Drought is the primary limiting factor for rice production in rainfed ecosystems and drought at the reproductive stage particularly causes a severe reduction in grain yield (Cruz & O'Toole, 1984). Due to the inherently high variable nature of rainfed environments, breeding for drought-prone rainfed ecosystems requires strong research commitments for a longer period to see changes in farmers' fields. There are not many examples of concerted and product-oriented long-term breeding efforts that led to a significant yield increase at the farmers' level in rainfed water-short drought-prone environments. Even now, most of the varieties grown in rainfed environments are either high-yielding but drought-susceptible varieties or traditional local varieties/landraces that are drought tolerant but low yielding and poor in grain quality. The varietal characteristics that need to be considered during the development of genotypes for rainfed environments are farmers' preferred grain quality traits, high yielding ability with good drought tolerance, and resistance to/tolerance of prevalent biotic stresses (Atlin, 2003; Kumar et al., 2008).

#### **3.1 Precise phenotyping under drought stress**

Standardized phenotyping under well-managed water stress conditions is a prerequisite for the success of a drought breeding program. Drought screening (DS), which clearly distinguishes high-yielding but drought-susceptible lines from drought-tolerant lines, is necessary for effective selection for higher grain yield under drought. A breeding program has to develop a suitable screening methodology depending upon the crop growth stage (seedling/vegetative/reproductive) at which drought occurrence is more frequent and severe in the region. Most breeding programs carry out large-scale screening of breeding/mapping populations in natural field conditions and make an adjustment in date of sowing and planting to synchronize the crop growth stage with the period most likely to have the least rainfall. In recent years, some advanced programs have developed a rainout shelter facility for uninterrupted drought screening. In some cases, a line-source sprinkler irrigation system that allows the development of different severity of stress, along the line away from the source, is also followed (Cruz & O'Toole, 1984; Fukai et al., 1996; Lanceras et al., 2004). The crop growth stage when drought should be imposed in the field depends upon the water-holding capacity of the soil. In general, in upland, drought appears in severe form in 7-10 days after stopping irrigation whereas in lowland it takes 18-21 days for severe drought occurrence. The severity of drought to be applied in a drought screen should be very close to the drought situation prevalent in the region. In a region with moderate drought stress every year, screening under severe drought stress that leads to a significant yield reduction will not be appropriate.

In lowland, in screening experiments, a yield reduction of 30% for regions with mild drought occurrence, a yield reduction of 31-65% for regions with moderate drought occurrence, and a yield reduction of 65-85% for regions with severe drought occurrence have been reported to be appropriate (Kumar et al., 2007). In upland, due to prevalent conditions, drought mostly occurs in severe form and screening under severe drought conditions is recommended. However, for places with favorable rainfall, screening under conditions that bring a yield reduction of 40% or less for regions with mild drought occurrence, a yield reduction of 41-75% for regions with moderate drought occurrence, and a yield reduction of 76-90% for regions with severe drought occurrence will be appropriate.

Sustainable Rice Yield in Water-Short Drought-Prone

listed in Table 2.

**S. no. Designation**

Environments: Conventional and Molecular Approaches 153

have been developed. At IRRI, traditional donors are used in developing mapping populations for the identification of major QTLs for grain yield under drought and better segregants combining appropriate plant type, high yield, and drought tolerance identified from such mapping populations are used in breeding programs. These improved prebreeding lines are crossed with high-yielding drought-susceptible popular varieties and appropriate segregants are selected. With popular high-yielding varieties, such poorcombining donors can also be used in a backcross breeding program and appropriate segregants can be selected from BC1F2 or BC2F2 generation onwards. Some of the traditional and improved donors that showed consistent performance in drought screening at IRRI are

> **Plant height (cm), non-stress**

Table 2. Traditional and improved donors for drought tolerance

While developing a breeding or mapping population, one of the parents should be a drought-resistant donor and the other parent should be a well-adapted local cultivar. The

**3.3 Development of populations**

1 IR86931-B-414 95 76 2827 2 IR77298-14-1-2 102 82 2725 3 Aus Bak Tulsi 128 76 2472 4 IR86918-B-382 95 77 2405 5 Aus 299 125 76 2353 6 IR77298-5-6-18 96 85 1171 7 IR77298-14-1-2-10 85 85 1183 8 Kali Aus 103 76 2126 9 IR55419-04 117 69 2128 10 IR80461-B-7-1 120 80 1574 11 IR74371-70-1-1 95 77 1971 13 IR74371-54-4-1 104 78 2131 14 IR81896-B-B-74 120 84 1984 15 IR80461-B-7-1 106 78 1684 16 IR84878-B-60-4-1 78 85 2418 17 IR83380-B-B124-1 76 87 1482 18 IR83373-B-B-24-4 84 82 2271 19 IR71525-19-1-1 127 85 1036 20 Apo 110 84 1125 21 N22 120 75 2992 22 Dhagad Desi 93 84 1482 23 Dular 136 76 1539 24 Swarna (check) 85 115 178 25 IR64 (check) 81 115 342 26 MTU1010 (check) 97 85 542

**Days to 50% flowering, non-stress**

**Grain yield (kg ha-1), drought**

In drought screens, adequate precautions need to be taken to irrigate the experiments at an appropriate time before drought is too severe to cause a loss of all genetic variability and affect an efficient selection strategy.

Severe drought screening at the reproductive stage is targeted in drought screens at IRRI. In upland screens, to initiate stress, experiments are drained at 35-45 days after seeding depending upon the duration of varieties. Stress plots are irrigated only when the soil water tension fall below -50 kPa at 30-cm soil depth. At this soil water potential, most lines wilt and exhibit leaf drying. This type of cyclic stress is considered to be efficient in screening for drought tolerance in populations consisting of genotypes with a broad range of growth duration (Lafitte, 2003 ) and ensures that all lines receive adequate stress during reproductive development. In lowland, to initiate stress, the field is drained 25-30 days after transplanting and experiments are irrigated only when the soil water tension falls below -60 kPa at 30-cm depth or alternatively when drought-susceptible checks along with around 70% of the lines show severe leaf rolling at 10 a.m. At IRRI, every season, several mapping and breeding populations are screened under severe reproductive-stage drought stress and the desired yield reductions as compared to yield in yield in irrigated control situation are achieved (Table 1).

Table 1. Yield reduction in different populations under managed drought stress

#### **3.2 Use of traditional and improved donors**

The selection of parents is an important critical step in breeding for drought tolerance. A large variation exists for drought tolerance in the available rice germplasm (Mackill et al., 1996). Traditionally grown landraces and wild species accessions have high adaptability to drought, and the hidden genetic potential available in these accessions provides a better opportunity to improve the drought tolerance of popular rice varieties. However, most of the drought-tolerant donors used in the breeding programs so far are either from the cultivated rice gene pool or traditional landraces. Even though wild species can offer better genes for drought tolerance, no population with wild species has been developed for drought studies. Wild species such as *Oryza rufipogon*, *O. australiensis*, *O. glaberrima*, and several accessions of rice germplasm consisting of traditional varieties, landraces, and breeding lines were screened at IRRI under drought over the seasons/years to identify new donors. Efforts are also being made to develop wild species-derived populations for selection and qunatitaive trait loci (QTL) mapping. Several important drought-tolerant donors such as Apo, Aday Sel, N22, Dular, and Dhagad Desi were identified (Table 2) and used effectively in developing populations to select high-yielding lines under drought following a pedigree breeding approach.

Traditional donors have largely been low yielding and they carry undesirable linkage drag. Improved donors through pre-breeding between traditional donors and improved cultivars

In drought screens, adequate precautions need to be taken to irrigate the experiments at an appropriate time before drought is too severe to cause a loss of all genetic variability and

Severe drought screening at the reproductive stage is targeted in drought screens at IRRI. In upland screens, to initiate stress, experiments are drained at 35-45 days after seeding depending upon the duration of varieties. Stress plots are irrigated only when the soil water tension fall below -50 kPa at 30-cm soil depth. At this soil water potential, most lines wilt and exhibit leaf drying. This type of cyclic stress is considered to be efficient in screening for drought tolerance in populations consisting of genotypes with a broad range of growth duration (Lafitte, 2003 ) and ensures that all lines receive adequate stress during reproductive development. In lowland, to initiate stress, the field is drained 25-30 days after transplanting and experiments are irrigated only when the soil water tension falls below -60 kPa at 30-cm depth or alternatively when drought-susceptible checks along with around 70% of the lines show severe leaf rolling at 10 a.m. At IRRI, every season, several mapping and breeding populations are screened under severe reproductive-stage drought stress and the desired yield reductions as compared to yield in yield in irrigated control situation are achieved (Table 1).

