THE EFFICACY of MULTIPLE ISOLATE RESISTANCE EVALUATION for Stenocarpella Maydis in BREEDING for EAR ROT RESISTANCE in TROPICAL MAIZE (Zea Mays L.)

THE EFFICACY OF MULTIPLE ISOLATE RESISTANCE EVALUATION FOR Stenocarpella maydis IN BREEDING FOR EAR ROT RESISTANCE IN TROPICAL MAIZE (Zea mays L.)

KELVIN SIMPASA

A dissertation submitted to school of Agricultural Sciences of the University of Zambia in partial fulfillment of the requirements of the degree of Master of Science in Plant Breeding and Seed Systems.

THE UNIVERSITY OF ZAMBIA

SCHOOL OF AGRICULTURAL SCIENCES

LUSAKA

2017

DECLARATION

APPROVAL

ABSTRACT

Maize ear rots caused by Stenocarpella maydis are among the most important impediments to increased maize production in Zambia. They cause reduction in yield and quality of the maize. The mycotoxins produced by the pathogen have health implications on livestock and humans. Breeding for resistance is the most feasible option in managing ear rots and it is affordable to small scale farmers. However, to obtain stable resistance to S. maydis has been a challenge partly due to effect of the environment. The effect due to isolates of S. maydis is not yet understood. The objectives of this study were therefore: (i) Determine the general combining ability (GCA) and specific combining ability (SCA) effects of the lines and crosses respectively (ii) the effect of multiple isolate inoculations in breeding for resistance to S. maydis; (iii) to determine the appropriateness of indirect trait selection for resistance to S. maydis in tropical maize. Seven inbred lines of varying resistance to S. maydis were mated in a half diallel to generate 21 F1 single crosses. The resultant crosses together with their parents were planted at two sites, Lusaka and Mpongwe for evaluation during the 2015/16 cropping season. The experiment was laid out as a randomized complete block design with 3 replications. The treatments were: (1) single inoculation of each isolate A, (2) single inoculation of each isolate B and (3) a multiple inoculation of two isolates AB and (4) control with no inoculation at all. The mean genotypic scores were found to be 5.52, 4.96, 5.50 and 1 for treatment 1, 2, 3 and 4 respectively. The t-test analysis revealed that treatment 1 had a higher mean disease severity score (5.52) as compared to treatment 2 (4.96) (P < 0.001). Equally mean for treatment 2 (4.96) and 3 (5.50) were significantly different (P < 0.001). However, there were no significant differences between mean disease severity score between treatment 1 and 3. This indicated that multiple inoculations cannot be used as a screening resistance breeding technique as it could give rise to inappropriate genetic information due to probable antagonistic effect between isolates (A could have suppressed isolate B when multiple inoculated). Specific combining ability (SCA) effects across all treatments were significant (P < 0.05) in specific locations. The variance components using Baker’s ratio were found to be 0.012 and 0.03 in Lusaka and Mpongwe respectively. The results indicate that non- additive gene effects were important in this study. Six and two crosses in location 1 and 2 respectively showed negative significant SCA effects to S. maydis reaction. Two crosses, (P2 x P4) and (P3 x P6) showed consistent significant negative SCA effects in both locations implying that they possess a trait resistant to S. maydis. Negative correlations of grain texture (r = -0.58, in both locations) and husk cover (r = -0.63 and -0.70 in Lusaka and Mpongwe respectively) to mean disease severity score of S. maydis across treatments were significant (P < 0.01). However, the r2 values i.e. grain texture ( 0.34 for both locations) and husk cover (0.40 and 0.49 for Lusaka and Mpongwe respectively) in relation to mean disease severity indicate that indirect selection for resistance to S. maydis cannot be utilized as a substitute for direct selection but can be used to supplement it.

Keywords: Maize, ear rot, Stenocarpella maydis, resistance, mycotoxin

iii

DEDICATION To my family

ACKNOWLEDGEMENTS

I would like to sincerely acknowledge, appreciate and thank my supervisors Dr. L. Tembo and Mr. H. Masole for the mentorship and tireless guidance during this study. Without their support this study would have been a rough ride. You made me sail smoothly through this journey despite the different hurdles and turbulences encountered along the way. Let me also recognize Seed Co Zambia Limited for according the scholarship to pursue this study. This gesture has been greatly appreciated.

I extend my gratitude to Dr. C. Chikoti and team at Zambia Agriculture Research Institute (ZARI), pathology laboratory for according me the opportunity to work from their laboratory and the technical support rendered. UNZA plant science laboratory staff, Sydney Mpimpa, Alex Bwalya and Sharon Matenga, for the technical support and according me an opportunity to do part of my work despite the busy schedules you had.

Lastly but not the least, I thank my family especially my wife Cindy for the emotional, moral and physical support and encouragement during the course of the study. Above all, Almighty God for according good health, protection and divine guidance during the course of this study.

TABLE OF CONTENTS DECLARATION ...... i

APPROVAL ...... i

DEDICATION ...... iv

ACKNOWLEDGEMENTS ...... v

TABLE OF CONTENTS ...... vi

LIST OF FIGURES ...... ix

LIST OF PLATES ...... x

CHAPTER 1 ...... 3

INTRODUCTION ...... 3

1.1Justification of Study ...... 4

1.2 Objectives ...... 5

1.3Research hypotheses ...... 5

CHAPTER 2 ...... 6

LITERATURE REVIEW ...... 6

2.1 The origin and description of maize ...... 6

2.2 Climatic requirements and adaptation ...... 7

2.3 Maize production ...... 8

2.3.1 Factors affecting maize production ...... 9

2.3.1 Distribution and Epidemiology of Stenocarpella maydis ...... 10

2.3.2 Management of Stenocarpella maydis ...... 12

2.4 Breeding for resistance to Stenocarpella maydis ...... 12

2.4.1 Isolates of Stenocarpella maydis ...... 12

2.4.2 Types of artificial inoculation ...... 13

2.4.3 Indirect selection for resistance ...... 14

2.4.4 Combining ability and inheritance to Stenocarpella maydis ...... 14

CHAPTER 3 ...... 16

MATERIALS AND METHODS ...... 16

3.1 Germplasm used in the study ...... 16

3.3 Pathogen isolation and culture ...... 17

3.3.1 Inoculation and evaluation of isolates obtained from Region II (Lusaka) and III (Mpongwe) ...... 18

3.3.2 Toothpick- inoculum preparation ...... 18

CHAPTER 4 ...... 25

RESULTS ...... 25

4.1 Characterization of Isolates ...... 25

4.2 Effect of multiple isolate inoculations ...... 26

4.3 Stenocarpella maydis ear rots genotypic disease severity effect and combining abilities ...... 27

4.4 Indirect trait selection of resistant genotypes to Stenocarpella maydis ...... 30

CHAPTER 5 ...... 31

DISCUSSION ...... 31

CHAPTER 6 ...... 35

CONCLUSION AND RECOMMENDATIONS ...... 35

6.1 CONCLUSION ...... 35

6.2 RECOMMENDATIONS...... 35

REFERENCES ...... 36

vii

LIST OF TABLES

Table 1: Maize production by small and medium scale farmers during the 2014/15

cropping season in Zambia ...... 9

Table 2: Germplasm used in the experiment for S. maydis in Lusaka and Mpongwe 16

Table 3: Expected mean squares and interpretations of a half-diallel Method 2, ...... 23

