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Evaluation of hybrids Sorghum (Sorghum bicolor L. Moench.) for growth and yield in a rainforest agro-ecological zone

A field experiment was carried out during 2016 and 2017 cropping seasons at the Teaching and Research Farm of The Federal University of Technology, Akure with the aim of evaluating growth and yield performance of twenty-five hybrids sorghum. The experiment was laid out in a randomised complete block design with three replications. Data collected on seedling emergence count, number of days to 50% flowering, number of days to 95% maturity, plant height (cm), panicle length (cm), panicle diameter (cm), panicle weight (g), 1000-grain weight (g), number of seeds per panicle and grain yield (kg ha-1) were subjected to analysis of variance. The hybrids differed (p≤0.05 and p≤0.01) for all the traits except seedling emergence count. Estimates of variance component, broad-sense heritability, correlation analysis and rank summation index (RSI) were computed. High genetic advance (689.64 and 433.13) accompanied moderate heritability for number of seeds per panicle and grain yield respectively. Panicle length had positive and significant correlation with panicle weight, panicle diameter, number of seeds per panicle and grain yield (r = 0.36, 0.57, 0.27 and 0.36, respectively). Panicle weight had negative and significant correlation with 1000-grain weight (r = -0.32) but positive correlations was recorded in panicle diameter, number of seeds per panicle and grain yield (r = 0.38, 0.89 and 0.98). Nevertheless, number of seeds per panicle had positive significant correlation with grain yield (r = 0.84). RSI showed that hybrid ICSA38 × ICSV400 had the best performance with a mean rank of (4.8) and followed by ICSA38 × PIRIRA-2-1 with a mean rank of (6.6). Hence, due consideration should be given to these characters; panicle length, panicle weight and number of seeds per panicle while planning a breeding strategy for increased sorghum grain yield.


INTRODUCTION
Sorghum (Sorghum bicolor L. Moench.) occupies a prominent position in global agriculture after wheat, rice and maize (FAO 2004). It constitutes the main grain food for over 750 million people who live in the semi-arid tropics of Africa, Asia and Latin America (FAO 2004). Major producers of sorghum in the world are USA, Nigeria, India, China, Mexico, Sudan and Argentina (USDA 2017). It has gained importance for its grain, fodder and stalk in developing countries, while in developed countries the crop is used primarily as animal feed (Obilana 2004). Sorghum as food could improve nourishment, as the air-dried whole grain sorghum contains approximately 8-19% moisture, 68-74% carbohydrates, 8-15% protein, 2-5% fats, 1-3% fibre and 1.5-2.0% ash Dasai et al. (1992). Industrially, grain sorghum is used in the production of flour, alcoholic, malted beverages, vegetable oil, adhesives, waxes, dyes, sizing for paper and cloth, are just some of the products that could be obtained (Obilana 2004, Paterson 2009). In developing countries particularly in West Africa, demand for sorghum is increasing (FAO 2010). This is due to not only to the growing population, but also to the countries' policy to enhance their processing and industrial utilization (Akintayo & Sedgo 2003). The ultimate goal is to enhance sorghum production efficiency and make good use of new economic opportunity in the brewing, non-alcoholic beverages and weaning foods industries, which are offered today to sorghum growers (Obilana 2004). In Nigeria, sorghum is the most widely cultivated staple cereal crop across the agro-ecological zones, the Sahel, Sudan, and Guinea savannas contributed 99% and the remaining 1% is grown in the derived savanna zone of southwestern (FMARD 2011). Climate change is affecting the above-mentioned zones, desert encroachment and insurgency issues (Boko Haram) threaten crop production with high sorghum production percentage (FMARD 2011, Mohammed & Ahmed 2015, Alade et al. 2017). There is a need to investigate the potential of hybrid sorghum production in the rainforest in order to provide information on adaptation of the selected hybrids to southwest agro-ecological zone which will eventually increase sorghum production in Nigeria. Correlation coefficients show associations among independent characteristics and the degree of linear relation between these characteristics while path analysis takes into account the cause and effect relationship between the variables by partitioning the association into direct and indirect effects through other independent variables (Mohammed & Talib 2008). Therefore, this work was initiated to evaluate growth and yield performance among some sorghum hybrids and determine relationship between yield and related characters.

