Maize is the most widely cultivated staple food crop in sub-Saharan Africa, where it contributes up to 70% of the daily caloric intake (Martin et al., 2000; FAO, 2007). It is a highly diverse grain crop with multiple applications and consists of different types, generally classified by kernel endosperm characteristics. The most common types of maize are flint, dent, flour, pop, pod, waxy and sweet.  The   physical   appearance   of   each    kernel    type   is determined by the endosperm pattern, quantity and quality. Cultivated maize varieties in West and Central Africa are mostly of the flint and dent types which have largely been improved by the use of both temperate and tropical exotic germplasm (Kim et al., 1987; Kim and Ajala, 1996).

Sweet corn (Zea mays L. var saccharata) is a highly perishable  vegetable  maize  crop, harvested exclusively for fresh human consumption when the grains are at the milk stage with approximately 75% moisture content. It is a type of maize with kernels that are sweet as a result of high sugar content which when consumed in the immature stage, has high levels of total sugars than normal field maize, rich in fibre, minerals and certain vitamins (Tracy, 1997; Lertrat and Pulam, 2007). It has also been reported to possess significant antioxidant properties which reduce the possibilities of developing cancer and inflammations in humans (Dewanto et al., 2002). Because of these qualities, sweet corn could play a significant role in the nutrition of the peoples of West and Central Africa (Adetimirin, 2008) where fresh green maize is an important component of human diet. The difference between sweet corn and field maize arises from a mutation that influences carbohydrate biosynthesis in the endosperm. In the genome of sweet corn, at least one of the eight mutant monogenic and recessive genes preventing the conversion of sugars to starch is present (Tracy et al., 2006; Qi et al., 2009; Santos et al., 2014) resulting in the characteristic sugary taste. Of these mutants, the four most useful are shrunken-2 (sh2), brittle-2 (bt2), sugary-1 (su1), and sugary enhancer (se). While sh2 and bt2, classified as class 1 mutants (super-sweet corn), are involved in large reductions in starch and large increase in sugar, su1 and se referred to as class 2 mutants (sweet corn) occur later in the starch biosynthesis pathway and influence the types and proportion of polysaccharides stored in the endosperm (Boyer and Shannon, 1984; Tracy, 1997). The grain of matured normal field maize is known to contain about 3% sugar, while sweet and super-sweet corns contain 9 to 14% and 15 to 30% sugar, respectively (Creech, 1965; Teixeira et al., 2013). The sh2 (Yousef and Juvik, 2002) and bt2 (Brewbaker, 1977) types of sweet corn have the greatest commercial value.

Nigeria produces about 40% of the maize production in West and Central Africa (FAO, 2016). Maize is grown throughout Nigeria from the high rainfall forest of the southeast to the low rainfall Sudan Savanna of the north. Widening food preferences have resulted in increased importation of canned sweet corn to Nigeria. Great potential therefore exists for the production and commercialisation of super-sweet corn. However, sweet corn cultivars are virtually nonexistent in Nigeria. To bridge the gap created by this challenge, a broad-base temperate super-sweet sh2 maize population was introduced into the country and adapted to the prevailing tropical environmental conditions by four cycles of mass selection (Adetimirin, 2008). This adapted population was meant to serve both as an open pollinated variety, as well as, basis for inbred line development.

Super-sweet corn has a narrow genetic base (Tracy, 2001; Teixeira et al., 2013; Mahato et al., 2018) and possesses some undesirable characteristics, such as poor field emergence and seedling vigour and susceptibility to diseases and pests.  In  addition,  tropical climatic conditions are characterized by high disease incidence, pest attack, short day length, and high temperatures. One way to improve the performance of this tropicalised population and broaden it genetic base is by crossing the sh2 maize with the more adapted field maize germplasm, which could be sources of favourable alleles for enhanced agronomic performance, as well as, increased disease and pest resistance. Previous studies (Tracy, 2001; Cartea et al., 1996; Malvar et al., 1997, 2001; Butrón et al., 2008; Entringer et al., 2017) have shown the utility of field corn in the improvement of agronomic performance of sweet corn. These studies have also indicated that field maize genotypes could differ in their ability to improve the agronomic performance and quality of sweet corn.

In order to develop hybrids, the source populations from which inbred lines are extracted for hybrid seed production should have superior qualities (Hallauer, 1990). One of such source populations are the open-pollinated varieties (Sleper and Poehlman, 2006; Hallauer et al., 2010). In this study, the estimates of variance components, heritability and genetic advance for measured traits in sh2 super-sweet corn populations derived from crosses between a tropicalised sh2 super-sweet corn population and tropical field maize genotypes were reported.

