Genetic Variability and Association of Traits among Sorghum Genotypes [Sorghum bicolor (L.) Moench] Under Drought Stress Area

Genetic Variability and Association of Traits among Sorghum Genotypes [Sorghum bicolor (L.) Moench] Under Drought Stress Area | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Genetic Variability and Association of Traits among Sorghum Genotypes [Sorghum bicolor (L.) Moench] Under Drought Stress Area Ambesu Tilaye This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4577500/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Drought is one of the most important factors that affect crop production worldwide and continues to be a challenge to plant breeders, despite many decades of research. Understanding the genetic variability among sorghum genotypes is the key objective to develop improved sorghum cultivars for drought-prone environments. The field experiment was conducted at Miesso during the 2021 main cropping season. A set of 72 sorghum genotypes advanced from a pedigree breeding approach was used in this study. The experiment was laid out using a Row-Column design with two replications. R statistical software was used to analyze the data. The analysis of variance indicated that there were significant variations among the tested genotypes for the studied traits. Genotypic and phenotypic coefficient of variation ranged from 0.56–23.88% and 0.66–28.99% respectively. Broad sense heritability ranged from 25.56–86.87% while genetic advance as a percent of mean ranged from 1.11–43.40%. Principal component analysis (PCA) revealed that five principal components with Eigenvalue greater than unity accounted for 74.1% of the total variation. Cluster analysis grouped the test genotypes into five clusters. Cluster I, II, III, IV, and V accounted for 41.667%, 6.944%, 26.389%, 16.667%, and 8.333% of the tested genotypes in that order. The highest intra-cluster distance was observed for cluster V whereas the maximum inter-cluster distance was observed between cluster IV and V. The lowest intra-cluster distance was observed for cluster III, whereas clusters I and III showed the lowest inter-cluster distance. The overall study revealed the presence of wide genetic variability among the studied sorghum genotypes in the study area where moisture stress is a critical problem for sorghum production. Plant Physiology and Morphology Genetic Advance Heritability and Cluster Analysis Figures Figure 1 INTRODUCTION Sorghum [Sorghum bicolor (L.) Moench] is the fifth leading cereal crop grown in the tropical and subtropical regions with limited rainfall. It is stable food of poor and the most food-insecure people, living mainly in the semiarid tropics [ 1 ]. It is often cross pollinated, diploid crop species (2n = 2x = 20) which belongs to the Poaceae family with a genome size of 730 Mb [ 2 ]. While it is primarily grown as feed grain in the developed world, sorghum is a staple crop for more than 500 million people in 30 sub-Saharan African and Asian countries and is essential to the food security of over 300 million people in Africa [ 3 ]. Ethiopia is the second largest sorghum producing country in Eastern Africa next to Sudan. Of the cereals, sorghum covers 15% of the total area and contributed 16% of the total grain production in Ethiopia. It is an important food and feed crop grown in dry lowland areas, where soil moisture is limited. In Ethiopia, many sorghum growing areas suffer from recurrent droughts due to shortage and uneven distribution of rainfall. Drought is one of the most important factors which affects crop production in the lowland areas of Ethiopia [ 4 ]. In many regions of the country, the rain comes late or stops early making the crop growing period very short leading to crop failures. The irregular rain pattern, coupled with subsistence farming system has made areas of the country vulnerable to drought and low productivity, leading to severe malnutrition and hunger. It acts as a serious limiting factor in agricultural production by preventing a crop from reaching the genetically determined theoretical maximum yield. Due to the above listed problems, in the study area, the current sorghum production per unit area is not sufficient to meet the demand for human consumption, animal feed, fuel, and building material requirements of a rapidly growing population. Genetic improvement in sorghum yield depends on the magnitude of genetic variability, heritability, and genetic advance in the population. In planning a sorghum improvement program, knowledge of the variability of traits could be a key success. Genetic parameters like the genotypic coefficient of variation, phenotypic coefficient of variation, heritability, and genetic advance are useful biometric tools for measuring genetic variability [ 5 ]. Therefore, the present study was designed to estimate genetic variability among sorghum genotypes for drought tolerance and to determine the association of yield and yield related traits under drought stress condition. MATERIALS AND METHODS Description of The Study Area The field experiment was conducted at Miesso, located in eastern Ethiopia, Oromia Region at 39°21'E longitude and 8°30'N latitude during the 2021 main cropping season. The altitude of Miesso is 1270 m.a.s.l. The area represents dry lowlands where sorghum is predominantly grown by smallholder farmers. The area also characterized by a semiarid climate with high rainfall variability and frequent drought events that affect crop productivity significantly. Long-term average maximum and minimum temperature of the area are 31.5°C and 16.2°C, respectively, and the total annual rainfall is about 571 mm. The study site has a bimodal rainfall distribution with very short rainfall season between March and May, and a main rainy season between end of June to September. Rainfall distributions are erratic and water scarcity is prevalent. The soil type of the experimental site is vertisol with a high clay content at the top 15cm [ 6 ]. The soil has a slightly basic pH (7.6–7.8) with relatively low organic matter content (0.9–1.5%). Experimental Materials The experimental materials comprised of 72 different sorghum genotypes including three checks (Table 1 .), which were released for moisture stress areas. The genotypes were obtained from Melkassa Agricultural Research Center (MARC). These genotypes were developed by the pedigree breeding method and with a subsequent selection of the derived segregating generation Table 1 List of sorghum genotypes used for the experiment Codes. Genotypes Pedigree Seed Sources G1 ETSC15437-2-2 14MILSDT7086/ “Gambella 1107” MW21NVTSeedInc#1 G2 ETSC16087-23-1 235421/ICSTG2372 MW21NVTSeedInc#2 G3 ETSC16066-18-1 ETSL101851/Teshale MW21NVTSeedInc#3 G4 ETSC16034-12-1 Argiti/ICSTG2372 MW21NVTSeedInc#4 G5 ETSC14573-5-4 Melkam/13sudanint10-1 MW21NVTSeedInc#5 G6 ETSC16091-10-1 235421/M204 MW21NVTSeedInc#6 G7 ETSC16032-4-1 05MW6073/M204 MW21NVTSeedInc#7 G8 ETSC15385-2-2 ETSC300301/Meko-1 MW21NVTSeedInc#8 G9 ETSC16034-10-1 Argiti/ICSTG2372 MW21NVTSeedInc#10 G10 ETSC15357-3-1 ICSV700/Meko-1 MW21NVTSeedInc#11 G11 ETSC14715-3-1 13MI5024/13sudanint13-2 MW21NVTSeedInc#12 G12 ETSC16005-9-1 14MWLSDT7310/M204 MW21NVTSeedInc#14 G13 ETSC15363-1-2 S35/ “Gambella 1107” MW21NVTSeedInc#16 G14 ETSC14695-1-2 Debir/13sudanint27 MW21NVTSeedInc#17 G15 ETSC14225-4-2 “Gambella 1107”/S35 MW21NVTSeedInc#18 G16 ETSC16035-9-1 Argiti/B35 or 05MI5064/B35 MW21NVTSeedInc#19 G17 ETSC15312-3-1 Debir/(Hodem/Gobiye) MW21NVTSeedInc#21 G18 ETSC17182-12-2 Local Bulk (White)/SRN39/E36-1/KariMatama1 MW21PYTSeedInc#22 G19 ETSC15363-1-2 WSV387/P-9403/ETSL101857 MW21NVTSeedInc#23 G20 ETSC17023-14-1 90BK4184/85MW5552/NTJ2 MW21PYTSeedInc#24 G21 ETSC17007-9-1 PGRCE6940/SAR24/Framida MW21PYTSeedInc#25 G22 ETSC17240-8-1 (ICSV111/B35)/ICSV111/ “Gambella 1107” MW21PYTSeedInc#26 G23 ETSC17268-7-1 MR812/B35/ “Gambella 1107” MW21PYTSeedInc#27 G24 ETSC17073-6-2 (E-35-1)-4/CS3541derive5-4-2-1)/P9401/SRN39 MS20PYT#90 G25 ETSC17201-1-2 CR: 35:5/ICSV-1005/76T1#23/ “Gambella 1107” MW21PYTSeedInc#29 G26 ETSC17258-13-1 ICSR24010/B35/SRN39 MS20PYT#95 G27 ETSC14804-4-2 SILA/13sudanint10-1 MW21PYTSeedInc#20 G28 ETSC17285-5-2 PGRCE69420/87PW3173/SRN39 MW21PYTSeedInc#32 G29 ETSC15312-3-1 14MWLSDT7324/ICSTG2372 MW21NVTSeedInc#21 G30 ETSC17140-9-1 WSV387/P9403/B35/KariMatama1 MW21PYTSeedInc#34 G31 ETSC17006-8-1 PGRCE6940/SAR24/SRN39 MW21PYTSeedInc#35 G32 ETSC17158-3-2 ICSR24010/B35/ “Gambella 1107” MW21PYTSeedInc#36 G33 ETSC17323-24-2 90BK4184/85MW5552/M-204 MW21PYTSeedInc#37 G34 ETSC17300-4-2 PGRCE6940/SAR24/SRN39 MS20PYT#221 G35 ETSC17296-3-1 PGRCE6940/SAR24/ “Gambella 1107” MW21PYTSeedInc#39 G36 ETSC17298-4-1 PGRCE6940/SAR24/ETSL101848 MW21PYTSeedInc#40 G37 ETSC17213-3-2 IESV92084/E36-1/Melkam MW21PYTSeedInc#42 G38 ETSC17142-9-3 WSV387/P9403/B35/ETSL100307 MW21PYTSeedInc#43 G39 ETSC17156-1-4 MR812/76T1#23/ETSL101865 MW21PYTSeedInc#44 G40 ETSC17301-10-2 PGRCE6940/SAR24/B35 MW21PYTSeedInc#45 G41 ETSC17268-5-3 MR812/B35/ “Gambella 1107” MW21PYTSeedInc#46 G42 ETSC17298-5-2 PGRCE6940/SAR24/ETSL101848 MW21PYTSeedInc#47 G43 ETSC17186-2-1 Local Bulk /SRN39/76T1#23/ “Gambella 1107” MW21PYTSeedInc#48 G44 ETSC17106-6-1 WSV387/P9403/E-36-1/M-204 MS20PYT#355 G45 ETSC17328-8-1 90BK4184/85MW5552/SRN39 MW21PYTSeedInc#50 G46 ETSC17268-5-1 MR812/B35/ “Gambella 1107” MW21PYTSeedInc#51 G47 ETSC17194-3-1 Local Bulk (White)/SRN39/76T1#23/NTJ2 MW21PYTSeedInc#52 G48 ETSC17043-8-1 (E-35-1)-4/CS3541Drv.5-4-2-1)/P9401/ETSL10865 MW21PYTSeedInc#41 G49 ETSC17354-12-1 WSV387/P-9403/ETSL101857 MW21PYTSeedInc#54 G50 ETSC17272-3-1 MR812/B35/SRN39 MW21PYTSeedInc#55 G51 ETSC17321-4-2 (E-35-1)-4/CS3541Drv.5-4-2-1)/P9401/ETSL10865 MW21PYTSeedInc#56 G52 ETSC17350-3-1 WSV387/P-9403/M-204 MW21PYTSeedInc#57 G53 ETSC17115-5-1 WSV387/P9403/E-36-1/ETSL102496 MW21PYTSeedInc#58 G54 ETSC17093-3-1 WSV387/76T1#23/ “Gambella 1107” MW21PYTSeedInc#59 G55 ETSC17213-1-1 IESV92084/E36-1/Melkam MW21PYTSeedInc#60 G56 ETSC14203-5-2 Karimtama1/N-13 MW21PYTSeedInc#61 G57 ETSC17071-6-2 (E-35-1)-4/CS3541Drv.5-4-2-1)/P9401/ETSL10848 MW21PYTSeedInc#62 G58 ETSC17111-3-1 WSV387/P9403/E-36-1/NTJ2 MW21PYTSeedInc#63 G59 ETSC17360-18-2 WSV387/P-9403/ETSL101853 MW21PYTSeedInc#67 G60 ETSC17257-6-1 ICSR24010/B35/ETSL101857 MW21PYTSeedInc#68 G61 ETSC17258-3-2 ICSR24010/B35/SRN39 MW21PYTSeedInc#70 G62 ETSC17354-9-1 WSV387/P-9403/ETSL101857 MW21PYTSeedInc#73 G63 ETSC17129-6-1 SDSL2690-2/76T1#23/NTJ2 MW21PYTSeedInc#77 G64 ETSC17175-5-4 MR812/B35/ETSL102496 MW21PYTSeedInc#78 G65 ETSC17113-6-1 WSV387/P9403/E-36-1/ETSL101853 MW21PYTSeedInc#80 G66 ETSC17360-5-1 WSV387/P-9403/ETSL101853 MW21PYTSeedInc#82 G67 ETSC17172-4-4 MR812/B35/NTJ2 MW21PYTSeedInc#83 G68 ETSC17032-6-1 90BK4236/87PW3173/ETSL101857 MW21PYTSeedInc#84 G69 ETSC16001-6-1 14MWLSDT7310/ICSTG2372 MW21PYTSeedInc#85 G70 Melkam WSV387 MW21Breeder Seed G71 Argiti WSV387/P9403 MW21Breeder Seed G72 Tilahun 2005MI5060/E36-1 MW21Breeder Seed Experimental Design and Procedures The experiment was laid out in an incomplete block of 24 rows by 6 columns in 2 replications according to the commonly used procedure by the National Sorghum Research Program of Ethiopia. The experimental plots consist of 2 rows, each 5 m in length with 75 cm between rows and 15 cm between plants. The experiment was planted on the 11th of July, 2021. Seeds were sown manually by hand drilling at a rate of 10 kgha − 1 . Thinning was done three weeks after the date of planting to maintain the recommended plant population. Fertilizer was applied at a rate of 100 kgha − 1 Di Ammonium Phosphate (DAP) and 50 kgha − 1 of Urea. DAP was applied at sowing while urea was applied at knee height stage (around 35 days after Planting). The field was maintained free of weeds through hand weeding while chemical sprays were made to control insect pests. Cypermethrin (22.5 g a.i. ha − 1 ) was sprayed 6 days after crop emergence to control shoot fly. Diazinon 48 EC, was applied 30 days after plantation to control fall army worm. Data Collection The data were collected both on plot and individual plant basis as per descriptor for sorghum [ 7 ]. Data collection on plant basis Plant height (cm) The average length of five randomly selected plants from the base of the plant to the tip of the panicle was taken at the time of maturity. Panicle length (cm) The average length of five randomly selected plants from the base of the panicle to the tip was measured using barcode ruler. Panicle weight (g) The average weight of five randomly selected panicles (un-threshed) / plot. Panicle yield (g) The average yield of five randomly selected panicles (threshed) per plot. Data collection on plot basis Days to 50% flowering (days) The number of days from emergence to the date at which 50% of the plants in a plot started flowering. Days to 90% physiological maturity (days) The number of days from emergence to the stage where 90% of the plants in a plot reached at physiological maturity which was recognized by a black layer formed on the bottom of the kernel. Grain filling period (days) The numbers of days from dates of 50% flowering to dates of 90% physiological maturity. Grain filling rate (kg/ha/days) : It is calculated as the ratio of grain yield (kg/ha) to grain filling period (days) as: Grain filling rate (kg/ha/days) = Grain yield / Grain filling period [ 8 ]. Stand count at harvest (No.) The total number of main plants in a plot was counted when 90% of the plants in a row mature physiologically. Harvest index (HI %) Calculated as the ratio of dried grain weight adjusted to 12% moisture content to the dried total above ground biomass weight and multiplied by 100. A 5m row of each plot was harvested, above ground biomass (stem and leaves) was dried for 10 days and weighed. Then the panicles were harvested, dried, threshed and weighed to compute the harvest index. Thousand seed weight (g) is the weight of 1000 seeds and adjusted to 12.5% moisture level. Grain yield (kg/ha) After harvesting, the panicles from each row were threshed, cleaned and weighed after adjusted to 12.5% moisture content. Then the raw grain yield (g/plot) was converted to total grain yield (kg/ha). Stay-green score Visual stay-green rating was done at physiological maturity using a scale of 1 to 5. Rating 1 indicates completely green normal size leaves (no leaf death), 2 = 25% of the leaves died, 3 = 26 to 50% of the leaves died, 4 = 51 to 75% are dead, 5 = 76 to 100% of the leaves and stem are dead (complete plant death). Drought tolerance score This was recorded at the time of physiological maturity with a scale of 1 to 5 where 1 = poor, 2 = fair, 3 = good, 4 = very good and 5 = excellent. Chlorophyll content of leaves At the flowering stage, the amount of chlorophyll in the leaves of five randomly chosen plants per plot was measured. A chlorophyll content meter, SPAD − 502 plus (Konica Minolta Sensing, Inc. Japan, Osaka), was used to measure two leaves per plant. The second and fourth leaves were measured from the top at the base of their leaf lamina using a chlorophyll meter (SPAD values). Data Analysis Analysis of Variances (ANOVA) The data