Combining Ability and Heterosis Estimation in Elite Sorghum [Sorghum bicolor (L) Moench] Inbred lines Under Moisture Stress Areas of Ethiopia

doi:10.21203/rs.3.rs-2866905/v1

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Combining Ability and Heterosis Estimation in Elite Sorghum [Sorghum bicolor (L) Moench] Inbred lines Under Moisture Stress Areas of Ethiopia

https://doi.org/10.21203/rs.3.rs-2866905/v1

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The most important prerequisite in crop improvement is the selection of suitable parents, which could combine well and produce desirable hybrids. However, narrow genetic base, lack of potential hybrids and lack of information on the genetic components are the most important limiting factors for sorghum yield improvement. Therefore, the present study was conducted to estimate the combining abilities and heterosis for yield and its components. A total of 42 sorghum genotypes were evaluated using alpha lattice experimental design with two replications at Mieso and Kobo during the cropping season of 2019. Combined analysis of variance revealed highly significant differences due to genotypes for all studied traits over locations, which indicates the availability of substation genetic variation among genotypes. Based on general combining ability analysis, inbred line 3 and 4 were identified as best general combiners for both days to flowering and plant height traits whereas inbred line 2 and 7 were identified as best general combiners for stay green traits. The hybrid crosses 4x14, 8x15 and 11x14 were identified as best specific combiners for grain yield while hybrid 1x15 was best specific combiner for days to flowering, days to maturity, panicle length, panicle width and thousand seed weight. The estimates of general and specific combining ability revealed the preponderance of non-additive gene action since the ratio of general combining ability to specific combining ability was less than unity for all the traits under study except for plant height. The maximum grain yield was obtained from a hybrid 4x14 (6.32 tha^-1) followed by hybrid 8x15(5.92 tha^-1), 1x15 (5.88 tha^-1), 13x14 (5.78 tha^-1) and 6x15 (5.57 tha^-1) with the average value of 5.0 tha^-1which had higher mean value than the mean of the parents and the check. Among the hybrids, 8x15 recorded maximum heterosis (112.41%) over the mid parents, hybrid 1x15 revealed maximum heterosis (68.71%) over the better parent whereas 4x14 recorded maximum grain yield with (30.71%) heterosis over the standard check for grain yield. Finally, based on mean yield performance, heterosis response and combining ability estimates for grain yield and its components, the hybrid crosses 4x14, 8x15, 1x15, 11x14, 11x15, 13x14 and 6x15 were found to be the most promising and potential hybrids which could be exploited commercially after critical evaluation for their superiority and yield stability across the locations over years.

Agronomy

Combining ability

Heterosis

Sorghum

Hybrid

Drought

Sorghum [Sorghum bicolor (L.) Moench; 2n = 2x = 20] is the fifth most important cereal crop after wheat, rice, corn and barley globally (FAO, 2019). Sorghum is an annual crop and belongs to the poaceae family (Clayton and Renvoize, 1986). It is a diploid (2n) and principally self-pollinating crop (Mullet et al., 2014). It is indigenous crop to Ethiopia, where the largest genetic diversity is available (Vavilov, 1951). Sorghum grows in a wide range of agro-ecologies, most importantly in the drought-prone parts where other crops can least survive (Adugna, 2007). This makes sorghum preferable by farmers in drought-prone areas due to its tolerance to drought and harsh environments (Tekle and Zemach, 2014). It is playing a remarkable role in addressing the problem of food insecurity and meeting the increasing world food demand.

Sorghum is the main staple food crop in Ethiopia, currently ranks third after tef and maize in total production; ranks second after maize in productivity per hectare and in area harvested (CSA, 2018). It serves as an important source of income for small scale farmers because of its wide range of uses. Sorghum is mainly grown for its grain as food for humans and livestock feed and for production of local beverages (Teshome et al., 1999; McGuire, 2000). It is the most important cereal crops grown in arid and semi-arid regions of the world. Sorghum has high grain yield potential comparable to other cereals such as rice and wheat under optimal conditions. The ability of the crop to withstand considerable drought stress and providing reasonable yields under adverse environmental conditions has proven its importance as a food security crop in arid and semi-arid tropics of the world.

The discovery of cytoplasmic male sterility system promoted sorghum research towards the commercial production of hybrid cultivars (Stephens and Holland, 1954). Stephens and Holland (1954) reported for the first time, breeding for heterosis in sorghum can be accomplished by identification of stable cytoplasmic male sterile lines, maintainer and restorer lines having high GCA for desirable characters. The existences of different cytoplasmic sources that induce male sterility apart from milo-kafir cytoplasmic male sterility system have become widely available (Quinby, 1980). This has enabled sorghum breeders to exploit the cytoplasm diversity available in different races and species of sorghum from diverse geographic locations (Pedersen et al., 1998). Similarly, the continued discovery of alternative male sterile cytoplasm would effectively allow the construction of heterotic pools different from the common R/B-lines defined in terms of A cytoplasm (Pedersen et al., 1998).

The line x tester analysis method is used to breed both self and cross-pollinated crops to estimate favorable parents, crosses, their general and specific combining abilities (Aslam et al., 2014). General combining ability (GCA) is attributed to additive gene effects and additive x additive epistasis and is theoretically fixable. On the other hand, specific combining ability (SCA) attributable to non-additive gene effect and may be due to dominance, epistasis or both which is non-fixable (Koze, 2017). The presence of non-additive genetic variance is the primary justification for initiating the hybrid program (Pradhan and Singh et al., 2008). General combining ability effect is used to select the desirable parents to be used in crosses. Selection of heterotic hybrid depends on expected level of heterosis as well as the specific combining ability effect. Combining ability is a powerful tool in identifying the best combiners that may be used in crosses either to exploit heterosis or to accumulate fixable genes and obtain desirable segregates that helps to understand the genetic architecture of various characters that enable the breeder to design effective breeding plan for future up-gradation of the existing materials.

Breeding strategies based on selection of hybrids require expected level of heterosis as well as the specific combining ability. In breeding, high yielding varieties of crop plant, the breeders often face with the problem of selecting parents and crosses. Combining ability studies provide useful information regarding the selection of suitable parents for effective hybridization programs and indicate the nature and magnitude of various types of gene action involved in the expression of quantitative characters (Sprague and Tatum, 1942). Heterosis is the superiority of hybrids over their parents and standard checks in terms of productivity, growth, development and resistance (Shull, 1914). The exploitation of heterosis through hybrid breeding is one of the landmark achievements in plant breeding (Duvick, 2001). Potential of sorghum hybrids is estimated from the percentage increase or decrease of their performance over the mid parent (average heterosis) and better parent (heterobeltiosis) (Ringo et al., 2015).

Several improved sorghum varieties have been developed and released with better drought tolerance and relatively high yield potential. However, on average, 2.7 tha^− 1 of grain yield is obtained (CSA, 2018), which is much lower than the potential yield of 7 to 9 tha^− 1 obtained under intensive management (Borrell et al., 2000). Success of any breeding program depends on proper characterization and quantification of the available genetic resources. In Eastern Africa, more than 70% of sorghum is cultivated in the dry and marginal areas (Mukuru, 1992), suggesting the crop has been adapted to such adverse environments. This, in turn, increases genetic plasticity of the crop to flourish under harsh environmental conditions. A wide genetic diversity of sorghum has been developed over the years as a result of continued active selection by farmers (Gebrekidan, 1973, Ayana and Bekele, 2000). This offers breeders greater opportunity to select superior parental genotypes for the production of commercial hybrids.

Development of high yielding, locally adapted and famers-preferred hybrids is one of the approaches to alleviate the inherent low productivity of crops in the semi-arid tropics. In Africa, the use of hybrid sorghum is lagging behind as compared to a long history of hybrid production in the US and Asia. For example, in the last 30 years the use of hybrid rice in China enabled reduction of a total amount of land by 20% while yield have been increased by 48% (FAO, 2004). Similarly, India through the use of hybrid sorghum has achieved a yield increase of 80% by reducing 37% of the total amount of land planted to sorghum during the same period (Mishra et al., 1992). Further, hybrid cultivars have been reported to be more productive and stable than pure line varieties (Kenga et al., 2004). Further, sorghum grain yield advantage of 50 to 100% has been reported in hybrids as compared to their parents over a range of environments (Blum et al., 1990; Haussmann et al., 1999).

The sorghum hybrid development research program in Ethiopia is at its infant stage. Attempts have been restricted to characterizing combining ability and assessing the heterotic patterns of exotic parental lines (Degu et al., 2009). The potential of the available genetic diversity within local landraces for hybrid cultivar development is not yet been exhaustively assessed. The genetic potential of any material is largely determined by its general and specific combing ability for yield and yield related traits under diverse environmental conditions. Quantifying the combining ability and heterosis of sorghum genotypes in phenological, yield and yield related traits contributing towards drought tolerance is vital for ultimate breeding. Therefore, this study was conducted to estimate magnitude of heterosis and combining ability of sorghum inbred lines in line x tester mating design and to identify potential parents and crosses of sorghum for yield and yield related traits.

2.1 Description of the Study Areas

The experiment was conducted across the two environments representing the dry lowlands areas of Ethiopia. These were Mieso from the Oromia Regional State and Kobo from the Amhara Regional State. In these target environments, drought is a serious challenge for sorghum production and they are considered as major testing sites for drought adaptation (EIAR, 2014).

Table 1

Description of the experimental locations
Location	Altitude (masl)	Rainfall (mm)	Temp (°C) Min	Max	Latitude	Longitude	Soil type
Mieso	1470	763	14.00	30.00	8º30΄N	39º21΄E	Vertisols
Kobo	1479	650	15.32	30.24	12º09΄N	39º38΄E	Vertisols

2.2 Plant materials and crosses

Thirteen selected inbred lines were crossed to two cytoplasmic male-sterile lines in a line x tester mating design. The 13 lines originated from different geographic origins mainly grown in lowland drought prone areas in Ethiopia and selected from prior genetic and agro-morphological studies based on relatively better yield and yield components under moisture stress. These lines were kept homogenous through continued selfing and selection and served as male parents. The 26 F_1s, 2 male, 13 B lines and one standard check were evaluated under two moisture stressed environments. The B lines were used in place of their male sterile counterparts. The seed parents were developed by back-crossing of the new B-lines with known B-lines to introgress the cytoplasmic male sterile gene through recurrent selection. Some of the seed parents were introduced from Purdue University whereas some of the seed parents developed by national sorghum research program (Melkassa Agricultural Research Center). These inbred lines were tested for adaptation and stability of male sterility and are being used for the hybrid development in the national program. The tester, Melkam is developed and released by Melkassa Agricultural Research Center, whereas ICSR-14 was developed for terminal moisture stress and obtained from the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT). They were used as restorer lines for low moisture stress areas and selected on the basis of their wider adaptability traits for drought stress environments and grain yield performance. The standard check (ESH-4) is early maturing, relatively short (120–200 cm) and semi loose head types which is released by Melkassa agricultural research center (MARC) for their moisture stress tolerance.

