NATURAL VARIATION IN LEHSUA (CORDIA MYXA ROXB.) I N
RAJASTHAN”
Doctor of Philosophy in
Horticulture
BY
Mr. BANWARI LAL NAGAR
2004
RAJASTHAN AGRICULTURAL UNIVERSITY, BIKANER S.K.N. COLLEGE OF AGRICULTURE, JOBNER
Table TITLE PAGE No. No. 1. Geographical locations of different provenances of Lehsua (Cordia myxa Roxb.) in Rajasthan 2. Extent of variation in morphological characteristics among the different provenances of Lehsua (Cordia myxa Roxb.) 3. Extent of variation in fruit characteristics among the different provenances of Lehsua (Cordia myxa Roxb.) 4. Extent of variation in fruit quality characteristics among the different provenances of Lehsua (Cordia myxa Roxb.) 5. Extent of variation in morphological characters on pooled mean basis in Lehsua (Cordia myxa Roxb.) 6. Extent of variation in fruit characteristics on pooled mean basis in Lehsua (Cordia myxa Roxb.) 7. Extent of variation in fruit quality characteristic on pooled mean basis in Lehsua (Cordia myxa Roxb.) 8. Variance and coefficient of variability for morphological characteristics during 2002 and 2003 in Lehsua (Cordia myxa Roxb.) 9. Estimates of genetic parameters for morphological characteristics during 2002 and 2003 in Lehsua (Cordia myxa Roxb.) 10. Variance and coefficient of variability for fruit characteristics during 2002 and 2003 in Lehsua (Cordia myxa Roxb) 11. Estimates of genetic parameters for fruit characteristics during 2002 and 2003 in Lehsua (Cordia myxa Roxb.) 12. Variance and coefficient of variability for quality
characteristics during 2002 and 2003 in Lehsua (Cordia myxa Roxb.) 13. Estimates of genetic parameters for fruit quality characteristics during 2002 and 2003 in Lehsua (Cordia myxa Roxb.) Table TITLE PAGE No. No. 14. Variance and coefficient of variability for morphological characteristics in Lehsua (Cordia myxa Roxb.) on pooled data basis 15. Estimates of genetic parameters for morphological characteristics in Lehsua (Cordia myxa Roxb.) on pooled data basis 16. Variance and coefficient of variability for fruit characteristics in Lehsua (Cordia myxa Roxb.) on pooled data basis 17. Estimates of genetic parameters for fruit characteristics in Lehsua (Cordia myxa Roxb.) on pooled data basis 18. Variance and coefficient of variability for fruit quality characteristics in Lehsua (Cordia myxa Roxb.) on pooled data basis 19. Estimates of genetic parameters for fruit quality characteristics Lehsua (Cordia myxa Roxb.) on pooled data basis 20 Genotypic (above diagonal) and phenotypic (below diagonal) correlation coefficient between various attributes and fruit weight in Lehsua (pooled basis) 21. Estimates of direct and indirect effects at genotypic (G) and
phenotypic (P) levels of various characters on fruit weight in Lehsua (Pooled basis) 22. Clustering of genetic divergence among different Lehsua (Cordia myxa Roxb.) provenances during 2002 23. Contribution of each character to divergence among the different Lehsua (Cordia myxa Roxb.) provenances during 2002 24. Average intra and inter cluster D2 values for different Lehsua (Cordia myxa Roxb.) provenances during 2002 25. Average intra and inter cluster distance (D values) among different Lehsua (Cordia myxa Roxb.) provenances during 2002
Table TITLE PAGE No. No. 26. Cluster mean of various characters in Lehsua during 2002 27 Clustering of genetic divergence among different Lehsua (Cordia myxa Roxb.) provenances during 2003 28 Contribution of each character to divergence among the different Lehsua (Cordia myxa Roxb.) provenances during 2003 29 Average intra and inter cluster D2 values for different Lehsua (Cordia myxa Roxb.) provenances during 2003 30 Average intra and inter cluster distance (D values) among different Lehsua (Cordia myxa Roxb.) provenances during 2003 31 Cluster mean of various characters in Lehusa during 2003 32 Clustering of genetic divergence among different Lehsua (Cordia myxa Roxb.) provenances (pooled basis) 33 Contribution of each character to divergence among the different Lehsua (Cordia myxa Roxb.) provenances (pooled basis) 34 Average intra and inter cluster D2 values for different Lehsua (Cordia myxa Roxb.) provenances (pooled basis) 35 Average intra and inter cluster distance (D values) among different Lehsua (Cordia myxa Roxb.) provenances (pooled basis) 36 Cluster mean of various characters in Lehusa (pooled basis)
LIST OF PLATES
PLAT PARTICULARS PAGE E No. No. 1. Variation in fruit size in Cordia myxa Roxb. ……
2. Variation in trunk shape in Cordia myxa Roxb. ……
3. Variation in number of fruits per cluster in Cordia myxa Roxb. ……
4. Branching pattern in Cordia myxa Roxb. ……
LIST OF APPENDICES S. PARTICULARS No. I Analysis of variance for morphological, fruit and fruit quality characteristics in Lehsua (Cordia myxa Roxb.) during 2002
II Analysis of variance for morphological, fruit and fruit quality characteristics in Lehsua (Cordia myxa Roxb.) during 2003
III Analysis of variance for morphological, fruit and fruit quality characteristics in Lehsua (Cordia myxa Roxb.) pooled basis
CONTENTS
DETAILS PAGE NO. 1. INTRODUCTION ------2. REVIEW OF LITERATURE 2.1 Genetic variability ------2.2 Correlations ------2.3 Path coefficient analysis ------2.4 ------DEGREE OF GENETIC DIVERGENCE 3. Materials and methods 3.1 ------3.2 DISTRICTS/ PROVENANCES/SITES ------3.3 StatisticalMETHODOLOGY analysis ADOPTED AND OBSERVATIONS ------3.4 Genetic divergence ------4. EXPERIMENTAL RESULTS 4.1 Evaluation of provenances ------4.2 Variability estimates and genetic studies ------4.3 Correlation studies ------4.4 Path coefficient studies ------4.5 Degree of genetic divergence for different traits ------5. DISCUSSION 5.1 Evaluation of provenances ------5.2 Variability estimates and genetic parameters ------5.3 Correlation studies ------5.4 Path coefficient studies ------5.5 Genetic divergence ------6. SUMMARY 6.1 Evaluation of different Lehsua provenance for the ------selection of plus tree in Rajasthan 6.2 Variability estimates and genetic studies ------6.3 Correlation studies ------6.4 Path coefficient studies ------6.5 Genetic divergence studies ------Conclusions ------BIBLIOGRAPHY ------ABSTRACT ------APPENDICES ------
RAJASTHAN AGRICULTURAL UNIVERSITY, BIKANER
S.K.N. COLLEGE OF AGRICULTURE, JOBNER
CERTIFICATE-I
Dated: ------2004
This is to certify that Mr. BANWARI LAL NAGAR successfully completed the comprehensive examination held on –03rd---September, 2001 as required under the regulation for Doctor of Philosophy degree.
HEAD Department of Horticulture S.K.N. College of Agriculture, Jobner
RAJASTHAN AGRICULTURAL UNIVERSITY, BIKANER S.K.N. COLLEGE OF AGRICULTURE, JOBNER
CERTIFICATE-II
Dated: ------2004
This is to certify that this thesis entitled “Natural variation in Lehsua (Cordia myxa Roxb.) in Rajasthan”, submitted for the degree of Doctor of Philosophy in the subject of Horticulture embodies bonafide research work carried out by Mr. BANWARI LAL NAGAR under my guidance and supervision and that no part of this thesis has been submitted for any other degree. The assistance and help received during the course of investigation have been fully acknowledged. The draft of the thesis was also approved by the advisory committee on 11th November, 2003.
(M.S. FAGERIA) HEAD Major Advisor Department of Horticulture S.K.N. College of Agriculture, Jobner
DEAN S.K.N. College of Agriculture, Jobner.
RAJASTHAN AGRICULTURAL UNIVERSITY, BIKANER S.K.N. COLLEGE OF AGRICULTURE, JOBNER
CERTIFICATE-III
Dated :------2004 This is to certify that this thesis entitled “Natural variation in Lehsua (Cordia myxa Roxb.) in Rajasthan”, submitted by Mr. BANWARI LAL NAGAR to Rajasthan Agricultural University, Bikaner in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Agriculture in the subject of Horticulture after recommendation by the external examiner was defended by the candidate before the following members of the advisory committee. The performance of the candidate in the oral examination on his thesis has been found satisfactory, we therefore, recommend that the thesis be approved.
(M.S. FAGERIA) Major Advisor
HEAD Department of Horticulture (R.S. DHAKA) S.K.N. College of Agriculture, Jobner Advisor
(I.J. GUPTA) Advisor
APPROVED (B.L. KAKRALIA)
Advisor Dean, Post Graduate Studies (DHIRENDRA SINGH) Rajasthan Agricultural University, Dean, PGS Nominee Bikaner
RAJASTHAN AGRICULTURAL UNIVERSITY, BIKANER S.K.N. COLLEGE OF AGRICULTURE, JOBNER
CERTIFICATE-IV
Dated :------2004
This is to certify that Mr. BANWARI LAL NAGAR of the Department of Horticulture, S.K.N. College of Agriculture, Jobner has made all corrections/modifications in the thesis entitled “Natural variation in Lehsua (Cordia myxa Roxb.) in Rajasthan”, which were suggested by the external examiner and the advisory committee in the oral examination held on ------2004. The final copies of the thesis duly bound and corrected were submitted on------2004, are enclosed herewith for approval.
(M.S. FAGERIA) Major Advisor
HEAD Department of Horticulture S.K.N. College of Agriculture, Jobner
DEAN S.K.N. College of Agriculture, Jobner
Approved
DEAN, PGS RAU, BIKANER
1. INTRODUCTION
Lehsua or Gonda or Indian cherry (Cordia myxa Roxb.) is a minor fruit that grows throughout India in arid and semi arid regions. Lehsua belongs to family Boraginaceae; probably originated in India. The plant is medium sized tree, can tolerate drought and moderate shade. Yet it is not grown in orchards and grows in wild state in wastelands along farm boundaries or on road side. It also seen on farm lands as scattered Solitary tree. Studies on the flowering and fruiting in Cordia myxa revealed that the average number of flower buds per cluster were twenty. The bud development may be divided into eight stages. The anthesis took place between 7.15pm to 8.45pm. Only two per cent buds formed fruits (Vashishtha et al,1985) Two flushes of vegetative growth takes place, first confined to March- April and second August-September period. Fruiting takes place on auxillary buds of current season growth. Study of variation is the first step for any breeding programme. Effective tree breeding depends on an understanding of tree variation in nature and preserving such variation for future use. Variation means, the occurrence of differences among populations and individuals within a population due to the differences in their genetic composition and the environment under which they are growing. In the natural population of a species the presence of geographic differences also cause variations. High genetic variation within and among populations has been demonstrated in all crop species. Most successful tree improvement programmes are those in which proper provenance or provenances are used (Zobel and Talbet, 1984). The
morphological and physiological traits exhibit a significant amount of genetic variation both within and between plant populations (Stebbins, 1950 ; Stern and Roche, 1974). Species exhibit both genetic and environmental variations at population level and genetic variation is expected to occur from the segregation of different genotypes. In India, Lehsua is commonly found in Rajasthan, Madhya Pradesh, Uttar Pradesh, Punjab, Maharashtra and Gujarat. Besides India, it is also found in Burma, Egypt, China, Sri Lanka and tropical Australia (Mc Cann, 1985). In Rajasthan, the highest population density of Lehsua is found in pushkar valley of Ajmer, Sadri area of pali and parts of Jodhpur, Barmer and Jalore. Green mature fruits are utilized for making good quality of the pickle and vegetable purpose while nutritive ripe fruits have mucilage and may be used for fresh consumption and liquor. Lehsua is also considered as one of the components of pachkutta. The fruits are used as medicine, astringent, anthelmintic, diuretc, demulcent and expectorant. They are also used in diseases of the chest and urinary passage (Anonymous, 1940). The fruit pulp is used as birdlime. The Kernels are used for curing ringworm (Mc Cann, 1985). Fruits are rich source of Carbohydrates (Chandra et al., 1994), phosphorus (Duhan et al., 1992) and contain 40 mg/ 100g of ascorbic acid (Pareek and Sharma, 1993). Experience shows that the fruits harvested before or after the optimum stage are less suitable for processing. The leaves are used as a fodder for goats while the wood is used for making agricultural implements, well curbs, gun-stocks, boat building, etc. In view of rapid genetic erosion due to population pressure, land utilization pattern and urbanization, conservation of its valuable gene pool is of immense importance The Lehsua perpetuates through seeds and thus the population is to show variation due to genetic differences and environmental effects. The plants raised
through vegetative methods mostly by budding (Shield budding) are uniform and can be used to estimate variation due to environment. Though genetic variation with respect to morphological, physiological and biochemical characters, has been studied in many tree species, yet Lehsua (Cordia myxa Roxb.) has not been given due consideration. Therefore, the present investigation entitled “Natural Variation in Lehsua (Cordia myxa Roxb.) in Rajasthan” was carried out by selecting fifteen edapho-climatically in Rajasthan with the following objectives. 1. To assess the genetic variation, 2. To assess the heritability and genetic advance, 3. To study the degree of divergence between the Lehsua growing locations, 4. To determine the correlation coefficients between different characters and, 5. To determine the direct and indirect effects (Path coefficient) between different characters and fruit weight.
2. REVIEW OF LITERATURE
Variation studies in general help us in comparing the populations and selecting superior trees for breeding purposes. The relevant literature available on various aspects included in the present study are briefly reviewed under the following sub heads. 2.1 Genetic variability 2.2 Correlations 2.3 Path coefficient analysis 2.4 Degree of genetic divergence
2.1 GENETIC VARIABILITY :
Genetic variability is the basis of all plant improvement programmes. Sufficient genetic variability, if present can be exploited to develop superior cultivars. Vavilov (1951) was the first to realize that a wide range of variability in any crop provided a better chance of selection of desirable types. A knowledge of heritability for different component traits is essential for any crop improvement progrmme because the heritable component is the consequence of genotype and is inherited from generation to generation. Wright (1921) reported that heritability comprises of additive and non-additive portions and it is the former which responds to selection. Estimation of expected genetic advance is important to have an idea of effectiveness of selection. Burton and Devane (1953) suggested that genetic
coefficient of variation together with heritability estimates would give reliable indication of the amount of improvement to be expected from selection and further remarked that expected genetic gain under particular system supplies a true practical information which is needed by a breeder. Johnson et al.(1955) also found more useful to estimate the heritability value together with genetic advance in predicting the expected progress to be achieved through selection. The earlier studies on variability in fruit crops and other plant species are reviewed as under : Rudolf (1956) suggested that growth rate, crown spread, resistance to climatic extremities, diseases, insects pest and animal damage, wood quality, photoperiod, seed production and relative tolerance to competition should be kept in mind, for the selection of superior phenotypes and plus trees. Geographic variation exists in trees just as it exists in other plants and animals. The development of differences within the species has taken a long time and has occurred over a great many types of climatic conditions. During this period many types of mutations have occurred in trees and have formed the genetic basis for geographical variation. Sub populations of a species are often geographically isolated from other populations. This isolation can result in genetic differentiation between sub-populations. The most widespread tree species appear to be composed of geographical clines or mortally distinct geographic ecotypes (Wright and Baldwin, 1957). Nath and Randhawa (1959a) used various leaf characteristics such as shape, apex, margin, colour of leaf and also colour and length of petiole for the classification and identification of pomegranate varieties. They also considered the spines the important characters in the classification of pomegranate varieties.
