African Journal of
Plant Science

  • Abbreviation: Afr. J. Plant Sci.
  • Language: English
  • ISSN: 1996-0824
  • DOI: 10.5897/AJPS
  • Start Year: 2007
  • Published Articles: 683

Full Length Research Paper

Correlation and path analysis of yield, yield contributing and malt quality traits of Ethiopian sorghum (Sorghum bicolor (L.) Moench) genotypes

Gobezayohu Haftu Mengesha
  • Gobezayohu Haftu Mengesha
  • Cereal Breeding, Ethiopian Institute of Agricultural Research Mekhoni Agricultural research Centre, Maichew, Tigray Ethiopia, P. O. Box 47, Mekhoni, Ethiopia.
  • Google Scholar
Firew Mekbib Hailemariam
  • Firew Mekbib Hailemariam
  • Plant Sciences, Haramaya University, Harar Ethiopia, P. O. Box 138, Dre Dawa Ethiopia.
  • Google Scholar
Taye Tadesse Mindaye
  • Taye Tadesse Mindaye
  • Plant breeding, Melkassa Agricultural Research Centre, Melkassa Ethiopia, P. O. Box 436, Melkassa Ethiopia.
  • Google Scholar
Berhane Lakew
  • Berhane Lakew
  • Plant breeder, Holeta agricultural research centre, Holeta Ethiopia, P. O. Box 31, Holeta Ethiopia.
  • Google Scholar
Ramesh Pal Singh Verma
  • Ramesh Pal Singh Verma
  • Barley Breeder, International Center for Agricultural Research in the Dry Areas (ICARDA), Biodiversity and Crop Improvement ProgramRue Hafiane Cherkaoui, Rabat, Morocco.
  • Google Scholar


  •  Received: 18 February 2019
  •  Accepted: 08 April 2019
  •  Published: 31 August 2019

 ABSTRACT

Sorghum is a drought tolerant C4 tropical crop with wide diversity grown for food, feed and beverages. There is a growing demand for food and malt type sorghum varieties due to the low supply of mat barley, and climate resilient and gluten free nature of the crop. This study was initiated to estimate the associations among traits and the relative importance of traits in influencing grain yield and malting quality of sorghum genotypes. The experiment was conducted at Fachagama in Mhoni ARC, Northern Ethiopia in 2016/2017 using α- lattice design in two replications using supplementary irrigation. Data were collected on agronomic traits, and a selection of 300 g pure seeds were malted (18 hr steeping, 72 hr in 28°C germinated and 24 hr in 50°C dried) for malt quality analysis. Positive and significant correlations with grain yield of TKW (0.766, 0.715), KL (0.671, 0.644), KW (0.524, 0.491) HLW (0.532, 0.504, FHWE (0.257, 0.241) and DP (0.275, 0.271) at both phenotypic and genotypic level was found respectively. TKW exerted high positive genotypic (0.334) and phenotypic (0.287) direct effect and even higher indirect effect on grain yield, which indicated that attention should be given to TKW primarily for direct and indirect selection for yield improvement. Thousand kernel weight and fine grind hot water extract showed a significant positive correlation with diastatic power at genotypic level and increment in these traits results in advancement of diastatic power.

 

Key words: Diastatic power, direct effect, indirect effect, genotypic and phenotypic association.


 INTRODUCTION

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.


 MATERIALS AND METHODS

Description of the experimental area
 
The experiment was carried out at Mehoni Agricultural Research center (MhARC) Fchagama test s tation site in Raya Azebo Woreda using supplementary irrigation in the 2016/2017 cropping season. Fachagama is located at 668 km from the capital Addis Ababa and about 120 km south of Mekelle, capital city of Tigray regional state. Geographically the experimental site is located at 12.70 °N latitude and 39.70 °E longitude with an altitude of 1578 m.a.s.l. The site receives a mean annual rainfall of 539 mm with an average minimum and maximum temperature of 12.8 and 23.2°C, respectively. The soil textural class of the experimental site was clay with pH of 6.89 (Gebremeskel et al., 2017).
Treatments and experimental design
 
The study genotypes (Table 1) including the two checks (Redswazi and Macia) were kindly availed by the national Sorghum Research Program of Melkasa Agricultural Research Center (MARC). The genotypes are selected based on their dominancy in production and historical usage for local beverage preparation and for some are recently released food varieties to evaluate whether they can be used for both food and malting.
 
The treatments (genotypes) were grown in (7, 8) α- lattice in two replications, 2 m path width between replications and 0.5 m path between plots found within incomplete blocks. The gross size of experimental  plot  was  1.5 m  x  3 m  (4.5 m2) accommodating two rows with spacing of 75 cm between rows and 20 cm between plants. The two outer most rows  at  both  ends  of first and the last blocks were treated as borders leaving two middle rows of each of the genotypes for sampling.
 
 
 
 


 RESULTS AND DISCUSSIONS

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).
 

 


 SUMMARY AND CONCLUSIONS

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.


 CONFLICT OF INTERESTS

The authors have not declared any conflict of interests.



