ONION (ALLIUM CEPA L.) GROWTH, YIELD AND STORABILITY AS INFLUENCED BY RATE AND TIME OF NITROGEN APPLICATION

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Abstract
Onion (Allium cepa L.) is an important commercial vegetable crop grown by small-holder farmers in Kenya, for both local and export markets. National average production is low and quality highly compromised due to use of low yielding varieties, low soil fertility and poor agronomic practices. Heavy loses estimated to be over 40% are also incurred in storage, mainly due to sprouting and rotting, further reducing the consumable yield. Nitrogen (N) is an important nutrient affecting onion growth and quality but with an impact on the shelf-life of the crop. This study was therefore conducted to investigate the effect of nitrogen fertilizer and time of application on onion bulb growth, yield, quality and storage.
Two field experiments were conducted in 2014 and 2015 with five N rates (0, 26, 52, 78 and 104 kg N/ha), applied as Calcium Ammonium Nitrate at 3, 6, 9 and 12 weeks after transplanting. Two commonly grown varieties of onions, Red Creole and Red Tropicana F1 hybrid were used. The experiments were laid in a randomized complete block design (RCBD), with a split-split plot arrangement and replicated three times. The varieties were the main plots, the fertilizer rates the sub plots and the time of application the sub-sub plots. The experiments were conducted under natural rainfall conditions supplemented with drip irrigation. All other agronomic practices regarding weeding and crop protection were applied as recommended for farmers. Onion bulbs were stored at room temperature conditions for a period of three months.
Agronomic data collection commenced three weeks after transplanting while storage data started four weeks after storage. Field parameters included plant height, leaf number, bulb ratios, % bolters, % fallen plants, total yield, marketable yield, bulb weight, bulb diameter, bulb size, bulb neck size and split bulbs. Parameters taken during storage were physiological weight loss (PWL), sprouted bulbs, number and length of sprouts, rotted bulbs and severity of rotting (%). Data were subjected to analysis of variance (ANOVA)and means obtained separated using Fishers protected LSD at 5% probability level.
Interaction between N rates and time of application affected plant height in both seasons while number of leaves, bulbing ratios and % fallen tops increased significantly with increasing N rates. Late application of N decreased plant height, reduced the number of leaves and bulbing ratios but stimulated growth late in the season hence delaying crop maturity.
Application of 104 kg N/ha increased total yields over the control by 59% in season one and 84% in season two. Marketable yield, average bulb weight and bulb diameter also increased significantly with increasing N rates in both seasons. Nitrogen fertilizer decreased Size A bulbs (<40 mm in diameter) while increasing the most marketable bulbs in Size B (40 – 80 mm in diameter) and C (>80 mm in diameter). However, late application of N at 12 weeks resulted in low bulb weight and narrow bulb diameters increasing size A bulbs and reducing total yield by 23% in season one and 27% in season two. Marketable yield reduced by 25% in both seasons. The yields increased linearly up to the highest level of N applied hence optimal production was not reached.
Application of N significantly (P<0.001) increased thick necked bulbs by 18% over the unfertilized check in season one and 32% in season two. Splitted bulbs increased with increasing N rates recording a 49% in season one. Late application of N at 12 weeks reduced neck sizes but increased splitted bulbs by 42% in season one and 87% in season two. Bolted bulbs were not influenced by N or its time of application.
Nitrogen increased significantly PWL, the number of rotted bulbs and length of sprouts in both seasons. High early application (3 weeks) increased rotting and physiological loss in weight due to larger bulbs and neck sizes while high late application accelerated sprouting. 
The Red Tropicana F1 hybrid performed better than the Red Creole variety, recording significant differences in growth and yield parameters. However, the Red Creole variety had a longer shelf life compared to the Red Tropicana F1 hybrid.
In conclusion, N fertilizer application improved growth and yield of onion but high rates from 78 kg N/ha had adverse effect on quality and storability of bulbs. Level 104 kg N/ha recorded the best growth and maximum yield for both varieties. Topdressing at 6 weeks after transplanting gave the best yields and quality. The yields increased linearly with N levels, warranting trials with higher levels to obtain an optimum and economic yield level. Application of 52 kg N/ha was best for bulbs intended for storage due to reduced rotting and sprouting. The Red Creole variety was a better option for storage.
Key words: Plant height, leaf number, crop maturity, marketable sizes, bulb ratios and diameters, bolted bulbs, PWL, accerated sprouting, increased splitting, increased rotting.



