Archives of Crop Science

ISSN: 2643-5772

Research Article | Volume 6 | Issue 1 | DOI: 10.36959/718/622 Open Access

Performance Evaluation of Sorghum (Sorghum bicolor (L.) Moench) Genotypes for Lowland Areas of Eastern Amhara, Ethiopia

Mulugeta Mamo, Solomon Mitiku, Yemata Beze and Eshetie Wudu

  • Mulugeta Mamo 1*
  • Solomon Mitiku 2
  • Yemata Beze 2
  • Eshetie Wudu 2
  • Sirinka Agricultural Research Center, P.O. box, 74, Sirinka, Ethiopia
  • Sirinka Agricultural Research Center, Ethiopia

Mamo M, Mitiku S, Beze Y, et al. (2023) Performance Evaluation of Sorghum (Sorghum bicolor (L.) Moench) Genotypes for Lowland Areas of Eastern Amhara, Ethiopia. Arch Crop Sci 6(1):206-211

Accepted: March 13, 2023 | Published Online: March 15, 2023

Performance Evaluation of Sorghum (Sorghum bicolor (L.) Moench) Genotypes for Lowland Areas of Eastern Amhara, Ethiopia

Abstract


Sorghum is an important food security crop in Ethiopia. As the grain is preferred for food the biomass is equally important for farmers to use it as animal feed. It is a major crop in lowland parts of eastern Amhara as the environment of the area best fits for the crop. The study was conducted with the objective of identifying high yielder and adaptable sorghum varieties for moisture deficit areas of eastern Amhara region. Eleven sorghum genotypes including two checks were evaluated at eight different environments of four locations namely; Sirinka, Jari, Chefa and Shewarobit within two years in 2016 and 2017 under rain feed condition. The experiment was implemented using a randomized complete block design (RCB) with three replications. The combined analysis of variance over years and across locations revealed highly significant difference (p < 0.01) among genotype for all traits. Genotype × year × environment interaction was non-significant except for plant height. The smallest days to maturity recoded by G8 (125.8 days) while G11 took more number of days to mature (132.9 days). G8 also recorded the highest panicle/head weight (4.56 tonha-1) whereas G11 recorded the lowest head weight (2.7 tonha-1). Genotypes ranged from 2.363 tonha-1 for G11 to 3.95 tonha-1 for G8 in grain yield. As the highest grain yield (3.95 tonha-1) was obtained by genotype G8 (Sima) while that of standard and local checks were 3.1 tonha-1 and 2.67 tonha-1, respectively. Thus, G8 (Sima) was found superior over the rest of the tested sorghum genotypes and it has 47.4% and 27.29% yield advantages over local and standard check, respectively. As a result G8 (Sima) was selected, verified and officially released for its early maturing and high yielding in 2019 by the name of Kalu for production in moisture deficit areas of eastern Amhara region and similar agro ecologies of the country.

Keywords


Sorghum genotypes, Yield, Maturity, Yield components, Moisture deficit

Introduction


Sorghum (Sorghum bicolor (L.) Moench) is a diploid C4 cereal crop which was domesticated in Africa. It has 2n = 20 chromosome and genome size of 750 Mb [1]. Sorghum is predominantly self-pollinated short day plant with the degree of spontaneous cross pollination, in some cases, reaching up to 30%, depending on the shape and type of panicles. The drier areas of the country (occupy 66%) are the major sorghum producing parts of sorghum as the crop also grown in different agro ecological zones of Ethiopia [2]. Thus, the crop grows from the lowland areas which receive lower amount of rainfall and high temperature to the highland characterized by low temperature and higher amount of rainfall [3].

Sorghum is the fifth major cereal crop in the world after rice, wheat, maize and barley grown in arid and semi-arid parts of the world [4] and it is third in Ethiopia which is the most important dry land crop grown by 6 million small holder farmers in more than 1.9 million hectare of land. It annually produced 4.7 million tone and has national average productivity of 2.72 tons per ha [5]. In Amhara region, sorghum covered a significant amount of cultivated land following tef. The area coverage and productivity of sorghum in Amhara region 672,491.78 hectare and 1,781,203.242 ton, respectively [5]. It is a major crop in lowland areas of eastern Amhara as the environment of the area best fits for the crop. It covered an estimated land area of 75802.33, 66550.27 and 35,254.39 in North, South Wollo and Oromia zone, respectively [5].