 REFERENCES

American Association of Cereal Chemists (AACC) (2000). Approved Methods of the American Association of Cereal Chemists. 10th Edition, American Association of Cereal Chemists Inc., St. Paul.

 

Abegaz K, Fekadu B, Langsrud T, Judith AN (2002). Indigenous processing methods and raw materials of borde, an Ethiopian traditional fermented beverage. Food Technology Africa 7:59-64.
Crossref

 
 

Abuali AI, Abdelmulla AA, Idris AE (2012). Character Association and Path Analysis in Pearl Millet (Pennisetum glaucum L.). American Journal of Experimental Agriculture 2(3):370-381.
Crossref

 
 

Adetunji A (2011). Development of a database of sorghum cultivars in southern Africa, with emphasis on end-use quality, particularly brewing quality. MSc Thesis. University of Pretoria, Pretoria, South Africa.

 
 

Agu R, Palmer C, Geoff H (2013). Evaluation of the potentials of millet, sorghum and barley with similar nitrogen contents malted at their optimum germination temperatures for use in brewing. Journal of
Crossref

 
 

Insitute of Brewing 119:258-264.

 
 

Alam MM, Hammer GL, Van Oosterom EJ, Cruickshank AW, Colleen H, Jordan DR (2014). A physiological framework to explain genetic and environmental regulation of tillering in sorghum. Australia. New Phytologist 203:155-167.
Crossref

 
 

Alhassan U, Adedayo A (2011). Genetic Diversity in Malting Quality of some Sorghum Genotypes [Sorghum bicolor (L.) Moench]. PAT 6(2):51-60.

 
 

Alhassan U, Yeye MY, Aba DA, Alabi SO (2008). Correlation and path coefficient analyses for agronomic and malting quality traits in some sorghum [Sorghum bicolor (L.) Moench] genotypes. Journal of Food, Agriculture and Environment 6(3-4):285288.

 
 

Amsalu A, Endashaw B (2012). Geographical patterns of morphological variation in sorghum [Sorghum bicolor (L.) Moench] germplasm from Ethiopia and Eritrea: Quantitative characters. Euphytica 115: 91-104.

 
 

Anheuser B (2010). Red bridge Beer Made with you in Mind. Availbale at: 

View

 
 

American Society of Brewing Chemists (ASBC) (2008). Method: malt analysis, in Methods of Analysis of the American Society of Brewing Chemists. American Society of Brewing Chemists: St Paul, MN.

 
 

Asfaw A (2007). The role of introduced sorghum and millets in Ethiopian agriculture. Journal I CRISAT 3(1):1-4.

 
 

Bello OB, Olaoye G (2009). Combining ability for maize grain yield and other agronomic characters in a typical southern guinea savanna ecology of Nigeria. African Journal of Biotechnology 8(11):2518-2522.
Crossref

 
 

Beta T, Rooney LW, Waniska RD (1995). Malting characteristics of sorghum varieties. Cereal Chemistry 72(6):533-538.

 
 

Bichoński A, Śmiałowski T (2004). Relationships and correlations between brewery traits of the spring barley varieties 7(2).

 
 

Biru A (1979). Agricultural field experiment management manual part II. AIR (Institute of Agricultural Research), Addis Ababa, Ethiopia.

 
 

Chiremba C, Rooney LW, Taylor JRN (2011). Relationship between simple grain quality parameters for the estimation of sorghum and maize hardness in commercial hybrid cultivars. Journal of Cereal Chemistry 88:570-575.
Crossref

 
 

Chittapur R, Biradar BD (2015). Association studies between quantitative and qualitative traits in rabi sorghum. Indian Journal Agricutural Science 49(5):468-471.
Crossref

 
 

Dewar J, Taylor JRN, Berjak P (1997a). Determination of improved steeping conditions for sorghum malting. Journal of Cereal Science 26:129-136.
Crossref

 
 

Dewar J, Taylor JRN, Berjak P (1997b). Effect of germination conditions, with optimised steeping on sorghum malt quality with particular reference to free amino nitrogen. Journal of the Institute of Brewing 103:171-175.
Crossref

 
 

Dewey DR, Lu KH (1959). A correlation and path coefficient analysis of components of crested wheat grass kernel production. Journal of Agronomy 51:515-518.
Crossref

 
 

Edney MJ, Eglinton JK, Collins HM, Barr AR, Legge WG, Rossnagel BG, Brew JI (2007). Importance of Endosperm Modification for Malt Wort Fermentability. Journal of Institute of Brewing 113(2):228-238.
Crossref

 
 

European Brewery Convention (1997). EBC-Analytica, 5th ed., Hans Carl Fachverlag, Nurnberg.

 
 

Ezeaku IE, Mohammed SG (2006). Character association and path analysis in grain sorghum. African Journal Biotechnology 5(14):1337-1340.

 
 

Food and agriculture organization (FAO) (2016). Cereals production and utilization. Biannual report, 2016.

 
 

Gebremeskel G, Yemane G, Solomon H (2017). Response of Sorghum (Sorghum bicolor (L.) Moench) varieties to blended fertilizer on yield, yield component and nutritional content in irrigation in Northern Ethiopia. International Journal of Agricultural Bioscience 6(3):153-162.