Table 4: Analysis of variance for spore counts between isolates evaluated in the

laboratory at the University of Zambia, School of Agricultural Sciences ...... 26

Table 5: Genotypic mean disease severity score comparisons (MDSC) among

treatments ...... 26

Table 6: Mean squares for Stenocarpella maydis cob rot disease severity scores

across two experimental locations and in each individual location

evaluated in 2015/16 season. 27

Table 7: Effect of treatments on the test genotypes across the locations during

2015/16 cropping season...... 28

Table 8: Specific combining ability effects of the crosses for disease severity scores

across treatments in Lusaka and Mpongwe during 2015/16 cropping season 29

Table 9: Association of mean disease severity with agronomic traits measured for

genotypes in Lusaka and Mpongwe ...... 30

viii

LIST OF FIGURES

Figure 1: Agro-ecological zones in Zambia, indicating where maize production occur ... 8

Figure 2: Distribution map of Stenocarpella maydis in the world:...... 10

Figure 3: Stenocarpella maydis ear rot life cycle. A. Inoculum of S. maydis

survives in infected maize residue on the soil surface. B. Splashing

water spreads conidia to the ear infecting it through the ear shank

or silks. C. Ears and husks can prematurely die. D. Dense white

mold begins at the base of the ear, later it becomes grayish-brown,

eventually engulfing and rotting the entire ear. E. Small black

pycinidia can also form on the kernels...... 11

LIST OF PLATES

Plate 1: Picture showing coloniz7ed toothpicks...... 19

Plate 2: Single inoculations of the test ear with Isolate A or B of S. maydis.

Inoculation was done at 3-4 weeks after mid silking stage...... 20

Plate 3: Multiple inoculations (AB) of the test ear with two isolates A and B of S.

maydis. Cobs were inoculated at 3 – 4 weeks after mid silking stage with the

toothpicks placed approximately 5 mm apart...... 21

Plate 4: From left to right the trend for visual disease severity scores of the infected

cobs. Severity rating scores S. maydis; 1 = 0 - 25%, 2 = 26 - 50%, 3 = 51 -

74%, 4 = 75 - 84%, 5 = 85 - 94%, 6 = 95 - 99% and 7 = 100%...... 22

Plate 5: Phenotypic differences between isolate A exhibited a dark brown color and

isolate B exhibited light brown color 3 weeks after inoculation...... 25

ABBREVIATIONS

ANOVA Analysis of Variance

BR Baker’s Ratio

CRD Completely Randomized Block Design

ED Ear Declination

ER Ear Rot

GCA General Combining Ability

GT Grain Texture

HC Husk Cover

LGB Larger Grain Borer

LSD Least Significance Difference

MAS Marker Assisted Selection

MDSC Mean Disease Severity Score Comparison

MSRS Mpongwe Seed Company Research Station

PDA Potato Dextrose Agar

RCBD Randomized Complete Block Design

REML Restricted Maximum Likelihood

SADC Southern Africa Development Community

SCA Specific Combining Ability

SPVD Sweet Potato Virus Disease

UNZA University of Zambia

ZARI Zambia Agriculture Research Institute

CHAPTER 1

INTRODUCTION

Maize (Zea mays) is the world’s most grown cereal and it is predicted that by 2020 it will surpass both rice and wheat to become the number one cereal in the world (M'mboyi, et al., 2010). The sub-Saharan populaces depend on maize (Zea mays L.) as the main staple source of carbohydrate (Fischer et al., 2014). Approximately 22 million hectares, about 15.7% of the 140 million hectares grown globally, accounts for sub-Saharan Africa (Pingali., 2001). Farmers consider maize, not only to be a major source of energy but also their main source of income.

Maize production is carried out in diverse climates because of its versatility and it is the most productive species of food plants (Dowswell et al., 1996). In terms of soil, maize can be grown in wide range of soils, ranging from deep fertile soils along river bottoms and lake basins to well-drained and easily worked upland soils (M’mboyi et al., 2010).

In Southern Africa Development Community (SADC) sub-region, South Africa is the largest producer of maize followed by Tanzania with Zambia in fourth (FAOSTAT, 2015). However, maize production is hampered by a number of biotic and abiotic stress factors. The biotic constraints in maize production include insects, weeds and pathogenic infection (M’mboyi et al., 2010). Among the diseases caused by pathogenic infection, ear rots caused by a fungal complex which include Fusarium spp, Stenocarpella spp, Nigrospora spp. and Aspergillus spp, are important pathogens (Flett and van Rensburg, 1992; Macdonald and Chapman, 1997). In this study emphasis will be on a review and study of Stenocarpella maydis which cause yield losses of 10-50% (Vigier et al., 2001). In addition it produces mycotoxins which reduce quality and pose a health risk to humans and livestock (Mukanga, et al., 2010). In pre- and post-harvest maize, the occurrence of mycotoxins is of great concern as they tend to cause health disorders in both livestock and humans who consume contaminated grain (Munkvold and Desjardins, 1997; Miller, 2001).

Susceptibility of the maize plant to S. maydis is at very early stages (seedlings before the primary node develops) and at very late stages (stalks and ears 3-4 weeks after

3 silking). To control ear rots, a combination of crop sanitation, good agronomic practices and timely harvesting have been used, but with limited success (Munkvold, 2003). For cereals deployment of resistant genotypes remains the most cost effective and efficient approach (Agrios, 2005). It is for this reason that this study seeks to investigate the effect of multiple isolate infections in breeding for resistance to S. maydis. However, lately the use of marker assisted selection (MAS) is being used to improve selection as it is independent of the environment and subjectivity associated with human scoring approach. This aspect (use of MAS), will not be the subject of interest in this study but a review of other indirect selection method using agronomic traits will be highlighted. Aspects of combining abilities and nature of inheritance to S. maydis will also be reviewed.

1.1 Justification of Study Maize ear rots caused by S. maydis are associated with health implications due to the mycotoxins produced by the fungus. Livestock fed on infected grain develop diplodiosis which is an endemic neuro-mycotoxicosis and it is suspected to have carcinogenic effects on humans. In addition to quality problems ear rots cause yield losses. To curb this problem, deployment of resistant genotypes through breeding is the most cost effective way especially for the resource poor farmers in Zambia. However, resistance to S. maydis is greatly affected by underlying issues of gene interactions and the type of germplasm under study (Mukanga et al., 2011; Tembo et al., 2013). Identification of genotypes with stable resistance across locations can be utilized as the source of resistance in genotypic combinations (Tembo et al., 2013). It should be noted that effectiveness of breeding for stable resistance may be influenced by the type of isolates and its interaction with the environment (Rossouw et al., 2009). Previous studies have established multiple inoculations of different ear rot pathogens, as not an appropriate breeding strategy due to antagonistic effects associated with these pathogens (Tembo et al., 2013). Little is known about the effect of multiple isolate inoculations of S. maydis in breeding for resistance. Therefore, there is need to investigate that effect. Genotypes which exhibit resistance across different isolates would probably offer stable resistance across locations as they possess desirable General Combining Ability (GCA) effects. However, other genotypes may produce desirable results when crossed with specific genotypes (Specific Combining Ability). Genotypes with desirable GCA and SCA across

4 isolates will therefore be evaluated in this study. It should be noted however, that the art of scoring for disease manifestation is subjective and above all the infection rates of S. maydis are dependent on the environment. In this vein, attempts will be made to evaluate for indirect selection for resistance to S. maydis using agronomic traits.