Sorghum is considered as major food security crop in Ethiopia which is contributing 18% of the total grain production [6,7]. Sorghum in Ethiopian has multiple uses. As the grain is preferred for food the biomass is equally important for farmers to use it as animal feed. Farmers feed their cattle while the plant is at the field and also store the biomass for the drier season. Hence, variety development considered dual purpose interest both grain and biomass yield. Sorghum grain has a wide range of nutritional compositions and constituted about 11% water, 340 KCal of energy, 11.6% protein, 73% carbohydrate and 3% fat by weight [8].

Ethiopia has a wealth of sorghum genetic resources that could be used for increasing productivity and nutritional quality of sorghum. In north east Ethiopia, drought is usually occurring due to delay in onset, dry spell after sowing and drought during critical crop stage (flowering and grain filling stage) and too early cessation of rain. These situations can be overcome by developing sorghum genotypes which are resistance to moisture deficit [9]. Developments of early maturing varieties are the major strategies in the sorghum breeding program. Genotypes specifically developed for the target environment through crossing of elite materials likely to be tested for their suitability to the moisture deficit environments.

Therefore, the objective of this study was to identify high yielder and adaptable sorghum variety for moisture deficit areas of eastern Amhara region.

Material and Methods


Description of test environment

The field trial was conducted during the main cropping season of 2016-2017 at four locations (Sirinka, Jari, Chefa and Shewarobit), representing the moisture deficit lowland areas of eastern Amhara region (Table 1 and Table 2).

Experimental design and trial management

A total of 13 genotypes including one released variety Raya as a standard check and popular local check variety (Jigurity) were evaluated from 2016 to 2017 (Table 3). The experiment was conducted at four locations namely; Sirinka, Jari, Chefa and Shewarobit. Randomized Complete Block Design (RCB) was used to lay down the genotypes with three replications. Each plot contained 5 rows of 5m length separated by 0.75m. The seed rate was 10 kgha-1 while the fertilizer was applied at the recommended rate of 39 kgha-1. Urea and 121 kgha-1 NPS. All the NPS and half of urea were applied during planting while the remained half of urea was applied at knee stage. Sowing was done in between end of June to first week of July when effective rain was received. The seeds were sown by hand in the rows as uniformly as possible and covered with soil manually and population was adjusted by thinning two weeks after emergence considering 0.15 m spacing between plants. Weeding was conducted three times during the growing period in each of the test sites.

Data collection and statistical analysis

All the data were collected from central three rows. Days to heading and days to maturity were taken when 50% of the plants in a plot reached half-bloom stage and 90% of the plants in a plot reached at physiological maturity, respectively. Plant height (cm) was taken from five randomly selected plants from the base of the plant to the tip of the panicle. Head/panicle weight and 1000 seed weight were recorded from each plot while grain yield was taken by adjusting to 12.5% moisture content. Data on phenological parameters, growth parameters, yield and yield components were subjected to analysis of variance (ANOVA). Analyses of variance for collected data were performed using the general statistics (Gen Stat) program version 18. Duncan's Multiple Range Test (DMRT) was used for mean separation.

Results and Discussion


The combined analysis of variance for all locations in 2016 showed that highly significant (p < 0.01) difference among genotypes on days to heading maturity, plant height, head weight and thousand seed weight (Table 3). A significant (p < 0.05) difference also observed among genotypes on days to heading and grain yield (Table 3). Genotype by environment interaction revealed highly significant difference (p < 0.01) on days to maturity, plant height, head weight and thousand seed weight, while it was not significant for days to heading and grain yield. This indicates that genotypes were showed consistence performance in across all locations. In 2016 the genotypes perform best in E3 (Cheffa) with environment mean of 3875 kgha-1 to the least E1 (Sirinka) with grain yield of 1479 kgha-1 even though no rank change showed between the genotypes. Genotype mean ranged from 1603 kgha-1 for G9 to 3349 kgha-1 for Sima, the candidate (Table 4).

