University of Ghana http://ugspace.ug.edu.gh IDENTIFICATION OF RICE (Oryza spp.) LANDRACES WITH NITROGEN USE EFFICIENCY IN GHANA BY NANA MUHAMMED OPUNI (10435580) THIS THESIS IS SUBMITTED TO THE UNIVERSITY OF GHANA, LEGON IN PARTIAL FULFILMENT OF THE REQUIREMENT FOR THE AWARD OF MPHIL IN CROP SCIENCE DEGREE. JULY, 2019 University of Ghana http://ugspace.ug.edu.gh May 05, 2020 April 29, 2020 i University of Ghana http://ugspace.ug.edu.gh ACKNOWLEDGEMENT I sincerely offer my unending gratitude to the Almighty God, who for His unfailing love gave me life, strength, courage, wisdom and understanding to carry out this research work. My appreciation goes to my supervisors, Dr. John S.Y. Eleblu and Dr. (Mrs.) Beatrice E. Ifie for their inspiration, excellent suggestions and constructive criticisms which have indeed led to the fine quality of this work. I am most thankful for the scholarship rendered by A.G. Leventis and Legon Botanical gardens. To Dr. (Mrs.) Matilda Bissau of the Plant Genetic Resource Research Institute, Bunso, thank you for the help in sorting out the landraces used for the study. To Mr. Agyekum and all staff of the University of Ghana farm, I am indeed grateful for the assistance rendered during the field work. I am heartily thankful to the staff of the Ecological Laboratory, University of Ghana, especially to Mr. Prince Owusu and Mr. Christian Drah, for the technical assistance received during the soil, grain and straw analysis. Finally to all my friends especially Dr. Augustine Boadu Asare, I humbly say you guys are the best and I am thankful for the support, love, prayers and encouragement. ii University of Ghana http://ugspace.ug.edu.gh DEDICATION I dedicate this work to Almighty God for granting mankind a beautiful environment full of diversity, the bedrock of an extraordinary world; who makes all things possible and beautiful in His time. Secondly, to my Parents (Mr. and Mrs. Opuni Sekyere) for their unfailing love, support, prayers and encouragement; who deemed it right to give me the best legacy I could ever have. iii University of Ghana http://ugspace.ug.edu.gh ABSTRACT Sustainability in rice cultivation requires increasing yield while protecting the environment against pollution from the over-use of fertilizers through the utilization of varieties that are nitrogen use efficient. Hence, the goals of the study were to: 1) characterize the assembled landraces of rice 2) describe the growth response of rice landraces under different nitrogen levels 3) assess the relationship between yield related traits and NUE components and 4) evaluate the extent of genotypic variations of NUE components and yield related traits among the landraces. Two experiments were conducted in pots and on the field which involved 20 rice landraces tested under two nitrogen levels; (no nitrogen fertilizer application) and low nitrogen (i.e. 50 kg/ha of nitrogen fertilizer). The experiments were conducted in the University of Ghana farm from February 2019 to June 2019. The experimental design for the pot experiment was completely randomized design in a factorial arrangement with three replicates. A split plot design was used for the field experiment with three replicates. Average diversity index was 0.70 and 0.33 for quantitative and qualitative traits respectively. Five clusters were created at a similarity index of 67 % among the landraces. Principal component analysis showed four independent principal components accounted for 71.9 % of the total variation. Root dry weight, leaf length, leaf width, shoot dry weight, number of leaves, plant height, chlorophyll content, culm number and grain yield significantly increased at 50 kg/ha of nitrogen (N) fertilizer. Root length increased by 8.79 % in the absence of N fertilizer. There was a reduction in yield related traits under 0 kg/ha of nitrogen fertilizer compared to 50 kg/ha of nitrogen fertilizer. A significant increase in NUE by 31.72% and 5.73 % in pot and field experiments respectively was observed under no N conditions compared to low N. NUE correlated significantly with filled spikelet, grain yield, panicle length, 1000 - grain weight and Nitrogen Uptake efficiency (NUtE). Genotypic coefficient of variation was lower than iv University of Ghana http://ugspace.ug.edu.gh its corresponding estimates for phenotypic coefficient of variation in all yield related traits and NUE. It can be concluded that GH1550, GH1801, GH1822 and GH2145 were nitrogen efficient and may be used for cultivation and/or used in future breeding programmes to decipher loci involved in NUE for developing superior varieties. v University of Ghana http://ugspace.ug.edu.gh Table of Contents DECLARATION............................................................................................................................ i ACKNOWLEDGEMENT ............................................................................................................. i DEDICATION.............................................................................................................................. iii ABSTRACT .................................................................................................................................. iv LIST OF TABLES ....................................................................................................................... ix LIST OF FIGURES ...................................................................................................................... x LIST OF ABBREVIATIONS ..................................................................................................... xi 1 INTRODUCTION................................................................................................................... 1 2 LITERATURE REVIEW ...................................................................................................... 5 2.1 Taxonomy, geographic origin, Botany, growth and life cycle of the rice plant ........................... 5 2.1.1 Taxonomy of the rice plant ....................................................................................................... 5 2.1.2 Geographic origin ...................................................................................................................... 5 2.1.3 Botany of the rice plant ............................................................................................................. 7 2.1.4 Growth and development of the rice plant ............................................................................ 10 2.2 Rice production systems in sub-Saharan Africa .......................................................................... 11 2.3 Socio-economic importance of rice ................................................................................................ 13 2.5 Nitrogen fertilizer: facts and effects .............................................................................................. 17 2.5.1 Consumption of N globally ...................................................................................................... 17 2.5.2 Loss of N fertilizer .................................................................................................................... 18 2.5.3 Consequences of N over use .................................................................................................... 18 2.6 NUE as a concept ............................................................................................................................ 19 2.6.1 Mechanism of N assimilation .................................................................................................. 20 2.6.2 Nitrogen uptake/ assimilation in plants.................................................................................. 20 2.6.3 Nitrogen remobilization ........................................................................................................... 21 2.7 Improving NUE ............................................................................................................................... 22 2.7.1 Agronomic practices ................................................................................................................ 22 2.7.2 Genotype selection.................................................................................................................... 22 2.8 The relationship between genetic variability and Nitrogen use Efficiency ................................ 23 3 MATERIALS AND METHODS .......................................................................................... 27 3.1 Description of the study area ......................................................................................................... 27 3.2 Plant material .................................................................................................................................. 28 3.3 Soil sampling and analysis .............................................................................................................. 28 3.4 Pot experiment ................................................................................................................................ 29 3.5 Field experiment .............................................................................................................................. 30 vi University of Ghana http://ugspace.ug.edu.gh 3.6 Phenotypic data scored ................................................................................................................... 30 3.6.1 Agro-morphological characterization .................................................................................... 31 3.6.2 Growth, yield related traits and NUE components ............................................................... 32 3.7 Statistical Analysis .......................................................................................................................... 34 3.7.1 Germplasm characterization .................................................................................................. 34 3.7.2 Growth parameters, yield and NUE components ................................................................. 34 3.7.3 Estimates of variance components .......................................................................................... 35 4 RESULTS .............................................................................................................................. 36 4.1 Characterization of landraces ........................................................................................................ 36 4.1.1 Diversity in qualitative traits in pot experiment ................................................................... 36 4.1.2 Diversity in quantitative traits in pot experiment ................................................................. 38 4.1.3 Correlation among traits in pot experiment .......................................................................... 40 4.1.4 Cluster and principal component analysis among rice landraces in pot experiment ........ 41 4.2 Correlation among the growth parameters in pot experiment ................................................... 48 4.3 Yield related traits of rice genotypes under no and low nitrogen levels in pot and field experiment ............................................................................................................................................. 49 4.4 Nitrogen use efficiency and its component traits in pot and field experiment .......................... 49 4.5 Genotypic and phenotypic coefficient of variations and heritability estimates for yield related traits and NUE components in pot and field experiments ................................................................. 52 4.6 Correlations among yield related traits and NUE components in pot and field experiments . 55 5 DISCUSSION ....................................................................................................................... 57 5.1 Characterization of germplasm ..................................................................................................... 57 5.1.1 Diversity among morphological traits in pot experiment ..................................................... 57 5.1.3 Cluster principal component analyses among landraces in pot experiment ...................... 58 5.2 Growth response of the rice genotypes in different nitrogen treatments in pot experiment ... 59 5.2.1 Effect of nitrogen on root morphology ................................................................................... 59 5.2.2 Effect of nitrogen on number of tillers, leaf length, leaf width and leaf number ............... 60 5.2.3 Effect of nitrogen on grain yield ............................................................................................. 60 5.2.4 Effect of nitrogen on chlorophyll content .............................................................................. 60 5.2.5 Effect of nitrogen on Plant height ........................................................................................... 61 5.2.6 Effect of nitrogen on shoot dry weight ................................................................................... 61 5.2.7 Correlation among growth parameters in pot experiment .................................................. 61 5.3 Yield related traits in pot experiment ........................................................................................... 62 5.4 Nitrogen use efficiency and its component traits ......................................................................... 63 5.5 Genotypic and phenotypic coefficient of variation ...................................................................... 64 5.6 Heritability....................................................................................................................................... 64 vii University of Ghana http://ugspace.ug.edu.gh 5.7 Correlation among traits in pot and field experiment ................................................................. 65 6 CONCLUSIONS AND RECOMMENDATIONS .............................................................. 67 6.1 Conclusions .................................................................................................................................... 67 6.2 Recommendations ......................................................................................................................... 68 REFERENCES ............................................................................................................................ 69 7 APPENDICES ........................................................................................................................ 88 7.1 Appendix A Accessions of rice and their collection site ..................................................... 88 7.2: Appendix B ANOVA for growth parameters in pot experiment ......................................... 89 7.3 Appendix C ANOVA for yield related traits and NUE components in pot experiment ... 92 7.4 Appendix D Analysis of variance for yield related traits and NUE under field experiment………………………………………………………………………………………..97 7.5 Appendix E Diversity in grain colour of some landraces used…….…………..………...103 viii University of Ghana http://ugspace.ug.edu.gh LIST OF TABLES Table 3.1: Physical and chemical properties of soil in the experimental site ........................ 28 Table 3.2: List of agro morphological traits scored ................................................................. 31 Table 3.3: Description of the 13 measured and calculated yield and NUE related trait…...33 Table 4.1: Qualitative traits showing the predominant state observed, distribution (%) and the calculated Shannon diversity indices (Hʹ) for each descriptor scored in pot experiment. ....................................................................................................................................................... 37 Table 4.2 Quantitative descriptors and calculated Shannon-Weiner index (Hʹ) of evaluated rice landraces in pot experiment ............................................................................................... 39 Table 4.3: Correlation matrices of the 20 quantitative variables in pot experiment ............ 40 Table 4.4: Principal components analysis based on the 14 quantitative trait ....................... 42 Table 4.5: Effect of two nitrogen levels on root length and dry weight, leaf length and width of twenty rice landraces in pot experiment............................................................................... 45 Table 4.6: Effect of two nitrogen levels on number of leaves, plant height and chlorophyll of twenty rice landraces in pot experiment ................................................................................... 46 Table 4.7: Effect of two nitrogen levels on number of tillers, shoot dry weight and grain yield of twenty rice landraces in pot experiment ..................................................................... 47 Table 4.8: Phenotypic correlation coefficient of growth parameters among twenty rice landraces in pot experiment ...................................................................................................... 48 Table 4.9: Summary of ANOVA for yield related traits under no and low nitrogen levels of twenty rice landraces in pot and field experiment ................................................................... 50 Table 4.10: Summary of ANOVA for Nitrogen use efficiency parameters under no and low nitrogen levels in pot and field experiments of twenty rice landraces ................................... 