Genetic Variability and Association Analysis of Underground and Aboveground Morphological Characteristics of Wild Cicer Species and Cultivated Chickpeas

Genetic Variability and Association Analysis of Underground and Aboveground Morphological Characteristics of Wild Cicer Species and Cultivated Chickpeas | 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 Article Genetic Variability and Association Analysis of Underground and Aboveground Morphological Characteristics of Wild Cicer Species and Cultivated Chickpeas Fatma Basdemir This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7004526/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Oct, 2025 Read the published version in Acta Agriculturae Scandinavica, Section B — Soil & Plant Science → Version 1 posted You are reading this latest preprint version Abstract Background: Wild relative species of cultivated plants possess resistance genes to withstand a/biotic stresses to survive in their natural environments. Although aboveground morphological characteristics of wild species were evaluated in breeding programs, underground morphological characteristics have usually been ignored due to difficulties working with underground materials. Methods: The present study was therefore conducted to perform comparative analyses of the underground and aboveground morphological characteristics of wild Cicer species -including 20 accessions of Cicer reticulatum , and 6 accessions of Cicer echinospermum - and 1 variety of cultivated C. arietinum species. Root length (RL), root dry (RDW) and fresh weight (RFW), number of nodules per plant (NNP), nodule fresh (NFW) and dry weight per plant (NDW) in flowering time were studied as underground morphological characteristics. Plant height (PH), stem dry (SDW) and fresh weight (SFW) were recorded as above morphological characteristics. Results: Significant morphological differences were observed between the wild accessions and cultivated chickpeas cultivars. The wild Cicer species exhibited superior root development with higher nodule fresh and dry weight ratio compared to the cultivated chickpea. The wild accessions sustained their root development despite extremely dry and hot periods compared to the cultivated variety. For broad sense heritability estimates, root and shoot traits showed moderate to high heritability while nodule traits exhibited low heritability. Compared to the other traits, highest phenotypic and genotypic variance were observed NNP. Higher phenotypic variances observed for root and nodule traits indicated quantitative nature of inheritance and high impact of environmental factors for the traits. Genotypic correlation coefficients were found higher than phenotypic correlation coefficients in most of the characters, indicating the presence genetic association among traits which is important for reliable improvement through selection. Path coefficient analysis revealed that NNP, RDW, and SFW had strong positive direct effects on SDW, indicating their importance in enhancing biomass accumulation in chickpea. Principal component (PCI) analysis clearly distinguished wild accessions based on the evaluated traits and explained 79.54% of the total variation, with PC1 accounting for 68.10%. Traits contributing most strongly to PC1 included SDW, SFW, RFW and RDW. PC2 was influenced mostly by nodulation traits including NDW, NFW, and the NNP. Domestication appeared to favor aboveground traits in cultivated chickpea compared to wild accessions. These findings underline the potential of wild Cicer species as valuable genetic resources for developing drought-resistant varieties. Biological sciences/Genetics Biological sciences/Plant sciences Chickpea Cicer Biplot Nodule Principal Component Analyses Heritability Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Chickpeas ( Cicer arietinum L.), the second most widely cultivated legume after beans, account for a significant portion of global legume production. Chickpeas contribute approximately 15% to the global legume production (FAO 2022). Chickpeas contain vital sources of protein and essential nutrients, offering significant benefits for sustainable agriculture through their ability to fix atmospheric nitrogen symbiotically (Foyer et al. 2016, Verma et al. 2013). The genus Cicer , includes 10 annual and 36 perennial species (Toker et al. 2021). Among these species, C. arietinum is the only widely cultivated species in the world (Singh et al. 2014). Originating from the Fertile Crescent, chickpea was domesticated alongside other crops between 12 000–10 000 years ago in Türkiye and Syria (Zohary and Hopf 2000; von Wettberg et al. 2018), The wild progenitor, Cicer reticulatum ( C. reticulatum ) Ladiz., endemic to Southern and Eastern Türkiye (Toker et al. 2014), was first identified in the Savur district of Mardin (Ladizinsky 1975). Within the genetic pools of Cicer , C. reticulatum is in the primary gene pool, having full compatibility with the cultivated species of Cicer arietinum , whereas Cicer echinospermum belongs to the secondary gene pool. The first interspecific hybridizations were made by Ladizinsky and Adler (1976), and were successful with C. reticulatum , leading to fertile offspring, while hybrids with C. echinospermum partial infertility problems were encountered, with sterility rates increasing in subsequent generations. Recent studies indicate changes in compatibility between C. echinospermum populations and cultivated chickpeas (Kahraman et al. 2017). The narrow genetic base of cultivated chickpea has hindered significant genetic improvement in breeding programs (Singh et al. 2021). Expanding the genetic diversity of chickpeas through the introgression from wild relatives offers a promising strategy to introduce novel adaptive traits (Berger et al. 2020). Recent studies have shown significant differences between wild and cultivated Cicer species concerning important agronomic traits, which underscores the untapped potential of wild Cicer species as gene sources in breeding programs (von Wettberg et al. 2018). Domesticated chickpea have been extensively studied for root and nodule traits by researchers worldwide (Hazra et al. 2021, Verma et al. 2024, Zaheer et al. 2016). However, these traits have been less investigated in wild accessions. Systematic characterization and evaluation of wild relatives as gene sources will help to exploit unexplored variability (Ladizinsky 1993; Singh et al. 2022). The ongoing challenge of climate change accentuates the need for sustainable food solutions. Utilizing wild and landraces could play a crucial role in addressing food security under changing environmental conditions. Recognizing and understanding the differences between wild and cultivated species is essential for breeding high-quality, resilient seeds. The aim of this study was to characterize the morphological traits of annual wild Cicer species and to explore the relationships through genetic variability, heritability, correlations and Principal Component Analysis (PCA) among these traits. Materials & Methods 1. Plant materials A total of 27 Cicer accessions were used, including 20 C. reticulatum 6 C. echinospermum accessions, and one C. arietinum variety (Gökçe). The wild accessions were collected in 2013 from the Eastern and Southeastern Anatolia regions of Türkiye, with detailed collection site information provided in Table 1 (von Wettberg et al. 2018). Table 1. Geographic information of the collection sites for wild Cicer accessions from Eastern and Southeastern Anatolia, Türkiye. Type Number of accesions Accesions Latitude Longitude Elevation C. echinospermum 8 Cermik_075 38.05 39.42 770.30 ng Deste_080 37.78 39.17 738.86 14 Gunas_062 38.01 39.37 841.60 15 Karab_092 37.82 39.76 1264.41 18 Ortan_066 37.47 39.56 861.33 19 S2Drd_065 37.82 39.64 1125.82 C. reticulatum 1 Bari1_092 37.49 41.37 976.17 2 Bari2_072N2 37.46 41.38 961.33 3 Bari3_072C 37.47 41.39 960.62 4 Bari3_100 37.47 41.39 950.74 5 Bari3_106D 37.47 41.39 952.13 6 Besev_075 37.52 40.85 902.23 7 Besev_079 37.52 40.86 902.06 9 CudiA_152 37.43 42.49 1285.94 ng CudiB_022C 37.43 42.50 1366.59 10 Derei_070 37.54 41.02 992.83 11 Derei_072 37.54 41.02 992.42 12 Egil_065 38.27 40.06 987.44 13 Egil_073 38.27 40.06 988.06 ng Kalka_064 38.16 40.09 841.85 16 Kayat_077 37.52 40.94 1086.14 17 Kesen_075 38.20 39.61 890.61 ng Oyali_084 37.73 37.80 940.23 20 Sarik_067 37.55 41.02 1002.58 21 Savur_063 37.55 40.91 914.56 22 Sirnak_060 37.54 42.45 1658.92 ng: not germinated 2. Experimental site The study was conducted in the experimental site of the Department of Field Crops, Faculty of Agriculture, Dicle University, Diyarbakır, Türkiye, in 2018 growing season. Diyarbakır is located at 37°53′ N latitude and 40°16′ E longitude, with elevation of 680 m, and is characterized by a predominantly semi-arid climate (Figure 1). The experiments were laid out in a randomized complete block design with three replications. Due to limited seed availability of the wild accessions each plot consisted of two rows, each 1.0 m in length and spaced 40 cm apart. To enhance germination, seed coat nicking was performed on wild seeds prior to sowing. Weed control was managed through hand weeding. 3. Characteristics studied Measurements were taken at the onset of flowering, when the first flower appeared on each plant. Plants were carefully taken out from the soil using shovels and they were placed in containers filled with water to prevent respiration. Roots were cleaned of soil under running tap water and gently dried with soft paper (Figure 2). Plant parts (stem, root, and nodule) were separated, and measurements were taken for plant height, root length, nodule fresh weight, and number of nodules per plant. All samples were then dried in an oven at 70 °C for 48 hours to achieve a constant weight, after which dry weights of the stems, roots, and nodules were recorded. Due to non-germination of four wild accessions (three C. reticulatum and one C. echinospermum ) during the growing season, no measurement could be taken from these accessions. Data collected on plant basis were indicated as follow Plant length (PL), root length (RL), stem fresh weight (SFW), root fresh weight (RFW), stem dry weight (SDW), root dry weight (RDW), nodule fresh weight (NFW), nodule dry weight (NDW), number of nodules per plant (NNP). 4. Soil characteristics The study site features a semi-arid climate with distinct wet winters and dry summers. The trial soil was slightly alkaline (pH 7.65), moderately calcareous (11.7% calcium carbonate). The soil itself is classified as clay-textured (72.6% clay) with low organic matter content (0.70%), and nitrogen (6.23 mg/kg). The soil exhibits contrasting levels of essential nutrients: moderate to high in phosphorus (13.0 mg/kg), high K2O (1363.2 kg ha-1) calcium (0.2208 mmol/L), and iron (0.138 mmol/L). Prior to seeding, the seedbed was prepared in October using a disc harrow for deep tillage (15-20 cm), followed by a cultivator pass at a shallower depth (10-15 cm) and planking three days before sowing. 5. Climatic data Climatic data for the experimental site are given in Figure 2. Low rainfall was recorded in March (11.6 mm) and April (48.8 mm), whereas May had extreme rainfall (157.8 mm). In addition to low rainfall, the growing season experienced high temperatures. Maximum temperatures reached 16°C in February, 24°C in March, 29°C in April, and 33°C in May. The minimum temperatures recorded from February to May were 1°C, 1°C, 3°C, and 9°C, respectively (Figure3). 6. Data analysis Statistical analysis including means, minimum and maximum values, standard deviations, and cluster analysis were conducted using JMP PRO 13 software. Principal component analysis was performed using Genstat 12. Genetic parameter estimates were calculated using the R statistical software . The following formulas were used to estimate genotypic and phenotypic variance (Equation 1-7) components: Equation 1. Genotypic variance (σ 2 g) = (MSg-MSe)/r, where: MSg = mean square due to genotypes MSe = error mean square, r = the number of replication Equation 2. Phenotypic variance (σ 2 p) = (σ 2 g) + (σ 2 e) Environmental variance (σ 2 e) = Mean square error = MSe Phenotypic coefficient of variation (PCV) = ( √ σ 2p/ X ) *100 Genotypic Coefficient of variation (GCV) = GCV = ( √ σ 2g/ X ) *100 where: x = grand mean of a character. Equation 3. Broad sense heritability (h 2 )= (σ 2 g/σ 2 p)*100, where: σ 2 g =genotypic variance, σ 2 p = phenotypic variance Equation 4. Expected genetic advance (GA) = h 2 x k x σp, Equation 5. Expected genetic advance as percentage of mean (GAM) = (GAx100)/μ where: k = 2.06 (selection differential at 5% σp= the phenotypic standard deviation; h 2 = broad sense heritability and μ= the grand populations mean for the trait under considerations. Equation 6. Phenotypic coefficient of correlation (cp) = Pcov xy /√(σ 2 px.σ 2 py) Equation 7. Genotypic coefficient of correlation (cg) = Gcov xy /√( 2 gx. σ 2 gy) Where: cp = Phenotypic correlation coefficient, cg = Genotypic correlation coefficient, Pcov xy = Phenotypic covariance between variables x and y, Gcov xy = Genotypic covariance between variables x and y, σ 2 gx = Genotypic variance for trait X, σ 2 gy = Genotypic variance for trait Y, σ 2 px = Phenotypic variance for trait X, σ 2 py =Phenotypic variance for trait Y. Equation 8. The path coefficients were obtained using the general formula of Dewey and Lu (1959) by solving the following simultaneous equations (Equation 8), which express the basic relationship between correlation and path coefficient. rij=pij+Σrik.pkj Where: rij = mutual association between the independent character (i) and dependent character (j) as measured by the genotypic correlation coefficient. Pij= components of direct effects of the independent character (i)= On the dependent variable (j)= As measured by the genotypic path coefficient; and Σrik.pkj = summation of components of indirect effects of a given independent character (i) on a given dependent character (j) via all other independent character (k). The contribution of the remaining unknown factor was measured as the residual factor (pr), which is calculated as, pr = 1-rijPij Results Analysis of variance was conducted for nine traits and highly significant differences among the genotypes were found for all traits (Table 2). Table 2. Analysis of variance for the 9 traits of chickpea genotypes PH RL NNP NFW NDW RFW RDW SFW SDW Genotype Df=22 159.85*** 18.05* 566.13*** 0.21*** 0.021*** 2.22*** 0.21*** 104.41*** 8.25*** CV (%) 18 18 56 61 10 47 45 55 54 R 2 Value 0.55 0.16 0.43 0.36 0.27 0.55 0.51 0.49 0.51 Note: ***, **, * and ns indicate highly significant at 0.01%, highly significant at 0.1%, significant at 5% and non- significant respectively. CV: Coefficient of variations and Df: Degree of freedom. PH: Plant height, RL: Root length, NNP: Number of nodules per plant, NFW: Nodule fresh weight, NDW: Nodule dry weight, RFW: Root fresh weight, RDW: Root dry weight, SFW: Stem fresh weight, SDW: Stem dry weight. PH among wild accessions varied widely, ranging from 10.0 cm to 32.0 cm. Mean PH varied from 14.88 cm in Karab-092 to 32.5 cm in the Gökçe cultivated variety. Among C. reticulatum accessions, the highest PH was in Egil-073 (29.1 cm), while the lowest was in Besev-075 (16 cm) and Sirnak-060 (16.8 cm). C. echinospermum accession Cermik-075 had the highest PH (23.2 cm). PH was highest in C. arietinum species, about 34% and 46% higher than in C. reticulatum and C. echinospermum species respectively. PH ranking among the species was as follows: C. arietinum > C. reticulatum > C. echinospermum . RL among wild accessions also showed wide variation, ranging from 9.0 cm to 33.0 cm. Mean RL for the three Cicer species ranged from 13.5 cm in Karab-092 to 20.0 cm in Egil-065. Among C. reticulatum accessions, Egil-065 (20.0 cm) had the highest RL, while Derei-070 had the lowest. Cermik-075 had the highest RL among Cicer echinospermum accessions. Root/shoot length ratio in cultivated chickpeas was 59%, compared to 98% and 82% in C. echinospermum and C. reticulatum , respectively. Wild accessions indicated a wide variation in the NNP, ranging from 0.0 to 59.0 (Table 3). The mean NNP for the three Cicer species varied from 3.77 in Gunas-062 to 40.1 in Gökçe. Among the C. reticulatum accessions, Derei-072 had the highest NNP (32.77). For C. echinospermum accessions, Cermik-075 had the highest value (22.77) (Table 3). NFW varied widely among wild accessions, from 0.0 g to 1.09 g. Mean NFW for the three Cicer species ranged from 0.07 g in Gunas-062 to 0.78 g in Gökçe. The highest NFW among C. reticulatum accessions was observed in Derei-072 (0.65 g). Cermik-075 had the highest value among C. echinospermum accessions (0.50 g) (Table 3). NDW also observed wide variation among wild accessions, ranging from 0.0 g to 0.8 g. Mean NDW for the three Cicer species ranged from 0.01 g in Gunas-062 to 0.25 g in Ortan-066. The highest NDW among C. reticulatum accessions was observed in Derei-072 (0.13 g) (Table 3). RFW among wild accessions also showed wide variation, ranging from 0.12 g to 3.96 g. Mean RFW for the three Cicer species ranged from 0.36 g in Karab-092 to 2.06 g in Derei-072. Among C. reticulatum accessions, Besev-075 (mean 0.43 g) had the lowest RFW. Cermik-075 had the highest (mean 1.62 g) RFW among Cicer echinospermum accessions. RDW among C. reticulatum accessions ranged from 0.1 g in Besev-075 to 0.6 g in Egil-065. For C. echinospermum species, the lowest RDW was in Karab-092 (0.17 g). SFW varied widely among wild accessions, from 0.82 g to 25.75 g. Mean SFW for the three Cicer species ranged from 1.99 g in S2Drd-065 to 12.29 g in Egil-073. The lowest SFW among C. reticulatum accessions was observed in Besev-075 (Mean 2.84 g). Cermik-075 had the highest value among C. echinospermum accessions (Mean 11.36 g). SDW among wild accessions ranged from 0.2 g to 7.1 g. Mean SDW for the three Cicer species ranged from 0.5 g in S2DRD-065 to 3.7 g in Derei-072. In C. reticulatum , Derei-072 (3.7 g) had the highest stem dry weight. For C. echinospermum , the highest value was in Cermik-075 (3.02 g). Estimates of genetic parameters Genotypic and phenotypic coefficients of variation (GCV and PCV) estimates are key indicators used to assess the variability within a given population (Tadesse et al., 2016). In this study, estimates of genotypic and phenotypic variances (σ 2 g and σ 2 p), GCV and PCV, broad sense heritability, genetic advance and genetic advance as percent of mean are presented in Table 3. Table 3. Descriptive statistics, genotypic and phenotypic variances, coefficient of variability, broad sense heritability, and genetic advance as a percentage of the mean for the nine traits of Cicer genotypes tested in 2018 PH RL NNP NFW NDW RFW RDW SFW SDW Max 53 33 65 1.37 0.80 3.96 1.62 27.03 8.25 Min 10 9 0 0 0 0.12 0 0,82 0.24 Mean 21.28 17.87 16.65 0.35 0.08 0.96 0.33 6.37 1.76 MST 159.85 18.05 566.13 0.21 0.021 2.22 0,21 104,41 8,25 MSE 1.30 1.06 2.95 0.06 0.02 0.15 0.05 1.18 0.31 σ 2 g 16.05 0.86 54.19 0.02 0.001 0.22 0.02 10.20 0.82 σ 2 p 31.40 11,14 132.56 0.06 0.008 0.43 0.04 22.74 1.70 GCV (%) 18.82 5.20 44.21 39.93 49.37 49.09 44.53 50.15 51.46 PCV (%) 26.33 18.67 69.14 71.84 109.7 68.05 64.19 74.86 74.02 H 2 b (%) 51 77 41 31 20 52 48 45 48 GA 5.90 0.53 9.69 0.16 0.04 0.70 0.21 4.41 1.29 GAM 27.73 2.98 58.23 45.72 45.79 72.97 63.64 69.21 73.57 PH: Plant height, RL: Root length, NNP: Number of nodules per plant, NFW: Nodule fresh weight, NDW: Nodule dry weight, RFW: Root fresh weight, RDW: Root dry weight, SFW: Stem fresh weight, SDW: Stem dry weight. Max: Maximum, Min: Minimum, MST: Mean square of treatments, MSE: Mean square of error, σ2g: Genotypic variance, σ2p: Phenotypic variance H 2 b (%): Broad sense heritability in percent, GCV (%): Coefficient of genotypic variance, PCV (%): Coefficient of phenotypic variance, GA: Genetic advance, GAM: Genetic advance as percent of means The results for all characters in the present investigation showed that the phenotypic variance was higher in magnitude than genotypic variance (Table 3). Estimates of the phenotypic coefficient of variation in this study were also higher than their corresponding genotypic coefficient of variation, suggesting the influence of environmental factors on the expression of these traits. In the present study the highest phenotypic and genotypic variance were observed from the NNP (132.56 and 54.19), followed by PH (31.40 and 16.05) respectively. The smallest phenotypic and genotypic variance were found in NDW (0.008 and 0.001), followed by RDW (0.04 and 0.02) and NFW (0.06 and 0.06) respectively (Table 3). In this study, GCV ranged from 5.20% RL to 51.46% for SDW while PCV ranged from 18.67% for root length to 109.7% for NDW. The highest GCV and PCV values (>20%) were observed for SDW (51.46% and 74.02), SFW (50.15% and 74.86%), NDW (49.37% and 109.7%), RFW (49.09% and 68.05%), RDW (44.53% and 64.19%), NNP (44.21% and 69.14%) and NFW (39.93% and 71.84%) respectively. PH showed moderate GCV (18.82%) and high PCV (26.33%) while RL showed low GCV (5.20%) and moderate PCV (18.67%). Estimates of Heritability Broad sense heritability estimates for the studied characters varied from 20% for NDW to 77% for RL (Table 3). In general, high heritability estimates indicate that selection for the trait will be more effective as genetic factors predominantly control its expression while low heritability estimates indicate that environmental factors have high influence, making genetic improvement through selection more difficult (Tesfay Belay, 2018). Estimates of expected genetic advance The highest magnitude of genetic advance was observed for the NNP (9.69), while the lowest was recorded for NFW (0.16) (Table 3). According to Johnson et al. (1955), genetic advance as a percentage of the mean can be categorized as low (0–10%), moderate (10–20%) and high (≥20%). In this study, the expected genetic advance as a percantage of the mean ranged from 2.98% for RL to 72.97% for RFW (Table 3). Correlation of traits Estimates of genotypic and phenotypic correlation coefficients between each pair of trait are given (Table 4). Genotypic correlation coefficients were found higher than phenotypic correlation coefficients in most of the characters, indicating the presence genetic association among traits which is important for reliable improvement through selection. Plant height showed highly significant positive genotypic correlation with RL (0.731), NNP (0.669), NFW (0.641), RFW (0.573), RDW (0.591), SFW (0.855) and SDW (0.85). Nodule dry weight showed no significant genotypic correlation with PH, RL, SFW and SDW. No negative genotypic correlations were observed (Table 4). At phenotypic level, SDW showed positive highly significant positive correlations with SFW (0.873), RDW (0.799), RFW (0.741), PH (0.721), NNP (0.468), NFW (0.455), RL (0.233) and NDW (0.179). No negative and no significant phenotypic correlations were observed for any trait pair (Table 4). Table 4. Genotypic (below diagonal) and phenotypic (above diagonal) correlations coefficients of the 9 traits chickpea genotypes PH RL NNP NFW NDW RFW RDW SFW SDW PH 1 0.220** 0.532** 0.513** 0.237** 0.543** 0.543** 0.729** 0.721** RL 0.731** 1 0.189** 0.264** 0.232** 0.402** 0.242** 0.316** 0.233** NNP 0.669** 0.642** 1 0.849** 0.426** 0.499** 0.444** 0.451** 0.468** NFW 0.641** 0.717** 0.998** 1 0.473** 0.571** 0.470** 0.478** 0.455** NDW 0.302 ns 0.298 ns 0.464* 0.538** 1 0.321** 0.291** 0.179** 0.179** RFW 0.573** 0.917** 0.699** 0.722** 0.459* 1 0.844** 0.764** 0.741** RDW 0.591** 0.964** 0.676** 0.702** 0.432* 0.999** 1 0.708** 0.799** SFW 0.855** 0.917** 0.738** 0.720** 0.290 ns 0.870** 0.878** 1 0.873** SDW 0.85** 0.898** 0.777** 0.764 ** 0.349 ns 0.882** 0.86** 1.014** 1 Note: **, * and ns indicate highly significant at 0.1%, highly significant at 5%, and non- significant respectively. PH: Plant height, RL: Root length, NNP: Number of nodules per plant, NFW: Nodule fresh weight, NDW: Nodule dry weight, RFW: Root fresh weight, RDW: Root dry weight, SFW: Stem fresh weight, SDW: Stem dry weight. Path coefficient analysis SDW was taken as the dependent variable in the path analysis, which was performed at phenotypic and genotypic levels to identify the underlying traits and determine the key components contributing to biomass production (Tables 5 and 6). In most cases, the phenotypic direct and indirect effects were slightly higher than genotypic effects. Genotypic direct and indirect effects of various characters on stem dry weight Path coefficient analysis revealed that traits with strong positive direct effects on SDW were the NNP, RDW, and SFW, indicating their importance in enhancing biomass accumulation in chickpea. The highest positive direct effect of 2.732 was exhibited by RDW and followed by SFW (1.824), NNP (1.20) The direct effects exhibited by PH, RL, NFW and RFW were negative. On the other hand, traits with strong negative direct effects were PH, RL, NFW and RFW. The low residual value (0.0174) suggests that the majority of variation in SDW was explained by the traits included in the model. These findings highlight the importance of nodulation and biomass-related traits in breeding for higher stem productivity. Traits with the highest positive indirect effects on SDW were PH, NFW, and RFW, primarily through their influence on RDW and SFW. Although RFW had a strong negative direct effect on SDW, its positive indirect contributions via RDW and SFW suggest that it still plays an important role in improving biomass accumulation. Table 5. Estimate of direct effect (bold face and diagonal) and indirect effects (off diagonal) at genotypic level in 23 chickpea genotypes PH RL NNP NFW NDW RFW RDW SFW CG PH -0.60300 -0.17645 0.80377 -0.66524 0.09691 -1.78180 1.61580 1.56002 0.85** RL -0.44113 -0.24119 0.77137 -0.74415 0.09565 -2.85188 2.63635 1.67305 0.898** NNP -0.40363 -0.15494 1.20080 -1.03547 0.14900 -2.17281 1.84825 1.34634 0.777** NFW -0.38674 -0.17304 1.19874 -1.03725 0.17272 -2.24469 1.92045 1.31382 0.7764** NDW -0.18249 -0.07204 0.55874 -0.55947 0.32022 -1.42874 1.18253 0.53118 0.349 ns RFW -0.34571 -0.22132 0.83950 -0.74915 0.14721 -3.10791 2.73233 1.58789 0.882** RDW -0.35653 -0.23268 0.81211 -0.72891 0.13856 -3.10732 2.73285 1.60221 0.86** SFW -0.51567 -0.22120 0.88622 -0.74703 0.09324 -2.70525 2.40023 1.82424 1.014** Residual value (0.0174), Note: **, * and ns indicate highly significant at 0.1%, highly significant at 5%, and non- significant respectively. PH: Plant height, RL: Root length, NNP: Number of nodules per plant, NFW: Nodule fresh weight, NDW: Nodule dry weight, RFW: Root fresh weight, RDW: Root dry weight, SFW: Stem fresh weight, SDW: Stem dry weight, CG: Genotypic correlation Phenotypic direct and indirect effects of various traits on stem dry weight The phenotypic correlation coefficients were partitioned into direct and indirect effects by various biomass contributing traits (Table 6). SFW (0.541) showed the highest positive direct effect on SDW followed by RDW (0.447), PH (0.151) and NNP (0.094), while highest negative direct effect for SDW was showed for RFW (-0.112) followed RL (-0.018), NFW (-0.077) and NDW (-0.056). RFW, PH, NFW and NNP exerted highest positive indirect effect on SDW via RDW and SFW (0.380 and 0.413; 0.244 and 0.394; 0.211 and 0.248; 0.199 and 0.244) respectively. While NFW showed the highest negative indirect effect on SDW via RFW (-0.064) followed by PH (-0.061), NNP (-0.056), RL (-0.045), and NDW (-0.036). The contribution of residual factors that influenced SDW was very low at both genotypic and phenotypic levels indicating that the most important traits are recorded in this investigation. Table 6. Estimate of direct effect (bold face and diagonal) and indirect effects (off diagonal) at phenotypic level in 23 chickpea genotypes PH RL NNP NFW NDW RFW RDW SFW CP PH 0.15116 -0.00413 0.05042 -0.04040 -0.01332 -0.06132 0.24462 0.39478 0.721** RL 0.03328 -0.01876 0.01790 -0.02076 -0.01297 -0.04540 0.10900 0.17150 0.233** NNP 0.08054 -0.00355 0.09463 -0.06676 -0.02386 -0.05639 0.19991 0.24439 0.468** NFW 0.07771 -0.00496 0.08039 -0.07759 -0.02754 -0.06451 0.21103 0.25857 0.455** NDW 0.03611 -0.00436 0.04050 -0.03881 -0.05646 -0.03677 0.14282 0.09828 0.179** RFW 0.08218 -0.00755 0.04731 -0.04495 -0.01817 -0.11279 0.38068 0.41388 0.741** RDW 0.08212 -0.00454 0.04202 -0.03683 -0.01768 -0.09536 0.44728 0.38331 0.799** SFW 0.11027 -0.00595 0.04273 -0.03755 -0.01012 -0.08626 0.31891 0.54117 0.873** Residual value (0.1473), Note: **, * and ns indicate highly significant at 0.1%, significant at 5%, and non- significant, respectively. PH: Plant height, RL: Root length, NNP: Number of nodules per plant, NFW: Nodule fresh weight, NDW: Nodule dry weight, RFW: Root fresh weight, RDW: Root dry weight, SFW: Stem fresh weight, SDW: Stem dry weight, CP: Phenotypic correlation. Principal Component Analysis The percentage of variation explained by the two most informative principal components (PC1 and PC2) and the vector loadings for each morphological trait in three different annual Cicer species are given in Table 7 and Figure 2. Table 7. Principal Component analysis on Cicer arietinum , Cicer reticulatum , and Cicer echinopspermum species. C.reti+C.echi+C.arie C.reti+C.echi+C.arie C.reti C.reti C.echi C.echi Parameter PC1 PC2 PC1 PC2 PC1 PC2 Eigenvalue 6.128 1.029 6.319 1.341 6.051 1.657 The proportion of variance (%) 68.10 11.44 70.22 14.91 56.16 41.52 Cumulative variance (%) 68.10 79.54 70.22 85.13 56.16 97.68 Characters*with greater weighting *SDW * NDW *RDW *PH *PH *NFW *SFW *NFW *RFW *RL *SDW * NDW *RFW *RDW *NFW *NNP *SDW *SFW *NDW *RFW *SFW *RDW *NNP C.reti: Cicer reticulatum , C.echi: Cicer echinospermum , C.ari: Cicer arietinum , SDW: Stem dry weight, SFW: Stem fresh weight, RFW: Root fresh weight, RDW: Root dry weight, NFW: Nodule fresh weight, NDW: Nodule dry weight, NNP: Number of nodules per plant, PH: Plant height, RL: Root length. In the combined analysis of C. reticulatum , C. echinospermum , and C. arietinum , the first two principal components (PCs) explained 79.54% of the total variation, with PC1 accounting for 68.10%. Traits contributing most strongly to PC1 included SDW, SFW, RFW and RDW. PC2 was influenced mostly by nodulation traits including NDW, NFW, and the NNP (Figure 4 and 5). The first two PCs explained 85.13% of the variation in C. reticulatum , with PC1 alone accounting for 70.22%. The PC1 was greatly influenced by traits such as RDW, RFW, SDW, SFW, and NDW. In PC2, PH and RL were important morphological traits with greater influence (Figure 5, 6 and 7). The PCA biplot supported the groupings identified in Biplot-Cluster analysis. Figure 5 indicates that PC1 and PC2 clearly distinguished wild accessions based on the evaluated traits. Ortan-066, a C. echinospermum accession, was the most distinct genotype for the traits investigated. Among the C. reticulatum accessions, Kayat-077 showed a strong association with RL (Figure 3). Also, C. reticulatum accessions of Egil_065, Egil_073 and Kayat_077 and C. echinospermum accession of Cermik-075 were closely related to all measured traits (Figure 6 and 7). For C. echinospermum , the first two PCs explained 97.68% of the variation. In PC1, PH, SDW, RFW, SFW, RDW and RL were the traits with the greatest influence. In PC2, the important traits were NFW and the NNP (Table 7). K-mean cluster analysis grouped all Cicer accessions into three distinct clusters (Figure 8). The first cluster contained Cermik-075, Derei-072 and Egil-065 accessions. the other accessions (Egil-073, Gökçe, Kayat-077, Ortan-066, S2DRD-065, Gunas-062, Karab-092) were distributed among the other two clusters. K-mean cluster analysis of C. reticulatum accessions were divided into three distinc groups (Figure 8). The first cluster contained only Derei-072, while the second cluster contained Egil-065 and Egil-073 accessions. The remaining ten accessions were included in a separate cluster. Interestingly four accessions (Bari1_092, Bari3_072C, Besev_075 and Kayat_077) did not group with these three primary clusters. Discussion Wild relatives of chickpea are important genetic resources to expand genetic variation and transfer of agronomically important traits. This study aimed to explore some important morphological characteristics of different Cicer species by investigating both cultivated genotypes ( C. arietinum ) and wild accessions ( C. reticulatum and C. echinospermum ). Numbers of nodules per plant, fresh and dry nodule weight in both cultivated and wild accessions were negatively affected by hot and dry conditions during the crop growth. This finding is consistent with Kantar et al. ( 2003 ), who also reported that the nodule dry weight was decreased in dry season. Although the number of nodules per plant was higher in cultivated genotypes, the nodule fresh and dry weight per plant, as well as the ratio of nodules, was found to be higher in wild accessions. C. echinospermum had 12% higher nodule fresh weight and 42% higher nodule dry weight compared to cultivated genotypes. These findings align with previous research by Jaiswal and Singh ( 1990 ), who reported that C. reticulatum exhibited a higher number of nodules per plant and greater fresh weight compared to cultivated chickpeas. Additionally, Kim et al. ( 2014 ) reported that nodule cultivation in chickpea varieties reduces symbiont diversity, while C. reticulatum wild accessions showed wider variation in symbionts compared to cultivated chickpeas. Istanbuli et al. ( 2022 ) noted drought stress decreased nodule characteristics, with tolerant genotypes exhibiting higher nodule characteristics compared to susceptible genotypes. In summary, the data indicates significant variability in nodule formation among different Cicer species and accessions, with wild species generally exhibiting a higher number of nodules compared to cultivated varieties. This variability emphasizes the genetic potential of wild accessions for enhancing nodule traits in breeding programs. These findings suggest that wild accessions may have greater potential for forming beneficial symbiotic relationships with soil microorganisms, which could contribute to their superior nodule characteristics under hot and dry conditions. The data indicates substantial variability in plant height, root length, and root and stem dry weight among the Cicer species. Wild species generally exhibit more variability compared to cultivated varieties, which can be crucial for breeding programs aimed at improving these traits. Cultivated chickpea varieties were characterized by taller plants with greater stem and root development compared to wild accessions. These results are consistent with Singh et al. ( 2014 ), who also reported that C. arietinum species exhibited greater plant height compared to wild species. Also, Robertson et al. ( 1997 ) noted marked variations in morphological characteristics between annual wild Cicer species and cultivated chickpeas, including leaf area and growth habits. The root/shoot length ratio is an important indicator of plant growth and development, as well as crop yield and quality. This study found that the root/shoot length ratio was higher in wild accessions than in cultivated chickpeas. Wild accessions had a more robust root system compared to cultivated chickpeas. These findings are consistent with Serraj et al. ( 2004 ), who determined a linear relationship. Berger et al. ( 2020 ) found that wild Cicer species in late types had relatively greater root systems. This relationship has important implications for crop breeding and improvement, as it provides a potential for enhancing plant growth and yield. The 2018 growing season was marked by hot and dry conditions, except for May. Wild accessions exhibited a higher root/shoot length ratio than cultivated varieties that might be an indicative potential tolerance to drought and heat stress. Greater root development in wild species was found to promote under early and late drought conditions. Pang et al. ( 2023 ) reported that plants possess the ability to adapt their root characteristics to improve in various soil environments. Kashiwagi et al. ( 2008 ) and Kumar et al. ( 2012 ) suggested that the root system and root depth are key factors in coping with drought stress and promoting growth in dry conditions. However, Kashiwagi et al. ( 2005 ) and Gaur et al. ( 2008 ) report that wild species have relatively poor root and biomass development compared to cultivated varieties. These discrepancies may be due to differences in genetic background or environmental conditions. Zaman-Allah et al. ( 2011 ) suggested that the variation in root growth components, including depth, length density, and dry weight, was not significantly different between drought-tolerant and susceptible chickpea genotypes. Additionally, Purushothaman et al. ( 2017 ) observed that in response to drought, root distribution decreased at the soil surface but increased at depths below 30 cm. Water uptake from the soil was found to have a maximum depth of 45–60 cm under dry conditions, while it branched at depths of 15–30 cm and 30–45 cm under irrigated conditions. The presence of genotypic and phenotypic variability among genotypes is important for determining the effectiveness of breeding programs (Tsehaye et al. 2020 ). The highest phenotypic and genotypic variance were observed for nodules per plant and plant height even though they were highly effected from environment. The correlation coefficient is an index representing the proportion of shared causative factors between two variables (Bowley, 1920 ). In most cases, the genotypic correlation coefficients were greater in magnitude than the phenotypic ones, suggesting strong inherent genetic relationships among traits that were less influenced by environment (Jakhar, 2014). PCA effectively differentiates Cicer accessions based on their morphological traits. The high percentage of variation explained by the first two principal components highlights the significance of these traits in distinguishing between accessions. PCA is a valuable tool for dimensionality reduction and identification of the most influential traits (Jolliffe and Cadima 2016 ). For instance, the strong influence of root and nodule traits on the principal components suggests these traits should be prioritized in breeding programs for drought resistance (Kashiwagi et al. 2008 ). This observed diversity is crucial for breeding programs aimed at improving drought tolerance and other agronomic traits (Berger et al. 2020 ). Easily measurable phenotypic traits-such as morphological, anatomical, and phenological characteristics-that are clearly distinguishable in the field and cost-effective to assess can be valuable tools for pre-breeding programs, especially in developing countries where crops are often grown in marginal environments. Crop wild relatives (CWRs), commonly used in breeding programs as sources of resistance to biotic stresses, often carry additional traits that enable them to thrive in marginal environments. Through natural selection over evolutionary time, these wild progenitors have developed the ability to maintain fitness under a wide range of environmental stresses. In contrast, modern breeding-focused on broad adaptation and uniformity-has led to reduced genetic diversity and increased vulnerability to both biotic and abiotic challenges. Harnessing the genetic heterogeneity found in wild relatives offers a valuable opportunity for developing cultivars better suited to the demands of marginal lands. Conclusions This study aimed to determine the importance of wild chickpea species as a genetic resource for breeding programs to enhance chickpea tolerance to abiotic stress factors, such as drought, in semi-arid climatic conditions. The genetic diversity presents in wild species, Cicer reticulatum and Cicer echinospermum , demonstrated a vast genetic resource that that holds great potential for plant breeding studies. The findings of this study demonstrated that the root system and nodule traits of wild species have significant potential in coping with drought stress. These traits can be valuable in breeding programs aimed at developing more resilient chickpea varieties, thereby contributing to sustainable agriculture in regions affected by climate change and water scarcity. Declarations Competing interests The author(s) declare no competing interests. Author Contribution The author Fatma Basdemir contributed to the study conceptualization, investigation, formal analysis, visualization, data curation and writing-original draft. Acknowledgement The author would like to express their gratitude to Abdullah Kahraman from the Faculty of Agriculture at Harran University for generously providing the annual wild Cicer seeds that were utilized in this study. Author is incredibly grateful to Behiye Tuba Biçer from the Faculty of Agriculture at Dicle University for her invaluable contribution to managing the experiment and writing the paper. Her expertise and dedication were crucial to the success of the research. Data Availability Data is provided within the manuscript files References Berger, J., Pushpavalli, R., Ludwig, C., Parsons, S., Basdemir, F. & Whisson, K. Wild and domestic differences in plant development and responses to water deficit in Cicer . Front. 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Research in Microbiology 167 , 510–520 (2016). https://doi.org/10.1016/j.resmic.2016.04.001 Zaman-Allah, M., Jenkinson, D. M. & Vadez, V. A conservative pattern of water use, rather than deep or profuse rooting, is critical for the terminal drought tolerance of chickpea. J Exp Bot. 62 , 4239–4252 (2011). https://doi.org/10.1093/jxb/err139 Zohary, D. & Hopf, M. Domestication of Plants in the Old World: The Origin and Spread of Cultivated Plants in West Asia, Europe, and the Nile Valley . (Oxford University Press, 2000). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 29 Oct, 2025 Read the published version in Acta Agriculturae Scandinavica, Section B — Soil & Plant Science → 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. 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13:15:55","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":857297,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative plants of wild (a) and cultivated (b) Cicer accessions after removal from the soil.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7004526/v1/330bd25a5463fcd8ea584702.png"},{"id":86334682,"identity":"727fb2d6-fe3e-4e4f-b8f8-1b14ccffb60d","added_by":"auto","created_at":"2025-07-09 13:07:55","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":68367,"visible":true,"origin":"","legend":"\u003cp\u003eClimatic data for experiment area (https://mgm.gov.tr/Diyarbakir/Turkiye)\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7004526/v1/8eddbb938aa6e3f25f79fa1b.png"},{"id":86335535,"identity":"84c4c9dd-5e45-4c48-a032-aa098568a103","added_by":"auto","created_at":"2025-07-09 13:15:55","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":49280,"visible":true,"origin":"","legend":"\u003cp\u003eRelationships among morphological traits, their association with genotypes, and trait-based grouping patterns across three \u003cem\u003eCicer\u003c/em\u003e species (\u003cem\u003eC. arietinum\u003c/em\u003e, \u003cem\u003eC. reticulatum\u003c/em\u003e, and \u003cem\u003eC. echinospermum\u003c/em\u003e).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7004526/v1/80b45aab21dc179f33340812.png"},{"id":86334694,"identity":"c3f2d771-29b2-4c49-a594-6aef3f7d7bc5","added_by":"auto","created_at":"2025-07-09 13:07:55","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":63492,"visible":true,"origin":"","legend":"\u003cp\u003eRanking and comparison of genotypes based on the mean values of morphological traits accross three \u003cem\u003eCicer\u003c/em\u003especies (\u003cem\u003eC. arietinum\u003c/em\u003e, \u003cem\u003eC. reticulatum\u003c/em\u003e, and \u003cem\u003eC. echinospermum\u003c/em\u003e).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7004526/v1/ca0c20ea8925bbac4bac84e6.png"},{"id":86334693,"identity":"07bb9326-286d-4580-9bc4-92ccc8471343","added_by":"auto","created_at":"2025-07-09 13:07:55","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":46846,"visible":true,"origin":"","legend":"\u003cp\u003eRelationships among traits, genotype-trait associations, and grouping pattern of the traits within \u003cem\u003eCicer reticulatum\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7004526/v1/3efce0340ca522a5ad350f5d.png"},{"id":86335537,"identity":"b42e316f-13ce-4924-9c4e-bf012acb7192","added_by":"auto","created_at":"2025-07-09 13:15:55","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":58883,"visible":true,"origin":"","legend":"\u003cp\u003eRanking and Comparison of genotypes based on mean values of morphological traits in \u003cem\u003eCicer reticulatum\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7004526/v1/c8b8f46428b3d2067795cfe8.png"},{"id":86334695,"identity":"5b68fb0a-c7e8-42b0-bc7c-d5e84248b9be","added_by":"auto","created_at":"2025-07-09 13:07:55","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":89496,"visible":true,"origin":"","legend":"\u003cp\u003eGouping of three \u003cem\u003eCicer \u003c/em\u003especies accessions based on morphological traits (left side) and subgrouping of \u003cem\u003eCicer reticulatum\u003c/em\u003eaccessions according to the investigated traits (right side).\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-7004526/v1/039cf4d3f43d50f66e8d35e6.png"},{"id":94886373,"identity":"530c8724-4a16-454f-83b7-36cd6b95d349","added_by":"auto","created_at":"2025-10-31 18:37:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4636933,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7004526/v1/3683ef90-33fe-4203-a220-02c48a2c5ea7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Genetic Variability and Association Analysis of Underground and Aboveground Morphological Characteristics of Wild Cicer Species and Cultivated Chickpeas","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChickpeas (\u003cem\u003eCicer\u003c/em\u003e \u003cem\u003earietinum\u003c/em\u003e L.), the second most widely cultivated legume after beans, account for a significant portion of global legume production. Chickpeas contribute approximately 15% to the global legume production (FAO 2022). Chickpeas contain vital sources of protein and essential nutrients, offering significant benefits for sustainable agriculture through their ability to fix atmospheric nitrogen symbiotically (Foyer et al. 2016, Verma et al. 2013).