In 2017 the over location combined analyses of variance showed there were significant difference (p < 0.01) among genotypes for all traits (Table 5). Genotype by environment interaction (Table 5) revealed highly significant difference (p < 0.01) for all traits except for head weight which showed non-significant. This result agrees with Habte, et al. [10] and Fentaye, et al. [11] who reported that genotype by environment interaction revealed highly significant difference on grain yield. Eight genotypes at Sirinka, seven genotypes at Jari and Shewarobit and six genotypes at Chefa lie above the grand mean of each location (Table 6). In 2017 genotypes perform best at Chefa (5167 kgha-1) and Sirinka (4338 kgha-1) followed by Shewarobit (2939 kgha-1) and Jari (2503 kgha-1) (Table 6). Genotypes mean ranged from G11 (2886 kgha-1) to (4551 kgha-1) for G11 (Table 6).

Homogeneity of residual variances was tested prior to analysis over locations using Bartlett's tests [12]. The result of homogeneity error variance was homogeneous. Combined analysis of variance (2016 and 2017) revealed highly significant (P < 0.01) difference among sorghum genotypes for all traits (Table 7), implying the presence of genotypes differences for the traits considered. Genotype × environment × year interaction was non-significant (except plant height)which contradictory to the findings of Habte, et al. [10] and Al-Naggar, et al. [13] that showed highly significant difference between genotypes by environment by year interaction. The highest grain yield 6.06 tonha-1 was recorded for the year 2017 as compared to the grain yield 4.77 tonha-1 for the year 2016 (Table 6) because of the optimum rain fall distribution for sorghum production in 2017. The combined analysis of variance (Table 7) revealed the candidate genotype, Sima took the smallest number of days to heading (74.7 days) even earlier than the standard check Raya (76.8 days) while G11 took more number of days to mature (81.7 days). Also the same genotype (Sima) took the smallest days to maturity (125.8 days) still better than standard check (126.7 days) while G11 took maximum days to mature (132.9) which resulted in low grain yield (2363 kgha-1). The highest panicle/head weight was recorded by the candidate genotype, Sima (4562 kgha-1) whereas the lowest panicle/head weight goes to genotype G11 (ICSA-101 × 214865) (2703 kgha-1) (Table 6). This result in agreement with Mulualem, et al. [14] who reported sorghum genotypes showed high variability to head weight which has direct effect on grain yield.

The mean grain yield of tested genotypes ranged from 2.67 tonha-1 from local check (Jigurty) to 3.95 tonha-1 for Sima, the candidate genotype while the standard check (Raya) was 3.10 tonha-1 (Table 7). Among the tested sorghum genotypes, Sima was continuously outsmarted in grain yield and earliness over the rest of the genotypes in all testing environments. The candidate genotype, Sima had 47.44% and 27.29% yield advantages over the local and standard check, respectively. The overall average grain yield for the candidate genotype (Sima) was obtained 3.95 toneha-1 which is higher than the current sorghum productivity in small scale farmers in Amhara region produced 2.72 toneha-1 [5]. The candidate genotype gave a grain yield which is comparable with yield of the varieties released previously for eastern Amhara region at Sirinka agriculture research center and Melekasa agriculture research center [15].

Conclusion and Recommendation


Sorghum is vital crop to Ethiopia where it is grown in a wider area of adaptation ranging from hot, dry lowland, intermediate to the highland environments. The crop is among the most important crops cultivated in Ethiopia with most of the acreages located in parts of the country affected by drought, Striga weed, insect, disease, low soil fertility and lack of improved varieties. In Ethiopia, the crop grown entirely by subsistence farmers to meet needs for food, income, feed, traditional brewing and construction purposes. Drought is one of the major yield's limiting factors. Most farmers grow long maturing local varieties some of which take 7-8 months to mature further complicating the drought problem. The research emphasis for drought is developing early maturing sorghum varieties that can be able to escape terminal drought. The tested genotypes did show consistent performance across locations and years. The present study showed that grain yield was not significantly influenced by change of environmental condition. The highest grain yield of 3.95 tha-1 was recorded from Sima. As a result, G8 (Sima) was selected, it was verified and officially released by the name of Kalu in 2019. This genotype relatively takes shorter days to maturity which will adapt easily to the low moisture areas of the Northeastern lowland parts of the country. So Kalu is recommended for sorghum production to Sirinka, Jari, Chefa and Shewarobit and other similar agroecologies of the country.