1.2 Objectives

The main objective of the study is to generate knowledge essential in breeding for resistance to Stenocarpella maydis in tropical maize in Zambia.

The specific objectives were to:

1. Determine the general combining ability (GCA) of the inbred lines and specific combining ability (SCA) effects of the crosses in tropical maize. 2. To determine the effect of multiple isolate inoculation on maize ear in breeding for resistance to Stenocarpella maydis. 3. To determine the appropriateness of indirect selection using agronomic traits for resistance to Stenocarpella maydis in maize.

1.3 Research hypotheses

1. Lines and crosses with good general combining ability (GCA) and specific combining ability (SCA) effects exist among germplasm. 2. Multiple isolate inoculations of S. maydis on maize ear will create antagonistic effect between isolates. 3. Use of indirect trait selection criterion using agronomic traits increases the efficiency of selection.

CHAPTER 2

LITERATURE REVIEW

2.1 The origin and description of maize

Maize descended from an annual species of Teosinte (Zea mexicana spp. parviglumis) native to the Balsas River Valley on the Pacific slopes of the states of Michoacán and Guerrero, Mexico, at elevations between 400 and 1200 metres (Piperno and Flannery, 2000). Teosinte shares a close genetic relationship with maize and evidence available indicates that it is a direct ancestor of maize (Matsuoka et al., 2002). However, over the years, numerous theories of origin of maize have been offered but only two receive serious consideration today. The first one is that wild pod maize, now extinct, was the ancestor of domesticated maize; and the other is that Teosinte (Zea mexicana) is the wild progenitor of corn (Brown et al., 1985).

Maize is a monoecious annual grass with overlapping sheaths, tall in stature and broadly evident alternating blades. Male and female flowers are found on the same plant as separate inflorescences. The tassel is comprised of the male flower while ear comprises of the female flower. The cob (ear) is enclosed in modified leaves called husks. The maize grain (kernel) consists of a tip cap, pericarp, endosperm and the embryo. Approximately the endosperm contains 80 % carbohydrates, 25 % minerals and 20 % fat, whereas the embryo contains 75 % minerals, 80 % fat and 20 % protein (Duplesis, 2003).

Maize grain maybe artificially defined according to the kernel type for example: flint, semi-flint, dent and semi-dent (Paiwal, 2000; Zilic et al., 2011). These characteristics are based on the quantity, quality and pattern of endosperm composition in the kernel and are not indicative of natural relationships (Brown et al., 1985).

Maize is a wind pollinated crop; however, self-pollination (3-5%) is also possible. Usually shed pollen remains viable for 10-30 minutes, but under favorable conditions it can remain viable for longer periods.

2.2 Climatic requirements and adaptation

Cultivation of maize is carried out in the tropical, subtropical and temperate climatic regions of the world. The proportion of land cultivated to maize is divided almost equally between the tropical-subtropical areas of the world (Turrent and Serratos, 2004). Five mega environments for maize have been recognized: subtropics and mid- altitude tropical zones, tropical highlands, lowland tropics (less than 900 metres above sea level) and temperate zones (Pingali and Pandey, 2000). The distribution and amount of annual rainfall, and solar radiation determines temperature and will determine the environment for plant growth. Solar radiation is the second most important factor in maize production as it is the source of energy used by plants for photosynthesis.

Maize needs more than 50 % of its total water requirements in about 30 to 35 days after tasseling and water or moisture stress at grain filling stage will result in shriveled grains and poor yields (Duplesis, 2003). Maize performs very well on well- drained fertile soils with adequate and not excessive rain (< 2000 mm). Maize production takes place on soils with clay content of less than 10 % (sandy soils) or in excess of 30 % (clay and clay-loam soils). However, the texture classes between 10 and 30 % have moisture and air regimes that are optimal for healthy maize production. The soil must have good effective depth, an optimal moisture regime, good internal drainage, and sufficient balanced quantities of plant nutrients. Rainfall amounts of 350 – 1000 mm per annum will be required to produce a yield of approximately 3, 000 kg/ha (Mungoma and Mwambula, 1997; Duplesis, 2003). The most important elements for normal growth of maize are nitrogen (N), phosphorous (P) and potassium (K). Total nutrient uptake of a single maize plant at flowering is 7 - 10 g of N, 3 - 5 g of P and 3 - 4 g of K (Duplesis, 2003).

In Zambia production of maize occurs in all agro ecological zones (Figure 1). The maize crop requires warm temperatures throughout its active life and its response varies with the stage of the crop. The minimum temperature requirement for germination is 10 oC though at 16-18 oC it will be faster and less variable. At any

Figure 1: Agro-ecological zones in Zambia, indicating where maize production occur

Source: The Zambian Agropreneur, 2016.

stage of growth it cannot withstand frost (Canadian Food Inspection Agency, 1994; Duplesis, 2003).

2.3 Maize production

Maize production in Zambia is carried out in all the environments ranging from the low rainfall areas of (Region I) to the high rainfall areas (Region III). Eastern province is the highest producer in the country followed by Central province (Table 1) and the least being Western province (CSO/Ministry of Agriculture 2014/15).

Table 1: Maize production by small and medium scale farmers during the 2014/15 cropping season in Zambia PROVINCEx QUANTITY HARVESTED (TONS)y Central 579653.32 Copperbelt 209761.56 Eastern 622136.12 Luapula 134269.57 Lusaka 97448.57 Muchinga 246587.91 Northern 283250.44 North-Western 195584.8 Southern 486200.8 Western 61120.55

Total 1504462.6 Where x is the province in Zambia and y is the harvested tonnage per province

2.3.1 Factors affecting maize production Maize production is affected by a number of challenges and these can be attributed to policy, socio-economic, technological, abiotic and biotic factors (Chemiat and Makone, 2015). Low and stagnant agricultural productivity especially for major crops like maize in sub-Saharan Africa has been attributed to smallholder farmers who mainly produce under rain-fed conditions. These lack inputs such as fertilizer, improved seeds, irrigation, uncertain variable rainfall and poor soils (M'mboyi, et al., 2010; Musaba and Bwacha, 2014). In maize production the dominant biotic stresses include stem borers, diseases both fungal and bacterial infected, Striga infection, maize weevil (Sitophilus zeamais Motschulsty) and the larger grain borer (LGB) (Prostephanus truncates Horn) in storage (M’mboyi et al., 2010). Of interest in this study is the maize ear rot caused by a fungal pathogen, S. maydis.