Table 2

Description of the genotypes included in the experiment at Mieso and Kobo in 2019 cropping season
S.N	Lines	Pedigree	S.N	Hybrids	Pedigree
1	TX-623B	TX-623B	21	P-851015A X ICSR − 14	P-851015A X ICSR-14
2	P-9501B	P-9501B	22	P-850341A X ICSR-14	P-850341A X ICSR-14
3	P-9505B	P-9505B	23	A5 X ICSR-14	A5 X ICSR-14
4	P-9534B	P-9534B	24	A6 X ICSR-14	A6 X ICSR-14
5	P-851015B	P-851015B	25	MARC1A X ICSR-14	MARC1A X ICSR-14
6	P-850341B	P-850341B	26	MARC2A X ICSR-14	MARC2A X ICSR-14
7	B5	B5	27	MARC3A X ICSR-14	MARC3A X ICSR-14
8	B6	B6	28	MARC6A X ICSR-14	MARC6A X ICSR-14
9	MARC1B	MARC1B	29	P9511A X ICSR-14	P9511A X ICSR-14
10	MARC2B	MARC2B	30	TX-623A X Melkam	TX-623A X Melkam
11	MARC3B	MARC3B	31	P-9501A X Melkam	P-9501A X Melkam
12	MARC6B	MARC6B	32	P-9505A X Melkam	P-9505A X Melkam
13	P9511B	P9511B	33	P-9534A X Melkam	P-9534A X Melkam
	Testers		34	P-851015A X Melkam	P-851015A X Melkam
14	Melkam	WSV387	35	P-850341A X Melkam	P-850341A X Melkam
15	ICSR-14	ICSR-14	36	A5 X Melkam	A5 X Melkam
	Check		37	A6 X Melkam	A6 X Melkam
16	ESH-4	PU20AXPU304	38	MARC1A X Melkam	MARC1A X Melkam
	Hybrids		39	MARC2A X Melkam	MARC2A X Melkam
17	TX-623A X ICSR-14	TX-623AX ICSR-14	40	MARC3A X Melkam	MARC3A X Melkam
18	P-9501A X ICSR-14	P-9501A X ICSR-14	41	MARC6A X Melkam	MARC6A X Melkam
19	P-9505A X ICSR-14	P-9505A X ICSR-14	42	P9511A X Melkam	P9511A X Melkam
20	P-9534A X ICSR-14	P-9534A X ICSR-14

2.2 Experimental Design and Trial Management

The experiment was laid out using alpha lattice (0, 1) design with two replications at two locations in the cropping season of 2019. Each genotype was planted in 2 rows of 5 m length with the row spacing of 75 cm which gives rise to plot area of 7.5 m². Each block was separated by 1 m length. The experiment accommodated seven plots per block and six blocks per replication. The seeds were drilled in each row at the rates of 12 kgha^− 1. After three weeks of sowing, the seedlings were thinned to 0.20 m distance between plants. All the standard agronomic packages and fertilizer rates of 100 kgha^− 1 NPS and 50 kgha^− 1 Urea were applied to basal and Nitrogen (Urea) was applied after three weeks of sowing. Weeds were controlled manually and Pests were controlled using insecticide karate.

2.3 Data Collection

Data were collected from both plot and plant based by random sampling technique with the use of descriptors for sorghum (IBPGR/ICRISAT, 1993). The important yield and yield component characters along drought resistant associated characters were collected using standard procedures here under.

Days to flowering (DTF): Number of days from emergence till 50% of the plants in a plot showed flowering halfway down the panicle.

Days to maturity (DTM): The number of days from emergence to the date when 95% of the plants matured physiologically.

Plant height (PH in cm): The length of the plant from the ground to the panicle tip at physiological maturity.

Number of leaves per plant: Total numbers of leaves were taken from 5 plants selected randomly on the main plant in each plot.

Panicle exertion (PE in cm): The length between the final (the most top) nodes up to the base of the panicle.

Stay green score (1–5): Stay greenness score visually observed at physiological maturity 1 = for highly green and 5 = for low greenness.

Grain yield (GY): Grain yield obtained from total harvest of the plot and then converted to ton/ha after adjusting to optimum seed moisture content.

Panicle yield (PY in g): The weight of individual panicle as measured using one representative samples in a plot.

Panicle length (PL in cm): The average length of five randomly selected plants from the base of the panicle to the tip.

Panicle width (PW in cm): The average length of five randomly selected plants at the middle of the panicle.

Total leaf area (LA in cm²): Area of the flag leaf computed as (Leaf length x Leaf width x 0.69) suggested by (Krishnamurthy et al., 1974).

Thousand seed weight (TSW in g): The weight of 1000 grains sampled from a plot at 12.5% moisture content recorded in gram from single plot.

2.5 Statistical analysis

Analysis of variances

The data were analyzed using PROC MIXED procedure in SAS (2018) by considering location, replication and blocks as random and genotype as fixed factors for individual location analyses. In the combined analyses, environments, replications within environments and blocks within replications and environments were considered as random while genotypes remained as fixed effects following same procedure of Moore and Dixon (2015). Combined analyses were performed for traits that showed significant genotypic differences in the individual location analyses, and after testing homogeneity of error variance using Bartlett’s test (Gomez and Gomez, 1984). Means were separated using Fisher’s Least Significant Difference (LSD) test at 5% level of probability as stated in Gomez and Gomez (1984).

Yijkl = µ + gi + sj + (g × s)ij + r(s)jk + eijkl

Where µ is the overall mean, gi is the effect of the ith genotype, sj is the effect of the jth site, (g×s)ij is the interaction effect of the ith genotype by the jth site, r(s)jk is the effect of the kth replication within the jth site and eijkl is the residual variance.

Combining ability analysis was carried out by the method suggested by Kempthorne (1957) as follows:-

General Combining Ability Effect (GCA) - General combining ability (GCA) effect of lines and testers were defined as a deviation of line and tester-mean from mean of hybrids and calculated using the following equations:

$$\text{G}\text{e}\text{r}\text{e}\text{r}\text{a}\text{l} \text{c}\text{o}\text{m}\text{b}\text{i}\text{n}\text{i}\text{n}\text{g} \text{a}\text{b}\text{i}\text{l}\text{i}\text{t}\text{y}\text{o}\text{f} \text{l}\text{i}\text{n}\text{e}\text{s} \left(\text{G}\text{C}\text{A}\text{i}\right)=\frac{\text{X}\text{i}}{\text{t}\text{r}}-\frac{\text{X}}{\text{l}\text{t}\text{r}}$$

$$\text{G}\text{e}\text{n}\text{e}\text{r}\text{a}\text{l} \text{c}\text{o}\text{m}\text{b}\text{i}\text{n}\text{i}\text{n}\text{g} \text{a}\text{b}\text{i}\text{l}\text{i}\text{t}\text{y} \text{o}\text{f} \text{t}\text{e}\text{s}\text{t}\text{e}\text{r}\text{s} \left(\text{G}\text{C}\text{A}\text{j}\right)=\frac{\text{X}\text{j}}{\text{l}\text{r}}-\frac{\text{X}}{\text{l}\text{t}\text{r}}$$

Where GCAi = GCA effect for the ith lines with Σ GCAi = 0; GCAj = GCA effect for the jth testers with Σ GCAj = 0; Xi. = the total of ith line over all testers (t) and replications (r); X. j = the total of the jth testers over all lines (lt) and replication (r) and X. = the total of all the hybrids over all lines (lt), testers (t) and replications (r).

Specific Combining Ability Effect (SCA) - Specific combining ability (SCA) effect of hybrid combinations is the deviation of each hybrid mean from the mean of all hybrids adjusted for corresponding GCA effects of parents and was computed as:

$$\text{S}\text{p}\text{e}\text{c}\text{i}\text{f}\text{i}\text{c} \text{c}\text{o}\text{m}\text{b}\text{i}\text{n}\text{i}\text{n}\text{g} \text{a}\text{b}\text{i}\text{l}\text{i}\text{t}\text{y} \left(\text{S}\text{C}\text{A}\text{i}\text{j}\right)=\frac{\text{X}\text{i}\text{j}}{\text{r}}-\frac{\text{X}\text{i}}{\text{t}\text{r}}-\frac{\text{X}\text{j}}{\text{l}\text{r}}+\frac{\text{X}}{\text{l}\text{t}\text{r}}$$

Where SCAij = SCA effect of the ijth hybrid with Σ Sij = 0 for each j; Xi j. = the total of ijth hybrid combination over all replications (r).

Standard errors for combining ability effects

The significance of GCA or SCA effects were tested by dividing the GCA effects of a particular line or males and SCA effects of a particular hybrid by its respective standard error.

$$\text{S}\text{i}\text{g}\text{n}\text{i}\text{f}\text{i}\text{c}\text{a}\text{n}\text{c}\text{e} \text{o}\text{f} \text{G}\text{C}\text{A} \text{e}\text{f}\text{f}\text{e}\text{c}\text{t}\text{s} \text{o}\text{f} \text{l}\text{i}\text{n}\text{e}\text{s} \text{t}\text{e}\text{s}\text{t}\text{e}\text{d}\left(\text{t}\right)=\frac{\text{g}\text{i}}{\text{S}\text{E}}\left(\text{g}\text{i}\right)$$

$$Significance of GCA of testers tested\left(t\right)=\frac{gi}{SE}\left(gj\right)$$

$$\text{S}\text{i}\text{g}\text{n}\text{i}\text{f}\text{i}\text{c}\text{a}\text{n}\text{c}\text{e} \text{o}\text{f} \text{S}\text{C}\text{A} \text{e}\text{f}\text{f}\text{e}\text{c}\text{t}\text{s} \text{h}\text{y}\text{b}\text{r}\text{i}\text{d}\text{s} \text{t}\text{e}\text{s}\text{t}\text{e}\text{d}\left(\text{t}\right)=\frac{\text{g}\text{i}\text{j}}{\text{S}\text{E}}\left(\text{s}\text{i}\text{j}\right)$$

Therefore, the SE was computed using SAS software using the following formulae:

$$\text{S}\text{t}\text{a}\text{n}\text{d}\text{a}\text{r}\text{d} \text{e}\text{r}\text{r}\text{o}\text{r} \text{o}\text{f} \text{G}\text{C}\text{A} \text{f}\text{o}\text{r} \text{l}\text{i}\text{n}\text{e}\text{s}\left(\text{g}\text{i}\right)=\surd (\text{m}\text{s}\text{e}/\text{t}\text{r})$$

$$\text{S}\text{t}\text{a}\text{n}\text{d}\text{a}\text{r}\text{d} \text{e}\text{r}\text{r}\text{o}\text{r} \text{o}\text{f} \text{G}\text{C}\text{A} \text{f}\text{o}\text{r} \text{t}\text{e}\text{s}\text{t}\text{e}\text{r}\text{s}\left(\text{g}\text{j}\right)=\surd (\text{m}\text{s}\text{e}/\text{r}\text{l})$$

$$\text{S}\text{t}\text{a}\text{n}\text{d}\text{a}\text{r}\text{d} \text{e}\text{r}\text{r}\text{o}\text{r} \text{o}\text{f} \text{S}\text{C}\text{A} \text{f}\text{o}\text{r} \text{h}\text{y}\text{b}\text{r}\text{i}\text{d}\text{s}\left(\text{s}\text{i}\text{j}\right)=\surd (\text{m}\text{s}\text{e}/\text{r})$$

Estimation of Variance Components for Combining Abilities

The estimates of genetic variance components due to lines, testers and hybrids were obtained (Kempthorne, 1957) as follows:

$$\text{V}\text{a}\text{r}\text{i}\text{a}\text{n}\text{c}\text{e} \text{f}\text{o}\text{r} \text{g}\text{c}\text{a}\text{i}=\frac{\text{M}\text{S}\text{l}-\text{M}\text{S}\text{l}\text{x}\text{t}}{\text{t}\text{r}}\dots ..\text{X}$$

$$\text{V}\text{a}\text{r}\text{i}\text{a}\text{n}\text{c}\text{e} \text{f}\text{o}\text{r} \text{g}\text{c}\text{a}\text{j}=\frac{\text{M}\text{S}\text{t}-\text{M}\text{S}\text{l}\text{x}\text{t}}{\text{l}\text{r}}\dots ..\text{Y}$$

$$\text{A}\text{v}\text{e}\text{r}\text{a}\text{g}\text{e} \text{v}\text{a}\text{r}\text{i}\text{a}\text{n}\text{c}\text{e}=\frac{\text{X}+\text{Y}}{\text{l}+\text{t}+\text{r}}$$

$$\text{V}\text{a}\text{r}\text{i}\text{a}\text{n}\text{c}\text{e} \text{f}\text{o}\text{r} \text{a}\text{d}\text{d}\text{i}\text{t}\text{i}\text{v}\text{e} \text{g}\text{e}\text{n}\text{e}\text{s}=4 \text{x} \text{a}\text{v}\text{e}\text{r}\text{a}\text{g}\text{e} \text{v}\text{a}\text{r}\text{i}\text{a}\text{n}\text{c}\text{e}$$

$$\text{V}\text{a}\text{r}\text{i}\text{a}\text{n}\text{c}\text{e} \text{f}\text{o}\text{r} \text{s}\text{c}\text{a}\text{i}\text{j}=\frac{\text{M}\text{S}\text{l}\text{x}\text{t}-\text{M}\text{S}\text{e}}{\text{r}}$$

$$\text{V}\text{a}\text{r}\text{i}\text{a}\text{n}\text{c}\text{e} \text{f}\text{o}\text{r} \text{d}\text{o}\text{m}\text{i}\text{n}\text{a}\text{n}\text{t} \text{g}\text{e}\text{n}\text{e}\text{s}=4 \text{x} \text{v}\text{a}\text{r}\text{i}\text{a}\text{n}\text{c}\text{e} \text{o}\text{f} \text{s}\text{c}\text{a}$$

Where, σ²gi = σ²gcai = Variance due to general combining ability for females σ²gj = σ²gcaj = Variance due to general combining ability for males σ²sij = σ²scaij = Variance due to specific combining ability for hybrids r = Number of replications l = Number of lines, t = Number of testers, MSl = Mean square due to lines, MSt = Mean square due to testers, MSlxt = Mean square due to hybrids, MSe = Mean square due to error.