 
 

Gomez AK, Gomez AA (1984). Statistical Procedures for Agricultural Research. John Willey and Sons Inc., New York. 657 p.

 
 

Harlan JR (1992). Crops and Man. 2nd Edition, American Society of Agronomy and Crop Socence. America, Madison, WI.

 
 

Jahufer MZZ, Gawler FI (2000). Genotypic variation for seed yield components in white clover (Trifoliumrepens L.). Australian Journal of Agricultural Research 51:657-663.
Crossref

 
 

Kalpande HV, Chavan SK, More AW, Patil VS, Unche PB (92014). Character association, genetic variability and component analysis in sweet sorghum [Sorghum bicolor (L. Moench]. Journal Crop and Weed 10(2):108-110.

 
 

Kassahun A, Habtamu Z, Geremew B (2011). Variability for yield, yield related traits, protein Content and association among traits of sorghum [Sorghum bicolor (L) Moench] Varieties in Wollo, Ethiopia. Journal Plant Breeding and Crop Science pp. 125-133.

 
 

Khandelwal V, Shukla M, Jodha BS, Nathawat VS, Dashora SK (2015). Genetic Parameters and Character Association in Sorghum [Sorghum bicolor (L.) Moenc]). Indian Journal of Science and Technology 8(22).
Crossref

 
 

Kumar V, Pal R, Verma S, Kumar D, Kharub AS, Sharma I (2014). Association of malting quality attributes under timely and late sown conditions in barley ( Hordeum vulgare L .). Jurnalof Wheat Research 6(2):167-170.

 
 

Laidig F, Peter H, Dirk P, Thomas R (2017). Breeding progress, genotypic and environmental variation and correlation of quality traits in malting barley in German official variety trials between 1983 and 2015. Journal of Theoretical and Appllied Genetics 130(11):2411-2429.
Crossref

 
 

Mesfin T, Tileye F (2013). Genetic Diversity of Wild Sorghum (Sorghum bicolor ssp. verticilliflorum (L.) Moench) Germplasm from Ethiopia as Revealed by ISSR Markers. Asian Journal of Plant Science 12(3):137-144.
Crossref

 
 

Muhammad A, Muhammad R, Muhammad ST, Amer H, Tariq M, Muhammad SA (2003). Character association and path coefficient analysis of grain yield and yield components in maize. Pakistan Journal of Biological Science 6(2):136-138.
Crossref

 
 

Orr A, Mwema C, Gierend A, Nedumaran S (2016). Sorghum and Millets in Eastern and Southern Africa. Facts, Trends and Outlook. Working Paper Series No. 62. ICRISAT Research Program, Markets, Institutions and Policies. Patancheru 502 324, Telangana, India: International Crops Research Institute for the Semi-Arid Tropics 76 p.

 
 

Poehlman JM, Sleper DA (1995). Breeding Field Crops 4th ed. Iowa State University Press, Ames. Iowa.USA. 494 p.

 
 

Pržulj N, Momcilovic V, Crnobarac J (2013). Path Coefficient Analysis of Quality of Two-Row Spring Barley. Genetika 1(45):121-30.
Crossref

 
 

Robertson GE (1959). The sampling variance of the genetic correlation coefficient. Biometric 15:469-485.
Crossref

 
 

Rooney LW, Milner FR (1982). Variation in the structure and kernel characteristics of sorghum. Processing international symposium on sorghum grain quality, ICRISAT: Patancheru, A., India pp. 143-162.

 
 

Schuler SF, Bacon RK, Gbur EE (1994). Kernel and spike character influence on test weight of soft red winter wheat. Journal of Cereal Science 34:1309-1313.
Crossref

 
 

Silva KJ, Teodoro PE, Menezes CB, De Júlio MP (2017). Contribution of morphoagronomic traits to grain yield and earliness in grain sorghum. Journal Genetics and Molecular Research 16(2).
Crossref

 
 

Singh RK, Chaudhary BD 91985). Biometrical Methods in Quantitative Genetics 3rd Editition. Kaliyani Publishers, New Delhi-Ludhiana.

 
 

Taylor JRN, Belton PS (2002). Sorghum. In: Belton PS, Taylor JRN (eds.), Pseudo cereals and Less Common Cereals pp. 55-59.
Crossref

 
 

Taylor JRN, Dewar J (2000). Fermented products: Beverage and porriges, pp.751-795. In Smith CW, Frederiksen RA (eds.), Sorghum: origin, history, technology, and production, Wiley, New York.

 
 

Taylor JRN, Taylor J (2008). Five Simple Methods for the Determination of Sorghum Grain End-Use Quality. Department of Food Science, University of Pretoria, South Africa. INTSORMIL Scientific Publications. Available at: 

View

 
 

Vavilov NI (1951). The origin, variation, immunity and breeding of cultivated plants. Chronica Botanica 13:1-366.

 
 

Wenzel WG, Pretorius AJ (1995). The genetic variability of malt quality and related characteristics in grain sorghum. South African Journal of Plant and Soil 12(1):38-41.
Crossref

 

 




          */?>