**S. no. Population Sesaon/year % yield reduction**  1 N22/Swarna 2010DS 78 2 N22/IR64 2010DS 82 3 IR77298-5-6-18/IR64 2009DS 80 4 IR77298-14-1-2-10/IR64 2010DS 63 5 Dhagad desi/Swarna 2010DS 65 6 Dhagad desi/IR64 2010DS 66

The selection of parents is an important critical step in breeding for drought tolerance. A large variation exists for drought tolerance in the available rice germplasm (Mackill et al., 1996). Traditionally grown landraces and wild species accessions have high adaptability to drought, and the hidden genetic potential available in these accessions provides a better opportunity to improve the drought tolerance of popular rice varieties. However, most of the drought-tolerant donors used in the breeding programs so far are either from the cultivated rice gene pool or traditional landraces. Even though wild species can offer better genes for drought tolerance, no population with wild species has been developed for drought studies. Wild species such as *Oryza rufipogon*, *O. australiensis*, *O. glaberrima*, and several accessions of rice germplasm consisting of traditional varieties, landraces, and breeding lines were screened at IRRI under drought over the seasons/years to identify new donors. Efforts are also being made to develop wild species-derived populations for selection and qunatitaive trait loci (QTL) mapping. Several important drought-tolerant donors such as Apo, Aday Sel, N22, Dular, and Dhagad Desi were identified (Table 2) and used effectively in developing populations to select high-yielding lines under drought

Traditional donors have largely been low yielding and they carry undesirable linkage drag. Improved donors through pre-breeding between traditional donors and improved cultivars

Table 1. Yield reduction in different populations under managed drought stress

**3.2 Use of traditional and improved donors**

following a pedigree breeding approach.

affect an efficient selection strategy.

have been developed. At IRRI, traditional donors are used in developing mapping populations for the identification of major QTLs for grain yield under drought and better segregants combining appropriate plant type, high yield, and drought tolerance identified from such mapping populations are used in breeding programs. These improved prebreeding lines are crossed with high-yielding drought-susceptible popular varieties and appropriate segregants are selected. With popular high-yielding varieties, such poorcombining donors can also be used in a backcross breeding program and appropriate segregants can be selected from BC1F2 or BC2F2 generation onwards. Some of the traditional and improved donors that showed consistent performance in drought screening at IRRI are listed in Table 2.

Table 2. Traditional and improved donors for drought tolerance

#### **3.3 Development of populations**

While developing a breeding or mapping population, one of the parents should be a drought-resistant donor and the other parent should be a well-adapted local cultivar. The

Sustainable Rice Yield in Water-Short Drought-Prone

followed is provided in Appendix 1.

of Rice (INGER) in different countries.

**5. Molecular breeding approaches**

effect QTLs for grain yield under drought in rice mega-varieties.

**5.1 Mapping of major-effect QTLs for grain yield under drought**

system.

Environments: Conventional and Molecular Approaches 155

(caused by *Pyricularia oryzae*) and brown spot (*Helminthosporium oryzae)* (Shrivastava & Verulkar, 2009). One of the parents used in developing segregating generations should possess tolerance of blast and brown spot and selection for blast and brown spot is practiced in segregating and advanced generations. A description of the detailed selection protocol

Rainfed upland and lowland drought-prone environments are highly variable. Large genotype × environment interactions lead to differential performance of breeding lines in different environments. This requires that advanced breeding lines be tested at several locations and for several seasons to identify lines suitable to different regions. Further, breeding lines need to be tested for several seasons to generate reliable data on their performance under different severity of drought and normal irrigated situations. From such multilocation-multiseason evaluation, identified lines providing high yield under normal irrigated situations, good yield under drought, acceptable grain quality traits, and resistance to insects and diseases should be tested in on-farm participatory varietal selection (PVS) experiments to identify breeding lines preferred by farmers. Farmers' preferred breeding lines should be promoted for release as varieties through the national

Drought-tolerant breeding lines developed at IRRI are tested in multilocation trials under a drought breeding network that runs across India, Bangladesh, and Nepal in South Asia; Laos and Cambodia in Southeast Asia; and Tanzania and Mozambique in East Africa. Highyielding, drought-tolerant, farmers' preferred lines are promoted to national systems for release as varieties. The developed breeding lines are shared with other national systems in other countries and are also tested under the International Network for Genetic Evaluation

Crop genetic improvement for environmental stresses such as drought is challenging due to its complex genetic nature and poor understanding of the physiological and molecular mechanisms associated with drought (Blum, 1988; Sinclair, 2011). It is a challenging task for any breeder to manipulate grain yield under drought with precision by traditional breeding approaches. The availability of complete rice genomic sequence information, rice linkage maps, and molecular marker technology has made it possible to dissect complex traits into individual quantitative trait loci (QTLs) (Temnykh et al., 2001; McCouch et al., 2002; Tuberosa, 2004; Tuberosa & Salvi, 2004, 2006). Linkage mapping, association mapping, nested association mapping, marker-aided recurrent selection (MARS), and genome-wide selection (GWS) are different approaches presently followed for the mapping and introgression of QTLs for drought tolerance (Tsonev et al., 2009). Major-effect QTLs can be exploited in maker-assisted selection more precisely to breed for drought tolerance. The drought molecular breeding program at IRRI aims at identifying and introgressing major-

Molecular breeding approaches are a fast-track approach to improve grain yield under drought of popular high-yielding varieties. The complex nature of drought, multigenic

selected parents should have good combining ability and complement each other to overcome their specific drawbacks in terms of pest and disease resistance or grain quality. Different breeding populations such as recombinant inbred lines (RILs), backcross inbred lines (BILs), doubled haploids (DH), chromosomal segment substitution lines (CSSLs), and multiparent advanced generation inter-cross (MAGIC)-derived lines are used for breeding drought tolerance in rice. It is always desirable to have a large breeding population as it provides a better chance for breaking linkage drag and to obtain segregants with the right combinations of traits to meet local conditions and farmers' preferences. The population size runs up to 2500 to 5000 F2 plants in breeding populations and 400 to 500 plants in mapping populations. Backcross-derived populations are more preferred for both breeding and mapping, as they help in the recovery of all the good traits of recipient parents and up to a certain extent break undesirable linkages. MAGIC populations are also being used in drought breeding but the development of populations is laborious. However, this offers the advantages of testing multiple drought-tolerant alleles in a single population and broadened genetic base of the recipient parent. Populations developed by marker-aided recurrent selection (MARS) and genome-wide selection are also being used in drought breeding.

#### **3.4 Grain yield as a selection parameter under drought**

In the past, secondary yield component traits and physiological traits such as harvest index, spikelet fertility, root length, root dry weight, root volume, osmotic adjustment, stomatal conductance, and relative water content were used as selection criteria for improving grain yield under drought in rice (Jongdee et al., 2002; Pantuwan et al., 2002). Through selection for secondary traits, desired improvement in grain yield under drought could not be achieved. Several experiments conducted at IRRI and elsewhere have clearly demonstrated that grain yield has moderate to high broad-sense heritability under drought. Further, the heritability of grain yield was comparable with the heritability of secondary yield traits or physiological traits under drought stress (Kumar et al., 2007). An increase in heritability of grain yield with an increase in severity of stress has also been reported (Kumar et al., 2007). Recently, grain yield has been suggested as a selection parameter in drought breeding programs under both upland and lowland situations (Bernier et al., 2008; Kumar et al., 2007; Kumar et al., 2008). By using this approach, improved breeding lines are developed at IRRI and in partner countries such as the Philippines, India, Nepal, and Bangladesh (Verulkar et al., 2010; Mandal et al., 2010). In Brazil and Thailand also, direct selection for yield has been successfully applied in breeding for drought tolerance in upland and rainfed lowland conditions (Ouk et al., 2006).

