC revealed a positive relationship with seed size and weight and received large contribution from seed length, seed thickness, seed width (0.917, 0.914 and 0.859, respectively). The PC II explained an additional 24.62% of total variation. The coefficient of third PC explained large contribution from S/K ratio, oil % on kernel basis and 20-seed weight (0.926, 0.888 and 0.748, respectively) and contributes 15.43% of total variation. The fourth PC (8.36% of total variation) largely contributed by fruit (0.925) and seed yield (0.922).
Genetic divergence in growth characteristics
Six clusters were delineated by K-mean clustering for the 72 accessions of Jatropha shown in Table 6. Cluster VI had highest 30 members in it and cluster IV had lowest 2 members in it. Cluster I and II had 13 and 10 members and cluster III and V had 9 and 8 members, respectively. Cluster I consisted of high mean value of height (267.50 cm), collar diameter (11.49 cm), number of secondary branches (17.00) and crown diameter (260.00 cm). Cluster IV consisted of highest mean of number of primary branches which had mean value of 2.50. The minimum inter-cluster distance seen between II and III (42.58) followed by I and VI (49.65). While maximum inter-cluster distance was seen between I and V with value of 192.69 depicted in Figure 1.
Genetic divergence in yield and seed characteristics
Sixty-five accessions of Jatropha were grouped in six
clusters on the basis of K-mean clustering shown in Table 7. Minimum one accession was separated in cluster III and maximum 25 were placed in cluster V followed by 20 in cluster IV. Accession AFRI-32 which is placed in cluster III showed highest mean value for fruit and seed yield, seed length, seed width and seed thickness and this showed lowest mean value for 3 characters viz. (20 seed weight, seed/kernel ratio and oil % on the basis of kernel). Lowest mean value for fruit and seed yield, seed length, seed width and seed thickness was showed by cluster V which had 25 members in it. Highest mean of seed/kernel ratio and oil % was seen in cluster VI with the value of 0.63 and 50.30%, respectively. Inter-cluster distance between cluster III and IV was the maximum at 1634. Minimum inter-cluster distance was seen between cluster IV and V followed by cluster I and VI with the distance value of 257.91 and 258.05, respectively (Figure 2).
Study revealed that different accessions of J. curcas exhibited considerable amount of morphological variability. The sources were statistically at par with respect to the plant height, collar diameter, numbers of secondary branches, crown diameter, fruit yield, seed yield, 20-seed weight, seed/kernel ratio, oil percent, seed length, seed width and seed thickness but the number of primary branches did not differ significantly as this favours the finding of Pant et al. (2006) and Vijayanand et al. (2009). The variability in growth performance of
accessed accession significantly differs and the finding agreed with Saikia et al. (2009) in which they got considerable amount of variation in plant height, stem girth and 100-seed weight in 34 accessed J. curcas accession collected from 17 States of India. The apparent variability in growth performance indicates that economic benefits may be obtained. The results of the present study will be valuable for the conservation of genetic variation, prospects of improvement and assessment of the potential of the locally adapted accession source. In present study fruit and seed yield significantly differ and agree with the finding of Francis et al. (2005) but in contrast with genetic variability, which is rather small in Indian germplasm (Basha and Sujatha, 2007). Seed oil content variation is more widely reported not only in annual crops but also in a wide variety of trees borne oil seed (Kaura et al., 1998). The variation found in oil content in the present study along with other seed morphological attributes presents us with a viable selection alternative at a very early stage (collection of germplasm) from base seed material. This could be of use in improvement programmes of J. curcas. The variation in J. curcas population has been recorded earlier by Wani et al. (2006) for oil content (27.8 to 39% on kernel basis) and 100-seed weight (44 to 77 g), in India accessions and by Kaushik et al. (2007) in 100 seed weight (49 to 69 g) and oil content (28 to 39%) in Haryana-India accessions. Similarly Rao et al. (2008) found wide variation in 100 seed weight (57 to 79 g) and oil content (30 to 37%) for Andhra Pradesh, India, accessions. Srivastava et al. (2011) reported 17 to 34% oil yield in ten restricted accessions screened on the basis of growth performance and biomass characterization. Large variation in average seed weight (0.46 to 0.83 g/seed) has been reported among 18 natural provenances of J. curcas in Mexico (Martinez- Herrera et al., 2010). Ouattara et al. (2013) reported high