**2.4 Molecular markers**

Molecular markers are based on DNA sequence polymorphism and bypass the limitations encountered in the use of morphological, cytological and biochemical markers. These have become the preferred method for evaluating crop genetic variations due to their simple inheritance, high reproducibility, widespread distribution in plant genome and being stable, highly polymorphic with minimum pleiotropic effects [5]. Molecular markers are not plant stage dependent and are least affected by environment. Large number of markers have been mapped on chromosomes of crop plants and livestock. Molecular markers show either dominant or co dominant inheritance mode. The codominant markers are preferred over dominant ones being more reliable and informative [6]. These have been extensively exploited for variety of applications like genetic fingerprinting, hybrid identification, functional genomics etc. In crop breeding, molecular markers help in early identification/selection of desired genotypes thereby shortening variety development time. These markers enhance breeders' capability of targeted breeding. The earlier version of hybridization- or PCR- based markers has now been upgraded to newer types based on sequencing or array platforms. Following are the groups of molecular markers based on principle techniques:


*Exploring Plant Genetic Variations with Morphometric and Molecular Markers DOI: http://dx.doi.org/10.5772/intechopen.95026*

7.Functional molecular markers (FMM): The term "Functional markers" was proposed by Andersen and Lübberstedt [9] for DNA markers that arise from sequence polymorphism among functional genes that are linked with variations in the desired phenotypic traits. Hence, these are more reliable and informative than all previous PCR- based markers.

Each marker system has its own benefits and disadvantages and variations exist on the basis of development cost, efficiency and reproducibility.

## **3. Need for genetic diversity assessment of sorghum germplasm**

#### **3.1 Sorghum origin**

**2.3 Biochemical markers**

*Genetic Variation*

**2.4 Molecular markers**

Biochemical markers have been among the most widely used markers for assessing variations among and within crop species before the advent of molecular/ DNA markers. The alternative forms of protein (isozymes) exhibit specific banding patterns on gel electrophoresis, owing to variations in charge- based protein mobility. Isozymes are the products of different alleles, their position can be mapped on to chromosomes and hence are used to map other genes. Protein/isozyme analysis is still among the simple, rapid and cheap methods and fits well in the projects where low level of genetic diversity estimation is desired. Though protein markers are more reliable than morphological markers, their expression is plant growth stage

Molecular markers are based on DNA sequence polymorphism and bypass the limitations encountered in the use of morphological, cytological and biochemical markers. These have become the preferred method for evaluating crop genetic variations due to their simple inheritance, high reproducibility, widespread distribution in plant genome and being stable, highly polymorphic with minimum pleiotropic effects [5]. Molecular markers are not plant stage dependent and are least affected by environment. Large number of markers have been mapped on chromosomes of crop plants and livestock. Molecular markers show either dominant or co dominant inheritance mode. The codominant markers are preferred over dominant

ones being more reliable and informative [6]. These have been extensively exploited for variety of applications like genetic fingerprinting, hybrid identification, functional genomics etc. In crop breeding, molecular markers help in early identification/selection of desired genotypes thereby shortening variety development time. These markers enhance breeders' capability of targeted breeding. The earlier version of hybridization- or PCR- based markers has now been upgraded to newer types based on sequencing or array platforms. Following are the groups of

1.Nucleic acid hybridization- based markers: Restriction fragment length

2.PCR- based markers: Randomly amplified polymorphic DNA (RAPDs),

3.PCR–RFLP markers: Cleaved amplified polymorphic sequences (CAPS)

4.Retrotransposons- based markers: Inter-retrotransposon amplified polymorphism (IRAP), Retrotransposon microsatellite amplification polymorphisms (REMAP), Retrotransposon-based insertion polymorphism

5.Sequence-based markers: Single-nucleotide polymorphism (SNP)

6.Array-based platforms like Diversity Arrays Technique (DArT), restriction site-associated DNA (RAD), single feature polymorphism (SFP), etc. [7, 8]

Amplified fragment length polymorphisms (AFLP), Microsatellites, or simple sequence repeats (SSRs), Randomly amplified microsatellite polymorphisms (RAMP), Sequence-related amplified polymorphism (SRAP), Inter simple sequence repeat (ISSR), Target region amplification polymorphism (TRAP)

molecular markers based on principle techniques:

(RBIP), Inter-primer binding site (iPBS).

polymorphisms (RFLPs).

**104**

dependent and is readily influenced by the environment [3, 4].