 
TABLE OF CONTENTS
 
DEDICATION II
ACKNOWLEDGEMENTS IV
TABLE OF CONTENTS V
LIST OF ABBREVIATIONS AND ACRONYMS VII
LIST OF TABLES VIII
LIST OF FIGURES XI
LIST OF APPENDICES XII
ABSTRACT XV

CHAPTER ONE
GENERAL INTRODUCTION
1.1. Background Information 1
1.2. Statement of the Problem 3
1.3. Justification 5
1.4. Research objectives 6
1.4.1. Broad objective 6
1.4.2. Specific objectives 6
1.5. Hypotheses 6

CHAPTER TWO
LITERATURE REVIEW
2.1. Origin, botany and nutritional value of onion 7
2.2. Onion ecology, growth and nutrition 9
2.3. Nitrogen nutrition and metabolism 12
2.4. Bulb development and factors that affect bulbing 15
2.5. Effect of nitrogen rates on yield and quality of onions 19
2.6. Storability of onion bulbs and factors affecting shelf life 22
2.7. Effect of time of fertilizer application 24

CHAPTER THREE
THE INFLUENCE OF N FERTILIZER RATES AND TIME OF APPLICATION ON GROWTH AND YIELD OF ONION
3.1. Abstract 27
3.2. Introduction. 28
3.3. Materials and Methods 29
3.3.1. Experimental site 29
3.3.2. Planting material 29
3.3.3. Land preparation and nursery planting 30
3.3.4. Experimental layout and treatment allocation 31
3.3.5. Transplanting and treatment application 32
3.3.6. Data collection and harvesting 32
3.3.6.1. Growth parameters measurements 33
3.3.6.2. Yield parameters measurements 34
3.3.7. Soil analysis 34
3.3.8. Data analysis 35
3.4. Results 36
3.4.1. Physico-chemical properties of the experimental site 36
3.4.2. Effect of nitrogen fertilizer and time of application on growth parameters 38
3.4.3. Effect of nitrogen fertilizer and time of application on yield and yield components 47
3.4.4. Correlation analysis 61
3.5. Discussion 62
3.5.1. Effect of N fertilizer and time of application on growth parameters 62
3.5.2. Effect of N fertilizer and time of application on yield and yield attributing factors 66
3.4.3. Correlation analysis on yield, yield attributing parameters and growth parameters 69

CHAPTER FOUR
THE INFLUENCE OF RATE AND TIME OF NITROGEN APPLICATION ON THE QUALITY AND STORABILITY OF ONIONS
4.1. Abstract 70
4.2. Introduction 71
4.3. Materials and Methods 72
4.3.1. Description of the experimental site 72
4.3.2. Experimental material 72
4.3.3. Treatments and experimental design 72
4.3.4. Harvesting, post-harvest storage and data collection 72
4.3.4.1. Quality parameters 73
4.3.4.2. Storage parameters 73
4.3.5. Data analysis 74
4.4. Results 74
4.4.1. Effect of nitrogen levels and time of application on quality parameters 74
4.4.2. Effect of nitrogen and time of application on storage parameters 80
4.5. Discusion 96
4.5.1. Effect of N fertilizer and time of application on quality parameters 96
4.5.2. Effect of N fertilizer and time of application on storage parameters 99

