INHERITANCE OF YIELD, DRY MATTER AND Β-CAROTENE CONTENTS IN FULL-SIB FAMILIES OF ORANGE FLESHED SWEET POTATO GENOTYPES

0 Review(s)

Product Category: Projects

Product Code: 00009283

No of Pages: 229

No of Chapters: 1-5

File Format: Microsoft Word

Price :

₦10000

Add to Cart
Buy Now

Report This Item

ABSTRACT

This study aimed at assessing the inheritance of important agronomic traits in full-sib families of orange-fleshed sweetpotato (OFSP) was conducted at National Root Crops Research Institute, Umudike, Abia State and at, Igbariam, Anambra State. The experiment comprised three phases viz; field evaluation, crosses in crossing block and progeny evaluation. The field evaluation was conducted to assess the magnitude of variability within 47 genotypes and to estimate the yield and nutritional performance which was used to establish a crossing block. The results from root yield at Igbariam showed that K 003 produced the highest root yield (32.60t/ha), followed by Umuspo/3(28.89t/ha), A 079b (26.22t/ha) and Umuspo/1(24.45t/ha). In Umudike, Umuspo/3 produced the highest root yield (29.81t/ha), followed by Delvia (27.88t/ha), Umuspo/1(27.33t/ha) and A 097a (27.19t/ha). With respect to location, Umudike recorded highest root yield (10.09t/ha), compared to that of Igbariam(9.28t/ha). In Igbariam the highest beta carotene, which were 12.35, 12.34, 11.76 and 11.76mg/100g FW were recorded from A 089, A 010a, B 060 and Ex-Oyunga respectively. The results obtained from Umudike showed that highest beta carotene content, which were 11.03 and 11.02 mg/100g FW were recorded from A 080 and A 010a respectively. The result also revealed that in Igbariam, genotype with the highest dry matter content were Delvia(52.16%), A 099 (52.05%), Malawi II (50.76) and Amelia (49.82%). The least dry matter content was recorded from Umuspo/3(17.83). With respect to location, highest dry matter content of 40.23% was obtained in Igbriam compared to Umudike(34.38%). The cluster means showed that cluster I comprised of high yielding genotypes with very high dry matter content, lowest beta carotene content and lowest vitamin A content. The ranking of the 47 OFSP genotypes showed that Delvia had the best overall performance with a Rank Summation Index (RSI) value of 49. The correlation coefficients (r) indicated that root yield had highly positive and significant correlation with total root weight per plant(r = 0.696**, p = 0.01) and total number of root per plant(r = 0.770**, p = 0.01) and highly significant but negatively correlated with pest incidence(r = -0.394**, p = 0.01). Beta carotene had significant and negative correlation with dry matter(r = -0.503**, p = 0.01) and starch (r = -0.364**, p = 0.05). Path coefficient analysis using root yield as dependent variable and others as independent variables showed the highest positive direct effect on root yield (RY) were exhibited by number of roots per plant(NRPP)(0.65) and root weight per plant(RWPP) (0.31). The progeny evaluation was conducted in RCBD involving 59 genotypes (three testers, fourteen lines and forty two crosses) of OFSP. From the results, phenotypic coefficients of variation was higher in magnitude than the genotypic coefficients of variation for all the characters. The magnitude of additive variance (σ2A) was consistently larger than that of dominance variance (σ2D) for all traits studied. All the characters studied had high broad sense heritability (>60%). Lines L5 (A 106 -1) and L13(Solo Abuja -1) were best general combiner for root yield per hectare. Line L7 (A 141 1), L3 (A 089 -1) and L1(A 079b -1) were best general combiners for increased beta carotene content whereas, line, L12(Malinda -2), L11(Malinda -1) and L6(A 106 -2) were best general combiner for dry matter content.

