**3. Genetic diversity evaluation using quantitative biomass traits of sorghum**

Sorghum genetic resource characterization is based on morphological, biochemical, and molecular marker approaches. The most economical approach is morphological characterization for diversity evaluation and identifying promising genotypes. The agro-morphological characterization of sorghum is well reported [33]. The genetic diversity of sorghum germplasm comprising of different sorghum types was evaluated [34] by exploiting the quantitative characters. Nine of 14 quantitative traits were selected on the basis of their diverse nature. Panicle width, stem girth, and leaf breadth proved more diverse traits as indicated by principal component analysis. The hierarchical cluster analysis grouped sorghum germplasm into six classes. The clusters 1 and VI contained the maximum and minimum numbers of accessions, respectively, while the clusters VI and IV were the most distantly related among all the clusters. The accessions grouped in cluster III had the highest average yield and hundred seed weight. The present study indicated that high yielding and diverse accessions can serve as better parents for sorghum variety development.

uptake patterns. This is a quantitative trait governed by nuclear genes [23]. Various sorghums

Sorghum is a short-day plant belonging to semiarid region. The photoperiod sensitivity of sorghum is a recessive trait that causes longer vegetative period, which supports plant growth and in turn the green mass production. Sorghum maturity trait is controlled by six genes: *Ma1*, *Ma2*, *Ma3*, *Ma4*, *Ma5*, and *Ma6*. *Ma1* gene is known to be regulated by photoperiod in order to effect height and flowering time. *Ma1* has the largest impact on flowering date of all the maturity genes [25]. The *Ma5* gene, when present in the dominant form together

Sorghum is referred as perennial grass due to its tillering capacity. The number and types of branching in sorghum are genetically controlled. Secondary and tertiary branches termed as vegetative branching are thought to be controlled by the same genetic factors [28], while distinct genetic elements might control tillering or mature branching in sorghum. Tillering enhances accumulation of sugars in sorghum stem for biofuel production [29, 30]. It imparts greater leaf area leading to higher intercepted radiations and thereby also affects biomass accumulation in sorghum. High-tillering sorghum thrives best in appropriate growth conditions where all the resources are best utilized [31]. Sorghum plants with excessive tillers and

Sorghum is a C4 plant with characteristic drought tolerance owing to its efficient root system. It is a single-stemmed grass anchored by spreading and fibrous root system having primary, secondary, and supporting roots. The roots may extend from 1.5 to 2.5 m up to 1 m below the soil in all directions. Higher biomass yield is associated with the cloning of genes linked with

Significant variability in leaf size has been noticed in sorghum. This affects energy-capturing potential, conversion into biomass, and physiological activity. Smaller leaves are adapted to dry and hot regions, whereas in cooler and humid climates, plants with larger leaves are found having insufficient energy conversion capacity. Several other traits are also desirable for energy sorghum, like low grain yield, resistance to lodging, low water content, and biomass quality [32].

**3. Genetic diversity evaluation using quantitative biomass traits of** 

Sorghum genetic resource characterization is based on morphological, biochemical, and molecular marker approaches. The most economical approach is morphological characterization for diversity evaluation and identifying promising genotypes. The agro-morphological characterization of sorghum is well reported [33]. The genetic diversity of sorghum germplasm comprising of different sorghum types was evaluated [34] by exploiting the quantitative characters. Nine of 14 quantitative traits were selected on the basis of their diverse nature. Panicle width, stem girth, and leaf breadth proved more diverse traits as indicated by principal component analysis. The hierarchical cluster analysis grouped sorghum germplasm into six classes. The clusters 1 and VI contained the maximum and minimum numbers of accessions, respectively,

have been reported exhibiting different types of stay-green phenotypes [24].

26 Advances in Biofuels and Bioenergy

with *Ma6*, very strongly inhibits floral initiation regardless of day length [26, 27].

limited water availability exhibit low biomass and grain yield potential [32].

root loci and improvement in root structure genetic design.

**sorghum**

Disasa et al. [35] conducted a study to characterize the brix degree, grain yield, and some morphological traits of 180 sorghum accessions from Ethiopia and analyzed them under different environments. Greater variability was observed among genotypes collected from different areas. Genotypes collected from northern areas of the country showed high brix value, while the rest of the collection contained high biomass for sugar stalk yield. Cultivars with high-biomass traits and brix value were recommended for utilization in breeding programs to develop sugar-rich sorghum genotypes.