CHAPTER FIVE
GENERAL DISCUSSION, CONCLUSION AND RECOMMENDATIONS
5.1. General discussion and conclusion 104
5.2. Recommendations 107
5.3. Recommendations for further studies 108
REFERENCES 108
APPENDICES 126




 
LIST OF ABBREVIATIONS AND ACRONYMS

ANOVA Analysis of Variance
ASTGS Agriculture Sector Transformation and Growth Strategy
APG Angiosperm Phylogeny Group
CAN Calcium Ammonium Nitrate
CEC Cation Exchange Capacity
cm Centimeter
o C Degree Celsius
DNA Deoxy-Nucleic Acid
et al. And others
e.g. For example
EU European Union
FAO Food and Agriculture Organization of the United Nations
FAOSTAT Food and Agriculture Organization Statistics
FINTRAC Financial Transaction Report Analysis Centre of Canada
g Gram
GOK Government of Kenya
GA Gibberellic Acid
GS-GOGAT Glutamine Synthetase-Glutamate Synthase pathway
ha Hectare
HCD Horticultural Crops Directorate
IAA Indole Acetic Acid
INM Integrated Nutrient Management
KALRO Kenya Agricultural and Livestock Research Organization
kg Kilogram
LSD Least Significant Difference
mg Milligram
m Metre
MOA Ministry of Agriculture 
MT Metric Tones
NARL
NAA National Agriculture Research Laboratories
Naphthalene Acetic Acid
N+ Nitrogen
NH4- Ammonium ion
NO3 Nitrate ion
ns None Significant
% Percentage
PLW Physiological Loss in Weight
pH Power of Hydrogen
PPM Parts Per Million
R/FR Red: Far Red light
RCBD Randomized Complete Block Design
RNA Ribo-Nucleic Acid
SE Standard Error
t Tonne
TSP Triple Supper Phosphate
UM Upper Midland zone
UNESCO United Nations Educational Scientific and Cultural Organization
USAID United States Agency for International Development
USDA United States Development Agency