variability in J. curcas seed traits with 100 seed weight ranging from 63.68 to 77.83 g among the 19 accessions collected from Senegal. In the present investigation, the 20 seed weight ranged from 5.87 to 12.80 g whereas oil % on kernel basis ranged from 27.43 to 57.32% in 65 seeded accession out of 72 collected accessions. Variation in characters could be due the fact that the species had been collected over a wide range of rainfall, temperature and soil type. Wen et al. (2012) observed that seed weight and oil content of J. curcas were positively correlated with the mean annual sunshine duration, mean annual temperature, mean minimum daily temperature of the coldest month, mean maximum daily temperature of the warmest month and the mean annual evaporation, but negatively correlated with altitude and the mean annual precipitation. Ndir et al. (2013) observed that seed oil content and seed thickness were correlated to rainfall; however, seed length, breadth and 20 seed-weight were not correlated to rainfall. Moreover, genetic diversity was not correlated to geographic position in J. curcas (Ndir et al., 2013). However, one part of variability is under genetic control. Kaushik et al. (2007) envisaged that environment has comparatively low influence on the seed traits and oil content. High heritability and high genetic advance for 100 seed weight have been reported by Kaushik et al. (2007) in J. curcas. Hence these characters can be considered as best gain characteristics for J. curcas improvement program because of its strong genetic control and the wide variability. Plant height and number of branches are also important characters that can be-looked upon as major selection indices when the objective is to incorporate J. curcas in an agro-forestry system. Variation observed in yield characters can be useful in selecting plant types for block plantations with high yield and higher % of oil in seed as the primary objective. The fruit and seed yield as expected is positively associated (rp and rg) with plant height and number of secondary branches suggesting that phenotypic and genotypic relation is reliable and in turn offer good scope for selection of CPP (Candidate plus plant) at primary level. Knowledge of genetic diversity within natural population in and outside the centre of origin is required to know the potentially valuable genetic material. Here the growth and yield attributes in these J. curcas accessions can be of great potential in improvement programs.
Correlation analysis is an important tool to bring information about relationship between growth and yield attributes, however lack of relationship between traits and environment makes selection of CPP poorly predictable for improvement program. The degree of correlation depends upon the gene causing such variation and their developmental relation. Correlation matrix revealed interesting relationship in the growth traits, yield traits and seed characters studied. The magnitude of genotypic correlation coefficient (rg) was higher than their corresponding phenotypic coefficient of correlations (rp) for almost all the growth and yield characters indicating the strong genetic inherent association ship or gene linkage among all the characters and suggests that their phenotype are more regulated with gene and less influenced by environmental effect. Such positive and significant correlation was registered in J. curcas and these characters are an advantage to the breeder for bringing improvement of traits (Ginwal et al., 2004; Das et al., 2010). It has been well known that seed related characteristics can also be used to examine variability with in plant species (Rawat and Bakshi, 2011). Ouattara et al. (2013) observed that seed length was significantly correlated to all seed traits excepted Seed/fruit ratio in J. curcas. In the present investigation positive significant correlation of 20-seed weight existed with seed/kernel ratio, oil %, seed length and seed thickness at both rg and rp level from these result it is evident that these traits are interrelated at their gene level or these are QTL (Quantitative Trait Loci) therefore, seed weight is important trait for early selection of seed sources. This is further in agreement with the finding of Rao et al. (2008) in J. curcas and Kaura et al. (1998) in Azadirachta indica. 