were subjected to analysis of variance by using the R- statistical software version 4.3 [ 9 ]. The experimental design was described by the model: \({\varvec{y}}_{\varvec{i}\varvec{j}\varvec{k}\varvec{l}}=\varvec{\mu }+{\varvec{\alpha }}_{\varvec{i}}\) + \({\varvec{\beta }}_{\varvec{j}}+{\varvec{\gamma }}_{\varvec{k}}+{\varvec{\delta }}_{\varvec{l}}+{\varvec{\epsilon }}_{\varvec{i}\varvec{j}\varvec{k}\varvec{l}}\) where y ijkl =the observation of i th treatment applied in the j th row and k th column for l th replication, µ is the grand mean effect, α i is the i th treatment effect, β j is the j th row effect, γ k is the k th column effect, δ l replication effect and ε ijkl are uncorrelated random errors with zero mean and constant variance (δ 2 ) (Table 2 ). Table 2 Analysis of Variance (ANOVA) Source of Variations Degrees of Freedom (DF) Sum of Squares (SS) Mean of Squares (MS) F-Values Rows R-1 SSR SSR/DFR MSR/MSE Columns C-1 SSC SSC/DFC MSC/MSE Treatments Trt-1 SSTrt SSTrt/DFTrt MSTrt/MSE Error (RC-1) - (R-1) - (C-1) - (Trt-1) SSE SSE/DFE Total R*C-1 SST DF = Degree Freedom, R = Rows, C = Columns, Trt = Treatments, DFE = Degree Freedom of Error, DFR = Degree Freedom of Rows, DFC = Degree Freedom of Columns, DFTrt = Degree Freedom of Treatments, SSR = Sum Squares of Rows, SSC = Sum Squares of Columns, SSTrt = Sum Squares of Treatments, SSE = Sum Squares of Error, SST = Sum Squares of Total, MSE = Mean Squares of Error, MSR = Mean Squares of Rows, MSC = Mean Squares of Columns, MSTrt = Mean Squares of Treatments. Estimation of Variance Components The phenotypic and genotypic variability of each quantitative trait was estimated as phenotypic and genotypic variances and coefficients of variation. These variance components were computed using the formula suggested by [ 10 ]. Heritability and Genetic Advance The proportion of phenotypic variance that is attributable to an overall genetic variance for the genotypes was estimated using broad sense heritability values by the formula adopted from [ 11 ]. Expected genetic advance under selection (GA) Genetic advance (GA) in absolute unit and as percent of the mean (GAM), assuming selection of superior 5% of the genotypes were estimated in accordance with the methods illustrated as: - \(GA = K * SDp * {H}^{2}b\) Where, GA = Genetic advance, SDp = Phenotypic standard deviation on mean basis; H 2 b = Heritability in the broad sense. K = the standardized selection differential at 5% selection intensity (K = 2.063). Genetic advance as percent of mean (GAM) Genetic advance as percent of mean was estimated as \(GAM=\frac{GA}{X}*100\) Where, GAM = Genetic advance as percent of mean GA = Genetic advance, x̄ = Mean. The GAM was categorized as low ( 20%) [12]. Clustering of Genotypes The cluster analysis was performed based on the Unweight Pair Group Method with Arithmetic Means (UPGM) clustering method from the Euclidean distance matrix. Principal Component Analysis Principal component analysis (PCA) based on a correlation matrix was computed to find out the characters, which accounted for much of the total variation. Based on the principal component analysis the inter-relationship among a large set of variables in terms of a relatively small set of variables or components was assessed without losing any essential information of original data set. RESULTS AND DISCUSSIONS Analysis of Variances From the analysis of variance, the tested genotypes exhibited significant variation for days to flowering (DTF), stay green score (SGs), days to maturity (DTM), stand count (SC), drought tolerance score (DTs), plant height (PH), chlorophyll content (CHLc), grain filling period (GFP), panicle length (PL), harvest index (HI), panicle weight (PW), panicle yield (PY), thousand seed weight (TSW), grain filling rate (GFR) and grain yield (GY) (Table 3 ). The result indicates that the tested genotypes were different in their potential to perform for variable characteristics at the tested location. Highly significant differences among sorghum genotypes with respect to days to flowering, days to maturity, plant height, head weight per plot, hundred seed weight, and grain yield also reported [ 13 ]. Similarly, significant differences in plant height, days to flowering, days to maturity, grain filling period, thousand seed weight, stay green, panicle exertion, panicle length, days to emergency, panicle width and grain yield were reported [ 8 ]. Table 3 Mean squares from the analysis of variance (ANOVA) for 15 traits of 72 sorghum genotypes evaluated at Miesso Agricultural Research Station in 2021 Mean Squares S/N Traits Trt. (T-1) (Df = 71) Row (R-1) (Df = 23) Col (C-1) (Df = 5) Err (R*C)-T (Df = 44) CV (%) 1 DTF 38.77*** 16.24*** 9.13* 3.25 6.24 2 CHLc 13.39. 50.76 ‘.’ 15.75*** 8.89 7.12 3 SGs 1.0671*** 1.5987*** 1.0501* 0.4485 29.66 4 DTM 32.23*** 43.64*** 20.72** 4.92 4.15 5 SC 124.84*** 74.06 ‘.’ 27.71ns 40.56 19.96 6 DTs 0.7094* 1.2276*** 0.4836ns 0.4205 37.20 7 GFP 33.32*** 42.99*** 24.95** 7.26 11.14 8 PH 1095.16*** 654.96*** 393.56* 152.43 13.74 9 PL 8.65*** 8.07** 0.75ns 3.17 12.27 10 PW 12230.9*** 12800*** 12805.9* 3715.5 19.92 11 PY 5853.4*** 7737.7*** 27263*** 2192 22.38 12 HI 70.98*** 76.26*** 150.29*** 21.32 28.93 13 GY 1399848*** 851509*** 1232283*** 178278 22.63 14 GFR 812.39*** 503.34*** 225.90** 63.70 24.24 15 TSW 29.79*** 31.401 ‘.’ 31.11ns 4.86 14.83 The significant codes indicate that if the P- value was in the range (0, 0.001), (0.001, 0.01), (0.01,0.05), P > 0.05, it had a significance code of ***, **, *,. and ns Mean Performance of Genotypes The range and mean values for 15 traits of 72 studied sorghum genotypes are indicated in Table 4 . Grain yield ranged from 2102.82 Kg/ha to 6322.95 Kg/ha with an average value of 4253.4 Kg/ha. In general, three genotypes had a mean value greater than the best standard check (Melkam = 4260 Kg/ha) for grain yield. Similar ranges and means for days to flowering, days to maturity, grain filling period and plant height are also reported. Table 4 Range and mean values for yield and agronomic traits of the test genotypes and standard check varieties. Traits Test Genotypes Check Varieties Overall Mean Minimum Maximum Average Melkam Argiti Tilahun DTF 64.00 86.00 75.00 72.00 82.00 76.00 77.00 CHLc 45.47 60.92 53.19 54.78 51.00 48.10 52.24 SGs 1.00 5.00 3.00 4.00 3.5.0 2.00 2.61 DTM 112.00 135.00 124.00 116.00 126.00 119.00 123.00 DTs 1.00 4.00 2.50 1.00 1.00 1.00 1.73 SC 25.00 70.00 48.00 46.00 58.00 53.00 47.00 GFP 37.00 61.00 49.00 40.50 45.00 42.50 46.00 PH 131.67 246.33 189.00 147.00 215.00 163.70 193.94 PL 13.17 26.00 19.59 26.00 20.67 20.50 21.08 PW 295.00 816.70 555.50 408.30 641.70 333.30 494.93 PY 184.46 525.90 355.18 323.60 409.80 217.20 339.65 HI 15.52 46.70 31.11 33.46 24.72 17.61 26.62 GY 2102.82 6322.92 4212.87 4.26 5.74 3.59 4253.40 GFR 43.34 140.91 92.16 105.19 132.15 84.45 93.50 TSW 17.60 36.30 26.95 30.85 28.55 24.15 28.03 DTF = days to flowering, CHLc = chlorophyll content, SGs = stay green score, DTM = days to maturity, DTs = drought tolerance score, SC = stand count, GFP = grain filling period, PH = plant height, PL = panicle length, PW = panicle weight, PY = panicle yield, HI = harvest index, GY = grain yield, GFR = grain filling rate and TSW = thousand seed weight. Estimates of Variance Components Phenotypic and Genotypic Coefficient of Variation Genotypic and phenotypic coefficient of variation ranged from 0.56% (stay green score) to 23.88% (harvest index) and 0.66% (stay green score) to 28.99% (harvest index), respectively (Table 5 ). High PCV and GCV values were observed for harvest index, grain filling rate and grain yield. High PCV values indicate that selection on the basis of phenotype would be effective for most of the characters [ 14 ]. Traits with high GCV indicate the basic prerequisite on which positive response due to selection depends. Low GCV values were recorded for stay green score, grain filling period, panicle length, days to flowering, chlorophyll content and days to maturity indicating that improvement of these traits through selection would be less effective due to lack of genetic variability. Low PCV values were recorded for days to flowering, stay green score, chlorophyll content, drought tolerance score and days to maturity. These traits contribute a low magnitude of heritable genetic (additive) factor to the next generation, which indicates no need for investment to improve these traits aiming for sorghum improvement. The lower GCV and PCV values for different traits in the current study was in agreement with findings reported [ 15 ]. Estimates of Heritability and Genetic Advance Broad sense heritability ranged from 25.56% for drought tolerance score to 86.87% for grain filling rate. High heritability values were noticed for grain filling rate, days to flowering, grain yield, thousand seed weight, plant height, days to maturity, harvest index and grain filling period (Table 5 ). These variables' high heritability values suggested that genetics accounted for the majority of the variance seen and that environmental factors had less of an impact. Thus, under stressful situations, these characteristics could be employed as selection criteria. Because the environment masks the genotypic effects, selection may be extremely difficult or even impossible for a character with low heritability. Accordingly, choosing genotypes based on grain yield and attributes related to yield would be a more satisfying way to enhance the performance of sorghum genotypes, according to the results of the current study [ 16 ]. Genetic advance as a percentage of mean ranged from 1.11% for drought tolerance score to 43.4% for grain filling rate (Table 5 ), indicating selection of the top 5% base population could result in an advance of 1.11% and 43.4% over the respective population. High genetic advance as percentage of mean was recorded for grain filling rate, harvest index, stand count, thousand seed weight, grain yield, panicle yield, panicle weight and plant height. High value, given as a percentage of mean, of the projected genetic advance observed for plant height and harvest index. When selection is based on characteristics with a sufficiently substantial genetic advancement as a percentage of mean, varieties will perform better for those traits [ 17 ]. Table 5 Estimates of variability components for fifteen traits of 72 sorghum genotypes evaluated at Miesso Agricultural Research Station during the 2021 growing season Traits Range Mean ± SEM σ 2 g σ 2 p σ 2 e GCV (%) PCV (%) H 2 b (%) GA GAM (%) DTF 64.00–86.00 77.00 ± 1.29 19.95 23.26 3.31 5.88 6.26 85.76 8.52 11.06 CHLc 45.47–60.92 52.24 ± 2.26 4.30 13.73 9.42 3.97 7.09 31.34 2.39 4.58 SGs 1.00–5.00 2.61 ± 0.47 0.31 0.76 0.45 0.56 0.66 40.82 0.73 1.14 DTM 112.00-135.00 123.00 ± 1.92 17.56 24.96 7.40 3.48 4.05 70.86 7.24 5.96 SC 25.00–70.00 47.00 ± 4.50 47.95 88.51 40.56 14.71 19.99 54.17 10.58 22.31 DTs 1.00–4.00 1.73 ± 0.46 0.14 0.56 0.42 0.78 0.60 25.56 0.39 1.11 GFP 37.00–61.00 46.00 ± 2.28 16.75 26.38 9.63 8.83 11.17 63.38 6.78 14.56 PH 131.67-246.33 193.94 ± 8.96 553.48 714.03 160.74 12.13 13.88 77.50 42.75 21.99 PL 13.17-26 21.08 ± 1.32 3.13 6.64 3.51 8.39 12.22 47.17 2.50 11.87 PW 295.00-816.00 494.93 ± 44.75 5781.08 9786.22 4005.14 15.36 19.99 59.07 120.38 24.32 PY. 184.46–525.90 339.65 ± 36.56 3107.68 5781.09 2673.41 16.41 22.38 53.76 84.19 24.79 HI 15.52–46.70 26.62 ± 3.09 40.43 59.57 19.15 23.88 28.99 67.86 10.79 40.53 GY 2102.82-6322.95 4253.4 ± 300.64 752491.82 933261.16 180769.34 20.36 22.67 80.63 1604.6 37.66 GFR 43.34-140.91 93.50 ± 5.81 446.88 514.29 67.51 22.61 24.25 86.87 40.58 43.40 TSW 17.60–36.30 28.03 ± 1.56 12.47 17.33 4.86 12.59 14.85 71.96 6.17 22.02 SEM = Standard error of mean, σ 2 g =genotypic variance, σ 2 e =environmental variance, σ 2 p =Phenotypic variance, PCV = Phenotypic coefficient of variation, GCV = Genotypic coefficient of variation, H 2 b = Broad sense heritability GA = Genetic advance in absolute unit, GAM = Genetic advance as percentage of mean, DTF = days to flowering, CHLc = chlorophyll content, SGs = stay green score, DTM = days to maturity, DTs = drought tolerance score, SC = stand count, GFP = grain filling period, PH = plant height, PL = panicle length, PW = panicle weight, PY = panicle yield, HI = harvest index, GY = grain yield, GFR = grain filling rate and TSW = thousand seed weight. Clustering of Genotypes Most breeding programs utilize diverse parents which are genetically far apart from one another; cluster analysis usually finds the extent of genetic diversity and groups the crop with similar parents into one cluster [ 18 ]. The analysis was based on an unweighted pair group method with an arithmetic means clustering method from euclidean distances matrix which grouped the 72 sorghum genotypes into five major clusters, consisting of 5 to 30 genotypes (Fig. 1 and Table 6 ). Cluster I was the largest cluster consisting of 30 genotypes and accounted for 41.667% of the total genotypes. Cluster III was the second largest cluster followed by cluster IV which consists of 19 genotypes (26.389%) and 12 genotypes (16.667%) of the total genotypes respectively. Cluster II and V have the lowest number and percentage of the genotypes. Such genetic divergence among sorghum genotypes indicated that crossing between distantly related genotypes of these clusters might provide desirable recombinants. Table 6 Distribution of 72 sorghum genotypes in to five different clusters based on fifteen quantitative traits Number of Clusters Proportion of Genotypes List of Genotypes. Cluster-I 30 (41.667%) G1, G30, G2, G23, G32, G36, G68, G48, G67, G42, G59, G53, G55, G63, G51, G66, G8, G37, G9, G47, G10, G43, G15, G71, G13, G65, G20, G24, G49, G62 Cluster-II 5 (6.944%) G3, G33, G34, G45, G70 Cluster-III 19 (26.389%) G4, G17, G38, G54, G26, G56, G61, G72, G5, G28, G31, G50, G41, G6, G7, G52, G12, G22, G39 Cluster-IV 12 (16.667) G11, G21, G25, G16, G46, G18, G44, G58, G57, G64, G19, G60 Cluster-V 6 (8.333%) G14, G27, G29, G35, G40, G69 Cluster Mean Analysis The mean values of fifteen quantitative characters distributed in to five clusters are presented in Table 7. Cluster I had mean values greater than overall mean for all traits except for days to flowering and stand count. Cluster II was distinguished from the others by having lower mean values than over all means for all traits except for panicle length, panicle weight, thousand seed weight and grain filling rate. The genotypes in cluster III had higher mean values for panicle weight, thousand seed weight, harvest index, panicle yield, grain filling rate and grain yield, which can be selected for further evaluation and could be suitable for improvement of sorghum yield under drought conditions. The low values of days to maturity and grain filling period in cluster II and days to flowering in cluster IV indicate the presence of early maturing genotypes, Thus, further evaluation of members of this cluster to develop early maturing variety would be promising option to improve the yield of sorghum for the area. Table 8 Mean values of five