#### **4. Combining high yield potential with good yield under drought**

Farmers in the water-short rainfed drought-prone environment need rice varieties that provide high yield in seasons with good rainfall and good yield in seasons with moderate to severe drought. Moreover, these varieties need to have resistance against prevalent insects and diseases and farmers' preferred quality traits. This requires that segregating populations be exposed to selection under normal irrigated situations, drought screens, diseases, insects, and grain quality traits. Drought conditions favor rice infestation by blast

selected parents should have good combining ability and complement each other to overcome their specific drawbacks in terms of pest and disease resistance or grain quality. Different breeding populations such as recombinant inbred lines (RILs), backcross inbred lines (BILs), doubled haploids (DH), chromosomal segment substitution lines (CSSLs), and multiparent advanced generation inter-cross (MAGIC)-derived lines are used for breeding drought tolerance in rice. It is always desirable to have a large breeding population as it provides a better chance for breaking linkage drag and to obtain segregants with the right combinations of traits to meet local conditions and farmers' preferences. The population size runs up to 2500 to 5000 F2 plants in breeding populations and 400 to 500 plants in mapping populations. Backcross-derived populations are more preferred for both breeding and mapping, as they help in the recovery of all the good traits of recipient parents and up to a certain extent break undesirable linkages. MAGIC populations are also being used in drought breeding but the development of populations is laborious. However, this offers the advantages of testing multiple drought-tolerant alleles in a single population and broadened genetic base of the recipient parent. Populations developed by marker-aided recurrent selection (MARS) and genome-wide

In the past, secondary yield component traits and physiological traits such as harvest index, spikelet fertility, root length, root dry weight, root volume, osmotic adjustment, stomatal conductance, and relative water content were used as selection criteria for improving grain yield under drought in rice (Jongdee et al., 2002; Pantuwan et al., 2002). Through selection for secondary traits, desired improvement in grain yield under drought could not be achieved. Several experiments conducted at IRRI and elsewhere have clearly demonstrated that grain yield has moderate to high broad-sense heritability under drought. Further, the heritability of grain yield was comparable with the heritability of secondary yield traits or physiological traits under drought stress (Kumar et al., 2007). An increase in heritability of grain yield with an increase in severity of stress has also been reported (Kumar et al., 2007). Recently, grain yield has been suggested as a selection parameter in drought breeding programs under both upland and lowland situations (Bernier et al., 2008; Kumar et al., 2007; Kumar et al., 2008). By using this approach, improved breeding lines are developed at IRRI and in partner countries such as the Philippines, India, Nepal, and Bangladesh (Verulkar et al., 2010; Mandal et al., 2010). In Brazil and Thailand also, direct selection for yield has been successfully applied in breeding for drought tolerance in upland and rainfed lowland

**4. Combining high yield potential with good yield under drought**

Farmers in the water-short rainfed drought-prone environment need rice varieties that provide high yield in seasons with good rainfall and good yield in seasons with moderate to severe drought. Moreover, these varieties need to have resistance against prevalent insects and diseases and farmers' preferred quality traits. This requires that segregating populations be exposed to selection under normal irrigated situations, drought screens, diseases, insects, and grain quality traits. Drought conditions favor rice infestation by blast

selection are also being used in drought breeding.

conditions (Ouk et al., 2006).

**3.4 Grain yield as a selection parameter under drought**

(caused by *Pyricularia oryzae*) and brown spot (*Helminthosporium oryzae)* (Shrivastava & Verulkar, 2009). One of the parents used in developing segregating generations should possess tolerance of blast and brown spot and selection for blast and brown spot is practiced in segregating and advanced generations. A description of the detailed selection protocol followed is provided in Appendix 1.

Rainfed upland and lowland drought-prone environments are highly variable. Large genotype × environment interactions lead to differential performance of breeding lines in different environments. This requires that advanced breeding lines be tested at several locations and for several seasons to identify lines suitable to different regions. Further, breeding lines need to be tested for several seasons to generate reliable data on their performance under different severity of drought and normal irrigated situations. From such multilocation-multiseason evaluation, identified lines providing high yield under normal irrigated situations, good yield under drought, acceptable grain quality traits, and resistance to insects and diseases should be tested in on-farm participatory varietal selection (PVS) experiments to identify breeding lines preferred by farmers. Farmers' preferred breeding lines should be promoted for release as varieties through the national system.

Drought-tolerant breeding lines developed at IRRI are tested in multilocation trials under a drought breeding network that runs across India, Bangladesh, and Nepal in South Asia; Laos and Cambodia in Southeast Asia; and Tanzania and Mozambique in East Africa. Highyielding, drought-tolerant, farmers' preferred lines are promoted to national systems for release as varieties. The developed breeding lines are shared with other national systems in other countries and are also tested under the International Network for Genetic Evaluation of Rice (INGER) in different countries.

#### **5. Molecular breeding approaches**

Crop genetic improvement for environmental stresses such as drought is challenging due to its complex genetic nature and poor understanding of the physiological and molecular mechanisms associated with drought (Blum, 1988; Sinclair, 2011). It is a challenging task for any breeder to manipulate grain yield under drought with precision by traditional breeding approaches. The availability of complete rice genomic sequence information, rice linkage maps, and molecular marker technology has made it possible to dissect complex traits into individual quantitative trait loci (QTLs) (Temnykh et al., 2001; McCouch et al., 2002; Tuberosa, 2004; Tuberosa & Salvi, 2004, 2006). Linkage mapping, association mapping, nested association mapping, marker-aided recurrent selection (MARS), and genome-wide selection (GWS) are different approaches presently followed for the mapping and introgression of QTLs for drought tolerance (Tsonev et al., 2009). Major-effect QTLs can be exploited in maker-assisted selection more precisely to breed for drought tolerance. The drought molecular breeding program at IRRI aims at identifying and introgressing majoreffect QTLs for grain yield under drought in rice mega-varieties.

#### **5.1 Mapping of major-effect QTLs for grain yield under drought**

Molecular breeding approaches are a fast-track approach to improve grain yield under drought of popular high-yielding varieties. The complex nature of drought, multigenic

Sustainable Rice Yield in Water-Short Drought-Prone

**5.2 Selective genotyping and bulk segregant analysis**

**5.3 Fine mapping of major-effect grain-yield QTLs**

al., 2007).

et al., 2010).

Environments: Conventional and Molecular Approaches 157

improve the yield of the recipient parent (Xing et al., 2002; Lanceras et al., 2004; Zou et al., 2005; Dixit et al., 2011). Many more such QTLs are likely to exist and need to be extracted from novel drought-tolerant donors. Wild progenitor species are an appropriate source for exploiting naturally occurring variation to harness QTL alleles for drought tolerance in rice. The AB-QTL analysis approach has been successful in exploiting favorable alleles for various traits of agronomic importance (Xiao et al., 1998; Zhang et al., 2006; Mc Couch et

The genotyping of large populations to identify QTLs involves high costs, and is laborious. To reduce the cost and time associated with whole genotyping, alternative approaches such as selective genotyping and bulk segregant analysis (BSA) were proposed (Darvasi & Soller, 1992; Bernier et al., 2007; Venuprasad et al., 2009; Vikram et al., 2009). In selective genotyping, only tail lines selected based on phenotype are genotyped and used for QTL detection. Major-effect QTL *qDTY12.1*, which was initially identified in a population of 436 lines, was detected by selective genotyping of only 169 lines (Navabi et al., 2009). Vikram et al. (2009) detected two major-effect QTLs, *qDTY1.1* and *qDTY8.1*, explaining up to 11.9% and 15.6% of the phenotypic variance by genotyping only 36.5% of the lines from the populations. BSA is a cost-effective and efficient genotyping method to detect major-effect QTLs (Michelmore et al., 1991). It has been used successfully in identifying QTLs for grain yield under drought in rice by Shashidhar et al. (2005). Venuprasad et al. (2009) used BSA to identify two large-effect QTLs, *qDTY2.1* and *qDTY3.1*. Vikram et al. (2009) detected two major-effect QTLs, *qDTY1.1* and *qDTY8.1*. Ghimire et al. (2011) detected a major-effect QTL, *qDTY1.1*, for grain yield under drought in more than one population. These cost-saving genotyping methods are more efficient and accurate in identifying major QTLs for grain yield under drought. With the availability of genome-wide polymorphic SNP markers, Single nucleotide polymorphism (SNP) genotypic arrays, and cheaper SNP assays, marker-assisted breeding can become a common breeding practice (McNally et al., 2009; Fukuoka