20-seed weight exhibited positive relationship with seed width at both rg and rp level but it's not at significant level. Very high degree of direct relationship observed between fruit yield and seed yield per plant at both rp (0.978) and rg (1.002) level indicate that both are in same and strong genetic control. Here, seed/kernel ratio exhibited high rp and rg value with oil % indicated that both characters are in strong genetic control and suggested the effectiveness of indirect selection for kernel oil content through 20-seed weight. The estimation of 20-seed weight being less expensive and laborious compared to kernel oil content, the former can be used as a tool during selection process. The existence of negative correlation at both phenotypic and genotypic level between oil % and seed length, seed width and seed thickness indicated that both characters are independent on each other at both level and these traits variation in response to changing environmental condition (Valencia-Diaz and Montana, 2005). Significant correlations between fruit and seed yield with plant height, collar diameter, number of secondary branches and crown diameter also indicates that plant with good height and branching tend to develop more crown and flower subsequently fruit and seed. It indicates that the selection in any one of these yield attributing traits will lead to increase in the other traits, thereby finally enhancing the yield. Selection from early plantations of J. curcas can be made on the basis of these characters because of the difficulty in selecting plants solely based on yield as the full potential of yield is reached only after several years of growth in J. curcas. Similar relations have been reported in Pennisetum typhoedes by Van Osteroma et al. (2006) as well and in Chenopodiem quinoa by Bhargava et al. (2007).
The results from principal component analysis indicate that among all the 12 studied variable, variation is contributed by plant height, collar diameter, number of secondary branch, crown diameter, fruit yield, seed yield, 20-seed weight, seed length, width, thickness, S/K ratio and oil %. The first four components in the collection with eigen values were able to explain 84.56% of the total variance for morphological traits. According to Mardia et al. (1979), the total variance accumulated by principal component close to 80% explains satisfactorily the variability manifested between individuals. It is concluded that the above variables could be used as characters to distinguish the germplasm entries and might also be taken into consideration for effective selection of parents during hybridization program of this use full plant.
Genetic diversity
Analysis of genetic diversity in collections facilitated reliable classification of accessions and identification of core subsets of the accessions for future utility in specific breeding purposes. K-means clusters clustering pattern in this study revealed that trees from different geographic regions were grouped together in a cluster and also trees from the same geographical area placed in different clusters, suggesting that geographical diversity did not go hand in hand with genetic diversity. K-means clustering is done to understand the trend of evolution and choose genetically diverse parents for obtaining desirable recombination (Tams et al., 2006). By clustering of growth attributes the maximum inter-cluster distance (192.69) was observed between I/V cluster while in yield and seed characters the distance was (1634.1) observed between III/V cluster indicating substantial segregation.
Existence of substantial variation and diversity can be utilized for further tree improvement programmers of the species. Selection of parent material from such cluster for hybridization programme will develop elite plant with desirable characters. The minimum inter-cluster distance observed in growth attributes (42.58) between II/III and in yield and seed attributes (257.91) between IV/V indicates that accessions in these groups are closely related. Therefore, the selection of parent plant from these clusters should be avoided. Finally the cluster that are having more inter-cluster distance and high mean will produce divergent candidate.
In the study, most of the accessions are growing well in arid climate region of, Rajasthan, India. However, accession AFRI-35, AFRI-52, AFRI-56, AFRI-12, AFRI-20, AFRI-21 and AFRI-39 performing better among studied 72 accessions. Significant positive association of kernel oil content (percent) with 20-seed weight suggested the effectiveness of indirect selection for kernel oil content through 20-seed weight. Principal component analysis stated that plant height, collar diameter, number of secondary branch, crown diameter, fruit yield, seed yield, 20-seed weight, seed length, width, thickness, S/K ratio and oil percent could be used as morphological marker to distinguish the germplasm. On the bases of observations recorded here on a divergent group of J. curcas accessions, it is concluded that hybridization between the accessions of variable clusters may help to produce wide spectrum of variation in the segregating progeny and thus may be helpful in hybridization program to cope up the fore coming limitations pertaining to improvement of bio-fuels species for biodiesel industry. It is also suggested that for creating variability and developing the best selection a large number of divergent lines, instead of few should be used in the hybridization.
