**2. Material and methods**

#### **2.1. Plant material**

glucose accumulation and yield. In some cases, stress conditions may increase sugar beet root quality and potential of recovery if plants were not highly damaged by water deficiency [29].

Higher nitrogen supply increases proline content and may also increase leaf area index (LAI) and drought stress impact. Positive and significant correlation among proline and glucose content in sugar beet root indicates the relationship between the response to stress, carbohydrates, and proline and glucose accumulation ratio. This is supported by the effect of treatment with di-1-p-mentene (anti-transpirant) and DMDP (2,5-dihydroxymetil-3,4-dihydroxypyrolidine, glycosidase inhibitor), which decreased proline content in roots of irrigated sugar beet [29]. Presence of compounds such as proline and glucose adversely affect sugar crystallization and lead to the formation of colored components, thus reducing industrial quality of beet roots [30]. Proline accumulated in sugar beet root, as a nitrogen compound, reduces the quality of roots. Both, the stress and an excess of nitrogen lead to the mobilization of accumulated carbohydrates, which are the source of energy essential for adaptation to the stress conditions. Moreover, chemicals containing nitrogen (e.g., proline) reduce the yield of sucrose and the quality of the roots [29]. The importance of the accumulation of proline in osmotic adjustment is still debatable and varies from species to species [31]. The highest proline accumulation was observed at the end of beet root growth [29]. Correlation between drought and proline content suggests, however, that alteration in proline concentration is useful stress indicator in sugar beet [28]. Proline may act as a signal molecule which alters mitochondrial function, affects cell division and gene expression. This role of proline may be very significant for plant

recovery when favorable conditions are regained [32].

74 Plant, Abiotic Stress and Responses to Climate Change

**1.6. The use of plant biotechnology to increase tolerance to water deficiency**

for tolerance to drought seems necessary to solve this complex problem [35].

Basic need for sustainable food production directed research programs towards improving traits of crops despite the size and complexity of their genome [33]. Plant biotechnology is a process in which the use of molecular and cytological techniques help to increase the productivity of the plants, to improve the quality of plant products, to prevent the damage caused under the influence of various biotic and abiotic stresses. Plant breeding reliving on the employment of molecular markers [Marker Assisted Selection (MAS)] is one of the promising techniques to improve crop resilience. A prerequisite for the success of MAS is defining the genes which regulate traits of interest and to test relationships between potential markers and those traits. Only when this link is defined, i.e., when the marker is physically located in the vicinity of or even within the gene of interest, it is possible to use it efficiently in breeding [34]. In sugar beet, development of breeding programs aimed to increase drought tolerance is further complicated by the fact that several types of abiotic stresses often occur at the same time during the growing season, and approach which involves a manipulation of a group of genes

In an era of rapid progress in the identification and characterization of complete segments of plant genome, proteins, transcripts, metabolites, as well as their interactions in a biological system, new discoveries will lead to better understanding and possibly to manipulation of physiological responses to water deficit [36]. Evaluation of the relative contribution of genes The study involved 11 genotypes (marked from 1 to 11) of sugar beet (*Beta vulgaris* ssp. *vulgaris*, L.) differing in levels of drought tolerance, according to observation test conducted in the field. According to this test, genotypes were divided into three groups: (1) sensitive genotypes: 2, 5, 6, and 8; (2) moderately tolerant: 3, 7, 9, and 11; and (3) tolerant: 1, 4, and 10.

Experiment was conducted in three stages:


for DNA/RNA analysis (leaves) were taken 5 days after the last watering (experiment 1) and used for DNA/mRNA extractions. mRNA was used to synthesize cDNA, and this cDNA was

Sugar Beet Tolerance to Drought: Physiological and Molecular Aspects

http://dx.doi.org/10.5772/intechopen.72253

77

Statistical analyses of data were performed by different statistical methods. ANOVA was applied, to photosynthetic pigments (MCMCglmm Methods, [51]), using Package R (http:// www.jstatsoft.org/v33/i02/). Logarithmic and Jonson's transformations (Minitab) were performed for parameters with large data variability, in order to normalize their distribution. Confidence intervals for fitted mean responses were calculated as quantiles of simulated distributions of the expected response values. Analyses were done with the R environment [52]

As previously indicated (**Tables 1** and **2**), climatic conditions in our region suggest the need for research, which has the potential to enhance selection of genotypes more tolerant to drought.