2.6 Estimation of Standard Heterosis

Heterosis in F_1’s was calculated as the difference of F₁ hybrid performance from average heterosis, Standard heterosis and better parent as per formula given by Falconer (1996).

$$Midparent heterosis \left(\%\right)=\frac{F1-midparent}{midparent}x100$$

$$Better parent heterosis\left(\%\right)=\frac{F1-better parent}{better parent}x100$$

$$Standard heterosis\left(\%\right)=\frac{F1-standard check}{standard check}x100$$

Where F₁ is the estimated mean performance of the hybrid, MP is the average of the estimated performance of the two inbred parents, and BP is the estimated mean values for the better performing inbred parent and SC is the mean value of standard check.

The differences in the magnitude of heterosis tested following the procedure of (Singh, 1985). Standard error and critical difference were also computed for testing the heterosis as follows:

The standard error (SE) of the difference for heterosis over mid-parent (MP)

$$SE\left(d\right)for MP=\pm \surd (3ME/2r)$$

$$CD for MP=SE\left(d\right)for MP x t at error degrees of freedom$$

The standard error (SE) of the difference for heterosis over better parent (BP) and standard check (SC)

$$SE\left(d\right)forBP=\pm \surd (2ME/r)$$

$$SE\left(d\right)forSC=\pm \surd (2ME/r)$$

$$CD for BP=SE\left(d\right)for BP x t at error degrees of freedom$$

$$CD for SC=SE\left(d\right)for SC x t at error degrees of freedom$$

SE (d) is standard error of the difference. MSe = error mean square from analysis of variance r = the number of replication CD = Critical difference t = value of t at error degree of freedom.

The test of significance of heterosis in relation to standard check was done by‘t’ test as suggested by Snedecor and Cochran (1967) as follows:

$$t\left(Midparent heterosis\right)= \frac{F1-MP}{ SE\left(d\right)}$$

$$t\left(Better parent heterosis\right)= \frac{F1-BP}{ SE\left(d\right)}$$

$$t\left(standard check\right)= \frac{F1-SV}{ SE\left(d\right)}$$

3.1 Analyses of Variance (ANOVA)

The mean squares due to the different sources of variations were estimated as per standard the procedure of analyses of alpha-lattice design for combined over the two locations. The mean squares due to genotypes exhibited significantly high (P < 0.01) for all the studied traits over combined locations (Table-3). This is indicated the presence of considerable variation in the genetic materials and the variation resulted in all traits were due to genotypes rather than environmental effects. The mean squares due to genotype x environmental interaction exhibited significantly high for days to flowering, plant height, days to maturity, effective productive tiller, panicle exersion, panicle yield, grain yield and thousand seed weight whereas significant variation is observed for panicle width trait. This implies the modification of genetic factors by environmental factors, and the role of genetic factors in determining the performance of genotypes in different environments. Genotype x environmental interaction is said to exist when genotype performance differs over environments. The performances of genotype vary greatly across environment because of the effect of environment on trait expression. Selection of superior genotypes in target environments is an important objective of plant breeding programs. In order to identify superior genotypes across multiple environments, plant breeders conduct trials across locations and years, especially during the final stages of cultivar development.

Table 3

Combined analysis of variance of sorghum genotypes for yield and yield related traits at Mieso and Kobo during 2019 cropping season
Traits	MS_L (DF = 1)	MS(Rep(Loc)) (DF = 2)	MS_G (DF = 41)	MS_GL (DF = 41)	MS_E (DF = 72)	CV	R²
DF	1080.21^**	0.01	13.23^**	5.51^**	2.62	2.29	0.91
DM	1494.05^**	7.29	15.10^**	13.74^**	4.67	1.95	0.89
PHT	14359.70^**	1955.70^**	7615.51^**	332.80^**	70.47	4.43	0.98
SG	63.14^**	0.06	0.78^**	0.51^ns	0.35	22.15	0.83
PL	117.66^**	5.42	27.08^**	3.80^ns	2.99	6.13	0.87
PW	308.34^**	13.03^**	3.86**	1.10^*	0.65	9.85	0.92
LA	439598.44^**	16.35	5662.39^**	3919.83	2812.38	16.84	0.81
TL	4864.38^**	233.35^**	36.13^**	40.81^**	20.47	24.14	0.86
PE	388.87^**	104.97^**	31.36^**	7.47^ns	5.31	28.33	0.85
PY	183467.16^**	9.24	2206.42^**	762.70^**	352.03	22.12	0.92
GY	858491.96^**	5700.15^**	5106.56^**	1708.55^**	869.54	21.75	0.94
TSW	7100.60^**	0.86	60.41^**	13.25^**	6.02	9.37	0.96

3.2 Mean Performance of Sorghum Genotypes for Yield and Yield Related Traits

The superior sorghum genotypes were identified based on mean performance for different traits as indicated in (Table-4). Interestingly, genotypes listed as number 17 (6.32 tha^− 1), 8 (5.92 tha^− 1), 1 (5.88 tha^− 1), 26 (5.78 tha^− 1) and 6 (5.57 tha^− 1) were high yielder whereas genotypes listed as number 34 (2.05 tha^− 1), 31 (2.13 tha^− 1), 32 (2.25 tha^− 1), 28 (2.34 tha^− 1), 33 (2, 36 tha^− 1) were low yielder as compared to the other genotypes. Generally, among the tested genotypes, twenty four genotypes gave higher than the average yield (4.29 tha^− 1). These included almost the hybrids other than lines and testers. The values of average yield performance of the genotypes ranged from 2.05 tha^− 1 to 6.32 tha^− 1. In addition to yield performance, considering growth and morphological parameters contributing for the yield performance as a selection criterion in the development of drought tolerance genotypes were suggested (Rosenow et al., 1983).

Days to flowering and maturity are among the most important attributes that need to be considered in selecting genotypes for drought affected areas. In this study, the mean number of days to flowering ranged from 68 days in the early flowered genotype (35) to 77 days in the late flowered genotypes (31). Similarly, mean number of days to maturity ranged from 108 to 114 for the same group of genotypes. Both early and late maturing genotypes had the same grain fill duration; however variation was detected for grain yield and related yield components among these genotypes, indicating that the variation in the other attributes might be associated with factors other than duration of grain fill.

The top yielder genotypes (17) required 69 days to flower and 108 days to mature which was close to the average for genotypes, 70 days for flowering and 111 days for maturity. This indicates that, the yielding potential is not necessarily associated with crop phenology provided that genes for high yield potential are incorporated in the genotypes. The global successes in improving sorghum yield by deploying high yielding early maturing hybrids also supports this idea. Meanwhile, delayed flowering for genotypes encountered severe drought condition was reported (Blum et al., 1989), which would have considerable effect on the productivity of the crop (Blum et al., 1989). Similarly, the actual mean values showed variation among genotypes for plant height and leaf area and these appeared to be under strong genetic control, although environment could have marked effect.

Mean plant height ranged from 107.50cm to 271cm, and leaf area ranged from (220.36cm² to 405.63cm²). Breeding for shorter plant height was one of the major goals of the sorghum breeding program for dry lowland areas where drought adversely affects the plants which had prolonged vegetative growth and to make commercial genotypes fit to mechanical harvesting. Drought resistance is a complex trait, expression of which depends on action and interaction of different morphological traits (earliness and reduced leaf area). Among the various drought resistance related traits, leaf area is very relevant by narrowing the leaf length and leaf width when the drought becomes severe in order to limit water loss. Generally, genotypes that were best performing in terms of several traits, i.e. high yield, early flowering, early maturity, shorter plant height and narrow leaf at the same time are preferable than genotypes that vary with different traits for instance, high yielder but late maturity and vice versa.

Table 4

Top and bottom mean performing sorghum genotypes foe selected traits at Mieso and Kobo during 2019 cropping season
Top 10 performing genotypes
Genotypes	DTF	Genotypes	DTM	Genotypes	PTH	Genotypes	GY	Genotypes	LA
35	67.75^m	26	107.75^j	34	107.50^t	17	6.32^a	31	220.36^l
29	67.75^m	17	107.75^j	28	113.40^ts	8	5.92^ba	33	242.19^lk
42	68.00^ml	2	108.00^ji	29	119.70^rs	1	5.88^ba	34	258.48^jlk
39	68.00^ml	4	108.50^jhi	33	119.70^rs	26	5.78^bac	37	260.07^jlik
28	68.50^mlk	1	108.50^jhi	42	125.50^rq	6	5.57^bac	32	263.75^jlihk
26	68.75^mljk	16	108.75^jhig	27	131.30^rq	22	5.51^bdac	27	265.36^jlihk
17	69.00^imljk	35	109.00^jhigf	32	132.90^q	9	5.37^ebdac	36	266.59^jlihkg
16	69.00^imljk	22	109.00^jhigf	30	133.30^q	14	5.33^ebdac	30	268.89^jlihkjf
4	69.25^imlhjk	21	109.00^jhigf	39	133.60^q	20	5.25^ebdacf	28	279.45^ejlihkg
3	69.25^imlhjk	20	109.00^jhigf	41	137.10^q	24	5.14^ebdacf	24	289.11^ejlidhkg
Bottom 10 performing genotypes
14	71.75^fcebdg	30	112.25^ebdac	11	237.90^ef	39	3.03^kjmil	15	343.22^ebdacf
37	72.00^fcebd	28	112.25^ebdac	12	243.50^ef	30	3.02^kjmil	26	345.14^ebdac
38	72.25^cebd	40	112.50^bdac	37	245.10^ed	36	3.00^kjmil	8	346.86^ebdac
32	72.25^cebd	41	112.75^bac	36	245.90^ecd	29	2.82^kjml	42	350.46^ebdac
18	72.25^cebd	42	113.00^bac	22	256.60^bcd	27	2.78^kml	16	351.73^ebdac
23	73.25^cbd	27	113.00^bac	24	257.70^bc	33	2.36^ml	1	353.84^ebdac
41	73.75^bc	33	113.50^ba	9	258.00^b	28	2.34^ml	13	355.22^bdac
27	73.75^bc	32	113.50^ba	25	259.10^b	32	2.25^ml	3	365.97^bac
40	74.00^b	23	113.50^ba	10	259.90^ba	31	2.13^m	5	3.78.56^ba
31	77.00^a	31	114.50^a	23	271.00^a	34	2.05^m	12	405.68^a
Mean	70.00		111.00		189.38		4.29		314.92
Maximum	77.00		114.50		271.00		6.32		405.68
Minimum	67.75		107.75		107.50		2.05		220.36
LSD (5%)	2.28		3.04		11.83		1.31		74.75
SD	1.62		2.16		8.39		0.93		53.03
R²	0.91		0.89		0.98		0.94		0.81

Mean Performance of Parents, Hybrids and Check for Yield and Yield Related Traits

Hybrids gave the highest mean performance for grain yield trait in comparison to the parents and the check. This ensured the superiority of hybrids (39–80%) over open pollinated varieties for yield (Quinby, 1962). This also indicates the suitability of hybrids in moisture stress areas where other open pollinated varieties lacked the adaptive traits for diverse local environments. The mean grain yield for hybrids ranged from 3.98 tha^-1 to 6.32 tha^-1. The highest yield was obtained from the hybrid cross of 4x14 (6.32 tha^-1) followed by the hybrid combinations of 8x15 (5.92 tha^-1), 1x15 (5.88 tha^-1), 13x14 (5.78 tha^-1) and 6x15 (5.57 tha^-1). The mean value of hybrid is 5.01 tha^-1, which is higher than the grand mean of the genotypes (4.29 tha^-1), mean of lines (2.80 tha^-1), mean of testers (3.84 tha^-1) and mean of check (4.47 tha^-1). This implied that, the performances of the parents and the check was lower as compared to hybrids and heterosis breeding is effective to improve this trait.

The superiority of the hybrids over the check variety in grain yield indicated the potential positive economic advantage of hybrids in the diverse sorghum-growing environments. Hybrid (4 x14) stood first in grain yield and second in early maturity trait among all genotypes which are preferable in moisture stress areas. From the statistical point of view, the hybrids were significantly different from lines, testers and check at (p < 0.05) level of significance for grain yield traits. There was statistically significant different between hybrids and testers in terms of days to flowering and days to maturity, indicating earlier maturity of hybrids compared to testers and the significant difference was revealed between hybrids and check for days to maturity trait.