Fine mapping is necessary to further narrow down the confidence interval of major-effect QTLs for precise linkage-drag-free introgression of the QTLs in marker-assisted selection. Fine mapping is carried out either in the same QTL mapping population or in a large advanced backcross population segregating only for the QTL region and genotyping the population with additional markers in the QTL region. There are several reports of fine mapping of QTLs for different traits under drought. A QTL for leaf rolling and leaf drying on chromosome 1 was fine-mapped to 3.8 cM region (Salunkhe et al., 2011). Ding et al. (2011) fine-mapped a major-effect QTL (*qFSR4*) for root volume per tiller to a 38-kb region using NILs. Nguyen et al. (2004) fine-mapped a QTL (*oa3.1*) for osmotic adjustment under drought and identified the candidate genes. A major-effect QTL for drought recovery score (DRS) was fine-mapped on chromosome 9 (Lang & Buu, 2008). Efforts were also made at IRRI to fine-map four large-effect grain-yield QTLs under drought such as *qDTY2.1*, *qDTY2.2*, *qDTY9.1*, and *qDTY12.1* in backcross-derived advanced populations (Bernier et al., 2007;

inheritance of grain yield, and the complexity to maintain quality and other desirable traits of well-established varieties necessitate the use of markers to track QTLs/genes controlling these traits. Molecular approaches were suggested to be appropriate for effective droughttolerance improvement in rice (Price et al., 2002b, 200b; Tuberosa 2004; Tuberosa & Salvi, 2004, 2006). Earlier, several efforts made to improve grain yield under drought in rice through the introgression of the identified QTLs for yield-related secondary traits did not yield the desired results. The identification and introgression of major-effect QTLs for grain yield under reproductive-stage drought stress in drought-susceptible rice varieties could be a suitable marker-assisted breeding (MAB) strategy. For marker-assisted introgression to be successful, the identification of QTLs with a high and stable effect in an improved genetic background is one of the essential requirements. Understanding all the sources of genetic variations such as QTL main effects, QTL × QTL, and QTL × environment interactions is very important before embarking on marker-assisted selection (MAS) of drought QTLs (Xing et al., 2002). To date, several QTLs with large and consistent effects on grain yield under drought stress have been identified at IRRI. Bernier et al. (2007) reported *qDTY12.1,* a QTL on chromosome 12 in the Vandana/Way Rarem population, explaining about 51% of the genetic variance for yield under severe upland drought stress over two years. A consistent major-effect QTL for grain yield, *qDTY1.1*, was identified to show an effect in several populations. Vikram et al. (2009) detected *qDTY1.1* in three RIL populations derived from the donor N22 crossed to drought-susceptible varieties Swarna, IR64, and MTU1010 consistently over two years Ghimire et al. (2011) also detected *qDTY1.1* in two RIL populations derived from donor Dhagad deshi crossed to Swarna and IR64 consistently over two seasons. Two major-effect QTLs, *qDTY3.1* and *qDTY2.1*, were identified in an Apo/2\*Swarna population explaining 30% and 15% of the phenotypic variance, respectively (Venuprasad et al., 2009). Four major-effect QTLs, *qDTY2.2*, q*DTY4.1*, *qDTY9.1*, and q*DTY10.1*, were identified in Adaysel/IR64-derived populations (Swamy et al., 2011b, unpublished). It is important to mention that most of the major-effect QTLs were consistent across water regimes and are suitable for improving varieties for different severities of water stress (Zou et al., 2005; Kamoshita et al., 2008). The major-effect QTLs and their additive effect on grain yield are provided in Table 3. Epistatic QTLs were also detected for grain yield under drought; they can be simultaneously introgressed together with the major-effect QTLs to

Table 3. Major-effect QTLs for grain yield under drought identified at IRRI

inheritance of grain yield, and the complexity to maintain quality and other desirable traits of well-established varieties necessitate the use of markers to track QTLs/genes controlling these traits. Molecular approaches were suggested to be appropriate for effective droughttolerance improvement in rice (Price et al., 2002b, 200b; Tuberosa 2004; Tuberosa & Salvi, 2004, 2006). Earlier, several efforts made to improve grain yield under drought in rice through the introgression of the identified QTLs for yield-related secondary traits did not yield the desired results. The identification and introgression of major-effect QTLs for grain yield under reproductive-stage drought stress in drought-susceptible rice varieties could be a suitable marker-assisted breeding (MAB) strategy. For marker-assisted introgression to be successful, the identification of QTLs with a high and stable effect in an improved genetic background is one of the essential requirements. Understanding all the sources of genetic variations such as QTL main effects, QTL × QTL, and QTL × environment interactions is very important before embarking on marker-assisted selection (MAS) of drought QTLs (Xing et al., 2002). To date, several QTLs with large and consistent effects on grain yield under drought stress have been identified at IRRI. Bernier et al. (2007) reported *qDTY12.1,* a QTL on chromosome 12 in the Vandana/Way Rarem population, explaining about 51% of the genetic variance for yield under severe upland drought stress over two years. A consistent major-effect QTL for grain yield, *qDTY1.1*, was identified to show an effect in several populations. Vikram et al. (2009) detected *qDTY1.1* in three RIL populations derived from the donor N22 crossed to drought-susceptible varieties Swarna, IR64, and MTU1010 consistently over two years Ghimire et al. (2011) also detected *qDTY1.1* in two RIL populations derived from donor Dhagad deshi crossed to Swarna and IR64 consistently over two seasons. Two major-effect QTLs, *qDTY3.1* and *qDTY2.1*, were identified in an Apo/2\*Swarna population explaining 30% and 15% of the phenotypic variance, respectively (Venuprasad et al., 2009). Four major-effect QTLs, *qDTY2.2*, q*DTY4.1*, *qDTY9.1*, and q*DTY10.1*, were identified in Adaysel/IR64-derived populations (Swamy et al., 2011b, unpublished). It is important to mention that most of the major-effect QTLs were consistent across water regimes and are suitable for improving varieties for different severities of water stress (Zou et al., 2005; Kamoshita et al., 2008). The major-effect QTLs and their additive effect on grain yield are provided in Table 3. Epistatic QTLs were also detected for grain yield under drought; they can be simultaneously introgressed together with the major-effect QTLs to

background QTL Ecosystem Additive effect

Vandana *qDTY12.1* Upland 47 IR64 *qDTY1.1* Lowland 32 IR64 *qDTY9.1* Lowland 27 IR64 *qDTY10.1* Lowland 22 IR64 *qDTY2.2* Lowland 13 IR64 *qDTY4.1* Lowland 14 Swarna *qDTY1.1* Lowland 25 Swarna *qDTY2.1* Lowland 19 Swarna *qDTY3.1* Lowland 25 Swarna *qDTY8.1* Lowland 16 MTU1010 *qDTY1.1* Lowland 17

Table 3. Major-effect QTLs for grain yield under drought identified at IRRI

(% ) over trial mean

Genetic

improve the yield of the recipient parent (Xing et al., 2002; Lanceras et al., 2004; Zou et al., 2005; Dixit et al., 2011). Many more such QTLs are likely to exist and need to be extracted from novel drought-tolerant donors. Wild progenitor species are an appropriate source for exploiting naturally occurring variation to harness QTL alleles for drought tolerance in rice. The AB-QTL analysis approach has been successful in exploiting favorable alleles for various traits of agronomic importance (Xiao et al., 1998; Zhang et al., 2006; Mc Couch et al., 2007).