LIST OF TABLES 

Table 1: Nutritional value of raw onion per 100g serving 9
Table 2. Physical and fertility analysis conducted on soil from plots of experiment conducted at NARL, Kenya in 2014 and 2015 seasons. 35
Table 3. Physico-chemical properties of soil from the plots of the field experiment conducted at NARL, Kenya in 2014 and 2015 seasons. 37
Table 4. Effect of nitrogen rate, time of application and variety on plant height in experiment conducted at NARL, Kenya in 2014 and 2015 seasons. 39
Table 5. Effect of interaction of nitrogen rate, time of application and variety on plant height in experiment conducted at NARL, Kenya in 2014 and 2015 seasons. 40
Table 6. Effect of nitrogen rate, time of application and variety on number of leaves in field experiment conducted at NARL, Kenya in 2014 and 2015 saesons 42
Table 7. Effect of nitrogen rate, time of application and variety on bulbing ratios in field experiment conducted at NARL, Kenya in 2014 and 2015 saesons. 44
Table 8. Effect of nitrogen rate, time of application and variety on total bulb yield in field experiment conducted at NARL, Kenya in 2014 and 2015 seasons 49
Table 9. Effect of nitrogen rate, time of application and variety on marketable yield of bulbs in field experiment conducted at NARL, Kenya in 2014 and 2015 seasons. 51
Table 10. Effect of interaction of fertilizer and variety on marketable yield in field experiment conducted at NARL, Kenya in 2014 season. 52
Table 11. Effect of nitrogen rate, time of application and variety on average bulb weight in field experiment conducted at NARL, Kenya in 2014 and 2015 seasons. 52
Table 12. Effect of nitrogen rate, time of application and variety on size A bulbs in field experiment conducted at NARL, Kenya in 2014 and 2015 seasons. 56
Table 13. Effect of nitrogen rate, time of application and variety on size B bulbs in field experiment conducted at NARL, Kenya in 2014 and 2015 seasons. 58
Table 14: Effect of interaction of variety and N rates on size A and B bulbs in field experiment conducted at NARL, Kenya in 2015 season. 60
Table 15: Effect of nitrogen rates on Size C bulbs in field experiment conducted at NARL, Kenya in 2014 and 2015 seasons. 60
Table 16. Effect of interaction of fertilizer and time on size C bulbs in field experiment conducted at NARL, Kenya in 2014 season. 61
Table 17. Correlation between yield and growth parameters in field experiment conducted at NARL, Kenya in 2014 and 2015 seasons. 62
Table 18. Effect of interaction of fertilizer(F) and variety(V) on neck thickness of bulbs in field experiment conducted at NARL, Kenya in 2015 season. 75
Table 19. Effect of nitrogen rate, time of application and variety on neck thickness of bulbs in field experiment conducted at NARL, Kenya in 2014 and 2015 seasons 75