The word sorghum originated from "*Syricum*" in Latin, meaning "Grain of Syria*"* [10]. Sorghum (*Sorghum bicolor*) belongs to class *Liliopsida*, family *Graminea*, genus *Sorghum Moench* and has five groups named as: *Hetrosorghum*, *Chaetosorghum*, *Spitosorghum*, *Parasorghum* and *Eusorghum*. It is an ancient grain that has been cultivated for thousands of years. It originated mainly from Sudanese and Ethiopian grasslands more than 6000 years ago.

#### **3.2 Global sorghum distribution and production**

About 100 countries grow sorghum worldwide (**Figure 1**). USA is the top sorghum producer with five countries viz.; Nigeria, Ethiopia, Mexico, India and China follow in the order of production (**Figure 2**). The countries of Japan, Mexico, and Philippines are the major importers of North American sorghum, while China is the world's largest sorghum importer.

#### **3.3 Sorghum in Pakistan**

In Pakistan, sorghum is grown for fodder and forage of livestock. It is grown as kharif fodder in irrigated and rain fed areas of Punjab and Sindh provinces. Production of sorghum (*Sorghum bicolor*) in Pakistan is 1.45 million metric tons in 2020 (www.indexmundi.com). Sorghum is the second largest fodder crop after berseem (Pakistan Bureau of Statistics, 2016). Scarce record exists on use and adoption of

**Figure 1.** *Country-wise production of sorghum in the world.*

*3.4.3 Sorghum as feedstock for biofuels*

*DOI: http://dx.doi.org/10.5772/intechopen.95026*

*3.4.5 Sorghum as a climate smart crop*

a relatively healthy future.

**sorghum**

**107**

*3.4.6 Sorghum as a diverse crop*

*3.4.4 Sorghum as fodder*

Sorghum starch, sugar, and biomass are used as feedstocks for biofuel. High biomass sorghums developed by selective breeding are used as biofuel feedstock. Moreover, sweet sorghum has emerged as a promising contender of bioenergy. Its

For livestock feed, sorghum may be utilized in a number of ways like as green chop, grazed and made into hay or silage [14]. By adopting a combination of these systems, sorghum sufficiently meets the year round needs of stock farmers.

Worldwide climate change forecasts suggest incidences of low rainfall with variable distribution, flooding, extended droughts and elevated temperatures. Sorghum thrives exceptionally well under low water availability, heat, salinity and low inputs and thus is named as "the camel of crops". It is anticipated to perform high for food security of large number of masses with scant resources in arid zones of the world. According to climate predictions for 2050, sorghum will remain world's top crop to survive coming harsh weathers across the globe [15]. The crop is set to enjoy

Sorghum exhibits promising diversity in yield and quality traits as well as resilience to different environmental conditions in dry arid, semi-arid, temperate and tropical areas. In order to harness immense benefits of sorghum and for long term maintenance, there is a dire need to preserve this variability in the form of germplasm collections. Once this biodiversity in these collections is lost, it cannot be brought back. A crop with narrow genetic base cannot cope with drastic climatic stresses. Estimation of diversity among and within the species of any crop helps identify the germplasm with maximum variability that can be exploited in developing varieties of wide genetic background to withstand biotic and abiotic stresses.

**4. Case studies on morphometric and molecular characterization of**

National Agriculture Research Center, Islamabad, Pakistan [16]. Data for Plant height (PH), Days of 50% flowering (DF), Brix value(BV), Number of leaves per plant (NL), Leaf length (LL), Leaf width (LW), Leaf area index (LAI), Stem girth (SG), Flag leaf width (FLW), Flag leaf length (FLL), Flag leaf area index (FLAI), Fresh weight (FW) and Dry weight (DW) were recorded. The means and standard

error of means for each trait were calculated [17] and presented in **Table 1**.

correlation was obtained for Plant height (PH) with BV.

We report morphological characterization of ten sweet sorghum genotypes from

Correlation for observed 14 morphological traits is presented in **Table 2**. Number of leaves per plant (NL) indicated positive strong correlation with BV, LL, LAI, DW and PH. Whereas, NL showed moderate to low correlation with DTF, FLL, FLW, FLAI and DTM. The morphological trait DW showed positive higher correlation with NL, BV, SG, LL, LW, LAI and FW. Significant (p = 0.01) strong positive

stalk, seeds and syrup are used for biomass and ethanol production [13].

*Exploring Plant Genetic Variations with Morphometric and Molecular Markers*

#### **Figure 2.**

grain and sweet sorghum types as silage, fodder and bioethanol source in Pakistan. Exploring diversity of different sorghum types is vital to develop better sorghums.