Some commercial pomegranate varieties of India were described on the basis of height, spread, suckering habit and vigour of the trees (Nath and Randhawa, 1959b). They reported maximum height of 2.64m in cultivar Dholka and minimum of 41cm in the cultivar Japanese dwarf. Zobel et al.(1960) carried out studies on phenotypic variation in loblolly pine (Pinus taeda) and reported considerable variation for morphological and physiological characteristics, both regionally and locally throughout its natural range. Vidakovic and Ahsan (1970) suggested the methodology for measurement of straightness in the selection of plus trees. Whitemore (1971) reported significant variation among different provenances of Cedrela species in respect of plant height, diameter, durability and number of branches at the time of planting out. Phenotypic variation can be estimated by occular comparison of trees or tree measurement for different quantitative and qualitative traits. A large number of physiological, morphological and chemical traits had been shown to be variable either by phenotypic survey in natural stands or plantations (Dorman, 1974). Leidig (1974) suggested the method of plus tree selection where the stands are of uneven age and availability of high species diversity, by using average value for different traits in the region and the tree which exceed the average is accepted as a plus tree. Whitmore and Macia (1975) reported that height of the plant varied greatly between and within sites. According to Ying and Bagley (1976), variation in growth, morphological and phenological traits of eastern cottonwood followed a clinal pattern from
north and west to south and east in a seven year old eastern Nebrasha plantations of provenance, representing a major part of the natural range of the species. Criannini and Pelizzo (1977) assessed the natural variation of Alnus cordata for six leaf characters of individual trees and observed that these were not related to ecological conditions. Khosla et al. (1980) studied the phenotypic variation in natural stand of Pinus roxburghii and found clinal variation in relation to morphological characters. Manohar et al. (1981) evaluated sixteen varieties of pomegranate (Punica granatum L.) and recorded a wide range of phenotypic variability for all thirteen characters studied. The genotypic component of variance was greater than the environmental component for most of the characters except for fruit length, 100 aril weight and T.S.S. The genetic coefficient of variation ranged from 5.78% for fruit length to 29.01% for per cent acidity. Aril/ fruit, rind weight, fruit yield, fruit weight and fruits/ tree had high genetic coefficient of variation, whereas, the other characters exhibited low GCV. Heritability ranged from 34.89% (fruit length) to 97.23% (rind weight). Highest heritability was observed for rind weight followed by per cent acidity (96.81%). Low to moderate heritability was observed for fruit length (34.89%), 100 aril weight (36.65%), T.S.S. (47.25%), rind thickness (57.49%), aril length (60.61%), fruit breadth (73.96%), aril breadth (78.57%) and fruits per tree (81.52%). The genetic advance expressed in percentage of mean ranged from 7.14% (fruit length) to 59.26% (per cent acidity). The rind weight, per cent acidity, fruit weight, aril/ fruit, fruit yield/ tree and fruits/ tree had high heritability alongwith high genetic advance. Molchenko (1982) used height, diameter at breast height, clear bole per cent and crown per cent for the selection of plus tree. However, selection criteria
changes with site, type and altitude. And also emphasized essentiality of identification of plus trees through selection methods for seed orchards establishment. Khurana and Khosla (1982) stressed upon phenotypic selection in natural stands of Populus ciliata. The wild pomegranate (Punica granatum L.) trees growing under Sanwara (Himachal Pradesh) conditions attained the height of 8 to 10m and the girth of the main stem was 48-78cm (Parmar and Kaushal, 1982). Khan (1983) from his studies on phenotypic variation in Pinus wallichiana reported the trend of variability in species with all geographical traits viz. altitude, sites, latitudes and provenance in Himalayan terrain. Kotwal (1983) devised an unbiased method for plus tree selection with minimum of twenty standard external characters, suitable for selection on gradation basis. He also necessitated on the implication genetics in forestry for improvement of quantitative characters. In natural populations of a species, the pressure of land masses, water bodies and mountain cause variation. High genetic variation within and among populations has been demonstrated and this distribution of variation and evolutionary history can led to the recommendation of future breeding progrmme (Namkoong, 1984). Dass et al. (1985) studied the genetic variability in ber and observed a wide range of phenotypic coefficient of variation (PCV). The PCV was maximum for pulp : stone ratio (54.41) and lowest for T.S.S. (9.60). Genetic coefficient of variation (GCV) also showed the same trend for different fruit characters. All the traits studied showed very high heritability estimates except
T.S.S. which was found moderate (63.90%). The genetic advance as percentage of mean ranged from 12.65% in T.S.S. to 103.16% in stone : pulp ratio. Variability in Jamun (Syzygium cuminii Skeels) was assessed by Daware et. al (1985) and observed highly significant differences among the strains for traits under study. Variability was highest for T.S.S. (10.00-18.00%) followed by acidity per cent (0.4-2.17), stone weight (0.16-4.1g), stone size (0.66- 4.26cm2), weight of fruit, (2.08-14.5g), reducing sugars (4.02-10.48%), size of fruit (3.03-11.03cm2) and total sugars (5.29-11.48%). Levin (1985) on a topic “current status and prospects of natural pomegranate population”, in Turkmen experiment station reported that selection of useful forms in inbred population using marker characters proved effective owing to the good maintenance of phenotype under inbreeding. The phenotypes from Trancaucasia and Soviet central Asia differed in several respects. Bisla and Daulta (1986) studied the variability, heritability and genetic advance for quality fruits in ber (Zizyphus mauritiana Lamk) and found a wide range of varietal variability for the traits studied. Heritability ranged from 54.2% for total soluble solids to 99.63% for disease intensity, the value for acidity was 91.61%. Manohar et al.(1986) reported a highly significant varietal difference for all the characters studied except fruit length in ber. The genotypic components of variance was greater than the environmental components for fruit breadth, T.S.S., pulp : stone ratio, whereas it was lower in case of fruit length. The genetic coefficient of variation (GCV) ranged from 3.00% (fruit breadth) to 31.01% (yield). T.S.S., fruit breadth and fruit length showed comparatively low GCV, whereas weight/ fruit, pulp : stone ratio and yield exhibited high GCV. Heritability ranged from 42.25% (fruit length) to 93.75% (T.S.S.). High
heritability was recorded in yield/ plant (91.62%) and pulp : stone ratio (91.67%). It was moderate for fruit breadth (66.67%) while low for fruit weight (44.03%). The genetic advance expressed as percentage of mean ranged from 12.48% (fruit length) to 61.16% (yield/ plant). Levin and Levina (1986) on the basis of a study of 1272 forms of pomegranate, fig, olive, persimon and Jujuba in Turkman used forms, combining earliness with good flavour and chemical composition in breeding programmes. Levin (1986) studied the gene bank of subtropical fruit crops and reported that 733 pomegranate accession have been added to give a total of 825, making the largest collection of this crop in the world. Following screening of the collection, 84 accessions were selected for trials. On the basis of 19 characters, 56 accessions were selected as breeding material. Boyle and Morgenstern (1987) in a study on black spruce (Picea mariana) estimated variation within population amounting to 99 percent of the total variation. They further emphasized for intra population sampling for improvement in this species because the relationship between geographic distance and genetic distance was weak. Bisla an Daulta (1988a) made a comprehensive study on the genetic variability and heritability involving 30 genotypes of ber and reported that all the characters studied where highly variable. The coefficient of variation was highest for fruit set (16.9) followed by number of leaves per shoot (14.2), yield (12.9), fruit drop percentage, shoot length and tree height. The high heritability values were exhibited for days from fruit set to ripening (99.2%), fruit set (94.7%), days from pruning to sprouting (93.6%), fruit drop (85%) and shoot length (82%). Expected genetic gain was highest for fruit set (142.8%) and lowest for days taken from pruning to flower initiation (3.5%). Bisla and Daulta (1988b)
evaluated ber cultivars at Hisar and observed high heritability for fruit weight (97.2%), fruit size (87.9%), pulp : stone ratio (87.5%) and seed weight (84.6%). These characters also showed high genetic advance. Shanker (1989) studied the natural variation in Alnus nepalensis and Alnus nitida in respect to height, diameter, crown volume and taper of the trees. Godara et al. (1989) assessed ten cultivars of pomegranate over 3 years for physical and chemical indices and reported that Chawa and Nabha were the best desert cultivars having large fruit size, soft to medium hardness, high T.S.S. and average value of fruit percentage juice and acidity. Bagchi et al. (1990) pointed out significant and heritable differences in seed parameters among different Acacia species. Vakshasya et al. (1992) while studying ten Dalbergia sissoo populations illustrated significant genetic variation among provenance for shoot length, rate of germination and seedling dry weight. Seed morphological variations obtained, were assigned to geographical and provenance variation appeared to be discontinuous in seed and seedling traits. Genetic parameter studies were carried out by Modgil and Modgil (1944) on plants selected from four natural populations of Rubus at six stage of fruit development for seven biochemical characters in two seasons. Variability was highest in ascorbic acid. Genotypic, phenotypic and environmental variances were highest in RNA followed by DNA, total sugars and non-reducing sugars. PCV was more than GCV in all the seven characters. High heritability was shown by RNA associated with high GA and highest genetic gain. Moderate heritability associated with high GA was reported with total sugars.
Pant (1996) reported high heritability alongwith high genetic gain for number of fruits per tree, rind thickness, total sugar, reducing sugar, per cent germination and growth parameters in pomegranate (Punica granatum L.) Singh et al. (1997) conducted genetic variability study on 15 cultivars of papaya (Carica papaya L.) The considerable variation was reported for plant height (140.67-235.33cm), number of fruits per plant (7.65-31.67), fruit length (16.35-23.04cm), fruit width (11.55-18.39cm), length (10.60-18.63cm), fruit cavity width (6.72-10.57cm), fruit weight (1283.33-2350.0g), fruit yield (11.18- 45.27kg) and T.S.S. (8.60-10.55%). The genotypic coefficient of variation (GCV) varied from 3.82(T.S.S.) to 43.14 (number of fruits/ plant), while phenotypic coefficient of variation (PCV) varied from 8.69 (T.S.S) to 75.39 (number of fruits/plant ). Moderate to low heritability was observed for all the characters studied. The highest genetic advance was observed for number of fruits per plant followed by yield. Singh and Sharma (1997) reported high broad sense heritability for all the characters studied. Plant height, weight of each fingers, days to flowers and pulp weight of rachis had high GCV alongwith high GA as well as high heritability. Chandra Babu (1997) observed a wide range of variability in the germplasm of almond (Prunus amygdalus) for all the characters studied. Phenotypic and genotypic variances were found to be higher than the environmental variances for all the characters. Phenotypic and genotypic coefficient of variation were highest for the character green almond yield /branch and least estimates for moisture percentage of the Kernel. Heritability was highest for the characters leaf area /unit, shoot length and least for the character volume of the tree. The yield component characters like number of flowers/unit, shoot length, number of fruits /unit, fruit set percentage, mean fruit weight and
mean Kernel weight had comparatively high GCV, PCV, heritability and genetic gain. Masilamani and Kamble (1998) studied twelve genotypes of mulberry (Morus spp.) and reported that the heritability estimates ranged from 48.42% to 94.09%. Heritability was high for number of nodes/ metre length of a branch (99.09%), leaf area (86.39%) and weight of 100 leaves (83.27%) while it was moderate for leaf yield /plant (76.91%), plant height (62.20%)and number of primary branches (58.42%). Low heritability was noticed for total number of leaves/plant (48.42%). The PCV was higher than the GCV for all cases. Leaf yield /plant showed highest value for PCV and GCV. Genetic advance varied from 13.65%to 66.54% being low for plant height, total number of leaves/plant and number of primary branches, while high for leaf yield /plant, number of nodes/ metre length, weight of 100 leaves and leaf area. Karale and Desai (1998) made a comprehensive study on yield and fruit quality components involving fifty two cross combinations of pomegranate (Purica granatum L.) and observed high heritability for seed mellowness (96.74%), rind thickness (69.16%) and fruit diameter (61.80%) while the yield/plant (35.36%), fruits/plant (33.63%) aril size (33.54%) and T,S.S : acid ratio (32.80%) showed a medium heritability. Genetic advance was very high for seed mellowness (124.08), high for rind thickness (51.46), juice weight/ fruit (39.97), aril weight/ fruit (33.28), fruit weight (34.15) and fruit volume (33.30), whereas it was low for other characters. The PCV was greater than the GCV for most of the characters. The estimates were very high for seed hardness (66.23 and 61.23,respecetively). Both the estimates were moderate for rind thickness, yield/ plant, juice weight/ fruit, aril weight/fruit, fruit weight, and fruit volume and low for remaining characters.
Dash et al. (1998) studied combining ability in papaya (Carica papaya L.) and observed that genotypic and phenoypic coefficient of variation were highest for fruit yield and lowest for days to fruit harvest. Heritability was higher for fruit weight (95.0%), fruiting height (92.8%), days to first fruiting (92.3%), flesh thickness (92.3%), days to fruit set (92.0%), fruit length (91.7%), fruit yield (91.5%), T.S.S.(86.4%) and plant height (84.6%), whereas ,it was moderate for days to fruit development (79.4%), days to fruit harvest (73.0%) and fruit number (50.7%). High genetic advance was observed for plant height and fruiting height, moderate for days to first fruiting (42.7), days to fruit set (39.3) and fruit length (36.3), while low for other characters. Chaudhary and Singh (1998a) in a study of twenty five wild apricot (Prunus armeniaca Linn.) selections, observed a significant variation for all the characters studied. The highest heritability was obtained for plant height (78.86%) and lowest for leaf length (28.77%). The highest genotypic coefficient of variation (GCV) was found for number of branches (51.41%) and lowest for leaf length (6.55%). Genetic advance as per cent of mean was found maximum for number of branches (82.65%) and minimum for leaf length (6.78%). Gupta and Mehta (2000) studied twelve ber cultivars and reported a wide variation for fruit set (29.0-36.50), fruit length (2.94-4.65 cm), fruit diameter (2.27-2.87 cm), fruit weight (10.50-18.85 g), fruit fly attack (12.33-29.33%), powdery mildew damage (7.83-90.66%), fruit retention (8.93-21.66%) and yield (87.85-167.50 kg). Higher estimates of heritability was obtained for fruit weight (99.90%), fruit length (99.40%), powdery mildew damage (99.30%) and fruit diameter (98.0%), while lowest heritability was recorded in leaf breath (3.5%). Genetic advance as percentage of mean was highest in fruit weight (84.30%) and lowest in fruit retention (9.85%). A high magnitude of genotypic coefficient of
variation (GCV) was observed for characters like powdery mildew damage, followed by fruit retention and fruit fly attack, while low for fruit diameter, leaf length and fruit set. Uma et al. (2000) evaluated twelve different ecotypes belonging to silk group of banana for 16 quantitative and qualitative characters. Bunch weight with a very high value of PCV, GCV, hertability and GA makes it a prime characters for direct selection. Plant height, crop duration, leaf breadth, number of leaves at shooting and plant girth with high values of heritability and moderate values of GA are other important characters which have to be considered for selection. Pareek (2001) reported high heritability alonwith high GA for fruit set, fruit length, fruit breadth, fruit weight, stone weight, stone length, stone diameter , pulp weight , fruit yield per tree, pulp : stone ratio, acidity, ascorbic acid, total sugar, reducing sugars, non-reducing sugars, T.S.S. : acid ratio, powdery mildew severity and fruit fly incidence in ber. Shukla and Singh (2002) studied 66 strains of amaranth and grouped in nine clusters depending upon the genetic constitution of strains. The genetic diversity among the genotypes may be due to factors like history of selection, heterogeneity, selection under diverse environments and genetic drift. Ram Rao et.al. (2003) assessed 30 genotypes of mulberry for different characters. Among eight characters, only five characters Viz. leaf yield/plant , no. of branches/plant ,no. of leaves/meter, no. of sec. Shoots/plant and wt. Of 100 leaves exhibited high heritability( h2) and high genetic advance ( GA) as percentage of mean clearly suggested that there traits are under the control of additive gene action and thus, these traits are reliable for selection.
2.2 CORRELATIONS
Correlation coefficient is a measure of the degree of association between the two traits worked out at the same time (Hayes et al., 1995). For selecting superior genotypes the breeder had to choose from the material on the basis of its phenotypic expression. As most of the traits of economic importance are complex involving several related traits, the knowledge of degree of phenotypic and genotypic correlation of the traits is important (Johnson et al., 1955). The earlier research work conducted on correlation studies in fruit crop and other species is being reviewed as under. Asadas et al. (1978) conducted studies on provenances of Larix leptolepis and reported a strong correlation between cone weight and both cone width and length and found that the locality samples from Nikko had the largest, widest and heaviest cones. Khosla et al. (1979) reported strong correlations between height and diameter, diameter and age of Populus ciliata. There was variation among different provenances, however, very low genetic variation was found to occur among natural stands. Brown and Doran (1985) reported weak and inverse correlation for height and diameter growth with the latitude of provenance. For height growth, a weak inverse correlation with altitude of provenance was also reported alongwith substantial differences in growth and branch characteristics among the provenances. Daware et al. (1985) observed in Jamun that significant positive correlation of fruit weight with size of fruit, weight of stone and size of stone.
The association of weight of fruit with quality characters was non-significant. The correlation of size of fruit with weight and size of stone was positive and significant. The association of physical fruit characters with qualitative characters was non-significant in most of the cases. However, the weight and size of stone revealed significant negative correlation with pulp percentage. T.S.S. had significant positive correlation with reducing sugars and total sugar. Reducing sugars indicated significant positive correlation with total sugar. Bisla and Daulta (1986) worked out correlation coefficient for yield/ tree, fruit quality traits and intensity of unspecified diseases from 30 varieties of ber (Zizyphus mauritiana L.) and revealed that yield was positively correlated with total sugar content and powdery mildew intensity. Bisla and Daulta (1987) reported that yield was positively and significantly correlation with fruit weight, fruit size, seed weight and pulp : stone ratio in ber (Zizyphus mauritiana L.) Shankar (1989) reported that height and age, height and diameter and diameter and age exhibited positive and highly significant correlation. Alvarez and Montalvo (1990) evaluated a half sib progeny traits with 26 families of Pinus cubensis at the age of ten years, Alnus nepalensis and Alnus nitida in respect to height, diameter and age exhibited positive and highly significant correlation. Bagchi et al. (1990) reported strong correlation between seed length and width. Similarly, while studying twenty one provenances of Acacia nilotica from six states of India for provenace variation in seed parameters, Bagchi and Dobriyal (1990) concluded that in all porvenances only length and width were significantly correlated.