Figure 2: Distribution map of Stenocarpella maydis in the world:

(Source: Knowledge Bank, 2016)

2.3.1 Distribution and Epidemiology of Stenocarpella maydis Stenocarpella ear rot is distributed throughout the world (Figure 2) with a predominant occurrence in the southern hemisphere. It is a seed transmitted and soil- borne disease of maize (Zea mays L.) (Rossouw et al, 2009). The life cycle of S. maydis is presented in Figure 3.

Yield losses are considerable under warm humid environments particularly when there is extended rainfall during silking to harvest period (Smith and White, 1988; Rossouw et al.,2009; Van Rensburg and Ferreira, 1997).

Figure 3: Stenocarpella maydis ear rot life cycle. A. Inoculum of S. maydis survives in infected maize residue on the soil surface. B. Splashing water spreads conidia to the ear infecting it through the ear shank or silks. C. Ears and husks can prematurely die. D. Dense white mold begins at the base of the ear, later it becomes grayish-brown, eventually engulfing and rotting the entire ear. E. Small black pycinidia can also form on the kernels.

Source: (Network C. P., 2016)

Infection of maize by S. maydis may be increased by the prevalence of bird and insect damages to ears and stalks and due to stem lodging (Urban-campaign, 1991; White, 1999). Well covered ears by husks and maturing in a droopy or suspended position usually have less ear rots as compared to those with open tips, loose husks and maturing in an upright position (Smith and White, 1998). S. maydis have a preference to colonize the pedicel and embryo of the kernel (Bensch, 1995). From the base tissues of the cob the pathogen grows into the kernels during the early stages of ear development.

The environment is a critical factor for disease and probable epidemic development of S. maydis in the presence of inoculum and a susceptible host. Genotypic resistance

11 over locations and seasons vary due to climatic conditions and inoculum potential (Flett and McLaren, 1994).

2.3.2 Management of Stenocarpella maydis Inoculum builds up and overwinters on maize stalk stover recollected on the soil surface or partly buried (Flett, 1991; Crafton, 2016). Cultural practices such as no-till and minimum tillage also result in the increase of inoculum due to more plant debris being left on the surface of the soil where the pathogen can overwinter (Latterell and Rossi 1983). Other cultural control approaches such as crop rotation, complete tillage and sanitation has been used to control ear rots but with equally limited success (Flett and Wehner, 1991). Planting maize at optimal plant populations and avoiding abnormally high plant populations could increase water stress. Planting at optimum times to reduce cold and heat stress and ensuring sufficient nutrient levels in the soil can reduce the incidence of S. maydis ear rots (Rossouw et al., 2009).

Ear rots can be successfully managed with applications of Benomyl, Mancozeb, or a mixture of Benomyl and Carbendazim fungicides (Beukes and Flett, 1992; Marley and Gbenga, 2004). Nevertheless, chemical control is considered as a last resort because it is not economically feasible to small scale farmers due to high cost (Rossouw et al., 2009). The most cost-effective and long term solution to manage S. maydis is through genetic resistance of genotypes (Rossouw, 2001).

2.4 Breeding for resistance to Stenocarpella maydis Selection of resistant genotypes to S. maydis will depend on type of pathogen inoculation method employed, skill of scoring and selection of resistant genotypes (Mesterházy et al., 2011; Tembo et al., 2013).

2.4.1 Isolates of Stenocarpella maydis Variations among isolates of S. maydis have been reported and may have different effects (Dorrance et al., 1999). Other authors have reported isolates which exhibited inhibition of growth at the edge of cultures and aversions among isolates in host tissues and culture media (Hoppe, 1936). Equally other isolates were examined from several states in the United States of America and the Republic of South Africa and differences were observed in mycelial growth temperature requirements and pathogenicity (Young et al., 1959). Isolates within S. maydis may exhibit differences

12 in mycelial colour, pycinidiospore production and phenotypic colour (Dorrance et al., 1999). Generally, S. maydis (Figure 4) spores are septate.

Figure 4: Picture showing spores of S. maydis as observed under a microscope.

Source: Forestry images: Bachi, 2017

2.4.2 Types of artificial inoculation The unpredictability of natural infection triggered the development of artificial inoculation techniques to induce disease and allow for discrimination among genotypes. In the past a number of techniques have been used in screening for ear rots such as dropping a spore suspension among the silks with a medicine dropper and brushing of the ear or silk with agar-spore slurry (Villena, 1969). Lately techniques utilized include conidial suspension, injection into the ear (Matiello et al., 2015); placing of ground kernels into the whorl (Rossouw et al., 2002); and the use of infested toothpicks inserted into the base of the ear (Rossouw, et al., 2000; Mukanga et al., 2011; Tembo et al., 2013).

The colonized toothpick inoculation method at the base of the ear was preferred in this study because it is efficient, rapid, and easy to use and allows favorable discrimination of genotypes (Rossouw et al., 2000; Mukanga et al., 2010; Tembo et

13 al., 2013). The aggressiveness of the technique allows for high level of infection severity and consistence in disease establishment which allow for rigorous discrimination among genotypes (Chambers, 1988; Reid and Hamilton, 1996; Rossouw et al., 2000; Jeffers, 2002).

2.4.3 Indirect selection for resistance Indirect use of agronomic related characteristics like grain texture, husk cover and drooping of the ear can be considered for deployment to enhance selection for resistant genotypes. Rossouw et al., 2002 reported that open husks at the cob tip allows for rain water to get inside the husks and into the cob and this creates a favorable micro-environment for disease development. Correlation of husk cover and ear drooping to disease severity has been reported (Pereira et al., 2015; Tembo et al., 2016). Hence selecting for well covered ears could possibly help in indirectly selecting for resistant genotypes. While drooping of the ear allows for rain water to drain off from the ear, this results in a much drier micro-environment that results in less ear rot (Rossouw, 2002). However, conflicting information about the correlation of grain type (flints, semi-flint, dents and semi-dents) to disease severity of S. maydis have been reported (Czembor and Ochodzki, 2009; Mario et al., 2011; Tembo et al., 2016).

2.4.4 Combining ability and inheritance to Stenocarpella maydis Inheritance of resistance to ear rots is complex and conflicting results have been obtained (Reid et al., 1992; Gevers et al., 1992; Dorrance et al., 1998). However, germplasm with resistance to S. maydis exists (Clements et al., 2004; Rossouw et al., 2009). Resistance to S. maydis has been found to be environmentally dependent (Mukanga et al., 2010) implying that germplasm need to be tested in each particular environment. Previous work by Tembo et al., 2013 revealed that genotypes with stable general combining ability (GCA) across environments exist. Identification of stable genotypes with desirable general combining ability (GCA) or specific combining ability (SCA) is important as such genotypes are likely to perform well across environments.

Whereas most authors agree that the nature of gene action conditioning resistance is predominantly additive (Das et al., 1984; Dorrance et al., 1998; Tembo et al., 2013), others found out that it is predominantly non-additive or both additive and non-

14 additive (Rossouw et al., 2002; Reid et al., 1992). Previous studies have been carried out without any regards to isolates employed (Dorrance et al., 1998; Rossouw et al., 2002; Tembo et al., 2013). There is a possibility that the isolate virulence may differ. In addition, a combination of isolates may have different effects on virulence compared to single isolate infection.