TABLES OF CONTENTS

Title page i

Declaration ii

Certification iii

Dedication iv

Acknowledgement v

Table of contents vii

List of tables xiii

List of figures xvi

Abstract xvii

CHAPTER 1 INTRODUCTION 1

1.1 Sweetpotato 1

1.2 The Aim of the Present Study 4

CHAPTER 2 LITERATURE REVIEW 5

2.1 Origin and Distribution of Sweetpotato 5

2.2 Origin of Sweetpotato 5

2.3 Distribution of Sweetpotato 6

2.4 Taxonomy of Sweetpotato 7

2.5 Botany and Morphology of sweetpotato 8

2.6 Growth Habit 9

2.7 Root System 9

2.8 Stem 9

2.9 Leaves 10

2.10 Flowers 10

2. 10.1 Flowering in sweetpotato 11

2.11 Fruit and Seeds 12

2.12 Storage Root 12

2.13 Economic Importance of Sweetpotato 13

2.13.1 Non-food Uses of sweetpotato 14

2.14 Attributes of Preferred Genotypes/Varieties 14

2.15 Agronomic requirements 16

2.15.1 Post-Harvest Handling of sweetpotato 16

2.15.2 Sorting and grading techniques: 17

2.15.3 Packaging and Transportation 17

2.15.4 Storage 17

2.15.5 Processors 17

2.16 Production Constraints of Sweetpotato 18

2.15.1 Biotic and abiotic constraints 18

2.15.2 Inadequate storage facilities 18

2.15.3 High cost of production inputs 18

2.15.4 Sweetpotato pests 18

2.15.5 Sweetpotato diseases and viruses 19

2.15.6 Poor breeding progress for sweetpotato 20

2.15.7 Beta carotene 21

2.16 Dry Matter Content of Orange Fleshed Sweetpotato (OFSP) 22

2.16.1 Factors affecting dry matter levels 24

2.16.2 Date of planting 24

2.16.3 Soil type 24

2.16.4 Fertilizers 25

2.16.5 Season 25

2.16.6 Harvest 26

2.16.7 Storage 26

2.16.8 Resistance to Losses During Storage 26

2.16.9 Breeding for high dry matter content 27

2.16.10 Selection for high dry matter content 27

2.17 Mendelian Genetics 27

2.18 Quantitative Genetics and Breeding 28

2.19 Heterosis 28

2.20 Incompatibility in Sweetpotato 29

2.18.1 The significance of incompatibility on sweetpotato improvement 30

2.18.2 The kinds and system of incompatibilities in sweetpotato 31

2.18.3 Methods to overcome incompatibilities 33

2.18.4 Narrow sense heritability (h2) 34

2.18.5 Negative and zero heritability and its causes 34

2.21 Estimating GCA and SCA 35

2.22 Major Mating Designs in Sweetpotato Breeding 36

2.22.1 The polycross mating design 36

2.22.2 North Carolina mating designs 37

2.22.3 Top cross design 38

2.22.4 Line x tester design 39

2.22.5 Diallel cross 40

2.23 Path Analysis 41

CHAPTER 3 MATERIALS AND METHODS 42

3.1 Experimental Site and Planting Materials 42

3.2 Experimental Design and Phases of The Experiment 44

3.2.1 Phase I (Preliminary field evaluation) 44

3.2.2 Phase II (Establishment of Crossing block and hybridization) 44

3.2.3 Hybridization procedure 45

3.2.4 Phase III (Final field evaluation) 46

3.3 Assessment of Sweetpotato Virus Disease Severity scoring 46

3.4 Flowering Synchronization/Induction 46

3.4.1 Short day treatment 49

3.4.2 Use of trellises to induce flowering 49

3.5 Data Collection 49

3.5.1 (A) Agronomic data 49

3.5.2 (B) Culinary quality of sweetpotato storage roots 50

3.6 Statistical Analysis 51

3.6.1 Estimation of genetic components 52

3.6.2 Combining ability analysis 56

CHAPTER 4 RESULTS AND DISCUSSION 57

4.1 Soil And Agro-Meteorological Data 57

4.2 Vine Length 60

4.3 Internode Length 62

4.4 Number of Branches 64

4.5 Pest Incidence 66

4.6 Virus Incidence 68

4.7 Days to 50% Flowering, Root Length and Root Girth 70

4.8 Number of Marketable and Unmarketable Roots Per Plant 72

4.9 Weight of Marketable and Un-Marketable Roots Per Plant 74

4.10 Yield of OFSP Genotypes Evaluated in Umudike and Igbariam In 2015 Planting 76

4.11 Beta Carotene and Vitamin A Content 78

4.12 Dry Matter and Starch 80

4.13 Cluster Analyses 82

4.14 Rank Summation Index 82

4.15 Correlation Analysis 83

4.16 Path Coefficient Analysis 83

4.17 Analysis of Variance for Line x Tester 84

4.17.1 Estimates of general combining ability effects 94