The authors have not declared any conflict of interests.
Authors are thankful to Director, Arid Forest Research Institute, Jodhpur, India for providing necessary institutional support.
REFERENCES
Basha SD, Sujatha M (2007). Inter and intra population variability of Jatropha curcas (L.) characterised by RAPD and ISSR markers and development of population-specific SCAR markers. Euphytica 156: 375–386.
Crossref |
|
|
Bhargava A, Shukla S, Ohri D (2007). Genetic variability and interrelationship among various morphological and quality traits in quinoa (Chenopodium quinoa Wild.). Field Crops Res. 101: 104–116.
Crossref |
|
|
|
Burely J, Huxely PA, Owino F (1984). Design, management and assessment of species, provenance and breeding trial of multipurpose tree. In: R.D. Barnes and G.L. Gibson (Eds). Provenance and genetic improvement strategies in tropical forest tree. Oxford, Commonwealth Forestry Institute, UK. pp. 70-80 |
|
|
Ceron-Rojas JJ, Crossa J, Sahagun-Castellanos J, Castillo-Gonzalez F, Antacruz-Varela A (2006). Selection index methods based on eigenanalysis. Crop Sci. 46: 1711-1721.
Crossref |
|
|
|
Chopra VL (2000). Plant breeding – Theory and practice 2nd ed. Oxford and IBH Pub. Co. Pvt. Ltd, New Delhi, p.10. |
|
|
|
Das S, Misra RC, Mahapatra AK, Gantayat BP, Pattnaik RK (2010). Genetic Variability, Character Association and Path Analysis in Jatropha curcas, World Applied Sci. J. 8(11): 1304-1308. |
|
|
Francis G, Edinger R, Becker K (2005). A concept for simultaneous wasteland reclamation, fuel production, and socio-economic development in degraded areas in India: need, potential and perspectives of Jatropha plantations. Nat. Resour. Forum 29: 12-24.
Crossref |
|
|
|
Ginwal HS, Phartyal SS, Rawat PS, Srivastav RL (2005). Seed source variation in morphology, germination and seedling growth of Jatropha curcas Linn. in Central Asia. Silvae Genetica 54: 76-80. |
|
|
|
Ginwal HS, Rawat PS, Srivastav RL (2004). Seed source variation in growth performance and oil yield of Jatropha curcas L. Central India. Silvae Genetica 53(4): 186-192. |
|
|
|
Hazell P, Pachauri RK (2006). Bio-energy and Agriculture: Promises and Challenges – An overview. Focus 14. In Bio-Energy and Agriculture: Promises and Challenges. Eds. Hazell P and Pachauri R. K. International Food Policy Research Institute, Washington, USA and The Energy and Resources Institute, New Delhi, India, pp1-2. |
|
|
|
Heller J (1996). Physic nut Jatropha curcas L. Promoting the conservation and use of underutilized and neglected crops. Institute of Plant Genetic and Crop Plant Research, Gatersleben/International Plant Genetic Resource Institute, Rome, Italy. p. 44. |
|
|
|
Idahosa DO, Alika JE, Omoregie AU (2010). Genetic variability, heritability and expected genetic advance as Indices for yield and yield components selection in cowpea (Vigna unguiculata (L.) walp. Academia Arena 2(5): 22-26. |
|
|
|
ISTA (1976). International rules for seed testing. Proc. Int. Seed Test. Assoc. (ISTA) 31: 1-152. |
|
|
|
Kaura SK, Gupta SK, Chowdhury JB (1998). Morphological and oil content variation in seeds of Azadirachta indica A. Juss. (Neem) from northern and western provenances of India. J. Plant Foods Hum. Nutr. (Formerly Qualitas Plantarum) 52: 132–136. |
|
|
Kaushik N, Kumar K, Kumar S, Kaushik N, Roy S (2007). Genetic variability and divergence studies in seed traits and oil content of Jatropha (J. curcas L.) accessions. Biomass Bioenergy 31: 497–502.