Table 20. Effect of nitrogen rate, time of application and variety on % bolted bulbs in field experiment conducted at NARL, Kenya in 2014 and 2015 seasons 77 
Table 21. Effect of nitrogen rate, time of application and variety on number of splitted bulbs in field experiment conducted at NARL, Kenya in 2014 and 2015 seasons 79
Table 22. Effect of nitrogen rates, time of application and variety on PWL of bulbs taken in storage experiment conducted at University of Nairobi, Kenya in 2014 and 2015 seasons. 83
Table 23. Effect of N rates, time of application and variety on the number of bulbs sprouted in storage experiment conducted at University of Nairobi, Kenya in 2014 and 2015 seasons 85
Table 24. Interaction effect of time and variety on the number of sprouts in storage experiment conducted at University of Nairobi, Kenya in 2015 season. 86
Table 25. Effect of N rates, time of application and variety on the number of sprouts in the storage experiment conducted at University of Nairobi, Kenya in 2014 and 2015 seasons 87
Table 26. Effect of N rates and time of application on the number of rotted bulbs in storage experiment conducted at the University of Nairobi, Kenya in 2014 and 2015 seasons. 93
Table 27. Effect of N rates, time of application and variety on severity of rotting (%) in storage experiment conducted at University of Nairobi, Kenya in 2014 and 2015 seasons. 95
Table 28. Interaction effect of N rate, time of application and variety on severity of rotting in storage experiment conducted at University of Nairobi, Kenya in 2014 and 2015 seasons. 96



 
LIST OF FIGURES

Fig 1. Interaction effect of fertilizer and time of application on bulb ratios in experiment conducted at NARL, Kenya in short rains of 2015. 44
Fig. 2. Effect of N rates (a and b) and time of application (c and d) on % fallen bulbs taken in field experiment conducted at NARL, Kenya during 2014 and 2015 seasons 46
Fig. 3. Yield response curves of Red Creole and Red Tropicana F1 hybrid to N rates in field experiment conducted at NARL, Kenya in 2014 (a) and 2015 (b) seasons. 48
Fig. 4. Effect of nitrogen rates (a and b) and time of application (c and d) on bulb diameter in field experiment conducted in NARL, Kenya in 2014 and 2015 seasons. 55
Fig.5. Effect of N rates on % bolted bulb in field experiment conducted atNARL, Kenya in 2015 season… 78
Fig. 6. Interaction effect of N rates and time of application on PWL of bulbs (a and b) in storage experiment conducted at University of Nairobi, Kenya in 2014 season. 82
Fig. 7. Effect of N rates on the length of sprouts (a, b) in storage experiment conducted at University of Nairobi, Kenya in 2014 and 2015 seasons. 89
Fig. 8. Interaction effect of N rates, time of application and variety on number of rotted bulbs in the storage experiment conducted at University of Nairobi, Kenya in 2014 (a,b) and 2015 (c,d). 92
 