\u003c/p\u003e\n\u003cp\u003eThe genus \u003cem\u003eCicer\u003c/em\u003e, includes 10 annual and 36 perennial species (Toker et al. 2021). Among these species, \u003cem\u003eC. arietinum\u003c/em\u003e is the only widely cultivated species in the world (Singh et al. 2014). Originating from the Fertile Crescent, chickpea was domesticated alongside other crops between 12 000\u0026ndash;10 000 years ago in T\u0026uuml;rkiye and Syria (Zohary and Hopf 2000; von Wettberg et al. 2018), The wild progenitor, \u003cem\u003eCicer reticulatum\u003c/em\u003e (\u003cem\u003eC. reticulatum\u003c/em\u003e) Ladiz., endemic to Southern and Eastern T\u0026uuml;rkiye (Toker et al. 2014), was first identified in the Savur district of Mardin (Ladizinsky 1975).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWithin the genetic pools of \u003cem\u003eCicer\u003c/em\u003e, \u003cem\u003eC. reticulatum\u003c/em\u003e is in the primary gene pool, having full compatibility with the cultivated species of \u003cem\u003eCicer arietinum\u003c/em\u003e, whereas \u003cem\u003eCicer echinospermum\u003c/em\u003e belongs to the secondary gene pool. The first interspecific hybridizations were made by Ladizinsky and Adler (1976), and were successful with \u003cem\u003eC. reticulatum\u003c/em\u003e, leading to fertile offspring, while hybrids with \u003cem\u003eC. echinospermum\u003c/em\u003e partial infertility problems were encountered, with sterility rates increasing in subsequent generations. Recent studies indicate changes in compatibility between \u003cem\u003eC. echinospermum\u003c/em\u003e populations and cultivated chickpeas (Kahraman et al. 2017).\u003c/p\u003e\n\u003cp\u003eThe narrow genetic base of cultivated chickpea has hindered significant genetic improvement in breeding programs (Singh et al. 2021). Expanding the genetic diversity of chickpeas through the introgression from wild relatives offers a promising strategy to introduce novel adaptive traits (Berger et al. 2020). Recent studies have shown significant differences between wild and cultivated \u003cem\u003eCicer\u003c/em\u003e species concerning important agronomic traits, which underscores the untapped potential of wild \u003cem\u003eCicer\u003c/em\u003e species as gene sources in breeding programs (von Wettberg et al. 2018). Domesticated chickpea have been extensively studied for root and nodule traits by researchers worldwide (Hazra et al. 2021, Verma et al. 2024, Zaheer et al. 2016). However, these traits have been less investigated in wild accessions. Systematic characterization and evaluation of wild relatives as gene sources will help to exploit unexplored variability (Ladizinsky 1993; Singh et al. 2022).\u003c/p\u003e\n\u003cp\u003eThe ongoing challenge of climate change accentuates the need for sustainable food solutions. Utilizing wild and landraces could play a crucial role in addressing food security under changing environmental conditions. Recognizing and understanding the differences between wild and cultivated species is essential for breeding high-quality, resilient seeds. \u0026nbsp;The aim of this study was to characterize the morphological traits of annual wild \u003cem\u003eCicer\u003c/em\u003e species and to explore the relationships through genetic variability, heritability, correlations and Principal Component Analysis (PCA) among these traits.\u003c/p\u003e"},{"header":"Materials \u0026 Methods","content":"\u003cp\u003e\u003cstrong\u003e1. Plant materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 27 \u003cem\u003eCicer\u003c/em\u003e accessions were used, including 20 \u003cem\u003eC. reticulatum\u003c/em\u003e 6 \u003cem\u003eC. echinospermum\u003c/em\u003e accessions, and one \u003cem\u003eC. arietinum\u003c/em\u003e variety (G\u0026ouml;k\u0026ccedil;e). The wild accessions were collected in 2013 from the Eastern and Southeastern Anatolia regions of T\u0026uuml;rkiye, with detailed collection site information provided in Table 1 (von Wettberg et al. 2018).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Geographic information of the collection sites for wild \u003cem\u003eCicer\u003c/em\u003e accessions from Eastern and Southeastern Anatolia, T\u0026uuml;rkiye.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"82%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eType\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of accesions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAccesions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLatitude\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLongitude\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eElevation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"6\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cem\u003eC. echinospermum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eCermik_075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e38.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e39.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e770.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003eng\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eDeste_080\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e37.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e39.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e738.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eGunas_062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e38.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e39.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e841.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eKarab_092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e37.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e39.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e1264.41\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eOrtan_066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e37.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e39.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e861.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eS2Drd_065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e37.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e39.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e1125.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"20\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cem\u003eC. reticulatum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eBari1_092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e37.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e41.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e976.17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eBari2_072N2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e37.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e41.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e961.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eBari3_072C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e37.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e41.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e960.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eBari3_100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e37.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e41.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e950.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eBari3_106D\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e37.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e41.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e952.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eBesev_075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e37.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e40.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e902.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eBesev_079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e37.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e40.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e902.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eCudiA_152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e37.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e42.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e1285.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003eng\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eCudiB_022C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e37.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e42.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e1366.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eDerei_070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e37.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e41.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e992.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eDerei_072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e37.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e41.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e992.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eEgil_065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e38.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e40.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e987.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eEgil_073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e38.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e40.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e988.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003eng\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eKalka_064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e38.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e40.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e841.85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eKayat_077\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e37.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e40.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e1086.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eKesen_075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e38.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e39.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e890.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003eng\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eOyali_084\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e37.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e37.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e940.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eSarik_067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e37.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e41.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e1002.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eSavur_063\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e37.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e40.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e914.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003eSirnak_060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e37.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e42.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e1658.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eng: not germinated\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2. \u0026nbsp;Experimental site\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in the experimental site of the Department of Field Crops, Faculty of Agriculture, Dicle University, Diyarbakır, T\u0026uuml;rkiye, in 2018 growing season. Diyarbakır is located at 37\u0026deg;53\u0026prime; N latitude and 40\u0026deg;16\u0026prime; E longitude, with elevation of 680 m, and is characterized by a predominantly semi-arid climate (Figure 1). The experiments were laid out in a randomized complete block design with three replications. Due to limited seed availability of the wild accessions each plot consisted of two rows, each 1.0 m in length and spaced 40 cm apart. To enhance germination, seed coat nicking was performed on wild seeds prior to sowing. Weed control was managed through hand weeding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3. \u0026nbsp;Characteristics studied\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMeasurements were taken at the onset of flowering, when the first flower appeared on each plant. Plants were carefully taken out from the soil using shovels and they were placed in containers filled with water to prevent respiration. Roots were cleaned of soil under running tap water and gently dried with soft paper (Figure 2). Plant parts (stem, root, and nodule) were separated, and measurements were taken for plant height, root length, nodule fresh weight, and number of nodules per plant. All samples were then dried in an oven at 70 \u0026deg;C for 48 hours to achieve a constant weight, after which dry weights of the stems, roots, and nodules were recorded. Due to non-germination of four wild accessions (three \u003cem\u003eC. reticulatum\u003c/em\u003e and one \u003cem\u003eC. echinospermum\u003c/em\u003e) during the growing season, no measurement could be taken from these accessions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData collected on plant basis were indicated as follow\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePlant length (PL), root length (RL), stem fresh weight (SFW), root fresh weight (RFW), stem dry weight (SDW), root dry weight (RDW), nodule fresh weight (NFW), nodule dry weight (NDW), number of nodules per plant (NNP).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4. \u0026nbsp;Soil characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study site features a semi-arid climate with distinct wet winters and dry summers. The trial soil was slightly alkaline (pH 7.65), moderately calcareous (11.7% calcium carbonate). The soil itself is classified as clay-textured (72.6% clay) with low organic matter content (0.70%), and nitrogen (6.23 mg/kg). The soil exhibits contrasting levels of essential nutrients: moderate to high in phosphorus (13.0 mg/kg), high K2O (1363.2 kg ha-1) calcium (0.2208 mmol/L), and iron (0.138 mmol/L). Prior to seeding, the seedbed was prepared in October using a disc harrow for deep tillage (15-20 cm), followed by a cultivator pass at a shallower depth (10-15 cm) and planking three days before sowing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e5. Climatic data\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eClimatic data for the experimental site are given in Figure 2. Low rainfall was recorded in March (11.6 mm) and April (48.8 mm), whereas May had extreme rainfall (157.8 mm). In addition to low rainfall, the growing season experienced high temperatures. Maximum temperatures reached 16\u0026deg;C in February, 24\u0026deg;C in March, 29\u0026deg;C in April, and 33\u0026deg;C in May. The minimum temperatures recorded from February to May were 1\u0026deg;C, 1\u0026deg;C, 3\u0026deg;C, and 9\u0026deg;C, respectively (Figure3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e6. \u0026nbsp;Data analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analysis including means, minimum and maximum values, standard deviations, and cluster analysis were conducted using JMP PRO 13 software. Principal component analysis was performed using Genstat 12. Genetic parameter estimates were calculated using the \u003cstrong\u003eR statistical software\u003c/strong\u003e. The following formulas were used to estimate genotypic and phenotypic variance (Equation 1-7) components:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEquation 1.