CHAPTER 3

MATERIALS AND METHODS

3.1 Germplasm used in the study

Seven white-kernel inbred lines that were utilized in the study were obtained from a public institution. These were previously evaluated and were found to have varying reactions to S. maydis infection (Table 2).

The inbreds were mated in a 7 x 7 half diallel, generating a total of 21 off springs (crosses). These crosses together with their parents (Table 1) were further evaluated during 2015/ 2016 cropping season. The diallel crossing block (nursery) was planted in Mpongwe (13o 32’S; 28o 03E, altitude 1206 m) at Mpongwe Seed Company Research Station (MSRS) during the off season of 2014/ 2015 season.

Table 2: Germplasm used in the experiment for S. maydis in Lusaka and Mpongwe

Parent Name Type Source Grain text Reaction to S. maydis

P1 XL 003 Inbred line Public Resistant F P2 XL 029 Inbred line Public Susceptible SF P3 XL 057 Inbred line Public Resistant F P4 XL 071 Inbred line Public Susceptible F P5 XL 083 Inbred line Public Moderate SF P6 XL 087 Inbred line Public Resistant F P7 XL 195 Inbred line Public F Resistant Where P- parent line, XL- experimental line, Grain texture, F-flint, SF-semi flint

3.2 Study sites management and experiment design

The evaluation trials were planted in December 2015/ 2016 cropping season at Lusaka West Seed Company Research Station, (150 24’S; 280 04’E, altitude 1216 m) and in Mpongwe at Mpongwe Seed Company Research Station, (13o 32’S; 28o 03E, altitude 1206 m ). The rainfall received during the 2015/ 16 cropping season was approximately 812 mm and 897 mm for Lusaka and Mpongwe respectively. Standard agronomical practices such as weeding, and fertilizer application were followed. Fertilizer was applied at each site as compound D (N 35%; P2O5 70%; K2O 35%) 350 kg/ha and 300 kg/ha of top dressing, Urea (46 % N). The trial layout was a randomized complete block design (RCBD), with parents and crosses assigned randomly, with three replications per location. The plants were established in two- row plots, 5 m long and 0.75 m apart and 0.25 m between plants. Trials were hand planted with two kernels per station and later thinned at two weeks to one plant after emergence to a uniform stand of 20 plants per 5 m. The cobs were inoculated with isolates of S. maydis approximately 3-4 weeks after mid-silking stage (Clements et al., 2003).

3.3 Pathogen isolation and culture

The pathogens used in the study were isolated from naturally infected rotten cobs collected from two agro-ecological zones of Zambia during the 2014/15 season i.e. Region II, Lusaka (150 24’S; 280 04’E) and Region III, Mpongwe (13o 32’S; 28o 03E) representing the medium and high rainfall areas of Zambia where the incidence of S. maydis ear rots are rampant under ideal climatic conditions. Ten (10) naturally infected cobs were collected from each region. The cobs were shelled separately, kernels mixed thoroughly, and a representative sample drawn from each sample as per Zecchinelli, (2013) standards. The samples were labelled isolate A and B denoting samples from Region II (Lusaka) and III (Mpongwe) respectively.

Potato dextrose agar (PDA) medium was prepared by weighing 3.9 % of PDA powder into glass bottles filled with 500 ml of distilled water in order to culture isolate A and B. The mixture was boiled while stirring until the powder dissolved completely. The bottles with the solution were then transferred to an autoclave for sterilization. The bottles and contents were autoclaved for 15 minutes at 1210 C at a

17 pressure of 15 MPa. 50 millimeters of the PDA solution was later poured into each of the 50 jars under the film board and left to cool overnight. Ten petri dishes were also filled with PDA solution and left to cool overnight. The petri dishes were used for initial culturing of the pathogen.

3.3.1 Inoculation and evaluation of isolates obtained from Region II (Lusaka) and III (Mpongwe)

Infected grain from Region II (infected with isolate A) and Region III (infected with isolate B) were first sterilized in domestic bleach of the JIK brand that contains 3.5% sodium hypochlorite (NaCIO) (Reckitt Benickiser South Africa (Pvty) Limited) solution for three minutes and then rinsed thrice in distilled water. The seeds were later blotted on sterilized filter paper under the film board to dry and then 3-4 seeds were plated on 3.9% PDA agar plates and incubated at 25-300 C. A plug of mycelium from a five-to-six-day old culture of S. maydis (prepared in section 3.3), was later transferred and placed at the center of a fresh PDA plate each with twelve autoclaved maize kernels clearly marked isolate A and B. To check for distinctiveness, the two isolates, A and B were evaluated for morphological differences and number of spores produced, 21 days after inoculation as done by Rossouw et al., 2002. The experiment was laid using a completely randomized design with three replications. The number of spores in each rep were counted and analyzed for spore production. The culturing was done by placing the plates in the incubator at 25-300C. After 21 days, the colonized kernels from one plate were placed in a blender with 80 ml of water and ground for 60 seconds to dislodge the spores. The suspension was filtered through four-layer cheese cloth. Spore counts were done using a hemocytometer from each replicate.

3.3.2 Toothpick- inoculum preparation

Toothpick-inoculum preparation was done using the modified procedure by Chambers (1998). A composite sample, from 10 naturally infected cobs, of S. maydis colonized kernels from the hot spot areas, each region denoted isolate sample A (Region II, Lusaka West) (150 24’S; 280 04’E) and B (Region III, Mpongwe) (13o 32’S; 28o 03E ) were first sterilized in domestic bleach of the JIK brand that contained 3.5% sodium hypochlorite (NaCIO) (Reckitt Benickiser South Africa

(Pvty) Limited) solution for three minutes and then rinsed thrice in distilled water. The kernels were blotted on sterilized filter paper to dry and then 3-5 kernels were plated on petri dishes with 3.9% potato dextrose agar (PDA) and incubated at 27- 300C. After 4-5 days the fungal growths on the plates were sub-cultured and ready to be transferred to toothpicks after 5-7 days.

The toothpicks were initially sterilized by boiling in water for 20 minutes and later air dried to room temperature. The toothpicks were then transferred to glass and plastic bottles which were initially autoclaved for 15 minutes and left to cool to room temperature. The bottles were filled with freshly prepared potato dextrose agar (PDA) and left to cool overnight to room temperature. The toothpicks were transferred to the bottles by placing them in an upright position in the bottles under the fume board (Plate 1). The plastic bottles contained approximately 100 toothpicks while the glass jars had between 150-200 toothpicks. Fungal culture plugs from pure cultures of each isolate of S. maydis were placed in specific bottles containing sterile toothpicks to allow the pathogen to fully colonize the toothpicks for about 10 days for the toothpicks to be used as carriers for inoculum. Fully colonized toothpicks were air dried before inoculating the genotypes.

Colonized bottle

Plate 1: Picture showing colonized toothpicks.

3.3.3 Inoculation of test ears

Inoculation was done by piercing through the base of the test ear. This was done 3-4 weeks after mid silking stage. Three treatments were used. Thus treatment 1, involved single inoculation using a toothpick colonized separately with isolate A; treatment 2 was done using single inoculation with toothpick colonized with isolate B and treatment 3, multiple inoculation (AB) using two toothpicks colonized by two different isolates A and B as done by Tembo et al., (2013). This was achieved by inserting, these two toothpicks 5 mm apart into the base of the ear (Plate 3). Treatment 4, control was left without any inoculation at all in the second row. For each treatment five (5) plants were inoculated and these were separated by three (3) un-inoculated plants which acted as borders. Artificial inoculation encourages symptom development and disease progression and thus five plants were considered enough for assessment of the disease.