Prajapati et al. (1996) found significant positive correlation between fruit yield, fruit set and pulp : stone ratio, whereas yield had significant negative correlation with fruit drop and stone weight in ber. Pant (1996) reported that total soluble solids were positively correlated with total sugar in pomegranate (Punica granatum L.). Highly significant and negative correlation was found between per cent incidence of Anar butterfly and rind thickness. Fruit length was found to be highly significant and positively correlated with fruit diameter and fruit weight. Number of branches showed highly significant and positive correlation with collar diameter, seedling height and number of leaves per seedling. Chandra Babu (1997) studied correlation between yield and its related traits in almond (Prunus amygdalus) and found that green almond yield/ tree was positively and significantly correlated with number of flowers/ unit shoot lenght, fruit set 40 days after full bloom (DAFB), fruit set before harvesting (75-105 DAFB), number of fruits/ unit shoot length and green almond yield/ branch. Singh, et al. (1997) observed significant positive correlation for number of fruits with fruit yield ; fruit weight with fruit length ; fruit length and width with fruit cavity length and cavity width in papaya. Most of the economic traits were positively correlated. Fruit weight was positively associated with other traits except number of fruits and plant height. Masilamani and Kamble (1998) worked out the phenotypic and genotypic correlations among the various characters in mulberry (Morus spp). All the characters, except number of nodes/ metre length of a branch were found high significant positive association with leaf yield/ plant. Number of nodes/ metre length had significant positive correlation with all characters except total number
of leaves/ plant. Leaf area had poor correlation with plant height, number of primary branches and total number of leaves/ plant. Leaf area had high significant positive correlation with weight of 100 leaves. Leaf yield/ plant had positive and significant correlations with all characters studied except number of nodes/ metre length of a branch. Chaudhary and Singh (1998a) studied the correlation coefficient both at genotypic and phenotypic levels in wild apricot (Prunus armeniaca Linn) and found that magnitude of genotypic correlations were higher than the phenotypic correlations. Kernel weight had positive and significant genotypic correlations with nut breadth and seed weight. Nut weight was found significant and positively correlated with nut length, nut breadth, nut thickness and seed weight. Nut thickness showed positive and significant correlations with nut length. Kernel weight was found positively correlated with nut length and nut thickness but not at significant level. Chaudhary and Singh (1998b) in a study of wild apricot (Prunus armeniaca Linn) found that collar diameter/ plant height, number of branches/ plant height, leaf length/ plant height, leaf breadth/ plant height, number of branches/ collar diameter and leaf breadth/ leaf length were positively and significantly associated with each other at genotypic and phenotypic level. The characters collar diameter, number of branches, leaf length and leaf breadth had significant positive association with plant height at genotypic and phenotypic level. Giridharan and Jindal (1999) reported that correlation of total phenols, organic acids, total sugars and soluble protein with duration of crop growth were non significant in grape (Vitis vinifera). Total sugar was found closely correlated (r = 0.813) with total duration of crop growth. Correlation between nut yield and yield attributing characters in cashew (Anacardium occidantale L.) was worked
out by Swarnapiria and Manivannan (1999) and found that the nut yield/ tree had significant positive correction with leaf length (0.712), number of nuts/ panicle (0.696) and girth of the tree (0.506). The number of nuts / panicles had significantly high positive correlation with apple weight (0.626) and nut weight (0.768). The apple girth had a significant positive correlation with apple weight (0.503). Gupta and Mehta (2000) worked out correlation for fruit yield and its components on twelve cultivars of ber. Characters like leaf breadth, fruit diameter, fruit weight and fruit retention showed significant positive correlation with yield, while the significant negative correlation was noticed between powdery mildew severity and yield. Karale and Desai (2000) reported that fruit weight was positively and significantly associated with fruit diameter, aril weight /fruit and yield in pomegranate.
2.3. PATH COEFFICIENT ANALYSIS
The Path coefficient analysis is simply a standardized partial regression which may be useful in choosing the characters (s) that have direct and indirect effects on yield. Such a study may be useful and effective in selection for simultaneous improvement of the component characters that contribute towards yield. Path analysis was initially suggested by Wright (1921) but was applied for the first time in plant breeding by Deway and Lu (1959). The earlier research work conducted on path analysis studies in fruit crops and other plant species is reviewed as under: In a study comprising 58 local types of jamun (Syzygium cuminii Skeels), Daware et al. (1985) observed that the size of fruit had medium direct effect on fruit weight. The indirect effect of size of fruit via weight of stone was
considerable more. The characters weight of stone and pulp (per cent) exhibited high direct effect on fruit weight. Selection therefore; based on pulp (juice) percentage and weight of stone may be useful in selection programmes. Bisla and Daulta (1986) reported that total sugar content and disease intensity had the highest direct effect on yield in ber. Further, they suggested that genotypes selection for improving fruit yield in ber should be based on disease resistance and sugar content. Bisla and Daulta (1987) reported in ber that fruit weight, seed weight and pulp : stone ratio had positive direct effects on yield. Prajapati et al. (1996) revealed a positive direct contribution of fruit set and fruit length and a negative contribution of fruit drop and stone weight on fruit yield in ber. Further they advocated that in breeding programmes importance should be given to these four characters for developing high yielding ber genotype. Chandra Babu (1997) worked out path analysis for yield in almond (Prunus amygdalus) and revealed that the characters number of flowers /unit shoot length, fruit set before harvesting and mean fruit weight had high direct positive effects on yield/ tree and yield/branch at both phenotypic and genotypic levels. Selection index showed that number of fruits/ unit shoot length, number of flowers/ unit shoot length and fruit set before harvesting had positive and non- significant contribution towards yield/ tree, whereas number of fruits/ unit shoot length, scion girth and mean fruit weight had positive and significant contribution towards yield/ branch. While working on mulberry (Morus spp.) Masilamani and kamble (1998) reported that plant height, number of primary branches, number of nodes/ metre length of a branch and weight of 100 leaves showed positive direct effect on leaf yield. Total number of laves/ plant and leaf area exerted negative direct effect on
leaf yield. The indirect effect of plant height via number of primary branches/ plant is higher than its direct effect. Chaudhary and Singh (1998) reported in wild apricot (Prunus armeniaca Linn.) that nut weight, nut breadth and nut thickness had high positive direct effect on kernel weight. These four characters had the positive indirect effect to kernel weight via other traits. The high direct effect of nut weight and nut length had provided the basis for the improvement of kernel yield.
2.4 GENETIC DIVERGENCE
Assessment of genetic divergence between populations is vital to the success of plant genetic improvement programme to exploit the genetic diversity within and among populations and the heterosis is often obtained by wide crossing. Grass improvement which include bamboo as one of the important plant groups seeks to improve many attributes such as morphological, physiological and fodder quality factors. Multivariate assessments are often made using phenotypic population means. If these are based on sufficiently large sample sizes and the traits measured shows significant differences between populations, they can provide a reasonable representation of overall genetic performance. Multivariate procedures have helped to evaluate germplasm collections used for evaluation, selection and breeding in number of grass species (Humpreys et al., 1980; Charmet et al., 1988). Kotaiah et al.(1986) showed by Mahalanobis D2 and metroglyph analysis in mid-duration genotypes of rice that days to 50 per cent heading, grain breadth, plant height and percentage of grain protein contributed maximum towards the total divergence in 26 diverse mid duration genotypes of rice. Deviations observed between D2 and metroglyph methods regarding the number of cluster
formed, number of genotypes in the clusters and super imposition of the genotypes within the cluster point out the precision and refinement of D2 technique in studying the germplasm collections. Katiyar et al. (1988) used metroglyph analysis of 78 genotypes of sugarcane for evaluating seven characters; sixty seven genotypes formed 9 complexes and 11 genotypes did not fall in any complex. The commercial hybrids formed compact mixed complexes and their ray patterns for different morphological characters resembled each other. On the basis of index score value, and ray patterns of different morphological characters, the genotypes of different complexes were selected. They concluded that genetic diversity is more important than geographical diversity. Veronesi and Falcinelli (1988) analysed 48 accessions of fall fescue (Festuca arundinacea schreb) collected from northern to southern Italy using both univariate and multivariate analysis applied to a set of 12 quantitative traits. Four principal components were found to explain 77 per cent of the total variation in the dependence structure. Productivity characters together with heading time and dimensions of flag leaf appeared major sources of diversity among tall fescue populations. On the basis of the 4 principal components, similar populations were clustered according to minimal distance analysis. Seven clusters were identified. The results of cluster analysis confirmed the presence of a remarkable diversity within the germplasm collection and explained why results of a univariate analysis of variance did not reveal significant differences among groups. The multivariate approach seemed to point out a problem of genetic erosion of the local germplasm in Northern Italy and on the whole, appeared to be valid system for tall fescue germplasm evaluation.
Surendran and Chandrasekharan (1988) assessed the magnitude of genetic divergence among thirty five single tree selections of Eucalyptus tereticornis Sm. From different agroclimatic zones of Tamil Nadu at 24 months growths phase to identify promising single tree selections to be utilized in crossing programme. Eight characters viz. plant height, number of leaves, girth at base, number of branches, leaf length, leaf length/ breadth ratio and internode length were recorded. Application of Mahalanois D2 statistics identified eleven cluster groupings. The study revealed that the variability exhibited was primary due to number of branches, number of leaves and plant height and secondarily due to internode length, leaf length/ breadth ratio and leaf length. Humpreys (1991) reported genetic differentiation among perennial rye grass populations by using multivariate procedures incorporating a broad range of seasonal growth, quality and persistancy traits. Principal components analysis, based on a genetic variance/ covariance matrix, resulted in a correlation of 0.70 between the relative weighting of traits in the first four principal components and corresponding between population heritabilities. Cluster analysis, based on principal component scores, produced four groups of populations separated by Mahalanobis distance ranging from 3.0 to 7.8. Considerable heterosis was obtained in crosses between populations from the more widely genetically separate groups. De et al. (1992) studied the genetic divergence in early rice under two situations. The strains were grouped into 5 and 6 clusters in direct seeded and transplanted conditions, respectively. They concluded that there is no relationship between geographical distribution and genetic divergence. Singh and Chaudhary (1992) carried out a study on wild Apricot (Prunus armeniaca L.) in Himachal Pradesh. The genetic diversity among 28 single tree
selections (plus tree) were estimated through their progenies for five development characters. These were grouped into three clusters. Intercluster (D value) ranged from 5.95 to 6.48 and intracluster distance was found maximum (3.09) in cluster I. Plant height and number of branches contributed considerably, accounting for 65 per cent of total divergence. Cluster II and III were obtained to be highly divergent and are likely to produce new genotypes with desired traits. The representative of cluster II and III could be used in hybridization programme for exploiting hybrid vigour for higher biomass. Considerable heterosis was obtained in crosses between populations from the more widely genetically separate groups. Singh (1993b) studied the genetic divergence in Bambusa tulda from North-East India. The findings revealed that the grouping in different clusters was not related to their geographic origin. Total culms per clump, length of internode and girth contributed maximum towards total genetic divergence. Pandey et al. (1995) studied the genetic divergence in Populus deltoides using Mahalanois D2 analysis among 12 clones of poplar with 16 component characters at 8 years of age. This led to their grouping into 5 clusters. Maximum and minimum distances were observed between cluster II and III and cluster I and V respectively. Shiv Kumar and Singh (1997) in triticale, Narendra Kumar( 1997) in chick pea, Balagopal (1997) in foxtail and Rajan et. al. (1997) in mulberry have reported that besides geographic diversity, the other factors like genetic drift and exchange of breeding materials found to be responsible for grouping of accessions in clusters. Das et al. (2000) reported that genetic divergence in a set of 16 genotypes of betelvine measured using Mahalanobis D2 technique, indicated the existence
of substantial genetic diversity. The genotypes were grouped into 5 different clusters. The clustering pattern of genotypes was random and did not follow the geographical origin. A wide range of variation was found in the cluster mean values in respect of number of leaves/ vine, leaf area, petiole length, internode length, leaf length, leaf breadth, number of laterals/ vine, vine length, diameter of internode, chlorophyll a and b and 100-leaf weight of which number of laterals/ vine as well as leaf length were the potent variables these may be used in selecting diverse parents in hybridization programme. Tikader and Roy (2002) assessed genetic divergence among 98 mulberry (Morus spp.) genotypes (63 exotic, 35 indigenous) of different eco-geographic origin using Mahalanobis D2 statistics. The total genotypes were grouped into seven clusters. Maximum number of genotypes were grouped in cluster III (19), IV (19), II (16), IV (16), VII (13) and V (12), respectively ; cluster I had only 3 exotic genotypes. All the clusters having both the exotic and indigenous genotypes except cluster I. The genotypes falling in cluster III had the maximum divergence followed by cluster I and II. The maximum and minimum divergence were revealed between cluster I and VI and between cluster V and VI, respectively. The cluster I and VI showed higher and lower mean values for most of the characters.
3. MATERIALS AND METHODS
The present investigation entitled “Natural Variation in Lehsua (Cordia myxa Roxb.) in Rajastan”. was carried out in the Department of Horticulture, S.K.N. College of Agriculture, Jobner (Jaipur), Rajastan during 2002 and 2003. The experimental details relating to Districts/ provenances, experimental site, materials used and methodology adopted for the study are described here in. 3.1 Districts/ provenances/sites 3.2 Methodology adopted and observations recorded 3.3 Statistical analysis 3.4 Genetic divergence
3.1 DISTRICTS/ PROVENANCES/SITES
3.1.1 Selection of sites
A pilot survey of population of Cordia myxa Roxb. in Rajasthan was undertaken to identify the sites, where this species occurs in the wild state. The sampling procedure includes delineation of the whole area, under the species into a number of sites depending upon the aspect variation in morphological characters. In this way fifteen sites were selected in five districts of Rajasthan.
3.1.2 Selection of trees
Three natural occurring trees of Lehsua (Cordia myxa Roxb.) having approximately the same age, height and diameter were selected within each site as per the mathods adopted by Pozdnjakov (1969), Dumitriu-Tataranu (1970),
Savnin (1976) and Pant (1996). These trees were marked for recording the morphological data and for the collection of fruits for further study. The observations on various characters namely plant height, plant spread, trunk shape, branching pattern, leaf size, maturity time, fruits/ cluster, fruit size, fruit shape, pulp : seed ratio, T.S.S and acidity were recorded .
3.2 METHODOLOGY ADOPTED AND OBSERVATIONS RECORDED
The procedure of data recorded on different characteristics are as follows :
3.2.1 Morphological characteristics
3.2.1.1 Plant height (m)
The plant height was measured from ground level to the apex of the longest branch at the peak of fruiting. The measuring tape was used to measure the height.
3.2.1.2 Plant spread (m2)
Spread of tree was measured in two opposite directions (NS-EW) with the help of measuring tape at the peak of fruiting and average spread of the tree was calculated in m2.
3.2.1.3 Trunk shape
Visual observations were made on selected plant of a particular site to judge the trunk shape.
3.2.1.4 Branching pattern
It was also observed by visual observation of the individual plants of the site.
3.2.1.5 Leaf size
Ten fully matured leaves from each tree at the time of fruit maturity were taken at random and average leaf length and width was calculated and expressed as cm.
3.2.2 Fruit characteristics
3.2.2.1 Maturity time
The fruiting time was recorded and on the basis of time, taken the genotype were grouped into three i e. early, mid and late maturity.
3.2.2.2 Fruits/ cluster
It was calculated by counting the total number of fruits in each cluster, in a tagged shoot.
3.2.2.3 Fruit weight
Fruit were collected from the selected trees. Twenty fruits from each of the selected trees were collected depending upon their direction i.e. five form south, five from north, five from east and five from west and mixed together. Fruit weight was recorded with the help of a pan balance. Weight of twenty fruits was taken and total weight was divided by number of fruits to get the average fruit weight in grams.
3.2.2.4 Fruit size/diameter
Fruit diameter of these selected twenty fruits were measured in cm using Vernier caliper and averaged.
3.2.2.5 Fruit shape
It was decided on the basis of visual observation.
3.2.2.6 Pulp : seed ratio
Pulp weight of selected twenty fruits per tree was estimated by deducting stone weight from the total fruit weight. Then pulp weight was divided by stone weight to calculate pulp : seed ratio and average was worked out.
3.2.3. Fruit quality characteristics
3.2.3.1 Total soluble solids (0Brix)
Pulp from twenty selected fruits was taken and macerated for juice extraction and total soluble solids of the juice was determined by using a hand refractometer of 0-30 per cent range. The values were corrected at 200C and expressed as per cent total soluble solids of the fruit juice (A.O. A.C., 1990).
3.2.3.2 Acidity (%)
Total acid was determined by diluting the known volume of juice and titrating the same against N/10 sodium hydroxide solution, using phenolphthalein as an indicator. The appearance of light pink colour was marked as the end point. It was expressed on percentage basis (A.O. A.C., 1990).
3.3 STATISTICAL ANALYSIS
The data were subjected to statistical analysis according to the methods given below :
3.3.1 Variability analysis
The data obtained were subjected to analysis of variance using RBD as described by Panse and Sukhatme (1967) and Chandel (1984). The fifteen sites were considered as treatments and the individual tree at each site was taken as the replication. The statistical analysis for each parameter was carried out on mean values. The analysis of variance (ANOVA) table indicating the source of variation, their degree of freedom (d.f.) and expectation of mean square (MS) is given as under. The component of variance namely genotypic (σ2g), phenotypic (σ2p) and environmental (σ2e) were calculated from the expectation of mean square following random model. ANOVA Table
Source of d.f. Mean Calculated F Expected mean variation squares value squares 2 2 Replication (r-1) Mr Mr/ Me σ e + t. σ r 2 2 Treatment (t-1) Mt Mt/ Me σ e + r. σ t 2 Error (r-1) (t-1) Me σ e Total (rt-1) Where, r = number of replications t = number of treatments
Mr = mean sum of square due to replications
Mt = mean sum of square due to treatments
Me = mean sum of square due to error 2 σ e = error variance = Me 2 σ t = genotypic variance = (Mt –Me)/r 2 σ r = variance due to replications = (Mr–Me)/t 2 2 2 σ p = phenotypic variance = σ t +σ e
The standard error of mean (SEm+) and critical difference (CD) for comparing the mean of any two lines were computed as follows : SEm + = (Me/r)1/2 SE(d) = (2 Me/r)1/2 CD (at 5%) = SE (d) x ‘t’ value at error d.f. at p = 0.05
3.3.2 Genetic analysis
From the components of variance, the genotypic and phenotypic coefficient of variation, heritability in broad sense and genetic advance expressed as percentage of mean were computed as given below :
3.3.2.1. Coefficient of Variation
The genotypic and phenotypic coefficients of variation were calculated by standard statistical procedures using following formulae earlier used by Burton and Devane (1953) and Johnson et al. (1955).