Acknowledgements


The authors are thankful to Amhara Agricultural Research Institute (ARARI) for funding this study.

Conflict of Interest


The authors confirm that the content of this article has no competing interests.

References


  1. Paterson AH, Bowers JE, Bruggmann R, et al. (2009) The Sorghum bicolor genome and the diversification of grasses. Nature 457: 551-556.
  2. Geremew G, Asfaw A, Taye T, et al. (2004) Development of sorghum varieties and hybrids for dryland areas of Ethiopia. J Agric Sci 9: 594-605.
  3. Taye M, Mace ES, Godwin ID, et al. (2016) Heterosis in locally adapted sorghum genotypes and potential of hybrids for increased productivity in contrasting environments in Ethiopia. The Crop Journal 4: 479-489.
  4. FAO (Food and agriculture organization) (2016) Cereals production and utilization. Biannual report 2016.
  5. CSA (Central Statistical Agency) (2018) Report on area and production of major crops, Addis Ababa, Ethiopia.
  6. CSA (Central Statistical Agency) (2017) Report on area and production of major crops. Addis Ababa, Ethiopia.
  7. Central Statistical Agency of Ethiopia (CSA) (2017) Agricultural sample survey 2016/2017. Stat BullP, 584.
  8. Hiebsch C, O’Hair SK (1986) Major domesticated crops. In: Hansen A, DE McMillan, Food in Sub-Saharan Africa, 177-206.
  9. Belay F, Meresa H (2017) Performance evaluation of sorghum [Sorghum bicolor (L.) Moench] hybrids in the Moisture Stress conditions of Abergelle District, Northern Ethiopia. J Cereals Oilseeds 8: 26-32.
  10. Nida H, Seyoum A, Gebreyohanes A (2016) Evaluation of yield performance of intermediate altitud Sorghum (Sorghum bicolor (L.) Moench) genotypes using genotype x environment interaction analysis and GGE biplot in Ethiopia. Int J Trend Res 3: 27-33.
  11. Belay F, Mekbib F, Tadesse T (2019) Genotype × environment interaction and yield stability of striga Resistant sorghum [Sorghum bicolor (L.) Moench] hybrids in Ethiopia. Afr J Plant Sci.
  12. Steel RG, Torrie JH (1980) Principles and procedures of statistics. A biometrical approach. (2 nd edn), McGraw-Hill, New York.
  13. Al Naggar AMM, Abd El Salam RM, Asran MR, et al. (2018) Yield Adaptability and Stability of Grain Sorghum. Genotypes across different Environments in Egypt using AMMI, GGE-biplot Models. Annu Res Rev 23: 1-16.
  14. Mulualem T, Alamrew S, Tadesse T, Wegary D (2018) Genetic variability, heritability and genetic advance for agronomical traits of Ethiopian sorghum [Sorghum Bicolor (L.) Moench] genotypes. Acad Res J Agri Sci Res 6: 251-259.
  15. Seyoum A, Tadesse T, Nega A, et al. (2019) Adaptation and verification of malt sorghum (Sorghum bicolor (L.) Moench) genotype in drought prone areas of Ethiopia. Res J Agric Sci 7: 160-165.