clusters based on fifteen studied traits of 72 sorghum genotypes Traits Cluster-I Cluster-II Cluster-III Cluster-IV Cluster-V GM DTF 77.00 77.00 77.00 78.00 74.00 77.00 CHLc. 53.08 498.82 52.42 51.41 55.20 52.24 DTM 124.00 118.00 123.00 123.00 128.00 123.00 SC 44.00 41.00 45.00 50.00 57.00 47.00 GFP 47.00 41.00 47.00 45.00 54.00 46.00 PH 195.06 152.00 192.09 195.01 241.67 193.94 PL 2122.53 22.67 20.86 20.82 24.00 21.08 PW 579.17 816.67 495.24 415.70 550.00 494.93 PY 418.81 306.81 348.21 278.14 184.46 339.65 TSW 30.25 40.21 26.29 22.63 15.52 26.10 HI 28.99 26.65 28.16 27.25 26.85 28.03 GFR 100.05 94.02 93.83 87.33 78.71 93.00 GY 4643.00 3847.00 4333.00 3909.00 4205.00 4261.00 DTF = days to flowering, CHLc = chlorophyll content, SGs = stay green score, DTM = days to maturity, DTs = drought tolerance score, SC = stand count, GFP = grain filling period, PH = plant height, PL = panicle length, PW = panicle weight, PY = panicle yield, HI = harvest index, GY = grain yield, GFR = grain filling rate and TSW = thousand seed weight. Genetic Distance among Clusters The range of variation present between genotypes determines the extent of improvement gained through selection and hybridization. The larger the distance between two clusters, the wider the genetic variability between them, for inclusion in the hybridization program [ 19 ]. The intra cluster distances ranged from 2.59702 to 3.12876 estimated by using Euclidian’s distance methods, indicating that the hybrids in clusters have dissimilarity in morphological features and performance (Table 8 ). The intra-cluster distance was significantly smaller than the inter-cluster one, indicating that the groupings were heterogeneous inside and homogeneous between them. Cluster V exhibited the maximum intra-cluster distance, whilst cluster III displayed the lowest intra-cluster distance. The highest inter cluster distance was observed between cluster II and IV while the lowest inter cluster distance was observed between cluster I and IV. Lowest inter cluster distances were indicative of close relationship and similarity for most traits in the genotypes hence selection of parents from these clusters is to be avoided [ 20 ]. Maximum inter cluster distance indicates that genotypes falling in these clusters had wide diversity and can be used for improvement program to get better recombinants. Genotypes that were both agronomically excellent and genetically varied were chosen using inter-cluster distances. More opportunities for crossing over would result from dissimilar groups coming together, which breaks up unwanted links and releases latent potential variability [ 21 ]. It is anticipated that offspring from these kinds of varied crossings will exhibit a broad range of genetic variability, which will increase the opportunity to identify transgressive segregants in later generations. From the mean analysis genotypes, G34, G45, G3, G50 and G39 are the most promising genotypes based on a combination of multiple studied traits. Table 8 Average intra (bold) and inter (off diagonal) cluster distance among five clusters of 72 sorghum genotypes No. of cluster Cluster-I Cluster-II Cluster-III Cluster-IV Cluster-V Cluster-I 2.90645 4.02052 2.78664 3.02085 3.90981 Cluster-II 3.00575 4.01958 5.29924 4.14042 Cluster-III 2.59702 2.95493 3.76775 Cluster-IV 2.68495 5.18341 Cluster-V 3.12876 CONCLUSION The genotypes employed for the evaluated characters showed a wide range of genetic diversity in this investigation, suggesting a high potential for use in trait enhancement. Furthermore, the presence of predicted GAM% and significant high heritability (H2) suggested possibilities for improving the traits through selection. From the principal component analysis, the first two principal components accounted for a cumulative of 39.5% of total variation indicating most of the important yield and yield attributing traits were present in these first two principal components. Cluster analysis based on unweighted pair group method with arithmetic means method grouped the 72 sorghum genotypes into five distinct clusters based on fifteen quantitative characters. Such genetic divergence among sorghum genotypes indicated that crossing between genotypes of these clusters might provide desirable recombinants and high yielding segregants. In general, based on the mean performance of genotypes, G14, G15 and G27 had a yield advantage over the best standard checks (Melkam). Genotypes, G34, G24, G40, G5, G29, G50, G27 and G49 are the most promising genotypes based on the combination of multiple traits. The overall study revealed the presence of wide genetic variability among the 72 sorghum genotypes evaluated which can be exploited to develop high-yielding varieties with desirable grain yield and early maturity in the study area where moisture stress is a critical problem for sorghum production. Declarations Acknowledgements The authors thank the Melkassa National Sorghum Research Program for their financial support to make the work possible. Great thanks to the research team for their every support, starting from planting to data collection. I wish to thank all of my friends and colleagues for their support. Significance Statement In Ethiopia sorghum is predominantly grown in arid and semi-arid areas. However, the yield of sorghum is affected by severe and recurrent drought where rainfall is inadequate, non-uniform and erratic. Development of high yielding varieties require detailed knowledge of variation among the traits and the association among yield components. There is a need of conducting genetic variability to generate information for further breeding work to develop varieties for the moisture stressed areas. Therefore, the present study was designed to estimate genetic variability among sorghum genotypes for drought tolerance, and to determine the association of yield and yield related traits under drought stress condition. Author’s contribution The following tasks have been confirmed as being within our purview as the research paper's authors: study idea and design; data collecting; analysis and interpretation of findings; and article writing. [Author 2] and [Author 3] designed the research study and secured funding. [Author 1] conducted the experiments, collected and analyses the data. The Author has the rights: (1) to use the manuscript in the Author's teaching activities; (2) to publish the manuscript, or permit its publication, as part of any book the Author may write; (3) to include the manuscript in the Author's own personal or departmental (but not institutional) database or on-line site. Conflict of interest Conflicts of interest, often known as "competing interests," arise when external factors influence or are thought to influence the impartiality or neutrality of research. It can occur at any point during the research cycle, including when a manuscript is being written, conducting experiments, or preparing an article for publication. Nonetheless, none of the research paper's authors had any conflicts of interest to declare. Each and every author says that they have no competing interests. References Azarinasrabad A et al (2016) Evaluation of water stress on yield, its components and some physiological traits at different growth stages. grain sorghum genotypes 8(2):204–210 Paterson AH et al (2009) Sorghum bicolor genome Diversif grasses 457(7229):551–556 Kidanemaryam W, Kassahun B, Taye TJJU (2018) Assessment of Heterotic Performance and Combining Ability of Ethiopian Elite Sorghum (Sorghum bicolor (L.) Moench) Lines. Gebretsadik R et al (2014) A diagnostic appraisal of the sorghum farming system and breeding priorities in Striga infested agro-ecologies of Ethiopia. 123: pp. 54–61 Aditya J, Bhartiya P, J.J.o.C A (2011) Genetic variability, heritability and character association for yield and component characters in soybean (G. max (L.) Merrill). 12(1):27–34 FAO FJR (2018) URL: http://faostat.fao. org, Food and agriculture organization of the United Nations. Rao NK et al (2004) Conserv utilization distribution sorghum germplasm 33:43 Endalamaw C, Z.J.I.J.o.A B, Semahegn, Research B (2020) Genetic Variability and Yield Performance of Sorghum (sorghum bicolor L.) Genotypes Grown in Semi-Arid Ethiopia. 8(2):193–213 Thomas R, Vaughan I (2013) and J. J.A.g.f.s.E.-e . Lello, Data analysis with R statistical software. Burton GW, De Vane dE (1954) Estimating heritability in tall fescue (Festuca arundinacea) from replicated clonal material. Falconer D, Mackay FJH, Essex E (1996) Introduction to Quantitative Genetic 4th Edition Longman Group Limited. : pp. 108–183 Johnson HW, Robinson H, Comstock R (1956) Estimates of genetic and environmental variability in soybeans. Amare K et al (2015) Variability for yield, yield related traits and association among traits of sorghum (Sorghum Bicolor (L.) Moench) varieties in Wollo, Ethiopia. Ranjith P et al (2017) Genetic variability, heritability and genetic advance for grain yield and yield components in sorghum. 7(1): pp. 90–93 Chavan S, Mahajan R, Fatak SUJCR (2011) Correlation path Anal Stud sorghum 42(1to3):246–250 Jilo T et al (2018) Genetic variability, heritability and genetic advance of maize (Zea mays L.) inbred lines for yield and yield related traits in southwestern Ethiopia. 10(10):281–289 Mahajan R et al (2011) Variability correlation path Anal Stud sorghum 2(1):101–103 Mohammadi R, Farshadfar E, Amri AJTCJ (2015) Interpreting genotype× Environ Interact grain yield rainfed durum wheat Iran 3(6):526–535 AMBESU T (2022) Genetic Variability and Association of Yield and Yield Related Traits among Sorghum Genotypes [Sorghum bicolor (L.) Moench] Under Drought Stress Conditions Praveen Singh PS et al (2014) Genetic divergence study in improved bread wheat varieties (Triticum aestivum). Thoday JMJH (1960) Effects of disruptive selection. III. Coupling and repulsion. 14: pp. 35–49 Additional Declarations The authors declare no competing interests. Supplementary Files 2.jpg Pictures taken from the field Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4577500","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":314137440,"identity":"5c5d94b1-e1a9-4974-8b3e-f8369ff1fb2d","order_by":0,"name":"Ambesu Tilaye","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3klEQVRIiWNgGAWjYFACHgaGBwwScvLsDUCOgQVRWhgbEhgsjA17DoC0SBCtpSKx4UYCiEeEFv5pZ48/SGyTYGyc+fzqhh8FEgz87d0JeLVI3M5LbABqYWaXzim72QN0mMSZsxvwW3M7xxCkhY1xdk7aDR6gFgOJXPxa5KFaeBhunkm7+YcYLQZQLRIMN9iP3SbKFkOgX2YknJMwMOzJYbstYyDBQ9AvcrdzD3z4UFZXP5/9+LObb/7YyPG39xLwPggwsoFIHgMwSVg5GPwBEewPiFQ9CkbBKBgFIw0AALwUSq2l8mJUAAAAAElFTkSuQmCC","orcid":"","institution":"Ethiopian Institute of Agricultural Research","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Ambesu","middleName":"","lastName":"Tilaye","suffix":""}],"badges":[],"createdAt":"2024-06-13 16:28:41","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false,"coiExplicitlySet":false},"doi":"10.21203/rs.3.rs-4577500/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4577500/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":58336602,"identity":"5a2b86a4-2e25-44cb-b7fd-04de3661cab3","added_by":"auto","created_at":"2024-06-14 05:31:52","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":107689,"visible":true,"origin":"","legend":"\u003cp\u003eDendrogram depicting similarity of 72 sorghum genotypes by unweighted pair group method with arithmetic means (UPGMA) clustering method from Euclidean distances matrix estimated for 15 quantitative traits\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4577500/v1/e97df16a7dbe19db7a0a60c9.jpg"},{"id":58337047,"identity":"07ab9bf6-e938-458c-b125-45ad3bb36c6e","added_by":"auto","created_at":"2024-06-14 05:39:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1384179,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4577500/v1/29bf77cb-327e-42a4-aa26-77ea4777a172.pdf"},{"id":58336603,"identity":"ea4df360-2bba-4c12-a40e-5818160de88e","added_by":"auto","created_at":"2024-06-14 05:31:53","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":10464402,"visible":true,"origin":"","legend":"\u003cp\u003ePictures taken from the field\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4577500/v1/2aa001e9ee7fc88ef7a2c358.jpg"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eGenetic Variability and Association of Traits among Sorghum Genotypes [Sorghum bicolor (L.) Moench] Under Drought Stress Area\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eSorghum \u003cem\u003e[Sorghum bicolor (L.) Moench]\u003c/em\u003e is the fifth leading cereal crop grown in the tropical and subtropical regions with limited rainfall. It is stable food of poor and the most food-insecure people, living mainly in the semiarid tropics [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. It is often cross pollinated, diploid crop species (2n\u0026thinsp;=\u0026thinsp;2x\u0026thinsp;=\u0026thinsp;20) which belongs to the Poaceae family with a genome size of 730 Mb [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. While it is primarily grown as feed grain in the developed world, sorghum is a staple crop for more than 500\u0026nbsp;million people in 30 sub-Saharan African and Asian countries and is essential to the food security of over 300\u0026nbsp;million people in Africa [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Ethiopia is the second largest sorghum producing country in Eastern Africa next to Sudan. Of the cereals, sorghum covers 15% of the total area and contributed 16% of the total grain production in Ethiopia. It is an important food and feed crop grown in dry lowland areas, where soil moisture is limited.\u003c/p\u003e \u003cp\u003eIn Ethiopia, many sorghum growing areas suffer from recurrent droughts due to shortage and uneven distribution of rainfall. Drought is one of the most important factors which affects crop production in the lowland areas of Ethiopia [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In many regions of the country, the rain comes late or stops early making the crop growing period very short leading to crop failures. The irregular rain pattern, coupled with subsistence farming system has made areas of the country vulnerable to drought and low productivity, leading to severe malnutrition and hunger. It acts as a serious limiting factor in agricultural production by preventing a crop from reaching the genetically determined theoretical maximum yield.\u003c/p\u003e \u003cp\u003eDue to the above listed problems, in the study area, the current sorghum production per unit area is not sufficient to meet the demand for human consumption, animal feed, fuel, and building material requirements of a rapidly growing population. Genetic improvement in sorghum yield depends on the magnitude of genetic variability, heritability, and genetic advance in the population. In planning a sorghum improvement program, knowledge of the variability of traits could be a key success. Genetic parameters like the genotypic coefficient of variation, phenotypic coefficient of variation, heritability, and genetic advance are useful biometric tools for measuring genetic variability [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Therefore, the present study was designed to estimate genetic variability among sorghum genotypes for drought tolerance and to determine the association of yield and yield related traits under drought stress condition.