\u003c/strong\u003e Genotypic variance (\u0026sigma;\u003csup\u003e2\u003c/sup\u003eg) = (MSg-MSe)/r,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ewhere:\u003c/p\u003e\n\u003cp\u003eMSg = mean square due to genotypes\u003c/p\u003e\n\u003cp\u003eMSe = error mean square,\u003c/p\u003e\n\u003cp\u003er = the number of replication\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEquation 2.\u003c/strong\u003e Phenotypic variance (\u0026sigma;\u003csup\u003e2\u003c/sup\u003ep) = (\u0026sigma;\u003csup\u003e2\u003c/sup\u003eg) + (\u0026sigma;\u003csup\u003e2\u003c/sup\u003ee)\u003c/p\u003e\n\u003cp\u003eEnvironmental variance (\u0026sigma;\u003csup\u003e2\u003c/sup\u003ee) = Mean square error = MSe\u003c/p\u003e\n\u003cp\u003ePhenotypic coefficient of variation (PCV) = \u003cstrong\u003e(\u003c/strong\u003e\u0026radic;\u003cem\u003e\u0026sigma;\u003c/em\u003e2p/\u003cem\u003eX\u003c/em\u003e) *100\u003c/p\u003e\n\u003cp\u003eGenotypic Coefficient of variation (GCV) = GCV \u003cstrong\u003e= (\u003c/strong\u003e\u0026radic;\u003cem\u003e\u0026sigma;\u003c/em\u003e2g/\u003cem\u003eX\u003c/em\u003e) *100\u003c/p\u003e\n\u003cp\u003ewhere:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003ex\u0026nbsp;\u003c/em\u003e= grand mean of a character.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEquation 3.\u003c/strong\u003e Broad sense heritability (h\u003csup\u003e2\u003c/sup\u003e)= (\u0026sigma;\u003csup\u003e2\u003c/sup\u003eg/\u0026sigma;\u003csup\u003e2\u003c/sup\u003ep)*100,\u003c/p\u003e\n\u003cp\u003ewhere:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026sigma;\u003csup\u003e2\u003c/sup\u003eg =genotypic variance,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026sigma;\u003csup\u003e2\u003c/sup\u003ep = phenotypic variance\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEquation 4.\u003c/strong\u003e Expected genetic advance (GA) = h\u003csup\u003e2\u003c/sup\u003e x k x \u0026sigma;p,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEquation 5.\u003c/strong\u003e Expected genetic advance as percentage of mean (GAM) = (GAx100)/\u0026mu;\u003c/p\u003e\n\u003cp\u003ewhere:\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;k = 2.06 (selection differential at 5%\u003c/p\u003e\n\u003cp\u003e\u0026sigma;p= the phenotypic standard deviation;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eh\u003csup\u003e2\u003c/sup\u003e= broad sense heritability and\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026mu;= the grand populations mean for the trait under considerations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEquation 6.\u003c/strong\u003e Phenotypic coefficient of correlation (cp) = Pcov\u003csub\u003exy\u003c/sub\u003e/\u0026radic;(\u0026sigma;\u003csup\u003e2\u003c/sup\u003epx.\u0026sigma;\u003csup\u003e2\u003c/sup\u003epy)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEquation 7.\u003c/strong\u003e Genotypic coefficient of correlation (cg) = Gcov\u003csub\u003exy\u003c/sub\u003e/\u0026radic;(\u003csup\u003e2\u003c/sup\u003egx. \u0026sigma;\u003csup\u003e2\u003c/sup\u003egy)\u003c/p\u003e\n\u003cp\u003eWhere:\u003c/p\u003e\n\u003cp\u003ecp = Phenotypic correlation coefficient,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ecg = Genotypic correlation coefficient,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePcov\u003csub\u003exy\u003c/sub\u003e = Phenotypic covariance between variables x and y,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGcov\u003csub\u003exy\u0026nbsp;\u003c/sub\u003e= Genotypic covariance between variables x and y,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026sigma;\u003csup\u003e2\u003c/sup\u003egx = Genotypic variance for trait X,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026sigma;\u003csup\u003e2\u003c/sup\u003egy = Genotypic variance for trait Y,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026sigma;\u003csup\u003e2\u003c/sup\u003epx = Phenotypic variance for trait X,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026sigma;\u003csup\u003e2\u003c/sup\u003epy =Phenotypic variance for trait Y.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEquation 8.\u003c/strong\u003e The path coefficients were obtained using the general formula of Dewey and Lu (1959) by solving the following simultaneous equations (Equation 8), which express the basic relationship between correlation and path coefficient.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003erij=pij+\u0026Sigma;rik.pkj\u003c/p\u003e\n\u003cp\u003eWhere:\u003c/p\u003e\n\u003cp\u003erij = mutual association between the independent character (i) and dependent character (j) as measured by the genotypic correlation coefficient.\u003c/p\u003e\n\u003cp\u003ePij= components of direct effects of the independent character\u003c/p\u003e\n\u003cp\u003e(i)= On the dependent variable\u003c/p\u003e\n\u003cp\u003e(j)= As measured by the genotypic path coefficient; and\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026Sigma;rik.pkj = summation of components of indirect effects of a given independent character (i) on a given dependent character (j) via all other independent character (k).\u003c/p\u003e\n\u003cp\u003eThe contribution of the remaining unknown factor was measured as the residual factor (pr), which is calculated as, pr = 1-rijPij\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eAnalysis of variance was conducted for nine traits and highly significant differences among the genotypes were found for all traits (Table 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Analysis of variance for the 9 traits of chickpea genotypes\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"638\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNNP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003eGenotype Df=22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e159.85***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e18.05*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e566.13***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.21***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.021***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 48px;\"\u003e\n \u003cp\u003e2.22***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.21***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e104.41***\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e8.25***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003eCV (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 48px;\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 94px;\"\u003e\n \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e Value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 57px;\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: ***, **, * and ns indicate highly significant at 0.01%, highly significant at 0.1%, significant at 5% and non- significant respectively. CV: Coefficient of variations and Df: Degree of freedom. PH: Plant height, RL: Root length, NNP: Number of nodules per plant, NFW: Nodule fresh weight, NDW: Nodule dry weight, RFW: Root fresh weight, RDW: Root dry weight, SFW: Stem fresh weight, SDW: Stem dry weight.\u003c/p\u003e\n\u003cp\u003ePH among wild accessions varied widely, ranging from 10.0 cm to 32.0 cm. Mean PH varied from 14.88 cm in Karab-092 to 32.5 cm in the G\u0026ouml;k\u0026ccedil;e cultivated variety. Among \u003cem\u003eC. reticulatum\u003c/em\u003e accessions, the highest PH was in Egil-073 (29.1 cm), while the lowest was in Besev-075 (16 cm) and Sirnak-060 (16.8 cm). \u003cem\u003eC. echinospermum\u003c/em\u003e accession Cermik-075 had the highest PH (23.2 cm). PH was highest in \u003cem\u003eC. arietinum\u003c/em\u003e species, about 34% and 46% higher than in \u003cem\u003eC. reticulatum\u003c/em\u003e and \u003cem\u003eC. echinospermum\u003c/em\u003e species respectively. PH ranking among the species was as follows: \u003cem\u003eC. arietinum\u003c/em\u003e \u0026gt; \u003cem\u003eC. reticulatum\u003c/em\u003e \u0026gt; \u003cem\u003eC. echinospermum\u003c/em\u003e.\u003c/p\u003e\n\u003cp\u003eRL among wild accessions also showed wide variation, ranging from 9.0 cm to 33.0 cm. Mean RL for the three \u003cem\u003eCicer\u003c/em\u003e species ranged from 13.5 cm in Karab-092 to 20.0 cm in Egil-065. Among \u003cem\u003eC. reticulatum\u003c/em\u003e accessions, Egil-065 (20.0 cm) had the highest RL, while Derei-070 had the lowest. Cermik-075 had the highest RL among \u003cem\u003eCicer echinospermum\u003c/em\u003e accessions.\u003c/p\u003e\n\u003cp\u003eRoot/shoot length ratio in cultivated chickpeas was 59%, compared to 98% and 82% in \u003cem\u003eC. echinospermum\u003c/em\u003e and \u003cem\u003eC. reticulatum\u003c/em\u003e, respectively.\u003c/p\u003e\n\u003cp\u003eWild accessions indicated a wide variation in the NNP, ranging from 0.0 to 59.0 (Table 3). The mean NNP for the three \u003cem\u003eCicer\u003c/em\u003e species varied from 3.77 in Gunas-062 to 40.1 in G\u0026ouml;k\u0026ccedil;e. Among the \u003cem\u003eC. reticulatum\u003c/em\u003e accessions, Derei-072 had the highest NNP (32.77). For \u003cem\u003eC. echinospermum\u003c/em\u003e accessions, Cermik-075 had the highest value (22.77) (Table 3).\u003c/p\u003e\n\u003cp\u003eNFW varied widely among wild accessions, from 0.0 g to 1.09 g. Mean NFW for the three \u003cem\u003eCicer\u003c/em\u003e species ranged from 0.07 g in Gunas-062 to 0.78 g in G\u0026ouml;k\u0026ccedil;e. The highest NFW among \u003cem\u003eC. reticulatum\u003c/em\u003e accessions was observed in Derei-072 (0.65 g). Cermik-075 had the highest value among \u003cem\u003eC. echinospermum\u003c/em\u003e accessions (0.50 g) (Table 3). NDW also observed wide variation among wild accessions, ranging from 0.0 g to 0.8 g. Mean NDW for the three \u003cem\u003eCicer\u003c/em\u003e species ranged from 0.01 g in Gunas-062 to 0.25 g in Ortan-066. The highest NDW among \u003cem\u003eC. reticulatum\u003c/em\u003e accessions was observed in Derei-072 (0.13 g) (Table 3).\u003c/p\u003e\n\u003cp\u003eRFW among wild accessions also showed wide variation, ranging from 0.12 g to 3.96 g. Mean RFW for the three \u003cem\u003eCicer\u003c/em\u003e species ranged from 0.36 g in Karab-092 to 2.06 g in Derei-072. Among \u003cem\u003eC. reticulatum\u003c/em\u003e accessions, Besev-075 (mean 0.43 g) had the lowest RFW. Cermik-075 had the highest (mean 1.62 g) RFW among \u003cem\u003eCicer echinospermum\u003c/em\u003e accessions. RDW among \u003cem\u003eC. reticulatum\u003c/em\u003e accessions ranged from 0.1 g in Besev-075 to 0.6 g in Egil-065. For \u003cem\u003eC. echinospermum\u003c/em\u003e species, the lowest RDW was in Karab-092 (0.17 g).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSFW varied widely among wild accessions, from 0.82 g to 25.75 g. Mean SFW for the three \u003cem\u003eCicer\u003c/em\u003e species ranged from 1.99 g in S2Drd-065 to 12.29 g in Egil-073. The lowest SFW among \u003cem\u003eC. reticulatum\u0026nbsp;\u003c/em\u003eaccessions was observed in Besev-075 (Mean 2.84 g). Cermik-075 had the highest value among C. echinospermum accessions (Mean 11.36 g). SDW among wild accessions ranged from 0.2 g to 7.1 g. Mean SDW for the three \u003cem\u003eCicer\u003c/em\u003e species ranged from 0.5 g in S2DRD-065 to 3.7 g in Derei-072. In \u003cem\u003eC. reticulatum\u003c/em\u003e, Derei-072 (3.7 g) had the highest stem dry weight. For \u003cem\u003eC. echinospermum\u003c/em\u003e, the highest value was in Cermik-075 (3.02 g).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEstimates of genetic parameters\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGenotypic and phenotypic coefficients of variation (GCV and PCV) estimates are key indicators used to assess the variability within a given population (Tadesse et al., 2016). In this study, estimates of genotypic and phenotypic variances (\u0026sigma;\u003csup\u003e2\u003c/sup\u003eg and \u0026sigma;\u003csup\u003e2\u003c/sup\u003ep), GCV and PCV, broad sense heritability, genetic advance and genetic advance as percent of mean are presented in Table 3.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u0026nbsp;\u003c/strong\u003eDescriptive statistics, genotypic and phenotypic variances, coefficient of variability, broad sense heritability, and genetic advance as a percentage of the mean for the nine traits of \u003cem\u003eCicer\u003c/em\u003e genotypes tested in 2018\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"91%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNNP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eMax\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e1.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e3.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e27.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e8.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eMin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0,82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e21.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e17.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e16.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e6.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eMST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e159.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e18.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e566.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e2.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0,21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e104,41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e8,25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eMSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e2.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e1.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026sigma;\u003csup\u003e2\u003c/sup\u003eg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e16.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e54.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e10.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u0026sigma;\u003csup\u003e2\u003c/sup\u003ep\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e31.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e11,14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e132.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e22.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e1.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eGCV (%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e18.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e5.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e44.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e39.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e49.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e49.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e44.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e50.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e51.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003ePCV (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e26.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e18.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e69.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e71.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e109.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e68.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e64.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e74.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e74.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eH\u003csup\u003e2\u003c/sup\u003eb (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eGA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e5.