Colonized toothpick

Plate 2: Single inoculations of the test ear with Isolate A or B of S. maydis. Inoculation was done at 3-4 weeks after mid silking stage.

Colonized toothpick with isolate A

Colonized toothpick with isolate B

Plate 3: Multiple inoculations (AB) of the test ear with two isolates A and B of S. maydis. Cobs were inoculated at 3 – 4 weeks after mid silking stage with the toothpicks placed approximately 5 mm apart.

Single inoculations were performed in the first row with each isolate inoculation separated by three non-inoculated plants. Multiple inoculations were performed in the second row of the plot with the remaining plants treated as control and border plants.

3.4 Data collection and analysis

The plants were harvested at maturity and data was collected. Disease severity score was determined visually from all the five (5) inoculated plants per treatment in 5 m long first two row plots. Each inoculated treatment per genotype was harvested separately and the plot number noted. Percentage ear rot (ER) was estimated visually (Plate 4) using percentage of ear colonized by the pathogen from the point of infection was made for each ear and the mean disease severity ratings computed. The rating was done using modified procedure by Tembo et al., (2013) with an S. maydis severity rating score as follows: 1= 0-25%; 2= 26-50%; 3= 51-74%; 4= 75-84%; 5=85-94%; 6= 95-99% and 7= 100% (completely rotten).

1 2 3 4 5 6 7

Plate 4: From left to right the trend for visual disease severity scores of the infected cobs. Severity rating scores for S. maydis; 1 = 0 - 25%, 2 = 26 - 50%, 3 = 51 - 74%, 4 = 75 - 84%, 5 = 85 - 94%, 6 = 95 - 99% and 7 = 100%.

Diallel analysis was performed using Griffing (1956) method 2, model I, fixed model in GenStat using Restricted Maximum Likelihood (REML) and regression approaches. The relative contribution of SCA (specific combining ability) was estimated. The parents and a set of F1 genotypes were analyzed. Statistical analysis using mean genotypic scores of the genotype used the following model by Griffing, 1956:

Yij= µ + gi + gj + Sij + eij

Where is the mean genotypic score, is the overall mean ; and is the general combining ability (GCA) effects of the ith and jth parents respectively; is the specific combining ability (SCA) effect of the cross between the ith and jth parents and eij is the experimental error.

Table 3: Expected mean squares and interpretations of a half-diallel Method 2,

Model I

Source of variation df EMS Replication

GCA

SCA

Error

Total

Where: and refer to number of replications and parents per diallel respectively.

Source: Griffing (1956)

Table 3 shows the expected mean squares and interpretations of a half-diallel design (Method 2, Model I).

Bakers ratio = , was used to determine the relative contribution of GCA and SCA i.e. additivity and non-additivity where and are the variance components of GCA and SCA respectively.

A paired two tailed t-test, was performed to compare all the possible two mean differences for S. maydis diseases severity scores among the three treatments (Treatments 1 [Inoculation with Isolate A], 2[Inoculation with Isolate B] and 3[Multiple inoculation with Isolate A & B]). This was performed in Microsoft excel 2010.

Husk cover (HC) was determined from the plants in un-inoculated two rows by estimating the openness of the husk over the tip of the ear where 1= husk with total cover of the ear and 5= poor husk cover with tips and grains exposed (CIMMYT, 1985). Ear declination (ED) of the ear relative to the stalk was determined at an average rating on a scale of one to five where 1= fully erect ears and 5= ears fully declined against the stalk. Grain texture (GT) for each treatment genotype was

23 estimated using a modified procedure by CIMMYT (1985) 1- 4 where 1= flint, 2= semi-flint, 3= semi-dent and 4= dent.

Data was collected on husk cover, ear declination and grain texture. These parameters were subjected to analysis of variance (ANOVA) and regression approaches using GenStat16th edition software. The means were separated using Fisher Protected Least Significance Difference (LSD) at P = 0.05. The association between disease severity under single and multiple inoculations of S. maydis to husk cover; ear declination and grain texture were determined using correlation analysis in GenStat.

CHAPTER 4

RESULTS

4.1 Characterization of Isolates

Isolates A obtained from Region II, (Lusaka) and B obtained from Region III, (Mpongwe) after incubation for 21 days showed some phenotypic differences (Plate 5). Generally, across plates, Isolate A showed a much darker color, black brown as compared to isolate B which showed pale brown color.

Production of spores by isolate A and isolate B after 21 days of incubation were evaluated using a hemocytometer (Table 3) which revealed significant (P < 0.01) differences between them. The mean spore counts between isolate A and B were 2.5 x 105 spores/ml and isolate 8.31 x 105 spores/ml respectively (LSD = 3.47x105).

Isolate A

Isolate A Isolate B

Plate 5: Phenotypic differences between isolate A exhibited a dark brown color and isolate B exhibited light brown color 3 weeks after inoculation.

Table 4: Analysis of variance for spore counts between isolates evaluated in the laboratory at the University of Zambia, School of Agricultural Sciences Source of variation df MS Isolate 1 5.13 x1011** Error 4 2.46 x1010 ** Highly significant at P ≤ 0.01

4.2 Effect of multiple isolate inoculations The mean disease severity scores across genotypes for treatment 1, treatment 2 and treatment 3 were 5.52, 4.96 and 5.50 respectively. A student’s paired t-test (Table 5) performed on comparison of treatment 1 mean disease severity score comparison (MDSC) and treatment 2, indicated highly significant (P < 0.001) differences. Significant mean disease severity score differences were equally found between treatment 2 MDSC and treatment 3 on disease severity.

Table 5: Genotypic mean disease severity score comparisons (MDSC) among treatments MDSC Student t-test (P- Value) Treatment 1 (5.52)x vs Treatment 2 (4.96) y < 0.001 Treatment 1 (5.52)x vs Treatment 3 (5.50)z 0.13 Treatment 2 (4.96)y vs Treatment 3 (5.50)z < 0.001 x, y, z mean disease severity score across genotypes for treatments 1, 2 and 3 respectively. Treatment 1, 2 and 3 represents treatments with: single inoculation with isolate A, Single inoculation with isolate B and multiple inoculations of Isolates A & B respectively.

4.3 Stenocarpella maydis ear rots genotypic disease severity effect and combining abilities Significant differences were obtained among genotypes with regards to S. maydis disease severity scores across inoculation treatments in each location (Table 6)

Table 6: Mean squares for Stenocarpella maydis cob rot disease severity scores across two experimental locations and in each individual location evaluated in 2015/16 season.