Genotypic coefficient of variation (GCV):
GCV = (σ2g)1/2 x 100 x Where, σ2g = genotypic variance x = general mean Phenotypic coefficient of variation (PCV) : PCV = (σ2p)1/2 x 100 X
Where, -2 o p = phenotypic variance x = general mean
3.3.2.2. Heritabilty
Heritability in broad sense was calculated by the formula given by Hanson et al. (1956) and was multiplied by 100 (Lush, 1940) to get it in percentage as shown below : Heritability (h2) = σ2g x 100 σ2p Where, σ2g = genotypic variance σ2p = phenotypic variance
3.3.2.3 Genetic Advance (GA)
The expected genetic advance was calculated as suggested by Johnson et al.(1955) Genetic advance = (h2) . (K) . (σp) Where, h2 = heritability (broad sense) K = 2.06 (selection differential at 5% selection intensity) σp = phenotypic standard deviation
3.3.2.4 Genetic advance as percentage of mean
The genetic advance as percentage of means was expressed as per the following formula GA Genetic advance as percentage of mean =------x 100 Grand mean
For categorizing the magnitude of different parameters, the following limits were used :
PCV and GCV > 30% = High 15-30% = Moderate < 15% = Low Heritability (h2) > 80% = High 50-80% = Moderate < 50% = Low Genetic advance > 50% = High 25-50% = Moderate < 25% = Low
3.3.3 Calculation of correlation coefficient
The simple correlation coefficient (Karl pearson’s) were worked out by using the following formula (Panse and Sukhatme, 1967). r (xy) = COV x y
V (x) V (y) r (xy) = simple correlation between x and y V (x) = variance of x character V (y) = variance of y character The significance of ‘r’ values were tested against (n-2) degrees of freedom by using Fisher and Yates table. For testing simple correlation, the ‘t’ value was calculated by the following formula.
r t = ------x n-2 1-r2 Where, r = simple correlation n = number of observations in the sample
3.3.4. Path coefficient analysis
A path coefficient is a standardized partial regression coefficient. It measures the direct and indirect effects of one variable on the other and allow to partition the total correlation coefficient between two variables into direct and indirect components. The estimate of direct and indirect effects were calculated by the path coefficient analysis as suggested by Wrigth (1921) and elaborated by Deway and Lu (1959) at both phenotypic and genotypic levels. The following sets of simultaneous equations were formed and solved for estimating the various direct and indirect effects. r1y = p1y + p2yr12 + p3yr13 +………………………… + pnyr1.n r2y = p1yr12 + p2y + p3yr23 +………………………… + pnyr2.n “ “ rny = p1y rn.1 + p2yrn.2 + …………………………….pny
Where,
r1y = correlation between first character (independent) and y (dependent) variables
p1y = direct effect of first character (independent) and y (dependent) characters.
P1y r1….n = indirect effect of first character on y (dependent character) via all the other characters (n in number).
The path coefficient analysis was done in three groups. The first group consisted of morphological characteristics, namely plant height, plant spread and leaf size. The second group consisted of fruit characteristics, namely fruit/ cluster, fruit size and pulp : seed ratio. The third group consisted of quality attributes, namely T.S.S. and acidity. In all the above groups the dependent attribute was fruit weight.
Residual effect
The residual effects were calculated as follows : Residual factor (x) : Pxy = (I-R2)1/2 2 2 Where R = Σ P iy + 21 Σ Piy. Pjyrij and i > j
3.4 GENETIC DIVERGENCE
Genetic divergence was estimated by Mahalanobis’ D2 statistics and the genotypes were grouped on the basis of minimum generalized distance using Tocher’s method as described by Rao (1952).
4. EXPERIMENTAL RESULTS
As explained earlier, fifteen provenances were included and code named as S1, S2, S3, ……… S15 (Table-1). Variation for various characteristics were studied during 2002 and 2003. The results of these investigations are summarised as under : 4.1 EVALUATION OF PROVENANCES 4.1.1 Variation in Morphological Characteristics 4.1.2 Variation in Fruit Characteristics 4.1.3 Variation in Fruit Quality Characteristics 4.1.4 Variation for Different Traits on Pooled Data Basis 4.2 VARIABILITY ESTIMATES AND GENETIC STUDIES 4.3 CORRELATION STUDIES 4.4 PATH COEFFICIENT STUDIES 4.5 DEGREE OF GENETIC DIVERGENCE FOR DIFFERENT TRAITS
4.1 EVALUATION OF PROVENANCES
4.1.1 Variation in Morphological Characteristics
Data pertaining to variation for plant height, spread and leaf size (leaf length and leaf width) has been given in table-2. A perusal of the table reveals that the maximum tree height was recorded from S2 (Gahnehra) provenance with mean value of 9.21 m followed by S3
(Devnagar) 7.97 m and S4 (Sagari farm) 7.83 m during 2002. The lowest tree height was recorded from S5 (Chopasani) with mean value of 6.60 m. More or
less same trend was recorded during 2003. S2 (Gahnehra ) provenance recorded the maximum value of 9.46 m for plant height followed by S3 (Devnagar) and S4
(Sagarifarm) whereas the minimum plant height of 6.69 m was recorded from S5 (Chopasani).. Variability was estimated in terms of range, mean and coefficient of variation during both the year of study and on pooled basis. In 2002, plant height showed a range of 6.60-9.21 m with mean value of 7.38 m, whereas in 2003 it ranged between 6.69-9.46 m with mean value of 7.48 m. But on pooled basis, it ranged between 6.64-9.34m with mean value of 7.43 m (Table-5). Coefficient of variation was found to be highest (9.06 per cent) during 2003 with comparison of 2002 with value of 8.02 per cent. However pooled analysis gave 8.56 per cent coefficient of variation for plant height (Table-5). During 2002, maximum mean value of 86.46 m2 for plant spread was recorded for S2 (Gahnehra) provenance; however, it did not differ significantly 2 from S7 (Sadri) provenance with mean value of 75.86 m . Whereas the minimum 2 plant spread of 37.70 m was recorded from S10 (Santhu). Same trend was recorded during 2003. S2 (Gahnehra) provenance recorded the maximum value of 96.86 m2 for plant spread. Whereas the minimum plant spread of 38.56 m2 was 2 recorded from S10 (Santhu). Plant spread showed widest range of 38.56-96.86 m during 2003 with mean value of 54.44 m2. In 2002, it ranged between 37.70- 86.46 m2 with mean value of 52.94 m2. But on pooled basis plant spread ranged between 38.13-91.66 m2 with mean value of 53.69 m2. The coefficient of variability was more during 2003 with value of 20.33 per cent in comparison to 20.01 per cent recorded during 2002. However, pooled analysis gave 20.18 percent coefficient of variation for plant spread. (Table-5).
It is clear from the table-2 that during both the years, S5 (Chopasani) provenance gave the highest mean value of 16.73 cm for leaf length, which was statistically at par with S4 (Sagari farm), S13(Siwana), S15 (Rawatsar),
S3(Devnagar) and S6 (Doli) provenances during 2002 and S4 (Sagarifarm) and S13 (Siwana) during 2003. Minimum mean leaf length of 13.27 cm was recorded from S11 (Sura) provenance. In 2003, S12 (Sharath) provenance gave the lowest value of 12.60cm for mean leaf length which was statistically at par with S11
(Sura), S8 (Ranawas), S14 (Karna) and S9 (Sojat) but noticed a significant variation from rest of the provenances. In 2002, leaf length showed a range of 13.27-16.73 cm with mean value of 14.44 cm, whereas in 2003 it ranged between 12.60-16.73 cm with mean value of 14.38. Coefficient of variation was found to be highest (8.73 per cent) during 2002 with comparison of 2003 with value of
6.52 per cent. It is clear from the table-2 that during both the years, S5 (Chopasani) provenance gave the highest mean value of 14.83 cm and 14.77 cm for leaf width respectively, which was statistically at par with S15 (Rawatsar), S13
(Siwana), S4 (Sagari farm), S9 (Sojat), S6 (Doli), S3 (Devnagar) and S14 (Karna) during 2002 and S13 (Siwana) and S15 (Rawatsar) during 2003. Minimum mean leaf width of 11.43 cm was recorded from S10 (Santhu) provenance. In 2003, S11 (Sura) provenance gave the lowest value of 11.87 cm for mean leaf width followed by S8 (Ranawas) with mean value of 11.97 cm. In 2002, leaf width showed a range of 11.43-14.83 cm with mean value of 12.82 cm whereas in 2003, it ranged between 11.87-14.77 cm with mean value of 12.89 cm. Coefficient of variation was found to be highest (10.44 per cent) during 2002 with comparison of 2003 with value of 5.80 per cent.
4.1.2 Variation in fruit characteristics among the different provenances of Lehsua
Data on fruit characteristics viz, fruits/cluster, fruit diameter, pulp : seed ratio, and fruit weight has been presented in table –3. Data presented in table-3 showed that fruits/cluster ranged between 8.00- 18.00 with mean fruits of 12.53 per cluster. Maximum fruits per cluster (18.00) were recorded for S1 (Bagolye) provenance which was statistically at par with S6
(Doli) and S5 (Chopasani) provenances. Whereas minimum fruits per cluster was recorded from S7 (Sadri) provenance with mean value of 8.00 which was statistically at par with S8 (Ranawas), S4 (Sagarifarm) and S10 (Santhu) provenances during 2002. However, coefficient of variation recorded during 2002 was higher than the coefficient of variation recorded during 2003. In 2002, coefficient of variation was 12.81 per cent, whereas in 2003 coefficient of variation had a lower value of 11.80 per cent.
In 2003, S6 (Doli) provenance registered maximum fruits per cluster with value of 17.67 which was found statistically at par with S1 (Bagolye) and S5
(Chopasani) provenances. S8 (Ranawas) provenance recorded the minimum (6.00) fruits per cluster and ranged between 6.00-17.67 with grand mean of 12.87. It is clear from the table-3 that there was a significant variation for fruit diameter during 2002 and 2003. Fruits collected from S6 (Doli) provenance recorded the highest value of 3.10 cm during 2002 which was statistically at par with S4 (Sagari farm), S2 (Gahnehra), S9 (Sojat) and S3 (Devnagar) provenances but significantly superior over rest of the provenances. S10 (Santhu) provenance recorded the lowest fruit diameter of 2.35 cm during 2002. Similar trend was observed during 2003. S6 (Doli) provenance recorded the maximum fruit diameter of 3.29 cm followed by S4 (2.93) cm, S3 (2.80) cm and S5 (2.78) cm.
The lowest fruit diameter during 2003 was recorded from S13 (Siwana)
provenance with mean value of 2.05 cm which was statistically at par with S15
(Rawatsar), S7 (Sadri) and S11 (Sura) provenances. In 2002, fruit diameter showed a range of 2.35-3.10 cm with mean value of 2.60 cm whereas in 2003 it ranged between 2.05-3.29 cm with mean value of 2.59 cm. Coefficient of variation was found to be higher (8.72 per cent) during 2002 with comparison of 2003 with value of 7.57 per cent .
During 2003, mean pulp : seed ratio was recorded to be maximum (3.16) from S5
(Chopasani) provenance. Which was statistically at par with S3 (Devnagar), S4
(Sagari farm), S2 (Gahnehra), S6 (Doli) and S10 (Santhu) provenances. Whereas the minimum pulp : seed ratio of 2.22 was recorded from S13 (Siwana) provenance.
In 2003, S5 (Chopasani) provenance gave the maximum pulp : seed ratio of 2.83 which was statistically at par with S2 (Gahnehra), S10 (Santhu), S4 (Sagari farm) and S12 (Sharath) provenances. Whereas minimum pulp : seed ratio was recorded from S15 (Rawatsar) provenance. In 2002, pulp : seed ratio showed a range of 2.22-3.16 with mean value of 2.57 whereas in 2003, it ranged between 2.14-2.83 with mean value of 2.48.The coefficient of variation was highest during 2002 with value of 13.42 per cent and lowest of 5.47 per cent during 2003.
It is clear from the table-3 that S5 (Chopasani) provenance recorded the maximum (17.90 g) fruit weight during 2002, which was statistically at par with
S6 (Doli), S8 (Ranawas), S4 (Sagari farm), S2 (Gahnehra), S3 (Devnagar) and S1
(Bagolye) provenances. Lowest mean fruit weight of 12.17g was recorded for S7
(Sadri) provenance which was statistically at par with S12 (Sharath), S15
(Rawatsar), S13 (Siwana), S14 (karna), S11 (Sura) and S9 (Sojat) provenances.
In 2003, S3 (Devnagar) provenance recorded the maximum fruit weight of
17.50g which was statistically at par with S4 (Sagari farm), S10 (Santhu), S8
(Ranawas), S5 (Chopasani), S1 (Bagolye), S2 (Gahnehra), S12 (Sharath) and S6
(Doli) provenances. Lowest fruit weight of 10.0g was recorded for S13 (Siwana) provenance which was statistically at par with S15 (Rawatsar) and S7 (Sadri) provenances. In 2002, fruit weight showed a range of 12.17- 17.90g with mean value of 15.11 g whereas in 2003 it showed widest range of 10.0- 17.50g with mean value of 15.20 g. However, coefficient of variation recorded during 2002 was less than the coefficient of variation recorded during 2003. In 2002, coefficient of variation gave the value of 7.82 per cent whereas in 2003, it was 10.13 per cent.
4.1.3 Variation in fruit quality characteristics among the different provenances of Lehsua
Data pertaining to fruit quality characteristics viz; T.S.S and acidity are presented in table-4. It is clear from the table that T.S.S. ranged between 5.80 to 7.67 0Brix with mean value of 6.73 0Brix and noticed 8.54 per cent coefficient of variation 0 during 2002. It was highest (7.67 Brix) in S5 (Chopasani) provenance which was statistically at par with that of S6 (Doli), S4 (Sagari farm), S13 (Siwana), S3
(Devnagar), S14 (Karna), S1 (Bagolye), S11 (Sura) and S15 (Rawatsar) 0 provenances. Lowest value of 5.80 Brix was noticed from S8 (Ranawas) provenance which was statistically at par with S9 (Sojat), S7 (Sadri), S2
(Gahnehra), S12 (Sharath ) and S10 (Santhu) provenances. In 2003, total soluble solids ranged between 5.73-7.67 0Brix with mean value of 6.69 and noticed 8.28 per cent coefficient of variation. It was highest
0 (7.67 Brix) in S6 (Doli) provenance which was statistically at par with S5
(Chopasani), S4 (Sagri farm), S1 (Bagolye), S13 (Siwana), S3 (Devnagar) and S15 0 (Rawatsar) provenances. Lowest value of 5.73 Brix was noticed from S9 (Sojat) provenance which was statistically at par with S7 (Sadri), S8 (Ranawas), S2
(Ganehra), S11 (Sura) and S14 (karna) provenances. Per cent acidity ranged between 0.08-0.11 with mean value of 0.096 during both the years. Higher coefficient of variation (9.62 %) was recorded during 2002 in comparison to 2003 with value of 7.44 per cent. High acidity content was recorded from the S7 (Sadri) and S8 (Ranawas) provenences with the mean value of 0.11 per cent during both the years. In 2002, high acidity content was recorded from the S7 (Sadri), S8 (Ranawas) and S10 (Santhu) provenences with the value of 0.11 per cent. While the minimum acidity content was recorded from S5 (Chopasani), S6 (Doli) and S15 (Rawatsar) provenances with the same value of 0.08 per cent. In 2003, maximum acidity content was recorded from the S2 (Gahnehar), S7 (Sadri) and S8 (Ranawas) provenances with the value of 0.11 per cent. Whereas minimum acidity content was recorded from the S3
(Devnagar), S13 (Siwana) and S15 (Rawatsar) provenances with the same value of 0.08 per cent. In general variation among provenances was found to be least for this character.
4.1.4 variation for different traits on pooled data basis.
Year wise data of each provenance has been discussed in the previous tables for various characteristics like morphological characteristics, fruit characteristics and fruit quality characteristics. Pooled analysis of the data was carried out to study the over all variation during both the years.
Variation in morphological characters:
The results of the pooled analysis has been presented in Table-5. It is evident from the data presented in table that plant height varied between 6.64-
9.34 m. S2 (Gahnehra) provenance recorded the highest value of 9.34 m for plant height, followed by S3 (Devnagar) with mean value of 8.00 m and S4 (Sagari farm) with mean value of 7.88 m. S5 (Chopasani) provenance recorded the lowest mean value of 6.64 m for plant height which was statistically at par with S12
(Sharath), S1 (Bagolye), S13 (Siwana), S14 (Karna), S9 (Sojat), S11 (Sura), S6
(Doli) and S8 (Ranawas) provenances. Among all the morphological characters studied, plant spread recorded the highest value for coefficient of variation (20.18 per cent). Plant spread showed the variation range between 38.13-91.66 m2 with mean value of 53.69 m2. Pooled analysis showed that during both the years of 2 study S2 (Gahnehra) provenance recorded highest mean value of 91.66m for 2 plant spread followed by S7 (Sadri) provenance with mean value of 76.12 m .
Likewise during both the years of study S10 (Santhu) provenance recorded the lowest mean value of 38.13 m. Mean leaf length on pooled data basis varied from 13.02-16.73 cm.
Maximum leaf length of 16.73 cm recorded for S5 (Chopasani) provenance which was statistically at par with S4 (Sagari farm) and S13 (Siwana) provenances. S12 (Sharath) provenance recorded the lowest value of 13.02 cm which was statistically at par with S11 (Sura), S8 (Ranawas), S14 (Karna), S10
(Santhu), S9 (Sojat) and S7 (Sadri) provenances. Leaf length showed 7.73 per cent coefficient of variation. Similarly on pooled basis (table-5) the maximum leaf width of 14.80 cm has been recorded for S5 (Chopasani) provenance which was statistically at par with S15 (Rawatsar) and S13 (Siwana) provenance. S11 (Sura) provenance
recorded the lowest value of 11.82 cm. Leaf width varied from 11.82-14.8 cm with the mean value of 12.86 cm and contributed 8.45 per cent coefficient of variation.