#### **3.4 Multiple uses of sorghum**

Sorghum is ranked as 5th most widely grown cereal crop of the world. It has C4 photosynthetic pathway which is useful for global food production. It is a staple food with significant nutritional qualities for about 500 million people around the globe. With growing world population, the demand for reliable food and feed sources has also escalated. In the context of possible limited water supplies and high temperatures, sorghum's role to feed the world will increase in importance owing to its higher adaptability. Sorghum has amazing range of multiple uses:

#### *3.4.1 Sorghum grain as food*

Sorghum grain is used for food and biofuels. Grain has an edible hull and retains the majority of its nutrients. It contains 86% total digestible nutrients, up to 15.6% protein and 3772 kcal/kg energy. Sorghum grain has higher levels of magnesium that help in higher absorption of calcium and thereby contribute to bone health. It is abundant in phenolic compounds and antioxidants that safeguard against age-onset degenerative diseases [11]. Sorghum grain is reported to reduce the risk of many important diseases like cancer, cardiac infarction and some neurological disorders [12]. The grain is consumed as whole or ground to nutritious flour for baking. Most importantly, sorghum food products are gluten free, have wide range of color, neutral flavor and low allergenicity.

#### *3.4.2 Sorghum grain as feed*

Sorghum grain is second to maize in consumption as feed in the USA. It is a significant component of animal feed in South America, Australia and China, and poultry feed in India. The low-tannin high digestible sorghum (HDS) varieties are quickly replacing corn in poultry feed.

*Exploring Plant Genetic Variations with Morphometric and Molecular Markers DOI: http://dx.doi.org/10.5772/intechopen.95026*

#### *3.4.3 Sorghum as feedstock for biofuels*

Sorghum starch, sugar, and biomass are used as feedstocks for biofuel. High biomass sorghums developed by selective breeding are used as biofuel feedstock. Moreover, sweet sorghum has emerged as a promising contender of bioenergy. Its stalk, seeds and syrup are used for biomass and ethanol production [13].

#### *3.4.4 Sorghum as fodder*

For livestock feed, sorghum may be utilized in a number of ways like as green chop, grazed and made into hay or silage [14]. By adopting a combination of these systems, sorghum sufficiently meets the year round needs of stock farmers.

#### *3.4.5 Sorghum as a climate smart crop*

Worldwide climate change forecasts suggest incidences of low rainfall with variable distribution, flooding, extended droughts and elevated temperatures. Sorghum thrives exceptionally well under low water availability, heat, salinity and low inputs and thus is named as "the camel of crops". It is anticipated to perform high for food security of large number of masses with scant resources in arid zones of the world. According to climate predictions for 2050, sorghum will remain world's top crop to survive coming harsh weathers across the globe [15]. The crop is set to enjoy a relatively healthy future.

#### *3.4.6 Sorghum as a diverse crop*

grain and sweet sorghum types as silage, fodder and bioethanol source in Pakistan. Exploring diversity of different sorghum types is vital to develop better sorghums.

Sorghum is ranked as 5th most widely grown cereal crop of the world. It has C4 photosynthetic pathway which is useful for global food production. It is a staple food with significant nutritional qualities for about 500 million people around the globe. With growing world population, the demand for reliable food and feed sources has also escalated. In the context of possible limited water supplies and high temperatures, sorghum's role to feed the world will increase in importance owing to

Sorghum grain is used for food and biofuels. Grain has an edible hull and retains the majority of its nutrients. It contains 86% total digestible nutrients, up to 15.6% protein and 3772 kcal/kg energy. Sorghum grain has higher levels of magnesium that help in higher absorption of calcium and thereby contribute to bone health. It is abundant in phenolic compounds and antioxidants that safeguard against age-onset degenerative diseases [11]. Sorghum grain is reported to reduce the risk of many important diseases like cancer, cardiac infarction and some neurological disorders [12]. The grain is consumed as whole or ground to nutritious flour for baking. Most importantly, sorghum food products are gluten free, have wide range of color,

Sorghum grain is second to maize in consumption as feed in the USA. It is a significant component of animal feed in South America, Australia and China, and poultry feed in India. The low-tannin high digestible sorghum (HDS) varieties are

its higher adaptability. Sorghum has amazing range of multiple uses:

**3.4 Multiple uses of sorghum**

*Worldwide sorghum production statistics from 2012 to 2019.*

**Figure 2.**

*Genetic Variation*

*3.4.1 Sorghum grain as food*

neutral flavor and low allergenicity.

quickly replacing corn in poultry feed.