LIST OF APPENDICES
Appendix 1. Soil analysis results in field experiment conducted at NARL, Kenya in 2014 and 2015 seasons. 126
1.1. Soil Texture Analysis (Hydrometer Method) 126
1.2. Soil Chemical (Fertility) Analysis 126
Appendix 2.1.1. ANOVA for plant height in field experiment conducted at NARL, Kenya in 2014
season. 126
Appendix 2.1.2. ANOVA for plant height in field experiment conducted at NARL, Kenya in 2015
season. 127
Appendix 2.2.1. ANOVA for number of leaves in field experiment conducted at NARL, Kenya in 2014 season 127
Appendix 2.2.2. ANOVA for number of leaves in field experiment conducted at NARL, Kenya in 2015 season. 128
Appendix 2.3.1. ANOVA for bulb ratios in field experiment conducted at NARL, Kenya in 2014
season 128
Appendix 2.3.2. ANOVA for bulb ratios in field experiment conducted at NARL, Kenya in 2015
season. 129
Appendix 2.4.1. ANOVA for % fallen tops in field experiment conducted at NARL, Kenya in 2014 season. 129
Appendix 2.4.2. ANOVA for % fallen tops in field experiment conducted at NARL, Kenya in 2015 season. 130
Appendix 2.5.1. ANOVA for total bulb yield in field experiment conducted at NARL, Kenya in 2014 season. 130
Appendix 2.5.2. ANOVA for total bulb yield in field experiment conducted at NARL, Kenya in 2015 season 131
Appendix 2.6.1. ANOVA for marketable yield of bulbs in field experiment conducted at NARL, Kenya in 2014 season. 131
Appendix 2.6.2. ANOVA for marketable yield of bulbs in field experiment conducted at NARL, Kenya in 2015 season. 132
Appendix 2.7.1. AONVA for average bulb weight in field experiment conducted at NARL, Kenya in 2014 season. 132
Appendix 2.7.2. ANOVA for average bulb weight in field experiment conducted at NARL, Kenya in 2015 season. 133
Appendix 2.8.1. ANOVA for diameter of bulbs in field experiment conducted at NARL, Kenya in 2014 season. 133
Appendix 2.8.2. ANOVA for diameter of bulbs in field experiment conducted at NARL, Kenya in 2015 season. 134
Appendix 2.9.1. ANOVA for size A bulbs in field experiment conducted at NARL, Kenya in 2014
season. 134 
Appendix 2.9.2. ANOVA for size A bulbs in field experiment conducted at NARL, Kenya in 2015 season. 135
Appendix 2.10.1. ANOVA for size B bulbs in field experiment conducted at NARL, Kenya in 2014 season. 135
Appendix 2.10.2. ANOVA for size B bulbs in field experiment conducted at NARL, Kenya in 2015 season. 136
Appendix 2.11.1. ANOVA for size C bulbs in field experiment conducted at NARL, Kenya in 2014 season. 136
Appendix 2.11.2. ANOVA for size C bulbs in field experiment conducted at NARL, Kenya in 2015 season. 137
Appendix 2.12.1. ANOVA for neck thickness of bulbs in field experiment conducted at NARL, Kenya in 2014 season. 137
Appendix 2.12.2. ANOVA for neck thickness of bulbs in field experiment conducted at NARL, Kenya in 2015 season. 138
Appendix 2.13.1 ANOVA for % bolted bulbs in field experiment conducted at NARL, Kenya in 2015 season. 138
Appendix 2.14.1. ANOVA for number of split bulbs in field experiment conducted at NARL, Kenya in 2014 season. 139
Appendix 2.14.2. ANOVA for number of split bulbs in field experiment conducted at NARL, Kenya in 2015 season. 139
Appendix 2.15.1. ANOVA for physiological weight loss of bulbs in storage experiment conducted at University of Nairobi, Kenya in 2014 season. 140
Appendix 2.15.2. ANOVA for physiological weight loss of bulbs in storage experiment conducted at University of Nairobi, Kenya in 2015 season. 140
Appendix 2.16.1. ANOVA for number of bulbs sprouted in storage experiment conducted at University of Nairobi, Kenya in 2014 season. 141
Appendix 2.16.2. ANOVA for number of bulbs sprouted in storage experiment conducted at University of Nairobi, Kenya in 2015 season. 141
Appendix 2.17.1. ANOVA for number of sprouts in storage experiment conducted at University of Nairobi, Kenya in 2014 season. 142
Appendix 2.17.2. ANOVA for number of sprouts in storage experiment conducted at University of Nairobi, Kenya in 2015 season. 142
Appendix 2.18.1. ANOVA for length of sprouts in storage experiment conducted at University of Nairobi, Kenya in 2014 season 143
Appendix 2.18.2. ANOVA for length of sprouts in storage experiment conducted at University of Nairobi, Kenya in 2015 season. 143
Appendix 2.19.1. ANOVA for number of rotted bulbs in storage experiment conducted at University of Nairobi, Keya in 2014 season. 144
Appendix 2.19.2. ANOVA for number of rotted bulbs in storage experiment conducted at University of Nairobi, Kenya in 2015 season. 144 
Appendix 2.20.1. ANOVA for severity of rotting of bulbs in storage experiment conducted at University of Nairobi, Kenya in 2014 season. 145
Appendix 2.20.2. ANOVA for severity of rotting of bulbs in storage experiment conducted at University of Nairobi, Kenya in 2015 season. 145
Appendix 3. Correlation Analysis in field experiment conducted at NARL, Kenya in 2014 and 2015 seasons. 146
3.1 Season 1 146
3.2 Season 2 147
Appendix 4: Minimum temperature data in field experiment conducted at NARL, Kenya in 2015 season. 148