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDescription of The Study Area\u003c/h2\u003e \u003cp\u003eThe field experiment was conducted at Miesso, located in eastern Ethiopia, Oromia Region at 39\u0026deg;21'E longitude and 8\u0026deg;30'N latitude during the 2021 main cropping season. The altitude of Miesso is 1270 m.a.s.l. The area represents dry lowlands where sorghum is predominantly grown by smallholder farmers. The area also characterized by a semiarid climate with high rainfall variability and frequent drought events that affect crop productivity significantly. Long-term average maximum and minimum temperature of the area are 31.5\u0026deg;C and 16.2\u0026deg;C, respectively, and the total annual rainfall is about 571 mm. The study site has a bimodal rainfall distribution with very short rainfall season between March and May, and a main rainy season between end of June to September. Rainfall distributions are erratic and water scarcity is prevalent. The soil type of the experimental site is vertisol with a high clay content at the top 15cm [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The soil has a slightly basic pH (7.6\u0026ndash;7.8) with relatively low organic matter content (0.9\u0026ndash;1.5%).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eExperimental Materials\u003c/h2\u003e \u003cp\u003eThe experimental materials comprised of 72 different sorghum genotypes including three checks (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.), which were released for moisture stress areas. The genotypes were obtained from Melkassa Agricultural Research Center (MARC). These genotypes were developed by the pedigree breeding method and with a subsequent selection of the derived segregating generation\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eList of sorghum genotypes used for the experiment\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCodes.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGenotypes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePedigree\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSeed Sources\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC15437-2-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14MILSDT7086/ \u0026ldquo;Gambella 1107\u0026rdquo;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21NVTSeedInc#1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC16087-23-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e235421/ICSTG2372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21NVTSeedInc#2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC16066-18-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eETSL101851/Teshale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21NVTSeedInc#3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC16034-12-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eArgiti/ICSTG2372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21NVTSeedInc#4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC14573-5-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMelkam/13sudanint10-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21NVTSeedInc#5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC16091-10-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e235421/M204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21NVTSeedInc#6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC16032-4-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e05MW6073/M204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21NVTSeedInc#7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC15385-2-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eETSC300301/Meko-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21NVTSeedInc#8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC16034-10-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eArgiti/ICSTG2372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21NVTSeedInc#10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC15357-3-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eICSV700/Meko-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21NVTSeedInc#11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC14715-3-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13MI5024/13sudanint13-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21NVTSeedInc#12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC16005-9-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14MWLSDT7310/M204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21NVTSeedInc#14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC15363-1-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eS35/ \u0026ldquo;Gambella 1107\u0026rdquo;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21NVTSeedInc#16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC14695-1-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDebir/13sudanint27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21NVTSeedInc#17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC14225-4-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026ldquo;Gambella 1107\u0026rdquo;/S35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21NVTSeedInc#18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC16035-9-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eArgiti/B35 or 05MI5064/B35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21NVTSeedInc#19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC15312-3-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDebir/(Hodem/Gobiye)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21NVTSeedInc#21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17182-12-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLocal Bulk (White)/SRN39/E36-1/KariMatama1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#22\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC15363-1-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWSV387/P-9403/ETSL101857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21NVTSeedInc#23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17023-14-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90BK4184/85MW5552/NTJ2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17007-9-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePGRCE6940/SAR24/Framida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17240-8-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(ICSV111/B35)/ICSV111/ \u0026ldquo;Gambella 1107\u0026rdquo;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17268-7-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR812/B35/ \u0026ldquo;Gambella 1107\u0026rdquo;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17073-6-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(E-35-1)-4/CS3541derive5-4-2-1)/P9401/SRN39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMS20PYT#90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17201-1-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCR: 35:5/ICSV-1005/76T1#23/ \u0026ldquo;Gambella 1107\u0026rdquo;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17258-13-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eICSR24010/B35/SRN39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMS20PYT#95\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC14804-4-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSILA/13sudanint10-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17285-5-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePGRCE69420/87PW3173/SRN39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC15312-3-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14MWLSDT7324/ICSTG2372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21NVTSeedInc#21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17140-9-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWSV387/P9403/B35/KariMatama1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG31\u003c/p\u003e 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align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17142-9-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWSV387/P9403/B35/ETSL100307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17156-1-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR812/76T1#23/ETSL101865\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#44\u003c/p\u003e \u003c/td\u003e 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colname=\"c2\"\u003e \u003cp\u003eETSC17106-6-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWSV387/P9403/E-36-1/M-204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMS20PYT#355\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17328-8-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90BK4184/85MW5552/SRN39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17268-5-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR812/B35/ \u0026ldquo;Gambella 1107\u0026rdquo;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17194-3-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLocal Bulk (White)/SRN39/76T1#23/NTJ2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17043-8-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e 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colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17321-4-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(E-35-1)-4/CS3541Drv.5-4-2-1)/P9401/ETSL10865\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17350-3-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWSV387/P-9403/M-204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17115-5-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWSV387/P9403/E-36-1/ETSL102496\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17093-3-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWSV387/76T1#23/ \u0026ldquo;Gambella 1107\u0026rdquo;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17213-1-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIESV92084/E36-1/Melkam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC14203-5-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKarimtama1/N-13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e 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colname=\"c3\"\u003e \u003cp\u003eWSV387/P-9403/ETSL101853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17257-6-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eICSR24010/B35/ETSL101857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17258-3-2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eICSR24010/B35/SRN39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17354-9-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWSV387/P-9403/ETSL101857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17129-6-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSDSL2690-2/76T1#23/NTJ2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e 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align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17360-5-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWSV387/P-9403/ETSL101853\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17172-4-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR812/B35/NTJ2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC17032-6-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90BK4236/87PW3173/ETSL101857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eETSC16001-6-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14MWLSDT7310/ICSTG2372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21PYTSeedInc#85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMelkam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWSV387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21Breeder Seed\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eArgiti\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWSV387/P9403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21Breeder Seed\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eG72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTilahun\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2005MI5060/E36-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMW21Breeder Seed\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eExperimental Design and Procedures\u003c/h2\u003e \u003cp\u003eThe experiment was laid out in an incomplete block of 24 rows by 6 columns in 2 replications according to the commonly used procedure by the National Sorghum Research Program of Ethiopia. The experimental plots consist of 2 rows, each 5 m in length with 75 cm between rows and 15 cm between plants. The experiment was planted on the 11th of July, 2021. Seeds were sown manually by hand drilling at a rate of 10 kgha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. Thinning was done three weeks after the date of planting to maintain the recommended plant population. Fertilizer was applied at a rate of 100 kgha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e Di Ammonium Phosphate (DAP) and 50 kgha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003eof Urea. DAP was applied at sowing while urea was applied at knee height stage (around 35 days after Planting). The field was maintained free of weeds through hand weeding while chemical sprays were made to control insect pests. Cypermethrin (22.5 g a.i. ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) was sprayed 6 days after crop emergence to control shoot fly. Diazinon 48 EC, was applied 30 days after plantation to control fall army worm.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData Collection\u003c/h2\u003e \u003cp\u003eThe data were collected both on plot and individual plant basis as per descriptor for sorghum [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eData collection on plant basis\u003c/h2\u003e \u003cp\u003e \u003cstrong\u003ePlant height (cm)\u003c/strong\u003e \u003cp\u003eThe average length of five randomly selected plants from the base of the plant to the tip of the panicle was taken at the time of maturity.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003ePanicle length (cm)\u003c/strong\u003e \u003cp\u003eThe average length of five randomly selected plants from the base of the panicle to the tip was measured using barcode ruler.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003ePanicle weight (g)\u003c/strong\u003e \u003cp\u003eThe average weight of five randomly selected panicles (un-threshed) / plot.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003ePanicle yield (g)\u003c/strong\u003e \u003cp\u003eThe average yield of five randomly selected panicles (threshed) per plot.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData collection on plot basis\u003c/h2\u003e \u003cp\u003e \u003cstrong\u003eDays to 50% flowering (days)\u003c/strong\u003e \u003cp\u003eThe number of days from emergence to the date at which 50% of the plants in a plot started flowering.