Across locations Individual sites Source of variation df Across locations df Lusaka Mpongwe Location 1 241.01** Replication/location 4 2 4.01 11.56 Genotype 27 4.69 27 1.95** 5.40** GCA 6 0.96 3.84 SCA 21 2.64*** 5.64** Isolate 3 770.44*** 3 557.54** 247.82** Location x Genotype 27 2.83** 27 Location x isolate 3 35.51*** 3 Genotype x isolate 81 1.80 81 0.62 2.52 Gen x Isolate x location 81 1.35 81 Error 444 1.06 222 0.5 2.02

**, *** significant at P ≤ 0.01, and P ≤ 0.001 respectively, MS, mean square

(P < 0.01). Similarly, across location data shows that the interaction between location by genotype and location by isolate were highly significant (P < 0.01 and 0.001 respectively).

Further analysis per location (Table 6) above revealed that specific combining ability (SCA) were highly significant (P < 0.001) in both locations.

The genotypic mean disease severity effects of each isolate vis-à-vis, treatment 1, treatment 2, treatment 3 and treatment 4 [as the control on the test genotypes] are tabulated in table 7 below.

Table 7: Effect of treatments on the test genotypes across the locations during 2015/16 cropping season.

Treatment Mean Treatment 1 5.52 Treatment 2 4.96 Treatment 3 5.50 Treatment 4 1.00

LSD (α = 0.05) 0.23 LSD, Fishers Protected Least Significant Difference test performed at P ≤ 0.05 Treatment 1, 2, 3 and 4 are: Single inoculation with isolate A, single inoculation with isolate B, multiple inoculations with isolate (A & B) and control without any inoculation respectively.

Specific combining ability (SCA) effects (Table 8) for the crosses in Lusaka showed that (P1 x P4), (P2 x P4), (P3 x P7) and (P6 x P7) had negative significant (P < 0.05) SCA effects while (P3 x P6) and (P4 x P5) showed negative significant (P < 0.01) SCA effects. Highly significant (P < 0.01) positive SCA effects were shown by the crosses (P2 x P6) and (P4 x P7) while (P3 x P4) showed highly significant (P < 0.001) positive SCA effects.

In location 2 (Mpongwe) crosses (P2 x P4) and (P3 x P6) showed negative significant (P < 0.05) SCA effects while (P3 x P4) showed positive significant (P < 0.05) effects with (P2 x P6) exhibiting positive highly significant (P < 0.01) SCA effects.

Baker’s ratio (BR) across the locations was computed to verify the gene action conditioning resistance to S. maydis. The Baker’s ratio in Lusaka and Mpongwe were found to be 0.012 and 0.03 respectively. This indicated that the gene action conditioning resistance was mainly due to non-additive gene effects.

Table 8: Specific combining ability effects of the crosses for disease severity scores across treatments in Lusaka and Mpongwe during 2015/16 cropping season

Lusaka Mpongwe Cross‡ Mean SCA Effect Mean SCA Effect P1XP2 3.86 -0.02ns 3.13 0.02ns P1XP3 4.11 0.04ns 3.546 0.13ns P1XP4 4.06 -0.40* 3.528 -0.48ns P1XP5 4.25 0.04ns 3.421 -0.06ns P1XP6 4.44 0.17ns 4.046 0.28ns P1XP7 4.17 0.17ns 3.25 0.11ns P2XP3 3.92 0.12ns 3.505 0.42ns P2XP4 3.79 -0.39* 2.917 -0.76* P2XP5 3.81 -0.13ns 2.88 -0.27ns P2XP6 4.50 0.51** 4.333 0.90** P2XP7 3.63 -0.09ns 2.504 -0.30ns P3XP4 5.05 0.67*** 4.684 0.70* P3XP5 4.26 0.13ns 3.338 -0.12ns P3XP6 3.65 -0.54** 2.88 -0.86* P3XP7 3.50 -0.42* 2.833 -0.28ns P4XP5 4.07 -0.45** 3.976 -0.07ns P4XP6 4.61 0.04ns 4.478 0.15ns P4XP7 4.83 0.53** 4.167 0.47ns P5XP6 4.54 0.21ns 3.833 0.03ns P5XP7 4.26 0.20ns 3.669 0.49ns P6XP7 3.73 -0.38* 2.963 -0.50ns S.E 0.18 0.37

ns, *, **, *** Data not significant, significant at P ≤ 0.05, P ≤ 0.01 and P ≤ 0.001 respectively. SE- Standard error of the mean; ‡ Crosses derived from parental inbreds P1 to P7 as described in Table 7.

4.4 Indirect trait selection of resistant genotypes to Stenocarpella maydis

Selection of resistant genotypes to S. maydis ear rots can be enhanced by the indirect use of agronomic disease related traits such as ear declination (droopiness), grain texture and husk cover.

In Lusaka (Table 9) negative correlations (r = -0.58 and r = -0.63) were found between two diseases related characteristics regarding, grain texture and husk cover respectively to the mean disease severity scores across treatments. Positive correlations (r = 0.56) were found for grain texture with ear declination, husk cover with grain texture (r = 0.55) and husk cover with ear declination (r = 0.71). Equally for Mpongwe, grain texture and husk cover with mean disease severity score across treatments showed negative (r = -0.58) and (r = -0.70) correlations respectively. Husk cover correlation with ear declination and grain texture indicated positive (r = 0.56) and (r = 0.67) relationships respectively. Equally grain texture with ear declination showed positive (r = 0.49) correlation.

Table 9: Association of mean disease severity with agronomic traits measured for genotypes in Lusaka and Mpongwe

Locality Variable ED GT HC Lusaka ED GT 0.56** HC 0.71*** 0.55** MDS -0.29 -0.58*** - 0.63***

Mpongwe ED GT 0.49** HC 0.56*** 0.67*** MDS -0.32 -0.58*** - 0.70***

*, *** Data significant at P ≤ 0.01 and 0.001 respectively; ED = ear declination; GT = grain texture; HC = husk cover; MDS = Mean Disease Severity Score for S. maydis

CHAPTER 5

DISCUSSION

Breeding for stable resistance against ear rots of maize caused by Stenocarpella maydis has been a challenge, primarily due to environmental factors. In addition, breeders have previously bred for resistance to S. maydis without particularly taking the aspects of isolates into consideration (Rossouw et al., 2002). It remains to be established if isolates have an effect in breeding for stable resistance. It was for this reason that the effect of isolates in breeding for resistance was investigated in this study. It was therefore, necessary to ensure that utilized isolates were distinct from each other.

Phenotypic differences in appearance of isolate A and B from the agar plates was observed as indicated (Plate 5). Isolate A exhibited a much darker brown- black color as compared to isolate B which had a pale- brown color. This suggests that the two isolates could be distinct. Further analysis on spore production per mm2 (Table 4) showed high significant (P < 0.001) differences between isolate A and isolate B indicating the possibility of distinctiveness of the two isolates being investigated. Earlier studies similarly indicated that variation occurs among isolates of S. maydis for phenotypic color, spore production and the degree of virulence (Dorrance et al., 1998; Rossouw et al., 2009).

