Sorghum (Sorghum bicolor (L.) Moench) is classified under the grass family of Poaceae, genus Sorghum Moench (Poehlman and Sleper, 1995). It originated in Africa, more precisely in Ethiopia, between 5000 and 7000 years ago Vavilov, (1951) and/or centre diversity Harlan, (1992). The crop has spread to other parts of Africa, India, and Southeast Asia, Australia and the United States (Mesfin and Tileye, 2013).
Sorghum is a drought tolerant C4 tropical crop with wide diversity. It is the fifth most important cereal crop in the world with grain production grown in arid and semi-arid parts of the world (FAO, 2016). It contributes to the protein and energy requirements for millions of people mainly living in Sub-Saharan Africa and Asia (Orr et al., 2016). Sorghum is one of the major staple food crops on which the lives of millions of Ethiopians depend. The majority of grain production goes towards the preparation of diverse food recipes, like porridge,”injera”, “Kitta”, “Nifro”, infant food and syrup (Asfaw, 2007). A small fraction of the grain it is malted for local beverages, such as “Arake”, “Tella”, and “Borde” (Abegaz et al., 2002).
Barley is the grain of choice for malting in modern brewing (Taylor and Dewar, 2000). Next to barley, of which sorghum malt found the most appropriate alternative for brewing (Agu et al., 2013) and further the brewing qualities are advanced due to gluten-free nature of sorghum protein to substitute the gluten rich cereals in the diet of people suffering from celiac disease (Anheuser, 2010).
Malting is the controlled germination of cereals in moist air, under controlled conditions for mobilizing the endogenous hydrolytic enzymes, especially α-amylase and β-amylase enzymes of the grain. The malting process modifies the grain structure, so that it will be readily solublized during the brewing process to produce fermentable wort (Taylor and Belton, 2002).
In any crop improvement program, the primary (or most essential) characteristic that the breeder looks into is the existence of genetic variability for the characters of interest (Jahufer and Gawler, 2000). Breeders are also interested in the relationship and interdependence that may exist between or among characters for direct and indirect selection (Muhammad et al., 2003).
Grain yield and its quality are the principal characters of a cereal crop (Bello and Olaoye, 2009). They are complex quantitative characters, which are influenced by a number of yield and malt quality contributing factors. Hence, the selection for desirable genotypes should not only be based on yield alone, but also other yield and malt quality components. Direct selection for yield is often misleading in sorghum because yield is polygenically controlled.
For effective utilization of the genetic stock in crop improvement, information of mutual association between yield, malt quality and yield components is necessary. It is therefore, necessary to correlate various characteristics with yield, malt quality and among themselves. The correlation between yield, malt quality and yield components usually show a complex chain of interacting relationship. Path coefficient analysis partitions the components of correlation into direct and indirect effects and highlights the relationship in a more meaningful way (Muhammad et al., 2003). However, no character association studies have been conducted at national level as wel as especially for yield and malt quality.
Although both correlation and path analysis have been extensively studied for agronomic traits in sorghum, such information is unavailable for malting quality traits in Ethiopia. Therefore, such association is essential among traits for further sorghum yield and malt quality improvement, particularly in the region and generally in the country for sorghum malt varieties development. Therefore, the current study was carried out to estimate; the magnitude of genotypic and phenotypic correlation between grain yield, malt quality and yield contributing characters and direct and indirect effects of yield related and malt quality traits for malting (diastatic power) and yield.
Correlation of grain yield with agronomic and malt quality traits
Estimates of phenotypic (rp) and genotypic (rg) correlation coefficients between each pair of the traits are presented in Table 2. Grain yield (kg ha-1) showed positive and highly significant (P <0.01) genotypic correlation with plant height (rg=0.453), thousand kernel weight (rg=0.766), hectoliter weight (rg=0.532), kernel length (rg=0.671), kernel width (rg=0.524) and kernel thickness (rg=0.445) at (P <0.05), for fine grind hot water extract (rg=0.257) diastatic power (rg=0.275) (Table 2), which indicates that improving these chaaracters may result in the improvement of yield due to high positive correlation. Selecting sorghum genotypes with late maturing and higher plant height might lead to larger grain size, seed weight, increased grain yield and fermentable extract. The findings of the present study are in agreement with the results obtained for plant height and days to flowering by Kalpande et al. (2014) and plant height and thousand kernel weights by (Ezeaku and Mohammed, 2006). Therefore, any improvement of these traits would result in a substantial increment on grain yield.