Sugar beet genotypes in semi-controlled conditions showed different reactions to 5-day water deficiency. As expected, decline in turgor was observed in all genotypes. Number of leaves was significantly different between treatments and respective controls. Concentrations of photosynthetic pigments and leaf area varied between genotypes and standard normal distribution was not observed here. Therefore, the data were subjected to Johnson's data transformation which proved to be very effective [55]. This procedure allowed assessing differences in

Secession in water supply caused water loss from plant tissues within both sensitive and tolerant genotypes. Due to this fact, sugar beet genotypes may be divided on the basis of tested

The results obtained in semi-controlled conditions (experiment 1) were compared to previous field observations (**Figure 3**). Proline concentration increased in all genotypes after exposure to water deficit as well as % of DM (except for genotypes 9 and 11). Changes within treatments with respect to control, referring to dry weight were less pronounced than changes referring to % of DM and RWC of root, stem, and leaf. Plants subjected to stress conditions had in aver-

The relationships between two effects on measured traits were assessed by mixed model (**Figure 4**). Crossed pink lines in diagrams represent average impact on genotypes in control

template in further PCR reactions [42].

and the contributed packages lme4 [53] and ggplot2 [54].

**3.1. Experiment under semi-controlled conditions in greenhouse**

parameters and following treatments (**Figure 2**).

*3.1.1. Sugar beet genotype classification based on physiological tests in semi-controlled* 

concentrations of photosynthetic pigments between different genotypes (**Figure 1**).

age three leaves less, 4% higher % of DM, and seven times higher proline content.

**2.2. Statistical analyses**

**3. Results and discussion**

*conditions*

#### *2.1.1. Experiment under semi-controlled conditions in greenhouse*

Sugar beet seeds were sown in growth substrate Potgrond H (Klasmann), mixed with river sand (17.5:1) in plastic pots (31 × 37 × 13 cm). A single pot contained 12 plants. During 90-day period, soil moisture was kept at 80% field capacity. Plant watering was conducted on the basis of evapotranspiration. When the plants were at the 6–12 leaves stage, they were exposed to water deficit by cessation of watering, while control plants were watered. Five days later, molecular and physiological analyses were done.

After drying plant material on 105–130°C to its constant mass, % of dry matter was determined. Activity of photosynthetic apparatus was assessed by monitoring of F0(initial), Fm(maximal), Fv(variable), Fv /Fm, and t1/2 using plant stress meter (PSM, BioMonitor S.C.I. AB). Free proline concentration was measured in the both *in vitro* and *in vivo* conditions [43]. Concentration of chloroplast pigments was determined spectrophotometrically [44, 45]. Leaf area (LA) was measured by automatic leaf area meter LI-3000 (LI-COR, USA).

#### *2.1.2. Experiment in tissue culture*

In this experiment, MS basic substrate was used [46] with 0.3 mg/l BA (benzyldenine) and 0.01 mg/l GA3 (gibberellic acid). In order to obtain sufficient number of axillary shoots (64), equal in size, subcultivation was done every 3 weeks. Lack of water was caused by addition of polyethylene glycol to the substrate. Obtained shoots were set on a substrate for micropropagation with 0, 3, and 5% of polyethylene glycol (PEG 6000, Duchefa, Netherlands). Plants were cultivated on this substrate for 4 weeks and afterwards fresh weight of shoots, as well as dry matter and free proline content were determined. The temperature during the experiment in air conditioning chamber was 21–23°C, with a photoperiod of 16 h of light and 8 h of dark.