51 Table 4.11: Estimation of genetic variability parameters for yield related traits in rice landraces under pot and field conditions. ................................................................................. 53 Table 4.12: Estimation of genetic variability parameters for nitrogen use efficiency in rice landraces under pot and field conditions….…...……………………………………………..54 Table 4.13: Correlation for yield related traits and nitrogen use efficiency in pot experiment ................................................................................................................................... 56 Table 4.14: Correlation for yield related traits and nitrogen use efficiency in field experiment……………………………………………………………………………………....56 ix University of Ghana http://ugspace.ug.edu.gh LIST OF FIGURES Figure 4.1 Dendogram generated by cluster analysis on the basis of agromorphological characters …………………………………………………………………………………..41 x University of Ghana http://ugspace.ug.edu.gh LIST OF ABBREVIATIONS % Percentage € Euros ADP Adenosine triphospahate ANR Apparent nitrogen recovery rate Asn Asparagine ATP Adenosine triphospahate AUE Agronomic use efficiency BCE Before the Common/Current/Christian era CD Culm diameter CE Common Era CL Culm length cm centimeters CN Culm number CPHY Chlorophyll EC Electrical conductivity FLL Flag leaf length FLW Flag leaf width g grams GDH Glutamate dehydrogenase GDP Gross domestic profit Gln Glutamate dehydrogenase GNC Grain nitrogen concentration xi University of Ghana http://ugspace.ug.edu.gh GOGAT Glutamine -2-oxoglutarate aminotransferase GY Grain yield H Heritability Hˊ Shannon-Weaver diversity index HGW 100-grain weight Kg/ha Kilogram per hectare LL Ligule length LN Low nitrogen LW Leaf width m3 meters cube mg/l milligram per liter mm millimeters MMT Million metric tons MoFA Ministry of Food and Agriculture N Nitrogen N North NADH Nicotinamide adenine dinucleotide NDM Number of days to maturity NDMH Number of days to main heading NL Number of leaves NR Nirate reductase NT Number of tillers NUE Nitrogen Use Efficiency xii University of Ghana http://ugspace.ug.edu.gh NUEg Nitrogen use efficiency in grain NUpE Nitrogen Uptake Efficiency NUtE Nitrogen Utilization Efficiency oC Degree celcius oF Farenhaeit PL Panicle length PLTH Plant height PN Panicle number RL Root length RW Root weight SNC Straw nitrogen concentration SW Straw weight US$ United States Dollars USDA United Sates Department of Agriculture W West xiii University of Ghana http://ugspace.ug.edu.gh CHAPTER ONE 1 INTRODUCTION Nitrogen (N) is an element and a key driver in living systems and in agriculture because all important processes in plants are associated with the activities of proteins which have this element as a major building block. In addition, it aids the absorption and utilization of other nutrients such as potassium and phosphorus and regulates the growth of plants which ultimately increases crop yields (Leghari et al., 2016). Although 78 % of the atmosphere constitutes nitrogen, plants are unable to utilize it unless it is converted to ammonium or nitrate (Leghari et al., 2016). Naturally, N can be fixed by lightening or biological nitrogen fixing organisms such as cyanobacteria and diazotropic bacteria but contributes only a fraction of N necessary for the cultivation of plants (Choudhury & Kennedy, 2005; Miller & Cramer, 2005). Thus, to meet with the pace of population increase and challenges faced with malnutrition and food production especially in developing countries, after World War II, the term Green Revolution was born which led to the adoption of industrial fertilizers (Hirel et al., 2011). This was a brilliant initiative as high input varieties were bred which required colossal amount of synthetic fertilizer for increased crop yield. Though this innovation solved the issues of food security, consequently, it led to environmental pollution (Erisman et al., 2008). This became a serious challenge especially for Africa where millions of people still live in abject poverty and are malnourished. More so, some areas are prone to lack of clean drinking water, which is buttressed by the fact that N leaches easily into water bodies (Pan Africa Chemistry Network –PACN, 2012). Balancing agricultural yield and maintaining environmental health especially in paddy fields that require high doses of fertilizer is challenging (Sharma & Bali, 2017). This is because, urea is the most popular nitrogen 1 University of Ghana http://ugspace.ug.edu.gh fertilizer source for rice but its efficiency in rice production is meager (around 30-40%), in some cases even lesser. Volatilization, denitrification, leaching and runoff of N fertilizer has led to a decline in N use efficiency (Choudhury & Kennedy, 2005). Conversely, excessive use of nitrogen does not even boost grain yield rather it leads to worsening climate change, biodiversity loss, environmental and health concerns and also increases prevalence of foliar pathogens and plant lodging (Samonte et al., 2006; Hirel et al., 2011). Rice, being rich in nutrients and contains a number of vitamins and minerals, is an excellent source of complex carbohydrates, one of the best source of energy making rice to occupy an enviable position among the cereal crops globally (Olembo et al., 2010), but the afore mentioned challenges limits its production and would hinder attaining food security if not addressed especially when the populace is envisioned to hit 9 billion by 2050 (Selvaraj et al., 2017). More so, the dilemma is not in the ability to cater for 9 billion people in 2050, but if it can be done sustainably, equitably and on time in the face of challenges such as the changing climatic conditions and poor soil fertility (Spiertz, 2010). For example, in the 1960s, cultivation of crops was carried out on a hectare of land which was able to feed two people without experiencing cost and pollution, by 2050, the same nutrient depleted soil will be required to feed more than triple the number of persons fed on a hectare. This will stir up farmers over applying fertilizer to increase yield especially for countries that import rice to meet up with the demand (Pan Africa Chemistry Network –PACN, 2012) which is already the current trend in today’s agriculture especially for Africa. For instance, Ghana has not yet reached self-sufficiency in terms of rice production because billions of dollars is spent on importation of rice annually, which is a tremendous loss to foreign exchange (Angelucci et al., 2013). The major limiting factor faced by Ghanaian farmers is the high levels of N deficiency in 2 University of Ghana http://ugspace.ug.edu.gh paddy fields. Farmers thus have to apply vast quantities of fertilizer which is not very much available and affordable as they are not even manufactured in Ghana (Fianko et al., 2011). Application of fertilizers in high doses does not guarantee high yield because a critical analyses of the consumption of synthetic fertilizer globally indicate that for the past 4 decades, the amount of fertilizer agricultural crops have utilized is 7.4 fold as against the yield of 2.4 fold. This implies that nitrogen use efficiency (NUE) has declined (Hirel et al., 2011). The decline in NUE can be as a result of deficiency in two main NUE mechanisms: the absorption of N, also referred to as nitrogen uptake efficiency (NUpE) and the assimilation of the absorbed N necessary for grain production termed N utilization efficiency (NUtE) (Han et al., 2015 ). Thus, to improve NUE, several studies have been conducted through agronomic management (Yadav et al., 2017; Dubois et al., 2017 ). For the purposes of overcoming setbacks associated with agronomic management in terms of nitrogen fertilization, breeding rice varieties that are less dependent on the heavy application of N fertilizers and responsive to limited N fertilizers is essential. Varieties able to utilize limited nitrogen fertilizer with high grain yield would contribute towards the goal of achieving long term sustainable production system. Sustainability in agriculture implies that improving resource-use efficiencies should center on higher yield with limited N fertilizer. It is based on the theory that the necessities of contemporary times are met without negotiating that of the future (Spiertz, 2010). Thus, improved NUE is a fundamental segment of a sustainable agriculture that fulfills human necessities, reduce production costs and safeguards biological diversity including the environment and health of the people. 3 University of Ghana http://ugspace.ug.edu.gh Prior to breeding for NUE rice genotypes, it is important to identify genotypes with NUE through recognizing plant phenotypes that correlate with high yield as well as high NUE to enable breeders utilize these traits in breeding programmes (Naveen et al., 2016). To identify nitrogen efficient genotypes, existing hybrids might not be the best genetic material because they are mostly bred for high usage of synthetic fertilizer, (Ali et al., 2018). In view of this, utilizing landraces in terms of identifying NUE lines is very useful. This is due to their past evolutionary history as they are better adapted to environmental stress under low input conditions and therefore constitute a unique germplasm for ascertaining NUE lines (Ali et al., 2018). Though NUE lines have been identified in various rice genotypes in Asia and some parts of Africa (Fageria et al., 2010; Segda et al., 2014; Rao et al., 2014; Lakew, 2015; Rao et al., 2018), there is a dearth of information on the identification of NUE lines in rice germplasm collections in West Africa such as Ghana (Segda et al., 2014). Thus, identification of NUE lines in Ghanaian rice landraces will aid in their usefulness as plant genetic resources. Hence, the objectives of the study were to: 1. characterize rice landraces for morphological traits; 2. determine growth of the landraces as affected by different levels of nitrogen; 3. identify NUE lines and assess the relationship between NUE components and yield related traits; 4. assess genotypic variations of NUE components and yield related traits among the landraces. 4 University of Ghana http://ugspace.ug.edu.gh CHAPTER TWO 2 LITERATURE REVIEW 2.1 Taxonomy, geographic origin, Botany, growth and life cycle of the rice plant 2.1.1 Taxonomy of the rice plant Rice has been classified to the family, Gramineae or Poaceae and genus, Oryza. The rice genus (Oryza) is made up of about 25 annual and perennial grass species distributed across diverse climatic zones in Africa, Asia, Australia and Southern America. It may be typically considered as an annual grass adapted to both temperate and tropical climates under a variety of water regimes such as lowland and upland conditions. Two out of these rice species are cultivated, namely; Oryza sativa and Oryza glaberrima, the remaining are undomesticated (Global Rice Science Partnership, 2013). 2.1.2 Geographic origin Rice history dates back to over a century ago when the seven continents, which were originally merged, progressively started drifting apart. Since then, rice has been growing everywhere apart from Antarctica (Shamar, 1991). Interestingly, rice in Latin is, “Oryza” in English it is “Rice” and these names have been coined out from the ancient Tamil word “Arisi”. Merchants from Arabia procured arisi and named it ‘Al-ruz” in Arabic. It is also called “Arroz”, “Oriza”, “Rizo”, “Riz” and “Reis” in Spanish, Greek, Italian, French and in German respectively (Shamar, 1991). Historically, Alexander the Great (400 BCE) was the first to describe rice in Africa. He imported rice into Egypt from India which led to the beginning of rice farming in 639 CE. The Greek philosopher and historian, Strabo, earlier noticed the presence of rice in Cyrinaica (Libya) around 5 University of Ghana http://ugspace.ug.edu.gh 12 CE (Nayar, 2012). The first description of rice farming in West Africa along the Niger River was by the Islamic scholar, Al-Bakri. Ibn Batuta, a well-known Moroccan traveler also gave account of the abundance of rice in the Inland Niger Delta. In the early 15th century, several early travelers also noticed the cultivation of rice in West Africa, before the arrival of the first Europeans (Nayar, 2012). The main center of diversification of the African rice (O. glaberrima) is the marshy basin of the upper Niger river in West Africa, apparently created around 3000 BC (Linares, 2002). Poteres (1970, as stated by Sweeney and McCouch, 2007) re-counted that O. glaberrima was originally planted in flood waters. Rice cultivation later extended to the saline waters using non-floating cultivars and later cultivars were chosen and planted on upland fields which were watered by rainfall. Two secondary centers were created 5 centuries later in the South West close to the Guinean Coast. The initial account was on the coast of Gambia, Casamance and Guinea Bissau, followed by that of Guinea forest amid Sierra Leone and Western Ivory coast about 100 BC ago (Agnoun et al., 2012). The major rice growing countries outside West Africa are Congo DR, Egypt, Madagascar, Mozambique and Tanzania (Nayar, 2012). Until the 1920s, most of the rice was produced in the Volta and Western regions of Ghana by traditional farmers. It was not until the 1960s that rice became an important crop in Ghana and now, the bulk of Ghana’s rice comes from the Northern region of the country. In the Volta region, rice cultivation is frequently carried out by women while the men mostly cultivate coffee, cocoa and rubber. These rice cultivars have been passed on from generations to generations (Kranjac- 6 University of Ghana http://ugspace.ug.edu.gh Berisavljevic et al., 2003). O. glaberrima is usually cultivated in upland conditions while some O. glaberrima varieties and O. sativa varieties are cultivated under lowland conditions (Kranjac- Berisavljevic et al., 2003) . 2.1.3 Botany of the rice plant 2.1.3.1 Root The rice plant has a relatively shallow and dense root system as compared to other upland cereal crops like maize and wheat probably because it grows under flooded conditions (Morita & Nemoto, 1995). Its root architecture is in two main categories; crown roots and nodal roots which sprout from the nodes. The nodes beneath the soil surface is where the crown roots grow from while the nodal roots are formed from the nodes above the soil surface at a water level of above 80 cm deep. In water-logged soils, rice roots occasionally surpass a depth of 40 cm because inadequate oxygen diffuses through the aerenchyma cells of roots to sustain the developing root tips (Maclean et al., 2002). 2.1.3.2 Culm The culm, which is also called a group of linked stems of rice consists of the nodes and internodes. As the rice plant develops, tillers sprout from the bottom of the main culm and these further gives rise to other tillers called the ancillary tillers. The ancillary tillers further gives rise to more tillers (Chang, 1965). 7 University of Ghana http://ugspace.ug.edu.gh 2.1.3.3 Leaves The leaves bear the sheath and blade and can be found on the culm in dual positions, a single leaf at each node. Connected to the sheath is the blade which encircles the jointed stem above the node in different sizes, shape and rigidity (Chang, 1965). The blades are usually attached at the base of the culm and are uniform. Rice varieties differ in blade size, girth, area, form, color, position and presence/absence of hair. The leaf below the panicle is called the flag leaf which differs in form, size and position. (Chang, 1965). Where the blade and the sheath intersect is a pair of claw-like attachments, known as the auricles. Rough hairs shields the external part of the auricles (Maclean et al., 2002). In the middle of the leaf sheath and the blade is a membranous, glabrous or ciliate ligule. It varies in length, color and form among varieties (Chang, 1965). The intersection between the sheath and blade is known as the collar or juncture. The collar appears as a raised region found at the back of the leaf (Chang, 1965). 2.1.3.4 Reproductive organs The reproductive structures of rice are modified shoots. They consist of the panicle, spikelet and the flowers. 8 University of Ghana http://ugspace.ug.edu.gh 2.1.3.4.1 Panicle The culm bears the panicle which are arranged in a racemose pattern on the topmost internodes. Around the panicle axle is the inflorescence which extends from the bottom of the panicle to its apex. The nodes on the panicle develops into a main twig which gives rise to ancillary twigs (Chang, 1965). 2.1.3.4.2 Spikelet The spikelet bears the pedicel which is a small stalk that is an extension of the panicle axle and the main or ancillary twig. At the upper end of the pedicel are two short rudimentary glumes: a duo of sterile lemmas and rachilla positioned amid the rudimentary glume and the spikelet (Yoshida, 1981). The flower is surrounded by the lemma and palea, which may perhaps be either awned or awnless (a fibrous bristle present in some cultivars, formed as an extension of the midrib of the lemma) (Yoshida, 1981). 2.1.3.4.3 Flower The flower consists of six pollen-bearing organs which contains 2-celled anthers found on the filaments while the pistil bears a single ovule. At the base of the flower lies two variegated, pristine, plump-like appendages attached to the palea (Chang, 1965). The rice fruit is also known as the caryopsis. It has only one seed joined to the edge of the mature ovary (pericarp). The grain is the ripened ovary with the lemma, palea, rachilla, sterile lemmas and perhaps the awn. The husk or hull bears the lemma, palea, sterile lemmas, rachilla and the awn (Chang, 1965). 