MATERIALS AND METHODS
The experiment was conducted at the Teaching and Research Farm, Federal University of Technology, Akure (FUTA); a tropical rainforest zone of southwestern Nigeria. It lies at an altitude of 332 m above sea level, between longitude 5º 06′ E to 5º 38′ E and between latitude 7º 07′ N to 7º 37′ N in rainforest south-western Nigeria (Ayeni 2011). The study location is characterized by bimodal pattern of rainfall with an annual mean of about 1542 mm with a mean temperature of 27ºC (Ayeni 2011).
The experiment was laid out in a randomised complete block design with three replications. The plot size was 2-row plots measuring 5m each. Spacing was 25 cm (intra-row) × 75 cm (inter-row). The plantings were done on 4 th August, 2016 and 28 th July, 2017 for the first and second year respectively. Five seeds were planted per hole. Thinning was done where necessary at 2-3 weeks after planting to obtain plant population. Hand weeding was also done when necessary to keep the field weed-free. NPK fertilizer (15:15:15) was applied at the rate of (60 kg ha -1 N, 30 kg ha -1 P 2 O 5 and 30 kg ha -1 K 2 O) at 3 weeks after planting. Urea (60 kg ha -1 ) was applied as top dressing at nine weeks after planting. Method of IPGRI (1993) was adopted for sorghum data collection. In each plot, the five middle rows were used to measure the following agronomic characters: a. Seedling emergence count: The number of emerged seedlings per plot was counted and recorded after 7 days of planting. b. Number of days to 50% flowering: The number of days from the sowing date to the day on which 50% of the plants in a plot flowered. c. Number of days to 95% maturity: The number of days from sowing date to the number of days on which 95% of the panicles in a plot reached physiological maturity, as monitored by the appearance of black glumes kernels.

d. Plant height at harvest:
The average of the lengths of five randomly selected plants (each measured from the ground to the tip of the panicle in centimetres).

e. Panicle length:
The average length of a panicle from the base of the panicle to the tip of a panicle from five randomly selected plants in a plot and measured in centimetres.

f. Panicle diameter:
The average width of a panicle from the main stem measured at the widest part of the panicle from five randomly selected plants in a plot and measured in centimetres.

g. Panicle weight:
The average weight of main panicle from five randomly selected plants in a plot and measured in gramme.
h. 1000-grain weight: The weight of 1000 grains was obtained by weighing samples of 1000 filled grains using electronic balance and measured in gramme. i. Number of seeds per panicle: The number of seeds counted from main panicles of five randomly selected plants in a plot. j. Grain yield: The weight of harvested grain per plot, expressed in kilograms per hectare (kg ha -1 ).
The data collected were subjected to analysis of variance using the MINITAB packaged (Version 17 software) and significant mean were separated using Tukey's test. PB tools (Version 1.4 software) were used to analyse genotypic and phenotypic correlation.
Phenotypic and genotypic coefficients of variation were computed using the procedure of (Singh & Chaudhury 1985) as follows. Broad sense heritability was estimated as the ratio of genetic variance to the phenotypic variance and expressed in percentage as recommended by (Singh & Chaudhury 1985): Where, Heritability percentage was categorized as low, moderate and high as by (Elrod & Stanfield 2002) as follows: 0 -20%: Low 20 -50%: Moderate 50% and above: High Genetic advance (GA) was computed according to the formula given by Johnson et al. (1955) as used by Fayeun et al. (2012).
√ Where, K = 2.06 (selection differential at 5%); ; ; ̅ Correlation coefficients were calculated to determine the degree of association among the characters. This was done according to the formula suggested by (Singh & Chaudhury 1985). Test of significance of correlation was done by comparing the computed values against tabular 'r' values given by (Fisher & Yates 1963). Path analysis for estimating direct and indirect effects of traits in yield was performed using formula given by (Dewey & Lu 1959). Rank Summation Index (RSI) to determine the rankings of the hybrids with regard to their overall performance according to (Mulamba & Mock 1978) was summed as follows: Where, Ri= The rank of the means of each of the selected traits; RSI= Aggregate performance of the hybrid using the rankings of the selected traits. Table 1. Means squares from analysis of variance for observed characters. Note: *, ** Significant at p = 0.05 and p = 0.01 respectively.