Variation in Fruit Characteristics :
Mean fruits per cluster on pooled data basis varied from 7.17-17.50 with mean value of 12.70 (table-6). S1 (Bagolye) provenance gave the highest mean fruits per cluster (17.50) which was statistically at par with S6 (Doli) and S5 (Chopasani) provenaces. Minimum mean fruits per cluster (7.17) were recorded for S8 (Ranawas) provenance which was statistically at par with S4 (Sagarifarm). Fruits per cluster recorded 12.30 per cent coefficient of variation. Pooled analysis of the data which has been given in table-6 reveals that the provenance which performed better during 2002 and 2003 also gave the better performance by and large on the pooled data basis. S6 (Doli) provenance gave the highest mean fruit diameter (3.20cm) which was statistically at par with
S4 (Sagari farm) with the value of 3.00 cm. Minimum fruit diameter of 2.26 cm was recorded for S13 (Siwana) provenance which was statistically at par with S15
(Rawatsar), S11 (Sura), S7 (Sadri) and S12 (Sharath) provenances. Fruit diameter ranged between 2.26-3.20cm with mean value of 2.60 cm and 8.17 per cent coefficient of variation. It is clear from the table that pulp : seed ratio varied between 2.20-2.99 with mean value of 2.52. S5 (Chopasani) provenance gave the highest mean pulp : seed ratio (2.99) during both the years of study, which was statistically at par with S4 (Sagri farm), S2 (Gahnehara) and S3 (Devnagar). S15 (Rawatsar) provenance recorded the lowest value of 2.20 for pulp : seed ratio which was statistically at par with S13 (Siwana), S8 (Ranawas), S9 (Sojat) S14 (Karna), S7
(Sadri) and S11 (Sura) provenances. Coefficient of variation for pulp seed ratio was 10.37 percent. Fruit weight was observed to be maximum among the fruits collected from S5 (Chopasani) with mean value of 17.55 g which was statistically at par with S4 (Sagari farm), S8 (Ranawas), S2 (Gahnehra), S3 (Devanagar), S1
(Bagolye), S6 (Doli) and S10 (Santhu) provenances. The lowest value of 11.38 g has been recorded for S13 (Siwana) provenance which was statistically at par with
S15 (Rawatsar) and S7 (Sadri) provenances. The fruit weight varied between 11.38-17.55 g with mean value of 15.16 g and contributed 9.05 per cent coefficient of variation.
Variation in fruit quality characteristics:
It is evident from the data presented in the table-7 that total soluble solids varied between 5.78-7.58 0Brix with mean value of 6.71 and noticed 8.41 per 0 cent coefficient of variation. It was highest (7.58 Brix) in S5 (Chopasani) provenance, which was statistically at par with that of S6 (Doli), S4 (Sagari farm), S13 (Siwana) S1 (Bagolye) and S3 (Devnagar) provenances. Lowest value 0 of 5.78 Brix was noticed from that of S9 (Sojat) provenance which was statistically at par with S7 (Sadri), S8 (Ranawas) and S2 (Gahnera) provenances.
Maximum acidity was recorded from S2 (Gahnera), S7 (Sadri) and S8 (Ranawas) provenances with same value of 0.11 per cent. While the lowest value of 0.08 per cent was recorded from S15 (Rawatsar) provenance. The acidity varied between 0.08-0.11 per cent with mean value of 0.096 per cent and contributed 8.59 per cent coefficient of variation.
4.2 VARIABILITY ESTIMATES AND GENETIC STUDIES
Variability was estimated in terms of range, mean, (discussed in previous tables for different characters), variance (phenotypic, genotypic) alongwith coefficient of variation. Genetic parameters were worked out with regard to estimates of heritability (broad sense), genetic advance and genetic advance as per cent of mean. The results obtained for variability and genetic parameters are presented in the ensuing tables and described as follow.
4.2.1 Variability estimates for morphological characters in Cordia myxa Roxb
During the year 2002, highest phenotypic and genotypic variances for plant spread were observed as 266.23 and 153.98, respectively. These values for the year 2003 were recorded as 323.91 and 201.42, respectively. Highest phenotypic coefficient of variation of 30.82 and 33.06 per cent were recorded for plant spread during the year 2002 and 2003, respectively. Plant spread also recorded the highest value of 23.44 and 26.07 per cent for genotypic coefficient of variation in 2002 and 2003, respectively (Table-8). The phenotypic coefficient of variation in all the characteristics were higher than the genotypic coefficient of variation. Table-8 Variance and coefficient of variability for morphological characteristics during 2002 and 2003 in Lehsua (Cordia myxa Roxb.). Characters Variance CV (%) Phenotypic Genotypic PCV GCV 2002 2003 2002 2003 2002 2003 2002 2003 Plant height 0.680 1.16 0.33 0.69 11.18 14.27 7.79 11.03
Plant spread 266.23 323.91 153.98 201.42 30.82 33.06 23.44 26.07 Leaf length 3.63 1.63 1.99 0.75 13.02 8.87 9.65 6.02 Leaf width 3.13 0.96 1.30 0.40 13.66 7.60 8.81 4.91
Table-9 Estimates of genetic parameters for morphological characteristics during 2002 and 2003 in Lehsua (Cordia myxa Roxb.). Characters Heritability (%) Genetic advance Genetic advance as (%) percentage of mean 2002 2003 2002 2003 2002 2003
Plant height 48.60 59.7 0.825 1.32 11.18 17.56
Plant spread 57.80 62.2 19.44 23.06 36.72 42.35 Leaf length 55.0 46.0 2.157 1.21 14.74 8.40 Leaf width 41.60 41.70 1.516 0.84 11.70 6.53
Plant height recorded the minimum respective values of 11.18 and 7.79 per cent for phenotypic and genotypic coefficient of variation during 2002. While during 2003, the minimum value of phenotypic and genotypic coefficient of variation were 7.60 and 4.91 per cent, respectively for leaf width. Plant spread recorded highest heritability (moderate) of 57.80 and 62.2 per cent with the genetic advances as percentage of mean of 36.72 and 42.35 during both the years of study (Table-9).
4.2.2 Variability estimates for fruit characteristics in Cordia myxa Roxb
Variability estimates and genetic parameters were worked out for fruits per cluster, fruit diameter, pulp : seed ratio and fruit weight in 2002 and 2003 and presented in Table-10. Among all the fruit characters fruits per cluster recorded the maximum value of 11.02 and 10.98 and 8.44 and 8.67 for phenotypic and genotypic variances respectively, during both the years of study.
Table-10 Variance and coefficient of variability in fruit characteristics during 2002 and 2003 in Lehsua (Cordia myxa Roxb.). Characters Variances CV (%) Phenotypic Genotypic PCV GCV 2002 2003 2002 2003 2002 2003 2002 2003 Fruits / cluster 11.02 10.98 8.44 8.67 26.48 25.75 23.18 22.89
Fruit diameter 0.09 0.13 0.040 0.096 11.64 14.15 7.71 11.96
Pulp : seed ratio 0.16 0.06 0.04 0.038 15.59 9.57 7.95 7.86
Fruit weight 5.51 7.66 4.11 5.30 15.53 18.22 13.42 15.14
Table-11 Estimates of genetic parameters in fruit characteristics during 2002 and 2003 in Lehsua (Cordia myxa Roxb.). Characters Heritability (%) Genetic advance Genetic advance as (%) percentage of mean 2002 2003 2002 2003 2002 2003
Fruits/ cluster 76.6 79.0 5.24 5.39 41.80 41.91
Fruit diameter 43.90 71.4 0.27 0.54 10.52 20.80
Pulp : seed ratio 26.0 67.4 0.21 0.33 8.34 13.28
Fruit weight 74.7 69.1 3.61 3.94 23.88 25.93
Highest phenotypic coefficient of variation of 26.48 and 25.75 per cent were recorded for fruits per cluster during the year 2002 and 2003, respectively. Fruits per cluster also recorded the highest value of 23.18 and 22.89 per cent for genotypic coefficient of variation in 2002 and 2003, respectively. Highest heritability of 76.6 and 7.90 per cent were recorded for fruits per cluster with genetic advance as percentage of mean of 41.80 and 41.91 during both the years of study. Lowest heritability of 26.0 and 67.4 with low genetic advance as percentage of mean of 8.34 and 13.28 were recorded for pulp : seed ratio during 2002 and 2003, respectively (Table -11 ).
4.2.3 Variability estimates in fruit quality characteristics in Cordia myxa Roxb.
Table-12 revealed that total soluble solids recorded the maximum value of 0.523 and 0.57 and 0.192 and 0.258 for phenotypic and genotypic variation during 2002 and 2003, respectively. Acidity gave the lowest value of 0.00016 and 0.00017 and 0.00011 and 0.00012 for phenotypic and genotypic variances during 2002 and 2003, respectively. Table-12 Variance and coefficient of variability for fruit quality characteristics during 2002 and 2003 in Lehsua (Cordia myxa Roxb.).
Characters Variance CV (%) Phenotypic Genotypic PCV GCV 2002 2003 2002 2003 2002 2003 2002 2003 T.S.S. 0.523 0.57 0.192 0.258 10.74 11.23 6.52 7.58
Acidity 0.00016 0.00017 0.00011 0.00012 12.30 11.18 7.66 8.35
Table-13 Estimates of genetic parameters for fruit quality during 2002 and 2003 in Lehsua (Cordia myxa Roxb.). Characters Heritability (%) Genetic advance Genetic advance as (%) percentage of mean 2002 2003 2002 2003 2002 2003
T.S.S. 36.80 45.60 0.548 0.706 8.14 10.55
Acidity 38.80 55.80 0.009 0.012 9.84 12.85
Acidity recorded the maximum value of 12.30 per cent for phenotypic coefficient of variation during 2002 and 7.66 and 8.35 per cent for genotypic coefficient of variation during both the years of study. Acidity also recorded highest heritability of 38.80 and 55.80 per cent with high genetic advance as percentage of mean during both the years of study (Table-13).
4.2.4. Variability estimates for different traits on pooled data basis
Range, mean and coefficient of variation for morphological, fruit characteristics and fruit quality on pooled data basis has been discussed in previous tables. Whereas, phenotypic and genotypic variances along with their coefficient of variation and genetic parameters such as heritability, genetic
advance and genetic advance as percentage of mean on pooled data basis has been presented in the ensuing tables. For morphological characters on pooled data basis (Table-14), maximum phenotypic and genotypic variances of 508.80 and 391.43 were calculated for plant spread. Plant spread also showed maximum value for phenotypic coefficient of variation (33.89 per cent) and genotypic coefficient of variation (27.23). Plant height recorded the minimum value of 1.517 per cent for phenotypic variance and 1.11 per cent for genotypic variance, whereas leaf width recorded the low value of 11.16 per cent for phenotypic coefficient of variation and 7.28 per cent for genotypic coefficient of variation. Table-15 indicated that plant spread recorded the highest heritabitity (64.60 per cent ) followed by high value of genetic advance and genetic advance as percentage of mean. While, leaf width recorded the minimum value of 42.60 per cent for heritability and 9.8% for genetic advance as percentage of mean. Table-14 Variance and coefficient of variability for morphological characteristics in Lehsua (Cordia myxa Roxb.) on pooled data basis. Characters Variances CV (%) Phenotypic Genotypic PCV GCV Plant height 1.517 1.11 13.46 10.39 Plant spread 508.80 391.43 33.89 27.23 Leaf length 4.06 2.80 11.30 8.25 Leaf width 2.93 1.74 11.16 7.28 Table-15 Estimates of Genetic parameters for morphological characteristics in Lehsua (Cordia myxa Roxb.) on pooled data basis Characters Heritability Genetic Genetic advance as (%) advance (%) percentage of mean Plant height 59.50 1.23 16.50
Plant spread 64.60 24.20 45.07 Leaf length 53.30 1.80 12.50 Leaf width 42.60 1.26 9.80
Among fruit characters, maximum phenotypic and genotypic variances of
19.43 and 16.99, respectively were observed for fruits per cluster. While pulp : seed ratio recorded the minimum value of 0.155 and 0.087 for phenotypic and genotypic variances.
Partitioning of total variances (Table-16) for fruit traits on pooled data basis showed that the fruit diameter recorded the minimum value of 12.48 per cent for phenotypic coefficient of variation. Whereas, pulp : seed ratio recorded the minimum value of 8.63 per cent for genotypic coefficient of variation. Fruits per cluster recorded highest value of 77.60 per cent for heritability. Minimum value of 40.90 per cent for heritability was registered for pulp : seed ratio.
Genetic advance as percentage of mean was maximum of 41.50 per cent for fruits per cluster. Whereas, pulp : seed ratio recorded the low value of 11.50 for genetic advance as percentage of mean (Table-17).
Table-16 Variance and coefficient of variability in fruit characteristics in Lehsua (Cordia myxa Roxb.) on pooled data basis. Characters Variances CV (%) Phenotypic Genotypic PCV GCV Fruits/ cluster 19.43 16.99 25.96 22.87
Fruit diameter 0.172 0.127 12.48 9.43 Pulp : seed ratio 0.155 0.087 13.49 8.63 Fruit weight 10.78 8.90 16.27 13.52
Table-17 Estimates of genetic parameters in fruit characteristics in Lehsua (Cordia myxa Roxb) on pooled data basis Characters Heritability Genetic advance Genetic advance as (%) (%) percentage of mean Fruits/ cluster 77.60 5.27 41.50 Fruit diameter 57.1 0.38 14.64 Pulp : seed ratio 40.90 0.29 11.50 Fruit weight 69.0 3.51 23.16
Phenotypic and genotypic variance were observed to be maximum for total soluble solids with the value of 0.853 and 0.535, respectively. Acidity recorded the minimum value of 0.00018 and 0.00017 for phenotypic and genotypic variances. Acidity also recorded the minimum value of 11.68 per cent for phenotypic and 7.90 per cent for genotypic coefficient of variation. Total soluble solids recorded the maximum value of 11.81 per cent for phenotypic coefficient of variation and 8.30 per cent for genotypic coefficient of variation (Table-18). Table-19 indicated that the total soluble solids recorded the highest value of 49.30 per cent for heritability and the value of 12.07 for genetic advance as percentage of mean.
Acidity recorded minimum value of 45.80 per cent for heritability with low value of 10.40 for genetic advance as percentage of mean.
Table-18 Variance and coefficient of variability for fruit quality
characteristic in Lehsua (Cordia myxa Roxb.) on pooled data
basis.
Characters Variance CV (%)
Phenotypic Genotypic PCV GCV
T.S.S. 0.853 0.535 11.81 8.30
Acidity 0.00018 0.00017 11.68 7.90
Table-19 Estimates of genetic parameters for fruit quality characteristic in
Lehsua (Cordia myxa Roxb.) on pooled data basis.
Characters Heritability (%) Genetic Genetic advance as
advance (%) percentage of mean
T.S.S. 49.30 0.81 12.07
Acidity 45.8 0.01 10.40
4.3 CORRELATION COEFFICIENT
Correlation coefficient among various morphological characters, fruit and fruit quality characteristics
at genotypic and phenotypic levels have been presented in table-20. In general, the genotypic
correlation coefficients were higher in magnitude than their respective phenotypic correlation
coefficients for most of the character pairs. The direction of phenotypic and genotypic correlation
coefficients were similar for most of the character combinations. The difference between genotypic
and phenotypic correlation coefficients was negligible. Hence, environmental interfered less with the
character expression. At genotypic level, fruit weight had significant positive correlation coefficient
with pulp : seed ratio (r = 0.843) and fruit size (r = 0.768) but leaf width showed significant and
negative correlation coefficient (-0.531) with fruit weight; rest of the correlation of fruit weight were
non-significant and positive except leaf length which was negative.
The correlation among the character interse showed that leaf width had highest significant positive association with leaf length (r = 0.949) while, significant negative with acidity (r = -0.598). Rest of the characters exhibited negative non-significant association with leaf width, except total soluble solids (0.192) which showed positive non-significant correlation with leaf width. Plant spread had high positive significant correlation with plant height (r = 0.886). Its association with fruits per cluster (0.026), fruit size (0.194), pulp : seed ratio (0.121) and acidity (0.231) were positive and non-significant. Plant spread showed non-significant and negative association with T.S.S. (-0.187) and leaf width (-0.163). Acidity had significant negative correlation with T.S.S. (r = -0.863) while plant height (0.398), plant spread (0.500) and fruit size (0.291) showed non- significant and positive association with acidity. T.S.S. had high positive correlation with pulp : seed ratio (0.608) while its non-significant correlation was observed with fruits per cluster (0.437), leaf length (0.128), leaf width (0.093) and fruit weight (0.246).
4.4 PATH COEFFICIENT ANALYSIS
The path coefficient analysis was performed at genotypic and phenotypic levels by utilizing genotypic and phenotypic correlation coefficients,
respectively, to partition the correlation coefficient into direct and indirect effects. The fruit weight was taken as dependent variable. In a breeding programmes, we are often concerned with the improvement in fruit weight as an overall product dependent on a number of morpho- physiological attributes. Such characters are often interrelated, hence their effect on fruit weight is also modified by others. Path coefficient analysis helps in separating the direct effect of a component character on fruit weight from indirect effects of other traits. The genotypic and phenotypic correlation coefficients of fruit weight with its contributing characters were partitioned into direct and indirect effects through path coefficient analysis and are presented in table (21). The results of path coefficient analysis indicated that the signs of direct effects at genotypic and phenotypic levels were positive for the characters viz. plant height, fruit size and pulp : seed ratio while for leaf length, the sign of direct effect was negative at genotypic and phenotypic levels. The signs of direct effect were differed at genotypic and phenotypic levels for plant spread, fruits per cluster, T.S.S., acidity and leaf width. At genotypic level, pulp : seed ratio (1.311) had highest direct effects followed by leaf width (1.032), fruit size (0.522), plant spread (0.140) and plant height (0.040) on fruit weight. Whereas, highest negative effects was recorded for leaf length (-0.847) followed by T.S.S. (-0.485), acidity (-0.281) and fruits per cluster (-0.125). Plant height (0.040) had positive direct effect but it also had indirect negative effects via fruits per cluster (-0.003), acidity (-0.112) and leaf width (- 0.277). Plant spread (0.140) had positive direct effect but, it also had indirect negative effects via fruits per cluster (-0.001), acidity (-0.141) and leaf width (- 0.329). Fruits per cluster (-0.125) had negative direct effect and it also had indirect negative effect via fruit size (-0.197), T.S.S. (-0.212) and leaf width (- 0.128). Fruit size (0.522) had positive direct effect but it also had negative
indirect effect via acidity (-0.082), and leaf width (-0.301). Pulp : seed ratio exerted highest direct effect and highest correlation coefficient with fruit weight but it also had indirect negative effect via fruits per cluster (-0.055), T.S.S. (- 0.295) and leaf width (-0.505). T.S.S. had negative direct effect but it also had positive indirect effect via. pulp : seed ratio (0.797), acidity (0.235) and leaf width (0.198). Acidity had negative direct effect and it also had negative indirect effect via pulp : seed ratio (-0.093) and leaf width (-0.617). Leaf length had negative direct effect and it also had negative indirect effect via fruit size, pulp : seed ratio, T.S.S. and also had negative correlation coefficient with fruit weight. Leaf width had positive direct effect and it also had positive indirect effect via fruits per cluster, T.S.S. and acidity. At phenotypic level, among the various characters, fruit size (0.522) exerted highest positive direct effect followed by T.S.S., acidity, plant height, fruits per cluster and pulp : seed ratio. Whereas leaf width, leaf length and plant spread had positive direct effect but the values were very low.