9 University of Ghana http://ugspace.ug.edu.gh 2.1.4 Growth and development of the rice plant The life cycle of rice spans from 80 to over 200 days (depending on the species) (Verhey, 2010). There are three agronomic phases associated with the growth and development of rice, namely: vegetative phase, reproductive phase and ripening phase. 2.1.4.1 Vegetative phase The seed imbibes water and becomes flexible. A sheath-like structure covering the radicle (coleorhiza) protrudes out of the seed coat, enabling the radicle to break forth from the coleorhiza and firmly attaches itself in the soil. This takes place within two days when temperatures ranges from 70 to 90 oF / 21 to 32 oC (Moldenhauer & Slaton, 2013). Germination will require longer time if temperatures are higher or lower than the above range. It involves rapid vegetative growth such as proliferation of tillers, boost in plant height and leaf development at steady rates. The main leaf acts as a shield for the emergence of new leaves. As the seedling grows, the emerging leaves protrudes and differentiates into three different fragments; the sheath, collar and blade (Olembo et al., 2010). Pre-tillering phase occurs during the growth of the main and ancillary leaves while tillering takes place when a sprout emerges from the crown just beneath the soil or the axle of the leaf base. This takes place three weeks after emergence (Verhey, 2010). Prior to the inception of the reproductive phase, the formation of tillers declines which is termed the vegetative lag phase. Subsequently, as the number of tillers reduces, plant height and stem girth progressively increases (Verhey, 2010). 10 University of Ghana http://ugspace.ug.edu.gh 2.1.4.2 Reproductive phase Before the reproductive phase commences, there is a reduction in the formation of tillers, culm begins to increase in length, booting is observed, the flag leaf appears, heading takes place and finally flowering begins (Moldenhauer & Slaton,2013). This stage differs based on cultivar and weather conditions. The opening and closing of the spikelet is peculiar to the flowering/ anthesis stage for the purposes of pollination and may last for an hour or two, after which fertilization occurs within 6 hours (Moldenhauer & Slaton, 2013). 2.1.4.3 Ripening phase According to Olembo et al. (2010), fertilization precedes ripening and may be divided into three phases, viz: 1) Milk stage – The starch in the kernels begin to form and a whitish fluid can be found in the center of the kernel. 2) Soft dough stage – The starch in the grain begins to thicken. 3) Hard dough stage – The spikelet becomes hard as it matures with 20 to 22 % moisture content. Ripening is attributed to leaf senescence and grain growth (Maclean et al., 2002). 2.2 Rice production systems in sub-Saharan Africa Rice is a semi-aquatic grass and grows in varied soil types and water regimes (Verhey, 2010). It is also described by its plasticity which aids its growth in different environments of West and Central Africa (Defoer et al., 2004). Rice is cultivated in various agro-ecological zones from humid forests 11 University of Ghana http://ugspace.ug.edu.gh to Sahel within which five major rice ecologies are noted based on the availability of water and topography in sub-Saharan Africa (Dofoer et al., 2004) viz: 1) Rainfed upland rice on plateaus and slopes; 2) Lowland rainfed rice in valleys and flood plains with varying degrees of water control; 3) Irrigated rice with relatively good water control in deltas and flood plains; 4) Deep water floating rice along river beds/ banks; 5) Mangrove swamp rice in lagoons and deltas in coastal areas. Three out of these are the chief ecologies in West and Central Africa. They are: rainfed uplands, rainfed lowlands and irrigated systems (Dofoer et al., 2004). 1) Rainfed upland rice on plateaus and slopes - It covers the largest area of about 44 % of which the coastal areas in the humid and sub-humid agro-ecological zone constitute the largest part. Main water supply is rainfall but the water recedes after sometime (Dofoer et al., 2004). This ecology is characterized by unpredictable rainfall patterns, hence, early maturing and drought tolerant varieties adapt to this ecology. (MoFA, 2009). Rice varieties adapted to this ecology are grown in soils that have greater percentage of sand. Few areas within West Africa, experience two rice growing seasons within a year due to the bimodal rainy season. On the other hand,with an estimated rainfall of 1600 mm a year, ratooning is practiced in some areas (Kranjac-Berisavljevic et al., 2003). 2) Lowland rainfed rice in valley bottoms and flood plains with different water regimes - It covers an area of about 31% of the rice cultivation area (Dofoer et al., 2004). This ecology 12 University of Ghana http://ugspace.ug.edu.gh has water management problems due to regular flooding from ground water and precipitation (MoFA, 2009). 3) Irrigated rice with relatively good water control in deltas and floodplains - It covers 12% of the rice cultivation area. This involves the use of irrigation schemes such as dams, water can also be channeled from rivers to cultivated lands (Dofoer et al., 2004). It may also be appropriate for rice-fish culture (MoFA, 2009). 2.3 Socio-economic importance of rice Rice occupies a leading position among food crops in the world, along with wheat and maize. An area of 214 million hectares of wheat is harvested yearly followed by rice with 154 million hectares and maize with 140 million hectares, making wheat the most cultivated cereal. However, based on their consumption, rice ranks higher with about 85 % as compared to wheat (72 %) and maize (18 %) (Maclean et al., 2002). In fact, in some parts of the world like Bangladesh, Cambodia, Lao PDR, Myanmar and Vietnam, the consumption rate is greater than 150 kg/capita/year (Hay et al., 2013), while in Ghana rice consumption accounts for more than 28 kg/capital/year with urban areas accounting for the highest rice consumption. This is because in the cities, rice is favored over other staples, the reason being that it is simple and convenient to cook and it allows for a wide variety of dishes. (Angelucci et al., 2013; MoFA, 2009). Other factors responsible for its high consumption rates are its nutritional and medicinal values - rice lowers the problem of bowel disorder and protects the body against constipation. This is possible because it is rich in insoluble fiber. It is also rich in carbohydrates, low in fat, with some amount of proteins and plenty of vitamin B (Olembo et al., 2010). Rice also provides the global human population with 21% per capita 13 University of Ghana http://ugspace.ug.edu.gh energy and 15% per capita protein (Maclean et al., 2002). Furthermore, it possesses socio-cultural values because it forms part of religious rites, festivals and ceremonies in some countries like Ghana (Norman & Kebe, 2006). It also has a paramount role in the ritual life of farming communities and it is also recognized as being of deep cultural significance among some Africans in the diaspora in South America (Teeken et al., 2012). Rice is also used in the fight against poverty due to its wide range of uses as outlined below: 1) Rice starch - is an important constituent used for ice cream, custard powder, puddings, gel and alcohol among others (Olembo et al., 2010); 2) Broken rice - is used for baby foods, soups and for brewing purposes (Olembo et al., 2010); 3) Rice bran- can be utilized as feed for livestock and fish. Its oil is used for pharmaceutical products and for human consumption (used for pastries like bread, snacks, cookies and biscuits) (Olembo et al., 2010; Verhey, 2010); 4) Defatted rice bran- is useful as cattle feed, organic fertilizers, medicinal purposes and in making wax (Olembo et al., 2010); 5) Rice straw - can be transformed into paper and also a source of cellulose for ruminant livestock. It is also used as manure, making building materials, as an ultra-pure source of silica and for making footwear and headwear. Rice marbles are used to add decorative effects on book covers, which is a unique use of rice. (Verhey, 2010); 6) Rice husk- can be converted into fuel, manufacture board and paper, used to make building materials and insulators. It is also useful in the making of compost and as a chemical by- product (Olembo et al., 2010). 14 University of Ghana http://ugspace.ug.edu.gh The leading producers of rice in the world are China and India. Thailand, India and Vietnam are the major rice exporting countries (Kam, 2011). According to FAOSTAT (2014), with respect to global cereal production, rice production accounted for 34.1% in 2011/2012 (about 485.9 million tonnes), 35.7% in 2012/2013 (about 490.1 million tonnes) and 36.3% in 2013/2014 (about 496.6 million tonnes). This shows that there is an increase in demand as a result of increase in population. In Africa, rice consumption is third after maize and sorghum, yet Africa produces only about 3.6% of the world’s paddy rice. Rice production ranks fifth with respect to area cultivated (alongside wheat) after millet (Pennisetum glacum; 21% area), sorghum (Sorghum bicolor (L.) Monenchafg; 19% area), maize (Zea mays L.; 12% area) and cassava (Manihot esculenta Cranz; 9% area) (Nayar, 2012). Rice production in Africa is relatively low; hence, African countries depend on large imports of rice. In fact, Africa is next to Asia in terms of rice importation (Kam, 2011). According to Samado et al. (2008) the cost of rice imports into sub-Sahara Africa, accounts for over US$1billion annually. This is a tremendous loss of foreign exchange especially for countries that are already in debt. For example, in Ghana rice import bills account for US$ 450 million annually (Angelucci et al., 2013). In Ghana, rice ranks second after maize and its consumption keeps increasing due to increase in population, urbanization and modification in consumer eating habits (MoFA, 2009). It accounts for approximately 15 % of the gross domestic product (GDP) making it important to the economy and agriculture. An area of about 45 % is allocated to rice production and it is a source of 15 University of Ghana http://ugspace.ug.edu.gh employment to the rural communities (Kranjac-Berisavljevic, 2000). Although rice production takes place in all the ten regions of the country, the chief rice producers are the Northern, Volta and Upper East regions, which together produce between 45000 – 60000 tonnes per year each. Rice production is mostly done by small holder farmers, whose farms are smaller than a hectare of land (Angelucci et al., 2013). Local rice production, therefore, falls far below consumption resulting in a high dependence on imported rice which accounts for 400,000 tonnes yearly (MoFA, 2009). 2.4 Constraints in rice production Rice as important as it is faces lots of challenges in its production pipeline. Its yield is controlled by a variety of environmental factors. In a study carried out in Vietnam, India and Burkina Faso problems which includes drought, problems related to minerals (such as acidity, alkalinity, phosphorus deficiency and iron toxicity), unavailability of suitable and improved varieties for diverse environments, weeds, pests and diseases, salinity, poor soil fertility and high cost of input conditions were observed (Thanh & Singh, 2006; Kam, 2011). In Ghana similar challenges are faced in rice production (MoFA, 2009). Poor soil fertility as affected by high input conditions will be one out of the many challenges discussed in the present study. In view of this, the major causes of poor soil fertility may be associated with prolonged cultivation of rice on the same piece of land without crop rotation and heavy withdrawal of nutrients as a result of cultivation of high yielding varieties and excessive and imbalanced application of fertilizer has added to the poor quality of soil for crop cultivation (Talpur et al., 2013). 16 University of Ghana http://ugspace.ug.edu.gh 2.5 Nitrogen fertilizer: facts and effects Important biochemical and physiological processes in plants are linked with proteins which contains nitrogen (Yadav et al., 2017). N promotes the development of root systems, which have a fundamental importance in the uptake of water and nutrients. It also aids in the transfer of energy such as adenosine diphosphate(ADP) and adenosine triphosphate (ATP) which plays a crucial part in the various metabolic processes of plants (Yadav et al., 2017). N not only supports physiological processes, but enhances food grain and nutritional qualities in plants (Leghari et al., 2016; Maheswari et al., 2017). Furthermore, dry matter production rises with the aid of leaf N associated with chloroplast, N also increases growth and tillering which regulates panicle number. (Samonte et al., 2006). 2.5.1 Consumption of N globally Due to population increase, from the 1960’s to date, fertilizer inputs are associated with yields from cultivated crops especially N fertilizers. The utilization of fertilizer surged from 70,000 tonnes in 1950 - 1951 to above 28 million tonnes in 2012, which has recorded 65 % being N fertilizer. (Rao et al., 2018). Fertilizer application trebled from a mean of 23 kg/ha to 109 kg/ha within 1961 to 2008 respectively (FAO, 2010). Since an estimated amount of 90 million metric tons (MMt) of N fertilizers are added to the global soil for agricultural purposes annually (Frink et al., 1999), it has been predicted to rise to 240 MMt by 2050. Despite the increase in N use, the overall increase in yield has been recorded to be only 2.4 fold (Tilman et al., 1999). In view of this, the affirmation from the World summit on food security demands a mean yearly surge in crop production of 44 million metric tons to cater for an estimated 9 billion people by 2050 (FAO, 2009). This has to correlate with N fertilizer application projected to rise in the next 4 decades. 17 University of Ghana http://ugspace.ug.edu.gh Hence, unless NUE is significantly improved, grave consequences of N fertilizers will continue to occur (Good et al., 2004). Therefore a second green revolution is required which does not rely on intensive fertilization but would aim at boosting yield in soils with reduced fertilizer application. 2.5.2 Loss of N fertilizer As important as nitrogen is to plants, the three most important cereals namely: rice, wheat and maize consumes about 60 % of only nitrogen fertilizer. Rice production utilizes about 20 % of the global N consumption, within which only 30 – 40 % of the N reaches the plant, the rest is lost to the environment (Rao et al., 2014). This is because the rice plant utilizes some amounts of N for its growth and development such as grain production. It has been predicted that 16 – 17 kg of N is used to produce one ton of rough rice with straw inclusive. In the process of increasing N fertilizer demand which would serve as insurance against poor soil fertility as the natural processes of nitrogen fixation contributes only a fraction to what is needed, excessive N amount is used (Rao et al., 2018). This act does not improve productivity because the efficiency of N fertilization is low due to ammonia volatilization, denitrification, leaching and runoff losses. To add with, the level at which N is lost depends on the environmental conditions and other agronomic management practices (Baldani et al., 2000). 2.5.3 Consequences of N over use Although, the importance of N cannot be overemphasized, it is associated with various consequences such as economic loss to farmers, health risk, energy as well as environmental cost. With respect to energy cost, a joint report by the International Fertilizer Industry Association (http://www.fertilizer.org), and United Nations Environmental Programmes, established that 1 18 University of Ghana http://ugspace.ug.edu.gh metric ton of fertilizer N manufactured through the Haber-Bosch process utilizes 873 m3 of natural gas. For crops such as rice, N fertilizer is associated with colossal expenses and this will intensify as resources becomes even more rarer (Xu et al., 2012). N loss to the environment is currently costing the European Union €70 to €320 billion annually. Not only is the consequence of N evident in Europe, in China, 67 main lakes were polluted as a result of high nitrate concentrations (Peng et al., 2011). In Ghana, the Tatafo stream within the Mampong-Ashanti Municipality suffers from eutrophication. This is because the levels of nitrate analyzed were above the WHO limits of (5.0 mg/l) (Wiafe, 2013). This polluted water is not just harmful to aquatic organisms (as it reduces oxygen percolation for their respiration and may lead to the release of toxic substances harmful to them) but is also indirectly harmful to livestock and humans. Reports from earlier studies indicate that ingesting nitrate N in drinking water causes methemoglobinemia in infants (Peng et al., 2011). Furthermore, N deposition which is as a result of ammonia released to the atmosphere via volatilization from agricultural fields can return back to the atmosphere as co-deposition with sulphur oxide which tampers with biological diversity leading to interference with ecosystems functions and services. Lastly, nitrous oxide formed through denitrification is an essential N based greenhouse gas which contributes to about 5% of the total climate change (Yadav, et al., 2017). 