Abstract


Sorghum is an important food security crop in Ethiopia. As the grain is preferred for food the biomass is equally important for farmers to use it as animal food. It is a major crop in lowland parts of eastern Amhara as the environment of the area best fits for the crop. The study was conducted with the objective of identifying high yielder and adaptable sorghum varieties for moisture deficit areas of eastern Amhara region. Eleven sorghum genotypes including two checks were evaluated at eight different environments of four locations namely; Sirinka, Jari, Chefa and Shewarobit within two years in 2016 and 2017 under rain feed condition. The experiment was implemented using a randomized complete block design (RCB) with three replications. The combined analysis of variance over years and across locations revealed highly significant difference (p < 0.01) among genotype for all traits. Genotype × year × environment interaction was non-significant except for plant height. The smallest days to maturity recoded by G8 (125.8 days) while G11 took more number of days to mature (132.9 days). G8 also recorded the highest panicle/head weight (4.56 tonha-1) whereas G11 recorded the lowest head weight (2.7 tonha-1). Genotypes ranged from 2.363 tonha-1 for G11 to 3.95 tonha-1 for G8 in grain yield. As the highest grain yield (3.95 tonha-1) was obtained by genotype G8 (Sima) while that of standard and local checks were 3.1 tonha-1 and 2.67 tonha-1, respectively. Thus, G8 (Sima) was found superior over the rest of the tested sorghum genotypes and it has 47.4% and 27.29% yield advantages over local and standard check, respectively. As a result G8 (Sima) was selected, verified and officially released for its early maturing and high yielding in 2019 by the name of Kalu for production in moisture deficit areas of eastern Amhara region and similar agro ecologies of the country.

References

  1. Paterson AH, Bowers JE, Bruggmann R, et al. (2009) The Sorghum bicolor genome and the diversification of grasses. Nature 457: 551-556.
  2. Geremew G, Asfaw A, Taye T, et al. (2004) Development of sorghum varieties and hybrids for dryland areas of Ethiopia. J Agric Sci 9: 594-605.
  3. Taye M, Mace ES, Godwin ID, et al. (2016) Heterosis in locally adapted sorghum genotypes and potential of hybrids for increased productivity in contrasting environments in Ethiopia. The Crop Journal 4: 479-489.
  4. FAO (Food and agriculture organization) (2016) Cereals production and utilization. Biannual report 2016.
  5. CSA (Central Statistical Agency) (2018) Report on area and production of major crops, Addis Ababa, Ethiopia.
  6. CSA (Central Statistical Agency) (2017) Report on area and production of major crops. Addis Ababa, Ethiopia.
  7. Central Statistical Agency of Ethiopia (CSA) (2017) Agricultural sample survey 2016/2017. Stat BullP, 584.
  8. Hiebsch C, O’Hair SK (1986) Major domesticated crops. In: Hansen A, DE McMillan, Food in Sub-Saharan Africa, 177-206.
  9. Belay F, Meresa H (2017) Performance evaluation of sorghum [Sorghum bicolor (L.) Moench] hybrids in the Moisture Stress conditions of Abergelle District, Northern Ethiopia. J Cereals Oilseeds 8: 26-32.
  10. Nida H, Seyoum A, Gebreyohanes A (2016) Evaluation of yield performance of intermediate altitud Sorghum (Sorghum bicolor (L.) Moench) genotypes using genotype x environment interaction analysis and GGE biplot in Ethiopia. Int J Trend Res 3: 27-33.
  11. Belay F, Mekbib F, Tadesse T (2019) Genotype × environment interaction and yield stability of striga Resistant sorghum [Sorghum bicolor (L.) Moench] hybrids in Ethiopia. Afr J Plant Sci.
  12. Steel RG, Torrie JH (1980) Principles and procedures of statistics. A biometrical approach. (2 nd edn), McGraw-Hill, New York.
  13. Al Naggar AMM, Abd El Salam RM, Asran MR, et al. (2018) Yield Adaptability and Stability of Grain Sorghum. Genotypes across different Environments in Egypt using AMMI, GGE-biplot Models. Annu Res Rev 23: 1-16.
  14. Mulualem T, Alamrew S, Tadesse T, Wegary D (2018) Genetic variability, heritability and genetic advance for agronomical traits of Ethiopian sorghum [Sorghum Bicolor (L.) Moench] genotypes. Acad Res J Agri Sci Res 6: 251-259.
  15. Seyoum A, Tadesse T, Nega A, et al. (2019) Adaptation and verification of malt sorghum (Sorghum bicolor (L.) Moench) genotype in drought prone areas of Ethiopia. Res J Agric Sci 7: 160-165.