#### **5.2 Selective genotyping and bulk segregant analysis**

The genotyping of large populations to identify QTLs involves high costs, and is laborious. To reduce the cost and time associated with whole genotyping, alternative approaches such as selective genotyping and bulk segregant analysis (BSA) were proposed (Darvasi & Soller, 1992; Bernier et al., 2007; Venuprasad et al., 2009; Vikram et al., 2009). In selective genotyping, only tail lines selected based on phenotype are genotyped and used for QTL detection. Major-effect QTL *qDTY12.1*, which was initially identified in a population of 436 lines, was detected by selective genotyping of only 169 lines (Navabi et al., 2009). Vikram et al. (2009) detected two major-effect QTLs, *qDTY1.1* and *qDTY8.1*, explaining up to 11.9% and 15.6% of the phenotypic variance by genotyping only 36.5% of the lines from the populations. BSA is a cost-effective and efficient genotyping method to detect major-effect QTLs (Michelmore et al., 1991). It has been used successfully in identifying QTLs for grain yield under drought in rice by Shashidhar et al. (2005). Venuprasad et al. (2009) used BSA to identify two large-effect QTLs, *qDTY2.1* and *qDTY3.1*. Vikram et al. (2009) detected two major-effect QTLs, *qDTY1.1* and *qDTY8.1*. Ghimire et al. (2011) detected a major-effect QTL, *qDTY1.1*, for grain yield under drought in more than one population. These cost-saving genotyping methods are more efficient and accurate in identifying major QTLs for grain yield under drought. With the availability of genome-wide polymorphic SNP markers, Single nucleotide polymorphism (SNP) genotypic arrays, and cheaper SNP assays, marker-assisted breeding can become a common breeding practice (McNally et al., 2009; Fukuoka et al., 2010).

#### **5.3 Fine mapping of major-effect grain-yield QTLs**

Fine mapping is necessary to further narrow down the confidence interval of major-effect QTLs for precise linkage-drag-free introgression of the QTLs in marker-assisted selection. Fine mapping is carried out either in the same QTL mapping population or in a large advanced backcross population segregating only for the QTL region and genotyping the population with additional markers in the QTL region. There are several reports of fine mapping of QTLs for different traits under drought. A QTL for leaf rolling and leaf drying on chromosome 1 was fine-mapped to 3.8 cM region (Salunkhe et al., 2011). Ding et al. (2011) fine-mapped a major-effect QTL (*qFSR4*) for root volume per tiller to a 38-kb region using NILs. Nguyen et al. (2004) fine-mapped a QTL (*oa3.1*) for osmotic adjustment under drought and identified the candidate genes. A major-effect QTL for drought recovery score (DRS) was fine-mapped on chromosome 9 (Lang & Buu, 2008). Efforts were also made at IRRI to fine-map four large-effect grain-yield QTLs under drought such as *qDTY2.1*, *qDTY2.2*, *qDTY9.1*, and *qDTY12.1* in backcross-derived advanced populations (Bernier et al., 2007;

Sustainable Rice Yield in Water-Short Drought-Prone

in an IR64 background.

is described in Appendix 2.

currently being used to apply MARS.

Environments: Conventional and Molecular Approaches 159

QTLs for grain yield under drought, the introgression of yield QTLs may produce desired results. The identified major-effect QTLs for grain yield under drought *qDTY12.1*, *qDTY3.1*, *qDTY2.2*, *qDTY9.1*, *qDTY10.1*, *qDTY4.1*, and *qDTY1.1* increased grain yield under stress conditions and did not have any adverse effect on grain yield under non-stress conditions. The introgression of these QTLs by marker-assisted backcross breeding provides an opportunity to improve the drought tolerance of well-adapted high-yielding but drought-susceptible popular rice mega-varieties of South and Southeast Asia, and Africa. The main objectives of MAS are to introgress and pyramid these QTLs and enhance yield by 1.0-1.2 t ha-1 under drought. *qDTY12.1* has been successfully introgressed in the background of Vandana. The Vandana-introgressed lines with *qDTY12.1* showed a yield advantage of 0.5 t ha-1 over drought-tolerant cultivar Vandana under drought and yielded similar to Vandana under normal irrigated situations. *qDTY2.2*, *qDTY4.1*, *qDTY9.1*, and *qDTY10.1* have been introgressed

The major-effect QTLs *qDTY1.1*, *qDTY2.1*, *QDTY2.2*, *qDTY3.1*, *qDTY4.1*, *qDTY9.1*, *qDTY10.1,* and *qDTY12.1* are being introgressed in several popular rice mega-varieties. In general, the major-effect QTLs identified for grain yield under drought have a genetic gain of 10% to 30%, with a yield advantage of 150 to 500 kg ha-1 over recipient parents. However, considering significant economical benefit to farmers, the development of droughttolerant rice varieties with a yield advantage of at least 1.0 t ha-1 could be the desired target for rice breeders. Marker-aided QTL pyramiding of major-effect QTLs through backcross breeding can be considered as an option for achieving this target. We have successfully pyramided four QTLs (*qDTY2.2*, *qDTY4.1*, *qDTY9.1*, and *qDTY10.1*) and introgressed lines with four, three, and two QTLs in an IR64 background developed. Introgressed lines with three and two QTLs in an IR64 background showed a yield advantage of 1.2-2.0 t ha-1 under drought, yielded similar to IR64 under normal irrigated situations, and possessed quality traits similar to those of IR64. Efforts are also under way to combine drought and submergence tolerance in Swarna-Sub1 and IR64-Sub1 backgrounds. The improved drought-tolerant NILs of IR64 and Vandana are ready for field testing by farmers (Kumar, 2011). The protocol procedure for pyramiding three QTLs

**6. Marker-aided recurrent selection for grain yield under drought**

Marker-aided recurrent selection helps in the introgression of all the significant QTLs detected for a set of traits in a population to develop an improved cultivar. The MARS scheme involves several cycles of selection and crossing based on the genotype. The gains achieved by this approach are suggested to be more than with phenotype-based breeding and other marker-assisted breeding approaches (Charmet et al., 1999; Ribaut & Ragot, 2007). MARS is highly useful in breeding combinations of traits, including grain yield under drought, yield potential under non-stress conditions, disease-insect resistance/tolerance, and grain quality characteristics. This approach has been successfully used in maize (Johnson, 2004; Crosbie et al., 2006). We have initiated programs to apply MARS for improving drought tolerance in rice at IRRI. Two populations, IR55419-04/Sambha Mahsuri and CT9993-5-10-1-M/Sambha Mahsuri, are

Venuprasad et al., 2009, Dixit et al., 2011). Uga et al. (2011) fine-mapped a major-effect QTL (*Dro1*) on chromosome 9 to a 608.4-kb region.

#### **5.4 Validation of major-effect QTLs**

The effect of major-effect grain-yield QTLs indentified at IRRI is validated across different backgrounds and environments. All these QTLs showed a consistent effect across different environments. The first major-effect QTL identified at IRRI, *qDTY12.1*, was evaluated in 21 field trials in the Philippines and eastern India. The effect of this QTL was consistent across the environments (Bernier et al., 2009). It was also interesting to note that the effect of *qDTY12.1* increased with an increase in severity of stress (Bernier et al., 2009). The majoreffect QTLs *qDTY3.1*, *qDTY2.2*, *qDTY4.1*, *q DTY9.1*, and *qDTY10.1* were evaluated at IRRI during 2010DS and 2011DS and the effects were consistent. The markers linked to the major-effect QTLs were validated on a panel of drought-tolerant lines to confirm their presence in a larger set of lines. It is notable that major-effect QTL *qDTY12.1* was present in 85% of the lines. *qDTY3.2*, *qDTY2.1*, *qDTY3.1*, *qDTY1.1*, *qDTY8.1*, and *qDTY1.2* were present in more than 50% of the lines. The study also indicated the presence of at least one major-effect grain-yield QTL in every drought panel line.