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e9.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e4.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003eGAM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e27.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e2.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e58.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e45.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e45.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e72.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e63.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e69.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e73.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ePH: Plant height, RL: Root length, NNP: Number of nodules per plant, NFW: Nodule fresh weight, NDW: Nodule dry weight, RFW: Root fresh weight, RDW: Root dry weight, SFW: Stem fresh weight, SDW: Stem dry weight.\u003c/p\u003e\n\u003cp\u003eMax: Maximum, Min: Minimum, MST: Mean square of treatments, MSE: Mean square of error, \u0026sigma;2g: Genotypic variance, \u0026sigma;2p: Phenotypic variance H\u003csup\u003e2\u003c/sup\u003eb (%): Broad sense heritability in percent, GCV (%): Coefficient of genotypic variance, PCV (%): Coefficient of phenotypic variance, GA: Genetic advance, GAM: Genetic advance as percent of means\u003c/p\u003e\n\u003cp\u003eThe results for all characters in the present investigation showed that the phenotypic variance was higher in magnitude than genotypic variance (Table 3). Estimates of the phenotypic coefficient of variation in this study were also higher than their corresponding genotypic coefficient of variation, suggesting the influence of environmental factors on the expression of these traits.\u003c/p\u003e\n\u003cp\u003eIn the present study the highest phenotypic and genotypic variance were observed from the NNP (132.56 and 54.19), followed by PH (31.40 and 16.05) respectively. The smallest phenotypic and genotypic variance were found in NDW (0.008 and 0.001), followed by RDW (0.04 and 0.02) and NFW (0.06 and 0.06) respectively (Table 3).\u003c/p\u003e\n\u003cp\u003eIn this study, GCV ranged from 5.20% RL to 51.46% for SDW while PCV ranged from 18.67% for root length to 109.7% for NDW. The highest GCV and PCV values (\u0026gt;20%) were observed for SDW (51.46% and 74.02), SFW (50.15% and 74.86%), NDW (49.37% and 109.7%), RFW (49.09% and 68.05%), RDW (44.53% and 64.19%), NNP (44.21% and 69.14%) and NFW (39.93% and 71.84%) respectively.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePH showed moderate GCV (18.82%) and high PCV (26.33%) while RL showed low GCV (5.20%) and moderate PCV (18.67%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEstimates of Heritability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBroad sense heritability estimates for the studied characters varied from 20% for NDW to 77% for RL (Table 3). In general, high heritability estimates indicate that selection for the trait will be more effective as genetic factors predominantly control its expression while low heritability estimates indicate that environmental factors have high influence, making genetic improvement through selection more difficult (Tesfay Belay, 2018).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEstimates of expected genetic advance\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe highest magnitude of genetic advance was observed for the NNP (9.69), while the lowest was recorded for NFW (0.16) (Table 3). According to Johnson et al. (1955), genetic advance as a percentage of the mean can be categorized as low (0\u0026ndash;10%), moderate (10\u0026ndash;20%) and high (\u0026ge;20%). In this study, the expected genetic advance as a percantage of the mean ranged from 2.98% for RL to 72.97% for RFW (Table 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelation of traits\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEstimates of genotypic and phenotypic correlation coefficients between each pair of trait are given (Table 4). Genotypic correlation coefficients were found higher than phenotypic correlation coefficients in most of the characters, indicating the presence genetic association among traits which is important for reliable improvement through selection.\u003c/p\u003e\n\u003cp\u003ePlant height showed highly significant positive genotypic correlation with RL (0.731), NNP (0.669), NFW (0.641), RFW (0.573), RDW (0.591), SFW (0.855) and SDW (0.85). Nodule dry weight showed no significant genotypic correlation with PH, RL, SFW and SDW. No negative genotypic correlations were observed (Table 4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAt phenotypic level, SDW showed positive highly significant positive correlations with SFW (0.873), RDW (0.799), RFW (0.741), PH (0.721), NNP (0.468), NFW (0.455), RL (0.233) and NDW (0.179). No negative and no significant phenotypic correlations were observed for any trait pair (Table 4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u003c/strong\u003e Genotypic (below diagonal) and phenotypic (above diagonal) correlations coefficients of the 9 traits chickpea genotypes\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNNP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.220**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.532**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.513**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.237**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.543**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.543**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.729**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.721**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.731**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.189**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.264**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.232**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.402**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.242**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.316**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.233**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNNP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.669**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.642**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.849**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.426**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.499**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.444**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.451**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.468**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.641**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.717**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.998**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.473**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.571**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.470**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.478**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.455**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.302 ns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.298 ns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.464*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.538**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.321**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.291**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.179**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.179**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.573**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.917**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.699**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.722**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.459*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.844**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.764**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.741**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.591**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.964**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.676**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.702**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.432*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.999**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.708**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.799**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.855**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.917**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.738**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.720**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.290 ns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.870**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.878**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.873**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.85**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.898**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.777**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.764 ** \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.349 ns\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.882**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.86**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1.014**\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: **, * and ns indicate highly significant at 0.1%, highly significant at 5%, and non- significant respectively.\u0026nbsp;PH: Plant height, RL: Root length, NNP: Number of nodules per plant, NFW: Nodule fresh weight, NDW: Nodule dry weight, RFW: Root fresh weight, RDW: Root dry weight, SFW: Stem fresh weight, SDW: Stem dry weight.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePath coefficient analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSDW was taken as the dependent variable in the path analysis, which was performed at phenotypic and genotypic levels to identify the underlying traits and determine the key components contributing to biomass production (Tables 5 and 6). In most cases, the phenotypic direct and indirect effects were slightly higher than genotypic effects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGenotypic direct and indirect effects of various characters on stem dry weight\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePath coefficient analysis revealed that traits with strong positive direct effects on SDW were the NNP, RDW, and SFW, indicating their importance in enhancing biomass accumulation in chickpea. The highest positive direct effect of 2.732 was exhibited by RDW and followed by SFW (1.824), NNP (1.20) The direct effects exhibited by PH, RL, NFW and RFW were negative. On the other hand, traits with strong negative direct effects were PH, RL, NFW and RFW. The low residual value (0.0174) suggests that the majority of variation in SDW was explained by the traits included in the model. These findings highlight the importance of nodulation and biomass-related traits in breeding for higher stem productivity.\u003c/p\u003e\n\u003cp\u003eTraits with the highest positive indirect effects on SDW were PH, NFW, and RFW, primarily through their influence on RDW and SFW. Although RFW had a strong negative direct effect on SDW, its positive indirect contributions via RDW and SFW suggest that it still plays an important role in improving biomass accumulation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5.\u003c/strong\u003e Estimate of direct effect (bold face and diagonal) and indirect effects (off diagonal) at genotypic level in 23 chickpea genotypes\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNNP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCG\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.60300\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.17645\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.80377\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.66524\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.09691\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-1.78180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1.61580\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1.56002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.85**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.44113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.24119\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.77137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.74415\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.09565\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-2.85188\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e2.63635\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1.67305\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.898**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNNP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.40363\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.15494\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.20080\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-1.03547\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.14900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-2.17281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1.84825\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1.34634\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.777**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.38674\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.17304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1.19874\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-1.03725\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.17272\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-2.24469\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1.92045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1.31382\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.7764**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.18249\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.07204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.55874\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.55947\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.32022\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-1.42874\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1.18253\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.53118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.349 ns\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.34571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.22132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.83950\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.74915\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.14721\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-3.10791\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e2.73233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1.58789\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.882**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.35653\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.23268\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.81211\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.72891\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.13856\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-3.10732\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.73285\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1.60221\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.86**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.51567\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.22120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.88622\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.74703\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.09324\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-2.70525\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e2.40023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.82424\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1.014**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eResidual value (0.0174),\u0026nbsp;Note: **, * and ns indicate highly significant at 0.1%, highly significant at 5%, and non- significant respectively. PH: Plant height, RL: Root length, NNP: Number of nodules per plant, NFW: Nodule fresh weight, NDW: Nodule dry weight, RFW: Root fresh weight, RDW: Root dry weight, SFW: Stem fresh weight, SDW: Stem dry weight, CG: Genotypic correlation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhenotypic direct and indirect effects of various traits on stem dry weight\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe phenotypic correlation coefficients were partitioned into direct and indirect effects by various biomass contributing traits (Table 6).