4.17.2 Number of branches at 18WAP 94

4.17.3 Days to 50% flowering 94 4.17.4 Root length 95

4.17.5 Root girth 95

4.17.6 Pest infestation and virus incidence 95

4.17.7 Yield and yield related components 95

4.18 General Combining Ability (GCA) For Culinary Qualities 96

4.20 Estimation of Specific Combining Ability (SCA) 100

4.21 Mean Agronomic Performance for Different Characters 103

4.21.1 Vine length 103

4.21.2 Internode length 106

4.21.3 Number of branches 106

4.21.4 Pest infestation 107

4.21.5 Virus incidence 116

4.21.6 Days to 50% flowering 116

4.21.7 Root girth 116

4.21.8 Root length 119

4.21.9 Number of marketable roots per plant 119

4.21.10 Weight of marketable roots per plant 119

4.21.11 Total number of roots per plant 122

4.21.12 Total weight of roots per plant 122

4.21.13 Root yield 122

4.21.14 Starch content (%) 131 4.21.15 Beta carotene (Mg/100gFW) 131

4.21.16 Dry matter content (%) 131

4.22 Mean Performance of Hybrids 136

4.22.1 Vine length 136

4.22.2 Number of branches 136

4.22.3 Pest infestation 137

4.22.4 Virus incidence 137

4.22.5 Days to 50 % flowering 137

4.22.6 Root girth 138

4.22.7 Root length (cm) 138

4.22.8 Number of marketable roots per plant 138

4.22.9 Weight of marketable roots per plant 139

4.22.10 Total number of roots per plant 139

4.22.11 Total weight of roots per plant 140

4.22.12 Root yield per hectare 140

4.22.13 Starch content (%) 140

4.22.14 Beta carotene content 140

4.22.15 Dry matter content 141

4.23 Estimates of Phenotypic and Genotypic Coefficients of Variation 141

4.23.1 Estimate of σ2g, σ2e, σ2A and σ2D 142

4.23.2 Broad sense and narrow sense heritability estimates 143

4.23.3 Estimates of genetic advance 143

4.24 Discussion 145

4.24.1 Mean performance of first evaluation 145

4.24.2 Cluster analysis 149

4.24.3 Rank summation index analysis 151

4.24.4 Correlation 151

4.24.5 Path Analysis 152

4.24.6 General combining ability effects of parents 153

4.24.7 Estimation of specific combining ability 155

4.24.8 Mean performance of newly developed hybrids (genotypes) 157

4.24.9 Genetic estimate 160

CHAPTER 5 CONCLUSION AND RECOMMENDATION 164

5.1 Conclusion 164

5.2 Recommendation 165

5.3 List of Co-Authored Published Papers on this Research Work 166

References 167

LIST OF TABLES

3.1 Plot number and names of fifty (50) OFSP genotype that were used for the experiment 43

3.2 Skeleton of ANOVA for Line X Tester Design 54

4.1 Meteorological data of the experimental area at Umudike and Igbariam in 2015, 2016 and

2017 58

4.2 Soil properties of the two experimental sites in 2015, 2016 and 2017 59

4.3 Vine length (cm) of the 47 OFSP genotypes evaluated in Umudike and Igbariam in 2015 planting season 61

4.4 Internode length (cm) of the 47 OFSP genotypes evaluated in Umudike and Igbariam in

2015 planting season 63

4.5 Number of branches (cm) of the 47 OFSP genotypes evaluated in Umudike and Igbariam in 2015 planting season. 65

4.6 Influence of location and OFSP genotypes on pest incidence observed in Umudike and

Igbariam in 2015 planting season. 67

4.7 Influence of location and OFSP genotypes on virus incidence observed in Umudike and

Igbariam in 2015 planting season. 69

4.8 Characteristics OFSP genotypes evaluated in Umudike and Igbariam in 2015 planting 71 season

4.9 Yield characteristics of OFSP genotypes evaluated in Umudike and Igbariam in 2015 73 planting season

4.10 Yield characteristics of OFSP genotypes evaluated in Umudike and Igbariam in 2015 75 planting season.

4.11 Yield characteristics of OFSP genotypes evaluated in Umudike and Igbariam in 2015 77 planting season.

4.12 Beta carotene and vitamin A content of the 47 OFSP genotypes evaluated in Umudike and

Igbariam in 2015 planting season. 79

4.13 Dry matter and starch content of the 47 OFSP genotypes evaluated in Umudike and

Igbariam in 2015 planting season. 81