Grain yield (kg ha-1) showed positive and highly significant (P <0.01) phenotypic correlation with plant height (rp=0.428) thousand kernel weight (rp=0.715), hectoliter weight (rp=0.504), kernel length (rp=0.644), kernel width (rp=0.491) kernel thickness (rp=0.425) and diastatic power (rp=0.271) and positive significant (P <0.05) correlation with germination energy (rp=0.207). This assures that as vigorousity increases high dry matter acumulation and possibility of grain yield improvement by phenotypic selection of these traits. Khandelwal et al. (2015) reported similar result for thousand kernel weights but negative significant correlation for plant height.
Grain yield had significant negative correlation with malt moisture content (rg=-0.344) and (rp=-0.329) at genotypic and phenotypic level, respectively. This is in accordance with Laidig et al. (2017) for thusand seed weight, grain size, malt extract and protein content and in contrary for hectoliter weight and malting weight loss. Similar results were also found by Alhassan et al. (2008) for germination energy and malting weight loss. The traits such as plant height, thousand kernel weight, hectoliter weight, kernel length, kernel width and kernel thickness showed positive and highly significant correlation (P≤0.01) at both genotypic and phenotypic levels, while DP showed significant correlation (P≤0.05) at phenotypic level with grain yield. This indicated that selection for PH, TKW, HLW, KL, KW, KT, FHWE and DP would improve grain yield.
Grain yield had shown highly significant negative genotypic and phenotypic correlation with malt moisture content and non significant negative correlation at both genotypic and phenotypic level for protein content. This could be due to nutrient and others competition between the traits that arise from their inherent nature of the linkage or pleiotropy. The negative correlation impedes the improvement of grain yield.
Phenotypic correlation among agronomic and malt quality traits
This study indicated that days to flowering showed positive and significant correlation at (P≤0.01) with plant height (rp=0.624) and kernel thickness (rp=0.47), whereas at (P≤0.05) with kernel width (rp=0.208) (Table 2) which sugests that selection for those traits improves grain yield simultaneously. Alam et al. (2014) reported positive and non significant phenotypic association to plant height and days to flowering. Days to flowering revealed highly significant negative correlation with hectoliter weight (rp= -0.379) and germination energy (rp = -0.349). Alhassan et al. (2008) found negative correlation of days to flowering with α- and β- amylase enzymes, whereas, positive correlation to germination energy and malting weight loss.
Plant height showed significant (P≤0.01) positive correlation with kernel length (rp = 0.347), kernel thickness (rp=0.328), hot water extract (rp=0.303) and diastatic power whereas, negatively and significantly correlated with germination energy (rp=- 0.195). Plant height showed significant positive association to germination energy and negative to association to α- and β- amylase enzymes were reported by Alhassan et al. (2008). The negative correlation between those traits makes it impossible to achieve the simultaneous improvement of those traits along with each other. Kernel length showed positive significant (P≤0.01) association with kernel thickness (rp=0.451) and germination energy (rp=0.3).
Thousand kernel weight revealed significant positive association (P≤0.01) for days to flowering (rp=0.27), plant height (rp=0.367), grain yield (rp=0.715), hectoliter weight (0.467), kernel length (rp=0.581), kernel width (rp=0.491) and kernel thickness (rp=0.493) and at (P≤0.05) for germination energy (rp=0.221). This indicates that simultaneously improvement of these traits. Amsalu and Endashaw (2012), found similar result with plant height and thousand kernel weight with days to flowering. The positive correlation of thousand kernel weight with germination energy, malting weight loss and diastatic power is similar with the finding of Beta et al. (1995). Positive correlation of thousand kernel weight with grain size and test weight were reported by Adetunji (2011). Hectoliter weight showed highly significant positive association (P≤0.01) with kernel length (rp=0.339), kernel width (rp=0.300) and malting weight loss (rp=0.287) while negative association with plant height.