#### **5.5 Meta analysis and comparative genomics of grain-yield QTLs**

The identification of the most accurate and precise major-effect QTLs across genetic backgrounds and environments through Meta analysis is a prerequisite for the successful use of QTLs in MAS across different genetic backgrounds. Khowaja et al. (2009) carried out Meta analysis of QTLs for various phenotypic traits identified under drought stress. Courtois et al. (2009) identified the meta-QTLs for root traits under drought. The number of QTLs was considerably reduced to a few consistent meta-QTLs and confidence intervals of QTL regions also decreased. MQTL regions with small genetic and physical intervals are important regions for MAS, fine mapping, candidate gene identification, and functional analysis. Meta analysis of 53 grain-yield QTLs identified from 15 reports resulted in 14 meta-QTLs (Swamy et al., 2011a). There were seven meta-QTLs of around 1.3 Mb and they corresponded to a reasonably small genetic distance of 6 cM and they are suitable for use in marker-assisted selection. These QTLs can be introgressed in popular rice mega-varieties to develop drought-tolerant and high-yielding lines. Meta-QTL regions were compared for synteny in other cereal crops. The major-effect MQTL1.4 was also found in maize on chromosome 3 near marker *msu2*, in wheat on chromosome 4B near marker *Rht-b1*, and in barley on chromosome 6H near marker *Bmac0316*, while major-effect MQTL3.2 was also found in maize on chromosome 1 near marker *Umc107a* (Swamy et al., 2011a).

#### **5.6 Marker-assisted backcross to improve drought tolerance**

Even though many QTLs have been identified for various drought-related traits in rice, there are few efforts to introgress them to develop improved breeding lines (Price et al., 2002b; Courtois et al., 2003). The lack of success may be due to the use of small-effect QTLs for secondary traits/physiological traits in introgression or the unavailability of tightly linked markers (Shen et al., 2001). Now, with the detection of several major-effect, consistent

Venuprasad et al., 2009, Dixit et al., 2011). Uga et al. (2011) fine-mapped a major-effect QTL

The effect of major-effect grain-yield QTLs indentified at IRRI is validated across different backgrounds and environments. All these QTLs showed a consistent effect across different environments. The first major-effect QTL identified at IRRI, *qDTY12.1*, was evaluated in 21 field trials in the Philippines and eastern India. The effect of this QTL was consistent across the environments (Bernier et al., 2009). It was also interesting to note that the effect of *qDTY12.1* increased with an increase in severity of stress (Bernier et al., 2009). The majoreffect QTLs *qDTY3.1*, *qDTY2.2*, *qDTY4.1*, *q DTY9.1*, and *qDTY10.1* were evaluated at IRRI during 2010DS and 2011DS and the effects were consistent. The markers linked to the major-effect QTLs were validated on a panel of drought-tolerant lines to confirm their presence in a larger set of lines. It is notable that major-effect QTL *qDTY12.1* was present in 85% of the lines. *qDTY3.2*, *qDTY2.1*, *qDTY3.1*, *qDTY1.1*, *qDTY8.1*, and *qDTY1.2* were present in more than 50% of the lines. The study also indicated the presence of at least one major-effect grain-yield QTL

The identification of the most accurate and precise major-effect QTLs across genetic backgrounds and environments through Meta analysis is a prerequisite for the successful use of QTLs in MAS across different genetic backgrounds. Khowaja et al. (2009) carried out Meta analysis of QTLs for various phenotypic traits identified under drought stress. Courtois et al. (2009) identified the meta-QTLs for root traits under drought. The number of QTLs was considerably reduced to a few consistent meta-QTLs and confidence intervals of QTL regions also decreased. MQTL regions with small genetic and physical intervals are important regions for MAS, fine mapping, candidate gene identification, and functional analysis. Meta analysis of 53 grain-yield QTLs identified from 15 reports resulted in 14 meta-QTLs (Swamy et al., 2011a). There were seven meta-QTLs of around 1.3 Mb and they corresponded to a reasonably small genetic distance of 6 cM and they are suitable for use in marker-assisted selection. These QTLs can be introgressed in popular rice mega-varieties to develop drought-tolerant and high-yielding lines. Meta-QTL regions were compared for synteny in other cereal crops. The major-effect MQTL1.4 was also found in maize on chromosome 3 near marker *msu2*, in wheat on chromosome 4B near marker *Rht-b1*, and in barley on chromosome 6H near marker *Bmac0316*, while major-effect MQTL3.2 was also found in maize on chromosome 1 near marker *Umc107a*

Even though many QTLs have been identified for various drought-related traits in rice, there are few efforts to introgress them to develop improved breeding lines (Price et al., 2002b; Courtois et al., 2003). The lack of success may be due to the use of small-effect QTLs for secondary traits/physiological traits in introgression or the unavailability of tightly linked markers (Shen et al., 2001). Now, with the detection of several major-effect, consistent

**5.5 Meta analysis and comparative genomics of grain-yield QTLs**

**5.6 Marker-assisted backcross to improve drought tolerance**

(*Dro1*) on chromosome 9 to a 608.4-kb region.

**5.4 Validation of major-effect QTLs**

in every drought panel line.

(Swamy et al., 2011a).

results. The identified major-effect QTLs for grain yield under drought *qDTY12.1*, *qDTY3.1*, *qDTY2.2*, *qDTY9.1*, *qDTY10.1*, *qDTY4.1*, and *qDTY1.1* increased grain yield under stress conditions and did not have any adverse effect on grain yield under non-stress conditions. The introgression of these QTLs by marker-assisted backcross breeding provides an opportunity to improve the drought tolerance of well-adapted high-yielding but drought-susceptible popular rice mega-varieties of South and Southeast Asia, and Africa. The main objectives of MAS are to introgress and pyramid these QTLs and enhance yield by 1.0-1.2 t ha-1 under drought. *qDTY12.1* has been successfully introgressed in the background of Vandana. The Vandana-introgressed lines with *qDTY12.1* showed a yield advantage of 0.5 t ha-1 over drought-tolerant cultivar Vandana under drought and yielded similar to Vandana under normal irrigated situations. *qDTY2.2*, *qDTY4.1*, *qDTY9.1*, and *qDTY10.1* have been introgressed in an IR64 background.

The major-effect QTLs *qDTY1.1*, *qDTY2.1*, *QDTY2.2*, *qDTY3.1*, *qDTY4.1*, *qDTY9.1*, *qDTY10.1,* and *qDTY12.1* are being introgressed in several popular rice mega-varieties. In general, the major-effect QTLs identified for grain yield under drought have a genetic gain of 10% to 30%, with a yield advantage of 150 to 500 kg ha-1 over recipient parents. However, considering significant economical benefit to farmers, the development of droughttolerant rice varieties with a yield advantage of at least 1.0 t ha-1 could be the desired target for rice breeders. Marker-aided QTL pyramiding of major-effect QTLs through backcross breeding can be considered as an option for achieving this target. We have successfully pyramided four QTLs (*qDTY2.2*, *qDTY4.1*, *qDTY9.1*, and *qDTY10.1*) and introgressed lines with four, three, and two QTLs in an IR64 background developed. Introgressed lines with three and two QTLs in an IR64 background showed a yield advantage of 1.2-2.0 t ha-1 under drought, yielded similar to IR64 under normal irrigated situations, and possessed quality traits similar to those of IR64. Efforts are also under way to combine drought and submergence tolerance in Swarna-Sub1 and IR64-Sub1 backgrounds. The improved drought-tolerant NILs of IR64 and Vandana are ready for field testing by farmers (Kumar, 2011). The protocol procedure for pyramiding three QTLs is described in Appendix 2.

#### **6. Marker-aided recurrent selection for grain yield under drought**

Marker-aided recurrent selection helps in the introgression of all the significant QTLs detected for a set of traits in a population to develop an improved cultivar. The MARS scheme involves several cycles of selection and crossing based on the genotype. The gains achieved by this approach are suggested to be more than with phenotype-based breeding and other marker-assisted breeding approaches (Charmet et al., 1999; Ribaut & Ragot, 2007). MARS is highly useful in breeding combinations of traits, including grain yield under drought, yield potential under non-stress conditions, disease-insect resistance/tolerance, and grain quality characteristics. This approach has been successfully used in maize (Johnson, 2004; Crosbie et al., 2006). We have initiated programs to apply MARS for improving drought tolerance in rice at IRRI. Two populations, IR55419-04/Sambha Mahsuri and CT9993-5-10-1-M/Sambha Mahsuri, are currently being used to apply MARS.