Source of variation
The mean squares from analysis of variance for 10 observed traits of 25 sorghum hybrid are presented in table 1. It was observed that highly significant differences (p<0.01) and (p<0.05) among hybrids in all the characters except seedling emergence count. Significant variation was observed for hybrid by year interaction in panicle length and 1000-grain weight. However, there were no significant differences between years in all the characters studied. Mean performance of the 25 sorghum hybrids evaluated for ten agronomic characters is presented in table 2. The highest significant mean for seedling emergence counts were obtained from hybrid ICSA223 × MACIA-2 (34.00) while the least mean for seedling emergence count was recorded in ICSA89003 × CHOKWE-1 (6.00). There were no significant differences for number of days to 50% flowering in 2016. Number of days to 95% maturity showed ICSA223 × CHOKWE-1, ICSA223 × PIRIRA-2-1, ICSA38 × CHOKWE-3, ICSA38 × MACIA-3, ICSA38 × NIJ-2, 1CSA38 × PIRIRA-2-1, ICSA89002 × PIRIRA-2-1 and ICSA89003 × CHOKWE-1 were not significantly different in 2016 while ICSA223 × SRN15401 recorded the least (100.33). ICSA38 × SRN15401 had the highest plant height in 2016 (273.73 cm) while ICSA223 × MACIA-3 recorded the least height (133.40 cm) among other hybrids. The longest panicle length was observed in hybrid ICSA38 × CHOKWE-1 (37.80 cm) while the shortest was 27.10 cm for hybrid ICSA89003 × NIJ-2 in year 2016. ICSA38 × ICSV400 recorded significantly highest mean for panicle weight (138.90 g) while ICSA89003 × NIJ-2 had the lowest panicle weight (60.00 g) for panicle weight in 2016. A significant difference was observed among the hybrid for 1000-grain weight in 2016, ICSA89003 × SRN15401 recorded the highest mean for 1000-grain weight (30.06 g) while ICSA223 × PIRIRA-2-1 had the lowest (16.79 g) mean for 1000-grain weight. There were no significant differences between the panicle diameter among the hybrids in 2016. ICSA38 × PIRIRA-2-1 was observed to have the highest mean for number of seeds per panicle (5862.33) while ICSA89003 × NIJ-2 had the lowest (1994.33). In 2016, ICSA38 × ICSC400 was highly significant and recorded the highest grain yield (4167 kg ha -1 ) while the lowest was recorded by ICSA89003 × NIJ-2 (1800 kg ha -1 ).
Estimates of genotypic coefficient of variation, phenotypic coefficient of variation, heritability, genetic advance and genetic gain for ten agronomic characters of 25 sorghum hybrids are presented in table 3. The genotypic coefficient of variation (GCV) was observed to be lower than phenotypic coefficient of variation (PCV) for all the characters under study. GCV for seedling emergence count, number of days to 95% maturity, panicle weight, 1000-grain weight, and grain yield was 19.90%, 1.56%, 14.47%, 7.60% and 14.48% respectively to PCV seedling emergence count (39.82%), number of days to 95% maturity (3.12%), panicle weight (28.94%), 1000-grain weight (15.20%) and grain yield (28.96%). Heritability estimates varied from 20.43% for panicle diameter to 25.46% for plant height. Genetic advance was relatively low for seedling emergence count (3.94) showing uniformity of seed germination, number of days to 50% flowering (2.73), number of days to 95% maturity (1.72), plant height (8.58), panicle length (1.24), 1000-grain weight (1.82), panicle diameter (0.40) and panicle weight (14.43) while other traits had comparatively high means. In 2016, the highest expected genetic gain was (20.47%) for seedling emergence count, number of seeds per panicle (16.00%), grain yield (14.91%) and