Protein content revealed negative significant correlation (P≤0.05) to days to flowering and also non significant negative correlation to plant height, grain yield, thousand kernel weight, hectoliter weight, kernel thickness, fine grind hot water extract and malt moisture content. This negative correlation between two desirable traits may impede to achieve the simultaneous improvement of those traits along with each other. Similar results were reported by Kassahun et al. (2011) for days to flowering, maturity, plant height, thousand kernel weight and grain yield. Alhassan et al. (2008) also reported similar finding for germination energy, malting weight loss and malt moisture content.
Fine grind hot water extract showed positive association (P≤0.01) for days to flowering, (0.363), plant height, (0.303), kernel width (0.286) and kernel thickness (0.377) also positive association for hectoliter weight, kernel length and malting weight loss. However, negative association to germination energy. Non significant positive association of fine grind hot water extract with medium size seed, hectoliter weight and thousand kernel weights was found by Adetunji (2011). Malt moisture content showed significant negative association at (P≤0.01) with grain yield (rp=-0.329) and plant height (rp=-0.322) and kernel width (rp=-0.294), at (P≤0.05) to plant height (rp=-0.241), kernel thickness (rp=-0.217) and kernel length (rp=-0.225). This is in harmony with Beta et al. (1995) and Alhassan and Adedayo (2011).
A positive significant correlation was shown for diastatic power at (P <0.01) with thousand kernel weight (rp = 0.246) and at (P <0.05) for grain yield (rp = 0.21) however, non significant negative correlation with days to flowering, protein content. According to Alhassan et al. (2008) Alfa- and β-amylase were positively correlated with thousand kernel weight, and negatively to days to flowering. Generally, positive phenotypic correlation of any pairs of traits of the present sorghum population indicated the possibility of correlated response to selection. In contrary to this, the negative correlation prevents the simultaneous improvement of those traits along with each other.
Genotypic correlation among the component traits
Days to flowering showed positive and highly significant correlation with kernel thickness (rg=0.479) and plant height (rg=0.679), while non significant positive correlation with kernel length (Table 2). In contrary, it shown highly significant negative association with hectoliter weight (rg=-0.395) and germination energy (rg=-0.362). Alhassan and Adedayo (2011), reported significant positive association of germination energy with days to flowering which is contrary to the current finding.
Plant height showed significant positive association (P≤0.01) with kernel length, (rg=0.379), (P≤0.05) kernel thickness (rg=0.338) whereas, negative association with germination energy. The positive correlation of GY, DF and PH suggests selecting sorghum genotypes with higher plant height might lead to reduced earliness and increased grain yield. This in agreement with Amsalu and Endashaw (2012) and in contrary to Alam et al. (2014) reported positive and non significant genotypic association to plant height and days to anthesis.
Thousand kernel weight showed positive significant correlation at (P≤0.01) with hectoliter weight (rg=0.502). Kernel length (rg=0.596), Kernel width (rg=0.603), kernel thickness (rg=0.513) and at (P≤0.05) with MWL (rg=0.3290). This probably indicated that longer phenological period of tall genotypes could result in large assimilate accumulation with the maximum contribution to thousand kernel weight and grain yield. This is partially agreed with the result of Amsalu and Endashaw (2012) for plant height and days to flowering. Non significant positive correlation of thousand kernel weight with test weight (Kg/hl) and positive significant for large side size and significant negative with small seed size association with grain size was found by Chiremba et al. (2011).