2.6 NUE as a concept The complexity of the term ‘Nitrogen use efficiency (NUE)’, may be due to the interplay between the environment and genetic factors. It may be described as the total biomass or grain yield produced per unit available N fertilizer. It could also possess different meaning in different context. Such as: Nitrogen uptake efficiency (NUpE): the absorption of N via the roots, Nitrogen utilization 19 University of Ghana http://ugspace.ug.edu.gh efficiency (NUtE): the remobilization of N for grain production (Xu et al., 2012; Haung et al., 2004). Apparent nitrogen recovery rate (ANR): the proportion of net increased total N absorbed by the plant with or without N fertilization to total amount of fertilizer, Agronomic use efficiency (AUE): the fraction of grain weight in the presence or absence of N fertilization to the total N fertilizer applied, Nitrogen physiological use efficiency (NpUE): the ratio of net increased grain weight to net increased N uptake with and without application of fertilizer N. Nitrogen use efficiency in grain (NUEg): grain production per unit available N, Harvest Index (HI): grain production of the total plant biomass (Xu et al., 2012; Han et al., 2015). Though a crop plant could produce huge amounts of biomass per unit N, without changing the acquired N to seed production and therefore have a low NUEg and HI. In a nut shell, two plant physiological components— NUpE and NUtE makes up plant NUE (Xu et al., 2012). 2.6.1 Mechanism of N assimilation In summary, NUE constitute two key parts, they are: NUpE and NUtE. Understanding the mechanisms regulating these processes is crucial for improving crop NUE. 2.6.2 Nitrogen uptake/ assimilation in plants Nitrogen uptake involves the absorption of N for the synthesis of proteins. Plants absorb nitrogen preferably in the form of nitrate. Therefore nitrogen, whatever the form it is present, should be changed into the available nitrate form which would then be converted or reduced into nitrite. Nitrite is also converted to ammonium which is used in the tissues to create various organic compounds (Yadav et al., 2017). Nitrate has to be broken down to ammonium which is further disintegrated into amino acids. The process of reducing nitrate into nitrite is catalysed in the cytosol 20 University of Ghana http://ugspace.ug.edu.gh by the enzyme nitrate reductase (NR) (Cassman et al., 2002). After which, nitrite is translocated to the chloroplast where it is broken down to ammonium by an enzyme called nitrite reductase (Berntsen et al., 2003). Ammonium from nitrate reduction and photorespiration or amino acid recycling is taken up into the plastid/chloroplast via the GS/glutamine-2-oxoglutarate aminotransferase (GOGAT) cycle (Yadav et al., 2017). 2.6.3 Nitrogen utilization/ remobilization Nitrogen remobilization is the ability of crops to utilize the acquired N for grain production. The processes are outlined as follows: In the course of the active growth stage, the leaves absorb N; subsequently, at maturity, the N stored in the leaves is channeled to the developing grains mainly as amino acids. For example, Arabidopsis and oilseed rape, from earlier studies have been shown to remobilize N from mature leaves to younger leaves at the vegetative phase and from mature leaves to seeds at the reproductive phase (Malagoli et al., 2005; Diaz et al., 2008; Lemaıˆtre et al., 2008). An estimated 95% of proteins in the grains is obtained from amino acids that are transferred to the grains after the proteins in leaves have been degraded, and the remaining is added from the soil and late top-dressed fertilizers. Glutamate (Gln) and asparagine (Asn) are chief classes of total amino acids in phloem and xylem sap of rice plants (Masclaux-Daubresse et al., 2010). A rise in both Asn and Gln concentrations during senescence in the phloem sap indicate their key role in representing N available for remobilization from the mature leaves. Some isoforms of NADH- glutamate dehydrogenase (GDH), and asparagine synthetase (AS) are strongly stimulated during N remobilization (Masclaux-Daubresse et al., 2010). 21 University of Ghana http://ugspace.ug.edu.gh 2.7 Improving NUE 2.7.1 Agronomic practices Improvement in agriculture will depend on increase in crop yields in soils with low fertilizer application (Kabir, 2014). Two basic approaches can be followed in order to improve crop productivity in a sustainable fashion. Firstly, effectual fertilizer management and innovative agronomic practices may improve NUE. Several reports have indicated agronomic practices that can contribute to NUE (Altom et al., 1996; Solie et al., 1996; Hirel, 2011; Dubios et al., 2017; Yadav et al., 2017). Secondly, varieties need to be responsive, to reduce adopting costly or labour intensive practices by the farmers. This can be achieved through initially screening genotypes for the desired traits before breeding can be initiated. 2.7.2 Genotype selection Characterization of germplasm may aid in identifying superior lines that may be used to breed cultivars with high NUE and of course high yields. NUE is hindered by poor characterization of the phenotype and genotype for crop N response and NUE. It is therefore important to first validate the variations in the genotypes through agromorphological characterization to obtain a clear- cut distinction among the varieties to be harnessed. “Characterization” means to describe a character or quality of an individual. The word “characterize” also means to “distinguish”, that is to differentiate or to separate into kinds, classes or categories. Therefore, characterization of genetic resources involves the differentiation of accessions (De Vincente et al., 2005). Morphological characterization of genotypes is necessary for documenting identical varieties, detection of exceptional traits and also the type of the 22 University of Ghana http://ugspace.ug.edu.gh population to be conserved (De Vincente et al., 2005). Morphological diversity is evaluated by taking note of variations in traits such as growth cycle, color of leaves, among others (Machoene, 2009). Morphological markers are also referred to as ‘traditional markers’. The level of analysis of these markers is phenotypic. There are certain demerits of morphological markers, namely: they are controlled by environmental conditions, they are labor demanding and require large populations of plants in performing breeding experiments. They also require large plots of land and/or green house for their growth, but they are still very useful and are of high recommendation before more in-depth biochemical or molecular studies are carried out (Smith & Smith, 1992). The main advantage of conducting morphological characterization is that published descriptors are readily available for most major crop species. Therefore, characterization of the agro- morphological characters of the rice landraces collected in this study and subsequent comparison of their diversity or relatedness, using the rice descriptors suggested by Bioversity et al., (2007), will provide useful information for future breeding purposes. 2.8 The relationship between genetic variability and Nitrogen use Efficiency Genetic variability in crops may be described as the heritable character of a species that portrays variability in growth in contrast to other species under favorable or unfavorable conditions. These conditions could be absorption, translocation and utilization of mineral elements (Fageria & Baligar, 2003). Due to the environmental and ecological challenges faced with nitrogen fertilizer input, an optimum fertilization level in paddy fields where NUE is of utmost priority is the need of the hour. Thus, screening for genotypic variability for NUE in breeders’ germplasm, coupled with genotype x N interactions as well as the precision in selection with varied levels of N is 23 University of Ghana http://ugspace.ug.edu.gh essential in discovering the right breeding strategies (Garnett et al., 2015). Understanding the mechanism associated with NUE in terms of the relationship with morphological and physiological traits would aid in simplifying and improving NUE’s selection efficiency as it is a complex trait (Hirel et al., 2007). Therefore, the heritability of traits related to NUE and its components (NUpE & NUtE) under different N levels is important. Indeed, this has been investigated in several studies in irrigated or rainfed low land rice in Asia (Inthapaya et al., 2000; Koutroubas & Ntanos, 2003; Haefele et al., 2008; Wu et al., 2016). However, previous studies revealed that different levels of nitrogen affects growth, yield and NUE components. Haque & Haque (2016) investigated the growth, yield and NUE of a new rice variety under six levels of nitrogen (0, 20, 40, 60, 80 & 100 kg/ha). Number of tillers, grain per panicle, panicle number and yield increased with increasing N but was higher at 60 kg/ha of N. In Ethiopia, twelve upland rice varieties under 0 and 64 kg/ha of nitrogen had higher grain yield, number of field spikelets, harvest index and grain N concentration as nitrogen increased. However, NUE declined at 64 kg/ha of nitrogen implying poor nitrogen absorption by the genotypes. Heritability estimates were also high indicating high variations among the varieties (Lakew, 2015). Interactions between N and genotypes were not significant except for flowering, grain N concentration, harvest index, NUE and NUtE in a study carried out by Rakotoson et al. (2017) in thirteen varieties under two contrasting levels of N fertilizer (0 kg/ha and 90 – 120 kg/ha). The traits that where influenced by N fertilizer where associated with N uptake and biomass production. Furthermore, panicle number increased when N was applied. 24 University of Ghana http://ugspace.ug.edu.gh Studies carried out on the function of roots in nitrogen assimilation indicates its importance to the growth of rice plants. To buttress the preceding point, studies show that root growth of super hybrid cultivars tends to decrease when subjected to high N treatment (Hu et al., 2017; Liu et al., 2018). Gallias & Coque (2006) observed that maize cultivated under either high or low N, had root architecture being a controlling factor on grain yield. This illustrates the underpinning significance of root traits in NUE. Hamoakoa et al., (2013) studied six rice cultivars under standard and low N conditions in laboratory conditions. Total dry weigh of straw were lighter under low N (LN), conversely, root dry weight and NUE increased under LN as compared to the standard N condition. Highlight from several studies showed positive or negative significant correlation between NUE and some morphological traits. A negative association among NUtE, grain and straw N concentrations has been described (Inthapanya et al., 2000; Koutroubas and Ntanos, 2003; Samonte et al., 2006; Wu et al., 2016). With respect to grain yield, an earlier study indicated a strong association between grain yields of rice and NUE (Haefele et al., 2008). Kumar (2016) recorded high heritability for plant height, number of productive tillers, panicle length, number of spikelets per panicle, grain yield per plant and NUE at low N conditions (50 % of the recommended level of N in irrigated conditions. Ju et al. (2015) found a significant genotype x nitrogen interaction for grain yield and N uptake in irrigated conditions. They associated the high NUE of two lowland japonica varieties with greater root biomass, deeper root distribution, longer root length and greater root oxidation activity. It is evident that nitrogen assimilation plays a central part in NUE for rice, as it accounts for 70 – 90 % of the total N in the grain (Tabuchi et al., 2007). Rao et al. (2018) studied NUE on rice landraces in Asia and they were able to identify donors for high N uptake and N translocation into grain and grain yields under low N. Numerous spikelets on 25 University of Ghana http://ugspace.ug.edu.gh the secondary branches, increase in N content in grain and yield seems to be associated low N. Identification of NUE has been carried out in Ethiopia and Burkina Faso (Lakew, 2015; Segda et al., 2014). Through selection and plant breeding techniques, resilient rice varieties against some biotic and abiotic stress are in the production pipeline. Similar achievement can be done through firstly screening for nitrogen efficient rice crops in Ghanaian rice landraces. 26 University of Ghana http://ugspace.ug.edu.gh CHAPTER THREE 3 MATERIALS AND METHODS 3.1 Description of the study area The experiment was carried out in the research farm of the Crop Science Department in the University of Ghana, Legon. The site has geographical co-ordinates of 5° 39 N, 0° 539 W in the Greater Accra region of Ghana and a gentle topography of 0.30. The region experiences a bi-modal seasonal rainfall pattern with an annual average precipitation which ranges between 700-1000 mm. The major and minor rainfall seasons start from April to July and September to December, respectively. The average annual temperature recorded at the site during the period is about 26.9 °C, with a maximum temperature of 33.3 oC and minimum temperature of 22.1 oC. The relative humidity for the night ranges from 60 to 90 % while in the day its ranges from 20 to 55 % throughout the year. The soil type is savanna ochrosol locally called Toje series which has been classified by Eze, (2008) as a Rhodustalf and Rhodic Lixisol according to USDA (1999, 2003). Toje series is among the most widely cultivated soils of the Accra Plains. Toje is developed on Quartzite schist (Fiagbedzi, 1989). 27 University of Ghana http://ugspace.ug.edu.gh 3.2 Plant material This comprised a set of twenty (20) landraces which were obtained from the Plant Genetic Resources Research Institute, Bonsu (Appendix 1). These genotypes varied in origin, cultivar type, plant height, and average growth duration. 3.3 Soil sampling and analysis A soil auger was used to collect soils at a depth of 0-15 cm. The following soil properties were analyzed before the experiment; pH, electrical conductivity (EC), soil texture, nitrogen (N), potassium (K), phosphorus (P) and carbon (C) (Table 3.1). Table 3.1: Physical and chemical properties of soil in the experimental site Soil properties Value pH 6.5 Electrical conductivity(ds/m) 0.04 Phosphorus (mg/kg) 30.1 Potassium (cmol/kg) 0.79 Carbon (%) 2.99 Nitrogen (%) 0.13 Soil particle size Value Sand (%) 56 Clay (%) 25 Silt (%) 19 Soil textural class Sandy clay loam 28 University of Ghana http://ugspace.ug.edu.gh 3.4 Pot experiment Pot experiment was conducted under natural temperature and sunlight in order to mimic the field experiment and compare the outcome under both conditions. Soil bags of 23 cm in width and 20 cm in length, were used for the experiment. The total number of pots used was 120. The soil was garnered from an uncultivated field at a depth of 0 – 15 cm. Roots and other plant debris were removed from the soil. The soil was subsequently crushed and sieved through 2 mm size mesh to obtain fine earth fraction. Five kilogram (5 kg) of the soil was weighed into each pot. The site for the pot experiment was cleared using cutlass and a hoe. Plastic sheets were used to cover the area to avoid soil micro infestation and reduce weeds proliferation. The trial was carried out from February 2019 to June 2019. The experimental design was a completely randomized design arranged in a factorial manner and replicated three times. Forty combinations of treatments were compared (20 landraces × 2 levels of fertilization) with three seeds sown in each pot. Two increasing doses of N namely; available N (no N) and low N (50 kg/ha) were applied. Nitrogen fertilizer was applied in two split doses: 50 % at tillering (25 kg/ha) and 50 % at panicle initiation (25 kg/ha). Other major nutrients such as P and K, were applied to all pots at 90 kg/ha. P in the form of triple superphosphate and K in the form of potassium chloride were applied in two split applications; tillering (45 kg/ha) and panicle initiation (45 kg/ha). Plants were watered on a daily basis to maintain moisture in the soil. 29 University of Ghana http://ugspace.ug.edu.gh 3.5 Field experiment The field experiment was conducted using a split plot design with three replicates. This was carried out from February to June 2019. Plot size was 2 m by 1.7 m. Beds were raised and the spacing between each bed and row was 70 cm with an alley of 1m between blocks. Two doses of N (0 and 50 kg/ha) constituted the main plot treatments while the subplots were represented by the 20 rice landraces. The seeds were sown directly into the soil and were maintained at 4 to 6 seeds per bed. Nitrogen fertilizer was applied in two split doses: 50 % at tillering (25 kg/ha) and 50 % (25 kg/ha) at panicle initiation. Other major nutrients such as P and K, were applied to all pots at 90 kg/ha. P in the form of triple superphosphate and K in the form of potassium chloride were applied in two split applications; tillering and panicle initiation stage. Plants were watered on a daily basis to maintain moisture in the soil. The trial was conducted in an upland condition during the rainy season. The plants were watered on rainless days. For the control of weeds, manual weeding of the alleys and hand weeding of the beds was done when necessary. 3.6 Phenotypic data scored In both pot and field experiments, data collection was conducted 3 times during the entire growth period at the following stages: active tillering (when the plant attained the first 3 tillers), heading (when panicle primordia starts protruding) and harvesting (when about 80 % of the spikelets were straw-coloured) sensu Getachew & Nabiyu (2018). For each sampling, three representative plants (in pot experiments) or hills (in field trials) for each landrace were garnered. 