Experimental site

The study was conducted at the experimental field of the Department of Agronomy, Faculty of Agriculture, along Parry road, University of Ibadan (7°26' N, 3°54' E), Ibadan, Nigeria.

Experimental design and layout

Twelve sh2 populations, eleven of which were derived from crosses between tropical field maize genotypes and a tropicalised sh2 donor population were evaluated over two years in a randomised complete block design with four replicates. The soil at the experimental site is sandy-loam with 20.3 g kg^-1 organic carbon, 0.90 g kg^-1 total nitrogen, 17.90 mg kg^-1 available P (Bray-1), 0.28 cmol kg^-1 K and a pH (H₂O) of 6.2. The populations in each block were planted in four 5.0 m long rows spaced at 0.75 m apart. Seeds were sown at 0.50 m apart within the row. Four seeds were sown per hill and later thinned to two to give a plant population of approximately 53,333 plants per hectare. At two weeks after planting (WAP), NPK 15-15-15 fertilizer was applied at the rate of 45 kg N ha^-1. This was top-dressed at 4 WAP using urea at the rate of 25 kg N ha^-1. Hand weeding was done as necessary to keep the plots weed free.

All agronomic and fresh ear yield data excluding flowering data collect­ed on the two middle rows of each plot. Data on days to anthesis (DA) and days to silking (DS) were recorded as number of days from planting to when 50% of the plants in a plot shed pollen or have emerged silks, respectively. Anthesis-silking interval (ASI) was calculated as the difference between DS and DA. Plant height (PH) and ear height (EH) measured in meters were taken at fresh ear yield harvest on all plants in the two middle rows of a plot, as the  average  distance  from  the  soil  level   to   the   collar   of   the uppermost leaf and collar of the leaf bearing the uppermost ear, respectively. Husk cover (HC) was scored on a scale of 1 to 9 (1 = husk tightly covers ear tip and extends beyond it; 9 = poor husk cover with ear tip clearly exposed). Harvesting of fresh ears was done three weeks after silking. Fresh ear yield data included: number of cobs (NC; fresh ears with husk removed) harvested per plot expressed per hectare; yield of cobs (YC; fresh ears with husks removed) recorded as total weight of cobs harvested per plot expressed in tonnes per hectare; number of marketable cobs (NMC; cobs with approximately 250 filled edible kernels) per plot expressed per hectare; yield of marketable cobs (YMC) recorded as total weight of marketable cobs per plot expressed in tonnes per hectare; number of kernel rows (KR) recorded as the average number of kernel rows of 10 top cobs; cob length (CL) measured in cm as the average length of 10 top cobs; cob diameter (CD) measured in mm using an electronic 6 in. digital calliper (Pittsburgh^®, Item #47257), as the average diameter of 10 top cobs taken at the middle portion of the cob.

Data analyses

The PROC MIXED procedure in SAS (SAS version 9.1.3, SAS Institute, 2003) was used to compute variance components for all traits. In the model, populations and the interaction of populations by environment were considered random, while environments and replications within environments were fixed. Each year was considered a separate environment.

Genotypic (GCV) and phenotypic (PCV) coefficients of variation were computed for all traits according to Singh and Chaudhary (2004) using the equations:

GCV (%) = {(√ σ²_g) /x} × 100

PCV (%) = {(√ σ²_p) / x} × 100

where σ²_g = genotypic variance, σ²_p = phenotypic variance and x = grand mean for the trait.

The GCV and PCV were considered low when less than 10%, moderate when 10 to 20% and high when greater than 20% as explained by Deshmukh et al. (1986).

Broad-sense heritability and their standard errors were estimated using variance ratios as explained by Hallauer et al. (2010) using the following equations:

H² = {σ²_g/ (σ²_g + σ²_ge/e + σ²/re)} × 100

SE (H²) = SEσ²_g/ (σ²_g + σ²_ge/e + σ²/re)

where σ²_g = genotypic variance, σ² = environmental variance, σ²_ge = variance due to genotype by environment interaction, σ²_p = phenotypic variance = σ²_g + σ²_ge + σ², r = number of replicates, e = number of environments and SE = standard error.

Heritability estimates were categorized into low (less than 40%), medium (40-59%), moderately high (60-79%) and very high (80% and above) as described by Singh (2001).

Genetic advance (GA) was estimated using the formula by Singh and Chaudhary (2004):

GA = i σ_p h²

where i = 1.40 (selection intensity at 20.0%), σ_p = phenotypic standard deviation, h² = broad-sense heritability.