*3.4.2 Sorghum grain as feed*

**106**

Sorghum exhibits promising diversity in yield and quality traits as well as resilience to different environmental conditions in dry arid, semi-arid, temperate and tropical areas. In order to harness immense benefits of sorghum and for long term maintenance, there is a dire need to preserve this variability in the form of germplasm collections. Once this biodiversity in these collections is lost, it cannot be brought back. A crop with narrow genetic base cannot cope with drastic climatic stresses. Estimation of diversity among and within the species of any crop helps identify the germplasm with maximum variability that can be exploited in developing varieties of wide genetic background to withstand biotic and abiotic stresses.

### **4. Case studies on morphometric and molecular characterization of sorghum**

We report morphological characterization of ten sweet sorghum genotypes from National Agriculture Research Center, Islamabad, Pakistan [16]. Data for Plant height (PH), Days of 50% flowering (DF), Brix value(BV), Number of leaves per plant (NL), Leaf length (LL), Leaf width (LW), Leaf area index (LAI), Stem girth (SG), Flag leaf width (FLW), Flag leaf length (FLL), Flag leaf area index (FLAI), Fresh weight (FW) and Dry weight (DW) were recorded. The means and standard error of means for each trait were calculated [17] and presented in **Table 1**.

Correlation for observed 14 morphological traits is presented in **Table 2**. Number of leaves per plant (NL) indicated positive strong correlation with BV, LL, LAI, DW and PH. Whereas, NL showed moderate to low correlation with DTF, FLL, FLW, FLAI and DTM. The morphological trait DW showed positive higher correlation with NL, BV, SG, LL, LW, LAI and FW. Significant (p = 0.01) strong positive correlation was obtained for Plant height (PH) with BV.


#### **Table 1.**

*Cumulative response of sorghum genotypes for fourteen phenotypic traits.*

In PCA, three PCs were selected out of nine because their Eigen value is more than one. Selected PCs cover the character variability (**Tables 3** and **4**).

Bi-Plot (**Figure 3**) showed allocation of genotypes on the basis of performance. The characters which were far away from origin showed more variability.

Our group previously reported RAPD- based genetic diversity evaluation of sorghum germplasm of Pakistan [10]. We also performed molecular diversity analysis of twelve sweet sorghum genotypes with 17 RAPD primers viz.; GLA03, GLB10, GLC01, GLC 02, GLI06, GLL02, GLL05, GLL07, GLL09, GLL10, GLL12, GLL14, GLL15, GLL16, GLL17, GLL18 and GLL19 [18]. These markers yielded 77 fragments of different sizes and 6.41 bands per primer were produced on average (**Figure 4**). RAPD primers identified 83.33% polymorphism among sweet sorghum genotypes (**Figure 5**).

Genetic similarity was assessed among sorghum genotypes via Nei's similarity indices with popgen 1.32. The genotypes MN 2363 and Dobbs showed minimum similarity (76.92%). Whereas, Masaka and Dobbs exhibited the lowest similarity (44.87%) and hence the maximum divergence (**Table 5**).

The genetic relationship among sorghum genotypes was assessed by Popgen 1.32. All twelve sorghum genotypes were clustered in two groups with the help of Cluster analysis. Two genotypes (Malnal and Maska) were present in one group. While the rest of the genotypes constituted the second group. A close similarity was present among Masaka and Malnal that were clustered in Group A. Group B comprised of three genotypes, among these Dobbs and MN 2363 were clustered together and MN 2109 resided separately in this group. The genotypes Chedomba, Kamandri, Dura Huria and Juar were placed in Group C and IS12833, Juar 49 and Early Folger constituted Group D. The highest similarity was observed among Malnal and Masaka. On the other hand, the highest divergence was recorded between Malnal and Early Folger exhibited (**Figure 6**).

In a separate study, we explored genetic divergence of 24 sorghum genotypes with RAPD markers (OPL-7, OPL-8, OPA-13 and OPA-3) [19]. These markers produced