Protein content showed significant negative correlation with fine grind hot water extract (rg=-0.275) and non significant negative correlation with days to flowering, plant height, grain yield, thousand kernel weight, hectoliter weight, kernel thickness, malt weight loss and diastatic power. For both genotypic and phenotypic associations this is in agreement with Adetunji (2011) for hectoliter weight, thousand kernel weight, seed size and fine grind hot water extract, and Alhassan et al. (2011) for plant height, days to flowering, malting weight loss and germination energy. The negative correlation of the desirable trait protein content to those traits may impede or makes it impossible to achieve the simultaneous improvement of those traits along with each other.
Fine grind hot water extract revealed positive correlation at (P≤0.01) with days to flowering (rg=0.378), thousand kernel weight (rg=0.369), and kernel thickness (rg=0.378) at (P≤0.05) with plant height (rg=0.303), kernel width (rg=0.288) and grain yield (rg=0.257) suggesting that longer phenological period of genotypes could result in large seed size with the maximum contribution to thousand kernel weight, grain yield and fermentable extract. Similarly, Adetunji (2011) reported positive correlation of total fermentable sugars to TKW and HLW.
Diastatic power revealed positive significant (P≤0.01) correlation with malt weight loss (rg= 0.454) and thousand kernel weight (rg=0.363); and at (P≤0.05) fine grind hot water extract (rg=0.276) and grain yield (rg=0.275). The significant positive correlation is in conformity with Edney et al. (2007). This indicates metabolic reaction created due to high disatatic power and germination energy resulted in respiration loss, rapid germination in short period of time and malting loss. The negative genetic correlation for some of the malting and agronomic traits indicated that improvement of malting quality traits will require more than just selection. According to Alhassan et al. (2008) α- and β-amylase were positively correlated with thousand kernel weight, and negatively to days to flowering were reported. Malt moisture content correlated negatively for all of the traits at both genotypic and phenotypic level. This is in accordance with Alhassan et al. (2008).
Generally, genotypic correlation coefficients were relatively higher in magnitude than that of phenotypic correlation coefficients, which indicated the presence of inherent association among various traits that could be mainly due to the presence of linkage and of the pleiotropic effects of different genes. However, in some cases the phenotypic correlation values were higher than the genotypic correlation values suggesting the importance of environmental effects. This finding is in agreement with previous findings of Khandelwal et al, (2015) in sorghum. The positive association between all possible pair of traits suggested that the possibility of correlated response to selection so that with the improvement of one trait, there will be an improvement in the other positively correlated trait. This is because a positive genetic correlation between two desirable traits makes the job of plant breeder easy for improving both traits simultaneously. Unlike positive correlation, negative correlation between two desirable traits may impede to achieve the simultaneous improvement of those traits along with each other.
Phenotypic direct and indirect effects of various traits on grain yield
Partitioning of phenotypic correlations into direct and indirect effects on grain yield (Table 2) revealed that the trait hectoliter weight showed the highest positive direct effect with value (0.307) on grain yield followed by thousand kernel weight (0.287), kernel length (0.258), plant height (0.227) while, diastatic power showed negligible positive direct effect on grain yield. However, kernel width (-0.072), malt moisture content (-0.068) and fine grind hot water extract (-0.025) had negative phenotypic direct effect on grain yield. So, the improvement of grain yield is as the expense of KW, MMC and FHE directly. Similar result was reported by Chittapur and Biradar (2015) for direct positive correlation of plant height, thusand kernel weight and seed size with grain yield.
Thousand kernel weights, both the direct and indirect positive effects largely via hectoliter weight and kernel length outweighed for the positive correlation with grain yield (rp = 0.715**). So, both direct positive and indirect positive effects were the causes of the significant correlation. Therefore, such considerable indirect effects should be considered for selection. Considerable direct effect and positive significant correlation of thousand kernel weight with grain yield was reported by Khandelwal et al.( 2015).
Plant height had positive direct effect and the phenotypic correlation with grain yield was significant positive. Its indirect effect via thousand kernel weight and other traits were mostly positive therefore, the positive correlation coefficient with grain yield was due to its direct and indirect effect. This is agreed with the finding of Kassahun et al. (2011).