LIST OF PLATES

Plate 1. Bolted bulbs of Red TropicanaF1 hybrid in field experiment conducted at NARL, Kenya in 2015 season 77
Plate 2. Split bulbs of Red Creole in field experiment conducted at NARL, Kenya in 2015 season 79
Plate 3. Sprouted bulbs of Red Tropicana F1 hybrid in storage experiment conducted at University of Nairobi, Kenya in 2014 and 2015 seasons. 84
Plate 4. A bulb (Red Tropicana F1 hybrid) with multiple sprouts in storage experiment conducted at University of Nairobi, Kenya in 2015 season. 86
Plate 5. A shrivelled bulb with long multiple sprouts in the storage experiment conducted at the University of Nairobi, Kenya in 2015 season. 88
Plate 6. Bulbs infected with white rot (Sclerotium cepivorum Berk) in storage experiment conducted at University of Nairobi, Kenya in 2014 season 91
Plate 7. Bulbs infected with black rot (Aspergillus niger) in storage experiment conducted at University of Nairobi, Kenya in 2015 season. 91




 
CHAPTER ONE
GENERAL INTRODUCTION

1.1. Background Information

Onion (Allium cepa L.), is one of the oldest vegetables known to man, its cultivation dating back to more than 5000 years (Shultz, 2010). It is believed to have originated from central Asia (Brewster, 1994). Today the bulb onion is an important commercial vegetable grown worldwide, with a wide adaptation from the tropics to sub-arctic regions.
Although onion is used in small amounts, the vegetable is consumed in almost every household. The crop is grown for its pungent bulbs which are essential for seasoning a variety of dishes. Their nutrition is however quite low, while their medicinal value is widely acclaimed (Pareek et al., 2017). Majority of onions are cultivated for dry bulbs (Fritsch and Friesen, 2002). According to Food and Agriculture Organization (FAO, 2016), over 9 million acres are devoted to growing onions world over. In 2016, world total production was over 93 million MT with China being the largest producer (23.9 million), followed by India (19.1 million), Egypt (3.1 million) and United States (3.0 million) MT (FAOSTAT, 2016). About 170 countries grow onionsworldwide but only eight percent of the total production goes for trading (USA National Onion Association, 2011). India is the world’s greatest exporter while Netherlands acts as an intermediary, importing and exporting onions (Brewster, 2008). The main exporting countries in Africa are Egypt, Tanzania, Morocco and Niger (Donna and Megan, 2007).
In Kenya, the bulbing onion is one of the most important vegetables after tomato and brassicas (MOA, 2004). It is mainly grown by small-scale farmers with very little on large scale. Records indicate that production does not meet the local market demand necessitating importation of about half the production capacity from India, Egypt and Tanzania (Tschirley et al., 2004; HCD, 2017). The yields vary between 5 – 20 tonnes/ha with an average of 15 tonnes /ha. Higher yields have been reported in other countries for example 65.3 MT/ha in Korea Republic, 56.4 MT/ha in USA, 56.2 in Australia and 54.1 MT/ha in Spain (FAOSTAT, 2016). Although the acreage under production has continued to increase over the years, the yields have remained low due to production challenges. On the other hand local demand has increased as a result of population increase, improved standards of living and diversification of eating habits. Kenya should target increasing the total production from its current average of 15 t/ha to over 60 t/ha to meet the growing demand (Fintrac, 2012).
Economically, onions rank second after tomato among vegetable crops in the world (Griffiths et al., 2002; Mallor et al., 2011). They are found present in most markets of the world at all seasons of the year. They have good price elasticity, being consumed in about the same amounts when the prices are high or low, with the demand remaining fairly constant. In Kenya, the onion is important for food security, commercial production and employment. Per capita consumption is about2 kg per annum (Helgi analytics, 2014). Most of the onions are consumed locally with very little exports. A highly specialized market allows exportation of 602.5 MT to EU market as vegetable mixes and prepacks. However, due to the high demand, Kenya is a net importer of onions which presents a good opportunity for growers. Market prices and demand show immense potential for increasing incomes of the local farmers.
Although favourable conditions for production exists in Kenya, several constraints impede onion production leading to low yields and poor quality.. The major biotic constraints include pests and diseases especially weeds which pose a major problem during cultivation leading to high yield losses (Waiganjoet al., 2009). Abiotic constraints contributing to low production include low soil fertility and inadequate moisture for production where irrigation is not available. The high cost of hybrid seed is another challenge as most farmers cannot afford hybrid seed. Added to these challenges is climate change. Selection of cultivars to be grown in various areas is not well done and husbandry is not adequate resulting to poor crop yield and quality of bulbs. Technical information regarding plant density, fertilizer, water application, diseases and pest control is limited due to inadequate research (Kibanyu, 2009; MOA, 2013).
Despite the achievements made in production, high post-harvest losses (40 -60%) pose another challenge. Onions are in production all year round and bulbs are stored due to seasonal glut in the market. Significant losses in quality and quantity are incurred due to physiological weight loss, sprouting and rotting (Maini et al., 1984). This results to poor supply of bulbs and hiking of prices during lean periods.