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eDays to 90% physiological maturity (days)\u003c/strong\u003e \u003cp\u003eThe number of days from emergence to the stage where 90% of the plants in a plot reached at physiological maturity which was recognized by a black layer formed on the bottom of the kernel.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eGrain filling period (days)\u003c/strong\u003e \u003cp\u003eThe numbers of days from dates of 50% flowering to dates of 90% physiological maturity.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eGrain filling rate (kg/ha/days)\u003c/b\u003e: It is calculated as the ratio of grain yield (kg/ha) to grain filling period (days) as: Grain filling rate (kg/ha/days)\u0026thinsp;=\u0026thinsp;Grain yield / Grain filling period [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eStand count at harvest (No.)\u003c/strong\u003e \u003cp\u003eThe total number of main plants in a plot was counted when 90% of the plants in a row mature physiologically.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eHarvest index (HI %)\u003c/strong\u003e \u003cp\u003eCalculated as the ratio of dried grain weight adjusted to 12% moisture content to the dried total above ground biomass weight and multiplied by 100. A 5m row of each plot was harvested, above ground biomass (stem and leaves) was dried for 10 days and weighed. Then the panicles were harvested, dried, threshed and weighed to compute the harvest index.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eThousand seed weight (g)\u003c/strong\u003e \u003cp\u003eis the weight of 1000 seeds and adjusted to 12.5% moisture level.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eGrain yield (kg/ha)\u003c/strong\u003e \u003cp\u003eAfter harvesting, the panicles from each row were threshed, cleaned and weighed after adjusted to 12.5% moisture content. Then the raw grain yield (g/plot) was converted to total grain yield (kg/ha).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eStay-green score\u003c/strong\u003e \u003cp\u003eVisual stay-green rating was done at physiological maturity using a scale of 1 to 5. Rating 1 indicates completely green normal size leaves (no leaf death), 2\u0026thinsp;=\u0026thinsp;25% of the leaves died, 3\u0026thinsp;=\u0026thinsp;26 to 50% of the leaves died, 4\u0026thinsp;=\u0026thinsp;51 to 75% are dead, 5\u0026thinsp;=\u0026thinsp;76 to 100% of the leaves and stem are dead (complete plant death).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eDrought tolerance score\u003c/strong\u003e \u003cp\u003eThis was recorded at the time of physiological maturity with a scale of 1 to 5 where 1\u0026thinsp;=\u0026thinsp;poor, 2\u0026thinsp;=\u0026thinsp;fair, 3\u0026thinsp;=\u0026thinsp;good, 4\u0026thinsp;=\u0026thinsp;very good and 5\u0026thinsp;=\u0026thinsp;excellent.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eChlorophyll content of leaves\u003c/strong\u003e \u003cp\u003eAt the flowering stage, the amount of chlorophyll in the leaves of five randomly chosen plants per plot was measured. A chlorophyll content meter, SPAD \u0026minus;\u0026thinsp;502 plus (Konica Minolta Sensing, Inc. Japan, Osaka), was used to measure two leaves per plant. The second and fourth leaves were measured from the top at the base of their leaf lamina using a chlorophyll meter (SPAD values).\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003eAnalysis of Variances (ANOVA)\u003c/h2\u003e \u003cp\u003eThe data were subjected to analysis of variance by using the R- statistical software version 4.3 [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The experimental design was described by the model: \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{y}}_{\\varvec{i}\\varvec{j}\\varvec{k}\\varvec{l}}=\\varvec{\\mu }+{\\varvec{\\alpha }}_{\\varvec{i}}\\)\u003c/span\u003e\u003c/span\u003e\u003cb\u003e+\u003c/b\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\varvec{\\beta }}_{\\varvec{j}}+{\\varvec{\\gamma }}_{\\varvec{k}}+{\\varvec{\\delta }}_{\\varvec{l}}+{\\varvec{\\epsilon }}_{\\varvec{i}\\varvec{j}\\varvec{k}\\varvec{l}}\\)\u003c/span\u003e\u003c/span\u003e where y\u003csub\u003eijkl\u003c/sub\u003e=the observation of i\u003csup\u003eth\u003c/sup\u003e treatment applied in the j\u003csup\u003eth\u003c/sup\u003e row and k\u003csup\u003eth\u003c/sup\u003e column for l\u003csup\u003eth\u003c/sup\u003e replication, \u0026micro; is the grand mean effect, α\u003csub\u003ei\u003c/sub\u003e is the i\u003csup\u003eth\u003c/sup\u003e treatment effect, β\u003csub\u003ej\u003c/sub\u003e is the j\u003csup\u003eth\u003c/sup\u003e row effect, γ\u003csub\u003ek\u003c/sub\u003e is the k\u003csup\u003eth\u003c/sup\u003e column effect, δ\u003csub\u003el\u003c/sub\u003e replication effect and ε\u003csub\u003eijkl\u003c/sub\u003e are uncorrelated random errors with zero mean and constant variance (δ\u003csup\u003e2\u003c/sup\u003e) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnalysis of Variance (ANOVA)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSource of Variations\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDegrees of Freedom (DF)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSum of Squares (SS)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean of Squares (MS)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eF-Values\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRows\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSSR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSSR/DFR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMSR/MSE\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eColumns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSSC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSSC/DFC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMSC/MSE\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreatments\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTrt-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSSTrt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSSTrt/DFTrt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMSTrt/MSE\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eError\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(RC-1) - (R-1) - (C-1) - (Trt-1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSSE/DFE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR*C-1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDF\u0026thinsp;=\u0026thinsp;Degree Freedom, R\u0026thinsp;=\u0026thinsp;Rows, C\u0026thinsp;=\u0026thinsp;Columns, Trt\u0026thinsp;=\u0026thinsp;Treatments, DFE\u0026thinsp;=\u0026thinsp;Degree Freedom of Error, DFR\u0026thinsp;=\u0026thinsp;Degree Freedom of Rows, DFC\u0026thinsp;=\u0026thinsp;Degree Freedom of Columns, DFTrt\u0026thinsp;=\u0026thinsp;Degree Freedom of Treatments, SSR\u0026thinsp;=\u0026thinsp;Sum Squares of Rows, SSC\u0026thinsp;=\u0026thinsp;Sum Squares of Columns, SSTrt\u0026thinsp;=\u0026thinsp;Sum Squares of Treatments, SSE\u0026thinsp;=\u0026thinsp;Sum Squares of Error, SST\u0026thinsp;=\u0026thinsp;Sum Squares of Total, MSE\u0026thinsp;=\u0026thinsp;Mean Squares of Error, MSR\u0026thinsp;=\u0026thinsp;Mean Squares of Rows, MSC\u0026thinsp;=\u0026thinsp;Mean Squares of Columns, MSTrt\u0026thinsp;=\u0026thinsp;Mean Squares of Treatments.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eEstimation of Variance Components\u003c/h2\u003e \u003cp\u003eThe phenotypic and genotypic variability of each quantitative trait was estimated as phenotypic and genotypic variances and coefficients of variation. These variance components were computed using the formula suggested by [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eHeritability and Genetic Advance\u003c/h2\u003e \u003cp\u003eThe proportion of phenotypic variance that is attributable to an overall genetic variance for the genotypes was estimated using broad sense heritability values by the formula adopted from [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eExpected genetic advance under selection (GA)\u003c/h2\u003e \u003cp\u003eGenetic advance (GA) in absolute unit and as percent of the mean (GAM), assuming selection of superior 5% of the genotypes were estimated in accordance with the methods illustrated as: - \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(GA = K * SDp * {H}^{2}b\\)\u003c/span\u003e\u003c/span\u003e Where, GA = Genetic advance, SDp = Phenotypic standard deviation on mean basis; H\u003csup\u003e2\u003c/sup\u003eb = Heritability in the broad sense. K = the standardized selection differential at 5% selection intensity (K\u0026thinsp;=\u0026thinsp;2.063).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eGenetic advance as percent of mean (GAM)\u003c/h2\u003e \u003cp\u003eGenetic advance as percent of mean was estimated as \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(GAM=\\frac{GA}{X}*100\\)\u003c/span\u003e\u003c/span\u003e Where, GAM\u0026thinsp;=\u0026thinsp;Genetic advance as percent of mean GA\u0026thinsp;=\u0026thinsp;Genetic advance, x̄ = Mean. The GAM was categorized as low (\u0026lt;\u0026thinsp;10%), moderate (10\u0026ndash;20%) and high (\u0026gt;\u0026thinsp;20%) [12].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eClustering of Genotypes\u003c/h2\u003e \u003cp\u003eThe cluster analysis was performed based on the Unweight Pair Group Method with Arithmetic Means (UPGM) clustering method from the Euclidean distance matrix.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003ePrincipal Component Analysis\u003c/h2\u003e \u003cp\u003ePrincipal component analysis (PCA) based on a correlation matrix was computed to find out the characters, which accounted for much of the total variation. Based on the principal component analysis the inter-relationship among a large set of variables in terms of a relatively small set of variables or components was assessed without losing any essential information of original data set.\u003c/p\u003e \u003c/div\u003e "},{"header":"RESULTS AND DISCUSSIONS","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003eAnalysis of Variances\u003c/h2\u003e \u003cp\u003eFrom the analysis of variance, the tested genotypes exhibited significant variation for days to flowering (DTF), stay green score (SGs), days to maturity (DTM), stand count (SC), drought tolerance score (DTs), plant height (PH), chlorophyll content (CHLc), grain filling period (GFP), panicle length (PL), harvest index (HI), panicle weight (PW), panicle yield (PY), thousand seed weight (TSW), grain filling rate (GFR) and grain yield (GY) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The result indicates that the tested genotypes were different in their potential to perform for variable characteristics at the tested location. Highly significant differences among sorghum genotypes with respect to days to flowering, days to maturity, plant height, head weight per plot, hundred seed weight, and grain yield also reported [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Similarly, significant differences in plant height, days to flowering, days to maturity, grain filling period, thousand seed weight, stay green, panicle exertion, panicle length, days to emergency, panicle width and grain yield were reported [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean squares from the analysis of variance (ANOVA) for 15 traits of 72 sorghum genotypes evaluated at Miesso Agricultural Research Station in 2021\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eMean Squares\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS/N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTraits\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTrt. (T-1) (Df\u0026thinsp;=\u0026thinsp;71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRow (R-1) (Df\u0026thinsp;=\u0026thinsp;23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCol (C-1) (Df\u0026thinsp;=\u0026thinsp;5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eErr (R*C)-T (Df\u0026thinsp;=\u0026thinsp;44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCV (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDTF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.77***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.24***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.13*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCHLc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.39.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.76\u003cb\u003e\u0026lsquo;.\u0026rsquo;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.75***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e7.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSGs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.0671***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.5987***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.0501*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.4485\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e29.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDTM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32.23***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.64***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.72**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e124.84***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74.06\u003cb\u003e\u0026lsquo;.\u0026rsquo;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.71ns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDTs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.7094*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.2276***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.4836ns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.4205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e37.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGFP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.32***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.99***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.95**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1095.16***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e654.96***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e393.56*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e152.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.65***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.07**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.75ns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e12.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12230.9***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12800***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12805.9*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3715.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5853.4***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7737.7***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27263***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70.98***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e76.26***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e150.29***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e28.