Kernel length was another trait which had positive direct effect which is small as compared to its correlation coefficient. But it also contributed considerable positive indirect effect to grain yield via thousand kernel weight and hectoliter weight. Therefore, high positive correlation of kernel length with grain yield was due to both its positive direct effect and indirect effect via thousand kernel weight and hectoliter weight. The high positive correlation of KW with GY was mainly due to the indirect effects of Kernel length and thousand kernel length, so, KL and TKW should considered for grain yield improvement.
Diastatic power and kernel thickness showed positive direct effect (Table 3). The indirect effect of diastatic power via other characters was positive and negligible except TKW; therefore, its significant positive correlation coefficient with grain yield was mainly due to the indirect effect of thousand kernel weight.
Fine grind hot water extract, kernel width and Malt moisture content exerted directly negative effect on and negative correlation to grain yield. The positive association of FHWE with grain yield is mainly due to indirect effect of TKW. However, the negative association malt moisture with grain yield is due to both negative direct and indirectly effects of most of the traits. Negative direct effect of FHWE to grain yield was reported in barley by Pržulj et al. (2013).
The traits that exerted positive direct effect (thousand kernel weight, hectoliter weight, plant height and kernel length, kernel thickness, and diastatic) and their positive significant correlation coefficient with grain yield were known to affect grain yield in the favorable direction and needs much attention during the process of selection. Moreover the small indirect effects of TKW (0.169), HLW (0.143), PH (0.083) and KL (0.151) through other traits should be simultaneously considered. The phenotypic residual value (0.24) indicated that the traits which were included in the phenotypic path analysis explained 75.66% of the variation in grain yield.
Genotypic direct and indirect effects of various traits on grain yield
Estimates of genotypic direct and indirect effects of the selected traits on grain yield are presented in (Table 4). Genotypic path analysis showed that thousand kernel weight (0.334), exerted the highest positive direct effect to grain yield followed by hectoliter weight (0.309), kernel length (0.256) plant height (0.219). Diastatic power and fine grind hot water extract exerted negligible positive direct effect to grain yield. Similar result was reported by Chittapur and Biradar (2015) for direct positive correlation of plant height and thousand kernel weight.
Thousand kernel weight and Hectoliter weight which had significant high positive correlation (0.766**) and (0.532**), respectively with grain yield exerted positive direct effect (0.334) and (0.309). This indicated that the correlations of these traits with grain yield were found to be partly due to their direct effects. Therefore, simultaneous selection through these traits will be effective for grain yield improvement. Considerable direct effect and positive significant correlation of thousand kernel weight with grain yield was reported by (Khandelwal et al., 2015; Silva et al., 2017).
Plant height had positive direct effect and the genotypic correlation with grain yield was significant and positive. Its indirect effect via thousand kernel weight was positive therefore, the positive correlation coefficient with grain yield was mainly due to its direct and indirect effect. The direct positive effect of plant height to grain yield is in accordance with Kalpande et al. (2014) and Silva et al. (2017)
Kernel length revealed small positive direct effect to grain yield and also showed positive indirect effect through thousand kernel weight and hectoliter weight to grain yield. The causes of the positive association of kernel length with yield were mainly due to its positive direct effect and indirect effects through thousand kernel weight and hectoliter weight. Kernel width exerted direct negative effect on grain yield. The positive correlation with GY was due to the counter balance of the positive indirect effects of TKW, HLW and KL. So, the TKW, HLW and KL should be considered for the increment of grain yield.
Fine grind hot water extract has negligible positive direct effect and positive genotypic correlation with grain yield. This indicated that the positive correlation was mainly through in direct effect of thousand kernel weight. Diastatic power showed negligible positive direct effect to grain yield. The positive significant correlation of diastatic power with grain yield is due to the positive direct effect and positive indirect effects of thousand kernel weight.
Malt moisture content exerted directly negative effect on and negative correlation to grain yield. The negative association with grain yield is mainly due to the equivalent indirect effect of thousand kernel weight. The negative direct effect and correlation of MMC to grain yield was favorable, as malt moisture does not need to increase.