panicle weight (14.90%) while other traits had low genetic gain. The correlation coefficients among characters are presented in table 4. The correlation result revealed that number of days to 50% flowering had positive and significant correlation with number of days to 95% maturity (r = 0.79) and number of seeds per panicle (r = 0.33) but had negative and significant correlation with plant height (r = -0.53) and 1000-grain weight (r = -0.56). The number of days to 95% maturity had negative and significantly correlated with plant height and 1000-grain weight (r = -0.52 and -0.38) but positively and significantly correlated with number of seed per panicle (0.36). Plant height was negatively and significantly correlated to panicle weight (r = -0.28), panicle diameter (r = -0.46), number of seeds per panicle (r = -0.49) and grain yield (r = -0.28) but had positive significant correlation with 1000-grain weight (r = 0.53). Panicle length had positive and significant correlation with panicle weight, panicle diameter, number of seeds per panicle and grain yield (r = 0.36, 0.57, 0.27 and 0.36, respectively). Panicle weight had negative and significant correlation with 1000-grain weight (r = -0.32) but positive correlations was recorded in panicle diameter, number of seeds per panicle and grain yield (r = 0.38, 0.89 and 0.98). 1000-grain weight had negative but significant correlation with number of seeds per panicle and grain yield (r = -0.76 and -0.32). Panicle diameter had positive significant correlation with number of seed per panicle (r = 0.28) and grain yield (r = 0.38). Nevertheless, number of seeds per panicle had positive significant correlation with grain yield (r = 0.84).
Path analysis depicted the strength of contributions of all independent variables understudy on the grain yield (Table 5). Panicle weight had the highest positive direct effect (0.961) on grain yield followed by days to 50% maturity (0.046) and the number of seeds per panicle (0.014). On the other hand plant height showed high negative direct effect on grain yield with (-0.014). Panicle length had low positive direct effect on grain yield (0.010). Its positive indirect effect was through seedling emergence count (0.001), number of days to 95% maturity (0.031), panicle weight (0.436), panicle diameter (0.003) and number of seeds per panicle (0.004), whereas its indirect effect was negative through, number of days to 50% flowering (-0.018), plant height (-0.002) and 1000 grain weight (-0.000). Panicle weight had high positive direct effect on grain yield (0.961). Its positive indirect effect was through seedling emergence count (0.009), number of days to 95% maturity (0.019), plant height (0.008), panicle diameter (0.002) and number of seeds per panicle (0.013), whereas its indirect effect was negative in the number of days to 50% flowering (-0.018). The number of seeds per panicle had positive direct effect on grain yield (0.014). Its positive indirect effect was through number of days to 95% maturity (0.030), plant height (0.009), panicle length (0.006), panicle weight (0.857) and panicle diameter (0.001), whereas its indirect effect was negative through seedling emergence count (-0.004), number of days to 50% flowering (-0.018) and 1000 grain weight (-0.002).  Table 6 shows the rank summation index. Hybrid ICSA38 × ICSV400 had the best performance with a mean rank of 4.8. It was followed by ICSA38 × PIRIRA-2-1 with a mean rank of 6.6. Hybrid ICSA89003 × NIJ-2 and ICSA223 × PIRIRA-2-1 had the poorest performance with the means of (18.1, 16.8) respectively.