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1399848***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e851509***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1232283***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e178278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGFR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e812.39***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e503.34***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e225.90**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e63.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e24.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTSW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.79***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.401\u003cb\u003e\u0026lsquo;.\u0026rsquo;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31.11ns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe significant codes indicate that if the P- value was in the range (0, 0.001), (0.001, 0.01), (0.01,0.05), P\u0026thinsp;\u0026gt;\u0026thinsp;0.05, it had a significance code of ***, **, *,. and ns\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eMean Performance of Genotypes\u003c/h2\u003e \u003cp\u003eThe range and mean values for 15 traits of 72 studied sorghum genotypes are indicated in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Grain yield ranged from 2102.82 Kg/ha to 6322.95 Kg/ha with an average value of 4253.4 Kg/ha. In general, three genotypes had a mean value greater than the best standard check (Melkam\u0026thinsp;=\u0026thinsp;4260 Kg/ha) for grain yield. Similar ranges and means for days to flowering, days to maturity, grain filling period and plant height are also reported.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRange and mean values for yield and agronomic traits of the test genotypes and standard check varieties.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTraits\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eTest Genotypes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eCheck Varieties\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOverall Mean\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMinimum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaximum\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAverage\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMelkam\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eArgiti\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eTilahun\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDTF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e86.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e75.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e72.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e82.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e76.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e77.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHLc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e53.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e54.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e51.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e48.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e52.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSGs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDTM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e112.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e135.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e124.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e116.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e126.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e119.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e123.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDTs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e70.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e48.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e46.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e58.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e53.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e47.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGFP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e61.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e49.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e40.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e45.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e42.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e46.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e131.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e246.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e189.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e147.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e215.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e163.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e193.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e20.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e20.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e21.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e295.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e816.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e555.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e408.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e641.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e333.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e494.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e184.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e525.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e355.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e323.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e409.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e217.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e339.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e33.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e24.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e17.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e26.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2102.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6322.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4212.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4253.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGFR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e43.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e140.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e92.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e105.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e132.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e84.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e93.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTSW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e30.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e28.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e24.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e28.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDTF\u0026thinsp;=\u0026thinsp;days to flowering, CHLc\u0026thinsp;=\u0026thinsp;chlorophyll content, SGs\u0026thinsp;=\u0026thinsp;stay green score, DTM\u0026thinsp;=\u0026thinsp;days to maturity, DTs\u0026thinsp;=\u0026thinsp;drought tolerance score, SC\u0026thinsp;=\u0026thinsp;stand count, GFP\u0026thinsp;=\u0026thinsp;grain filling period, PH\u0026thinsp;=\u0026thinsp;plant height, PL\u0026thinsp;=\u0026thinsp;panicle length, PW\u0026thinsp;=\u0026thinsp;panicle weight, PY\u0026thinsp;=\u0026thinsp;panicle yield, HI\u0026thinsp;=\u0026thinsp;harvest index, GY\u0026thinsp;=\u0026thinsp;grain yield, GFR\u0026thinsp;=\u0026thinsp;grain filling rate and TSW\u0026thinsp;=\u0026thinsp;thousand seed weight.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eEstimates of Variance Components\u003c/h2\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003ePhenotypic and Genotypic Coefficient of Variation\u003c/h2\u003e \u003cp\u003eGenotypic and phenotypic coefficient of variation ranged from 0.56% (stay green score) to 23.88% (harvest index) and 0.66% (stay green score) to 28.99% (harvest index), respectively (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). High PCV and GCV values were observed for harvest index, grain filling rate and grain yield. High PCV values indicate that selection on the basis of phenotype would be effective for most of the characters [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Traits with high GCV indicate the basic prerequisite on which positive response due to selection depends. Low GCV values were recorded for stay green score, grain filling period, panicle length, days to flowering, chlorophyll content and days to maturity indicating that improvement of these traits through selection would be less effective due to lack of genetic variability. Low PCV values were recorded for days to flowering, stay green score, chlorophyll content, drought tolerance score and days to maturity. These traits contribute a low magnitude of heritable genetic (additive) factor to the next generation, which indicates no need for investment to improve these traits aiming for sorghum improvement. The lower GCV and PCV values for different traits in the current study was in agreement with findings reported [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eEstimates of Heritability and Genetic Advance\u003c/h2\u003e \u003cp\u003eBroad sense heritability ranged from 25.56% for drought tolerance score to 86.87% for grain filling rate. High heritability values were noticed for grain filling rate, days to flowering, grain yield, thousand seed weight, plant height, days to maturity, harvest index and grain filling period (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). These variables' high heritability values suggested that genetics accounted for the majority of the variance seen and that environmental factors had less of an impact. Thus, under stressful situations, these characteristics could be employed as selection criteria. Because the environment masks the genotypic effects, selection may be extremely difficult or even impossible for a character with low heritability. Accordingly, choosing genotypes based on grain yield and attributes related to yield would be a more satisfying way to enhance the performance of sorghum genotypes, according to the results of the current study [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGenetic advance as a percentage of mean ranged from 1.11% for drought tolerance score to 43.4% for grain filling rate (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), indicating selection of the top 5% base population could result in an advance of 1.11% and 43.4% over the respective population. High genetic advance as percentage of mean was recorded for grain filling rate, harvest index, stand count, thousand seed weight, grain yield, panicle yield, panicle weight and plant height. High value, given as a percentage of mean, of the projected genetic advance observed for plant height and harvest index. When selection is based on characteristics with a sufficiently substantial genetic advancement as a percentage of mean, varieties will perform better for those traits [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eEstimates of variability components for fifteen traits of 72 sorghum genotypes evaluated at Miesso Agricultural Research Station during the 2021 growing season\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTraits\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eσ\u003csup\u003e2\u003c/sup\u003eg\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eσ\u003csup\u003e2\u003c/sup\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eσ\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ee\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGCV (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePCV (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eH\u003csup\u003e2\u003c/sup\u003eb (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eGA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eGAM (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDTF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e64.00\u0026ndash;86.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e77.00\u0026thinsp;\u0026plusmn;\u0026thinsp;1.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e5.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e6.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e85.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e8.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e11.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHLc\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45.47\u0026ndash;60.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e52.24\u0026thinsp;\u0026plusmn;\u0026thinsp;2.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e7.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e31.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e4.58\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSGs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00\u0026ndash;5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e2.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e40.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDTM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e112.00-135.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e123.00\u0026thinsp;\u0026plusmn;\u0026thinsp;1.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e4.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e70.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e7.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e5.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25.00\u0026ndash;70.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e47.00\u0026thinsp;\u0026plusmn;\u0026thinsp;4.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e47.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e88.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e40.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e14.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e19.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e54.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e10.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e22.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDTs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.00\u0026ndash;4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e1.73\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e25.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGFP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37.00\u0026ndash;61.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e46.00\u0026thinsp;\u0026plusmn;\u0026thinsp;2.