ABSTRACT
The productivity of sweetpotato (Ipomoea batatas (L.) Lam.] is mainly dependent on the acquisition of genotypes which possess desirable traits and development of high yielding varieties with desired quality attributes. For this purpose, a field experiment was carried out at the National Root Crops Research Institute, Umudike, Nigeria, to characterize and evaluate the level of diversity within and across eight different sweetpotato families (LIGRI X SAUTI, SAUTI X 442162, LIGRI X FAARA, LIGRI X APOMODEN, SAUTI X BOHYE, SAUTI X LIGRI, LIGRI POLY CROSS AND SAUTI POLY CROSS) during the 2015 and 2016 cropping seasons.. A total of 141 sweetpotato genotypes obtained from eight different families of sweetpotato seeds sourced from the West Africa Sweetpotato Breeding Platform, Kumasi, Ghana and two checks were used for this research work. The sweetpotato families which were poly-cross (half-sib) and controlled cross (full-sib) were characterized morphologically using International Potato Centre (CIP) descriptors. The total of 143 genotypes were laid out in an augmented design. Varied numbers of genotypes recorded significantly higher values than the mean of the checks for days to physiological maturity, fresh weight of storage roots, total storage root yield, marketable storage root yield, dry matter and starch content. However, non significant differences were observed among the genotypes for unmarketable weight. Ligri PC/17 had the highest storage root yield in 2015 cropping season, Sauti X Bohye/8 had the highest storage root yield in 2016 cropping season. For the half-sib families, SAUTI PC and LIGRI PC dry matter ranged from 23.59% to 50.76% while starch content ranged from 13.6400mg100g-1 to 30.1200mg100g-1 while for the full-sib families, LIGRI X APOMEDEN, SAUTI X 440163, SAUTI X LIGRI, SAUTI X BOHYE, LIGRI X FAARA, LIGRI X SAUTI dry matter ranged from 18.89% to 51.49% while starch content ranged from 11.21mg100g-1 to 33.41mg100g-1. LIGRI X FAARA/8 gave the highest dry matter content of 51.49% while SAUTI X LIGRI/5 gave the lowest 18.89%. LIGRI X FAARA/6 gave the highest starch content of 33.41mg100g-1 while SAUTI X 440163/5 gave the lowest of 11.21mg100g-1. Results from the study showed the presence of considerable variation among the genotypes for several traits studied and the possibility of selecting accessions for further testing for different breeding objectives.
TABLE OF CONTENTS
Title page i
Declaration ii
Certification iii
Dedication iv
Acknowledgements v
Table of Contents vi
List of Tables viii
Abstract x
CHAPTER 1
1.0 Introduction 1
CHAPTER 2: REVIEW OF RELEVANT LITERATURES 4
2.1 Origin
and Distribution of Sweetpotato 4
2.2 Botany of Sweetpotato 5
2.3 Dry
Matter Content in Sweetpotato 6
2.4 Production and Importance
of Sweetpotato 9
2.5 Constraints
to Sweetpotato Production 12
2.6 Genetic
Diversity of Sweetpotato 12
2.7 Breeding Sweetpotato for
High Dry Matter Content 14
2.8 Starch 15
2.9 Digestible
and Non-Digestible Starch Fractions 17
CHAPTER 3: MATERIALS AND METHODS 18
3.1 Experimental
Site 18
3.2 Planting Materials 18
3.3 Cultural Practices 20
3.3.1 Nursery management 20
3.3.2 Irrigation 20
3.3.3 Land preparation 20
3.3.4 Soil sampling 20
3.4 Experimental
Design and Data Collection 21
3.5 Statistical Analysis 23
CHAPTER
4: RESULTS AND DISCUSSION 24
4.1 Soil and Agrometeorological Data 24
4.2 Dry Matter and
Starch Content for Genotypes across the Full-sib and
Half-sib Families 27
4.3 Dry Matter and Starch Content for
Full-sib Families 31
4.4 Dry Matter and Starch Content for
Half-sib Families 41
4.5 Fresh
Yield of Storage Roots 47
4.6 Number
of Marketable and Unmarketable Storage Root 52
4.7 Total
Storage Root Yield 57
4.8 Comparison of the
Yield Characters for Both Cropping Seasons 67