Table 5

Mean Comparison of genotypes, Parents, Hybrids and Check at Mieso and Kobo during 2019 cropping season
Statistics	DTF	PHT	DTM	SG	PL	PW	LL	LW	LA	GY	TSW
Grand Mean	70.69	189.38	110.58	2.68	28.20	8.23	63.03	7.16	314.92	4.29	26.18
Max	77.00	271.00	114.5	3.5	33.45	10.1	70.08	8.50	405.68	6.32	34.33
Min	67.75	107.50	107.75	1.25	22.50	6.05	52.50	6.00	220.36	2.05	17.53
Mean of Hybrid	70.36	209.18	109.67	2.80	29.36	8.85	64.27	7.40	332.39	5.05	27.87
Max of Hybrid	73.02	269.58	112.86	3.58	32.65	9.86	68.60	8.50	405.68	6.32	34.26
Min of Hybrid	68.37	175.02	107.09	2.02	25.68	7.73	57.63	6.68	287.70	3.98	23.23
Mean of Line	71.08	160.42	111.87	2.54	25.65	6.95	59.87	6.61	275.45	2.80	22.13
Max of Line	77.00	245.90	114.50	3.50	29.50	7.60	66.00	7.33	333.62	3.94	27.53
Min of Line	67.75	107.50	109.00	1.25	22.50	6.05	52.50	6.00	220.36	2.05	17.53
Mean of Tester	73.88	151.60	112.63	2.62	27.13	8.65	63.95	7.38	325.15	3.84	30.99
Max of Tester	74.00	166.10	112.75	2.75	28.50	9.25	65.08	7.58	341.15	4.12	31.48
Min of Tester	73.75	137.10	112.50	2.50	25.75	8.05	62.83	7.17	309.14	3.55	30.50
Mean of Check	68.00	125.50	113.00	1.75	33.45	7.05	70.08	7.25	350.46	4.77	25.20
LSD (5%)	2.28	11.83	3.04	0.83	2.44	1.14	7.36	1.20	74.75	1.31	3.45
SD	1.62	8.39	2.16	0.59	1.73	0.81	5.22	0.85	53.03	9.32	2.45
CV (%)	2.29	4.43	1.95	22.15	6.13	9.85	8.28	11.93	16.84	21.75	9.37

Combining Ability Analyses for Yield and Yield Related Traits

The analysis of combining ability variance components was performed to determine precisely the importance of additive and dominance components in the inheritance of the traits under study. The GCA variance of parents and SCA variance of crosses for the different traits are the important basic criteria for selection and hybridization program. The significance of mean squares for line x testers provides a direct test of significance of dominance variance, σ²D, while significance of σ²A is provided by significance of lines and testers mean squares. Combining ability analysis of variance over the two locations confirmed the presence of variation among the tested genotypes. The mean squares of general combining ability (GCA) and specific combining ability (SCA) estimates were analyzed for all the traits as indicated in (Table-6).

Significant lines and tester’s variance indicated substantial genetic variability for general combining ability among the lines and testers respectively for traits like days to flowering, plant height, stay green, panicle length, panicle exersion, panicle yield and thousand seed weight. But the highest contribution towards general combining ability for many of the traits was due to female parental lines. The significant mean squares due to parents also reflect the preponderance of additive gene variance which is important to improve the parents through selection breeding procedure. The mean squares due to lines x testers interaction revealed significant different for plant height and panicle width, which indicated the presence of specific combining ability variances among the crosses. The non- additive gene variance was important to improve the concerned traits through heterosis breeding or hybridization breeding method.

The variation among the hybrids was further partitioned into genetic components attributable to general combining ability (GCA) and specific combining ability (SCA). Similarly, in earlier studies Xingming et al, (2004; Glover et al, (2005) and Kidanemariam Wagaw et al., (2020) recorded significant mean squares of GCA and SCA effects for yield and yield components in sorghum. The results clearly suggested considerable amount of average heterosis in the hybrids and this reflected the presence of adequate genetic variability in the genetic materials for the superiority of hybrids. Similar finding has been reported for average heterosis by comparing parent vs. hybrid in single degree of freedom for fifty hybrids derived from ten female and five male sorghum lines (Kumar et al., 2017). The variance due to environment x different source of variations like parents, lines, testers, hybrids and hybrid vs. parent were found to be significant for the concerned traits of their respective interaction which indicates considerable amount of interaction between the different sources of variations and the environments.

Table 6

Combining ability analysis for yield and yield related traits in sorghum at Mieso and Kobo during 2019 cropping season
Traits
Source of Variation	DF	DTF	PHT	DTM	SG	PL	PW	LA	GY	TSW
Location	1	1080.21^**	14359.70^**	1494.05^**	63.14^**	117.66^**	308.34^**	439598.44^**	858491.93^**	7100.60^**
Rep(L)	2	0.00	1955.70^**	7.29	0.06	5.42	13.03^**	16.35	5700.15^**	0.86
Parents	14	28.15^**	10121.19^**	8.88^*	1.15^**	19.44^**	2.44^**	4837.30^*	1678.97^**	81.06^**
Hybrids	25	5.10^**	4288.77^**	7.41	0.64^*	11.79^**	1.62	2958.47	1264.76	41.95^**
Lines	12	8.12^**	8724.51^**	9.63	0.88^**	19.27^**	1.25	2606.25	1390.63	76.62^**
Testers	1	3.47	572.46^**	0.47	0.24	2.28	0.34	18171.24^**	318.85	13.37
Lines x Testers	12	2.22	162.71^*	5.76	0.42	5.10	2.10^*	2042.97	1217.71	9.65
Parent Vs Hybrids	1	45.55^**	95086.83^**	198.48^**	2.34^*	468.66^**	109.99^**	96749.62^**	167591.62^**	792.48^**
Parent * L	14	13.41^**	350.14^**	28.74^**	1.08^**	4.25	1.11	2549.44	617.10*	10.96
Hybrid *L	25	1.86	349.75^**	4.90	0.31	3.59	0.83	3586.11	1020.53	11.74^**
Lines*L	12	2.45	618.29^**	6.71	0.32	5.57	1.38	3651.38	1474.88	18.23^**
Testers *L	1	7.00	48.74	7.00	0.24	1.16	0.01	3681.66	608.61	10.15
Lines Testers L	12	0.84	106.29	2.92	0.30	1.82	0.34	3512.88	600.51	5.39
Hybrid vs parent*L	1	11.97	448.11	198.48^**	1.51	0.68	9.65^**	26771.48^**	41045.72^**	124.94^**
Error	72	2.62	70.47	4.67	0.35	2.99	0.65	2812.38	869.54	6.02
CV (%)		2.29	4.43	1.95	22.15	6.13	9.85	16.84	21.75	9.37
LSD (5%)		2.28	11.83	3.04	0.83	2.44	1.14	74.75	1314.4	3.45
R-square		0.91	0.98	0.89	0.83	0.87	0.92	0.81	0.94	0.96
, *- significant at 5% and 1% level respectively, DTF = days to flowering, PHT = plant height, DTM = days to maturity, SG = stay green, PL = panicle length, PW = panicle width, LA = leaf area, PY = panicle yield, GY = grain yield, TSW = thousand seed weight, L = location, CV = coefficient of variation, LSD = least significant difference

Estimation of General Combining Ability (GCA) Effects of Parents

In this study, significant positive and negative GCA effects were observed for some traits (Table-7). This indicated the preponderance of additive gene effects for further improvements of significant traits through critical and intensive selection breeding method. The GCA for the days to flowering was found to be significantly high for line 10 and significant difference was obtained in lines (3, 4, 5 and 13). This indicated the presence of additive genetic variance which controls the days to flowering trait. In areas where drought stress is a problem, negative GCA effects for days to flowering has positive effect through escaping terminal stress. Hence, the genotypes listed as number 3, 4 and 13 are suggested to be used for breeding for early maturity. The other rest lines and the two testers revealed non-significant for days to flowering of GCA analysis, which implied that either the non-additive gene controlled the trait or it is environmentally influenced.

General combining ability of plant height varied significantly high (p < 0.01) for the parental lines. The GCA of all lines exhibited significantly high except for lines (5, 6 and 7) and the two testers were found non-significant for this trait. For the plant height, negative values of GCA are desirable under moisture stressed environments to hasten physiological maturity. All parental lines showed significant negative GCA effects, except lines (5, 6 and 7) and are considered as good general combiners. For those with significant positive GCA effects of female parents will be selected when the biomass experimental research is needed unless the present study was conducted under moisture stressed areas, thus the focus on selecting short stature sorghum parents, which mature earlier and escape drought stresses and selection breeding method is effective to improve this trait.

GCA analysis revealed non-significant difference among all the parental lines for days to maturity character except line 10 with maximum and significantly high GCA (2.44). However, negative GCA values are desirable for days to maturity. Therefore, highest negative GCA effect (-1.55) was obtained in line 4 followed by line 2 (-1.18) to be considered, even if the values were found non-significant. GCA analysis due to stay green trait was found significantly high in line 2 and 7. This indicated, the additive gene is important for the selection of parental lines in moisture stressed areas. Highly significant of GCA was obtained for the parental lines (4, 10, 11, and 12) for panicle length, but positive GCA (2.29) analysis is desirable for panicle length. Hence, line 4 was identified as good general combiner for panicle length. This result implies the preponderance of additive gene action and the suggested breeding procedure would be population improvement to improve panicle length. The same results were also reported by Tadesse et al., (2008).

Neither additive nor non-additive effects were statistically significant for leaf area and panicle width in the analysis of variance, possibly because they were largely influenced by the environment. The result of GCA analysis was significantly high in lines (3, 6, 9, and 10) and significant in lines (2. 7, 13, 14 and 15) for panicle exersion. This implied predominance of additive gene for the improvement of the trait. Excellent exertion is one of important trait associated with drought tolerance in sorghum which, implies that, the higher exserted parental lines withstand moisture stress environments. The results strongly agreed with the previous work of Kenga et al., (2004), Tadesse et al., (2008).

All the parents were found to be non-significant for grain yield and panicle yield traits, which implied these traits, were governed either by non-additive gene or environmental effects. Thus, the breeding methodologies, which can be applied for the improvement of parental lines could be heterosis breeding since the environment x parental interaction was found non-significant. GCA analysis showed highly significant for thousand seed weight in parental line (6, 10, 12), while significance difference was obtained for parental line (5, 7, 9, 11), although positive GCA is preferable for thousand seed weight. Hence, lines (9, 10, 11, and 12) were identified as good general combiner and this trait was governed by additive gene action. The same result was also reported by Tadesse et al.(2008).

Table 7

General combining ability (GCA) effect of parents for yield and yield related traits in sorghum at Mieso and Kobo during 2019 cropping season
Traits
Lines	DTF	PH	DM	SG	PL	PW	LA	PE	PY	GY	TSW
1	0.51^ns	-22.08^**	0.07^ns	-0.17^ns	0.89^ns	-0.07^ns	10.64^ns	-1.33^ns	0.83^ns	562.5^ns	0.44^ns
2	-0.60^ns	-27.48^**	-1.18^ns	0.57^**	0.54^ns	-0.52^ns	2.07^ns	-1.53^*	-3.34^ns	-165.0^ns	-1.47^ns
3	-1.23^*	-30.93^**	-0.80^ns	0.32^ns	-0.01^ns	-0.75^ns	26.35^ns	1.81^**	-6.59^ns	-216.5^ns	-2.27^ns
4	-1.23^*	-28.83^**	-1.55^ns	-0.42^*	2.29^**	0.05^ns	-22.62^ns	-0.98^ns	3.75^ns	492.5^ns	1.60^ns
5	1.26^*	-5.63^ns	0.31^ns	-0.17^ns	0.91^ns	0.09^ns	16.54^ns	-0.80^ns	-11.49^ns	-473.0^ns	-3.09^*
6	0.02^ns	-12.38^ns	0.81^ns	-0.04^ns	0.69^ns	0.37^ns	5.85^ns	4.24^**	-17.49^ns	277.5^ns	-4.43^**
7	-0.48^ns	-16.33^ns	-0.68^ns	0.57^**	1.41^ns	-0.27^ns	-17.99^ns	-1.68^*	-10.76^ns	-14.5^ns	-3.45^*
8	0.02^ns	-24.13^**	0.31^ns	0.07^ns	0.49^ns	-0.20^ns	-5.62^ns	-0.38^ns	18.25^ns	258.0^ns	-1.29^ns
9	-0.35^ns	48.07^**	-0.68^ns	0.07^ns	-0.16^ns	0.47^ns	-3.99^ns	2.46^**	8.25^ns	400.5^ns	3.34^*
10	2.02^**	56.22^**	2.44^**	-0.29^ns	-2.51^**	0.64^ns	-23.41^ns	-2.40^**	0.78^ns	-681.0^ns	4.01^**
11	0.39^ns	38.56^**	0.81^ns	-0.17^ns	-2.63^**	0.29^ns	-25.43^ns	-0.06^ns	1.70^ns	-480.5^ns	3.34^*
12	0.89^ns	42.06^**	0.94^ns	-0.42^ns	-2.35^**	0.04^ns	19.94^ns	-0.88^ns	10.30^ns	-318.5^ns	4.65^**
13	-1.23^*	-17.13^**	-0.80^ns	0.07^ns	0.44^ns	-0.15^ns	17.68^ns	1.56^*	5.78^ns	358.0^ns	-1.35^ns
SE (Lines)	0.53	8.04	0.87	0.19	0.80	0.39	20.52	0.65	11.69	412.527	1.45
Testers
14	0.18^ns	2.34^ns	0.07^ns	0.05^ns	0.15^ns	-0.06^ns	-13.21^ns	-0.10^*	-0.75^ns	55.34^ns	-0.35^ns
15	-0.18^ns	2.34^ns	0.07^ns	-0.05^ns	0.15^ns	0.06^ns	13.21^ns	0.10^*	0.75^ns	-55.34^ns	0.35^ns
SE(Testers)	0.25	0.77	0.25	0.04	0.11	0.01	5.94	0.02	1.13	76.49	0.31
, *- significant at 5% and 1% level respectively, DTF = days to flowering, PHT = plant height, DTM = days to maturity, SG = stay green, PL = panicle length, PW = panicle width, LA = leaf area, PE = panicle exertion PY = panicle yield, GY = grain yield, TSW = thousand seed weight, L = location, CV = coefficient of variation, LSD = least significant difference