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e16.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e26.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e11.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e63.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e6.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e14.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e131.67-246.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e193.94\u0026thinsp;\u0026plusmn;\u0026thinsp;8.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e553.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e714.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e160.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e12.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e13.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e77.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e42.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e21.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.17-26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e21.08\u0026thinsp;\u0026plusmn;\u0026thinsp;1.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e8.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e12.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e47.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e11.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e295.00-816.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e494.93\u0026thinsp;\u0026plusmn;\u0026thinsp;44.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5781.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9786.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4005.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e15.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e19.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e59.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e120.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e24.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePY.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e184.46\u0026ndash;525.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e339.65\u0026thinsp;\u0026plusmn;\u0026thinsp;36.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3107.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5781.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2673.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e16.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e22.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e53.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e84.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e24.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15.52\u0026ndash;46.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e26.62\u0026thinsp;\u0026plusmn;\u0026thinsp;3.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e40.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e59.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e19.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e23.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e28.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e67.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e10.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e40.53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2102.82-6322.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e4253.4\u0026thinsp;\u0026plusmn;\u0026thinsp;300.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e752491.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e933261.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e180769.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e20.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e22.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e80.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1604.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e37.66\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGFR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e43.34-140.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e93.50\u0026thinsp;\u0026plusmn;\u0026thinsp;5.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e446.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e514.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e67.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e22.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e24.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e86.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e40.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e43.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTSW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17.60\u0026ndash;36.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e28.03\u0026thinsp;\u0026plusmn;\u0026thinsp;1.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e12.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e14.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e71.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e6.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e22.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSEM\u0026thinsp;=\u0026thinsp;Standard error of mean, σ\u003csup\u003e2\u003c/sup\u003eg =genotypic variance, σ\u003csup\u003e2\u003c/sup\u003ee =environmental variance, σ\u003csup\u003e2\u003c/sup\u003ep =Phenotypic variance, PCV\u0026thinsp;=\u0026thinsp;Phenotypic coefficient of variation, GCV\u0026thinsp;=\u0026thinsp;Genotypic coefficient of variation, H\u003csup\u003e2\u003c/sup\u003eb\u0026thinsp;=\u0026thinsp;Broad sense heritability GA\u0026thinsp;=\u0026thinsp;Genetic advance in absolute unit, GAM\u0026thinsp;=\u0026thinsp;Genetic advance as percentage of mean, DTF\u0026thinsp;=\u0026thinsp;days to flowering, CHLc\u0026thinsp;=\u0026thinsp;chlorophyll content, SGs\u0026thinsp;=\u0026thinsp;stay green score, DTM\u0026thinsp;=\u0026thinsp;days to maturity, DTs\u0026thinsp;=\u0026thinsp;drought tolerance score, SC\u0026thinsp;=\u0026thinsp;stand count, GFP\u0026thinsp;=\u0026thinsp;grain filling period, PH\u0026thinsp;=\u0026thinsp;plant height, PL\u0026thinsp;=\u0026thinsp;panicle length, PW\u0026thinsp;=\u0026thinsp;panicle weight, PY\u0026thinsp;=\u0026thinsp;panicle yield, HI\u0026thinsp;=\u0026thinsp;harvest index, GY\u0026thinsp;=\u0026thinsp;grain yield, GFR\u0026thinsp;=\u0026thinsp;grain filling rate and TSW\u0026thinsp;=\u0026thinsp;thousand seed weight.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eClustering of Genotypes\u003c/h2\u003e \u003cp\u003eMost breeding programs utilize diverse parents which are genetically far apart from one another; cluster analysis usually finds the extent of genetic diversity and groups the crop with similar parents into one cluster [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. The analysis was based on an unweighted pair group method with an arithmetic means clustering method from euclidean distances matrix which grouped the 72 sorghum genotypes into five major clusters, consisting of 5 to 30 genotypes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Cluster I was the largest cluster consisting of 30 genotypes and accounted for 41.667% of the total genotypes. Cluster III was the second largest cluster followed by cluster IV which consists of 19 genotypes (26.389%) and 12 genotypes (16.667%) of the total genotypes respectively. Cluster II and V have the lowest number and percentage of the genotypes. Such genetic divergence among sorghum genotypes indicated that crossing between distantly related genotypes of these clusters might provide desirable recombinants.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of 72 sorghum genotypes in to five different clusters based on fifteen quantitative traits\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of Clusters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProportion of Genotypes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eList of Genotypes.\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCluster-I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30 (41.667%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eG1, G30, G2, G23, G32, G36, G68, G48, G67, G42, G59, G53, G55, G63, G51, G66, G8, G37, G9, G47, G10, G43, G15, G71, G13, G65, G20, G24, G49, G62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCluster-II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5 (6.944%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eG3, G33, G34, G45, G70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCluster-III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19 (26.389%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eG4, G17, G38, G54, G26, G56, G61, G72, G5, G28, G31, G50, G41, G6, G7, G52, G12, G22, G39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCluster-IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12 (16.667)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eG11, G21, G25, G16, G46, G18, G44, G58, G57, G64, G19, G60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCluster-V\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6 (8.333%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eG14, G27, G29, G35, G40, G69\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eCluster Mean Analysis\u003c/h2\u003e \u003cp\u003eThe mean values of fifteen quantitative characters distributed in to five clusters are presented in Table\u0026nbsp;7. Cluster I had mean values greater than overall mean for all traits except for days to flowering and stand count. Cluster II was distinguished from the others by having lower mean values than over all means for all traits except for panicle length, panicle weight, thousand seed weight and grain filling rate. The genotypes in cluster III had higher mean values for panicle weight, thousand seed weight, harvest index, panicle yield, grain filling rate and grain yield, which can be selected for further evaluation and could be suitable for improvement of sorghum yield under drought conditions. The low values of days to maturity and grain filling period in cluster II and days to flowering in cluster IV indicate the presence of early maturing genotypes, Thus, further evaluation of members of this cluster to develop early maturing variety would be promising option to improve the yield of sorghum for the area.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean values of five clusters based on fifteen studied traits of 72 sorghum genotypes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTraits\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCluster-I\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCluster-II\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCluster-III\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCluster-IV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCluster-V\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGM\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDTF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e77.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e77.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e77.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e78.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e74.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e77.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCHLc.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e53.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e498.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e52.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e51.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e55.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e52.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDTM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e124.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e118.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e123.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e123.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e128.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e123.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e44.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e50.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e57.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e47.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGFP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e41.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e47.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e45.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e54.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e46.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e195.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e152.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e192.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e195.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e241.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e193.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2122.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e20.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e24.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e21.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e579.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e816.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e495.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e415.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e550.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e494.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e418.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e306.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e348.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e278.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e184.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e339.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTSW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e22.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e26.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e27.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e26.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e28.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGFR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e100.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e94.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e93.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e87.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e78.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e93.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGY\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4643.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3847.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4333.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3909.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4205.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4261.