Sustainable Rice Yield in Water-Short Drought-Prone

Environments: Conventional and Molecular Approaches 161

Appendix 1. Conventional breeding approach for developing drought-tolerant rice varieties

#### **7. Development of QTL-NILs for physiological and molecular studies**

Understanding the physiological and molecular mechanisms associated with drought tolerance of major-effect QTLs is one of the major components of drought breeding. For this purpose, near-isogenic lines for QTLs (QTL-NILs) are being developed through markerassisted introgression and background recovery of the recipient genome. The NILs differing only at QTLs and similar in the background genotype are used to understand the physiological and molecular mechanisms of increased yield under drought provided by QTLs.

#### **8. Success stories of drought breeding at IRRI**

The drought breeding program at IRRI standardized phenotyping under managed drought stress in field conditions. Direct selection for grain yield under drought has been applied as a criterion for developing improved cultivars through conventional as well as molecular approaches. Grain yield under drought has also been used in mapping and introgressing QTLs. Several major-effect, consistent QTLs have been identified in the background of popular rice mega-varieties. Following conventional breeding approaches, many varieties have been developed and released for cultivation in partner countries. During 2009 and 2010, three breeding lines, IR74371-70-1-1 as Sahbhagi dhan in India, IR74371-54-1-1 as Sahod ulan in the Philippines, and IR80411-B-49-1 as Tarharra 1 in Nepal, were released as drought-tolerant varieties. In 2011, three varieties, IR74371-3-1-1, IR74371-46-1-1, and IR74371-70-1-1, were released in Nepal as Sookha dhan 1, Sookha dhan 2, and Sookha dhan 3, respectively. IR74371-70-1-1 has been release as BRRI dhan56 in Bangladesh. IR77080-B-34-3 and IR81047-B-3-4 are breeding lines identified as promising in Mozambique. Through molecular approaches, major-effect QTLs have been introgressed and pyramided in the background of Vandana and IR64. Many improved lines developed through conventional and molecular approaches are being evaluated through participatory varietal selection in different countries.

#### **9. Conclusions and future perspectives**

Grain yield under drought is a very complex trait. Long-term and consistent efforts are required to make a significant improvement in the drought tolerance of rice varieties. A prior knowledge of the target area with respect to drought pattern, farmers' preferences, and prevailing pests and diseases is essential. The selection of parents and breeding strategies plays an important role in a successful breeding program. The conventional breeding approach with grain yield as a selection parameter has been successful in developing improved drought-tolerant varieties. Through molecular breeding approaches, major QTLs for grain yield under drought have been identified and introgressed in popular rice varieties. Meta analysis and QTL validation of major-effect grain-yield QTLs indicate their consistent effect across environments and variable but significant effect against different genetic backgrounds. The drought breeding program at IRRI has been successful in developing and releasing drought-tolerant varieties in partner countries that showed a yield advantage of 0.8-1.2 t ha-1 under drought over presently cultivated varieties. The challenges ahead are the effective use of the drought QTLs and their combinations in breeding for drought tolerance, fine mapping of QTLs to facilitate precise introgression without undesirable linkages, and understanding the physiological and molecular mechanisms associated with major-effect grain-yield QTLs under drought.

Understanding the physiological and molecular mechanisms associated with drought tolerance of major-effect QTLs is one of the major components of drought breeding. For this purpose, near-isogenic lines for QTLs (QTL-NILs) are being developed through markerassisted introgression and background recovery of the recipient genome. The NILs differing only at QTLs and similar in the background genotype are used to understand the physiological and molecular mechanisms of increased yield under drought provided by QTLs.

The drought breeding program at IRRI standardized phenotyping under managed drought stress in field conditions. Direct selection for grain yield under drought has been applied as a criterion for developing improved cultivars through conventional as well as molecular approaches. Grain yield under drought has also been used in mapping and introgressing QTLs. Several major-effect, consistent QTLs have been identified in the background of popular rice mega-varieties. Following conventional breeding approaches, many varieties have been developed and released for cultivation in partner countries. During 2009 and 2010, three breeding lines, IR74371-70-1-1 as Sahbhagi dhan in India, IR74371-54-1-1 as Sahod ulan in the Philippines, and IR80411-B-49-1 as Tarharra 1 in Nepal, were released as drought-tolerant varieties. In 2011, three varieties, IR74371-3-1-1, IR74371-46-1-1, and IR74371-70-1-1, were released in Nepal as Sookha dhan 1, Sookha dhan 2, and Sookha dhan 3, respectively. IR74371-70-1-1 has been release as BRRI dhan56 in Bangladesh. IR77080-B-34-3 and IR81047-B-3-4 are breeding lines identified as promising in Mozambique. Through molecular approaches, major-effect QTLs have been introgressed and pyramided in the background of Vandana and IR64. Many improved lines developed through conventional and molecular approaches are being evaluated through participatory varietal selection in

Grain yield under drought is a very complex trait. Long-term and consistent efforts are required to make a significant improvement in the drought tolerance of rice varieties. A prior knowledge of the target area with respect to drought pattern, farmers' preferences, and prevailing pests and diseases is essential. The selection of parents and breeding strategies plays an important role in a successful breeding program. The conventional breeding approach with grain yield as a selection parameter has been successful in developing improved drought-tolerant varieties. Through molecular breeding approaches, major QTLs for grain yield under drought have been identified and introgressed in popular rice varieties. Meta analysis and QTL validation of major-effect grain-yield QTLs indicate their consistent effect across environments and variable but significant effect against different genetic backgrounds. The drought breeding program at IRRI has been successful in developing and releasing drought-tolerant varieties in partner countries that showed a yield advantage of 0.8-1.2 t ha-1 under drought over presently cultivated varieties. The challenges ahead are the effective use of the drought QTLs and their combinations in breeding for drought tolerance, fine mapping of QTLs to facilitate precise introgression without undesirable linkages, and understanding the physiological and molecular mechanisms

**7. Development of QTL-NILs for physiological and molecular studies**

**8. Success stories of drought breeding at IRRI**

**9. Conclusions and future perspectives**

associated with major-effect grain-yield QTLs under drought.

different countries.

Appendix 1. Conventional breeding approach for developing drought-tolerant rice varieties

Sustainable Rice Yield in Water-Short Drought-Prone

**(DA2)**

M14 (**DA3**)

segregating

homozygous

allele, and

background

under drought

**(RA)**

BC2F3 60 Screen QTL+ and QTL– lines

Note\* M = marker, DA = Donor allele, RA = Recipient allele

**10. References**

14-22

Vol. 47, 507-516

Press. 222 p

BC2F2 4000 Confirm F2

Environments: Conventional and Molecular Approaches 163

Select the plants with all three QTLs, **RP** flanking, and more recipient background

Advance the lines

**QTL***1.1* – M1, M2, M3 **(DA1) QTL***1.2* – M4, M5, M6, M7, M8, M9

**QTL***1.3* – M10, M11, M12, M13,

SSR markers in selected plants Check for QTL flanking markers

condition, flanks with recipient

having more recipient genome

Appendix 2. Protocol for pyramiding of three major-effect grain yield QTLs under drought

Alcamo, J., Leemans, R., & Kreileman, E. (1999). Global Change Scenarios of the 21th Century: Results from the Image 2.1 Model. *Elsevier Science*, The Netherlands Atlin, G. (2003). Improving drought tolerance by selecting for yield. In: Fischer, K.S., Lafitte,

Bernier, J., Kumar, A., Venuprasad, R., Spaner, D., & Atlin, G.N. (2007). A large-effect QTL

Bernier, J., Atlin, G.N., Serraj, R., Kumar, A., & Spaner, D. (2008). Breeding upland rice for

Bernier, J., Kumar, A., Venuprasad, R., Spaner, D., Verulkar, S., Mandal, N.P., Sinha, P.K.,

Blum, A. (1988). Plant breeding for stress environments. Boca Raton, Florida (USA): CRC

drought resistance (a review). *J. Sci. Food Agric.,* Vol. 88, 927-939

in the Philippines and eastern India. *Euphytica,* Vol. 166, 207-217

R., Fukai, S., Atlin, G., Hardy, B. (eds.). Breeding rice for drought-prone environments. Los Baños (Philippines): International Rice Research Institute. pp.

for grain yield under reproductive-stage drought stress in upland rice. *Crop Sci.*,

Peeraju, P., Dongre, P.R., Mahto, R.N., & Atlin, G. (2009). Characterization of the effect of a QTL for drought resistance in rice, *qtl12.1,* over a range of environments