Estimation of Specific Combining Ability (SCA) Effects of Hybrids

The specific combining ability value of any cross is useful in predicting the performance of the better parents. The result of SCA effects of crosses across the two environments for the different traits is presented in (Table-8). The usefulness of a particular cross in the exploitation of heterosis is judged by specific combining ability effects. The result for SCA estimates detected both negative and positive SCA values for the lines crossed with the two testers with equal SCA values in magnitude and opposite in direction, but varied among the traits under study. This may be due to the two testers, which had equal combining ability in magnitude, but opposite in direction and the possible explanation is that both testers used in the hybrid may have the same gene controlling effect on the traits. Similar result was reported in case of sorghum using 35 male line and two female lines as of the SCA effects was equal in magnitude but opposite in sign (Kidanemariam Wagaw et al., 2020) and in the case of maize using 16 female lines and 2 male lines (Ejigu et al.,2017).

Hybrids evaluated in this study revealed considerable variation in specific combining ability (SCA) effects for the traits studied. It was observed that some crosses involved good general combined parents which can produced hybrids, with poor specific combining ability for a given trait example yield. This indicated that, parents with high GCA effects might not always give hybrids with high SCA effects. The possible explanation is that both testers used in the hybrid may have the same gene controlling effect to the trait(s) studied and hybrids were not able to take advantage of any additive gene action. Regarding days to flowering only two hybrid combinations were highly significant at (p < 0.01), while four hybrids were significant at (p < 0.05) probability level. For days to flowering, negative values of SCA is desirable. But, among the significant hybrids for SCA effects, only three (1 x 15, 8 x 14 and 10 x 15) hybrids showed significant negative SCA effects for earliness and the rest were positive combiner for this trait. Some female lines manifested significant negative GCA for this trait. Therefore, days to flowering was controlled by both additive and non-additive gene action and it is possible to look for both selection and heterosis breeding to improve the genetic materials for this trait. In conclusion, both additive and dominance variance are important under drought stress. Therefore, both selection and hybridization would be effective for improving drought tolerance under drought stress conditions.

Out of the 26 hybrids, only two hybrids (11x14, 11x15) showed significant SCA effect for plant height. For plant height, negative values of SCA are desirable. However, only one hybrid (11x15) showed significant negative SCA effects for dwarfness. As indicated in the Table-7 of the general combining ability, the combining ability effect was due to additive genetic effects. This implies that, GCA effects were more important than specific combining ability. Therefore, selection is the most effective breeding procedure to improve plant height. Girma et al., (2010) reported similar result for plant height. About eight hybrids revealed significance for days to maturity. However, negative SCA values are desirable for this trait. But only four hybrids showed significant negative SCA (1x15, 6x15, 10x15, and 13x15) effects for earliness. SCA effects had a slightly higher influence than GCA as observed from both tables of GCA and SCA, and heterosis breeding is effective to improve days to maturity.

The estimates of SCA for stay green were found non-significant (P ≤ 0.05) for all crosses. Hence, this trait was controlled by additive gene action, GCA effects had higher influence than SCA as observed from the table of GCA and selection is effective population improvement for stay green trait. In conclusion, additive variance is important under drought stress. Therefore, selection would be effective for improving drought tolerance under drought stress conditions.SCA analysis of showed high significant in four hybrids, whereas it was significant in four hybrids for panicle length. But only four hybrids had positive desirable SCA for panicle length and these hybrids were identified as good specific combiners. SCA analysis revealed the panicle width was totally controlled by non-additive gene effects, which implied that, the breeding procedure would be heterosis breeding to improve this trait.

SCA analysis of some hybrids was found highly significant for thousand seed weight and panicle exersion. However, the present study revealed the preponderance of additive gene action rather than non-additive gene action, which implied the GCA, was more important as compared to SCA. Similar results were reported for thousand seed weight by Girma et al., (2010). None of the crosses had significant SCA effects for leaf area. The environmental effects could have played a major role on leaf area, as neither the additive nor the non-additive effects were significant. The SCA for grain yield was higher than that of GCA, because grain yield is a complex trait which results from the contribution of many grain yield components each adding varying levels of genetic effects (Umakanth et al., 2005). This study revealed highest and positive significant SCA for yield in hybrid (4x14) and followed by some other cross combinations like 8x15 and 11x14 as presented in Table-8. It is evident that cross combinations, which expressed high SCA effects for grain yield, have invariable positive SCA effects for one or more yield related traits. Secondly to get best specific combination for yield, it would be important to give due attention to yield related traits. Grafius (1959) has already suggested that there may not be separated gene(s) for yield and yield related being end product of multiple gene interactions among various yield components.

Table 8

Specific Combining Ability (SCA) effects for line x tester interaction in sorghum at Mieso and Kobo during 2019 cropping season
Line	Tester	DTF	PHT	DMT	SG	PL	PW	LA	PE	PY	GY	TSW
1	14	0.69^*	-1.09^ns	1.18^*	0.32^ns	-1.24^**	-0.79^**	2.52^ns	-1.20^ns	-5.49^ns	-331.34^ns	-2.03^**
1	15	-0.69^*	1.096^ns	-1.18^*	-0.32^ns	1.24^**	0.79^**	-2.52^ns	1.20^ns	5.49^ns	331.34^ns	2.03^**
2	14	0.31^ns	-4.29^ns	0.43^ns	-0.17^ns	1.01^*	0.20^ns	21.86^ns	0.19^ns	-8.67^ns	40.15^ns	-0.49^ns
2	15	-0.31^ns	4.29^ns	-0.43^ns	0.17^ns	-1.01^*	-0.20^ns	-21.86^ns	-0.19^ns	8.67^ns	-40.15^ns	0.49^ns
3	14	-0.30^ns	-5.84^ns	-0.19^ns	0.33^ns	-0.05^ns	0.58^**	6.09^ns	-2.70^**	5.27^ns	5.65^ns	1.83^*
3	15	0.30^ns	5.84^ns	0.19^ns	-0.33^ns	0.05^ns	-0.58^**	-6.09^ns	2.70^**	-5.27^ns	-5.65^ns	-1.83^*
4	14	-0.31^ns	1.55^ns	-0.44^ns	-0.17^ns	0.65^ns	0.78^**	6.83^ns	0.54^ns	15.97^**	727.65^**	1.21^ns
4	15	0.31^ns	-1.55^ns	0.44^ns	0.17^ns	-0.65^ns	-0.78^**	-6.83^ns	-0.54^ns	-15.97^**	-727.65^**	-1.21^ns
5	14	0.44^ns	-5.44^ns	-0.06^ns	0.08^ns	0.23^ns	-0.06^ns	16.29^ns	0.92^ns	-9.42^ns	-428.84^ns	-1.14^ns
5	15	-0.44^ns	5.44^ns	0.06^ns	-0.08^ns	-0.23^ns	0.06^ns	-16.29^ns	-0.92^ns	9.42^ns	428.84^ns	1.14^ns
6	14	0.44^ns	-3.49^ns	1.18^*	-0.29^ns	-0.14^ns	-0.59^**	10.60^ns	-1.02^ns	0.37^ns	-310.34^ns	0.17^ns
6	15	-0.44^ns	3.49^ns	-1.18^*	0.29^ns	0.14^ns	0.59^**	-10.60^ns	1.02^ns	-0.37^ns	310.34^ns	-0.17^ns
7	14	0.19^ns	5.65^ns	-0.06^ns	0.07^ns	-0.37^ns	-0.34^ns	-2.74^ns	0.74^ns	-5.84^ns	163.65^ns	0.19^ns
7	15	-0.19^ns	-5.65^ns	0.06^ns	-0.07^ns	0.37^ns	0.34^ns	2.74^ns	-0.74^ns	5.84^ns	-163.65^ns	-0.19^ns
8	14	-1.06^**	-2.04^ns	-1.06^ns	0.08^ns	-1.59^**	-0.41^*	-6.77^ns	0.64^ns	-6.57^ns	-675.84^**	0.58^ns
8	15	1.06^**	2.04^ns	1.06^ns	-0.08^ns	1.59^**	0.41^*	6.77^ns	-0.64^ns	6.57^ns	675.84^**	-0.58^ns
9	14	-0.18^ns	-3.04^ns	-0.06^ns	-0.17^ns	0.80^ns	0.55^**	18.84^ns	-0.40^ns	3.67^ns	15.65^ns	0.72^ns
9	15	0.18^ns	3.04^ns	0.06^ns	0.17^ns	-0.80^ns	-0.55^**	-18.84^ns	0.40^ns	-3.67^ns	-15.65^ns	-0.72^ns
10	14	0.69^*	3.20^ns	1.30^*	-0.29^ns	0.90^*	0.63^**	-4.37^ns	-0.32^ns	0.75^ns	-163.84^ns	0.92^ns
10	15	-0.69^*	-3.20^ns	-1.30^*	0.29^ns	-0.90^*	-0.63^**	4.37^ns	0.32^ns	-0.75^ns	163.84^ns	-0.92^ns
11	14	-0.43^ns	7.55*	-1.06^ns	0.07^ns	0.22^ns	-0.06^ns	-4.73^ns	1.32^ns	10.07^ns	527.65^*	-0.20^ns
11	15	0.43^ns	-7.55^*	1.06^ns	-0.07^ns	-0.22^ns	0.06^ns	4.73^ns	-1.32^ns	-10.07^ns	-527.65^*	0.20^ns
12	14	0.06^ns	5.45^ns	0.05^ns	0.32^ns	-0.59^ns	-0.41^*	-40.01^ns	0.24^ns	-3.22^ns	104.65^ns	-1.44^ns
12	15	-0.06^ns	-5.45^ns	-0.05^ns	-0.32^ns	0.59^ns	0.41^*	40.01^ns	-0.24^ns	3.22^ns	-104.65^ns	1.44^ns
13	14	-0.55^ns	1.85^ns	-1.19^*	-0.17^ns	0.20^ns	-0.06^ns	8.17^ns	1.04^ns	3.10^ns	325.15^ns	-0.32^ns
13	15	0.55^ns	-1.85^ns	1.19*	-0.17^ns	-0.20^ns	0.06^ns	-8.17^ns	-1.04^ns	-3.10^ns	-325.15^ns	0.32^ns
SE(ij)		0.31	3.59	0.58	0.18	0.45	0.19	20.13	0.95	5.98	263.22	0.78
, *- significant at 5% and 1% level respectively, DTF = days to flowering, PHT = plant height, DMT = days to maturity, SG = stay green, PL = panicle length, PW = panicle width, LA = leaf area PE = panicle exersion, PY = panicle yield, GY = grain yield, TSW = thousand seed weight, SE = standard error.