4.9 Selection
of Highest Yielding of 15 Genotypes from the 141
Sweetpotato Genotypes on the Basis of Means. 67
4.10 Pearson Correlation Co-efficients (r) for
the Storage Root
Characters of the 141 Genotypes of Sweetpotato 71
4.11 Selection for High Dry Matter and Starch Content 75
CHAPTER
5:
CONCLUSION AND RECOMMENDATIONS 78
5.1 Conclusion 78
5.2 Recommendations
78
References 79
Appendix 88
LISTS OF TABLES
2.1:
Composition of raw sweetpotato 8
2.2:
Nigeria Production of sweetpotato (tons) 11
3.1: The families of the sweetpotato seeds and their quantity 19
4.1
Soil physical and chemical properties of the experimental sites in
2015
and 2016 cropping season 25
4.2: Agro-meteorological
data of the experimental site for 2015
and
2016 26
4.3: Genotype Mean for Dry Material and Starch across
the full-sib
and half-sib families 28
4.4: Mean of Genotypes of Dry Matter and Starch within Family of
LIGRI X APOMEDEN 33
4.5: Means of Genotypes of Dry Matter and Starch
within Family
of SAUTI X 440163 33
4.6: Means of Genotypes for Dry Matter and Starch
within Family
of SAUTI X LIGRI 36
4.7: Means Genotypes of Dry Matter and Starch within
Family
of SAUTI X
BOYHE 36
4.8: Means Genotypes of Dry Matter and Starch within
Family
of SAUTI X
FAARA 39
4.9: Means of genotypes for Dry Matter and Starch
within Family
of LIGRI X SAUTI 40
4.10: Means of
Genotpyes of Dry Matter and Starch within Family
of SAUTI PC 44
4.11: Means of Genotypes of Dry Matter and Starch
Within Family
of LIGRI PC 45
4.12 Means of genotypes for marketable and
unmarketable storage roots weight/ha for 2015 and 2016 planting seasons 49
4.13: Means of genotypes for marketable and
unmarketable root numbers
for 2015 and
2016 planting seasons 54
4.14
Means of genotypes for total storage root yield for 2015 and 2016
planting seasons 60
4.15
Means of genotypes for total storage root yield of Poly cross and
Controlled
cross genotypes for 2015 planting season t/ha 63
4.16
Means of genotypes and total storage root yield for Poly cross and Controlled
cross genotypes for 2016 planting season 65
4.17: Mean squares of the analysis of
variance for comparison of years (2015 and
2016) for storage roots character
across the families of the sweetpotato
genotypes 68
4.18: Highest
yielding 15 genotypes from the 141 sweetpotato genotypes
on the basis of
means 68
4.19: Mean squares for the combined
analysis of variance for
storage root characters across the
families of the sweetpotato genotypes
for 2015 and 2016 cropping seasons. 69
4.20: Pearson Correlation Co-efficients (r) for the
storage root
characters for the 141 genotypes of sweetpotato 72
4.21:
Selection for high dry matter across the eight different families
of
the sweetpotato genotypes 74
4.22:
Selection for high starch content across the eight different families
of
the sweetpotato genotypes. 77
CHAPTER
1
INTRODUCTION
Sweetpotato
(Ipomoea batatas (L.) Lam.) is the seventh most important food crop in
the world (FAOSTAT, 2012). In developing countries it ranks fifth in terms of
economic value of production (Loebenstein, 2009). Among the tropical root crops,
it is the second most important after cassava (FAOSTAT, 2012). In sub-Saharan
Africa, where the crop is grown on some 13.37 million hectares of land
(FAOSTAT, 2012), it is the third most important root crop after cassava (Manihot
esculenta Crantz) and yam (Dioscorea spp.). The crop is mainly grown
in developing countries where over 95 % of the world‟s production occurs
(Loebenstein, 2009). Asia is the world’s largest producing region while China,
being the largest producing country, (FAOSTAT, 2012) accounts for over 70 % of
the world‟s production (Loebenstein, 2009). Most of the crop produced in China
(70 %) and other parts of Asia are used to feed animals, particularly pigs.