4.14 Classification of 47 OFSP according to cluster analysis 86

4.15 Cluster mean values of some characteristics of 47 OFSP genotypes evaluated in Umudike and Igbariam. 87

4.16 Nutritional and yield characteristics, their ranks and rank summation index of the 47 OFSP

genotypes evaluated in 2015 in Umudike and Igbariam. 88

4.17 Combined Spearman correlation coefficient among some agronomic traits in orange fleshed sweetpotato genotypes evaluated in Umudike and Igbariam. 90

4.18 Line x Tester ANOVA for combining ability for agronomic and root characters of OFSP

combined across two location 91

4.19 Line x Tester ANOVA for combining ability for pests damage and root yield characters

of OFSP genotypescombined across two locations 92

4.20 Line x Tester ANOVA for combining ability for root yield and nutritional qualities of

OFSP genotypes combined across two locations 93

4.21 Estimates of general combining abilities (GCA) for parents of some characters in

sweetpotato in combined locations 97

4.22 Combined estimate of general combining ability (GCA) of parents for yield and yield

related characters in different locations 98

4.23 Combined estimates of general combining ability (GCA) of parents for culinary qualities

in sweetpotato from different locations 99

4.24 Combined estimates of specific combining ability (SCA) effect for the hybrids for some 101 characters from different locations

4.25 Combined estimates of specific combining ability (SCA) effect for the hybrids for root

yield from different locations 102

4.26 Combined estimates of specific combining ability (SCA) effect for culinary qualities in 104 hybrids

4.27 Summary of best general combiners and specific combiners for different characters 105

4.28 Mean values of vine length of OFSP tester, lines and their progenies at 6, 12 and 18WAP 108

4.29 Mean values of internode length of OFSP tester, lines and their F1 hybrids at 6, 12 and 110

18WAP

4.30 Mean values of number of branches of OFSP tester, lines and their F1 hybrids at 6, 12 and 112 18WAP.

4.31 Mean values of pest infestation of OFSP tester, lines and their F1 hybrids at 6, 12 and 114

18WAP

4.32 Mean values of virus incidence of OFSP testers, lines and their F1 hybrids at 6, 12 and 117

18WAP

4.33 Mean values of phenological and root characteristics of OFSP tester, lines and their 120 F1 hybrids

4.34 Mean values of root characteristics of OFSP testers, lines and their F1 hybrids 123

4.35 Mean values of unmarketable root characteristics of OFSP testers, lines and their 125

F1 hybrids

4.36 Mean values of root characteristics of OFSP testers, lines and their F1 hybrids 127

4.37 Mean values of root yield and starch content of OFSP tester, lines and their F1 hybrids 129

4.38 Mean values of nutritional qualities of root of OFSP tester, lines and their F1 hybrids 132

4.39 Mean values of nutritional qualities of root of OFSP tester, lines and their F1 hybrids 134

4.40 Estimate of mean, genetic components of variance, heritability and genetic advance of orange -fleshed sweetpotato combined across locations. 144

LIST OF FIGURES

Page 1 Flower synchronization/induction using short day treatment 47

2 Fastened female and male parent flowers 47

3 The fastened flowers ready for pollinationthe following morning 47

4 Peeling back the corolla to expose stamen 47

5 Exposed anther 47

6 Peeling back the corolla to expose stamen 47

7 Fastened female parent flowers after hybridization 48

8 Immature sweetpotato capsules with seeds 48

9 Germinating the seeds 48

10 Seedlings in trays 48

11 Transplanted seedlings growing out in polyethene bags 48

4.1 Dendrogram of 47 OFSP genotypes based on agronomic and culinary characters 85

4.2 Path diagram and correlation coefficient of seven characters. Single headed arrow denotes direct effect on root yield, double headed arrow denotes the correlation 89

coefficients between traits.