\u003c/p\u003e\n\u003cp\u003eSFW (0.541) showed the highest positive direct effect on SDW followed by RDW (0.447), PH (0.151) and NNP (0.094), while highest negative direct effect for SDW was showed for RFW (-0.112) followed RL (-0.018), NFW (-0.077) and NDW (-0.056).\u003c/p\u003e\n\u003cp\u003eRFW, PH, NFW and NNP exerted highest positive indirect effect on SDW via RDW and SFW (0.380 and 0.413; 0.244 and 0.394; 0.211 and 0.248; 0.199 and 0.244) respectively. While NFW showed the highest negative indirect effect on SDW via RFW (-0.064) followed by PH (-0.061), NNP (-0.056), RL (-0.045), and NDW (-0.036). The contribution of residual factors that influenced SDW was very low at both genotypic and phenotypic levels indicating that the most important traits are recorded in this investigation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6.\u003c/strong\u003e Estimate of direct effect (bold face and diagonal) and indirect effects (off diagonal) at phenotypic level in 23 chickpea genotypes\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNNP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.15116\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.00413\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.05042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.04040\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.01332\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.06132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.24462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.39478\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.721**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.03328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.01876\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.01790\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.02076\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.01297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.04540\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.10900\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.17150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.233**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNNP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.08054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.00355\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.09463\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.06676\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.02386\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.05639\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.19991\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.24439\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.468**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.07771\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.00496\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.08039\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.07759\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.02754\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.06451\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.21103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.25857\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.455**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.03611\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.00436\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.04050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.03881\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.05646\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.03677\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.14282\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.09828\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.179**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.08218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.00755\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.04731\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.04495\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.01817\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-0.11279\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.38068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.41388\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.741**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.08212\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.00454\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.04202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.03683\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.01768\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.09536\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.44728\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.38331\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.799**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.11027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.00595\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.04273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.03755\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.01012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e-0.08626\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.31891\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.54117\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e0.873**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eResidual value (0.1473),\u0026nbsp;Note: **, * and ns indicate highly significant at 0.1%, significant at 5%, and non- significant, respectively.\u0026nbsp;PH: Plant height, RL: Root length, NNP: Number of nodules per plant, NFW: Nodule fresh weight, NDW: Nodule dry weight, RFW: Root fresh weight, RDW: Root dry weight, SFW: Stem fresh weight, SDW: Stem dry weight, CP: Phenotypic correlation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrincipal Component Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe percentage of variation explained by the two most informative principal components (PC1 and PC2) and the vector loadings for each morphological trait in three different annual \u003cem\u003eCicer\u003c/em\u003e species are given in Table 7 and Figure 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 7.\u0026nbsp;\u003c/strong\u003e Principal Component analysis on\u003cem\u003e\u0026nbsp;Cicer arietinum\u003c/em\u003e, \u003cem\u003eCicer reticulatum\u003c/em\u003e,\u003cem\u003e\u0026nbsp;\u003c/em\u003eand \u003cem\u003eCicer echinopspermum\u003c/em\u003e species.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"620\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC.reti+C.echi+C.arie\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC.reti+C.echi+C.arie\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC.reti\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC.reti\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC.echi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC.echi\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePC1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePC2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePC1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePC2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePC1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePC2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eEigenvalue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e6.128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e1.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e6.319\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e1.341\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e6.051\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e1.657\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eThe proportion of variance (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e68.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e11.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e70.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e14.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e56.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e41.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eCumulative variance (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e68.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e79.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e70.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e85.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e56.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e97.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 196px;\"\u003e\n \u003cp\u003eCharacters*with greater weighting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e*SDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e*\u003cstrong\u003eNDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e*RDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e*PH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e*PH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e*NFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e*SFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e*NFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e*RFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e*RL\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e*SDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e*\u003cstrong\u003eNDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 95px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e*RFW\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e*RDW\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e*NFW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e*NNP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e*SDW\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e*SFW\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e*NDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 57px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e*RFW\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e*SFW\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e*RDW\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e*NNP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eC.reti: \u003cem\u003eCicer reticulatum\u003c/em\u003e, C.echi: \u003cem\u003eCicer echinospermum\u003c/em\u003e, C.ari: \u003cem\u003eCicer arietinum\u003c/em\u003e,\u003cem\u003e\u0026nbsp;\u003c/em\u003eSDW: Stem dry weight, SFW: Stem fresh weight, RFW: Root fresh weight, RDW: Root dry weight, NFW: Nodule fresh weight, NDW: Nodule dry weight, NNP: Number of nodules per plant, PH: Plant height, RL: Root length.\u003c/p\u003e\n\u003cp\u003eIn the combined analysis of \u003cem\u003eC.\u003c/em\u003e \u003cem\u003ereticulatum\u003c/em\u003e, \u003cem\u003eC. echinospermum\u003c/em\u003e, and \u003cem\u003eC. arietinum\u003c/em\u003e, the first two principal components (PCs) explained 79.54% of the total variation, with PC1 accounting for 68.10%. Traits contributing most strongly to PC1 included SDW, SFW, RFW and RDW. PC2 was influenced mostly by nodulation traits including NDW, NFW, and the NNP (Figure 4 and 5).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe first two PCs explained 85.13% of the variation in \u003cem\u003eC. reticulatum\u003c/em\u003e, with PC1 alone accounting for 70.22%. The PC1 was greatly influenced by traits such as RDW, RFW, SDW, SFW, and NDW. In PC2, PH and RL were important morphological traits with greater influence (Figure 5, 6 and 7).\u003c/p\u003e\n\u003cp\u003eThe PCA biplot supported the groupings identified in Biplot-Cluster analysis. Figure 5 indicates that PC1 and PC2 clearly distinguished wild accessions based on the evaluated traits. Ortan-066, a \u003cem\u003eC. echinospermum\u003c/em\u003e accession, was the most distinct genotype for the traits investigated.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAmong the \u003cem\u003eC. reticulatum\u003c/em\u003e accessions, Kayat-077 showed a strong association with RL (Figure 3). Also, \u003cem\u003eC. reticulatum\u003c/em\u003e accessions of Egil_065, Egil_073 and Kayat_077 and \u003cem\u003eC. echinospermum\u003c/em\u003e accession of Cermik-075 were closely related to all measured traits (Figure 6 and 7).\u003c/p\u003e\n\u003cp\u003eFor \u003cem\u003eC. echinospermum\u003c/em\u003e, the first two PCs explained 97.68% of the variation. In PC1, PH, SDW, RFW, SFW, RDW and RL were the traits with the greatest\u0026nbsp;influence. In PC2, the important traits were NFW and the NNP (Table 7).\u003c/p\u003e\n\u003cp\u003eK-mean cluster analysis grouped all \u003cem\u003eCicer\u0026nbsp;\u003c/em\u003eaccessions into three distinct clusters (Figure 8). The first cluster contained Cermik-075, Derei-072 and Egil-065 accessions. the other accessions (Egil-073, G\u0026ouml;k\u0026ccedil;e, Kayat-077, Ortan-066, S2DRD-065, Gunas-062, Karab-092) were distributed among the other two clusters.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eK-mean cluster analysis of \u003cem\u003eC. reticulatum\u003c/em\u003e accessions were divided into three distinc groups (Figure 8). The first cluster contained only Derei-072, while the second cluster contained Egil-065 and Egil-073 accessions. The remaining ten accessions were included in a separate cluster. Interestingly four accessions (Bari1_092, Bari3_072C, Besev_075 and Kayat_077) did not group with these three primary clusters.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWild relatives of chickpea are important genetic resources to expand genetic variation and transfer of agronomically important traits. This study aimed to explore some important morphological characteristics of different \u003cem\u003eCicer\u003c/em\u003e species by investigating both cultivated genotypes (\u003cem\u003eC. arietinum\u003c/em\u003e) and wild accessions (\u003cem\u003eC. reticulatum\u003c/em\u003e and \u003cem\u003eC. echinospermum\u003c/em\u003e).