Genetic advance expressed as percentage of the mean was estimated as described by Souza et al. (2009) as follows:

GA (%) = GA/x × 100

where x = grand mean of all hybrids for the trait.

The GA was considered low (less than 10%), moderate (10-20%) and high (above 20%) according to Johnson et al. (1955).

Mean performance of populations

Selection of genetically superior genotypes as well as inbred lines for hybrid seed production requires sufficient genetic variability and high heritability in the base population. The populations evaluated in this study exhibited a wide range in values for all the traits assessed (Table 1). This indicates that a sufficient range of variability in all the traits exists among the populations. The presence of variability could be a consequence of the differences in the ability of the field maize genotypes involved in the development of derived sh2 populations to improve the donor sh2 population (Butrón et al., 2008; Entringer et al., 2017) as well as a reflection of the influence of environment on the expression of the traits.

Estimates of variance components, heritability and genetic advance  

Estimates of genetic variance (σ²_g) were significant only for YC, NC KR, HC, EH and DA, while estimates of environmental variance (σ²_e) were significant for all variables (Table 2). The estimates of genetic variances were higher than the corresponding environmental variances for all traits except PH and ASI. The EH had the highest significant genetic and environmental variances. The observed differences among the genotypes for most of the traits were therefore more due to genetic than environmental causes. The PCV estimates in this study were higher than the corresponding GCV for all traits, although the differences between values were low except for ASI. The PCV and GCV were high for HC, whereas only PCV was high for ASI. The GCV and PCV estimate for YC, as well as GCV for ASI and PCV for YMC were moderate. All other traits manifested low GCV and PCV values. The range in values of GCV and PCV were 1.43 (DS) to 26.50 (HC) and 1.75 (DS) to 30.05 (HC), respectively (Table 2). The slightly higher PCV than GCV for all traits in this study indicates that the expressions of the traits were influenced, though to a limited extent, by the environment and there is the possibility of improvement using phenotypic selection. Similar results indicating higher PCV than GCV for all traits were reported by Saleh et al. (2002), Alan et al. (2013) and Niji et al. (2018) in sweet corn as well as Maphumulo et al. (2015), Sesay et al. (2016) and Jilo et al. (2018) in field maize. The PCV for ASI was more than twice the GCV, an indication of limited chance for selection for the trait in the populations studied. Jilo et al. (2018) reported similar results for ASI. The high GCV exhibited by HC shows that the trait is less affected  by environmental fluctuations, which guarantees selection progress for the trait. High GCV estimates are indicative of low amenability of the trait to environmental changes (Hefny, 2011). Emphasis on HC is therefore important in the development of cultivars from the present genetic materials. In sweet corns, good husk covering is one of the most important quality characteristics (Tracy, 1997) as complete husk covering shields of the ears from earworm attack (Lynch et al., 1999; Gardner et al., 2000). Consistent with the results of the present study, Alan et al. (2013) and Niji et al. (2018) reported low PCV and GCV estimates for DA, DS, PH, CL and CD in sweet corn.

Estimates of broad-sense heritability ranged from 22.2% for ASI to 85.1% for DA. The heritability estimates were low for ASI, medium for PH, moderately high for YMC, NMC, YC, NC, KR, CL, CD, HC, EH and DS, and very high for DA (Table 2). Genetic advance expressed as a percentage of the mean ranged from 1.7 (DS) to 32.7 (HC). The YC and HC exhibited medium and high GA, respectively, while the estimates for all other variables were low (Table 2). In this study, heritability estimates were moderately high to very high for the traits considered, except PH and ASI.  However, the GA expressed as a percentage of the mean accompanying these estimates were low, except for YC with medium GA and HC with high GA. This suggests that genetic control of the traits was predominantly non-additive. Johnson et al. (1955) and Jilo et al. (2018) had previously suggested the simultaneous consideration of heritability estimates and GA because high heritability may not always be associated with high GA. These traits may respond to phenotypic selection and could be improved through heterosis breeding (Bello et al., 2012; Nzuve et al. 2014). The moderately high heritability estimate for HC in this study coupled with high GA indicated that husk covering is  a   quality   trait   exhibiting   additive  gene  action and selection for the trait would be effective. However, HC manifested high PCV suggesting a strong influence of environment on its expression.

The donor sh2 population used in this study was generously provided by Professor V. O. Adetimirin of the Department of Agronomy, University of Ibadan. The normal endosperm tropical field maize genotypes were sourced from the Maize Improvement Programme of the International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria. This research did not benefit from any specific grant whatsoever.