DISCUSSION
The variation observed among the hybrids for the agronomic traits may be attributed to the genetic makeup of the hybrid parents. Various researchers have reported significant variation in sorghum hybrid (Fayeun et al. 2012, Arunkumar 2013, Menezes et al. 2015, Eniola 2019. Among the hybrids, ICSA38 × ICSA400, ICSA38 × PIRIRA-2-1 had the highest mean for panicle weight and number of seeds per panicle, respectively. While these hybrids can be recommended for utilization, the parents can be recommended for further improvement; and probably tested in various agro-ecological zones for yield potential, pest and disease reaction and adaptation for adoption. The phenotypic coefficient of variation was higher than genotypic coefficients of variation for all corresponding traits indicating some contribution of the environment in the expression of the characters. Higher phenotypic coefficient of variation has being reported in different crops like soybean and fluted pumpkin for seedling traits (Mohammadi & Pourdad 2009, Fayeun et al. 2016. Broad sense heritability was moderate for most characters considered and low genetic advance was recorded for most of the traits except number of seeds per panicle and grain yield. This suggests the moderate influence of the environment on most of the traits under study; and may be relatively suitable in many ecological zone for propagation by farmer and sorghum stakeholders to boost production. Selection will also be possible in the desired direction. Fayeun et al. (2017) equally reported in extra-early maize hybrids moderate effect of environment. The phenomenon, therefore, implies continuous evaluation of hybrid sorghum just like in maize for genotypic and environmental expression for identifying adaptable genotypes.
Knowledge of correlation between traits of economic importance are not only of interest from theoretical consideration of quantitative inheritance of characters, but of practical value since selection is usually concerned with changing two or more traits simultaneously (Prasuna 2012). Johnson et al. (1955) explained that where the genetic correlation coefficients are high, there is a strong heritability between characters. This means that selection for these characters can be carried out irrespective of the locations. The low values of the correlation coefficient obtained may slow down the progress from selection. High negative values of correlation coefficients were obtained for some characters. This showed that selection for some of these characters would affect each other in the opposite direction as earlier suggested by Bello et al. (2001).
The correlation coefficient helps in determining the direction of selection and number of characters to be considered in improving the grain yield. So it is a matter of great importance to the plant breeders to find out of the characters that are correlated with yield and also how they are associated with themselves. From this study, grain yield shows positive and significant correlation with panicle length, panicle weight, panicle diameter and number of seeds per panicle. Previous workers have also reported sorghum grain yield as a function of number of seed per panicle (Aba & Obilana 1994, Eniola 2019, and panicle weight (Aba & Zaria 2000, Eniola 2019). Thus, it was revealed from the present study that the traits like panicle length, panicle weight and number of seeds per panicle are of great importance in yield components. Hence, due consideration should be given to these characters, while planning a breeding strategy for increased grain yield.
Path coefficient analysis measures the direct influence of one variable upon the other and permits separation of correlation coefficient into components of direct and indirect effects. Partitioning of total correlation into direct and indirect effects provides actual information on the contribution of characters and thus forms the basis for selection to improve yield. Hence genotypic correlations were partitioned into direct and indirect effects to know the relative importance of the components.
In this study, it was observed that number days to 95% maturity, panicle length, panicle weight, 1000-grain weight, panicle diameter and number of seeds per panicle had positive and direct effect on grain yield while panicle weight had the highest positive direct effect on grain yield indicating the importance of these characters to grain yield. These traits should be considered simultaneously when developing selection criteria for grain yield improvement in sorghum. Several researchers, (Jindla & Gill 1984, Singh & Govila 1989, Bidinger et al. 1993, Eniola 2019) also found similar results in sorghum. It is inferred from correlation and path analysis that panicle weight which recorded significant positive correlation co-efficient and also had high positive direct effect that might be regarded as the prime character. This indicates that panicle weight is the most important trait influencing the grain yield. Thus, selection for heavy panicle is a pre-requisite to attaining higher grain yield in sorghum. Next to it is number of seeds per panicle which showed high positive direct effect as well as high correlation with grain yield per plant. Its indirect effect through panicle weight has also been high among all traits that contributed significantly to grain yield.
The ranking summation index (RSI) is a tool that allows the plant breeders to select the genotypes with the best performance in terms of yield and its components in the two or more seasons of testing (Harriman et al. 2012). The hybrids that showed better performance in terms of yield and traits that contribute to it include ICSA38 × ICSV400, ICSA38 × PIRIRA-2-1 and ICSA38 × MACIA-2.

CONCLUSION
There is a potential of increased sorghum yields through the use of hybrids. Variation existed among the hybrids in a number of traits. These were number of seeds per panicle, panicle length and panicle weight of sorghum. Also, there existed significant correlation between panicle length, panicle weight and number of seeds per panicle. Consequently, selection for any of these traits could lead to indirect selection for improved grain yield. Simultaneous selection for these characters can be made for the improvement of grain yield. The exploitation of these traits provides an excellent opportunity to increase the performance of sorghum in terms of high yield and yield potential.