Generally, the positive significant correlation and positive direct effect of PH, TKW, HLW, KL, KT and FHWE, synchronization with considerable indirect effects of thousand kernel weight (0.204), hectoliter weight (0.155) plant height (0.084) and kernel length (0.154) will be most effective in improving grain yield of these genotypes. For all the traits taken to path analysis the direct effects are not equivalent to their correlation coefficients, so this allows for simultaneous selection at phenotypic level. The genotypic residual value (0.17) indicated that the traits used in the genotypic path analysis explained 82.06 % of the variation for grain yield.
Genotypic direct and indirect effects of various traits on diastatic power
Estimates of genotypic direct and indirect effects of the selected traits on diastatic power are presented in (Table 5). Genotypic path analysis showed that malt weight loss (rg=0.382) had the greatest unfavorable positive direct effect. So, selection could be effective for genotypes having high diastatic power with low to medium malt weight loss. The positive direct effect of malting weight loss on diastatic power is indicative of the respiratory loss during seedling growth. The current study is in conformity with Wenzel and Pretorius (1995) in sorghum. Alhassan et al. (2008) reported direct effect of (0.16) MWL to alpha amylase.
Thousand kernel weight (rg=0.122), FHWE (rg=0.171) exerted considerable direct effect and positive correlation to DP and showing the direct effects were higher than indirect effects. The considerable direct effect and positive correlation of FHWE to DP and the DP value of the genotypes above specification (28 SDU/g) indicates the availability of enough diastase enzymes to digest the starch to get fermentable sugars. This is in agreement with Kumar et al. (2014) for both timely and late sown barley and in contrary to Bichoński and Śmiałowski (2004) in Bbarley of DP and FHWE. Kumar et al. (2014) also reported that TKW (0.222) direct effect to malt extract in late sown barley. Grain yield exerted negligible positive direct effect to DP and its significant correlation with DP was due its both direct effect and indirect positive effects of TKW, MWL and FHWE. Therefore, Selection through direct positive effect of TKW, FHWE and low to medium malt weight loss content (higher dry malt mass) genotypes will be effective in improving sorghum diastatic power.
Path coefficient analysis in this study did not account for all variation in diastatic activity as indicated by the magnitude of the residual effects (0.66) of the nine agronomic and malting quality traits which pointed out that there are other traits in addition to the four traits to be included in the path analysis that contribute to diastatic activity. This is agreed with the high residual effect (0.97) for sorghum diastatic power as reported by Wenzel and Pretorius (1995), (0.4) for sorghum α-amylase activity (Alhassan et al., 2008) and for finger millet agronomic traits to grain yield (0.89) (Abuali et al., 2012).
Grain yield (kg ha-1) was found to be positively and significantly correlated with PH, TKW, HLW, KL, KW, KT, FHWE and DP both at phenotypic and genotypic level and significant positive correlation with GE at phenotypic level. So, the significant genotypic correlations of PH, TKW, HLW, KL, KT and higher rg than rp can be concluded that the association was inherent and selection would be effective to improve GY of the genotypes.
Focus on the direct and indirect favorable effect and significant positive correlation of TKW, HLW, KL, KT, and PH at both Phenotypic and genotypic level needs much attention and implies that selection on these traits would have a tremendous value for yield improvement of these sorghum genotypes. The considerable direct effect of TKW (0.122), FHWE (0.171) and their positive correlation with DP at genotypic level and increment in these traits would results in advancement of DP. However, unfavorable positive direct effect and significant correlation of MWL with DP genotypic level impedes DP improvement.
So, in order to bring an effective improvement of grain yield and malt quality traits, more attention should be given for traits such as PH, TKW, kernel size which showed high positive phenotypic and genotypic correlation coefficients with a considerable direct and indirect effect on grain yield and the positive correlation of the most limiting malt quality traits of DP and FHWE with grain yield of sorghum genotypes in the present study.