Crossref |
|
|
Keith OP (2000). A review of Jatropha curcas an oil plant of unfulfilled promise. Biomass Bioenergy 19: 1-15.
Crossref |
|
|
|
Mahajen R, Pongen I, Dutt S, Chand T, Rana RC (2009). Oil content variation of pruning nut (Jatropha curcas Linn.) seeds in Uttarakhand. Ann. For. 17(1): 97-100. |
|
|
|
Mardia KV, Kent JT, Bibby JM (1979). Multivariate Analysis. Probability and Mathematical Statistics. Academic Press, London. |
|
|
|
Martinez-Herrera J, Martinez-Ayala AL, Makkar H, Francis G, Becker K (2010). Agroclimatic condition, chemical and nutritional characterization of different provenances of Jatropha curcas L. from Mexico. Eur. J. Sci. Res. 39: 396-407. |
|
|
Mishra DK (2009). Selection of candidate plus phenotypes of Jatropha curcas L. using method of paired comparisons. Biomass Bioenergy 33(3): 542-545.
Crossref |
|
|
Mode CJ, Robinson HF (1959). Pleitropism and genetic variance and covariance. Biometrics 15: 518-537.
Crossref |
|
|
|
Mohapatra S, Pande PK (2010). Genetic variability on growth, phenological and seed characteristics of Jatropha curcas L. Nat. Sci. Biol. 2(2): 127-132. |
|
|
|
Nabil AE Azzaz, Yasser AM Khalifa (2012). Jatropha curcas Oil as Insecticide and Germination Promoter. J. Appl. Sci. Res. 8(2): 668-675. |
|
|
|
Ndir KN, Kane M, Ouattara B, Bayala R, Diedhiou I (2013). Variability in seed traits, oil content and genetic diversity in local and exotic accessions of Jatropha curcas L. in Senegal. Afr. J. Biotechnol. 12(34): 5267-5277. |
|
|
|
Ouattara B, Diedhiou I, Ndir KN, Agbangba EC, Cisse N, Diouf D, Akpo EL, Zongo JD (2013). Variation in seed traits and distribution of Jatropha curcas L. in Senegal. Int. J. Curr. Res. 5(2): 17-21. |
|
|
|
Pant KS, Khosla V, Kumar D, Gairola S (2006) Seed oil content variation in Jatropha curcas Linn. in different altitudinal ranges and site conditions in H.P. India. Lyonia 11(2): 31–34. |
|
|
|
Parikh J, Walia A (2002). Techno-economic Assessment of Bioenergy in India; Technology Information Forecasting and Assessment Council (TIFAC), Ministry of Science and Technology, Government of India, New Delhi, India. |
|
|
|
Raje RS, Rao SK (2000). Genetic parameters of variation for yield and its components in mungbean (Vigna radiata [L.] Wilc.) over environments. Legume Res. 23(4): 211–216. |
|
|
Randae SA, Srivastava AP, Rana TS, Srivastava J, Tuli R (2008). Easy assessment of diversity in Jatropha curcas L. plant using two single-primer amplification reaction (SPAR) methods. Biomass Bioenergy 32: 533-540.
Crossref |
|
|
Rao GR, Korwar GR, Shanker AK, Ramakrishna YS (2008). Genetic associations,variability and diversity in seed characters, growth, reproductive phenology and yield in Jatropha curcas (L.) accessions. Trees. doi:10.1007/s00468-008-0229-4.