CHAPTER 1 INTRODUCTION

β-carotene which is a Vitamin A precursor, is an important nutrient required for maintaining immune function, eye health, vision, growth and survival in human beings (National Research Council, 1989). Vitamin A deficiency is among the most serious problems in third world countries and the common cause of childhood blindness. Ninety percent of the blind children in the world live in Asia and Africa where 66.7 percent of children who do not meet their requirements for vitamin A die from increased vulnerability to infection (Omolase et al., 2008). In Nigeria, over 1 million children are blind and another 1.5 million are visually impaired (Georgina, 2014), mainly due to the deficiency in vitamin A. In females, deficiency in vitamin A increases risk of death during gestation, as well as giving birth to children with low weight. The recent research findings demonstrate that vitamin A can have profound effects on maternal to child transmission of HIV/AIDS Virus (Kapinga et al., 2005; WHO, 2009; Sommer, 2008). In view of the above, management of childhood blindness is regarded as the most pressing matter within the WHO’s Vision 2020 initiative: the right to vision (WHO, 1997). Thus, vitamin A malnutrition is an utmost society health concern of the developing countries. Strategies to manage deficiency in vitamin A involve dietary diversification and food fortification. Dietary diversification involves the cultivation of β-carotene-rich crops, like orange fleshed sweetpotato (OFSP). Because of its high β-carotene content, the orange-fleshed sweetpotato is becoming important as the most affordable source of antioxidant and biofortified crop to fight malnutrition in marginal agroecolgy. Consequently, the impoverished people having only lean access to the exorbitant vitamin A prolific animal products such as fish oil, egg, milk and butter, can satisfy the daily intake of vitamin A along with some other essential nutrients by increasing the consumption of these root crops.

1.1 SWEETPOTATO (IPOMOEA BATATAS (L.) LAM)

This is a dicotyledonous plant belonging to the family Convolvulaceae. Sweetpotato is a hexaploid with 2n=6x=90 chromosomes (Austin, 1977). Sweetpotato is among the most important food crops in the world and ranks third among tuber and root crops worldwide (FAO, 2005). In Nigeria however, sweetpotato has been identified to be the 4th (fourth) most vital root crop after Cassava,

Yam, and Cocoyam (Okonkwo et al., 2009). Although categorized as poor man’s food or famine crop, it has significant capability to contribute and promote food security because of its diverse range of positive attributes like high yield with limited inputs, short duration, high nutritional value and tolerance to various production constraints. Thus, orange-fleshed sweetpotato (OFSP) is now becoming an important member of the tropical root crops having huge potentials as a dependable source of vitamin A(Horton, 1998). The young leaves and shoots are sometimes eaten green for its anthocyanin pigments which have anti-inflammatory and anti-carcinogenic properties (Anthony, 2013). Its starchy root contain vitamin A and some other minerals that are comparable to those of many fruits. Also, the edible leaves contain 34.5% crude protein (Truong, 1989) which could be given to animals as forage. Sweetpotatoes are used for a variety of purposes in Nigeria. Apart from being used as vegetable for cooking at home, it is also used for industrial purposes. About 50% of sweetpotatoes grown worldwide are consumed fresh and the rest are processed into potato food products and food ingredients, feed for pigs, cattle and chickens, or converted into starch for industries, or re-used as seed roots for raising the next season's sweetpotato crop. Sweetpotato starch is also widely used by the textile, wood, pharmaceutical and paper industries as an adhesive, texture, binder agent and filler and by oil drilling firms to wash boreholes. Its starch is a 100% bio-degradable substitute for polystyrene and other plastics (Kapinga, 2003). Inspite of being the cheap source of energy, the roots are high in sugars, minerals, starch and vitamin A in the form of β-carotene.