30 University of Ghana http://ugspace.ug.edu.gh 3.6.1 Agro-morphological characterization Agro-morphological characterization was implemented to distinguish among the landraces and to record vegetative data to facilitate comparison among the landraces. Agro-morphological evaluation was monitored in the pot experiment using 13 quantitative and 17 qualitative rice descriptors in accordance with the method described by Bioversity International et al. (2007) (Table 3.2). Table 3.2: List of agro morphological traits scored Qualitative trait Quantitative trait Awn presence Awn length Awn color Culm diameter Auricle color Culm number Culm habit Days to flowering Culm kneeing ability Days to maturity Culm diameter Flag leaf length Culm lodging resistance Flag leaf width Culm strength Ligule length Caryopsis color Leaf blade length Caryopsis shape Leaf blade width Leaf blade pubescence Hundred grain weight Leaf blade width type Panicle length Leaf blade length type Panicle number Lemma and palea color Panicle attitude Panicle exertion Stigma color 31 University of Ghana http://ugspace.ug.edu.gh 3.6.2 Growth, yield related traits and NUE components Data was accrued from the pot experiment for only growth parameters to avoid bias. This is because root destruction was only carried out in the pot experiment. Conversely, both pot and field data was taken for yield related traits and NUE components. During active tillering, chlorophyll content was recorded using a chlorophyll meter, SPAD-502 Plus (Konica Minolta, INC). Chlorophyll was recorded on five leaves and averaged. Leaf length was recorded from the base of the leaf sheath to the tip and leaf width was measured within the center of the leaf using a 30 cm meter rule. At maturity, number of tillers were counted and plant height was measured using a 30 cm meter rule. Furthermore, roots from potted plants marked for destructive sampling were gently removed, thoroughly washed and separated from shoot portion with knife. The root length was measured using a 30 cm meter rule from the base of the stem to the tip of the root. The roots were dried in an oven at 60˚C for 72 h until constant weight was obtained and was expressed in grams. Plants were reaped and disjointed into straw and panicle at maturity. Filled grains (spikelets) were separated from empty grains, oven dried at 60˚C for 72 h and weighed. Filled grains were used to evaluate grain yield (GY) and grain N concentration (GNC). 250 filled grains and 250 empty grains were weighed for the estimation of the total number of filled and empty grains. Straw samples were oven dried at 60 °C for 72 h and weighed to measure straw yield (SY). The harvest index (HI) was enumerated from GY and SY (Table 3). NUE, NUpE, NUtE were calculated sensu Moll et al. (1982) (Table 3). 32 University of Ghana http://ugspace.ug.edu.gh Table 3.3: Description of the 15 measured and calculated yield and NUE related traits Code Trait Formula Unit FG Filled grain 100 × FG / total number of spikelets % GNC Grain N concentration Grain N concentration of 3 hills at maturity % GY Grain yield PN × SPIPAN × FG × TGW kg/ha HI Harvest Index GY/(GY + SY) - kg grain kg/N NUE Nitrogen use efficiency GY/N supply kg N kg/N NUpE Nitrogen uptake efficiency TNUP/N supply kg grain kg/N NUtE Nitrogen utilization efficiency GY/TNUP - PN Number of panicles Mean of panicle number of 3 hills SNC Straw N concentration SNC of 3 hills at maturity % SPIPAN Number of spikelets per panicle Mean of number of spikelets of 3 hills - SY Straw Yield Biomass of 9 hill kg/ha TGW 1000-grain weight Weight of 250 filled spikelets × 4 g TNUP Total plant N uptake GNC × GY + SNC × SY kg/ha RL Root length Measured from base of stem to tip of roots cm RW Root weight Weight of oven dried roots g 3.6.3 Tissue nitrogen concentration N concentration in the leaf blades, sheaths plus stems and panicles were analyzed by the Kjeldahl procedure using the standard protocol (Piper, 1966). The straw and grain samples were oven dried at 65˚C for 72 h and pulverized separately into fine powder. 0.1g of the samples was used for the analysis. The percent N was calculated using the formula below: (𝑇𝑖𝑡𝑟𝑒 𝑣𝑎𝑙𝑢𝑒−𝐵𝑙𝑎𝑛𝑘)∗1400 % TN = 𝑤𝑒𝑖𝑔ℎ𝑡∗5∗1000 33 University of Ghana http://ugspace.ug.edu.gh 3.7 Statistical Analysis 3.7.1 Germplasm characterization Phenotypic diversity of the landraces was estimated using Shannon-Weaver diversity index (Hˊ) (Sotto & Rabara, 2007). Based on an arbitrary scale adapted from Jamago & Cortes (2012), indices were divided into maximum (Hˊ= 1.00), high (Hˊ = 0.76 – 0.99), moderate (Hˊ = 0.46 – 0.75) and low diversity (0.01– 0.45). This was calculated based on the method used by Lexerød & Eid (2006): Hˊ = pi (log2 pi)/log2 N pi = frequency proportion of the descriptor state N = number of states The standardized Shannon-Weaver provided a constrained index between zero and one with the highest value indicating maximum abundance (Jamago & Cortes 2012). Correlation, cluster and principal component analysis were carried out using Minitab® 19 statistical analysis package. 3.7.2 Growth parameters, yield and NUE components Analysis of variance was carried out using GENSTAT statistical analysis package (version 12) Sources of variation such as genotype, N level, replication and the interaction of genotype × N level were used in the statistical model. These were considered as fixed effects (genotype, N level, replication, genotype × N). A significant level of p ≤ 0.05 was computed and a Post Hoc test for values with p ≤ 0.05 using Turkey’s test was carried out. Pearson phenotypic correlation coefficients based on means of varieties over replicates were calculated for all traits using Minitab® 19 statistical analysis package. Correlation coefficients were classified as weak (r = 0.35), moderate (r = 0.36) and strong (r > 0.68) (Taylor, 1990). 34 University of Ghana http://ugspace.ug.edu.gh 3.7.3 Estimates of variance components The population’s variability were estimated using the mean, phenotypic and genotypic variance and coefficient of variation. To estimate the phenotypic and genotypic variance, phenotypic and genotypic coefficients of variation were calculated sensu Rosmania et al. (2016) as follows: σ2 G = [(MSG) – (MSE)] / r σ2 P = [σ2 G + (σ2 E/r)], Where: σ2 G = Genotypic variance; σ2 P = Phenotypic variance; σ2 E = environmental variance (error mean square from the analysis of variance); MSG = mean square of genotypes; MSE = error mean square; r = number of replications. Genotypic coefficient of variation (GCV) = (σ2 G) 1/2/x) × 100; Phenotypic coefficient of variation (PCV) = (σ2 P) 1/2/X) × 100, where: σ2 G = Genotypic variance; σ2 P = Phenotypic variance; X is grand mean of a character. Broad-sense heritability (H2) for all traits at each level of N was calculated from variance components using the formula: H = σ2 2G/σ P, 35 University of Ghana http://ugspace.ug.edu.gh CHAPTER FOUR 4 RESULTS 4.1 Characterization of landraces 4.1.1 Diversity in qualitative traits in pot experiment Based on the qualitative traits recorded, ligule shape and culm kneeing ability were invariables. This implies that all the landraces characterized had a 2-cleft ligule shape and the culms had no kneeing ability (Table 4.1). Eight of the traits scored were predominated by one character in each trait with a distribution ranging between 78 % - 95 %. These included awn related characters (awn presence and color). Most of the landraces had dense culms and upright culm habit. Moderately diverse traits were observed for six descriptors with indices ranging between 0.46 - 0.70. Most of these traits were inflorescence related such as panicle and spikelet characters. Diversity in seed coat color was evident. These were white seed coat (60 %), red (10 %), light brown (20 %) and black (10 %). Two out of the 19 traits had high diversity with a mean index of 0.82. These traits were culm-related which measured rice hardiness during maturity and harvest. Though, the principal character was intermediate lodging resistance, 35 % of the landraces had strong to very strong lodging resistance at maturity (Table 4.1). 36 University of Ghana http://ugspace.ug.edu.gh Table 4.1: Qualitative traits showing the predominant state observed, distribution (%) and the calculated Shannon diversity indices (Hʹ) for each descriptor scored in pot experiment. Descriptor Predominant State % Hʹ index Invariant Ligule shape 2-cleft 100.00 0.00 Culm kneeing ability Strong 100.00 0.00 Low diversity Awn presence Awnless 94.03 0.11 Awn color (late observation) Awnless 94.04 0.12 Leaf blade pubescence Intermediate 95.20 0.12 Culm diameter type Thick 91.10 0.12 Culm habit Erect (< 15˚) 84.08 0.26 Auricle color Whitish 89.05 0.31 Panicle attitude Drooping 84.11 0.32 Stigma color White 78.12 0.45 Moderate diversity Lemma and Palea color Straw 57.09 0.46 Leaf blade width type Intermediate (~ 50 cm) 61.12 0.55 Leaf blade length type Intermediate 60.01 0.54 Panicle exertion Well exerted 54.13 0.67 Caryopsis pericarp color (seed coat color) White 50.18 0.68 Caryopsis shape Long spindled shape 43.03 0.70 High diversity Culm lodging resistance Intermediate 39.03 0.80 Culm strength Intermediate 42.11 0.83 Average diversity 0.33 37 University of Ghana http://ugspace.ug.edu.gh 4.1.2 Diversity in quantitative traits in pot experiment Awn length and Ligule length were the only traits that portrayed low diversity (Table 4.2). Only five landraces exhibited awns in their grains (GH 1531, GH 1552, GH 2145, GH1599 and GH 1514). GH2145 had the shortest awn length (0.6 cm) while GH1552 and GH1514 had the longest awn length (3.5cm). Ligule length was observed to be the longest (3.5 cm) in two out of 20 landraces (GH 1538; GH 1574). The shortest ligule length was demonstrated by GH1574 which had a length of (0.5 cm). Culm diameter was the only trait which exhibited moderate diversity (0.52). Ten out of the 13 quantitative traits had high diversity with a diversity index ranging from 0.72 – 0.90 (Table 4.2). It was observed that GH2145 had the shortest flag leaf length (16.00 cm) while GH1538 had the longest flag leaf length (26.90 cm). Maturity of the characterized germplasm ranged from 55 – 105 days. GH1514 had the shortest days to maturity while GH 1519 had the longest days to maturity. Grain weight diversity was observed in the germplasm with GH 1550 having the lightest grain weight (1.00 g) and GH2145 having the heaviest grain weight (2.20 g). Two varieties had equal number of panicle and culm number with GH1550 recording the lowest number (8) and GH2145 recording the highest number (33). In a nut shell, the mean index was 0.70. Almost all the traits measured exhibited moderate to high diversity. 38 University of Ghana http://ugspace.ug.edu.gh Table 4.2 Quantitative descriptors and calculated Shannon-Weiner index (Hʹ) of evaluated rice landraces in pot experiment Descriptors Hʹ Min. Variety Max. Variety Mean Trait Trait (± Standard Value Value deviation) Low diversity Ligule length (cm) 0.11 0.50 GH1574 1.10 GH1552 0.89 ± 0.23 Awn length (cm) 0.12 0.60 GH2145 3.50 GH1514; GH1552 0.43 ± 1.05 Moderate diversity Culm diameter (cm) 0.52 0.40 Aunty Jane 1.20 GH1515 0.54 ± 0.06 High diversity Flag leaf length (cm) 0.72 16.00 GH2145 26.90 GH1538 20.67 ± 3.26 Leaf blade length(cm) 0.78 23.50 GH1514 40.10 GH1583 32.14 ± 5.01 Flag leaf width (cm) 0.82 0.80 GH1801 1.80 GH1552 1.09 ± 0.23 Flowering (days) 0.85 40.00 GH1514 79.00 GH1519 54.70 ± 9.88 Leaf blade width (cm) 0.85 0.50 AUNTY JANE 1.10 GH1549 0.85 ± 0.18 Maturity (days) 0.87 55.00 GH1514 105.00 GH1519 85.00 ± 13.88 Culm number 0.88 8.00 GH1550 33.00 GH2145 18.05 ± 6.96 100 Grain weight(g) 0.88 1.00 GH1552 2.00 GH2145 1.44 ± 0.30 Panicle length 0.89 18.00 GH1822 26.50 GH2145 20.91 ± 2.42 Panicle number 0.90 8.00 GH1550 33.00 GH2145 18.05 ± 6.96 Average diversity 0.70 39 University of Ghana http://ugspace.ug.edu.gh 4.1.3 Correlation among traits in pot experiment 76 % of the trait combinations had weak correlations while 14 % had moderate correlations. Several traits showed significant correlations (p ≤ 0.05, ≤ 0.01) among each other. Two of these trait combinations had strong correlation; panicle number per plant with culm number (r = 0.97) and number of days to main heading with number of days to maturity (r = 0.89), while 7 trait combinations had moderate correlations. These were: flag leaf width with leaf blade length (r = 0.53), number of days to maturity with culm number (r = 0.53), culm length with leaf blade length (r = 0.52), number of days to maturity with ligule length (r = 0.48), number of days to maturity with panicle number (r = 0.47), number of days to main heading with leaf blade length (r = 0.46) and panicle length with flag leaf length (r = 0.46) (Table 4.3). Table 4.3: Correlation matrices of the 20 quantitative variables in pot experiment LL LBL LBW FLL FLW CL CN CD PN PL NDMH NDM LBL 0.26ns LBW -0.19n 0.18ns FLL 0.22ns 0.36ns 0.24ns FLW 0.43ns 0.53* 0.36ns 0.38ns CL 0.15ns 0.52* 0.28ns 0.31ns 0.35ns CN 0.33ns 0.10ns -0.47ns 0.33ns 0.03ns 0.07ns CD -0.06ns 0.23ns 0.15ns 0.06ns 0.06ns 0.28ns 0.18ns PN 0.29ns 0.02ns -0.45ns 0.32ns 0.06ns 0.07ns 0.97** 0.14ns PL 0.08ns 0.36ns 0.20ns 0.46* 0.05ns 0.31ns 0.14ns 0.09ns 0.13ns NDMH 0.44ns 0.46* -0.10ns 0.03ns 0.34ns 0.02ns 0.41ns 0.16ns 0.36ns 0.19ns NDM 0.48* 0.30ns -0.15ns 0.21ns 0.25ns 0.19ns 0.53* 0.13ns 0.47* 0.32ns 0.89** HGW -0.48ns 0.31ns 0.20ns 0.02ns 0.42ns 0.14ns 0.20ns 0.06ns 0.13ns 0.41ns -0.77ns -0.77ns ∗, ∗∗, ns are significant at the 5 and 1% probability level and non- significant, respectively LL: Ligule length NDMH: Number of days to main heading LBL: Leaf blade length NDM: Number of days to maturity LBW: Leaf blade width HGW: 100-grain weight FLL: Flag leaf length CN: Culm number FLW: Flag leaf width CL: Culm length CD: Culm diameter PN: Panicle number PL: Panicle length 40 University of Ghana http://ugspace.ug.edu.gh 4.1.4 Cluster and principal component analysis among rice landraces in pot experiment A dendogram was generated for the 20 rice landraces based on their observable characters. At a similarity index of 67%, the landraces were grouped into 5 clusters (Figure 4.4). Cluster 1 had the largest number of landraces. These landraces were peculiar for their light grain weight. Cluster 2 and 1 were similar in ligule length and culm diameter except that cluster 2 had longer leaf length and flag leaf length. Cluster 3 were early maturing, had heavier grain weight and highest panicle number. The fourth cluster had 2 genotypes which had the longest days to maturity and longest culms which implies that they were tall plants. Cluster 5 were shorter due to their culm length and had longer panicle length. Figure 4.1: Dendogram generated by cluster analysis based of morphological characters in pot experiment 1: GH1549 6: GH1550 11: GH1531 16: GH1590 2: GH1587 7: GH1515 12: GH2145 17: GH1583 3:GH1574 8: GH1552 13: GH 1801 18: GH1599 4: GH1822 9. GH1535 14: GH1519 19: GH 1516 5:GH1514 10. GH 1538 15: GH 1599 20: Aunty Jane 41 University of Ghana http://ugspace.ug.edu.gh 4.1.5 Principal component analysis based on the 14 quantitative traits Principal component analysis was carried out to describe the relative contribution of the different traits to the total variation in the landraces. Four significant principal components were identified and accounted for 71.9 % of the total variation. The first component accounted for 28.9 % of the total variation while the second, third and fourth components contributed 28.9 %, 21.8 %, 11.6 % and 9.6 % respectively (Table 4.4). Quantitative traits such as ligule length, culm number, panicle number, number of days to main heading and number of days to maturity contributed positively to the variations in PC1 (Table 4.4). Leaf blade length, flag leaf length, flag leaf width and culm number, positively correlated with PC2. PC3 was associated with culm diameter and awn length. In the fourth component, culm diameter had a high loading of 0.31. Table 4.4: Principal components analysis based on the 14 quantitative trait Variable PC1 PC2 PC3 PC4 Ligule Length 0.306 0.190 0.211 0.014 Leaf Blade Length 0.177 0.395 -0.122 -0.258 Leaf Blade Width -0.180 0.291 -0.290 0.079 Flag Leaf Length -0.086 0.411 0.052 -0.147 Flag Leaf Width 0.161 0.424 -0.004 0.113 Culm Length -0.019 0.381 0.244 -0.228 Culm Number 0.364 -0.196 0.270 -0.336 Culm Diameter -0.087 0.173 0.303 0.307 Panicle Number 0.328 -0.223 0.302 -0.333 Awn Length -0.064 0.217 0.612 0.178 Panicle Length -0.160 0.179 -0.207 -0.587 Number of Days to Main heading 0.426 0.120 -0.243 0.013 Number of Days to Maturity 0.453 -0.000 -0.200 0.114 Grain weight -0.381 -0.129 0.147 -0.365 Eigenvalue 4.05 3.06 1.61 1.34 Proportion 0.29 0 . 2 2 0 . 1 2 0 . 0 9 Cumulative 0.29 0.51 0.62 0 . 7 2 42 University of Ghana http://ugspace.ug.edu.gh 4.2 Response of different accessions to different nitrogen levels in pot experiment Observations from the twenty genotypes indicated that there were significant differences (p ≤ 0.05)for all the growth parameters under two levels of nitrogen application (Tables 4.5, 4.6, 4.7). The genotype by nitrogen interaction (G × N) was significant for all the traits. Root length was influenced significantly by the two nitrogen levels among the genotypes. However, the longest root length was recorded for Aunty Jane variety (60.00 cm) when no nitrogen was applied while the shortest root length was recorded for variety GH1531 at 50 kg/ha of nitrogen application (Table 4.5). Significant differences in root dry weight was observed under different levels of nitrogen among the genotypes. The heaviest root dry weight was recorded for GH1552 (95.00 g) when nitrogen was applied while the lightest was noted in variety GH1514 (6.00 g) at 0kg/ha of nitrogen (Table 4.5). Different levels of nitrogen affected the leaf length of the genotypes significantly. Variety GH1549 had the longest leaf length (49.00 cm) when 50 kg/ha of nitrogen was applied while variety GH1514 had the shortest leaf length (23.17 cm) when nitrogen was not applied. However GH1515 remained constant (32.00 cm) across the two levels of nitrogen (Table 4.5). Leaf width was affected noticeably with the addition of nitrogen fertilizer. The maximum leaf width was recorded in variety GH1587 (1.70 cm) when 50 kg/h of nitrogen was applied while the minimum was variety GH1531 (0.60 cm) with no nitrogen application (Table 4.5). 