A paired t-test revealed that mean disease severity scoring for treatment 1 was higher than that for treatment 2. The fact that the mean disease severity for treatment 3 was higher (P < 0.01) than treatment 2, but not significantly different from treatment 1, indicates that isolate A could have suppressed the virulence effect of isolate B when multiple inoculated. Previous studies on ear rot pathogens discouraged multiple inoculations of ear rot pathogens as a breeding strategy (Tembo et al., 2013) because of the antagonistic effects which may arise due to multiple inoculations of different pathogens. This study reports the effect of multiple isolate inoculations which have not been fully exploited recognizing that different isolates exists for S. maydis. However, contradictory information has been reported in sweet potato and common beans upon multiple infections with sweet potato virus disease (SPVD) and

Collectorichum lindemuthianum respectively, whereby in this scenario synergistic interactions occurred (Gibson et al., 1998; Gasura and Mukasa, 2010; Chilipa et al., 2016).

From the current and previous research, it can be deduced that multiple inoculation can either create antagonistic or synergistic effects. Multiple inoculations among different pathogens or isolates of the same pathogen with synergistic effects can be reliable and a beneficial screening approach for breeders. On the other hand multiple inoculation approach of pathogens with antagonistic effects generates less informative genetic information (Tembo et al., 2013).

The 7 x 7 half diallel (Table 8) analysis for S. maydis ear rot mean disease severity for the crosses in location 1 (Lusaka) and location 2 (Mpongwe) indicated that specific combining ability (SCA) effects of the crosses across isolates were highly significant (P < 0.001). The Baker’s ratio (BR) of 0.012 and 0.03 for Lusaka and Mpongwe respectively indicated that the nature of gene action to S. maydis across inoculations was conditioned predominantly by non-additive gene action in both locations. Therefore, the best breeding approach would be through the production of hybrids.

Previous studies have revealed contradictory results. While some authors suggested additive gene action, others suggested non-additivity or both (Mc Lennan 1991; Dorrance et al., 1998; Chungu et al., 1996; Mukanga et al., 2010; Reid et al., 2009; Tembo et al., 2013). Differences obtained might be due to the environment, inoculation technique and germplasm under study. In this study no parental genotypes (Table 6) were identified to possess significant general combining ability (GCA) effects. Previous studies have reported genotypes with good general combining ability (GCA) effects (Mukanga et al., 2010; Tembo et al., 2013), an indication that this is dependent on type of germplasm used. However, some crosses were found to possess significant specific combining ability (SCA) effects in both locations. Specific combining ability (SCA) effects can also assist in ascertaining which parental materials can be utilized in hybridization. In Lusaka six crosses; (P1 x P4), (P2 x P4), (P3 x P7), (P6 x P7), (P3 x P6) and (P4 x P5) had negative significant (Table 8) SCA effects. This implied that these crosses exhibited higher resistance to S. maydis in their specific combinations when compared to other

32 crosses with either one of the parents in common. In Mpongwe (P2 x P4) and (P3 x P6) had negative significant (P < 0.05) SCA effects. Therefore, crosses (P2 x P4) and (P3 x P6) showed consistence negative significant SCA effects in both locations. Crosses which exhibited negative specific combining abilities only in one specific location could be planted or produced specifically for those locations. However, for those crosses which showed consistent negative specific combining abilities (SCA) could be planted in both locations and be able to give good results. However, since the locations were regarded as random in this model, there is still need to re-evaluate all the desirable genotypes across the agro-ecological zones using mixed model with location being fixed. This will give us relatively reliable performance tests for each location. It has been shown in this study that parental genotypes involved in a cross do not need to be resistant to produce a hybrid with desirable SCA effect. For example, cross (P2 x P4) is comprised of two susceptible parental lines. This means in certain cases resistance and susceptibility exhibited by the crosses can be attributed to specific combining ability (SCA) effects related to non-additive gene action such as epistasis (Rossouw et al., 2002; Shashikumar et al., 2011).

The correlations analysis conducted on non-inoculated cobs showed significant positive and negative correlations among different disease related traits in both locations. Grain texture was significantly negatively correlated (r = - 0.58) (P < 0.01) to mean disease severity across treatments in both locations. This indicated that as the mean disease severity score was increasing the score for grain texture was reducing implying that dents were more resistant relative to the flints. Similar results were reported by Mario et al., 2011 who found that dents had a lower disease severity relative to the flints. However, other studies reported conflicting results that flints were more resistant to ear rots relative to dents (Czembor and Ochodzki, 2009; Tembo et al., 2016). The differences can be attributed to other interacting genetic factors that influence resistance to ear rots. The other factor could also be the increase in chemical composition of the kernels in amylose, phenol content and chitinase activity which have a negative correlation to disease severity meaning that higher concentrations of these reduce disease incidence (Hefny et al., 2012). However, in our study the amount of phenotypic variation explained by grain texture was found to be low (r2 = 0.34) indicating that texture cannot substitute direct selection but can only supplement it. Equally husk cover in Lusaka and Mpongwe

33 was highly significant (P < 0.001) negatively correlated (r) values of – 0.63 and – 0.70 respectively to genotypic mean disease severity. Negative correlations implied that the mean disease severity was favored by closed tips. However, other studies have reported conflicting results were closed tips had less ear rot infections as compared to open tips (Rossouw et al., 2002). In this study, there is a possibility that cobs with open tips may have possessed tight husks and the reverse may have been true with closed husk tipped cobs. Tight husks were found to cause less ear rot due to relatively less moisture which is harbored within the cob, creating a relatively less conducive micro environment for fungal growth and multiplication (Rossouw et al., 2002; Tembo et al., 2013). The contradictory results may also suggest that there could be other underlying genetic factors that influence resistance to ear rots such as chemical composition as earlier alluded (Hefny et al., 2012). In this study, the amount of phenotypic variation explained (r2) accounted for 40% and 49% in Lusaka and Mpongwe respectively for husk cover. On the other hand, grain texture accounted for 34% phenotypic variation explained in both locations. In summary, the computed r2 values for the amount of phenotypic variation explained for evaluated agronomic traits where low to suffice for the substitution of direct selection with indirect selection methods. Similar results were reported by Hefny et al., 2012 who concluded that resistance to Fusarium moniliforme should be directly evaluated by resistance itself than the use of agronomic traits in breeding programs.

CHAPTER 6

CONCLUSION AND RECOMMENDATIONS

6.1 CONCLUSION

The specific combining ability (SCA) effects were found to be significant in Lusaka and Mpongwe. The estimated Baker’s ratios were 0.012 and 0.03 for Lusaka and Mpongwe respectively, indicating non- additive gene effects were important in breeding for resistance to S. maydis. Two crosses (P2 x P4) and (P3 x P6) showed consistence by negative SCA effects in two locations (Lusaka and Mpongwe). It can be predicted that the genotypes [(P2 x P4) and (P3 x P6)] can be produced and marketed in the two locations. In breeding for resistance to S. maydis, multiple isolate inoculation technique was found to be inappropriate due to the possibility of antagonistic effects of the isolates as it could lead to misleading genetic information.

In consideration of indirect selection using agronomic traits, this study found that indirect selection using agronomic traits (in this case grain texture and husk cover) cannot be employed as a selection criterion but can be used as a supplement to direct selection due to low R values (less than 0.50).

6.2 RECOMMENDATIONS

The experiment should be repeated in other locations with different germplasm and probably other isolates to gain a further insight of the effect of isolates in breeding for resistance to S. maydis.

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