**Variables**

**109**

NL DTF

BV SG LL LW LAI FW DW FLL FLW FLAI

PH DTM

*\*,\*\*: Significant at 5% and 1% probability*

**Table 2.** *Correlation*

 *matrix for different traits in sweet sorghum genotypes.*

 0.466

 0.958

 0.764

> *level.*

 0.741

 0.662

 0.678

 0.654

 0.137

 0.470

 0.631

 0.396

 0.552

 0.764

**1**

0.722

 0.753

 1.000

 0.883

 0.903

 0.937

 0.957

 0.404

 0.739

 0.572

 0.543

 0.614

**1**

0.764

0.403

 0.479

 0.614

 0.551

 0.482

 0.670

 0.599

 0.064

 0.319

 0.914

 0.920

**1**

0.614

 0.552

0.403

 0.340

 0.543

 0.519

 0.367

 0.638

 0.541

 0.109

 0.299

 0.683

**1**

0.920

 0.543

 0.396

0.321

 0.550

 0.572

 0.487

 0.504

 0.579

 0.542

 0.004

 0.279

**1**

0.683

 0.914

 0.572

 0.631

0.787

 0.466

 0.739

 0.823

 0.799

 0.569

 0.719

 0.888

**1**

0.279

 0.299

 0.319

 0.739

 0.470

0.643

 0.123

 0.404

 0.594

 0.488

 0.245

 0.406

**1**

0.888

 0.004

 0.109

 0.064

 0.404

 0.137

0.717

 0.642

 0.957

 0.898

 0.947

 0.946

**1**

0.406

 0.719

 0.542

 0.541

 0.599

 0.957

 0.654

0.529

 0.699

 0.937

 0.853

 0.810

**1**

0.946

 0.245

 0.569

 0.579

 0.638

 0.670

 0.937

 0.678

*Exploring Plant Genetic Variations with Morphometric and Molecular Markers*

0.770

 0.640

 0.903

 0.872

**1**

0.810

 0.947

 0.488

 0.799

 0.504

 0.367

 0.482

 0.903

 0.662

0.686

 0.755

 0.883

**1**

0.872

 0.853

 0.898

 0.594

 0.823

 0.487

 0.519

 0.551

 0.883

 0.741

0.722

 0.753

**1**

0.883

 0.903

 0.937

 0.957

 0.404

 0.739

 0.572

 0.543

 0.614

 1.000

 0.764

0.347

**1**

0.753

 0.755

 0.640

 0.699

 0.642

 0.123

 0.466

 0.550

 0.340

 0.479

 0.753

 0.958

*DOI: http://dx.doi.org/10.5772/intechopen.95026*

**1**

0.347

 0.722

 0.686

 0.770

 0.529

 0.717

 0.643

 0.787

 0.321

 0.403

 0.403

 0.722

 0.466

 **NL**

 **DTF**

 **BV**

 **SG**

 **LL**

 **LW**

 **LAI**

 **FW**

 **DW**

 **FLL**

 **FLW**

 **FLAI**

 **PH**

 **DTM**


#### *Exploring Plant Genetic Variations with Morphometric and Molecular Markers DOI: http://dx.doi.org/10.5772/intechopen.95026*

**Table 2.**

*Correlation matrix for different traits in sweet sorghum genotypes.*

In PCA, three PCs were selected out of nine because their Eigen value is more

**Variables Range Mean Std. deviation**

NL 8.55 11.89 10.00 1.17 DTF 58.33 77.56 71.45 6.02 BV 6.81 9.87 8.22 0.97 SG 1.60 5.67 3.71 1.12 LL 34.71 76.90 53.70 12.86 LW 3.33 7.23 4.97 1.15 LAI 130.71 518.36 277.51 126.90 FW 56.70 100.80 82.25 13.03 DW 32.55 52.85 41.90 6.19 FLL 21.84 33.75 27.66 4.03 FLW 2.36 3.36 2.71 0.35 FLAI 57.36 113.35 75.78 20.20 PH 158.71 230.02 191.40 22.50 DTM 106.33 124.78 117.45 5.84

**Minimum Maximum**

Bi-Plot (**Figure 3**) showed allocation of genotypes on the basis of performance.

Our group previously reported RAPD- based genetic diversity evaluation of sorghum germplasm of Pakistan [10]. We also performed molecular diversity analysis of twelve sweet sorghum genotypes with 17 RAPD primers viz.; GLA03, GLB10, GLC01, GLC 02, GLI06, GLL02, GLL05, GLL07, GLL09, GLL10, GLL12, GLL14, GLL15, GLL16, GLL17, GLL18 and GLL19 [18]. These markers yielded 77 fragments of different sizes and 6.41 bands per primer were produced on average (**Figure 4**). RAPD primers identified 83.33% polymorphism among sweet sorghum genotypes (**Figure 5**). Genetic similarity was assessed among sorghum genotypes via Nei's similarity indices with popgen 1.32. The genotypes MN 2363 and Dobbs showed minimum similarity (76.92%). Whereas, Masaka and Dobbs exhibited the lowest similarity

