Breeding Sunflower For Drought Tolerance 

With an 8% share of global oilseed production, sunflower is a significant oilseed crop. Although it is a crop that tolerates mild dryness, severe drought lowers yield of seeds and oil.

With an 8% share of global oilseed production, sunflower is a significant oilseed crop. Although it is a crop that tolerates mild dryness, severe drought lowers the yield of seeds and oil.

Due to the fact that sunflowers are a summer crop, their productivity varies frequently from one year to the next. But in recent years, temperatures have been increasing daily or erratically as a result of global warming.

Water availability has a considerable impact on oilseed crop, sunflower production; during flowering, when water is most scarce, yield losses are the greatest. Therefore, it is essential to control the detrimental consequences of drought stress at this moment.

Developing crop genotypes with greater drought tolerance is the most cost-efficient and effective strategy to combat drought. But the process of breeding for drought resistance is proceeding slowly because of bad breeding practises and weak selection criteria.

This means that for the sustainable improvement of sunflower oilseed crop yield and oil quality under drought stress, it is necessary to integrate various management options, including agronomic management, traditional breeding, and modern biotechnological advances.

According to Tollenaar and Wu (1999), stress can be defined as any factor that lowers yield, regardless of whether it is present or not. Similar to this, a plant may experience a drought if it is unable to meet its evapotranspirational needs.

As stated by Sinha (1996), it can also be described as “the inadequacy of water availability (including precipitation and soil moisture storage capacity) in quantity and distribution during the life cycle of a crop, thereby restricting the expression of its full genetic yield potential.”

According to Yurdanov et al. (2000), drought is a multifaceted stress that has an impact on plants at different organisational levels. Wide variations in precipitation, precipitation quantity, and distribution within and between seasons are characteristics of drought conditions (Swindale and Bidinger, 1981).

Stress typically has a negative impact on development and photosynthesis (Yordanov et al., 2000). According to Fischer and Turner (1978) and Boyer (1982), the biggest single factor reducing yield globally is dryness.

Effects of Drought stress

Sunflower is classified as a crop with low to medium sensitivity to drought. Sunflower oilseed crop yield and oil yield have been discovered to be significantly impacted by the quantity and distribution of water (Fereres et al., 1986; Andrich et al., 1996; Krizmanic et al., 2003).

However, drought treatment did not significantly impact the quality of sunflower oil (Petcu et al., 2001). According to Lorens et al. (1987), genotype tolerance, crop growth stage, and drought severity all influence how much output is reduced by drought stress.

Although drought stress affects sunflowers at every stage of growth, the greatest yield drop was noticed when the drought struck during the reproductive stage (Karaata, 1991).

The most significant drop in output occurred when drought was administered during flowering, according to experiments done by Karaata (1991) to determine the growth stages of sunflower oilseed crop that are especially sensitive to drought.

Similar to this, Vijay (2004) investigated how the yield of achenes responded to watering at four different times: initially, at 15-20 days after planting (DAS), during capitulum start (30–35 DAS), during flowering (50–60 DAS), and during grain development (70–80 DAS).

Achene output was observed to increase with irrigation during the flowering period. According to several studies (Terbea et al., 1995; Sgherri et al., 1996; Kang and Zhang, 1997), the cellular effects of drought stress include cell shrinkage, cell membrane damage, and the formation of free radicals that harm the cellular structure.                                                                                                             

Sunflower seed yield and oil yield reduction under drought stress

The + sign indicates an increase rather than decrease. The figures in parenthesis in oil yield column represent oil percentage. NA denotes that the respective trait was not assessed in the study.

Agronomical approach:

Drought can be controlled to lessen its negative consequences. Irrigating the field is the best strategy for managing drought stress from an agronomic perspective.

The use of mulches to reduce evaporation losses, improved weed control, crop rotation, enhanced cultivation methods to increase infiltration rate, foliar sprays, and effective irrigation practises (e.g., drip, sprinkler) are some additional drought management strategies (Rachidi et al., 1993; Gajri et al., 1997; Unger and Howell, 1999).

All of these management strategies share the fundamental tenet of reducing the negative effects of drought and making effective use of water.

All of these agronomic techniques have been demonstrated to increase production during drought stress by 15–25% by enhancing water supply (Edmeades & Bänziger, 1997). But such management practices cannot be exploited by the farmer with small holdings or who cannot afford these inputs.

Through Genetic modification

Additionally, drought can be controlled by altering plant shape or adding characteristics that make it easier for plants to withstand drought stress (Yordanov et al., 2000). In order to deal with drought, genetic alteration is typically the best and most affordable option.

Since breeding-induced changes to plant morphology and physiology are heritable, once introduced into a breeding material, drought tolerance will be inherited permanently. Breeding for enhanced drought tolerance can be roughly defined as heritable adjustments made within a crop with the intention of increasing drought tolerance.

Molecular Breeding for Drought Tolerance in Sunflower:

We now have a potent tool to supplement and complete the conventional ways of plant improvement thanks to the development of new, cutting-edge techniques in molecular biology and plant cell biology.