4.5 GENETIC DIVERGENCE
4.5.1 Estimates of divergence among the different Lehsua provenances during 2002
The application of Mahalanobis D2 statistics for data of 2002 revealed that the fifteen provenances differed genetically among themselves (Table - 22). These genotypes were grouped into four clusters on the basis of D2 estimates (Table 22). The maximum number of genotypes (11) were included in cluster I (S1, S6, S5, S11, S12, S9, S3, S2, S13, S10 and S15). Two genotypes were included in cluster II (S4 and S8) whereas single genotypes was included in cluster III (S7) and cluster IV (S14). The D2 value for the different characters showed the per cent contribution of each character to divergence. The fruit weight contributed maximum (30.476%) followed by fruits per cluster (29.524%). Contribution of the leaf length was 13.33 per cent (Table 23) while fruit diameter contributed 7.619 per cent. Table-22 Clustering of genetic divergence among different Lehsua (Cordia myxa Roxb.) provenances during 2002. Clusters Population
I S1, S6, S5, S11, S12, S9, S3, S2, S13, S10 and S15
II S4 S8
III S7
IV S14
Table- 23 Contribution of each character to divergence among the different Lehsua (Cordia myxa Roxb.) provenances during 2002
Charac Plant Plant Fruits/ Fruit Pulp : T.S.S. Acidity Leaf Leaf Fruit ters height spread cluster Dia. seed length width weight ratio Per- 5.714 0.952 29.524 7.619 2.857 4.762 3.81 13.33 0.952 30.476 cent Contr- ibution
Table-24 Average intra and inter cluster D2 values for different Lehsua (Cordia myxa Roxb.) provenances during 2002 Cluster I II III IV I 26.33 51.30 67.94 42.79
II 31.48 58.13 65.46
III 0.00 68.61
IV 0.00
Table-25 Average intra and inter cluster distance (D values) among different Lehsua (Cordia myxa Roxb) provenances during 2002 Cluster I II III IV I 5.13 7.16 8.24 6.54
II 5.61 7.62 8.09
III 0.00 8.28
IV 0.00
Table-26 Cluster mean of various characters in Lehusa during 2002. Character I II III IV Plant height (m) 7.30 7.75 7.73 7.10 Plant spread (m2) 50.76 55.43 75.86 49.01 Fruits/ cluster 13.73 8.50 8.00 12.00 Fruit diameter (cm) 2.54 3.09 2.42 2.51 Pulp : seed ratio 2.59 2.63 2.46 2.28 T.S.S. (0Brix) 6.82 6.55 5.93 6.90 Acidity (%) 0.094 0.10 0.11 0.09 Leaf length (cm) 14.25 14.58 13.83 19.73 Leaf width (cm) 12.68 12.84 12.40 16.83 Fruit weight (g) 15.07 17.50 12.17 13.67
The average intra and inter cluster D values are presented in table-25. The generalized intra cluster distances (D) were 5.13 and 5.61 for cluster I and II, respectively. The generalized inter cluster distances were 7.16 (between I and II), 8.24 (between I and III), 6.54 (between I and IV), 7.62 (between II and III), 8.09 (between II and IV) and 8.28 (between III and IV). The cluster II showed highest fruit weight (17.50g), fruit diameter (3.09cm), pulp : seed ratio (2.63) and plant height (7.75m). While the minimum values for the characteristics viz, fruit diameter (2.42cm), fruits per cluster (8.00), leaf length (13.83cm), leaf width (12.40cm) and fruit weight (12.17g) were recorded in cluster III during 2002. However, the maximum plant spread (75.86m2) was recorded in cluster III (Table-26). It is clear from the above rating that all the genotypes within each cluster were genetically closer since all the clusters had low (< 50) intra cluster distances. The relative divergence of one cluster from other (inter cluster
distance) indicated high order of divergence between cluster III and IV (8.28) followed by cluster I and III (8.24) and cluster II and IV (8.09).
4.5.2 Estimates of divergence among different Lehsua provenances during 2003
In 2003 (Experiment-2), the 15 genotypes representing the provenances of Lehsua were genetically different with each other (Table 27). On the basis of D2 analysis these genotypes were grouped into three clusters. The maximum number of genotypes (13) were included in cluster I (S1, S6, S3, S5, S12, S11, S9, S2, S4, S10,
S14, S9 and S15). Cluster II and cluster III had one genotypes each with S8 and S13 , respectively. The D2 values for the different characters showed the per cent contribution of each character to divergence. In 2003, too, the maximum contribution was by the fruit weight (26.17%). This was followed by fruits per cluster (16.19%) and leaf width (16.19%). T.S.S. and fruit diameter contributed 10.48 and 7.62 per cent respectively, while the contribution of the plant height was 6.67 per cent (Table 28). The average intra and inter cluster D values are presented in table-30. The generalized inter cluster distances were 10.99 (between I and II), 9.06 (between I and III). The maximum generalized inter cluster distances were 15.11 (between cluster II and III).
Table-27 Clustering of genetic divergence among different Lehsua (Cordia myxa Roxb.) provenances during 2003 Clusters Population
I S1, S6, S3, S5, S12, S11, S9, S2, S4, S10 S14, S7 and S15
II S8
III S13 Table-28 Contribution of each character to divergence among the different Lehsua (Cordia myxa Roxb.) provenance during 2003
Chara- Plant Plant Fruits/c Fruit Pulp : T.S.S. Acidity Leaf Leaf Fruit cters height spread luster Dia. seed length width weight ratio
Per- 6.667 2.857 16.190 7.619 5.714 10.476 1.905 5.714 16.19 26.17 cent contribu tion
Table-29 Average intra and inter cluster D2 values for different Lehsua (Cordia myxa Roxb.) provenances during 2003 Cluster I II III
I 47.42 120.78 82.00 II 0.00 228.41 III 0.00
Table-30 Average intra and inter cluster distance (D values) among different Lehsua (Cordia myxa Roxb.) provenances during 2003 Cluster I II III
I 6.89 10.99 9.06 II 0.00 15.11 III 0.00
Table-31 Cluster mean of various characters in Lehusa during 2003. Character Cluster I II III
Plant height (m) 7.55 7.77 7.12 Plant spread (m2) 54.88 63.83 39.39 Fruits/ cluster 13.41 6.00 12.67 Fruit diameter (cm) 2.57 3.39 2.05 Pulp : seed ratio 2.51 2.26 2.27 T.S.S. (0Brix) 6.72 6.00 7.10 Acidity (%) 0.095 0.11 0.08 Leaf length (cm) 14.39 13.30 15.37 Leaf width (cm) 12.88 11.97 14.00 Fruit weight (g) 15.43 17.40 10.00
The cluster II was characterized by the highest fruit weight (17.40g), maximum fruit diameter (3.39cm), tallest plant (7.77m), more plant spread (63.83m2) and minimum number of fruits per cluster (6.00), while cluster III registered minimum fruit weight (10.00g), smaller plant (7.12m) with minimum plant spread (39.39m2), least fruit diameter (2.05cm) and maximum total soluble solids (7.10 0Brix). Considering the data of 2002 and 2003, it appears that the genotypes within each clusters were genetically related, since all the clusters had low (µ 50) intra cluster distances. The relative divergence of each cluster from other clusters (inter cluster distance) indicated high order of divergence between cluster II and III (15.11) followed by cluster I and II (10.99) and cluster I and III (9.06).
4.5.3 Estimate of Divergene among different Lehsua provenances (pooled basis)
Pooled data analysis revealed that the 15 sites representing the provenances of Lehsua (S1……….S15) showed marked genetic divergence among themselves (Table 32). On the basis of D2 analysis these genotypes were grouped into six clusters (Table 33). The maximum number of genotypes (7) were included in cluster I
(S1, S6, S5, S11, S3, S12, and S9). Cluster II, cluster III and cluster IV had two genotypes each with S4, S10; S7, S15 and S13, S14 respectively, whereas single genotype was included in cluster V (S8) and cluster VI (S2). The D2 values for the different characters showed the per cent contribution of each character to divergence. The per cent contribution of different characters towards divergence showed that fruit weight (32.38%) contributed to the maximum followed by fruits per cluster (23.81%). Plant height contributed 10.476 per cent. While, the contribution of leaf width was zero per cent (Table- 33). Table-32 Clustering of genetic divergence among different Lehsua (Cordia myxa Roxb.) provenances (pooled basis) Clusters Population
Cluster I S1, S6, S5, S11, S3, S12, and S9
Cluster II S4, S10
Cluster III S7, S15
Cluster IV S13, S14
Cluster V S8
Cluster VI S2
Table-33 Contribution of each character to divergence among the different Lehsua (Cordia myxa Roxb.) provenance (pooled basis)
Chara- Plant Plant Fruits/c Fruit Pulp : T.S.S. Acidity Leaf Leaf Fruit cters height spread luster Dia. seed length width weight ratio
Per- 10.476 4.762 23.81 9.524 2.857 3.81 2.857 9.524 0.000 32.38 cent contribu tion
Table-34 Average intra and inter cluster D2 values for different Lehsua (Cordia myxa Roxb) provenances (pooled basis) Clusters I II III IV V VI I 15.29 28.22 39.58 29.39 17.22 28.22 II 17.58 44.89 39.11 28.44 8.79 III 27.76 24.16 38.33 44.89 IV 0.00 31.26 39.11 V 20.96 28.44 VI 17.58
Table-35 Average intra and inter cluster distance (D values) among different Lehsua (Cordia myxa Roxb.) provenances (pooled basis). Clusters I II III IV V VI I 3.91 5.31 6.32 5.42 4.15 5.31 II 4.19 6.70 6.25 5.33 2.96 III 5.27 4.91 6.19 6.70 IV 0.00 5.59 6.25 V 4.58 5.33 VI 4.19
Table-36 Cluster mean of various characters in Lehusa (pooled basis) Character Clusters I II III IV V VI Plant height (m) 7.26 7.32 7.30 7.08 6.39 7.32 Plant spread (m2) 50.72 43.13 60.50 38.94 46.21 43.13 Fruits/ cluster 14.86 9.42 10.59 12.33 12.39 9.42 Fruit diameter (cm) 2.59 2.76 2.32 2.26 2.24 2.76 Pulp : seed ratio 2.61 2.73 2.27 2.25 2.19 2.73 T.S.S. (0Brix) 6.86 7.01 6.35 7.05 5.80 7.01 Acidity (%) 0.094 0.095 0.095 0.090 0.082 0.095 Leaf length (cm) 13.95 14.69 14.54 15.43 12.14 14.69 Leaf width (cm) 12.56 12.69 13.33 13.97 10.81 12.69 Fruit weight (g) 15.59 16.88 12.17 11.38 13.45 16.88
The average intra and inter cluster D values are presented in table-35. The generalized intra cluster distance (D) were 3.91, 4.19, 5.27, 0.00, 4.58 and 4.19 ,respectively, for cluster I, II III, V and VI. Maximum and minimum generalized
inter cluster distances were 6.70 (between cluster III and VI; II and III) and 2.96 (between cluster II and VI), respectively. On pooled data basis cluster II and VI were characterized by the highest fruit weight (16.88g), tallest plant (7.32m), maximum fruit diameter (2.76cm) and pulp : seed ratio (2.73) and minimum fruits per cluster (9.42). While cluster IV showed minimum plant spread (38.94m2), maximum T.S.S. (7.05 0Brix), more leaf length (15.43cm) and leaf width (13.97cm) and lowest fruit weight 11.38g (Table-36). It is clear from the above rating that all the genotypes within each cluster were genetically closer ; since all the clusters had low ( < 50) intra cluster distances. The relative divergence of each cluster from other clusters (inter cluster distance) indicated high order of divergence between cluster III and VI; II and III followed by cluster I and III; IV and VI (Table-35).
Table-1. Geographical locations of different provenances of Lehsua (Cordia myxa Roxb.) in Rajasthan. Code name Provenances Districts
S1 Bagolye Ajmer (pushkar)
S2 Gahnehra
S3 Devnagar
S4 Sagari farm Jodhpur
S5 Chopasani
S6 Doli
S7 Sadri Pali
S8 Ranawas
S9 Sojat
S10 Santhu Jalore
S11 Sura
S12 Sharath
S13 Siwana Barmer
S14 Karna
S15 Rawatsar
Table-4 Extent of variation in fruit quality characteristics among the different provenances of Lehsua (Cordia myxa Roxb.) in Rajasthan. Code Provenances T.S.S. (%) Acidity (%) name 2002 2003 2002 2003
S1 Bagolye 6.87 7.10 0.09 0.09
S2 Gahnehara 6.43 6.07 0.10 0.11
S3 Devnagar 6.93 6.97 0.10 0.08
S4 Sagari farm 7.30 7.37 0.09 0.10
S5 Chopasani 7.67 7.50 0.08 0.09
S6 Doli 7.37 7.67 0.08 0.09
S7 Sadri 5.93 5.87 0.11 0.11
S8 Ranaws 5.80 6.00 0.11 0.11
S9 Sojat 5.83 5.73 0.10 0.10
S10 Santhu 6.67 6.70 0.11 0.10
S11 Sura 6.87 6.50 0.10 0.10
S12 Sharath 6.53 6.47 0.10 0.10
S13 Siwana 7.00 7.10 0.09 0.08
S14 Karna 6.90 6.60 0.09 0.09
S15 Rawatsar 6.83 6.77 0.08 0.08
CD (0.05) 0.956 0.922 0.016 0.02 Range 5.80-7.67 5.73-7.67 0.08-0.11 0.08-0.11 Mean 6.73 6.69 0.096 0.096 CV(%) 8.54 8.28 9.62 7.44
Table-5 Extent of variation in morphological characters on pooled mean basis in Lehsua (Cordia myxa Roxb.).