Sweetpotato therefore plays an important role in many rural economies in Asia
(Loebenstein, 2009). Africa produces about 15 % of the world’s sweetpotato
(Loebenstein, 2009). The largest producer in Africa is Tanzania, followed
closely by Nigeria with production figures of about 3.6 and 3.3 million tons,
respectively (FAOSTAT, 2012). Unlike Asia where most of the crop is used in the
animal industry, the crop is a major staple in countries surrounding the Great
Lakes in Eastern and Central Africa; Malawi, Angola, Mozambique, Uganda, and
Madagascar in Southern Africa, and Nigeria in West Africa. In Ghana and parts
of West Africa it is referred to as
a secondary crop because it complements the major root and tubers crops -
cassava and yam (Akoroda, 2009).
In
Nigeria, most of the sweetpotato landraces have white fleshed roots with
negligible amount of the pro-vitamin A pigment. However, Ijeh and Ukpabi (2004)
have shown that a popular local yellow fleshed landrace (known as Ex-Igbariam)
has appreciable but relatively limited
quantity of β-carotene (3 µg/g fresh root sample). Recently (2005 to
2006), the National Root Crops Research Institute (NRCRI), Umudike, Nigeria
acquired some yellow and orange fleshed sweetpotato genotypes with improved
agronomic traits from the International
Potato Centre, Lima, Peru (known by its Spanish acronym of CIP) through its
substation in East Africa. These genotypes, especially those of orange fleshed
sweetpotato (OFSP), were bred as a tool for the global fight against vitamin A
deficiency in areas that lack vitamin A
rich food materials (Degras, 2003).
Sweetpotato has many positive attributes. It produces
more carbohydrate per unit area per unit time than other root crops; it has short
production cycle; it grows well in many
agroecologies; it requires low inputs,
and is fairly tolerant to production stresses such as high temperature, water
deficits, insects, diseases and low soil fertility (Woolfe, 1992).
Nutritionally, its high levels of proteins, minerals and dietary fibre, make it
superior to most staples (Low et al., 2007). The orange-fleshed
varieties are rich in provitamin A. It is reported that regular intake of one
hundred grams of orange-fleshed varieties containing about 3 mg/100 g
β-carotene on a fresh weight basis is adequate to meet the recommended daily
allowance of vitamin A, and prevent vitamin A deficiency in pregnant mothers,
and also prevent blindness in children (Mcharo and La Bonte, 2007). Sweetpotato
is also a good source of dietary fiber and provides a feeling of satiation that
helps to control food intake and promote a healthy digestive tract. Thus,
consumption of sweetpotato helps to lower the risk of constipation,
diverticulosis, colon and rectal cancer and obesity (Willcox et al.,
2009). The orange and purple-fleshed varieties are known to have antioxidant
properties which give protection from the formation of free radicals and
therefore, prevent cancers (Willcox et al., 2009). Sweetpotato is known
to have low glycemic index, in that, the slow rate of digestion of its complex
carbohydrate, lowers the rate of absorption of sugars into the blood stream. It
is therefore, a suitable source of food for the diabetics (Willcox et al.,
2009).
Sweetpotato has many industrial applications (Lin et
al., 2007). It is an industrial source of starch and alcohol (Rahman et
al., 2003), yielding 30–50 % more starch than rice, corn and wheat sources
measured under the same conditions. Its high grade starch is suitable for food
and pharmaceutical industries, and has been used in textile, paper, cosmetics,
insulating and adhesive industries (Rahman et al., 2003;
Veeraragavathatham et al., 2007).
Sweetpotato has a long history as a lifesaver and a
food security crop. It saved lives after the second world war, and when
typhoons demolished rice fields, millions were kept from starvation in
famine-plagued China in the early 1960s and Rwanda in 1999 (Veeraragavathatham et
al., 2007). Sweetpotato therefore, has immense potential and has a major
role to play in human nutrition, health, food security, industry, and poverty
alleviation.
Despite the importance of sweetpotato
in developing countries there are several constraints facing production of the
crop. Among these are abiotic
and biotic constraints such as viral infection, weevil infestation, lack of
quality planting materials and lack of improved cultivars with high and stable
yields. The key constraints to sweetpotato
production are diseases and insect pests. Sweetpotato weevils constitute a
major constraint to sweetpotato production and utilisation worldwide (Veeraragavathatham et al., 2007).
Therefore the objectives of this study are:
1. To compare the observed variation between half-sib
and full-sib families in dry matter content, starch content, fresh root yield.
2. To study the variation within and
across bi-parental families in root yield and yield components.
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