As a result, Saeed (Breeding sunflower for drought tolerance) 37 has focused much of its recent research on isolating and evaluating the expression of drought-tolerant genes. Following subtractive hybridization of cDNA synthesised from RNA recovered from drought-stressed and unstressed plants, novel stress-sensitive genes were discovered.

Identified genes related to drought tolerance such as SunTIP, HaDhn1, HaDhn2, Sdi (sunflower drought induced), Gdi15, Hahb-4, and HAS1 or HAS1.1 showed an abundance of their transcript levels under drought stress, and it was proposed that they play a role in the sunflower oilseed crop response to drought (Ouvrard et al., 1996; Cellier et al., 1998; Sarda et al., 1999; Gopalakrishna et al., 2001; Liu and Baired, 2003; Dezar et al., 2005; Herrera Rodriguez et al., 2007). When compared to genotypes that were drought-sensitive, they only displayed expression in drought tolerant types (Roche et al., 2007).

These genes are expressed in a variety of organs. Sdis and HaRPS28, on the other hand, were associated with the formation of specific ACC oxidase antioxidants or dehydrins and showed the highest expression in fully grown leaves, while HAS1 and HAS1.1 showed higher expression in roots when compared to leaves. It has been demonstrated that a few genes influence the expression of other genes to increase drought resistance.

According to Manavella et al. (2006), plants overexpressing Hahb-4 entered the senescence pathway later and were less vulnerable to exogenous ethylene. Genes involved in ethylene synthesis, including ACO and SAM, and genes involved in ethylene signalling, like ERF2 and ERF5, are significantly repressed by the expression of this transcriptional factor.

The stress of a drought causes abscisic acid to be produced. Along with having a differential impact on biomass partitioning, HaDhn2, Sdis (sdi1, sdi5, sdi9, sdi6, sdi8), Ha-RPS28, and Hahb-4 are among the genes that regulate drought tolerance (Ouvrard et al., 1996; Cellier, 1998). Giordani et al. (1999) did point out the existence of two regulating mechanisms for the accumulation of HaDhn1a transcripts, one ABA-dependent and the other ABA independent, which may have additive effects.

The highest amount of HaDhn1 transcript accumulated towards the middle of the day, and its expression was not constant throughout the day/night cycle (Cellier et al., 2000). Dehydrins (Dhn1), a gene associated with drought stress, and other genes have also been utilised to examine the genetic and evolutionary differences between cultivated and wild sunflower for this gene.

The expressed protein revealed that the perennial and annual Helianthus species differed in their biochemical characteristics.

However, compared to wild sunflower, the cultivated sunflower oilseed crop has less genetic variation for the dehydrin genes (Giordani et al., 2003; Natali et al., 2003). The stress-responsive gene (Dhn1) can also be utilised to analyse the phylogeny of Helianthus; it was also determined.

Molecular Markers Concept

Our ability to directly access any region of the plant genome has been revolutionised by the idea of DNA-based markers. This has created new opportunities, such as the ability to screen a large population of segregating individuals for QTLs associated with drought tolerance without actually subjecting them to drought and independent of plant growth stage.

Quantitative trait loci (QTL) account for the vast majority of physiological features in nature. According to Tanksley (1993), quantitative traits exhibit continuous phenotypic distributions influenced by numerous loci and exhibit considerable interaction with the environment.

The development of a molecular marker for QTLs associated with drought tolerance in sunflower, however, has received very little attention (Jamaux et al., 1997; Hervé et al., 2001; Kiani et al., 2007b). To identify QTL associated with net photosynthesis, stomatal motions, and water status (transpiration and leaf water potential), Hervé et al. (2001) used the AFLP linkage map.

An AFLP linkage map was used to identify 19 QTL, which account for 8.8–62.9% of the phenotypic variance for each characteristic. On linkage group IX, two significant QTL for net photosynthesis were found. On linkage group VIII, a single QTL co-location for stomatal motions and hydration status was discovered. On linkage group XIV, coincident sites for QTL controlling photosynthesis, transpiration, and leaf water potential were identified.

On the other hand, in well-watered conditions, Kiani et al. (2007b) discovered 24 QTLs, of which 5 (or around 21%) were also discovered in the water-stressed treatment. Between 6% and 29% of the phenotypic variance was explained by the QTLs.

Among the eight QTLs detected for 38 Communications in Biometry and Crop Science, 3(1) OA, four of them (50%) were co-located with the QTLs for turgor potential (Psi(t)) on linkage group IV (OA.4.1), with the QTL for osmotic potential at full turgor (Psi(sFT)) in well-watered RILs on linkage group VII (OA. 12.2), and with QTLs of several traits on linkage group V (OA.5.1 and OA.5.2).

The four additional OA QTLs (50%) were extremely specialised. They came to the conclusion that since these QTLs were discovered under greenhouse conditions, their utility for marker-assisted selection should be assessed in the field and validated in populations with different genetic backgrounds. Similar to this, Jamaux et al. (1997) used RAPD bulk analysis to identify RFLP and STS molecular markers of relative water loss and osmotic adjustment.