Crossref |
|
|
|
Rao MRG, Ramesh S, Rao AM, Gangappa E (2009). Exploratory studies on components of variability for economic traits in jatropha (Jatropha curcas L.). Karnataka J. Agric. Sci. 22(5): 967-970. |
|
|
|
Rawat K, Bakshi M. (2011). Provenance variation in cone, seed and seedling characteristics in natural populations of Pinus wallichiana A.B. Jacks (blue pine) in India. Ann. For. Res. 54: 39-55. |
|
|
|
Reddy MP, Chikara Patolia JS, Ghosh A (2007). Genetic Improvement of Jatropha curcas adaptability and oil yield. Expert seminar on Jatropha curcas L. Agronomy and Genetics. 26-28 March, Wageningen, The Netherlands, Published by FACT Foundation. |
|
|
|
Sakaguchi S, Somabi M (1987). Exploitation of Promising Crops of Northeast Thailand Siriphan Offset. Thailand: Khon Kaen. |
|
|
|
Saikia SP, Bhau BS, Rabha A, Dutta SP, Choudhari RK (2009). Study of accession source variation in morpho-physiological parameters and growth performance of Jatropha curcas Linn. Curr. Sci. 96(12): 1631-1636. |
|
|
|
Sharma S, Dhamijha HK, Parashar B (2012). Jatropha curcas: A Review Asian J. Res. Pharm. Sci. 2(3): 107-111. |
|
|
Srivastava P, Behera SK, Gupta J, Jamil S, Singh N, Sharma YK (2011). Growth performance, variability in yield traits and oil content of selected accessions of Jatropha curcas L. growing in a large scale plantation site. Biomass Bioenergy 35: 3936-3942.
Crossref |
|
|
Tams SH, Bauer E, Oettler G, Melchinger AE, Scho¨n C (2006). Prospects for hybrid breeding in winter triticale: II. Relationship between parental genetic distance and specific combining ability. Plant Breed. 125: 331–336.
Crossref |
|
|
Tiwari AK, Kumar A, Raheman H (2007). Biodiesel production from Jatropha (Jatropha curcas) with high free fatty acids: An optimized process. Biomass Bioenergy 31: 569-575.
Crossref |
|
|
Valencia-Diaz S, Montana C (2005). Temporal variability in the maternal environment and its effect on seed size and seed quality in Flourensia cernua DC. (Asteraceae). J. Arid Environ. 63: 686-695.
Crossref |
|
|
Van Osteroma EJ, Weltzienb E, Yadav OP, Bidingerb FR (2006). Grain yield components of pearl millet under optimum conditions can be used to identify germplasm with adaptation to arid zones. Field Crops Res. 96: 407–421.
Crossref |
|
|
Vijayanand V, Senthil N, Vellaikumar S, Paramathma M (2009). Genetic Diversity of Indian Jatropha Species as Revealed by Morphological and ISSR Markers. J. Crop Sci. Biotech 12(3):115-120. DOI No. 10.1007/s12892-009-0081-0
Crossref |
|
|
|
Voncarlowitz PGL (1986). Defining ideotypes of multipurpose trees for their phenotypic selection and subsequent breeding. In: Proceedings of the international workshop on biological diversity and genetic resources of underexploited plants, Kew, 14, UK. |
|
|
|
Von Gadow K, Bredenkamp BV (1992). Forest management. Pretoria: Academica. |
|
|
|
Wani SP, Osman M, D'silva E, Sreedevi TK (2006). Improved livelihoods and environmental protection through biodiesel plantations in Asia. Asian Biotechnol. Dev. Rev. 8(2): 11–29. |
|
|
Wen Y, Tang M, Sun W, Zhu H, Wei Z, Chen F, Tang L (2012). Influence of Climatic Factors and Soil Types on Seed Weight and Oil Content of Jatropha curcas in Guangxi, China. Procedia Environ. Sci. 12: 439-444.
Crossref |
.png)
.png)