\u003c/p\u003e\u003cp\u003eNumbers of nodules per plant, fresh and dry nodule weight in both cultivated and wild accessions were negatively affected by hot and dry conditions during the crop growth. This finding is consistent with Kantar et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2003\u003c/span\u003e), who also reported that the nodule dry weight was decreased in dry season. Although the number of nodules per plant was higher in cultivated genotypes, the nodule fresh and dry weight per plant, as well as the ratio of nodules, was found to be higher in wild accessions. \u003cem\u003eC. echinospermum\u003c/em\u003e had 12% higher nodule fresh weight and 42% higher nodule dry weight compared to cultivated genotypes. These findings align with previous research by Jaiswal and Singh (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e1990\u003c/span\u003e), who reported that \u003cem\u003eC. reticulatum\u003c/em\u003e exhibited a higher number of nodules per plant and greater fresh weight compared to cultivated chickpeas. Additionally, Kim et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) reported that nodule cultivation in chickpea varieties reduces symbiont diversity, while \u003cem\u003eC. reticulatum\u003c/em\u003e wild accessions showed wider variation in symbionts compared to cultivated chickpeas. Istanbuli et al. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) noted drought stress decreased nodule characteristics, with tolerant genotypes exhibiting higher nodule characteristics compared to susceptible genotypes. In summary, the data indicates significant variability in nodule formation among different \u003cem\u003eCicer\u003c/em\u003e species and accessions, with wild species generally exhibiting a higher number of nodules compared to cultivated varieties. This variability emphasizes the genetic potential of wild accessions for enhancing nodule traits in breeding programs. These findings suggest that wild accessions may have greater potential for forming beneficial symbiotic relationships with soil microorganisms, which could contribute to their superior nodule characteristics under hot and dry conditions.\u003c/p\u003e\u003cp\u003eThe data indicates substantial variability in plant height, root length, and root and stem dry weight among the \u003cem\u003eCicer\u003c/em\u003e species. Wild species generally exhibit more variability compared to cultivated varieties, which can be crucial for breeding programs aimed at improving these traits. Cultivated chickpea varieties were characterized by taller plants with greater stem and root development compared to wild accessions. These results are consistent with Singh et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), who also reported that \u003cem\u003eC. arietinum\u003c/em\u003e species exhibited greater plant height compared to wild species. Also, Robertson et al. (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e1997\u003c/span\u003e) noted marked variations in morphological characteristics between annual wild \u003cem\u003eCicer\u003c/em\u003e species and cultivated chickpeas, including leaf area and growth habits.\u003c/p\u003e\u003cp\u003eThe root/shoot length ratio is an important indicator of plant growth and development, as well as crop yield and quality. This study found that the root/shoot length ratio was higher in wild accessions than in cultivated chickpeas. Wild accessions had a more robust root system compared to cultivated chickpeas. These findings are consistent with Serraj et al. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), who determined a linear relationship. Berger et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) found that wild \u003cem\u003eCicer\u003c/em\u003e species in late types had relatively greater root systems. This relationship has important implications for crop breeding and improvement, as it provides a potential for enhancing plant growth and yield.\u003c/p\u003e\u003cp\u003eThe 2018 growing season was marked by hot and dry conditions, except for May. Wild accessions exhibited a higher root/shoot length ratio than cultivated varieties that might be an indicative potential tolerance to drought and heat stress. Greater root development in wild species was found to promote under early and late drought conditions. Pang et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) reported that plants possess the ability to adapt their root characteristics to improve in various soil environments. Kashiwagi et al. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) and Kumar et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) suggested that the root system and root depth are key factors in coping with drought stress and promoting growth in dry conditions. However, Kashiwagi et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) and Gaur et al. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) report that wild species have relatively poor root and biomass development compared to cultivated varieties. These discrepancies may be due to differences in genetic background or environmental conditions. Zaman-Allah et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) suggested that the variation in root growth components, including depth, length density, and dry weight, was not significantly different between drought-tolerant and susceptible chickpea genotypes. Additionally, Purushothaman et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) observed that in response to drought, root distribution decreased at the soil surface but increased at depths below 30 cm. Water uptake from the soil was found to have a maximum depth of 45\u0026ndash;60 cm under dry conditions, while it branched at depths of 15\u0026ndash;30 cm and 30\u0026ndash;45 cm under irrigated conditions.\u003c/p\u003e\u003cp\u003eThe presence of genotypic and phenotypic variability among genotypes is important for determining the effectiveness of breeding programs (Tsehaye et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The highest phenotypic and genotypic variance were observed for nodules per plant and plant height even though they were highly effected from environment.\u003c/p\u003e\u003cp\u003eThe correlation coefficient is an index representing the proportion of shared causative factors between two variables (Bowley, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e1920\u003c/span\u003e). In most cases, the genotypic correlation coefficients were greater in magnitude than the phenotypic ones, suggesting strong inherent genetic relationships among traits that were less influenced by environment (Jakhar, 2014).\u003c/p\u003e\u003cp\u003ePCA effectively differentiates \u003cem\u003eCicer\u003c/em\u003e accessions based on their morphological traits. The high percentage of variation explained by the first two principal components highlights the significance of these traits in distinguishing between accessions. PCA is a valuable tool for dimensionality reduction and identification of the most influential traits (Jolliffe and Cadima \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). For instance, the strong influence of root and nodule traits on the principal components suggests these traits should be prioritized in breeding programs for drought resistance (Kashiwagi et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). This observed diversity is crucial for breeding programs aimed at improving drought tolerance and other agronomic traits (Berger et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eEasily measurable phenotypic traits-such as morphological, anatomical, and phenological characteristics-that are clearly distinguishable in the field and cost-effective to assess can be valuable tools for pre-breeding programs, especially in developing countries where crops are often grown in marginal environments.\u003c/p\u003e\u003cp\u003eCrop wild relatives (CWRs), commonly used in breeding programs as sources of resistance to biotic stresses, often carry additional traits that enable them to thrive in marginal environments. Through natural selection over evolutionary time, these wild progenitors have developed the ability to maintain fitness under a wide range of environmental stresses. In contrast, modern breeding-focused on broad adaptation and uniformity-has led to reduced genetic diversity and increased vulnerability to both biotic and abiotic challenges. Harnessing the genetic heterogeneity found in wild relatives offers a valuable opportunity for developing cultivars better suited to the demands of marginal lands.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study aimed to determine the importance of wild chickpea species as a genetic resource for breeding programs to enhance chickpea tolerance to abiotic stress factors, such as drought, in semi-arid climatic conditions. The genetic diversity presents in wild species, \u003cem\u003eCicer reticulatum\u003c/em\u003e and \u003cem\u003eCicer echinospermum\u003c/em\u003e, demonstrated a vast genetic resource that that holds great potential for plant breeding studies. The findings of this study demonstrated that the root system and nodule traits of wild species have significant potential in coping with drought stress. These traits can be valuable in breeding programs aimed at developing more resilient chickpea varieties, thereby contributing to sustainable agriculture in regions affected by climate change and water scarcity.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eCompeting interests\u003c/h2\u003e\u003cp\u003eThe author(s) declare no competing interests.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eThe author Fatma Basdemir contributed to the study conceptualization, investigation, formal analysis, visualization, data curation and writing-original draft.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe author would like to express their gratitude to Abdullah Kahraman from the Faculty of Agriculture at Harran University for generously providing the annual wild Cicer seeds that were utilized in this study. Author is incredibly grateful to Behiye Tuba Bi\u0026ccedil;er from the Faculty of Agriculture at Dicle University for her invaluable contribution to managing the experiment and writing the paper. Her expertise and dedication were crucial to the success of the research.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData is provided within the manuscript files\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBerger, J., Pushpavalli, R., Ludwig, C., Parsons, S., Basdemir, F. \u0026amp; Whisson, K. Wild and domestic differences in plant development and responses to water deficit in \u003cem\u003eCicer\u003c/em\u003e. \u003cem\u003eFront. Genet\u003c/em\u003e.\u003cstrong\u003e11\u003c/strong\u003e, 607819. (2020). https://doi.org/10.3389/fgene.2020.607819.\u003c/li\u003e\n\u003cli\u003eBowley, A. L. Elements of Statistics. \u003cem\u003eIndian J. Agric. Sci.\u003c/em\u003e \u003cstrong\u003e3\u003c/strong\u003e, 44. 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(Oxford University Press, 2000).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"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":"Chickpea, Cicer, Biplot, Nodule, Principal Component Analyses, Heritability","lastPublishedDoi":"10.21203/rs.3.rs-7004526/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7004526/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Wild relative species of cultivated plants possess resistance genes to withstand a/biotic stresses to survive in their natural environments. Although aboveground morphological characteristics of wild species were evaluated in breeding programs, underground morphological characteristics have usually been ignored due to difficulties working with underground materials.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003eThe present study was therefore conducted to perform comparative analyses of the underground and aboveground morphological characteristics of wild Cicer species -including 20 accessions of \u003cem\u003eCicer reticulatum\u003c/em\u003e, and 6 accessions of \u003cem\u003eCicer echinospermum\u003c/em\u003e- and 1 variety of cultivated \u003cem\u003eC. arietinum\u003c/em\u003especies. Root length (RL), root dry (RDW) and fresh weight (RFW), number of nodules per plant (NNP), nodule fresh (NFW) and dry weight per plant (NDW) in flowering time were studied as underground morphological characteristics. Plant height (PH), stem dry (SDW) and fresh weight (SFW) were recorded as above morphological characteristics.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003eSignificant morphological differences were observed between the wild accessions and cultivated chickpeas cultivars. The wild \u003cem\u003eCicer \u003c/em\u003especies exhibited superior root development with higher nodule fresh and dry weight ratio compared to the cultivated chickpea. The wild accessions sustained their root development despite extremely dry and hot periods compared to the cultivated variety. For broad sense heritability estimates, root and shoot traits showed moderate to high heritability while nodule traits exhibited low heritability. Compared to the other traits, highest phenotypic and genotypic variance were observed NNP. Higher phenotypic variances observed for root and nodule traits indicated quantitative nature of inheritance and high impact of environmental factors for the traits. Genotypic correlation coefficients were found higher than phenotypic correlation coefficients in most of the characters, indicating the presence genetic association among traits which is important for reliable improvement through selection. Path coefficient analysis revealed that NNP, RDW, and SFW had strong positive direct effects on SDW, indicating their importance in enhancing biomass accumulation in chickpea. Principal component (PCI) analysis clearly distinguished wild accessions based on the evaluated traits and explained 79.54% of the total variation, with PC1 accounting for 68.10%. Traits contributing most strongly to PC1 included SDW, SFW, RFW and RDW. PC2 was influenced mostly by nodulation traits including NDW, NFW, and the NNP. Domestication appeared to favor aboveground traits in cultivated chickpea compared to wild accessions. These findings underline the potential of wild \u003cem\u003eCicer\u003c/em\u003especies as valuable genetic resources for developing drought-resistant varieties.\u003c/p\u003e","manuscriptTitle":"Genetic Variability and Association Analysis of Underground and Aboveground Morphological Characteristics of Wild Cicer Species and Cultivated Chickpeas","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-09 13:07:50","doi":"10.21203/rs.3.rs-7004526/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":"b0dacc70-063b-45c0-a4a6-0199db8046dc","owner":[],"postedDate":"July 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":51179546,"name":"Biological sciences/Genetics"},{"id":51179547,"name":"Biological sciences/Plant sciences"}],"tags":[],"updatedAt":"2025-10-31T18:37:41+00:00","versionOfRecord":{"articleIdentity":"rs-7004526","link":"https://doi.org/10.1080/09064710.2025.2577416","journal":{"identity":"acta-agriculturae-scandinavica-section-b-soil-and-plant-science","isVorOnly":true,"title":"Acta Agriculturae Scandinavica, Section B — Soil \u0026 Plant Science"},"publishedOn":"2025-10-30 00:00:00","publishedOnDateReadable":"October 30th, 2025"},"versionCreatedAt":"2025-07-09 13:07:50","video":"","vorDoi":"10.1080/09064710.2025.2577416","vorDoiUrl":"https://doi.org/10.1080/09064710.2025.2577416","workflowStages":[]},"version":"v1","identity":"rs-7004526","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7004526","identity":"rs-7004526","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}