43 University of Ghana http://ugspace.ug.edu.gh Significant differences were observed for number of leaves. Number of leaves increased as nitrogen level increased. GH2145 had the highest leaf number (60.00) when N was applied while GH1549 and GH1589 had the lowest number of leaves (7.00) (Table 4.6) Under different levels of nitrogen, plant height differed significantly with variety GH1552 having the highest plant height of 144.50 cm at 50 kg/ha of nitrogen while the shortest observed plant height was 78.00 cm from varieties GH1574 and GH1599 in the absence of nitrogen application (Table 4.6). Due to variations in nitrogen levels, chlorophyll concentrations differed significantly. It increased (44.53) when N was 50 kg/ha in variety GH1549 while the minimum was from GH1531 at 0 kg/ha of nitrogen (Table 4.6). Number of tillers significantly increased (30.00) when nitrogen was applied in variety GH2145 while variety GH1549 recorded the minimum tiller number of 7.00 (Table 4.7). Different levels of nitrogen fertilizer affected shoot dry weight significantly. Variety GH1587 had the maximum shoot dry weight of 35.00 g when nitrogen was applied while variety GH1514 had the minimum shoot dry weight of 6.00 g without nitrogen fertilizer (Table 4.7). Grain yield significantly increased when nitrogen was applied at 50 kg/ha. This was observed in variety GH2145 with 8035 kg/ha of yield having the highest grain yield while GH1549 had the lowest grain yield of 357.00 kg/ha when nitrogen was not applied (Table 4.7). 44 University of Ghana http://ugspace.ug.edu.gh Table 4.5: Effect of two nitrogen levels on root length and dry weight, leaf length and width of twenty rice landraces in pot experiment Root length (cm) Root dry weight (g pot-1) Leaf length (cm) Leaf width (cm) Genotype No N Low N Mean No N Low N Mean No N Low N Mean No N Low N Mean GH1549 40.00cd 42.00gh 41.00 30.00e 45.00d 37.50 26.23b 49.00k 37.62 1.03cd 1.60ef 1.31 GH1587 38.00bc 35.00de 36.50 75.00l 81.00j 78.00 36.17gh 44.00hi 40.08 1.03cd 1.70f 1.36 GH1574 42.00de 46.00i 44.00 55.00j 83.00j 69.00 27.00bc 35.00de 31.00 0.90bcd 1.10c 1.00 GH1822 43.00de 39.00fg 41.00 25.00d 37.00c 31.00 33.00f 46.00ij 39.50 1.11d 1.40de 1.25 GH1514 44.00ef 30.00ab 37.00 6.00a 10.00a 8.00 23.17a 42.17fg 32.67 0.70ab 1.10c 0.90 GH1550 47.00f 38.00ef 42.50 11.00b 25.00b 18.00 29.00cd 29.17ab 29.08 0.70ab 1.40de 1.05 GH1515 32.00a 57.00k 44.50 66.67k 95.00k 80.84 32.00ef 32.00c 32.00 0.80abc 0.80ab 0.80 GH1552 42.00de 50.00j 46.00 85.33m 95.67k 90.50 39.00i 42.00fg 40.50 1.10d 1.00bc 1.06 GH1535 40.00cd 38.00ef 39.00 39.00g 57.00f 48.00 34.00fg 58.17l 46.08 0.9bcd 1.50ef 1.20 GH1538 35.00ab 29.00ab 32.00 15.00c 27.00b 21.00 36.53gh 31.00bc 33.77 1.00cd 1.50ef 1.25 GH1531 43.00de 27.00a 35.00 50.00hi 75.00i 62.50 30.17de 35.00de 32.58 0.66a 0.60a 0.60 GH2145 43.00de 33.00cd 38.00 52.00i 62.67g 57.34 26.00b 33.00cd 29.50 1.00cd 1.01c 1.06 GH1801 40.00cd 35.00cd 37.50 66.00k 85.00j 75.50 33.00f 41.00fg 37.00 0.60a 1.00bc 0.81 GH1519 43.00de 40.00fg 41.50 35.00f 40.00c 37.50 38.03hi 37.00e 37.50 0.80abc 0.80ab 0.80 GH1599 40.00cd 40.00fg 40.00 58.00j 63.00g 60.50 38.00hi 47.00jk 42.50 0.80abc 0.97bc 0.88 GH1590 33.00a 35.00de 34.00 36.00fg 49.00de 42.50 36.00gh 43.00gh 39.50 0.97bcd 1.20cd 1.08 GH1583 43.00de 30.00ab 36.50 30.00e 68.00h 49.00 36.03gh 40.50fg 38.27 0.80abc 1.50ef 1.15 GH1599 35.00ab 38.00ef 36.50 49.00hi 64.00gh 56.50 37.00hi 40.00f 38.50 0.80abc 1.20cd 1.00 GH1516 47.00f 32.00bc 39.50 29.00e 50.00e 39.50 27.00bc 35.00de 31.00 0.80abc 1.00bc 0.91 Aunty Jane 60.00g 43.00hi 51.50 48.00h 74.00i 61.00 29.00cd 27.00a 28.00 0.97bcd 1.00bc 1.00 Mean 41.5 37.85 45.20 59.32 32.35 39.35 0.87 1.18 G N ** ** ** ** G × N ** ** ** ** CV (%) ** ** ** ** 2.5 6.8 2.5 8.9 G: genotype, N: nitrogen, CV: coefficient of variation Means followed by the same letter in the same column are not significantly different at the 5% probability level by Tukey’s test. ** Significant at p = 0.001 45 University of Ghana http://ugspace.ug.edu.gh Table 4.6: Effect of two nitrogen levels on number of leaves, plant height and chlorophyll of twenty rice landraces in pot experiment Number of leaves (No) Plant height (cm) Chlorophyll Genotype No N Low N Mean No N Low N Mean No N Low N Mean GH1549 15.00ab 45.00cde 28.50 82.50b 92.00c 87.25 30.50i 44.53j 37.52 GH1587 16.00bc 38.00bc 27.50 111.50j 138.5n 125.00 25.13g 46.00j 35.57 GH1574 17.00bcd 48.67cdef 32.50 78.00a 82.00a 80.00 20.20cd 35.63cde 27.92 GH1822 22.00efg 60.00hi 35.50 95.53e 116.00k 105.77 28.00h 34.63c 31.32 GH1514 16.00bc 26.67a 17.83 95.00e 110.5ij 102.77 19.63bcd 37.07ef 28.35 GH1550 25.00g 40.00cd 28.67 82.00b 100.50fg 91.25 23.13f 34.00c 28.57 GH1515 20.00def 51.00efgh 31.00 96.57e 102.0g 99.28 23.63fg 41.13hi 32.38 GH1552 24.00g 54.00efgh 36.00 124.50k 144.50m 124.50 34.13j 39.53gh 36.83 GH1535 20.00def 59.33ghi 38.67 104.50gh 120.00l 112.25 19.50bcd 35.23cd 27.37 GH1538 24.00g 57.67fghi 35.67 106.50hi 113.0j 109.75 27.30h 40.63hi 33.97 GH1531 20.00def 66.00i 38.17 88.53d 89.00b 88.77 17.03a 30.37a 23.70 GH2145 30.00h 67.00i 43.00 101.00f 105.00h 103.00 18.20ab 38.00fg 28.10 GH1801 25.00g 59.00fghi 39.50 103.60g 123.50m 113.55 18.63abc 41.50i 30.07 GH1519 18.00bcd 48.00cdef 30.00 107.00i 110.00i 108.5 18.00ab 29.60a 23.80 GH1599 12.00a 28.00ab 20.00 88.00d 92.00c 90.00 19.56bcd 38.00fg 28.78 GH1590 19.00cde 20.00a 14.50 81.33b 95.00d 25.10g 39.50gh 32.30 88.17 GH1583 15.00ab 25.00a 19.50 87.50d 98.00ef 22.53ef 37.07ef 29.80 92.75 GH1599 12.00a 28.00ab 20.00 78.00a 80.00a 24.10fg 32.27b 28.18 79.00 GH1516 19.00cde 27.00ab 21.00 85.00c 90.00bc 27.57h 36.63def 32.10 87.50 Aunty Jane 23.00fg 38.00bc 24.50 95.00e 97.00de 21.00de 41.07hi 31.03 96.00 Mean 13.88 44.32 94.58 103.93 23.15 37.62 G ** ** ** N ** ** ** G × N ** ** ** CV (%) 0.8 9.4 1.8 G: genotype, N: nitrogen, CV: coefficient of variation. Means followed by the same letter in the same column are not significantly different at the 5% probability level by Tukey’s test. ∗∗ Significant at p = 0.001. 46 University of Ghana http://ugspace.ug.edu.gh Table 4.7: Effect of two nitrogen levels on number of tillers, shoot dry weight and grain yield of twenty rice landraces in pot experiment Genotype Number of tillers (No) Shoot dry weight (g pot-1) Grain yield (kg/ha) No N Low N Mean No N Low N Mean No N Low N Mean GH1549 7.00a 15.00ab 11.00 11.00cd 20.00c 15.50 357.00a 2970.00m 1664.00 GH1587 9.00abcd 16.00b 12.33 30.00i 35.00g 32.50 1117.10m 1459.00d 1288.00 GH1574 7.00ab 17.00bcd 12.17 22.00efg 28.00ef 25.00 597.10e 1449.00d 1023.00 GH1822 12.00def 23.00efg 17.00 19.00e 30.00f 24.50 1676.10o 2841.00l 2259.00 GH1514 8.00abc 17.00bc 12.00 6.00a 11.00a 8.50 957.50j 1173.00b 1065.00 GH1550 25.00g 25.00g 25.00 25.00gh 28.00ef 26.50 1099.00l 4703.00p 2901.00 GH1515 11.00cdef 21.00def 15.5 10.00bcd 25.00de 17.50 1024.00k 3564.00o 2294.00 GH1552 12.00def 24.00g 18.00 23.00fg 30.00f 26.50 699.10g 2448.00j 1574.00 GH1535 8.00abc 21.00def 14.00 13.00d 24.00d 18.50 1160.10n 2995.00m 2078.00 GH1538 10.00abc 23.00g 17.00 10.00bcd 13.00ab 11.50 703.00h 1921.00i 1308.00 GH1531 10.00abc 20.00def 15.17 9.00abc 16.00b 12.50 679.00f 1792.00h 1236.00 GH2145 14.00f 30.00h 22.00 21.00ef 31.00f 26.00 2092.10r 8035.00q 5064.00 GH1801 13.00ef 25.00g 19.00 20.00ef 23.00cd 21.50 1970.00q 2800.00k 2385.00 GH1519 9.00abcd 18.00bcd 13.5 19.00e 28.00f 23.50 599.20e 1652.00f 1126.00 GH1599 8.00abc 14.00a 10.00 8.00abc 15.00b 11.50 450.00b 627.00a 539.00 GH1590 12.00def 19.00cde 15.5 28.00hi 35.00g 31.50 1785.00p 3420.00n 2602.00 GH1583 9.00abcd 15.00ab 12.00 13.00d 31.00f 22.00 579.20d 1741.00g 1160.00 GH1599 10.00abc 18.00bcd 14.00 7.00ab 10.00a 8.50 576.00c 1359.00c 968.00 GH1516 11.00cdef 19.00cde 15.00 13.00d 22.00cd 17.50 779.10i 1539.00e 1159.00 Aunty Jane 12.00def 24.00fg 17.5 11.00cd 16.00b 13.50 699.10g 3002.00m 1850.00 Mean 1 0.88 19.88 15.90 23.55 979.94 2574.08 ** G ** ** ** N ** ** ** G × N ** 5.1 ** CV (%) 6.8 0.4 G:genotype, N: nitrogen, CV: coefficient of variation. Means followed by the same letter in the same column are not significantly different at the 5% probability level by Tukey’s test. ∗∗ Significant at p = 0.001. 47 University of Ghana http://ugspace.ug.edu.gh 4.3 Correlation among the growth parameters in pot experiment Significant positive correlation was observed for six trait combinations (Table 4.8). Four out of the seven trait combinations had strong positive correlation. These were: root weight with number of tillers (r = 1.00), grain yield with number of tillers (r = 0.74), grain yield with number of tillers (r = 0.74) and leaf width with chlorophyll (r = 0.64). Moderate correlations were observed in: plant height with number of leaves (r = 0.47), number of leaves with number of tillers (r = 0.46), number of leaves with grain yield (r = 0.46). 80 % of the trait combination had weak correlation coefficient. Table 4.8: Phenotypic correlation coefficient of growth parameters among twenty rice landraces in pot experiment CPHY NT GY LL LW NL PLTH RL RW NT -0.04ns GY 0.00ns 0.74** LL 0.16ns -0.46ns -0.29ns LW 0.64** -0.08ns 0.16ns 0.36ns NL -0.09ns 0.46* 0.46* -0.06ns -0.00ns PLTH 0.30ns 0.19ns 0.15ns 0.34ns 0.28ns 0.47* RL 0.11ns 0.17ns 0.04ns -0.27ns -0.11ns 0.07ns 0.00ns RW -0.04ns 1.00** 0.74** -0.46ns -0.08ns 0.46ns 0.19ns 0.16ns SW 0.21ns 0.32ns 0.44ns 0.19ns 0.34ns 0.18ns 0.35ns 0.06ns 0.32ns ∗, ∗∗, ns are significant at the 5 and 1% probability level and non- significant, respectively NT: Number of tillers RW: Root weight GY: Grain yield SW: Straw weight LL: Leaf length CPHY: Chlorophyll LW: Leaf width NL: Number of leaves PLTH: Plant height RL: Root length 48 University of Ghana http://ugspace.ug.edu.gh 4.4 Yield related traits of rice landraces under no and low nitrogen levels in pot and field experiment Rice landraces showed different nitrogen uptake ability attributing to yield and nitrogen use efficiency at different nitrogen levels. A wide range with a general trend of reduction for the eight yield related traits was observed in the twenty landraces under no N compared to low N across both pot and field evaluation (Table 4.9). Significant differences and interactions were observed for all the traits. However, unfilled spikelets was higher as nitrogen level increased which ranged from 70 – 750 and 86 – 781 in pot and field experiments respectively. Low unfilled spikelets was recorded at no N level which ranged from 10 – 90 and 31 – 71 in pot and field experiments, respectively. Among the rice genotypes, GH2145 had the highest grain yield (8,035 kg/ha) followed by GH1550 (6,025 kg/ha). GH2145 and GH1550 also had the highest number of filled spikelets per panicle in pot (150 and 138) and field (161 and 152) experiments (Tables 4.9). Genotypes showed significant differences for N harvest index with mean ranging from 38.36 – 50.06 % under no and low N conditions in pot experiment and 33.19 % - 46.78 % in field experiment. N harvest index of GH2145, GH1550, GH 1822, GH1801 and GH1590, GH1514 and Aunty Jane were higher than the overall mean. 4.5 Nitrogen use efficiency and its component traits in pot and field experiment There were significant genotypic effects for N use efficiency and its component traits (p< 0.05) (Table 4.10). In this study, wide ranges of means were recorded with a general trend in increase for NUE, NUpE, and NUtE under no N conditions as compared to low N conditions in pot and field experiments. GNC and SNC increased slightly under low N conditions as compared to no N. The highest grain yield producing landraces had the highest NUE. 49 University of Ghana http://ugspace.ug.edu.gh Table 4.9: Summary of ANOVA for yield related traits under no and low nitrogen levels of twenty rice landraces in pot and field experiment Range Mean Trait Pot Field Pot Field No N Low N No N Low N No N Low N No N Low N N G G × N FS 300.00-1400.00 522.00 – 3360.00 311.00 – 1461.00 580.00 – 3407.00 683.40 1419.20 730.83 1482.25 ** ** ** GY 357.00-2092.00 627.13 – 8035.00 403.00 – 2121.00 636.00 – 8107.00 979.94 2574.08 1011.72 2633.33 ** ** ** PN 7.00 – 14.00 11.00 – 30.00 10.00 – 19.00 15.00 – 34.00 10.40 19.83 14.18 23.35 ** ** * PL 16.00 – 26.50 20.00 – 30.00 18.00 – 29.00 22.00 – 33.00 20.80 25.31 22.27 26.83 ** ** ** TGW 10.00 – 20.00 10.00 – 25.00 9.00 – 24.00 17.00 – 32.00 14.45 17.75 16.41 20.77 ** ** ** UFS 10.00 – 90.00 70.00 – 750.00 31.00 – 71.00 86.00 – 781.00 32.72 381.91 50.65 415.70 ** ** ** SPN 50.00 -100.00 70.00 – 150.00 55.00 – 121.33 76.00 – 161.00 65.45 91.15 77.55 101.15 ** ** ** HI 21.36 – 61.65 29.43 – 65.25 21.23 – 50.31 26.14 – 69.25 38.36 50.06 33.19 46.78 ** ** ** ∗, ∗∗, ns are significant at the 5 and 1% probability level and non- significant, respectively FS: Filled spikelet UFS: Unfilled spikelet GY: Grain yield SPN: Spikelet per panicle PN: Panicle number HI: Harvest Index TGW: 1000-grain weight 50 University of Ghana http://ugspace.ug.edu.gh Table 4.10: Summary of ANOVA for Nitrogen use efficiency parameters under no and low nitrogen levels in pot and field experiments of twenty rice landraces. Range Mean Trait Pot Field Pot Field No N Low N No N Low N No N Low N No N Low N N G G × N NUE 27.46 – 160.88 27.17 – 160.71 30.94 – 163.11 12.72 – 163.11 75.38 51.47 76.11 71.75 ** ** ** NUpE 79.77 – 609.20 34.15 – 567.85 102.80 – 566.71 41.89 – 546.57 255.98 159.10 262.19 159.44 ** ** ** NUtE 0.13 – 0.93 0.22 – 0.69 0.19 – 0.75 0.23 – 0.59 0.33 0.35 0.32 0.35 ** ** * GNC 0.65 – 2.37 0.78 – 2.88 0.68 – 2.33 0.79 – 2.82 1.53 1.79 1.53 1.77 ** ** ** SNC 0.71 – 1.77 0.82 – 1.87 0.53 – 1.72 0.65 – 1.97 1.07 1.21 0.88 1.05 ** ** ** **, * Significant at 1% and 5% probability level respectively NUE: Nitrogen Use Efficiency NUpE: Nitrogen Uptake Efficiency NUtE: Nitrogen Utilization Efficiency GNC: Grain nitrogen concentration SNC: Straw nitrogen concentration 51 University of Ghana http://ugspace.ug.edu.gh 4.6 Genotypic and phenotypic coefficient of variations and heritability estimates for yield related traits and NUE components in pot and field experiments Genotypic coefficient of variation (GCV) was less than its corresponding estimates of phenotypic coefficient of variation (PCV) for all yield related traits (Table 4.11). There were differences between PCV and GCV for NUE and NUpE. For NUtE, GNC and SNC, there was no difference between GCV and PCV (Table 4.11) In the present study, broad-sense heritability estimates for the yield related traits ranged from 97.83 % to 100 % under pot and field conditions (Table 4.12). NUE components observed for both pot and field experiments had heritability estimates of 95.37% to 100.00% (Table 4.12). 