Code name Provenances Plant height Plant spread Leaf size (cm) (m) (m2) Length Width S1 Bagolye 6.98 48.88 14.52 12.65
S2 Gahnehra 9.34 91.66 14.43 12.25
S3 Devnagar 8.00 63.04 14.63 12.90
S4 Sagari farm 7.88 48.12 15.50 13.25
S5 Chopasani 6.64 46.41 16.73 14.80
S6 Doli 7.71 55.33 14.52 12.72
S7 Sadri 7.77 76.12 14.05 12.57
S8 Ranawas 7.72 63.48 13.42 11.93
S9 Sojat 7.18 49.50 14.02 13.03
S10 Santhu 6.75 38.13 13.87 12.13
S11 Sura 7.37 52.20 13.23 11.82
S12 Sharath 6.96 39.67 13.02 12.42
S13 Siwana 7.08 38.94 15.43 13.97
S14 Karna 7.14 49.00 13.70 12.35
S15 Rawatsar 6.82 44.88 15.02 14.08
CD (0.05) 0.7515 12.459 1.32 1.287
Range 6.64-9.34 38.13-91.66 13.02-16.73 11.82-14.8
Mean 7.43 53.69 14.41 12.86
CV (%) 8.56 20.18 7.73 8.45
Table- 6 Extent of variation in fruit characteristics on pooled mean basis in Lehsua (Cordia myxa Roxb.). Code Provenances Fruits/ Fruit Pulp : seed Fruit name cluster diameter ratio weight (g) (cm) S1 Bagolye 17.50 2.55 2.57 16.65
S2 Gahnehra 15.00 2.64 2.73 17.05
S3 Devnagar 12.50 2.77 2.73 16.90
S4 Sagari farm 8.83 3.00 2.80 17.45
S5 Chopasani 15.67 2.72 2.99 17.55
S6 Doli 17.33 3.20 2.61 16.55
S7 Sadri 10.17 2.37 2.34 12.20
S8 Ranawas 7.17 2.52 2.28 17.45
S9 Sojat 13.17 2.71 2.30 13.72
S10 Santhu 10.00 2.51 2.65 16.30
S11 Sura 14.00 2.36 2.49 13.70
S12 Sharath 13.83 2.47 2.58 14.09
S13 Siwana 12.33 2.26 2.25 11.38
S14 Karna 12.00 2.56 2.34 14.20
S15 Rawatsar 11.00 2.32 2.20 12.13
CD (0.05) 1.8399 0.249 0.308 1.6159 Range 7.17-17.50 2.26-3.20 2.20-2.99 11.38-17.55
Mean 12.70 2.60 2.52 15.16 CV (%) 12.30 8.17 10.37 9.05
Table-7 Extent of variation in fruit quality characteristic on pooled mean basis in Lehsua (Cordia myxa Roxb.). Code name Provenances T.S.S. (%) Acidity (%)
S1 Bagolye 6.98 0.09
S2 Gahnehara 6.25 0.11
S3 Devnagar 6.95 0.09
S4 Sagari farm 7.33 0.09
S5 Chopasani 7.58 0.09
S6 Doli 7.52 0.09
S7 Sadri 5.90 0.11
S8 Ranaws 5.90 0.11
S9 Sojat 5.78 0.10
S10 Santhu 6.68 0.10
S11 Sura 6.68 0.10
S12 Sharath 6.50 0.10
S13 Siwana 7.05 0.09
S14 Karna 6.75 0.09
S15 Rawatsar 6.80 0.08
CD (0.05) 0.6648 0.0097 Range 5.78-7.58 0.08-0.11 Mean 6.71 0.0962 CV(%) 8.41 8.599
Table-2 Extent of variation in morphological characteristics among the different provenances of Lehsua ( Cordia myxa Roxb.). Co Provenan Plant height (m) Plant spread (m2) Leaf Size (cm) de ces Length Width Na me 2002 2003 2002 2003 2002 2003 2002 200 3 S1 Bagolye 6.97 7.00 48.28 49.47 14.33 14.70 12.37 12.9 3 S2 Gahnehra 9.21 9.46 86.46 96.86 14.20 14.67 11.80 12.7 0 S3 Devnagar 7.97 8.03 62.45 63.64 14.73 14.53 12.70 13.1 0 S4 Sagarifar 7.83 7.93 47.72 48.52 15.63 15.37 13.77 12.7 m 3 S5 Chopasan 6.60 6.69 45.76 47.07 16.73 16.73 14.83 14.7 i 7 S6 Doli 7.67 7.75 54.84 55.82 14.63 14.40 12.97 12.4 7 S7 Sadri 7.73 7.80 75.86 76.39 13.83 14.27 12.40 12.7 3 S8 Ranawas 7.67 7.77 63.13 63.83 13.53 13.30 11.90 11.9 7 S9 Sojat 7.13 7.23 49.13 49.87 14.10 13.93 13.03 13.0 3 S10 Santhu 6.70 6.80 37.70 38.56 13.57 14.17 11.43 12.8 3 S11 Sura 7.33 7.40 51.58 52.81 13.27 13.20 11.77 11.8 7 S12 Sharath 6.93 7.00 39.28 40.06 13.43 12.60 12.27 12.5 7 S13 Siwana 7.03 7.12 38.48 39.39 15.50 15.37 13.93 14.0 0 87 S14 Karna 7.10 7.18 49.01 48.98 13.83 13.57 12.60 12.1 0 S15 Rawatsar 6.77 6.87 44.40 45.37 15.17 14.87 14.57 13.6 0 CD (0.05) 0.985 1.136 17.648 18.433 2.129 1.560 2.252 1.24 6 Range 6.60- 6.69- 37.70- 38.56- 13.27 12.60- 11.43 11.8 - - 7- 9.21 9.46 86.46 96.86 16.73 16.73 14.83 14.7 7 Mean 7.38 7.48 52.94 54.44 14.44 14.38 12.82 12.8 9 CV (%) 8.02 9.06 20.01 20.33 8.73 6.52 10.44 5.80
Table-3 Extent of variation in fruit characteristics among the different provenances of Lehsua (Cordia myxa Roxb.).
Cod Provena Fruits/ cluster Fruit diameter Pulp : Seed ratio Fruit weight e nces (cm) (g)
88 Na 2002 2003 2002 2003 2002 2003 2002 2003 me S1 Bagolye 18.00 17.00 2.50 2.60 2.55 2.59 16.20 17.1 0 S2 Gahnehr 15.00 15.00 2.78 2.49 2.72 2.74 17.00 17.1 a 0 S3 Devnag 12.00 13.00 2.73 2.80 2.97 2.48 16.30 17.5 ar 0 S4 Sagarifa 8.67 9.00 3.07 2.93 2.95 2.65 17.50 17.4 rm 0 S5 Chopasa 15.33 16.00 2.66 2.78 3.16 2.83 17.90 17.2 ni 0 S6 Doli 17.00 17.67 3.10 3.29 2.62 2.59 17.70 15.4 0 S7 Sadri 8.00 12.33 2.42 2.32 2.46 2.22 12.17 12.2 0 S8 Ranawa 8.33 6.00 2.50 2.53 2.30 2.26 17.50 17.4 s 0 S9 Sojat 13.00 13.33 2.74 2.67 2.30 2.30 13.80 13.6 3 S10 Santhu 10.00 10.00 2.35 2.66 2.61 2.68 15.20 17.4 0 S11 Sura 14.00 14.00 2.36 2.35 2.52 2.45 13.70 13.7 0 S12 Sharath 13.67 14.00 2.39 2.55 2.56 2.60 12.60 15.5 7 S13 Siwana 12.00 12.67 2.46 2.05 2.22 2.27 12.70 10.0 S14 Karna 12.00 12.00 2.51 2.61 2.28 2.39 13.67 14.7 3 S15 Rawatsa 11.00 11.00 2.47 2.18 2.26 2.14 12.70 11.5 r 7 CD (0.05) 2.674 2.529 0.377 0.326 0.573 0.226 1.966 2.56 1 Range 8.00- 6.00- 2.35- 2.05- 2.22- 2.14- 12.17- 10.0- 89 18.00 17.67 3.10 3.29 3.16 2.83 17.90 17.5 0 Mean 12.53 12.87 2.60 2.59 2.57 2.48 15.11 15.2 0 CV (%) 12.81 11.80 8.72 7.57 13.42 5.47 7.82 10.1 3
90
5. DISCUSSION
The present study was undertaken with the objectives to understand the nature and magnitude of variability and association amongst various traits. Many studies on provenance and seed source have been made or are currently underway (Wright and Baldwin, 1957; Wells and Wakeley, 1970; Lacaze, 1978; Pant, 1996) in determining the best species and source to be used for most of the species. The source information available leading to the reliability and availability of the desired source of seed, needs to be determined. According to Anderson (1966)- a reliable provenance would be one producing a descent crop with 90 per cent probability rather than outstanding crop of 50 per cent in the time, and an available provenance is one from which seeds are readily and economically available as required”. Natural variation occurs as a product of evolution and serve as a raw material which is renewable and utilizable involving basic tools such as selection and manipulation of the variability in the biological population. The results of the present investigations entitled “Natural variation in Lehsua (Cordia myxa Roxb) in Rajasthan” have bee discussed under the following headings. : 5.1 EVALUATION OF PROVENANCES 5.1.1. Variation in morphological characteristics 5.1.2 Variation in fruit characteristics
91 5.1.3 Variation in fruit quality characteristics 5.2 VARIABILITY ESTIMATES AND GENETIC PARAMETERS 5.3 CORRELATION STUDIES 5.4 PATH COEFFICIENT STUDIES 5.5 GENETIC DIVERGENCE
5.1 EVALUATION OF PROVENANCES
5.1.1 Variation in morphological characteristics (natural population)
Differences in natural stand for tree height ranged between 6.64-9.34m with mean value of 7.43m (Table-5). These results are in line with the findings of Verma and Vashishtha (1993) who reported that the Cordia myxa growing naturally under Rajasthan conditions attained the average height of 7.3m. The range in mean values, an indicator of variability, was wider for plant spread, leaf length and leaf width (Table-5).
5.1.2 Variation in fruit characteristics
The results indicate that the fruit size was the highest in S6 (Doli) provenance with mean fruit size of 3.20cm.
However, highest fruit weight was recorded for S5 (Chopasani) provenance. The increase in fruit size might be due to the enhanced synthesis of carbohydrates and water uptake and their movement into the fruits (Miniraj and Shanmugavelu, 1987). The increase in fruit size might also been due to an enlargement of the cells in the fleshy part of the fruits as have been observed by Tukey and Young (1939). Hendrickson and Veihmeyer (1934) reported that the prune fruits affected by
92 lack of available moisture during the fruit growing season, remained small even with subsequent irrigation. Thus, the lesser fruit weight under low soil moisture condition was the result of small fruit size due to lack of optimum soil moisture during the period when the fruits were increasing in size. Further, increase in fruit size and weight with the increase in soil moisture content may be attributed to greater vegetative growth under wettest conditions. Various workers have observed an increase in fruit size as a result of increasing level of irrigation in pome and stone fruit trees (Nasharty and Ibrahim, 1961; Werenfels, 1964; Kumashiro and Fateishi, 1967). The weight of individual fruit ranged between 11.38-17.55g with mean value of 15.16g (Table-6). Significant variation was recorded for fruits per cluster. Fruits per cluster ranged between 7.17-17.50 with mean value of 12.70 (Table-6). High pulp : seed ratio is also an indicator of good quality fruit. Variation for pulp : seed ratio was found to be significant among provenances. It ranged between 2.20-2.99 with mean value of 2.52.
5.1.3 Variation in fruit quality characteristics
The variation in the fruit quality characteristics were well reflected in the form of significant variation among the provenances. Increase in fruit T.S.S might be associated with increased translocation of organic assimilates from leaves to hormonal stimulation (Hansen, 1967; Kriedemann, 1968). Higher T.S.S. in present investigation could be attributed to the enhanced photosynthetic efficiency of the leaves and possible increase in the translocation of assimilates (Jindal and Dwivedi, 1984; Barua 1990), apricot (Chander, 1987) and with cytozyme in Kinnow (Daulta et al., 1986). The highest T.S.S. was recorded for Chopasani provenance (Table-7). It ranged between 5.78-7.58 with mean value of 6.71. There was significant variation for per cent acidity content among different provenances though it ranged between 0.08-0.11 with mean value of 0.096. Various factors like hormonal 93 stimulation of translocation of assimilates (Booth et al., 1962; Davies and Wareing, 1965) alteration of skins may contribute to depression or enhancement of acid content in fruits.
5.2 VARIABILITY ESTIMATES AND GENETIC PARAMETERS
Variation refers to the observable differences in individuals for a particular trait. These differences may be partly due to genotypic factor and partly due to environmental effects. The combined reflection of both these factor is the phenotypic effect (Jain, 1982). For the proper utilization of observed variation in a species, it is pre-requisite to know the extent of variation and also that whether it is due to the genetic or the environmental factors. Hence, information on variation for the desirable characters and their correlation is vital for any breeding programme (Johnson et al., 1955). Therefore, a species exhibiting a wide range of variability (in terms of wide range of parameters, value and high standard deviation, variance, coefficient of variation and genotypic coefficient of variation) offer ample scope for undertaking screening for the desired traits. The observed variation in a character is partly composed of genetic (heritable) variation and partly of non heritable. The proportion of total variation which is due to genetic differences is termed as the heritability in broad sense (Lush, 1937). Heritability provides a measure of genetic variation upon which all the possibilities of changing the genetic composition of the species depend. Genetic advance as percentage of mean gives the relative measurement of change produced by selection in mean genetic level of the species. This is the mean genotypic value for a particular trait of the selected individuals in relation to the entire population. The genetic coefficient of variation indicates the range and magnitude of genetic variability existing between the characters, whereas the observed variation in a group of individual is known as phenotypic coefficient of variation. 94 In the present investigation, the results obtained for the different characters with regard to the variability parameters indicates that values have a wide range depicting the presence of good amount of variation (Table-5). The plant spread recorded the highest value of 20.18 per cent for coefficient of variation (Table-5) while leaf length recorded the lowest value of 7.73 per cent for coefficient of variation (pooled basis). Fruit characteristics also showed wide range of variations. Fruits per cluster ranged between 7.17-17.50 with 12.30 per cent coefficient of variation (Table-6). Fruit diameter and pulp : seed ratio ranged between 2.26-3.20 and 2.20-2.99, respectively, with 8.17 and 10.37 per cent of coefficient variation. Fruit weight also recorded the widest range of 11.38- 17.55g with 9.05 per cent of coefficient of variation. Fruit quality parameters viz; T.S.S. and acidity gave 8.41 and 8.59 per cent of coefficient variation, respectively. Plant spread showed high value of genotypic variance, heritability and genetic advance as percentage of mean. This indicates that this traits is under strong genetic control. The PCV and GCV (which are free from the units of measurement) were highest for plant spread followed by fruits per cluster and fruit weight . Besides information on PCV and GCV, heritability is useful in predicting the expected progress to be achieved through selection (Burton and Devane, 1953 and Johnson et al., 1955). Those characters which have high heritability followed with high genetic advance as percentage of mean showed that judicious selection can be effective directly for the improvement of the species by evaluating these growth parameters. Johnson et al., (1955) observed that high genetic advance as percentage of mean is usually more useful than the heritability values alone in predicting the resultant effect from selecting the best provenance. Therefore, high heritability estimates does not necessarily mean an increased genetic advance. Fruits per cluster recorded the highest value for heritability with high genetic advance as percentage of mean followed by fruit weight. This indicates that there is a greater amount of variability in the population for these characters. 95 Though high heritability (Broad sense) was observed for all the characters but some characters possessed high genetic advance as percentage of mean, whereas, other have comparatively less. High heritability estimates coupled with high genetic advance as percentage of mean recorded in the present investigation indicates that the improvement in these traits can be made through direct selection. These findings are in line with that reported by Pandey and Bist (1955). The traits having lower range suggested limited variability in the population and need to generate more variability for improvement.
5.3 CORRELATION COEFFICIENT
Success of any breeding programme depends upon the efficiency of the selection. Selection can not be applied on the basis of single character because most of the characters are polygenic in nature and are influenced by each other. Correlation coefficients among different characters including fruit weight were calculated at phenotypic as well as genotypic level (Table-20). The knowledge of character association is imperative as it facilitates quick assessment of high yield provenances in the selection programme in addition to the available information on variability and heritability existing within the material. The total correlation is the result of interaction between provenances and environments so the true association could be known only through genotypic correlation, which eliminates the environmental influences. Hence, the study of genotypic correlations are needed to measure the association between fruit weight and its contributing characters at genotypic level which helps in identification of the important characters to be considered as a selection criterion in a breeding programme. In the present investigation, generally the genotypic correlation coefficients were higher than the corresponding phenotypic ones indicating the inherent association, among the various traits (Table-20). From these associations it appears that higher fruit weight can be obtained by increasing the fruit size and pulp : seed ratio and also reducing by leaf width. 96 Significant correlations of the fruit characters suggest the scope of indirect selection for the further improvement. Positive association among fruit weight, fruit size and pulp : stone ratio in ber have been reported earlier (Bisla and Daulta, 1987; Prajapati et al. 1996; Gupta and Mehta, 2000) and these results are in agreement with the present study. Significant positive association of weight and size of fruit in jamun has been reported by Daware et al (1985). Positive association of leaf width with leaf length and T.S.S.; plant height with plant spread, fruits per cluster, fruits size, pulp : seed ratio and acidity; plant spread with fruits per cluster, fruit size, pulp : seed ratio and acidity ; fruits per cluster with pulp : seed ratio and T.S.S.; fruit size with pulp : seed ratio and acidity; pulp : seed ratio with T.S.S. and T.S.S. with leaf length have been recorded(Table-20). Significant negative correlation of fruit weight with leaf width; leaf width with acidity; leaf length with acidity and acidity with T.S.S. have been observed.
5.4 PATH COEFFICIENT
The correlation analysis provides an information, which is incomplete in the sense that it does not throw light on the underlying causes that are operative for the various interrelationships. Path coefficient analysis, which is simply a standardized partial regression analysis developed by Wright (1921), is helpful in partitioning the correlation coefficient into direct and indirect effects. Hence, the study of path coefficient analysis was included in the present investigation to obtain the information on the direct and indirect effects of different attributes on fruit weight. Since, the results of path coefficient analysis based on genotypic correlation was not different from those obtained from phenotypic correlation and hence, the results based on genotypic and phenotypic correlation coefficient are discussed here. Among the attributes, pulp : seed ratio had the maximum positive direct effects at genotypic level on fruit weight followed by leaf width and fruit size. Magnitude of the correlation coefficients between a causal factor and the effect is 97 almost equal to its direct effect. Hence, correlations explain the true interrelationship and suggest that a direct selection through these traits will be effective. Direct positive effects of fruit weight, stone weight and pulp : stone ratio (Bisla and Daulta, 1987) in ber have been reported and the results of the present study are in accordance. Direct positive effects on fruit weight of fruit size, stone weight and pulp percentage in jamun was reported by Daware et al. (1985), these are supported by the observations made in the present study. At phenotypic level, fruit size had maximum positive direct effect followed by T.S.S. and acidity. Plant height, fruits per cluster and pulp : seed ratio had positive direct effect whereas, leaf width, leaf length and plant spread had negative direct effect but the values were very low. The high magnitude of residual factor at phenotypic level for the morphological, fruit and fruit quality attributes, indicated the limitation of characters included in the present investigation which need to be supplemented by more number of these traits so as to describe the whole range of variation.