The genetic relationship among sorghum genotypes was assessed by Popgen 1.32. All twelve sorghum genotypes were clustered in two groups with the help of Cluster analysis. Two genotypes (Malnal and Maska) were present in one group. While the rest of the genotypes constituted the second group. A close similarity was present among Masaka and Malnal that were clustered in Group A. Group B comprised of three genotypes, among these Dobbs and MN 2363 were clustered together

and MN 2109 resided separately in this group. The genotypes Chedomba,

Kamandri, Dura Huria and Juar were placed in Group C and IS12833, Juar 49 and Early Folger constituted Group D. The highest similarity was observed among Malnal and Masaka. On the other hand, the highest divergence was recorded

In a separate study, we explored genetic divergence of 24 sorghum genotypes with RAPD markers (OPL-7, OPL-8, OPA-13 and OPA-3) [19]. These markers produced

than one. Selected PCs cover the character variability (**Tables 3** and **4**).

*Cumulative response of sorghum genotypes for fourteen phenotypic traits.*

**Table 1.**

*Genetic Variation*

**108**

The characters which were far away from origin showed more variability.

(44.87%) and hence the maximum divergence (**Table 5**).

between Malnal and Early Folger exhibited (**Figure 6**).


#### **Table 3.**

*Principle component analysis.*


#### **Table 4.**

*PCA factor loadings for sorghum genotypes.*

74 bands of varying sizes/intensities. On average, each primer produced 18.5 bands.

While, previous fingerprinting studies showed 58% [20] and 52% polymorphism [21] among various sorghum genotypes. The primer OPL7 produced the maximum number of fragments [22] whereas, the minimum number of fragments were generated by OPA3 (14) (**Figure 7**). The low level of similarity indicated high

More recently, we exploited sixteen SSR markers for DNA fingerprinting of fifty sorghum genotypes [8]. The molecular analysis indicated significant polymorphism

The bands varied in size and intensity. The number of bands per primer per genotypes also varied. Some bands showed a high level of polymorphism indicating great variation among the sorghum germplasm (**Figure 8**). Marker diversity among

RAPD markers revealed 77.13% polymorphism among sorghum genotypes.

divergence among the sorghum germplasm under study.

*Number of polymorphic bands per primer in sorghum genotypes.*

among these genotypes.

**Figure 4.**

**Figure 5.**

**111**

*Number of bands recorded per sorghum genotype.*

*DOI: http://dx.doi.org/10.5772/intechopen.95026*

*Exploring Plant Genetic Variations with Morphometric and Molecular Markers*

**Figure 3.** *PCA Biplot.*

*Exploring Plant Genetic Variations with Morphometric and Molecular Markers DOI: http://dx.doi.org/10.5772/intechopen.95026*

**Figure 4.** *Number of bands recorded per sorghum genotype.*

#### **Figure 5.**

**F1 F2 F3 F4 F5 F6 F7 F8 F9**

Eigen value 9.292 2.103 1.154 0.604 0.381 0.281 0.114 0.054 0.017 Variability (%) 66.373 15.024 8.241 4.316 2.722 2.006 0.812 0.385 0.122 Cumulative % 66.373 81.397 89.638 93.953 96.675 98.681 99.493 99.878 100.000

**Variables PC1 PC2 PC3** NL 0.750 0.394 0.248 DTF 0.768 0.206 0.528 BV 0.970 0.032 0.104 SG 0.939 0.170 0.066 LL 0.913 0.218 0.092 LW 0.911 0.148 0.070 LAI 0.948 0.068 0.024 FW 0.469 0.747 0.311 DW 0.781 0.556 0.139 FLL 0.668 0.577 0.189 FLW 0.632 0.476 0.527 FLAI 0.712 0.568 0.397 PH 0.970 0.032 0.104 DTM 0.796 0.229 0.433 Eigen value 9.292 2.103 1.154 Variability (%) 66.373 15.024 8.241 Cumulative % 66.373 81.397 89.638

**Table 3.**

*Genetic Variation*

**Table 4.**

**Figure 3.** *PCA Biplot.*

**110**

*PCA factor loadings for sorghum genotypes.*

*Principle component analysis.*

*Number of polymorphic bands per primer in sorghum genotypes.*

74 bands of varying sizes/intensities. On average, each primer produced 18.5 bands. RAPD markers revealed 77.13% polymorphism among sorghum genotypes.

While, previous fingerprinting studies showed 58% [20] and 52% polymorphism [21] among various sorghum genotypes. The primer OPL7 produced the maximum number of fragments [22] whereas, the minimum number of fragments were generated by OPA3 (14) (**Figure 7**). The low level of similarity indicated high divergence among the sorghum germplasm under study.