52 University of Ghana http://ugspace.ug.edu.gh Table 4.11: Estimation of genetic variability parameters for yield related traits in rice landraces under pot and field conditions. Trait Mean σ2 G σ 2P GCV (%) PCV (%) H (%) Pot Field Pot Field Pot Field Pot Field Pot Field Pot Field FG 1051.3 1106.54 11200.89 12246.05 11201.97 12246.05 10.00 9.74 10.00 9.75 99.00 100.00 GY 1777.01 1822.53 74874.29 80090.67 74874.99 80092.08 15.39 15.53 15.40 15.53 99.99 99.99 PN 15.11 18.76 0.69 0.90 0.70 0.91 5.50 5.05 5.54 5.08 98.57 98.90 PL 23.05 24.55 0.45 0.68 0.46 0.69 2.91 3.35 2.94 3.38 97.83 98.55 TGW 16.10 18.59 0.93 1.01 0.94 1.02 5.98 5.40 6.02 5.43 98.94 99.02 UFS 211.32 233.18 755.60 782.37 756.87 782.38 13.01 11.99 13.02 11.99 99.83 99.99 SPIPAN 78.30 89.35 23.75 26.59 23.76 26.59 6.22 5.77 6.23 5.77 99.96 100.00 HI 44.26 39.98 7.61 6.24 7.64 6.26 6.23 6.25 6.24 6.26 99.61 99.68 FG: Filled spikelet TGW: 1000- grain weight GY: Grain yield SPIPAN: Spikelet per panicle HI: Harvest Index UFS: Unfilled spikelet PN: Panicle number PL: Panicle length 53 University of Ghana http://ugspace.ug.edu.gh Table 4.12: Estimation of genetic variability parameters for nitrogen use efficiency in rice landraces under pot and field under conditions. Trait Mean σ2 G σ 2P GCV (%) PCV (%) H (%) Pot Field Pot Field Pot Field Pot Field Pot Field Pot Field NUE 63.43 73.93 76.98 170.44 80.72 171.54 13.83 17.65 14.16 17.72 95.37 99.34 NUpE 207.54 210.81 1220.39 1187.08 1221.31 1187.38 16.83 16.34 16.84 16.35 99.92 99.97 NUtE 0.34 0.33 0.01 0.01 0.01 0.01 29.41 30.30 29.41 30.30 100.00 100.00 GNC 1.65 1.65 0.01 0.01 0.01 0.01 6.06 6.06 6.06 6.06 100.00 100.00 SNC 1.14 0.96 0.01 0.01 0.01 0.01 8.68 9.43 8.73 9.43 100.00 100.00 NUE: Nitrogen Use Efficiency NUpE: Nitrogen Uptake Efficiency NUtE: Nitrogen Utilization Efficiency GNC: Grain nitrogen concentration SNC: Straw nitrogen concentration 54 University of Ghana http://ugspace.ug.edu.gh 4.6 Correlations among yield related traits and NUE components in pot and field experiments Several traits showed significant positive correlation and were observed for 21 % of trait combinations (Table 4.13). Significant correlations were observed between grain yield and field spikelet (r = 0.91), panicle length with grain yield (r = 0.81). Similarly, 1000 - grain weight showed significant correlation with grain yield (r = 0.81) and panicle length (r =1.00) (Table 4.13). Spikelet per panicle showed positive correlation with field spikelet (r = 0.63) and unfilled spikelet (r = 0.75). NUE also had significant correlation with filled spikelet (0.96), grain yield (0.96), panicle length (0.76), and one thousand grain weight(r = 0.76). NUpE had significant correlation with filled spikelet (r = 0.90) and grain yield (r = 0.93). HI also correlated with grain yield (r = 0.56), panicle length (r = 0.69), 1000 - grain weight (r = 0.69), NUE(r = 0.55). On the other hand, 59% of the trait combinations had weak correlations. Positive correlations were observed among yield related traits and NUE components in the field experiment. (Table 4.14). About 59 % of the trait combinations had weak correlations. Strong positive correlation were observed for: straw nitrogen concentration and nitrogen uptake efficiency (r = 0.98), NUpE with grain yield (r = 0.95) and filled spikelet (r = 0.90), grain yield with harvest index (r = 0.70), filled spikelet with harvest index (r = 0.61) and grain yield (r = 0.90) and panicle number with grain yield (r = 0.74), In both pot and field experiments, strong correlations were observed between NUE with filled spikelet, grain yield, panicle length and one thousand grain weight. Also, NUpE had strong correlations with filled spikelet, grain yield harvest index, panicle length, one thousand grain weight and NUE. Furthermore, NUtE had weak correlations with all the yield parameters, NUE and NUtE. 55 University of Ghana http://ugspace.ug.edu.gh Table 4.13: Correlation for yield related traits and nitrogen use efficiency in pot experiment FS GY PN PL UFS TGW SPIPAN NUE NUpE NUtE GNC SNC GY 0.91** PN 0.06ns -0.01ns PL 0.59* 0.81* 0.07ns UFS 0.11ns -0.14ns 0.07ns -0.33ns TGW 0.59* 0.81* 0.07ns 1.00** -0.33ns SPIPAN 0.63** 0.41ns 0.23ns 0.15ns 0.75** 0.15ns NUE 0.96** 0.96** 0.09ns 0.76** -0.03ns 0.76** 0.50* NUpE 0.90** 0.93** 0.10ns 0.63** -0.08ns 0.63** 0.44ns 0.92** NUtE -0.17ns -0.21ns -0.01ns 0.16ns -0.02ns 0.16** -0.04ns -0.14ns -0.43ns GNC 0.54* 0.52* -0.19ns 0.03ns -0.06ns 0.03ns 0.19ns 0.48ns 0.65** -0.71ns SNC 0.48* 0.64* 0.15ns 0.60** -0.38ns 0.60** 0.05ns 0.57* 0.71** -0.43ns 0.38ns HI 0.48* 0.56* -0.14ns 0.69** -0.32ns 0.69** 0.06ns 0.56* 0.31ns 0.47ns 0.03ns 0.35ns ∗, ∗∗, ns are significant at the 5 and 1% probability level and non- significant, respectively FG: Filled spikelet UFS: Unfilled spikelet GY: Grain yield SPN: Spikelet per panicle PN: Panicle number HI: Harvest Index TGW: 1000- grain weight NUE: Nitrogen use efficiency NUpE: Nitrogen uptake efficiency GNC: Grain N concentration SNC: Straw N concentration NUtE: Nitrogen utilization efficiency Table 4.14: Correlation for yield related traits and nitrogen use efficiency in field experiment FS GY PN PL UFS TGW SPIPAN NUE NUpE NUtE GNC SNC GY 0.91** PN 0.70** 0.74** PL 0.08ns 0.03ns -0.18ns UFS 0.12ns -0.14ns -0.37ns 0.09ns TGW 0.42ns 0.62** 0.50** 0.03ns -0.37ns SPIPAN 0.65** 0.43ns 0.02ns 0.25ns 0.73** 0.03ns NUE 0.66** 0.76** 0.45* 0.30ns -0.21ns 0.56** 0.38ns NUpE 0.90** 0.95** 0.74** 0.08ns -0.09ns 0.56** 0.49* 0.76** NUtE -0.13ns -0.19ns -0.29ns 0.17ns 0.07ns 0.06ns -0.01ns -0.18ns -0.39ns GNC 0.53* 0.59** 0.61** -0.26ns -0.28ns 0.39ns 0.07ns 0.47* 0.67** -0.66ns SNC 0.87** 0.97** 0.72** 0.01ns -0.17ns 0.58** 0.42ns 0.76** 0.98** -0.38ns 0.70** HI 0.61** 0.70** 0.53** 0.01ns -0.30ns 0.65** 0.17ns 0.68** 0.56** 0.31ns 0.33ns 0.58** ∗, ∗∗, ns are significant at the 5 and 1% probability level and non- significant, respectively FG:Filled spikelet UFS: Unfilled spikelet NUpE: Nitrogen uptake efficiency GY: Grain yield SPN: Spikelet per panicle GNC: Grain N concentration PN: Panicle number HI: Harvest Index SNC: Straw N concentration TGW: 1000-grain weight NUE: Nitrogen use efficiency NUtE: Nitrogen utilization efficiency 56 University of Ghana http://ugspace.ug.edu.gh CHAPTER FIVE 5 DISCUSSION 5.1 Characterization of germplasm 5.1.1 Diversity among morphological traits in pot experiment Sturdy culm was an important trait with high diversity in the qualitative trait. Most of the landraces characterized (98 %) had dense culms. Conversely, when the landraces were evaluated for lodging resistance, only 37 % indicated strong or very strong lodging resistance. High culm strength, tightly wrapped leaf sheath and plant height (< 150 cm) may contribute to the varieties being resistant to lodging (Hitaka, 1969; Mahbub et al., 2007). This is an important trait needed to improve yield as lodging leads to low yield in rice production. On the average, the diversity index for the qualitative traits scored was low (0.33). Low qualitative diversity may be as result of similar geographic locations where landraces used for the study were collected. This result resonates with a study carried out in the Philippines, were 307 varieties used had low qualitative diversity (Rabara et al., 2014). Future collection trips should focus on these traits to enhance their diversity in our gene bank. Awns were present in five of the landraces which is considered as a valuable trait in rice domestication. Awn is an important trait which aids the dispersal of seeds as seeds attach themselves to animal fur and protects them from animal predators. Furthermore, in barley, it aids in photosynthesis during grain filling. Conversely, the awns in rice lack chlorenchyma and cannot aid in photosynthesis (Bullard, 1985; Furata et al., 2015). The bulu or Javanica collection in the tropical Japonica varieties possess awned grains together with limited tillers and elongated 57 University of Ghana http://ugspace.ug.edu.gh panicles (Vaughan, 2008). Farmers prefer varieties with no to short awns because it allows for easier harvesting and reduces yield loss (Hu et al., 2011; Frank et al., 2015). 5.1.2 Correlation among traits in pot experiment Panicle number per plant and culm number was the only trait combination that was strong, indicated that almost all tillers were productive tillers and able to bear inflorescence. Flag leaf length correlated with most of the traits. Previous studies indicate that flag leaves are the principal source of phloem-delivered photoassimilates during the grain-filling stage in rice (Yu et al., 2006; Narayanan et al., 2007). Earlier studies have shown that when flag leaves are removed, about 45 % grain yield loss is observed (Abou-Khalifa et al., 2008). They are also useful in grain filling, because 80 % of the entire carbohydrate reserved in the grains are produced by flag leaves in rice (Gladun & Karpov, 1993). Similar findings were found in a study carried out by Rabara et al. (2014). Number of days to maturity correlated with panicle number indicating that the higher the panicle number the longer the days to maturity (Lakew, 2015). 5.1.3 Cluster and principal component analyses among landraces in pot experiment The overall cluster analysis showed the diversity in the accessions collected. It has also aided in grouping the accessions with similar traits (Wijayawardhana et al., 2015; Baloch et al., 2016). Sohrabi et al. (2012), clustered 50 accessions of upland rice into six groups based on 12 quantitative traits. Ahmadikhah et al. (2008) clustered 58 rice varieties into four groups based on 18 morphological traits. In this study, 5 clusters were created at a similarity index of 68 %. Principal component analysis indicated the most important traits that contributed to the cluster 58 University of Ghana http://ugspace.ug.edu.gh analysis such as ligule length, culm number, panicle number, number of days to main heading and number of days to maturity, leaf blade length, flag leaf length, flag leaf width and culm number and culm diameter. Caldo et al. (1996) recorded the first 10 principal components accounting for 67 % of the total variation. Lasalita-Zapico et al. (2010) also computed 82.7 % of the total variation among 32 upland rice varieties. 5.2 Growth response of the rice genotypes in different nitrogen treatments in pot experiment Findings from the pot experiment indicated that root dry weight, shoot dry weight, plant height, number of leaves, number of tillers, leaf length, leaf width, chlorophyll and grain yield increased as a result of nitrogen application except for root length which declined as nitrogen was applied. 5.2.1 Effect of nitrogen on root morphology In the present study, sub-optimal N fertilization reduced root length as compared to no N levels. N stress might have caused an increase in root length density to explore a larger soil volume or increase N uptake (Mi et al., 2008). Technically, increase in nitrate supply causes a decline in auxin concentration in the phloem, suggesting that shoot-root auxin transport may be inhibited by high N supply (Coenen & Lomax, 1997). Considering the antagonism between auxin and cytokinin, increase in cytokinin levels may lead to a decrease in auxin level which may have negative influence on root apex activity. This causes weakening in root apical dominance, leading to a reduction in root elongation and an increase in lateral root growth (Mi et al., 2008). Similar studies supports this finding (Evans et al., 1994; Chen et al., 2008). This finding was contrary to López-Bucio et al. (2003) who found out that fertilizer application led to root elongation. 59 University of Ghana http://ugspace.ug.edu.gh 5.2.2 Effect of nitrogen on number of tillers, leaf length, leaf width and leaf number The number of tillers, leaf length, leaf width and leaf number increased due to an increase in the size and number of meristematic cells which results in new shoots (Lawlor, 2002). N fertilizer has been identified as a promoter of cytokinin levels which affects the expansion of cell wall (Arnold et al., 2006). Hence, it is reasonable to suspect that N was involved directly or in directly in the expansion and division of new cells and in the production of tissues which were accountable for the increase in growth characteristics. The reduction in tiller number, leaf length and width observed at 0kg/ha of nitrogen may be as a result of intra plant competition for nitrogen. This is in agreement with Mesquita & Pinto (2000) and Pathan, (2010). 5.2.3 Effect of nitrogen on grain yield Nitrogen promotes carbohydrate build up in culms and leaf sheaths throughout the pre-heading phase and in the grain during the ripening phase of rice (Bahmanyar & Ranjbar, 2007). Furthermore, high grain yield may be as a result of nitrogen fertilizer encouraging dry matter production, improving rice growth rate, promoting elongation of internodes and the activity of growth hormones like gibberellins. Singh et al. (2000) also observed similar findings. 5.2.4 Effect of nitrogen on chlorophyll content Chlorophyll concentration increased due to fertilizer application. Chlorophyll depends on nitrogen nutrition which stimulates the production of active photosynthetic pigments by increasing the quantity of stromal and thylakoid proteins in leaves (Cooke et al., 2005; Filho et al., 2011 & Li et al., 2012). This increases the formation of chloroplast throughout the period of leaf growth. 60 University of Ghana http://ugspace.ug.edu.gh Furthermore, optimum availability of N is involved in cell division and the formation of active photosynthetic pigments such as chlorophyll. This result is in agreement with Razaq et al. (2017). 5.2.5 Effect of nitrogen on Plant height Application of N increased plant height, due to an increase in protein formation from manufactured carbohydrates, less carbohydrate is deposited in the vegetative portion of the plant which leads to increase in plant height. On the contrary, when N is deficient, carbohydrates are deposited in the vegetative cells causing them to thicken (Tisdale et al., 2003). Similar findings were observed a study carried out by Fageria et al. (2010). 5.2.6 Effect of nitrogen on shoot dry weight Shoot dry weight among the genotypes was heavier when nitrogen was applied. This may be due to N the decrease in spikelet sterility. Similar findings was observed in a study carried out by Fageria & Baligar (1999). Furthermore, a decline in the number of sterile spikelet trebles the number of grain and eventually increases grain yield performance. An increase in yield will lead to an increase in grain number and heavier shoot dry weight. 5.2.7 Correlation among growth parameters in pot experiment Root dry weight showed a strong association with number of tillers. It is logical to speculate that the root surface is in close contact with the soil which led to high absorption of nutrients. This indicates that resource uptake increases with root surface area. Increase in nutrient assimilation may have aided the crop to generate more tillers (Casen & Barber, 1976). A strong relationship was also observed between root weight and grain yield. This may be due to the nutrient absorption 61 University of Ghana http://ugspace.ug.edu.gh achieved through increased root mass. This might have led to the increase in grain yield. Similar findings were observed in studies carried by Narayanan et al. (2014). Leaf width and chlorophyll content had positive correlation. This may be due to better penetration of sunlight for the formation of active photosynthetic pigment. 5.3 Yield related traits in pot experiment Genetic variations were observed among the landraces due to significant differences indicated by the analysis of variance. The varied range of responses to no N in the present study affirms the differences in N metabolism proficiencies of the landraces. The reduction in panicle number under no N could be due to competition for assimilates among young panicles and tillers in the course of panicle development. This leads to slow growth among many young tillers which may senesce without producing panicle (Fageria & Baligar, 2001). Analogous observations were described by other authors (Mendhe et al., 2002; Uddin et al., 2011). Spikelet per panicle increased as nitrogen fertilizer was applied. Increase in number of grains per panicle at higher nitrogen rate might be due to increase in nitrogen uptake which promoted formation of higher number of twigs per panicle (Rahman et al., 2007). Previous studies observed similar findings (Lakew, 2015; Rao et al., 2018). The high yielders had more filled spikelet per panicle. This indicates that number of filled spikelet promotes high grain yield due to adequate supply of N fertilizer. These findings resonates with that of Lawal & Lawal (2002). On the contrary, unfilled spikelet were increased when nitrogen was applied. This could be because nitrogen increases the number of spikelet as a result of increase in panicle number which may reduce the production of carbohydrate from sink to support the growth of all spikelet leading to a reduction in filled spikelet. This might happen especially when 62 University of Ghana http://ugspace.ug.edu.gh solar radiation is low leading to less assimilation of photosynthates. Similar result was observed in a study carried out by Yuan et al. (2013). Conversely, Lakew (2015) experienced reduction in filled spikelet when nitrogen was applied. In the case of 1000 - grain weight, the difference was relatively low between the two levels of nitrogen because it has be reported to be a genetically controlled character. Comparable results were established by other scientists and they concluded that there is little opportunity to improve grain size through agronomic management (Maske et al., 1997; Ahmed et al., 2005). High yielding genotypes had high harvest index indicating the importance of harvest index as a yield component. Rao et al. (2018) also found similar results. 5.4 Nitrogen use efficiency and its component traits Although significant differences were observed for NUE, NUpE and NUtE. The variations between no and low nitrogen level was small. The assessment of NUE in crop plants is significantly required to measure the fate of applied nitrogen and their role in improving maximum economic yield through efficient absorption or utilization by the plant. The relatively similar trend of NUE at no and low N levels indicate that the rice genotypes in the current study are able to absorb or utilize N at no N levels. This may be due to the fact that they are landraces with the ablility to grow mostly under low or minimal input conditions and are therefore likely to harbour the trait of resource use efficiency such as NUE. Perhaps, higher levels of N (levels above sub- optimal level used in the present study) may have shown lower NUE as observed in previous studies (Lakew, 2015; Haque & Haque, 2016). 63 University of Ghana http://ugspace.ug.edu.gh Interestingly, some of the high yielders such as GH 2145, GH1822 and GH1801 produced high grain under both no and low nitrogen levels. This may be buttressed by the fact that nitrogen efficient varieties may be able to produce high grain yields under no, low and high N fertility conditions (Beatty et al., 2010). Use of such better N use efficient varieties could improve the success of farmers as much of applied N can be absorbed and utilized for higher yield. 5.5 Genotypic and phenotypic coefficient of variation Genotypic coefficient of variation (GCV) was lower than its equivalent evaluations of phenotypic coefficient of variation (PCV) for all traits signifying the vital role of the environment in the expression of these traits. The difference between PCV and GCV for the yield related parameters indicates that these traits were influenced by the environment as compared to the genotypic effect. For NUE and its component traits as well as grain and straw nitrogen concentrations both the environment and genetic components played nearly equal roles as little to no difference was observed. Lakew, (2015) also observed similar results in his study. 