5.5 GENETIC DIVERGENCE STUDIES
The assessment of genetic divergence between the provenances using Mahalanobis generalized distance (D2) analysis and then the grouping of these genotypes in different clusters showed that the selected genotypes were highly divergent among each other. In experiment I (2002), the selected genotypes were grouped into four clusters. The maximum number of genotypes (11) were included in cluster I (S1, S6, S5¸S11, S12, S3, S2, S13, S10 and S15). Two genotypes in cluster II (S4 and S8) while single genotype in cluster III (S7) and cluster IV (S14). In experiment II (2003), the selected genotypes were grouped into three clusters. The maximum number of genotypes
(13) were included in cluster I (S1, S6, S3¸S5, S12, S11, S9, S2, S4, S10, S14, S7 and S15). Whereas single genotype was included in cluster II (S8) and cluster III (S13). However, on pooled data basis the selected genotypes were grouped into six clusters. The maximum number of genotypes (7) were included in cluster I (S1, S6, S5¸S11, S3, S12, and S9); two genotypes in cluster II (S4 98 and S10); two genotypes in cluster III (S7 and S15), two in cluster IV (S13 and S14); one genotype in cluster V (S8) and one in cluster VI (S2). Provenances falling in different clusters are also sharing by and large geographical continuity. However, considerable divergence is shown by some of the provenances since these genotypes were selected from the different locality of Rajasthan; they showed varied differences among each other which may be attributed to the edaphic and\or climatic conditions. Besides this, the genetic constitution of this species must be the cause of huge variation in these traits. Therefore, the variation observed may be due to the different genetic architecture as a result of breeding system, level of heterogeneity and adaptation to diverse environmental conditions. The pattern of group constellations proved that geographical diversity need not necessarily be related to genetic diversity. This was in line with the results obtained by Shwe et al. (1972) and Ayyamperumal (1991) in soybean; Suthamathi and Dorairaj (1994) in Napier grass; Pant (1996) in wild pomegranate and Ram Rao (2003) in mulberry . Genetic drift and exchange of breeding materials might be responsible for such grouping as reported in literature (Singh et al, 1991; Shiv kumar and Singh,1997; Narendra kumar,1997; Rajan et al, 1997 and Shukla and Singh, 2002). This means that geographic diversity though important, may not be the only factor in determining genetic divergence. Genetic diversity is the outcome of several factors, including geographical diversification. Therefore, selection of genotypes for hybridization should be based on genetic diversity rather than geographical diversity (Singh, 1993b). The clustering of genotypes from different locality into one cluster indicated the genetic similarity among the germplasm coming from different geographic region, as was observed by Jaylal (1994) in Soybean; Suthamathi and Dorairaj (1994) in Pennisetum purpureum (Napier grass). This may also be due to the fact that the unidirectional selection practiced for a particular trait in several places produced similar phenotypes which were aggregated in one cluster irrespective of their distant geographic origin (Singh and Bains, 1968).
99 On the other hand, many genotypes originating from one region were scattered over different clusters. Such genetic diversity among the genotypes of common geographic origin could be due to the factors like heterogeneity, genetic architecture of the populations, past history of selection, developmental traits and degree of general combining ability (Murthy and Arunachalam, 1966). On the basis of the present investigations, it can be suggested that though geographic diversity may not necessarily be an index of genetic diversity, due attention should be paid to geographic diversity if sufficient genetic diversity has to be accumulated in the germplasm (Ram and Panwar, 1970). The generalized intra and inter cluster distances in experiment I one were 5.13 and 5.61 respectively for cluster I and II. The generalized inter cluster distance were 7.16 (between I and II), 8.24 (between I and III), 6.54 (between I and IV), 7.62 (between II and III) and 8.28 (between III and IV) (Table 25). The relative divergence of one cluster from other cluster (inter cluster distance) indicated high order of divergence between cluster III and IV followed by cluster I and III and II and IV. In experiment II, the maximum and minimum generalized inter cluster distances were 15.11 (between cluster II and III) and 9.06 between cluster I and III, respectively. This signifies that the genotypes within each cluster were genetically related since all the clusters had low (µ 50) inter cluster distance. The relative divergence of each cluster from other clusters (inter distance) indicated high order of divergence between cluster II and III followed by cluster I and II, and cluster I and III (Table 30). On pooled data basis, the generalized intra cluster distance was maximum in cluster III (5.27) while the minimum was in cluster I (3.91). Maximum and minimum inter cluster distances were recorded between cluster III and VI, II and III (6.70) and cluster II and VI (2.96), respectively. In addition to the general features of variation and divergence, this study also provided information on the characters that contributed maximum to the total divergence among genotypes. The most important traits causing maximum genetic 100 divergence were fruit weight, fruits per cluster and leaf length. While the minimum was contributed by leaf width, plant spread, pulp : seed ratio and acidity. In second experiment (2003), the important traits causing maximum genetic divergence was fruit weight followed by fruit per cluster, leaf width, T.S.S., fruit diameter, whereas, acidity and plant spread contributed minimum towards genetic divergence. On pooled data basis, fruit weight contributed maximum towards genetic divergence followed by fruits per cluster and plant height. On the other hand pulp : seed ratio and acidity contributed minimum towards genetic divergence. The characters contributing maximum to D2 values have given more emphasis for the purpose of fixing priority of parents in hybridization programme (Singh, 1993b). Low variability for the traits in such a wide variety of genotypes may also suggest high degree of constancy and heritability of these traits. In a breeding programme aimed at crop improvement, the choice of parents is quite important and only component characters of yield should be taken into account for selecting genetically divergent parents. The hybridization among genetically diverse parental genotypes for specific trait may be useful in bringing the new gene pool in population and expanding the range of adaptation. The divergent genotypes may be utilized as donor parents for enhancing the yield of
’ other genotypes grouped in a cluster in F1 s and can be fixed by selecting transgressive segregants followed by continued selection in advance generations which may lead to development of a high yielding varieties with desired component characters.
101
6. SUMMARY AND CONCLUSION
Lehsua or Gonda or Indian cherry (Cordia myxa Roxb.) is a minor fruit, belongs to family Boraginaceae. The plant is medium sized tree, can tolerate drought and moderate shade. Yet, it is not grown in orchards and grows in wild state in wastelands along farm boundaries or on road side. As compared to other tree species, less efforts have been made for the genetic improvement of this species. The present investigation entitled, “Natural variation in Lehsua (Cordia myxa Roxb.) in Rajasthan” was carried out in the Department of Horticulture, S.K.N. college of Agriculture, Jobner (Jaipur) , Rajasthan during 2002 and 2003. A survey was undertaken in fifteen different provenances from five districts of Rajasthan viz., Ajmer, Jodhpur, Pali, Jalore and Barmer to study the extent and pattern of variation with respect to natural stand and fruit characteristics. The observations recorded for the characters were utilized for calculating variability estimates, genetic divergence, correlation and path coefficient among various characters. From each provenance selected for the study, three trees were selected. From each tree, twenty fruits were collected depending on their direction (viz, five each from east, west, north and south). Before extraction of seed from fruits, the various fruit characters such as fruits per cluster, fruit size and fruit weight were studied for each tree selected in each
102 provenance. Fruits were also analyzed for fruit quality such as T.S.S. and acidity. The salient features of the present investigation are summarized under the following headings.
6.1 EVALUATION Of DIFFERENT LEHSUA PROVENANCES FOR THE SELECTION OF PLUS TREE IN RAJASTHAN
6.1.1. Variation in Morphological Characters
On the basis of variation present in natural population, Gahnehra provenance recorded the highest value for plant height and plant spread. Maximum leaf length and leaf width was recorded from Chopasani provenance.
6.1.2. Variation in Fruit Characteristics
Bagolye provenance recorded the highest fruits per cluster followed by Doli. Highest fruit diameter was recorded from Doli provenance, followed by Sagari farm. Chopasani provenance gave the highest pulp: seed ratio followed by Sagari farm. Maximum fruit weight was recorded from Chopasani provenance followed by Sagari farm.
6.1.3 Variation in Fruit Quality Characteristics
Highest T.S.S. was recorded from Chopasani provenance, while highest acidity was recorded from Gahnehra, Sagari farm and Ranawas.
6.2 VARIABILITY ESTIMATES AND GENETIC STUDIES
Most of the characters especially, fruits per cluster, fruit weight, plant spread, fruit diameter and plant height had high heritability and genetic advance as percentage of mean indicating these to be more under genetic control. Which in turn
103 implied that the large extent of variation observed in them can be exploited for genetic improvement of this species. The potential exists for improvement because of great heterogeneity.
6.3 CORRELATION STUDIES
Possibility of indirect selection is also there as high significant positive correlation exists among characters; at genotypic level fruit weight had significant positive correlation coefficient with pulp: seed ratio and fruit size.
6.4 PATH COEFFICIENT STUDIES
The information on the direct and indirect effects of different attributes on fruit weight indicated that the pulp: seed ratio had the maximum positive direct effect on fruit weight followed by leaf width and fruit size.
6.5 GENETIC DIVERGENE STUDIES
Selection of genotypes should be based on genetic diversity as geographical diversity is not the only factor in determining genetic divergence. Thus, hybridization between more diverse genotypes can produce high heterotic vigour. Therefore, in any possible hybridization programme parents should be selected from diverse sources. In present study, the
S2 (Gahnehra), S7 (Sadri) and S15 (Rawatsar) provenances are found to be more divergent and thus there is a great scope to select the desirable diverse plant material for further use in breeding programme for improvement in Cordia myxa.
CONCLUSION
Considering the overall performance of fifteen different provenances, the Chopasani and Gahnehra provenances were found to be promising especially with regard to fruit size and fruit quality parameters. Hence, direct selection for desired plant type can be made from these provenances. The genetic divergence study shows that the provenances like S2 104 (Gahnehra), S7 (Sadri) and S15 (Rawatsar) were more divergent and thus, there is great scope to select the desirable diverse plant material for further use in breeding programme for improvement in Cordia myxa.
105 Appendix- 1 Analysis of variance for morphological, fruit and fruit quality characteristics in Lehsua (Cordia myxa Roxb.) during 2002. Source of Mean Sum of Squares variation Df Plant Plant Leaf Leaf Fruits per Fruit Pulp : Fruit weight T.S.S. Acidity height spread length width cluster diameter seed ratio Replication 2 0.241 70.135 7.801 3.190 0.267 0.002 0.085 3.744 0.562 0.0002 Treatme 14 1.340* 574.187* 7.619* 5.733* 27.895* 0.172* 0.243* 13.731* 0.907* 0.0003* nt Error 28 0.350 112.257 1.634 1.828 2.576 0.052 0.119 1.395 0.330 0.0001 * Significant at þ = 0.05
Appendix- 2 Analysis of variance for morphological, fruit and fruit quality characteristics in Lehsua (Cordia myxa Roxb.) during 2003. Source of Mean Sum of Squares variation Df Plant Plant Leaf Leaf Fruits per Fruit Pulp : Fruit weight T.S.S. Acidity height spread length width cluster diameter seed ratio Replication 2 0.117 150.729 0.278 0.486 4.067 0.199 0.020 2.483 0.779 0.0002 Treatme 14 2.537* 726.753* 3.124* 1.762* 28.324* 0.326* 0.132* 18.254* 1.080* 0.0006* nt Error 28 0.466 122.487 0.879 0.560 2.305 0.038 0.018 2.369 0.307 0.0004 * Significant at þ = 0.05
Appendix- 3 Analysis of variance for morphological, fruit and fruit quality characteristics in Lehsua (Cordia myxa Roxb.) Pooled basis. Mean Sum of Squares Source of Df Plant Plant spread Leaf Leaf Fruits per Fruit Pulp : Fruit weight T.S.S. Acidity variation height length width cluster diameter Seed ratio Location (L) 1 0.568 50.875 1.467 0.089 2.500 0.004 0.170 0.148 0.028 0.000004 Replication 2 0.319 212.953 5.551 0.884 1.233 0.118 0.087 2.862 1.325 0.00008 (R) LXR 2 0.0393 7.852 2.568 2.791 3.100 8.367 0.016 3.365 0.016 0.000008
106 Treatme 14 3.734* 1291.677* 9.666* 6.403* 53.409* 0.428* 0.329* 28.587* 1.923* 0.0004* nt (T) LXT 14 0.139 9.256 1.077 1.091 2.809 0.069 0.045 3.397 0.064 0.00007 Error 56 0.408 117.373 1.256 1.194 2.440 0.045 0.068 1.882 0.319 0.00006 * Significant at þ = 0.05
107
Natural variation in Lehsua (Cordia myxa Roxb.) in Rajasthan
Researcher Major Advisor Banwari Lal Nagar Dr. M. S. Fageria
ABSTRACT
A survey experiment was conducted under Department of Horticulture, S.K.N. College of Agriculture, Jobner during 2001-02 and 2002-03 to study the natural variation in lehsua (Cordia myxa Roxb.) in Rajasthan. A survey was undertaken in fifteen different provenances from five districts of Rajasthan namely Ajmer, Jodhpur, Pali, Jalore and Barmer. Here, fifteen different provenances were taken as treatments and from each site, three trees were taken as replication and evaluated under randomized block design. Observations were recorded on morphological (plant height, plant spread, leaf length, leaf width), fruit (fruits per cluster, fruit diameter, pulp: seed ratio, fruit weight) and fruit quality (T.S.S. and acidity) characteristics. Provenances showed a wide range of variability for plant height, plant spread, leaf length, leaf width, fruit weight, fruits per cluster, fruit diameter, pulp: seed ratio and T.S.S. The highest values for plant height and plant spread were recorded from Gahhehra provenance. Maximum leaf length, leaf width, fruit weight, pulp seed ratio and T.S.S. were recorded from Chopasani provenance while highest fruit diameter and fruits per cluster recorded from Doli provenances. The results further, revealed that heritability and genetic advance were high for most of the characters especially for fruits per cluster, fruit weight, plant spread, fruit diameter and plant height indicating these to be more under genetic control. High significant positive correlation coefficient of fruit weight was noticed with pulp: seed ratio and fruit size. The significant and negative correlation was observed between T.S.S. and acidity. Path coefficient analysis revealed that pulp: seed ratio had highest positive direct effect on fruit weight followed by leaf width and fruit size. It appears that selection of genotypes should be based on genetic diversity as geographical diversity is not the only factor in determining genetic divergence. Thus, hybridization between more diverse genotypes can produce with higher heterotic vigour. Therefore, in any possible hybridization programme parents should be selected from diverse sources. In the present study, the S2 (Gahnehra), S7 (Sadri) and S15 (Rawatsar) provenances were found to be more divergent and thus great scope is existed to select the desirable diverse plant material for further use in breeding programme for improvement in Cordia myxa.
Table-20 Genotypic (above diagonal) and phenotypic (below diagonal) correlation coefficient between various attributes and fruit weight in Lehsua (pooled basis)
Character Plant Plant Fruits/ Fruit size Pulp : seed T.S.S. Acidity Leaf Leaf Fruit height spread cluster ratio length width weight Plant - 0.886** 0.021 0.324 0.218 -0.252 0.398 -0.006 -0.268 0.348 height Plant 0.815** - 0.010 0.232 0.091 -0.431 0.500 -0.104 -0.319 0.243 spread Fruits/ -0.20 0.026 - -0.378 0.441 0.437 -0.451 -0.111 -0.124 0.140 cluster Fruit size 0.179 0.194 -0.190 - 0.322 -0.127 0.291 -0.062 -0.291 0.768** Pulp : seed 0.116 0.121 0.235 0.234 - 0.608* -0.071 -0.210 -0.490 0.843** ratio T.S.S. -0.176 -0.187 0.287 -0.142 0.428 - -0.836** 0.257 0.192 0.335 Acidity 0.233 0.231 -0.258 0.123 -0.103 -0.550* - -0.523* -0.598* 0.152 Leaf length 0.048 0.008 -0.123 -0.031 -0.119 0.128 -0.314 - 0.949** -0.154 Leaf width 0.110 -0.163 -0. 066 -0.151 -0.282 0.093 -0.384 0.662 - -0.531* Fruit 0.157 0.120 0.097 0.541* 0.386 0.246 0.056 -0.136 -0.230 - weight * Significant at þ = 0.05 ** Significant at þ = 0.01
Table-21 Estimates of direct and indirect effects at genotypic (G) and phenotypic (P) levels of various characters on fruit weight in Lehsua (pooled basis) Character Plant Plant Fruits/ Fruit size Pulp : seed T.S.S. Acidity Leaf Leaf Correlation with height spread cluster ratio length width fruit weight Plant height G 0.040 0.124 -0.003 0.169 0.279 0.122 -0.112 0.005 -0.277 0.348 P 0.166 -0.091 -0.002 0.102 0.006 -0.070 0.044 -0.003 0.004 0.157 Plant spread G 0.035 0.140 -0.001 0.121 0.120 0.209 -0.141 0.088 -0.329 0.243 P 0.136 -0.111 0.003 0.111 0.006 -0.074 0.044 -0.001 0.007 0.120 Fruits per G 0.001 0.001 -0.125 -0.197 0.578 -0.212 0.127 0.094 -0.128 0.140 cluster P -0.003 -0.003 0.124 -0.108 0.011 0.114 -0.049 0.008 0.003 0.097 Fruit size G 0.013 0.033 0.047 0.522 0.423 0.062 -0.082 0.052 -0.301 0.768** P 0.030 -0.022 -0.024 0.569 0.011 -0.056 0.023 0.002 0.006 0.541* Pulp : seed G 0.008 0.013 -0.055 0.168 1.311 -0.295 0.020 0.178 -0.505 0.843** ratio P 0.019 -0.013 0.029 0.133 0.049 0.169 -0.020 0.008 0.011 0.386 T.S.S. G -0.010 -0.061 -0.054 -0.066 0.797 -0.485 0.235 -0.218 0.198 0.335 P -0.029 0.021 0.036 -0.081 0.021 0.396 -0.105 -0.009 -0.004 0.246 Acidity G 0.016 0.070 0.056 0.152 -0.093 0.406 -0.281 0.433 -0.617 0.152 P 0.039 -0.026 -0.032 0.070 -0.005 -0.218 0.191 0.022 0.015 0.056 Leaf length G 0.000 0.015 0.014 -0.032 -0.275 -0.125 0.147 -0.847 0.980 -0.154 P 0.008 -0.001 -0.015 -0.017 -0.006 0.050 -0.060 -0.069 -0.027 -0.136 Leaf width G -0.011 -0.045 0.015 -0.152 -0.642 0.093 0.168 -0.804 1.032 -0.531* P -0.018 0.018 -0.008 -0.086 -0.014 0.037 -0.073 -0.046 -0.040 -0.230 *Significant at þ = 0.05 and ** Significant at þ = 0.01 Diagonal values represent direct effects Residual effect : Phenotypic = 0.5219, Genotypic = 0.0860
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