However, white fleshed sweetpotato provides adequate dry matter content for consumption. Varieties with high dry matter content is the main characteristic in sweetpotato preferred by processors and consumers of sweetpotato. Dry matter is regarded as a measurement of the weight of product when completely dried. Most of the DM in sweetpotato (85 to 90%) is carbohydrates, thus factors that affect the total carbohydrate fraction are essentially the same as those that influence DMC. The carbohydrate fraction consists of starch, sugars, pectin, cellulose and probably hemicellulose. Dry matter of plant would include carbohydrates (starch), fats, proteins, vitamins, minerals, etc. Starch however, is a carbohydrate and an important energy constituent of food products and stock feed. There is a continued effort and need to develop and release new sweetpotato varieties possessing high dry matter content and high yielding abilities. Most OFSP varieties cultivated currently in sub Saharan Africa have a dry matter (DM) content that is very low ie 20-25% to be used as raw materials in the processing industries, that prefers dry matter above 35% (Lu and Sheng, 1990). Farmers and consumers readily prefer varieties with a dry matter content that is more than 25%, while processing industries accept varieties whose dry matter content is 35% and above (Shuzbusha et al., 2010; Gruneberg et al., 2009; Tumwegamire et al., 2004). However, most sweetpotato varieties under cultivation in Nigeria have dry matter content that is below the required standard which is between 25-35% to serve as effective raw material for the industries. Constraints limiting the expanded production of orange-fleshed varieties are low dry mater and low yields. Low dry matter contents of the available orange-fleshed varieties limit the increased utilization at household level mainly by adults. African consumers prefer high dry matter varieties, usually over 30% dry matter. Similarly for the communities that have initiated the processing into flours, it has been observed that very small quantities of flours are obtained when low dry matter varieties are used. According to Hussein et al. (2014), sensory evaluation scores showed that up to 38% inclusion of sweetpotato starch gave acceptable bread, while up to 48% inclusion of starch to wheat produced acceptable cakes with preferred colours, and 48% inclusion of flour to wheat gave acceptable chinchin for general acceptability and colour.

Therefore, these varieties should carry increased β-carotene and dry matter to promote their adoption and large-scale production. The sustainability and expansion of sweetpotato production depend on the availability of varieties that meet end-users preferences. Consequently, a sweetpotato breeding programme should incorporate valuable traits such as high dry matter content and farmers-preferred traits before the release of elite clones. The development of a new variety of sweetpotato with high dry matter content requires efficient methods of crossing, selection of clones from recombined parents and evaluation of the effects of genetic by environment interactions. This permits the release of end-users preferred varieties at the target production environment. Thus developing an OFSP varieties with high DM content and β-carotene will not just boost their utilization in the confectionary industries but will also increase the vitamin A bio fortification of these products.

Yield is another important attribute used by African farmers to accept or reject varieties. The average yields characteristics of OFSP have also limited their large scale adoption. Although several orange-fleshed sweetpotato germplasm accessions have been introduced into Nigeria from International Potato Centre (CIP) and International Institute of Tropical Agriculture (IITA). More have also been sourced from farmers’ field for utilization and evaluation and information on the nature and extent of variability among these collected varieties for characters of economic importance is lacking. Thus the need to quantify the magnitude and the nature of variability for root yield and yield related characters with the aid of genetic parameters like genotypic coefficients of variation, phenotypic coefficients of variation as well as heritability.

1.2 THE AIMS OF THE PRESENT STUDY THEREFORE INCLUDE TO;

(1) determine the agronomic and quality characteristics and yield potentials of OFSP lines.

(2) estimate genetic parameters of yield and yield components that would aid OFSP improvement.

(3) identify and select promising OFSP hybrids for future breeding work.

Click “DOWNLOAD NOW” below to get the complete Projects

FOR QUICK HELP CHAT WITH US NOW!

+(234) 0814 780 1594

Click to view other Projects >> Postgraduate Projects >> Agronomy Projects

Buyers has the right to create dispute within seven (7) days of purchase for 100% refund request when you experience issue with the file received.

Dispute can only be created when you receive a corrupt file, a wrong file or irregularities in the table of contents and content of the file you received.

ProjectShelve.com shall either provide the appropriate file within 48hrs or send refund excluding your bank transaction charges. Term and Conditions are applied.

Buyers are expected to confirm that the material you are paying for is available on our website ProjectShelve.com and you have selected the right material, you have also gone through the preliminary pages and it interests you before payment. DO NOT MAKE BANK PAYMENT IF YOUR TOPIC IS NOT ON THE WEBSITE.

In case of payment for a material not available on ProjectShelve.com, the management of ProjectShelve.com has the right to keep your money until you send a topic that is available on our website within 48 hours.

You cannot change topic after receiving material of the topic you ordered and paid for.