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eDTF\u0026thinsp;=\u0026thinsp;days to flowering, CHLc\u0026thinsp;=\u0026thinsp;chlorophyll content, SGs\u0026thinsp;=\u0026thinsp;stay green score, DTM\u0026thinsp;=\u0026thinsp;days to maturity, DTs\u0026thinsp;=\u0026thinsp;drought tolerance score, SC\u0026thinsp;=\u0026thinsp;stand count, GFP\u0026thinsp;=\u0026thinsp;grain filling period, PH\u0026thinsp;=\u0026thinsp;plant height, PL\u0026thinsp;=\u0026thinsp;panicle length, PW\u0026thinsp;=\u0026thinsp;panicle weight, PY\u0026thinsp;=\u0026thinsp;panicle yield, HI\u0026thinsp;=\u0026thinsp;harvest index, GY\u0026thinsp;=\u0026thinsp;grain yield, GFR\u0026thinsp;=\u0026thinsp;grain filling rate and TSW\u0026thinsp;=\u0026thinsp;thousand seed weight.\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eGenetic Distance among Clusters\u003c/h2\u003e \u003cp\u003eThe range of variation present between genotypes determines the extent of improvement gained through selection and hybridization. The larger the distance between two clusters, the wider the genetic variability between them, for inclusion in the hybridization program [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The intra cluster distances ranged from 2.59702 to 3.12876 estimated by using Euclidian\u0026rsquo;s distance methods, indicating that the hybrids in clusters have dissimilarity in morphological features and performance (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). The intra-cluster distance was significantly smaller than the inter-cluster one, indicating that the groupings were heterogeneous inside and homogeneous between them. Cluster V exhibited the maximum intra-cluster distance, whilst cluster III displayed the lowest intra-cluster distance. The highest inter cluster distance was observed between cluster II and IV while the lowest inter cluster distance was observed between cluster I and IV. Lowest inter cluster distances were indicative of close relationship and similarity for most traits in the genotypes hence selection of parents from these clusters is to be avoided [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMaximum inter cluster distance indicates that genotypes falling in these clusters had wide diversity and can be used for improvement program to get better recombinants. Genotypes that were both agronomically excellent and genetically varied were chosen using inter-cluster distances. More opportunities for crossing over would result from dissimilar groups coming together, which breaks up unwanted links and releases latent potential variability [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. It is anticipated that offspring from these kinds of varied crossings will exhibit a broad range of genetic variability, which will increase the opportunity to identify transgressive segregants in later generations. From the mean analysis genotypes, G34, G45, G3, G50 and G39 are the most promising genotypes based on a combination of multiple studied traits.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAverage intra (bold) and inter (off diagonal) cluster distance among five clusters of 72 sorghum genotypes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo. of cluster\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCluster-I\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCluster-II\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCluster-III\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCluster-IV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCluster-V\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCluster-I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e2.90645\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.02052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.78664\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.02085\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.90981\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCluster-II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e3.00575\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.01958\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.29924\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.14042\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCluster-III\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e2.59702\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.95493\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.76775\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCluster-IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e2.68495\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.18341\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCluster-V\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003e3.12876\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThe genotypes employed for the evaluated characters showed a wide range of genetic diversity in this investigation, suggesting a high potential for use in trait enhancement. Furthermore, the presence of predicted GAM% and significant high heritability (H2) suggested possibilities for improving the traits through selection. From the principal component analysis, the first two principal components accounted for a cumulative of 39.5% of total variation indicating most of the important yield and yield attributing traits were present in these first two principal components. Cluster analysis based on unweighted pair group method with arithmetic means method grouped the 72 sorghum genotypes into five distinct clusters based on fifteen quantitative characters. Such genetic divergence among sorghum genotypes indicated that crossing between genotypes of these clusters might provide desirable recombinants and high yielding segregants. In general, based on the mean performance of genotypes, G14, G15 and G27 had a yield advantage over the best standard checks (Melkam). Genotypes, G34, G24, G40, G5, G29, G50, G27 and G49 are the most promising genotypes based on the combination of multiple traits. The overall study revealed the presence of wide genetic variability among the 72 sorghum genotypes evaluated which can be exploited to develop high-yielding varieties with desirable grain yield and early maturity in the study area where moisture stress is a critical problem for sorghum production.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank the Melkassa National Sorghum Research Program for their financial support to make the work possible. Great thanks to the research team for their every support, starting from planting to data collection. I wish to thank all of my friends and colleagues for their support.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSignificance Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn Ethiopia sorghum is predominantly grown in arid and semi-arid areas. However, the yield of sorghum is affected by severe and recurrent drought where rainfall is inadequate, non-uniform and erratic. Development of high yielding varieties require detailed knowledge of variation among the traits and the association among yield components. There is a need of conducting genetic variability to generate information for further breeding work to develop varieties for the moisture stressed areas. Therefore, the present study was designed to estimate genetic variability among sorghum genotypes for drought tolerance, and to determine the association of yield and yield related traits under drought stress condition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026rsquo;s contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe following tasks have been confirmed as being within our purview as the research paper\u0026apos;s authors: study idea and design; data collecting; analysis and interpretation of findings; and article writing. [Author 2] and [Author 3] designed the research study and secured funding. [Author 1] conducted the experiments, collected and analyses the data. The Author has the rights: (1) to use the manuscript in the Author\u0026apos;s teaching activities; (2) to publish the manuscript, or permit its publication, as part of any book the Author may write; (3) to include the manuscript in the Author\u0026apos;s own personal or departmental (but not institutional) database or on-line site.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConflicts of interest, often known as \u0026quot;competing interests,\u0026quot; arise when external factors influence or are thought to influence the impartiality or neutrality of research. It can occur at any point during the research cycle, including when a manuscript is being written, conducting experiments, or preparing an article for publication. Nonetheless, none of the research paper\u0026apos;s authors had any conflicts of interest to declare. Each and every author says that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAzarinasrabad A et al (2016) Evaluation of water stress on yield, its components and some physiological traits at different growth stages. grain sorghum genotypes 8(2):204\u0026ndash;210\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePaterson AH et al (2009) Sorghum bicolor genome Diversif grasses 457(7229):551\u0026ndash;556\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKidanemaryam W, Kassahun B, Taye TJJU (2018) \u003cem\u003eAssessment of Heterotic Performance and Combining Ability of Ethiopian Elite Sorghum (Sorghum bicolor (L.) Moench) Lines.\u003c/em\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGebretsadik R et al (2014) \u003cem\u003eA diagnostic appraisal of the sorghum farming system and breeding priorities in Striga infested agro-ecologies of Ethiopia.\u003c/em\u003e 123: pp. 54\u0026ndash;61\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAditya J, Bhartiya P, J.J.o.C A (2011) Genetic variability, heritability and character association for yield and component characters in soybean (G. max (L.) Merrill). 12(1):27\u0026ndash;34\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFAO FJR (2018) URL: http://faostat.fao. org, \u003cem\u003eFood and agriculture organization of the United Nations.\u003c/em\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRao NK et al (2004) Conserv utilization distribution sorghum germplasm 33:43\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEndalamaw C, Z.J.I.J.o.A B, Semahegn, Research B (2020) Genetic Variability and Yield Performance of Sorghum (sorghum bicolor L.) Genotypes Grown in Semi-Arid Ethiopia. 8(2):193\u0026ndash;213\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThomas R, Vaughan I (2013) and J.\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003eJ.A.g.f.s.E.-e\u003c/span\u003e\u003cspan address=\"http://J.A.g.f.s.E.-e\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Lello, \u003cem\u003eData analysis with R statistical software.\u003c/em\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBurton GW, De Vane dE (1954) \u003cem\u003eEstimating heritability in tall fescue (Festuca arundinacea) from replicated clonal material.\u003c/em\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFalconer D, Mackay FJH, Essex E (1996) \u003cem\u003eIntroduction to Quantitative Genetic 4th Edition Longman Group Limited.\u003c/em\u003e : pp. 108\u0026ndash;183\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJohnson HW, Robinson H, Comstock R (1956) \u003cem\u003eEstimates of genetic and environmental variability in soybeans.\u003c/em\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmare K et al (2015) \u003cem\u003eVariability for yield, yield related traits and association among traits of sorghum (Sorghum Bicolor (L.) 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Moench] Under Drought Stress Conditions\u003c/em\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePraveen Singh PS et al (2014) \u003cem\u003eGenetic divergence study in improved bread wheat varieties (Triticum aestivum).\u003c/em\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThoday JMJH (1960) \u003cem\u003eEffects of disruptive selection. III. Coupling and repulsion.\u003c/em\u003e 14: pp. 35\u0026ndash;49\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Ethiopian Institute of Agricultural Research","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Genetic Advance, Heritability, and Cluster Analysis","lastPublishedDoi":"10.21203/rs.3.rs-4577500/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4577500/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDrought is one of the most important factors that affect crop production worldwide and continues to be a challenge to plant breeders, despite many decades of research. Understanding the genetic variability among sorghum genotypes is the key objective to develop improved sorghum cultivars for drought-prone environments. The field experiment was conducted at Miesso during the 2021 main cropping season. A set of 72 sorghum genotypes advanced from a pedigree breeding approach was used in this study. The experiment was laid out using a Row-Column design with two replications. R statistical software was used to analyze the data. The analysis of variance indicated that there were significant variations among the tested genotypes for the studied traits. Genotypic and phenotypic coefficient of variation ranged from 0.56\u0026ndash;23.88% and 0.66\u0026ndash;28.99% respectively. Broad sense heritability ranged from 25.56\u0026ndash;86.87% while genetic advance as a percent of mean ranged from 1.11\u0026ndash;43.40%. Principal component analysis (PCA) revealed that five principal components with Eigenvalue greater than unity accounted for 74.1% of the total variation. Cluster analysis grouped the test genotypes into five clusters. Cluster I, II, III, IV, and V accounted for 41.667%, 6.944%, 26.389%, 16.667%, and 8.333% of the tested genotypes in that order. The highest intra-cluster distance was observed for cluster V whereas the maximum inter-cluster distance was observed between cluster IV and V. The lowest intra-cluster distance was observed for cluster III, whereas clusters I and III showed the lowest inter-cluster distance. The overall study revealed the presence of wide genetic variability among the studied sorghum genotypes in the study area where moisture stress is a critical problem for sorghum production.\u003c/p\u003e","manuscriptTitle":"Genetic Variability and Association of Traits among Sorghum Genotypes [Sorghum bicolor (L.) Moench] Under Drought Stress Area","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-14 05:31:48","doi":"10.21203/rs.3.rs-4577500/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2d815dd0-2a57-4bd3-a41c-692ea192802c","owner":[],"postedDate":"June 14th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":33223661,"name":"Plant Physiology and Morphology"}],"tags":[],"updatedAt":"2024-06-14T05:31:48+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-14 05:31:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4577500","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4577500","identity":"rs-4577500","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}