Magnitude of Heterosis for the Combined Analysis over Locations

The existence of heterosis demonstrates the presence of degree of genetic variation between parents and some degree of dominance. The heterosis over mid parent (Relative heterosis), over better parent (heterobeltiosis) and over standard check (standard heterosis/useful heterosis) were estimated for all the traits studied. Among the parents, testers were greater than inbred line in mean values whereas inbred lines showed the presence of genetic diversity than testers. All of the hybrids manifested significant positive heterosis over mid parents for grain yield, while 25 and 18 hybrids recorded significant positive heterosis over the better parent and the standard check for grain yield respectively. Similar work was reported by Kumar, (2013). This result demonstrated the superiority of hybrids over their respective parents and the commercial hybrid variety under cultivation. Eleven and three hybrids showed significant negative heterosis over mid parents and better parents for days to flowering respectively. Since negative heterosis is desirable for days to flowering, those hybrids with negative heterosis were selected to enhance earliness and escape the erratic and terminal drought which affects the hybrid production under moisture stress areas.

Sixteen, seven and twenty hybrids manifested significant positive heterosis for thousand seed weight over mid parents, better parents and standard check respectively. This indicates that, the large seeds in weight were vigorous and good in germination as compared to those seeds with small in weight. As far as heterotic performance for stay green is concerned, seventeen, twenty two and twenty six hybrids exhibited significant and positive heterosis in desirable direction over mid parents, better parents and standard hybrid check variety respectively. This result implied that, hybrids exhibited superiority in terms tolerance or resistance, where drought adversely affects crop growth and production over their parents and standard check. Most of the hybrids exhibited significantly high heterosis over their parents and standard check for panicle exersion trait, which is associated with drought tolerance in sorghum.

Table 9

Mean, range and number of hybrids with positive effect for mid-parent, high parent and standard heterosis (%)at Mieso and Kobo during 2019 cropping season
MPH (%)					BPH (%)				SH (%)
Traits	Mean	Max	Min	#of Hybrids with Positive effects	Mean	Max	Min	#of Hybrids with Positive effects	Mean	Max	Min	#of Hybrids with Positive effects	#of Hybrids with Positive effects
DTF*	-2.91	1.07	-6.06	25	-0.61	3.69	-4.99	14	3.47	7.38	0.54	0	25
PHT*	34.74	50.95	22.48	0	51.83	77.70	32.66	0	66.37	114.80	39.46	0	0
DTM*	-2.29	1.68	-4.54	25	-1.69	3.07	-4.44	24	-2.95	-0.12	-5.23	26	25
GY	53.27	112.41	6.26	26	31.70	68.71	-0.23	25	5.81	30.71	-16.4	18	26
TSW	4.78	23.95	-7.48	16	-10.02	12.33	-26.21	7	10.60	35.95	-7.82	20	16
PL	11.43	26.04	-1.70	25	10.00	100.39	-7.05	21	-12.22	-2.39	-23.23	0	25
PW	13.79	36.88	1.58	26	2.87	19.88	-12.43	15	25.58	39.86	9.65	26	26
LL*	4.33	16.01	-5.14	20	8.08	29.90	-1.77	23	-8.29	-2.11	-17.77	26	20
LW*	5.93	17.24	-5.18	22	12.58	31.58	-3.47	23	2.13	17.24	-7.86	13	22
LA*	10.82	34.99	0.01	0	22.39	71.99	3.32	0	-5.16	15.76	-17.91	5	0
LN	3.04	66.23	-10.50	16	8.37	66.86	-9.56	22	5.13	75.47	-11.29	17	16
TL*	26.38	119.45	-43.09	4	78.80	210.89	-39.64	2	-28.37	24.34	-65.66	24	4
SG	10.05	51.50	-23.05	17	23.45	142.40	-19.20	22	60.13	104.57	15.43	26	17
PE	45.98	152.56	-28.85	23	-8.17	40.17	-53.67	11	-9.40	47.50	-41.14	6	23
* Those traits which are preferable for the negative effect

Estimation of Magnitude of Heterosis over Locations

Heterosis is the key determinant for hybrid production especially for traits governed by non-additive gene action. Heterosis over the mid parents, better parents and standard check of the hybrids among 13 inbred lines and two testers were summarized in (Table-10). There were genetic variations for levels of heterosis among the parental genotypes and hybrids. The magnitudes of heterosis varied from cross to cross and trait to trait. For a specific trait, considerable high heterotic effects were observed in certain crosses and low in others, which revealed that, the nature of gene action varied with the genetic makeup of parents. The results indicated those both positive and negative heterosis were observed for studied traits. A negative heterosis estimate for days to flowering is desirable which means the crosses flowered earlier than the parents. Eleven crosses were better than the mid-parents while only three crosses surpassed the better- parents for days to flowering with the maximum heterosis of -6.06% for the cross 5x15 and − 4.99% for cross 1x15 respectively. Thus, it appeared that the earliest tester parent (15) has contributed for earliness, in comparison of mid-parent and better parent heterosis. In general, the lowest value of negative heterosis was preferable than higher value of positive heterosis for days to flowering. Similar findings were reported by Mishra et al, (2013).

The use of early maturing sorghum varieties are encouraged to overcome the drastic effect of drought in semi-arid tropics regions where either seasonal rainfall is short or its distribution is erratic. These varieties may not be necessarily superior to long maturing cultivars in terms of yield, but give more stable yield under water stress environments by escaping the terminal drought. The majority of the hybrids exhibited negative significantly high and negative significant heterosis for days to maturity over mid-parents, better parents and standard check. Similar results were reported by Bantilan et al., (2004).For the lowland areas, negative heterosis is desirable for plant height in order to shorten days to flowering and physiological maturity as well as to get lodging free hybrids. As indicated in (table-10) all hybrids exhibited positive and significantly high heterosis over their parents and standard check for plant height. As a result, none of the hybrids are preferable for this trait in moisture stress areas. For both stay green and panicle exertion traits, the development of superior hybrids are very critical to withstand the stress environments were drought is the limiting factor for sorghum production. From the present study, both stay green and panicle exertion found highly significant for all the crosses over the parents and standard check. For stay green, percentage heterosis ranged from − 23.05 to 51.50%,-19.20 to 142.40%and 15.43 to 104.57% over mi-parent, better parent and standard check respectively. From the obtained results, hybrids have more tolerance to abiotic stress and resistance to premature leaf and stalk death induced by post-flowering drought (Crasta et al., 1999). For panicle exertion trait, -28.85 to 152.56%, -53.67 to 40.17% and − 41.14 to 47.50% percentage heterosis were obtained over mi-parent, better parent and standard check respectively and well exserted hybrids are more preferred for drought tolerant trait. Panicle exertion is an important attribute that often determine the quality of the grains. Poor panicle exertion is disadvantageous because the leaf sheath provides favorable conditions for fungi and insects to develop at the base of the panicle and can extend to the whole panicle as also reported by (Dogget, (1988).

The mid-parents heterosis for grain yield ranged from 6.26 to 112.41 (%) across locations with mean value of 53.27%. The better parent heterosis for grain yield ranged from − 0.23 to 68.71% with the mean value of 31.70%, whereas the magnitude of heterosis of the hybrids over the standard check hybrid ranged from − 16.49 to 30.71% with the mean value of 5.81% over the environments. This result implied the highest yield advantages obtained in hybrids over the mid-parents, better parents and commercial hybrid variety (ESH-4). The findings of the present investigation are consistent with the earlier reports of Jain and Patel, (2013). Among the 26 hybrids, 15 potential hybrids get greater than 50% heterosis over mid-parents and 5 hybrids showed greater than 50% heterosis over better parents whereas 15 hybrids displayed positive and significantly high heterosis over the standard check (ESH-4) in desirable direction for grain yield. Among the genotypes, the maximum grain yield was obtained by the hybrid cross of 4 x 14 (6.32 tha^− 1) which recorded 30.71% yield advantage over standard check and promising candidate hybrid was obtained to be released after making critical evaluation of yield stability across location over years. Thus, out of twenty six hybrids, as mentioned in (Table-10), twenty six, twenty five and eighteen hybrids exhibited positive and significantly high heterosis for grain yield over mid-parents, better parents and standard check respectively. From this result, promising hybrids were identified over environments and these can be exploited for heterosis breeding program. A similar result was reported by Kenga et al, (2004).

The mid-parent values ranged between − 6.06 to 1.07% and the better parent heterosis was ranged from − 26.4 to 12.33%, whereas the standard heterosis estimate was between − 7.82 to 35.55% for thousand seed weight. Sixteen crosses exhibited positive heterosis over the mid-parent and seven crosses performed the better than better parents. All hybrids manifested highly significant over standard heterosis and out of this, twenty hybrids showed positive significant heterosis for thousand seed weight. Since the seed weight is strongly influenced by post flowering drought. The large seed size and weight are important indication of vigor and drought tolerance. All of the 26 studied crosses manifested significantly high heterosis over mid-parent, better parent and standard check for panicle length. Twenty five crosses showed positive in desirable direction and the highest mid-parent heterosis for this trait was 26.04% for the cross 8x15. All crosses expressed highly significant better parent heterosis for panicle length and out of all the hybrids, twenty one crosses showed positively highly significant in desirable direction. The highest percent of better parent heterosis was 100.09%, which was manifested by cross 2x15 and all crosses negative in their magnitude over standard check which displayed the mean of crosses were lower than the mean of the standard check for panicle length. But some crosses revealed significantly high and significant in this trait. The present results agreed with the results reported by Rafiq et al., (2003). All the crosses manifested highly significant heterosis over the mi-parents, better parents and standard check with the range of 1.58 to 36.88%, -12.43 to 19.88% and 9.65 to 39.86% of the panicle width respectively.

All of the hybrids showed positive and significantly high heterosis over both standard and mid-parent heterosis which has direct relation with yield and contributed to yield in advance level. However, some hybrids showed negative and highly significant heterosis were observed for better parent heterosis for panicle width, which indicates the mean performance of some hybrids were lower than the particular better parents. Sharma H and Sharma V (2006) reported superiority of hybrids over mid and better parents for grain yield as associated with manifestations of heterotic effects in yield components including panicle length and panicle width. For number of leaves per plant, almost all of the crosses exhibited positive and negative significantly high heterosis over mid-parent, better parent and standard heterosis with the range from − 10.50 to 66.23%, -9.56 to 66.86% and − 11.29 to 75.47% respectively. Significantly high negative heterosis is desirable for number of leaves per plant, which is critical in moisture stress areas by limiting number of leaves per plant. Similar results were obtained by different authors (Liang et al., 1973, Harer and Bapat, 1982).

For leaf length, leaf width and leaf area traits, all crosses exhibited non-significant heterosis over the mid parent, better parent and standard check. All the hybrids appeared positive in their mean over the above mentioned heterosis but significantly high negative heterosis is desirable for leaf length, leaf width and leaf area to reduce transpiration effects in moisture stress areas. All of the hybrids revealed non-significant heterosis was over mid-parent and better parent for number of productive tillers, while the highest negative significant standard heterosis expressed in the crosses 2x14, 3x14, 3x15, 8x15, and 9x15.

In sorghum, productive tillers contribute to overall grain yield when water supply is not limiting but profuse tillering is undesirable in dry lowland agro-ecologies, because would it reduce water use efficiency as also reported by Rajendrakumar et al, (2013).The detailed analysis for heterosis regarding of mid-parents, better parents and standard heterosis were presented in (Table-10). In general, lower value negative heterosis was preferable than higher value of positive heterosis for days to flowering, plant height, days to maturity, leaf length, leaf width, leaf area and number of tillers. In another way, higher value of positive heterosis was preferable for the rest of the traits such as grain yield, panicle yield, thousand seed weight, panicle length, panicle width, stay green and panicle exertion traits.