1.2. Statement of the Problem

Low yields(5 – 20 t/ha) and low acreages lead to low National total production necessitating importation of large amounts to meet the growing demand (HCD, 2017). Quality is also compromised so that the commodity is not competitive in the market. Post-harvest losses estimated to be over 40%, further compound the problem, leading to poor seasonal distribution, escalation of prices during lean periods and reduction of marketable yield.
Despite a continuous increase in acreage over the years, the productivity continuous to be low due to limited availability of quality seed and associated technologies (Fintrac, 2012). Low soil fertility and inappropriate cultural practices contribute to the low yields and quality of bulbs. The old National recommended fertilizer rates of 78 kg N/ha have been overtaken by loss of soil fertility as a result of continuous crop cultivation. Growers are known to fertilize the crop at the late stages of bulb growth perhaps to compensate for losses incurred through leaching or merely from anxiety that the yields will be less than needed to maintain profitability (MOA, 2013). Improper application of fertilizers can have negative results on yield and quality of onion bulbs.
The problem of bulb splitting and thick necks is common in the onion growing areas and may be due to excess irrigation and application of high doses of nitrogen fertilizers. The extent of bulb splitting is estimated at 30 to 40% which greatly affects quality hence the marketable yield (MOA, 2013). Splitting of onion bulbs is a physiological disorder resulting from shoots coming from multiple growing points which could be influenced by cultural or environmental factors. Cultural factors such as application of high soil moisture or excessive nitrogen in the early stages of bulb formation can lead to the malformation (Abdissa et al., 2011; Valenzuela et al., 1999). Varieties also show great differences in bulb splitting with some exhibiting a higher degree of the malformation(Eltayeb, 2006;Jilanand Ghaffor, 2003;Steer, 1980).
The high post-harvest losses incurred in storage due to sprouting and rotting greatly reduce the consumable yield and farmers are forced to sell their onions at low prices in the glut period (Abate, 2012). Storage losses of onions have been reported to reduce considerably by treatment of maleic hydrazide, ultraviolet radiation, controlled atmosphere storage, low and high temperature storage. Although these techniques work well to control post-harvest losses, most of them involve costly investment with specialized equipment and storage structures not feasible for the small-scale Kenyan farmer. Low-cost farm level technology is required to extend the shelf life of the crop. Manipulation of certain preharvest factors such as plant nutrition and time of bulb lifting can be done to extend shelf-life and increase marketability of the commodity.
Nitrogen is one of the primary macronutrients necessary for plant growth, development and good yields. Different levels of this nutrient have been reported to affect differently the yields,
marketable quality, taste and even shelf-life of the crop in storage. In view of this, the current study was carried out to investigate the influence of varying rates of N and time of top dressing on growth, yield, quality and shelf-life of two onion varieties commonly grown in Kenya.

1.3. Justification

The onion is a horticultural crop which is an important source of income for small-holder farmers and business communities involved in cross border trade (Kimani et al., 1991). Although Kenya exports about 602.5 MT of onions annually, it is a net importer of the commodity. Local production does not meet the domestic demand necessitating importation of about half the production capacity from Tanzania (Tschirley et al., 2004; MOA, 2004).
Although favourable conditions for production exist in Kenya, yields are still very low, averaging 15 tons/ha compared to 50-60 tons/ha in countries like China, Korea, USA and Spain (FAOSTAT, 2016). The low yield is attributed to use of low yielding varieties, poor agronomic practices and pests and disease infestation. Post-harvest losses contribute to further reduction of marketable yield due to poor keeping quality and handling practices. Quality of onions particularly bulb splitting is another factor that greatly affects competitiveness of Kenyan onions in the market.
Through the Agriculture Sector Transformation and Growth Strategy (ASTGS), the government aims to boost house hold food resilience, increase small-scale farmer incomes and increase overall agricultural output for economic growth (GoK, 2019-2029). Onion production presents a real opportunity for enhancing rural farm incomes, reduce poverty and improve Kenyan economy. There is huge unmet demand for the crop and focus is on research opportunities as well as the constraints that are impeding production. This study sought to improve production and quality to curb post-harvest losses.
 
1.4. Research objectives
1.4.1. Broad objective
To improve yield, quality and storability of onions for food and nutrition security and improved livelihoods.

1.4.2. Specific objectives
1. To determine the effect of different rates of N and time of application on growth, yield, and quality of onion.
2. To determine the influence of N and time of application on storability of onion.

1.5. Hypotheses
1. Nitrogenand its time of application has no effect on growth, yieldand quality of onion.

2. Nitrogen and its time of application has no effect on shelf life of onion bulbs.

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