#### *2.1.3. Gene expression analyses of water regime responsible genes in leaves (plants grew in the first experiment)*

The changes in gene expression were analyzed in the leaves of the sugar beet plants grown in the greenhouse experiment. Candidate genes were selected from the previous studies [47–50]. For 13 candidate genes which are, considered to be, involved in osmotic and salt stress responses, primers were constructed and used to screen for polymorphisms at the DNA and gene expression levels. Ten selected candidate genes were homologous probes (BI543470, BI096135, AW697770, BI543640, BG932913, BI096146, BQ060651, BF011094, BI096078, and BF011254), and heterologous probes from maize (X15290), alfalfa (BI543243), and carrot (BI073246). Samples for DNA/RNA analysis (leaves) were taken 5 days after the last watering (experiment 1) and used for DNA/mRNA extractions. mRNA was used to synthesize cDNA, and this cDNA was template in further PCR reactions [42].

#### **2.2. Statistical analyses**

Experiment was conducted in three stages:

76 Plant, Abiotic Stress and Responses to Climate Change

**2.** In in vitro conditions of tissue culture.

greenhouse experiment).

Fv

**1.** Under semi-controlled conditions in greenhouse.

molecular and physiological analyses were done.

automatic leaf area meter LI-3000 (LI-COR, USA).

*2.1.2. Experiment in tissue culture*

0.01 mg/l GA3

*first experiment)*

*2.1.1. Experiment under semi-controlled conditions in greenhouse*

**3.** Gene expression analyses of water regime responsible genes in leaves (plants from the

Sugar beet seeds were sown in growth substrate Potgrond H (Klasmann), mixed with river sand (17.5:1) in plastic pots (31 × 37 × 13 cm). A single pot contained 12 plants. During 90-day period, soil moisture was kept at 80% field capacity. Plant watering was conducted on the basis of evapotranspiration. When the plants were at the 6–12 leaves stage, they were exposed to water deficit by cessation of watering, while control plants were watered. Five days later,

After drying plant material on 105–130°C to its constant mass, % of dry matter was determined. Activity of photosynthetic apparatus was assessed by monitoring of F0(initial), Fm(maximal), Fv(variable),

/Fm, and t1/2 using plant stress meter (PSM, BioMonitor S.C.I. AB). Free proline concentration was measured in the both *in vitro* and *in vivo* conditions [43]. Concentration of chloroplast pigments was determined spectrophotometrically [44, 45]. Leaf area (LA) was measured by

In this experiment, MS basic substrate was used [46] with 0.3 mg/l BA (benzyldenine) and

equal in size, subcultivation was done every 3 weeks. Lack of water was caused by addition of polyethylene glycol to the substrate. Obtained shoots were set on a substrate for micropropagation with 0, 3, and 5% of polyethylene glycol (PEG 6000, Duchefa, Netherlands). Plants were cultivated on this substrate for 4 weeks and afterwards fresh weight of shoots, as well as dry matter and free proline content were determined. The temperature during the experiment in air conditioning chamber was 21–23°C, with a photoperiod of 16 h of light and 8 h of dark.

*2.1.3. Gene expression analyses of water regime responsible genes in leaves (plants grew in the* 

The changes in gene expression were analyzed in the leaves of the sugar beet plants grown in the greenhouse experiment. Candidate genes were selected from the previous studies [47–50]. For 13 candidate genes which are, considered to be, involved in osmotic and salt stress responses, primers were constructed and used to screen for polymorphisms at the DNA and gene expression levels. Ten selected candidate genes were homologous probes (BI543470, BI096135, AW697770, BI543640, BG932913, BI096146, BQ060651, BF011094, BI096078, and BF011254), and heterologous probes from maize (X15290), alfalfa (BI543243), and carrot (BI073246). Samples

(gibberellic acid). In order to obtain sufficient number of axillary shoots (64),

Statistical analyses of data were performed by different statistical methods. ANOVA was applied, to photosynthetic pigments (MCMCglmm Methods, [51]), using Package R (http:// www.jstatsoft.org/v33/i02/). Logarithmic and Jonson's transformations (Minitab) were performed for parameters with large data variability, in order to normalize their distribution. Confidence intervals for fitted mean responses were calculated as quantiles of simulated distributions of the expected response values. Analyses were done with the R environment [52] and the contributed packages lme4 [53] and ggplot2 [54].