More recently, we exploited sixteen SSR markers for DNA fingerprinting of fifty sorghum genotypes [8]. The molecular analysis indicated significant polymorphism among these genotypes.

The bands varied in size and intensity. The number of bands per primer per genotypes also varied. Some bands showed a high level of polymorphism indicating great variation among the sorghum germplasm (**Figure 8**). Marker diversity among


*are symbols just to separate above diagonal and below diagonal* 

**Table 5.**

*Similarity matrix of 12 sweet sorghum genotypes.*

fifty sorghum genotypes was studied using Powermarker software. The number of alleles per locus ranged from 2 to 3 with mean value of 2.875 alleles per locus. Genetic relationship among sorghum genotypes was evaluated by using popgen 1.32. All genotypes were grouped in two major clusters which were further divided into sub-groups. One small group consisted of eight genotypes (15, 39, 16, 35, 20, 22, 24, and 18) and the other large group contained remaining 42 sorghum genotypes. Maximum genetic distance was observed between 1st and 18th genotype.

*–24: Sorghum*

*PCR amplification of 24 sorghum genotypes with RAPD primer L-7. Lanes L: Ladder, 1*

**Figure 6.**

**Figure 7.**

*genotypes.*

**113**

*Dendrogram of 12 sweet sorghum genotypes based on RAPD analysis.*

*Exploring Plant Genetic Variations with Morphometric and Molecular Markers*

*DOI: http://dx.doi.org/10.5772/intechopen.95026*

*Exploring Plant Genetic Variations with Morphometric and Molecular Markers DOI: http://dx.doi.org/10.5772/intechopen.95026*

#### **Figure 6.** *Dendrogram of 12 sweet sorghum genotypes based on RAPD analysis.*

**Figure 7.**

*PCR amplification of 24 sorghum genotypes with RAPD primer L-7. Lanes L: Ladder, 1–24: Sorghum genotypes.*

fifty sorghum genotypes was studied using Powermarker software. The number of alleles per locus ranged from 2 to 3 with mean value of 2.875 alleles per locus. Genetic relationship among sorghum genotypes was evaluated by using popgen 1.32. All genotypes were grouped in two major clusters which were further divided into sub-groups. One small group consisted of eight genotypes (15, 39, 16, 35, 20, 22, 24, and 18) and the other large group contained remaining 42 sorghum genotypes. Maximum genetic distance was observed between 1st and 18th genotype.

**pop ID**

**112**

1 2 3 4 5 6 7 8 9 10 11 12

*Nei's genetic identity (above diagonal) and genetic distance (below diagonal). 1: Malnal, 2: Masaka, 3: MN 2109, 4: Chedomba,*

*11: Kamandri,* *\*\*\*\* are symbols just to separate above diagonal and below diagonal values*