Table 10

Mid-parent heterosis, Heterobeltiosis and Standard heterosis for yield and yield component trait of sorghum across location at Mieso and Kobo during 2019 cropping season
Traits DTF				PHT			DTM			SG			GY
Hybrid	MPH (%)	BPH (%)	SH (%)	MPH (%)	BPH (%)	SH (%)	MPH (%)	BPH (%)	SH (%)	MPH (%)	BPH (%)	SH (%)	MPH (%)	BPH (%)	SH (%)
1X14	-2.55^ns	-2.39^ns	5.87^ns	27.37^ns	44.25^ns	50.92^ns	-1.11^ns	-0.88^ns	-1.33^ns	8.36^**	16.00^**	70.29^**	54.32^**	29.13^**	11.59^**
2X14	-1.05^ns	2.92^ns	3.68^ns	28.99^ns	58.96^ns	43.63^ns	-2.72^*	-2.83^ns	-3.26^*	31.20^**	31.20^**	87.43^**	55.52^**	21.83^**	5.28^**
3X14	-2.18^ns	2.33^ns	1.96^ns	22.48^ns	46.22^ns	39.46^ns	-2.43^ns	-1.77^ns	-3.51^*	43.20^**	43.20^**	104.57^**	43.56^**	20.97^**	4.54^**
4X14	-5.54^**	-3.72^*	0.88^ns	22.67^ns	37.76^ns	46.33^ns	-4.54^**	-4.44^*	-5.07^**	-20.36^**	-10.33^**	25.14^**	74.65^**	51.26^**	30.71^**
5X14	-4.83^**	-2.79^ns	5.66^ns	26.68^ns	33.76^ns	59.24^ns	-3.51^*	-2.65^ns	-3.08^*	26.59^**	53.71^**	53.71^**	31.49^**	-0.23^**	-13.78^**
6X14	-3.00^ns	-1.83^ns	4.31^ns	31.67^ns	48.12^ns	56.85^ns	-0.79^ns	-0.35^ns	-0.79^ns	-9.33^**	-4.80^**	36.00^**	55.02^**	19.74^**	3.48^**
7X14	-3.38^*	-1.87^ns	3.54^ns	41.27^ns	68.65^ns	60.85^ns	-3.14^*	-2.71^ns	-3.14^*	25.82^**	38.40^**	97.71^**	60.86^**	26.55^**	9.36^**
8X14	-4.45^**	-2.61^ns	2.04^ns	35.34^ns	72.23^ns	47.53^ns	-2.71^*	-2.17^ns	-3.68^*	-0.33^**	19.60^**	70.86^**	51.13^**	13.17^**	-2.20^**
9X14	-0.95^ns	3.62^ns	3.24^ns	32.40^ns	40.79^ns	104.14^ns	-1.60^ns	-0.02^ns	-3.56^*	51.47^**	127.20^**	62.29^**	46.94^**	36.36^**	17.84^**
10X14	1.07^ns	3.57^ns	7.38^ns	30.86^ns	42.08^ns	114.80^ns	1.68^ns	3.07^ns	-0.12^ns	-7.60^**	-7.60^**	32.00^**	20.66^**	4.30^**	-9.86^**
11X14	-3.75^*	-2.42^ns	3.32^ns	24.92^ns	54.62^ns	104.65^ns	-2.75^*	-2.43^ns	-3.50^*	10.40^**	10.40^**	57.71^**	27.38^**	24.63^**	7.70^**
12X14	-2.09^ns	-0.90^ns	5.29^ns	30.14^ns	56.23^ns	106.76^ns	-1.16^ns	-0.94^ns	-1.81^ns	10.00^**	10.00^**	57.14^**	33.26^**	18.50^**	2.41^**
13X14	-3.70^*	0.54^ns	0.54^ns	30.19^ns	46.03^ns	47.32^ns	-4.06^**	-3.30^*	-5.23^**	15.37^**	21.78^**	56.57^**	60.80^**	39.57^**	20.61^**
1X15	-4.99^**	-4.99^*	3.04^ns	37.77^ns	40.81^ns	47.39^ns	-4.16^**	-4.05^*	-4.27^**	-17.91^**	-14.18^**	34.86^**	89.43^**	68.71^**	25.71^**
2X15	-2.31^ns	1.43^ns	2.18^ns	47.69^ns	63.12^ns	44.36^ns	-3.47^*	-3.25^*	-3.89^*	31.43^**	38.00^**	97.14^**	61.20^**	33.58^**	-0.47^**
3X15	-2.57^ns	1.74^ns	1.37^ns	41.10^ns	51.35^ns	40.90^ns	-2.95^*	-2.18^ns	-3.91^*	3.24^**	8.40^**	54.86^**	47.54^**	32.40^**	-1.35^**
4X15	-4.55^**	-2.88^ns	1.76^ns	30.79^ns	32.66^ns	64.69^ns	-3.48^*	-3.26^*	-3.90^*	-14.43^**	-10.55^**	40.57^**	43.20^**	32.39^**	-1.35^**
5X15	-6.06^**	-3.99^*	4.13^ns	44.29^ns	38.35^ns	57.91^ns	-3.30^*	-2.55^ns	-2.76^ns	8.89^**	40.00^**	40.00^**	71.48^**	37.21^**	2.24^**
6X15	-4.10^*	-3.10^ns	2.96^ns	46.80^ns	49.12^ns	47.64^ns	-3.22^*	-2.90^ns	-3.12^*	11.27^**	11.27^**	74.86^**	94.85^**	58.99^**	18.47^**
7X15	-4.33^*	-3.00^ns	2.35^ns	44.31^ns	54.80^ns	47.10^ns	-3.47^*	-3.15^*	-3.36^*	13.04^**	16.67^**	85.71^**	62.56^**	35.33^**	0.84^**
8X15	-1.67^ns	0.06^ns	4.84^ns	50.95^ns	71.73^ns	105.94^ns	-0.93^ns	-0.26^ns	-1.81^ns	-11.04^**	1.09^**	58.86^**	112.41^**	67.50^**	24.81^**
9X15	-0.71^ns	3.69^ns	3.31^ns	44.39^ns	54.94^ns	107.24^ns	-1.40^ns	0.29^ns	-3.26^*	51.50^**	142.40^**	73.14^**	53.05^**	52.50^**	13.63^**
10X15	-0.51^ns	1.79^ns	5.53^ns	35.81^ns	50.01^ns	89.63^ns	-0.13^ns	1.35^ns	-1.79^ns	7.05^**	12.40^**	60.57^**	38.61^**	27.90^**	-4.70^**
11X15	-2.52^ns	-1.33^ns	4.47^ns	24.53^ns	73.58^ns	94.12^ns	-0.62^ns	-0.18^ns	-1.28^ns	-4.76^**	0.01^**	42.86^**	6.26^**	1.01^**	-16.49^**
12X15	-2.59^ns	-1.58^ns	4.57^ns	31.76^ns	77.70^ns	48.81^ns	-1.57^ns	-1.24^ns	-2.12^ns	-23.05^**	-19.20^**	15.43^**	35.79^**	29.20^**	-3.73^**
13X15	-2.26^ns	1.87^ns	1.87^ns	37.98^ns	39.79^ns	47.32^ns	-2.06^ns	-1.17^ns	-3.14^*	21.20^**	34.67^**	73.14^**	52.99^**	41.79^**	5.65^**

TSW				TL			PL			LN			PW
Hybrid	MPH (%)	BPH (%)	SH (%)	MPH (%)	BPH (%)	SH (%)	MPH (%)	BPH (%)	SH (%)	MPH (%)	BPH (%)	SH (%)	MPH (%)	BPH (%)	SH (%)
1X14	-3.72^ns	-18.17^*	2.22^**	18.84^ns	27.03^ns	-36.48^ns	6.23^**	1.75^**	-13.30^ns	2.43^**	2.79^**	10.40^**	1.89^**	-12.43^**	14.89^**
2X14	-0.06^*	-19.31^ns	0.79^**	-43.09^ns	-39.64^ns	-65.66^*	14.20^**	8.49^**	-7.56^**	-3.99^**	3.24^**	-3.64^**	1.58^**	-9.41^**	18.87^**
3X14	1.51^*	-14.58^*	6.71^**	-35.27^ns	-24.48^ns	-57.03^*	4.74^**	2.81^**	-12.41^ns	-7.85^**	4.18^**	-11.29^**	1.77^**	-10.05^**	18.01^**
4X14	11.11^**	-2.92^**	21.27^**	0.52^ns	7.45^ns	-46.28^ns	12.68^**	10.87^**	-2.39^**	0.39^**	4.09^**	4.09^**	24.03^**	6.59^**	39.86^**
5X14	-4.06^ns	-25.32^ns	-6.71^**	5.85^ns	45.94^ns	-16.97^ns	12.08^**	8.25^**	-7.77^**	0.08^**	2.61^**	4.89^**	7.54^**	-2.05^**	28.51^**
6X14	-5.59^ns	-26.21^ns	-7.82^**	4.91^ns	54.18^ns	-12.28^ns	17.73^**	5.33^**	-10.25^*	5.14^**	13.05^**	5.51^**	20.39^**	-0.43^**	30.64^**
7X14	-4.59^ns	-23.38^ns	-4.29^**	5.70^ns	5.70^ns	-39.86^ns	15.27^**	6.77^**	-9.03^*	-2.61^**	0.62^**	1.33^**	6.37^**	-8.86^**	19.57^**
8X14	8.39^**	-14.64^*	6.63^**	58.04^ns	87.67^ns	-22.34^ns	8.63^**	-0.14^**	-14.92^ns	-2.21^**	0.26^**	2.49^**	5.38^**	-11.14^**	16.60^**
9X14	6.73^**	0.03^**	24.96^**	10.77^ns	12.50^ns	-37.93^ns	14.09^**	5.58^**	-10.04^*	3.97^**	17.54^**	0.09^**	15.82^**	1.73^**	33.48^**
10X14	13.97^**	3.65^**	29.48^**	60.57^ns	70.30^ns	-3.10^ns	2.07^**	-1.51^**	-16.08^ns	11.30^**	17.22^**	13.78^**	16.07^**	5.41^**	38.30^**
11X14	7.48^**	-2.13^**	22.26^**	47.18^ns	118.55^ns	24.34^ns	2.64^**	-4.39^**	-18.54^ns	3.23^**	4.68^**	9.33^**	7.31^**	-3.14^**	27.09^**
12X14	8.96^**	-2.64^**	21.63^**	74.54^ns	87.76^ns	6.83^ns	3.38^**	-7.05^**	-20.81^ns	-0.71^**	0.34^**	5.51^**	2.41^**	-8.11^**	20.57^**
13X14	-7.48^ns	-17.15^*	3.49^**	32.11^ns	52.12^ns	-13.45^ns	4.72^**	2.95^**	-9.21^*	7.18^**	18.85^**	4.80^**	6.75^**	-7.68^**	21.13^**
1X15	16.92^**	0.69^**	21.87^**	32.26^ns	72.67^ns	-46.41^ns	21.04^**	20.50^**	-6.19^**	-10.50^**	-9.56^**	-4.18^**	23.95^**	13.17^**	29.22^**
2X15	8.61^**	-11.25^**	7.42^**	33.96^ns	104.67^ns	-36.48^ns	11.25^**	100.39^**	-14.53^ns	-1.43^**	5.24^**	-1.78^**	10.98^**	5.47^**	20.43^**
3X15	-6.46^ns	-20.26^ns	-3.49^**	-12.52^ns	50.67^ns	-53.24^*	10.60^**	7.65^**	-12.05^ns	3.81^**	16.49^**	-0.80^**	2.05^**	-3.98^**	9.65^**
4X15	5.98^**	-6.13^**	13.61^**	23.23^ns	60.89^ns	-50.07^ns	11.78^**	5.44^**	-7.77^**	0.56^**	3.56^**	3.56^**	14.42^**	4.47^**	19.29^**
5X15	9.81^**	-13.54^*	4.64^**	42.21^ns	200.22^ns	-6.83ns	14.65^**	13.32^**	-10.37^*	1.45^**	3.30^**	5.60^**	19.36^**	16.02^**	32.48^**
6X15	-2.63^ns	-23.02^ns	-6.83^**	26.63^ns	188.44^ns	-10.48^ns	24.06^**	16.23^**	-10.52^*	-6.69^**	-0.38^**	-7.02^**	36.88^**	19.88^**	36.88^**
7X15	-1.17^ns	-19.67^ns	-2.78^**	119.45^ns	210.89^ns	-3.52^ns	23.64^**	20.16^**	-7.50^**	-3.66^**	-1.15^**	-0.44^**	23.55^**	12.42^**	28.37^**
8X15	8.40^**	-13.64^*	4.52^**	19.05^ns	38.89^ns	-56.90^*	26.04^**	21.51^**	-6.46^**	-9.65^**	-8.00^**	-5.96^**	25.14^**	11.93^**	27.80^**
9X15	5.81^**	0.66^**	21.83^**	-0.32^ns	38.44^ns	-57.03^*	12.48^**	9.20^**	-15.93^ns	10.88^**	24.43^**	5.96^**	16.01^**	8.45^**	23.83^**
10X15	10.80^**	2.23^**	23.73^**	81.53^ns	177.33^ns	-13.93^ns	-1.70^**	-3.09^**	-23.23^ns	7.62^**	12.55^**	9.24^**	11.54^**	8.07^**	23.40^**
11X15	12.69^**	4.10^**	25.99^**	20.48^ns	177.78^ns	-13.79^ns	4.59^**	2.25^**	-21.29^ns	3.17^**	3.91^**	8.53^**	19.87^**	15.40^**	31.77^**
12X15	23.95^**	12.33^**	35.95^**	17.71^ns	83.11^ns	-43.17^ns	12.99^**	6.41^**	-18.09^ns	66.23^**	66.86^**	75.47^**	20.91^**	15.65^**	32.06^**
13X15	-1.19^ns	-10.26^**	8.61^**	41.51^ns	139.78^ns	-25.59^ns	7.19^**	0.37^**	-11.48^*	0.82^**	10.99^**	-2.13^**	16.62^**	7.20^**	22.41^**