5.6 Heritability Broad-sense heritability estimates for traits such as FS, GY, PN, PL, TGW, SPIPAN and HI as well as NUE and its components had high to very high heritability estimates. High heritability estimates can be used as a baseline for selection according to the morphological traits. Earlier studies by Woldeyesus et al. (2004) on barely genotypes and by Alemayehu et al. (2006) on tef genotypes indicated that broad-sense heritability estimates were high for yield related traits and NUE and its component traits. 64 University of Ghana http://ugspace.ug.edu.gh 5.7 Correlation among traits in pot and field experiment In order to improve a trait of interest, selecting traits that show strong association is pivotal. Grain yield correlated significantly with filled spikelet, panicle length and total grain weight. This was in accordance with results obtained by Rao et al. (2018). Furthermore, grain yield also had strong positive correlation with NUE and NUpE. This indicates that the ability of plants to become high yielders is as a result of their ability to efficiently absorb limited amount of nitrogen and channel the photoassimilates gained for grain production. Grain and straw nitrogen concentration as well as harvest index correlated with grain yield which indicates possible improvement of these traits. This is similar to earlier studies (Lakew, 2015). In this study, NUpE had strong association with NUE than the comparison between NUtE and NUE. Hence, NUpE seems more important in determining NUE. Earlier studies indicated by Van Sanford & Mackown (1986) and Lakew (2015) showed that strong positive correlation was observed between NUE and NUpE while weak correlations were observed between NUE and NUtE. Also, Muurinen et al. (2006) on rice and Woldeyesus et al. (2004) on barely genotypes found out that NUpE was more significant than NUtE in influencing NUE. Variations between pot and field experiments and their correlations may be ascribed to dissimilarity in the light intensity, nutrient absorption and water availability. Pot experiment appears to be more vulnerable to no N conditions for filled spikelet, grain yield, panicle number, 65 University of Ghana http://ugspace.ug.edu.gh panicle length, 1000-grain weight, spikelet per panicle and harvest index, whereas, unfilled spikelet seem vulnerable in field experiment at low N. 66 University of Ghana http://ugspace.ug.edu.gh CHAPTER SIX 6 CONCLUSIONS AND RECOMMENDATIONS 6.1 Conclusions Twenty rice landraces were characterized to evaluate their phenotypic diversity. Generally, the rice landraces exhibited moderate diversity based on quantitative characters (average index of 0.70) while qualitative characters had low diversity (average index of 0.33). Cluster analysis identified landraces with similar characteristics and principal component analysis indicated 71.9% of the total variation. Hence, in order to bridge the gap in terms of traits identified as low diversity, germplasm collection mission can be embarked upon and particularly, landraces that have been passed on from generation to generation and still cultivated in communities may be garnered. Furthermore, important traits such as early maturing and high tiller number identified can be utilized in breeding programs. The rice landraces responded differently to nitrogen levels. Panicle length, plant height, number of leaves, leaf length, leaf width, chlorophyll, grain yield, root dry weight and shoot dry weight increased as nitrogen was applied. Hence, 50 kg/ha of nitrogen can improve yield in landraces such as GH2145 and GH1550. NUE correlated with filled spikelet, grain yield, panicle length, 1000-grain weight and NUpE in the present study. Negative correlation was observed for NUE and NUtE. True to the study’s premise, landraces with promising yield under no N with efficient utilization of absorbed N were identified. They include; GH2145, GH1550, GH1822 and GH1801. Based on results of this study, it can be concluded that the identified landraces can be used in breeding programmes. 67 University of Ghana http://ugspace.ug.edu.gh Correlation coefficient provide a measure of association between the assessed characters which aids in the identification of significant as well as insignificant traits. This promotes the importance of these traits during selection for breeding purposes. Phenotypic coefficient of variation, genotypic coefficient of variation and heritability were high for yield related traits and NUE components. Selection of landraces with high heritability may aid breeding during crop improvement. 6.2 Recommendations 1. GH 1550, GH 2145 and GH1514 can be used to produce superior lines in terms of early maturity and high panicle number. 2. 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Acta Genetica Sinica, 33:824– 832. 87 University of Ghana http://ugspace.ug.edu.gh 7 APPENDICES 7.1 Appendix A: Accessions of rice and their collection site S/N Accession number Gene bank 1. GH1514 PGRRI/Bonsu 2. GH1515 PGRRI/Bonsu 3. GH1516 PGRRI/Bonsu 4. GH1519 PGRRI/Bonsu 5. GH1531 PGRRI/Bonsu 6. GH1535 PGRRI/Bonsu 7. GH1538 PGRRI/Bonsu 8. GH1549 PGRRI/Bonsu 9. GH1550 PGRRI/Bonsu 10. GH1552 PGRRI/Bonsu 11. GH1574 PGRRI/Bonsu 12. GH1583 PGRRI/Bonsu 13. GH1587 PGRRI/Bonsu 14. GH1590 PGRRI/Bonsu 15. GH1599 PGRRI/Bonsu 16. GH1599 PGRRI/Bonsu 17. GH1801 PGRRI/Bonsu 18. GH1822 PGRRI/Bonsu 19. GH2145 PGRRI/Bonsu 20. AUNTY JANE CRI/Kumasi 88 University of Ghana http://ugspace.ug.edu.gh 7.2: Appendix B: ANOVA for growth parameters in pot experiment Appendix 1b: Analysis of variance for chlorophyll Source of variation d.f. s.s. m.s. v.r. F pr. GeNOtype 19 1606.7349 84.5650 288.95 <.001 N 1 6285.7688 6285.7688 21477.57 <.001 Genotyp.N 19 665.9362 35.0493 119.76 <.001 Residual 80 23.4133 0.2927 Total 119 8581.8532 Appendix 2b: Analysis of variance for culm number Source of variation d.f. s.s. m.s. v.r. F pr. Genotyp 19 1585.367 83.440 75.85 <.001 N 1 2430.000 2430.000 2209.09 <.001 Genotyp.N 19 353.000 18.579 16.89 <.001 Residual 80 88.000 1.100 Total 119 4456.367 Appendix 3b: Analysis of variance for grain yield Source of variation d.f. s.s. m.s. v.r. F pr. Genotype 19 1.138E+08 5.990E+06 1.063E+05 <.001 N 1 7.624E+07 7.624E+07 1.352E+06 <.001 Genotyp.N 19 5.172E+07 2.722E+06 48284.70 <.001 Residual 80 4.510E+03 5.637E+01 Total 119 2.418E+08 Appendix 4b: Analysis of variance for leaf length Source of variation d.f. s.s. m.s. v.r. F pr. Genotype 19 2819.4016 148.3896 190.43 <.001 N 1 1484.7367 1484.7367 1905.34 <.001 Genotype.N 19 1757.7649 92.5139 118.72 <.001 Residual 80 62.3400 0.7792 Total 119 6124.2433 89 University of Ghana http://ugspace.ug.edu.gh Appendix 5b: Analysis of variance for Leaf width Source of variation d.f. s.s. m.s. v.r. F pr. Genotype 19 4.388250 0.230961 27.72 <.001 N 1 2.852083 2.852083 342.25 <.001 Genotype.N 19 1.862917 0.098048 11.77 <.001 Residual 80 0.666667 0.008333 Total 119 9.769917 Appendix 6b: Analysis of variance for number of leaves Source of variation d.f. s.s. m.s. v.r. F pr. Genotype 19 7863.133 413.849 54.88 <.001 N 1 27785.633 27785.633 3684.28 <.001 Genotype.N 19 5498.700 289.405 38.37 <.001 Residual 80 603.333 7.542 Total 119 41750.800 Appendix 7b: Analysis of variance for plant height Source of variation d.f. s.s. m.s. v.r. F pr. Genotype 19 20619.7676 1085.2509 1554.43 <.001 N 1 2621.7401 2621.7401 3755.18 <.001 Genotype.N 19 1753.6782 92.2989 132.20 <.001 Residual 80 55.8533 0.6982 Total 119 25051.0393 90 University of Ghana http://ugspace.ug.edu.gh Appendix 8b: Analysis of variance for root length Source of variation d.f. s.s. m.s. v.r. F pr. Genotype 19 2370.825 124.780 124.78 <.001 N 1 399.675 399.675 399.68 <.001 Genotype.N 19 2805.825 147.675 147.67 <.001 Residual 80 80.000 1.000 Total 119 5656.325 Appendix 9b: Analysis of variance for root weight Source of variation d.f. s.s. m.s. v.r. F pr. Genotype 19 63125.825 3322.412 1916.78 <.001 N 1 5978.408 5978.408 3449.08 <.001 Genotype .N 19 3508.092 184.636 106.52 <.001 Residual 80 138.667 1.733 Total 119 72750.992 Appendix 10b: Analysis of variance for straw weight Source of variation d.f. s.s. m.s. v.r. F pr. Genotype 19 6082.425 320.128 320.13 <.001 N 1 1755.675 1755.675 1755.68 <.001 Genotype.N 19 459.825 24.201 24.20 <.001 Residual 80 80.000 1.000 Total 119 8377.925 91 University of Ghana http://ugspace.ug.edu.gh 7.3 Appendix C: ANOVA for yield related traits and NUE components in pot experiment Appendix 1c: Analysis of variance for filled spikelet Source of variation d.f. s.s. m.s. v.r. F pr. Genotype 19 17028534.4 896238.7 5366.70 <.001 N 1 16244256.7 16244256.7 97271.00 <.001 Genotype .N 19 7342232.8 386433.3 2313.97 <.001 Residual 80 13360.0 167.0 Total 119 40628383.9 Appendix 2c: Analysis of variance for grain yield Source of variation d.f. s.s. m.s. v.r. F pr. Genotype 19 1.138E+08 5.990E+06 1.063E+05 <.001 N 1 7.624E+07 7.624E+07 1.352E+06 <.001 Genotype .N 19 5.172E+07 2.722E+06 48284.70 <.001 Residual 80 4.510E+03 5.637E+01 Total 119 2.418E+08 Appendix 3c: Analysis of variance for Harvest index Source of variation d.f. s.s. m.s. v.r. F pr. Genotype 19 11630.417 612.127 211.10 <.001 N 1 4037.284 4037.284 1392.32 <.001 Genotype .N 19 3916.322 206.122 71.08 <.001 Residual 80 231.975 2.900 Total 119 19815.999 92 University of Ghana http://ugspace.ug.edu.gh Appendix 4c: Analysis of variance for NUE Source of variation d.f. s.s. m.s. v.r. F pr. Genotype 19 1.227E+05 6.458E+03 2.158E+05 <.001 N 1 1.715E+04 1.715E+04 5.730E+05 <.001 Genotype .N 19 2.730E+04 1.437E+03 48008.30 <.001 Residual 80 2.395E+00 2.993E-02 Total 119 1.672E+05 Appendix 5c: Analysis of variance for panicle length Source of variation d.f. s.s. m.s. v.r. F pr. Genotype 19 708.6029 37.2949 41.44 <.001 N 1 609.7521 609.7521 677.50 <.001 Genotype .N 19 29.2029 1.5370 1.71 0.052 Residual 80 72.0000 0.9000 Total 119 1419.5579 Appendix 6c: Analysis of variance for panicle number Source of variation d.f. s.s. m.s. v.r. F pr. Genotype 19 1070.0333 56.3175 57.27 <.001 N 1 2669.6333 2669.6333 2714.88 <.001 Genotype .N 19 282.0333 14.8439 15.10 <.001 Residual 80 78.6667 0.9833 Total 119 4100.3667 93 University of Ghana http://ugspace.ug.edu.gh Appendix 7c: Analysis of variance for spikelet/panicle Source of variation d.f. s.s. m.s. v.r. F pr. Genotype 19 36130.200 1901.589 1768.92 <.001 N 1 19814.700 19814.700 18432.28 <.001 Genotype .N 19 13890.300 731.068 680.06 <.001 Residual 80 86.000 1.075 Total 119 69921.200 Appendix 8c: Analysis of variance for unfilled spikelets Source of variation d.f. s.s. m.s. v.r. F pr. Genotype 19 1.150E+06 6.055E+04 59553.51 <.001 N 1 3.828E+06 3.828E+06 3.765E+06 <.001 Genotype .N 19 8.796E+05 4.630E+04 45538.09 <.001 Residual 80 8.133E+01 1.017E+00 Total 119 5.858E+06 Appendix 9c: Analysis of variance for 1000-grain weight Source of variation d.f. s.s. m.s. v.r. F pr. Genotype 19 1426.800 75.095 75.09 <.001 N 1 326.700 326.700 326.70 <.001 Genotype .N 19 531.300 27.963 27.96 <.001 Residual 80 80.000 1.000 Total 119 2364.800 94 University of Ghana http://ugspace.ug.edu.gh Appendix 10c: Analysis of variance for straw nitrogen concentration Source of variation d.f. s.s. m.s. v.r. F pr. Genotype 19 15.271313 0.803753 95.31 <.001 N 1 0.604920 0.604920 71.73 <.001 Genotype .N 19 0.907247 0.047750 5.66 <.001 Residual 80 0.674667 0.008433 Total 119 17.458147 Appendix 11c: Analysis of variance for grain nitrogen concentration Source of variation d.f. s.s. m.s. v.r. F pr. Genotype 19 15.806997 0.831947 617.40 <.001 N 1 1.986613 1.986613 1474.30 <.001 Genotype .N 19 2.055987 0.108210 80.30 <.001 Residual 80 0.107800 0.001348 Total 119 19.957397 Appendix 11c: Analysis of variance for nitrogen uptake efficiency Source of variation d.f. s.s. m.s. v.r. F pr. Genotype 19 1.8119584 0.0953662 209.43 <.001 N 1 0.0080325 0.0080325 17.64 <.001 Genotype. N 19 0.2396036 0.0126107 27.69 <.001 Residual 80 0.0364296 0.0004554 Total 119 2.0960241 95 University of Ghana http://ugspace.ug.edu.gh Appendix 12c: Analysis of variance for nitrogen utilization efficiency Source of variation d.f. s.s. m.s. v.r. F pr. Genotype 19 1856390.75 97704.78 1331.04 <.001 N 1 281538.76 281538.76 3835.42 <.001 Genotype .N 19 199612.00 10505.89 143.12 <.001 Residual 80 5872.40 73.41 Total 119 2343413.91 96 University of Ghana http://ugspace.ug.edu.gh 7.4 Appendix D: Analysis of variance for yield related traits and NUE under field experiment Appendix 1d: Analysis of variance for filled spikelet Source of variation d.f. s.s. m.s. v.r. F pr. Rep stratum 2 6.672E+01 3.336E+01 571.86 Rep.N stratum N 1 1.694E+07 1.694E+07 2.904E+08 <.001 Residual 2 1.167E-01 5.833E-02 0.37 Rep.N.Genotype stratum Genotype 19 1.768E+07 9.307E+05 5.977E+06 <.001 N.Genotype 19 7.067E+06 3.719E+05 2.389E+06 <.001 Residual 76 1.183E+01 1.557E-01 Total 119 4.169E+07 Appendix 2d: Analysis of variance for grain yield Source of variation d.f. s.s. m.s. v.r. F pr. Rep stratum 2 8.645E+01 4.322E+01 57.00 Rep.N stratum N 1 7.889E+07 7.889E+07 1.040E+08 <.001 Residual 2 1.517E+00 7.583E-01 0.71 Rep.N.Genotype stratum Genotype 19 1.156E+08 6.087E+06 5.685E+06 <.001 N. Genotype 19 5.238E+07 2.757E+06 2.575E+06 <.001 Residual 76 8.137E+01 1.071E+00 Total 119 2.469E+08 97 University of Ghana http://ugspace.ug.edu.gh Appendix 3d: Analysis of variance for harvest index Source of variation d.f. s.s. m.s. v.r. F pr. Rep stratum 2 52.734 26.367 7.23 Rep.N stratum N 1 5546.849 5546.849 1521.16 <.001 Residual 2 7.293 3.646 2.57 Rep.N.Genotype stratum Genotype 19 9044.173 476.009 335.67 <.001 N.Genotype 19 3031.348 159.545 112.51 <.001 Residual 76 107.775 1.418 Total 119 17790.173 Appendix 4d: Analysis of variance for NUE Source of variation d.f. s.s. m.s. v.r. F pr. Rep stratum 2 161.69 80.85 0.97 Rep.N stratum N 1 571.86 571.86 6.87 0.120 Residual 2 166.53 83.27 1.00 Rep.N.Genotype stratum Genotype 19 247705.08 13037.11 156.42 <.001 N.Genotype 19 129154.56 6797.61 81.56 <.001 Residual 76 6334.52 83.35 Total 119 384094.25 98 University of Ghana http://ugspace.ug.edu.gh Appendix 5d: Analysis of variance for panicle length Source of variation d.f. s.s. m.s. v.r. F pr. Rep stratum 2 70.3500 35.1750 4221.00 Rep.N stratum N 1 625.6333 625.6333 75076.00 <.001 Residual 2 0.0167 0.0083 0.04 Rep.N.Genotype stratum Genotype 19 984.0333 51.7912 262.99 <.001 N.Genotype 19 42.7000 2.2474 11.41 <.001 Residual 76 14.9667 0.1969 Total 119 1737.7000 Appendix 6d: Analysis of variance for panicle number Source of variation d.f. s.s. m.s. v.r. F pr. Rep stratum 2 66.6167 33.3083 3997.00 Rep.N stratum N 1 2520.8333 2520.8333 3.025E+05 <.001 Residual 2 0.0167 0.0083 0.04 Rep.N.Genotype stratum Genotype 19 1308.1333 68.8491 326.35 <.001 N.Genotype 19 357.8333 18.8333 89.27 <.001 Residual 76 16.0333 0.2110 Total 119 4269.4667 99 University of Ghana http://ugspace.ug.edu.gh Appendix 7d: Analysis of variance for Spikelet/ panicle Source of variation d.f. s.s. m.s. v.r. F pr. Rep stratum 2 78.0500 39.0250 520.33 Rep.N stratum N 1 16708.8000 16708.8000 2.228E+05 <.001 Residual 2 0.1500 0.0750 0.43 Rep.N.Genotype stratum Genotype 19 38403.6333 2021.2439 11696.54 <.001 N.Genotype 19 16381.5333 862.1860 4989.30 <.001 Residual 76 13.1333 0.1728 Total 119 71585.3000 Appendix 8d: Analysis of variance for unfilled spikelet Source of variation d.f. s.s. m.s. v.r. F pr. Rep stratum 2 7.035E+01 3.517E+01 201.00 Rep. N stratum N 1 3.998E+06 3.998E+06 2.284E+07 <.001 Residual 2 3.500E-01 1.750E-01 1.43 Rep. N. Genotype stratum Genotype 19 1.130E+06 5.946E+04 4.859E+05 <.001 N. Genotype 19 9.181E+05 4.832E+04 3.949E+05 <.001 Residual 76 9.300E+00 1.224E-01 Total 119 6.046E+06 100 University of Ghana http://ugspace.ug.edu.gh Appendix 9d: Analysis of variance for 1000-grain weight Source of variation d.f. s.s. m.s. v.r. F pr. Rep stratum 2 19.2667 9.6333 Rep.N stratum N 1 567.6750 567.6750 Residual 2 0.0000 0.0000 0.00 Rep.N.Genotype stratum Genotype 19 1472.4917 77.4996 83.27 <.001 N.Genotype 19 316.8250 16.6750 17.92 <.001 Residual 76 70.7333 0.9307 Total 119 2446.9917 Appendix 10d: Analysis of variance for grain nitrogen concentration Source of variation d.f. s.s. m.s. v.r. F pr. Rep stratum 2 9.032E-03 4.516E-03 126.02 Rep.N stratum N 1 1.697E+00 1.697E+00 47356.49 <.001 Residual 2 7.167E-05 3.583E-05 0.99 Rep.N.Genotype stratum Genotype 19 1.713E+01 9.017E-01 24799.00 <.001 N.Genotype 19 8.821E-01 4.643E-02 1276.83 <.001 Residual 76 2.763E-03 3.636E-05 101 University of Ghana http://ugspace.ug.edu.gh Total 119 1.972E+01 Appendix 11d: Analysis of variance for nitrogen uptake efficiency Source of variation d.f. s.s. m.s. v.r. F pr. Rep stratum 2 0.0048305 0.0024152 6.37 Rep.N stratum N 1 0.0249399 0.0249399 65.78 0.015 Residual 2 0.0007582 0.0003791 3.27 Rep. N. Genotype stratum Genotype 19 1.0152424 0.0534338 460.45 <.001 N.Genotype 19 0.2469330 0.0129965 111.99 <.001 Residual 76 0.0088196 0.0001160 Total 119 1.3015237 Appendix 12d: Analysis of variance for nitrogen utilization efficiency Source of variation d.f. s.s. m.s. v.r. F pr. 102 University of Ghana http://ugspace.ug.edu.gh Rep stratum 2 1951.37 975.68 3.10 Rep.N stratum N 1 316753.42 316753.42 1004.80 <.001 Residual 2 630.48 315.24 13.74 Rep.N.Genotype stratum Genotype 19 1714581.92 90241.15 3933.13 <.001 N.Genotype 19 177521.76 9343.25 407.22 <.001 Residual 76 1743.73 22.94 Total 119 2213182.69 103 University of Ghana http://ugspace.ug.edu.gh 7.5 Appendix E: Diversity in grain colour of some landraces used GH1516 GH1801 GH1514 GH1550 GH1587 104 University of Ghana http://ugspace.ug.edu.gh 105