**Table 5.** *Similarity matrix of 12 sweet sorghum genotypes.*

 *12: Early Folger*

0.4855

 0.5725

 0.5281

 0.3864

 0.4249

 0.5955

 0.5500

 0.5725

 *5: Dobbs, 6: MN 2363, 7: Dura Huria, 8: IS 12833, 9: Juar 49, 10:Juar 48,*

 0.3864

 0.6431

 0.5500

 \*\*\*\*

0.6431

 0.8602

 0.3494

 0.2963

 0.2963

 0.4055

 0.2963

 0.3494

 0.4855

 0.4855

 \*\*\*\*

 0.5769

0.6431

 0.5500

 0.3494

 0.4055

 0.5725

 0.3314

 0.3677

 0.4249

 0.5281

 \*\*\*\*

 0.6154

 0.5256

0.3864

 0.6431

 0.4249

 0.4855

 0.4855

 0.4855

 0.4855

 0.3137

 \*\*\*\*

 0.5897

 0.6154

 0.6795

0.5281

 0.7191

 0.3677

 0.4649

 0.3864

 0.2792

 0.3494

 \*\*\*\*

 0.7308

 0.6538

 0.7051

 0.5641

0.6931

 0.6431

 0.3137

 0.3677

 0.4855

 0.3677

 \*\*\*\*

 0.7051

 0.6154

 0.6923

 0.7436

 0.5769

0.5500

 0.7458

 0.3137

 0.4447

 0.2624

 \*\*\*\*

 0.6923

 0.7564

 0.6154

 0.7179

 0.6667

 0.5513

0.5500

 0.8014

 0.2792

 0.3677

 \*\*\*\*

 0.**7692**

0.5500

 0.5955

 0.3137

 \*\*\*\*

 0.6923

 0.6410

 0.6923 0.6154

 0.6795

 0.6154

 0.5641

 0.7436

 0.6538

 0.6282

 0.6154

 0.6667

 0.7436

 0.6795

0.4447

 0.6190

 \*\*\*\*

 0.7308

 0.7564

 0.7308

 0.7308

 0.6923

 0.6538

 0.7051

 0.7051

 0.5897

0.4855

 \*\*\*\*

 0.5385

 0.5513

 **1** \*\*\*\*

 0.6154

 0.6410

 0.5769

 0.5769 **0.4487**

0.4744

 0.5256

 0.4872

 0.5256

 0.5769

 0.4231

 0.5641

 0.5769

 0.5000

 0.5897

 0.6795

 0.5256

 0.5256

 0.6154

**2**

**3**

**4**

**5**

**6**

**7**

**8**

**9**

**10**

**11**

**12**

*Genetic Variation*

**Sr. # Sorghum germplasm Morphological traits References**

*Exploring Plant Genetic Variations with Morphometric and Molecular Markers*

28 agro morphological traits (Vigor at emergence 5(Ve), Coleoptile color (Cc), Leaf anthocyanin pigmentation (Lap), Panicle compactness (Pc), Pedicellate spikelet length (Psl) and Persistence (Psp), Glume length (Gl) and opening (Go), Awn (Aw), Kernel shape (Ks), Kernel rotation (Kr), Glume color (Gc), Kernel color (Kc), Anthocyanin spots on kernels (Ask), Glume adherence (Ga), Seed coat or testa (Sc) and Kernel vitreousness (Kv), Plant height (Ph), Leaf number (Ln), Length (Ll) and Width (Lw) of the third leaf under the panicle, Number of effective tillers (Net), Panicle length (Pl), Panicle weight (Pw), Harvested seed weight (Hsw) and 1000-seed weight (1000-Sw)

Lowering time, Plant height, and panicle type/ inflorescence, Panicle type and glumes

Stay-green, Peduncle exertion, Panicle length and width, Plant height, Days to flowering and maturity, Grain yield, Biomass and Harvest

Days to flowering (DF), Days to maturity (DM), Plant height (PH) (cm), Panicle length (PL) (cm), Panicle exertion (cm), Head weight (HW) (g), Yield per panicle (YPP) (g), Thousand seed weight (TSW) (g), Biomass (BM) yield (ton/ha) and GY (kg/ha)

Days to flowering, Days to maturity, Plant height, Grain yield per plant, Panicle length, Number of tillers per plant, Panicle weight, Panicle exsertion, Thousand seed weight, Grain-

Days to 50% flowering, Days to maturity, Plant height, Panicle length, Panicle width, Leaf length, Leaf breadth, Number of leaves per plant, Stem girth, Number of primary branches per panicle, Hundred-seed weight, Yield per plant, Panicle weight and Dry matter

Leaf rolling, Head compactness, Glume cover, Glume color, Leaf orientation, Midrib color,

Biomass and Biofuel traits Mocoeur et al. [30]

coverage, grain color

index under Drought stress

7 25 sorghum genotypes Seedling vigor, Number of leaves, Leaf area,

filling period

production

Barro-Kondombo et al. [26]

Sharma et al. [27]

Abraha et al. [28]

Sabiel et al. [29]

Mohammed et al.

[31]

Sinha and Kumaravadivel [32]

Amelework et al.

[33]

5 124 sorghum from Burkina Faso

*DOI: http://dx.doi.org/10.5772/intechopen.95026*

6 156 sorghum accessions

8 9 sorghum genotypes from Sudan

9 Recombinant inbred line of *Sorghum bicolor* made by crossing E-Tian, a sweet sorghum accession with Ji2731

10 Diallel set of 10

11 40 accessions of

Nadu

12 267 sorghum genotypes from Ethiopia

**115**

parents and their 90 crosses including reciprocals of sorghum

sorghum from Tamil

length (LL) and Leaf width (LW), Panicle shape (PS), Panicle type (PT), Coleoptile's color (CC), Quantity of lipid white powder on stem and leaves (LWP), Color of midrib (MC), Neck length of panicle (PNL), Awn presence (AP), Glume color (GC), Growth in early stage (GES), Endosperm type (ET), Aphid resistance (AR), Number of regenerated tillers (NRT), Regrowth (RG) and Resistance to insecticides (RI)

This study revealed positive correlation among the allele number, gene diversity and PIC value. The ease of using these PCR-based markers for diversity evaluation, for allocating genotypes to heterotic groups, and for DNA fingerprinting proved advantageous for selecting biomass- related traits and for sorghum breeding programs.