LL				LW			LA			PE
Hybrid	MPH (%)	BPH (%)	SH (%)	MPH (%)	BPH (%)	SH (%)	MPH (%)	BPH (%)	SH (%)	MPH (%)	BPH (%)	SH (%)
1X14	8.41^ns	8.66^ns	-2.54^ns	6.91^ns	17.33^ns	-2.90^ns	16.34^ns	25.93^ns	-4.65^ns	5.71^**	-6.67^**	-41.14^**
2X14	3.11^ns	4.23^ns	-8.53^ns	12.51^ns	18.31^ns	6.07^ns	16.77^ns	22.97^ns	-1.94^ns	-15.54^**	-40.76^*	-28.98^**
3X14	-0.32^ns	2.09^ns	-8.38^ns	6.38^ns	6.90^ns	5.79^ns	9.34^ns	12.67^ns	0.27^ns	-28.85^**	-53.67^ns	-26.02^**
4X14	4.42^ns	5.98^ns	-7.75^ns	0.89^ns	7.58^ns	-6.07^ns	4.82^ns	12.66^ns	-13.56^ns	57.23^**	35.73^**	-9.77^**
5X14	10.08^ns	20.91^ns	-9.42^ns	9.13^ns	18.91^ns	-0.28^ns	20.48^ns	44.75^ns	-8.98^ns	45.75^**	14.73^**	-3.52^**
6X14	4.78^ns	7.87^ns	-8.68^ns	11.11^ns	17.60^ns	4.14^ns	18.19^ns	28.36^ns	-3.40^ns	52.67^**	6.51^**	30.11^**
7X14	5.54^ns	13.05^ns	-11.27^ns	2.43^ns	8.41^ns	-4.00^ns	8.97^ns	24.03^ns	-14.29^ns	41.33^**	25.27^**	-21.70^**
8X14	2.21^ns	8.78^ns	-13.58^*	3.47^ns	7.35^ns	-1.24^ns	8.01^ns	18.60^ns	-12.53^ns	62.96^**	40.17^**	-6.02^**
9X14	9.71^ns	11.90^ns	-3.52^ns	-1.38^ns	-0.27^ns	-1.38^ns	8.29^ns	8.95^ns	-5.06^ns	2.41^**	-33.68^*	8.52^**
10X14	-0.73^ns	1.98^ns	-13.30^*	0.81^ns	6.70^ns	-5.52^ns	0.32^ns	8.32^ns	-17.60^ns	-15.63^**	-35.68^*	-40.80^**
11X14	-5.14^ns	-1.77^ns	-17.77^**	5.63^ns	12.64^ns	-1.66^ns	1.09^ns	10.62^ns	-17.91^ns	17.61^**	-19.74^**	6.25^**
12X14	5.07^ns	7.24^ns	-7.68^ns	-5.18^ns	-3.47^ns	-7.86^ns	0.06^ns	3.32^ns	-14.44^ns	1.34^**	-27.58^**	-18.52^**
13X14	6.90^ns	8.51^ns	-2.44^ns	-2.50^ns	-1.93^ns	-3.03^ns	8.03^ns	10.46^ns	-2.05^ns	43.84^**	0.09^**	23.41^**
1X15	6.32^ns	7.93^ns	-2.71^ns	9.72^ns	24.17^ns	2.76^ns	15.86^ns	32.41^ns	0.25^ns	152.56^**	37.66^**	-13.18^**
2X15	3.86^ns	6.88^ns	-6.21^ns	1.42^ns	9.85^ns	-1.52^ns	5.80^ns	17.48^ns	-6.32^ns	13.12^**	-40.76^*	-28.98^**
3X15	1.50^ns	2.21^ns	-5.08^ns	4.11^ns	6.48^ns	6.48^ns	8.28^ns	9.50^ns	4.24^ns	78.42^**	-7.62^**	47.50^**
4X15	3.70^ns	7.16^ns	-6.72^ns	-0.36^ns	9.48^ns	-4.41^ns	3.96^ns	17.93^ns	-9.52^ns	110.71^**	14.36^**	-23.98^**
5X15	16.01^ns	29.90^ns	-2.68^ns	17.13^ns	31.58^ns	10.34^ns	34.99^ns	71.99^ns	8.14^ns	68.35^**	-10.14^**	-24.43^**
6X15	2.10^ns	7.05^ns	-9.38^ns	10.71^ns	20.72^ns	6.90^ns	12.67^ns	29.20^ns	-2.77^ns	130.76^**	20.74^**	47.50^**
7X15	4.56^ns	14.15^ns	-10.42^ns	8.57^ns	18.38^ns	4.83^ns	13.53^ns	36.72^ns	-5.52^ns	85.67^**	1.27^**	-36.70^**
8X15	5.54^ns	14.46^ns	-9.08^ns	9.75^ns	17.24^ns	7.86^ns	15.51^ns	33.98^ns	-1.18^ns	116.88^**	17.63^**	-21.14^**
9X15	-4.08^ns	-0.38^ns	-14.11^*	1.95^ns	3.68^ns	4.83^ns	0.01^ns	5.87^ns	-7.74^ns	42.95^**	-26.04^*	21.02^**
10X15	2.70^ns	7.44^ns	-8.66^ns	3.71^ns	13.08^ns	0.14^ns	7.43^ns	22.46^ns	-6.85^ns	30.93^**	-30.49^*	-36.02^**
11X15	-4.00^ns	1.24^ns	-15.24^*	12.72^ns	23.85^ns	8.14^ns	8.15^ns	25.01^ns	-7.23^ns	9.63^**	-42.83^*	-24.32^**
12X15	9.40^ns	13.71^ns	-2.11^ns	17.24^ns	22.83^ns	17.24^ns	28.51^ns	39.78^ns	15.76^ns	30.77^**	-31.31^**	-22.73^**
13X15	-1.23^ns	-1.23^ns	-8.28^ns	7.22^ns	9.66^ns	9.66^ns	5.81^ns	8.20^ns	0.77^ns	53.83^**	-19.54^**	-0.80^**

Table 11

Good general, specific combiners and heterotic performances for yield and yield related traits at Mieso and Kobo during 2019 cropping season .
Traits	Good general combiners	Good specific combiners		Better crosses
			MPH	BPH	SH
DTF	3, 4 & 13	1x15, 8x14 & 10x15	4x14, 5x14, 8x14, 1x15, 4x15, 5x15	4x14, 1x15, 5x15	-
PTH	1, 2, 3, 4, 8 & 13	11x15	-	-	-
DTM	-	1x15, 6x15, 10x15 & 13x14	4x14, 5x14, 13x14, 1x15, 2x15, 4x15	4x14, 13x14, 1x15, 2x15, 4x15, 7x15	3x14, 4x14, 8x14, 9x14, 13x14, 1x15, 2x15, 3x15
SG	2 & 7	-	All except some crosses	All except some crosses	All crosses
PL	4	1x15, 2x14, 8x15 & 10x14	All except 10x15 crosses	All except some crosses	-
PW		1x15, 3x14, 4x14, 6x15, 8x15, 9x14, 10x14 & 12x15	All crosses	All except some crosses	All crosses
PE	3, 6, 9 & 12	3x15	All except some crosses	All except some crosses	6x14, 9x14, 11x14, 13x14, 3x15, 6x15, 9x15
GY	-	4x14, 8x15 & 11x14	All crosses	All except 5x14 crosses	All except some crosses
TSW	9, 10, 11 & 12	1x15 & 3x14	All except some crosses	9x14, 10x14, 1x15, 9x15, 10x15, 11x15	All except some crosses

Combining ability and heterosis are the most powerful genetic term which used for the selection of suitable parents with high GCA and hybrids with SCA in order to boost productivity. The mean squares due to different sources of variations were estimated over the environments and presented in pooled analysis showed significantly high variability among all the genotypes for different traits. The presence of genetic variation among genotypes implies selection could be effective to improve genotypes for different traits. Potential and promising parents and hybrids were identified based on general and specific combining ability analysis for different traits. The types of genes action involved in the expression of the traits were also identified to formulate and execute an efficient breeding program for achieving maximum genetic gain and improving the studied traits. The general combining ability effects of promising parents based on desirable direction and consistent performance over two environments were identified. For the days to flowering, inbred line 3, 4 and 13 were identified as best general combiners, whereas all inbred lines were identified as best general combiners, except inbred line 5, 6, 7 and the two testers for plant height. This implied the preponderance of additive gene action in the expression of plant height and the selection breeding strategy would be effective to improve the population for this trait.

Inbred lines (2, 4, 7) for stay green, inbred lines (4) for panicle length, inbred line (2, 3, 6, 7, 9, 10, 13, 14 and 15) for panicle exersion, inbred line (9, 10, 11 and 12) for thousand seed weight were identified as best general combiners and the all above mentioned inbred lines for their respective traits were controlled by additive gene actions in which population improvement could be achieved through effective selection. Based on specific combining ability analysis hybrid cross (1x15, 8x14 and 10x15) for days to flowering, (11x15) for plant height, (1x15, 6x15, 10x15 and 13x15) for days to maturity, (1x15, 2x14, 8x15 and 10x14) panicle length,(1x15, 3x14, 4x14, 6x15, 8x15, 9x14, 10x14 and 12x15) for panicle width, (3x15) for panicle exersion, (4x14) for panicle yield, (4x14, 8x15, 11x14) for grain yield, (1x15) for thousand seed weight were identified as best specific combiners. The dominant gene actions were involved in the expression of the traits and heterosis breeding strategy is effective to improve the traits.

The predictability ratio (GCA vs. SCA) over the environments were found to be less than unity for most of the traits (viz., days to 50 percent flowering, days to maturity, stay green, panicle length, panicle width, leaf area, panicle exersion, grain yield and thousand seed weight). This indicates the importance of non-additive gene action in the inheritance of these traits and greater is predictability based on specific combining ability alone for improvement the of respective traits. The predictability ratio GCA vs. SCA was found to be more than unity over the environments for plant height, indicating importance of additive gene action for inheritance of this trait and greater is the predictability based on general combining ability alone for improvement of the respective trait.

This study identified significant and valuable heterobeltiosis, average heterosis and economic heterosis for yield and yield components in sorghum that could be harnessed for improving productivity. The highest yield was obtained from hybrid cross 4x14 (6.32 tha^− 1) followed by hybrid combination 8x15 (5.92 tha^− 1), 1x15 (5.88 tha^− 1), 13x14 (5.78 tha^− 1) and 6x15 (5.57 tha^− 1) with the average value of 5.01 tha^− 1 which had higher mean value than the grand mean of check and mean of parent. The Relative heterosis, heterobeltiosis and useful heterosis were estimated for all the studied traits. Eleven crosses were better than the mid-parents while three crosses surpassed the better- parents for days to flowering with the maximum heterosis of -6.06% for the cross 5x15 and − 4.99% for the cross 1x15 respectively. The above hybrids matured earlier than their parents and are more important under water stress environments by escaping the terminal drought.

Competing interests: The authors declare no competing interests.

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Combining Ability and Heterosis Estimation in Elite Sorghum [Sorghum bicolor (L) Moench] Inbred lines Under Moisture Stress Areas of Ethiopia

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Abstract

1. INTRODUCTION

2. MATERIALS AND METHODS

2.1 Description of the Study Areas

2.2 Plant materials and crosses

2.2 Experimental Design and Trial Management

2.3 Data Collection

2.5 Statistical analysis

2.6 Estimation of Standard Heterosis

3. RESULT AND DISCUSSION

3.1 Analyses of Variance (ANOVA)

3.2 Mean Performance of Sorghum Genotypes for Yield and Yield Related Traits

4. SUMMARY AND CONCLUSIONS

DECLARATION

REFERANCES

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