In a recent study, the genetic divergence among 208 Pakistani sorghum genotypes was estimated [36] by evaluating the 14 different quantitative traits for two consecutive years. Multivariate tools like principal component analysis (PCA) and unweighted pair-group method with arithmetic mean (UPGMA) analysis were employed. Study revealed broader variability in fresh biomass, dry biomass, flag leaf area index, leaf area index, and plant height. Broad-sense heritability was reported to be >80% for all traits in both years. The PCA showed that all the biomass-related traits with eigenvalue >1 were contributing significantly in the first three PC axes (75.39 and 71.21% for both years). This indicated the presence of maximum variability among these genotypes. Such a diverse germplasm might be a good candidate for varietal development. Pearson correlation analysis indicated that fresh and dry biomass had a significant positive correlation with leaf area index, number of leaves per plant, flag leaf area index, days to maturity, and 50% days to flowering for 2 years. UPGMA analysis classified the germplasms into 141 morphotypes and 7 classes in the first year and 136 morphotypes and 5 classes in the second year. The genotype P-13-2013 was found to be the best performer with relevance to traits such as the number of leaves per plant, stem thickness, leaf length, fresh biomass, dry biomass, and flag leaf area index. The genotypes Indian-6, BM-726, P-10-2013, and Johar-2013 showed good performance in terms of fresh biomass and days to 50% flowering.

Further, Shokat [37] performed assessment of 1300 diverse USDA sorghum collections on the basis of morphological traits for two consecutive years (2015–2017). The 24 high-biomass sorghum lines selected from the first year trials were further investigated for biomass-related traits in the second year. Out of nine traits evaluated, viz., germination percentage, number of leaves per plant, number of nodes per plant, days to 50% flowering, stem girth, fresh biomass, dry biomass, days to maturity, and plant height, three proved statistically significant, including number of leaves, number of nodes, and stem girth. Sorghum accession number NSL-54978 gave highly significant value for the number of leaves and number of nodes, while sorghum accession number PI-525981-01-SD exhibited significantly higher value for stem thickness. Correlation analysis indicated a significant relationship among stem girth and fresh biomass, days to maturity, and fresh biomass. PCA exhibited 48.9% expression for the number of leaves and number of nodes, while 46.9% expression was recorded for fresh biomass. The biplot analysis showed maximum diversity in fresh biomass, stem girth, days to maturity, and plant height characters (**Figures 1** and **2**).

**4. QTL mapping of quantitative traits in sorghum**

**Figure 3.** Cluster analysis of 24 sorghum genotypes on the basis of morphological characters.

sites), and DArTs (diversity arrays technology) [39–41].

traits.

Germplasm characterization using morphological traits has some limitations. The expression of a phenotype is mostly influenced by the environment and depends upon plant organ as well as plant developmental stages. Owing to these shortcomings, it is the least preferred means of characterizing crop germplasms. Hence, investigating DNA polymorphism is a reliable means of genetic diversity assessment. Molecular markers are extensively used in molecular breeding being reliable, abundant, phenotypically unbiased, and time and stage independent. These markers are helpful in improving breeding programs through different ways. The marker-assisted selection (MAS) technology makes use of an association between the expression of desired characters and markers present in the DNA. Quantitative trait loci (QTL) for many traits can be evaluated by using molecular markers [38]. For a given trait in a particular population, increasing marker density can increase the resolution of the genetic map, thus enhancing the precision of QTL mapping. Genetic mapping studies are based mainly on BTx623 and other grain sorghum types. Widely used polymerase chain reaction (PCR)-based markers are RAPD (random amplified polymorphic DNA), AFLP (amplified fragment length polymorphism), SSRs (simple sequence repeats), STS (sequence-tagged

Genetic Improvement of Sorghum for Biomass Traits Using Genomics Approaches

http://dx.doi.org/10.5772/intechopen.73010

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Recently, there has been a growing interest in exploiting QTL mapping for different traits. About >700 QTLs have been identified for several traits in sorghum (http://www.gramene. org). However, fewer studies have been carried out to find out the molecular basis of these

The biomass trait of sorghum depends on stem height and thickness, which are vital for bioethanol production. Taller varieties produce higher biomass with thicker stem and higher sugar contents. Height is positively correlated with biomass production and independent of stem structural composition like cellulose, hemicellulose, and lignin content. The QTL for total dry biomass has been found to localize with height QTLs [42, 43]. In sorghum, height is controlled by few QTLs. Genetic study has identified four loci controlling stem height: *Dw1*, *Dw2*, *Dw3*, and *Dw4* [44]. *Dw3*, which encodes a P-glycoprotein that controls polar auxin transport, has been cloned [45]. This gene is also co-localized with a height QTL on chromosome 7 [42]

**Figure 1.** Biplot with sorghum genotypes.

UPGMA analysis generated 9 morphotypes of 24 sorghum genotypes (**Figure 3**). Total of 24 genotypes were divided into five different classes. Cluster analysis revealed that the main cluster was divided into two major clusters. The first subcluster comprised four genotypes (6, 24, 16, and 20), while the second subcluster was further subdivided into four different small clusters. Two genotypes were present in the cluster with blue-colored cluster, and 11 genotypes were placed in light blue-colored cluster. The class represented by red color consists of two genotypes, whereas the class represented by green color includes three genotypes.

**Figure 2.** Biplot with cumulative sorghum variables and genotypes.

**Figure 3.** Cluster analysis of 24 sorghum genotypes on the basis of morphological characters.