Select plants with QTLs in

homozygous condition Background selection for

Select plants with all three QTLs in

**QTL***1.1* – M1, M2, M3 **(DA1) QTL***1.2* – M4, M5, M6, M7, M8, M9

**QTL***1.1* –M1, M2, M3 **(DA1)**

**QTL***1.1* – M1, M2, M3 **(DA1) QTL***1.2* – M4, M5, M6, M7, M8, M9

**QTL***1.3* – M10, M11, M12, M13,

Select plants with all the QTLs

**QTL***1.<sup>1</sup>* – M1, M2, M3 **(DA1) QTL***1.2* – M4, M5, M6, M7, M8, M9

**QTL***1.3* – M10, M11, M12, M13,

Select plants with all three QTLs Background selection using 100

chromosomes in selected plants

**QTL***1*.*<sup>1</sup>* – M1, M2, M3 **(DA1) QTL***1.2* – M4, M5, M6, M7, M8, M9

**QTL***1.3* – M10, M11, M12, M13,

Select plants with all three QTLs

SSR markers in selected plants

Background selection for

SSR markers uniformly distributed on all the

Select plants with QTL

**QTL***1.2* – M4, M5, M6, M7, M8, M9

**Genotyping Cross**

Make crosses between plants with **QTL***1.1* and

Make crosses between plants having **QTL***1.1* and **QTL***1.2* with plants having **QTL***1.3*

Cross F1 plants with three QTLs to recipient

Cross BC1F1 with three

Self the selected plants

parent (**RP**)

QTLs to **RP**

**QTL***1.2*

**Generation No. of**

Selection of parents

(two QTLs)

(three QTLs)

F1

F1

**plants**

**(DA2)**

**(DA2)**

**(DA2)**

**(DA2)**

**(DA2)**

M14 (**DA3**)

segregating

M14 (**DA3**)

M14 (**DA3**)

50 Confirm F1

100 Confirm F1

BC1F1 1000 Confirm BC1F1

BC2F1 2000 Confirm BC2F1

Note\* M = marker, DA = Donor allele, RA = Recipient allele

Appendix 2. Protocol for pyramiding of three major-effect grain yield QTLs under drought

#### **10. References**

Sustainable Rice Yield in Water-Short Drought-Prone

analysis. *BMC Genomics*, Vol. 10, 276

QTL effects*. Field Crops Res*., Vol. 103, 42-52

153-163

35, 25-34

107, 221-231

2011

23–26.

207

135, 384-399

*Omonrice*, Vol. 16, 9-15

Environments: Conventional and Molecular Approaches 165

Jongdee, B., Fukai, S., & Cooper, M. (2002). Leaf water potential and osmotic adjustment as

Kamoshita, A., Babu R.C., Boopathi, N.M., & Fukai, S. (2008). Phenotypic and genotypic

Khowaja, F.S., Norton, G.J., Courtois, B., & Price, A.H. (2009). Improved resolution in the

Khush, G.S. (1997). Origin, dispersal, cultivation and variation of rice. *Plant Mol. Biol*., Vol.

Kumar, A., Bernier, J., Verulkar, S., Lafitte, H.R., & Atlin, G.N. (2008). Breeding for drought

Kumar, A. (2011). Making rice less thirsty: progress at IRRI. Annual Seminar series, March 3,

Kumar, R., Venuprasad, R., & Atlin, G.N. (2007). Genetic analysis of rainfed lowland rice

Lafitte, R. (2003). Managing water for controlled drought in breeding plots. In: Fischer, K.S.,

Lanceras, J.C., Pantuwan, G.P., Jongdee, B., & Toojinda, T. (2004). Quantitative trait loci

Lang, N.T. & Buu, B.C. (2008). Fine mapping for drought tolerance in rice (*Oryza sativa* L.).

Mackill, D.J., Coffman, W.R., & Garrity, D.P. (1996). Rain-fed Lowland Rice Improvement

Mandal, N.P., Sinha, P.K., Variar, M., Shukla, V.D., Perraju, P., Mehta, A., Pathak, A.R.,

McCouch, S.R., Teytelman, L., Xu, Y., Lobos, K.B., Clare, K., Walton, M., Fu, B., Maghirang,

McCouch, S.R., Sweeney, M., Li, J., Jiang, H., Thomson, M., Septiningsih, E., Edwards, J.,

International Rice Research Institute, Los Baños, Philippines, 242 p

rainfed upland environments. *Field Crops Res*., Vol. 118, 135-144

rain fed environments. *Field Crops Res.*, Vol. 109, 1-23

physiological traits to improve drought tolerance in rice. *Field Crops Res.*, Vol. 76,

analysis of drought-resistance traits for development of rice cultivars adapted to

position of drought-related QTLs in a single mapping population of rice by meta-

tolerance: direct selection for yield, response to selection and use of drought tolerant donors in upland and lowland-adapted populations. *Field Crops Res.*, Vol.

drought tolerance under naturally-occurring stress in eastern India: heritability and

Lafitte, R., Fukai, S., Atlin, G., Hardy, B. (eds.). Breeding rice for drought-prone environments. Los Baños (Philippines): International Rice Research Institute. pp.

associated with drought tolerance at reproductive stage in rice. *Plant Physiol.,* Vol.

Dwivedi, J.L., Rathi, S.P.S., Bhandarkar, S., Singh, B.N., Singh, D.N., Panda, S., Mishra, N.C., Singh, Y.V., Pandya, R., Singh, M.K., Sanger, R.B.S., Bhatt, J.C., Sharma, R.K., Raman, A., Kumar, A., & Atlin, G. (2010). Implications of genotype × input interactions in breeding superior genotypes for favorable and unfavorable

R., Li, Z., Xing, Y., Zhang, Q., Kono, I., Yano, M., Fjellstrom, R., Declerck, G., Schneider, D., Cartinhour, S., Ware, D., & Stein, L. (2002). Development and mapping of 2240 new SSR markers for rice (*Oryza sativa* L.). *DNA Res.*, Vol. 9, 199-

Moncada, P., Xiao, J., Garris, A., Tai, T., Martinez, C., Tohme, J., Sugiono, M., McClung, A., Yuan, L.P., & Ahn, S.N. (2007). Through the genetic bottleneck: *O.*

Charmet, G., Robert, N., Perrtant, M.R., Gay, G., Sourdille, P., Groos, C., Bernard, S., &

Courtois, B., Ahmadi, N., Khowaja, F., Price, A., Rami, J.F., Frouin, J., Hamelin, C., & Ruiz,

Courtois, B., Shen, L., Petalcorin, W., Carandang, S., Mauleon, R., & Li, Z. (2003). Locating

Crosbie, T.M., Eathington, S.R. & Johnson, G.R. (2006). Plant breeding: past, present, and

Cruz, R.T. & O'Toole, J.C. (1984). Dry land rice response to an irrigation gradient at

Darvasi, A. & Soller, M. (1992). Selective genotyping for determination of linkage between a marker locus and a quantitative trait locus. *Theor. Appl. Genet*., Vol. 85, 353-359 David, C.C. (1991). The world rice economy: challenges ahead. In: Khush, G.S. and Toenniessen, G.H. (eds.). *Rice Biotechnology*, CAB International, UK, pp 19-54 Ding, X., Li, X. & Xiong, L. (2011). Evaluation of near-isogenic lines for drought resistance

root volume in rice. *Theor. Appl. Genet.*, DOI: 10.1007/s00122-011-1629-1O Dixit, S., Swamy, B.P.M., Vikram, P., Ahmed, H.U., Sta Cruz, M.T., Amante, M., Atri, D.,

FAO (2002). Crops and drops – making the best use of water for agriculture. Food and

Fukuoka, S., Ebana, K., Yamamoto, T., & Yano, M. (2010). Integration of genomics into rice

Fukai, S., Cooper, M., & Salisbury, J. (eds.) (1996). Breeding Strategies for Rainfed Lowland

Ghimire, K.H., Quiatchon, L.A., Vikram, P., Swamy, B.P.M., Hernandez, J.E., Borromeo,

Gleick, P.H. (1993). Water and conflict: fresh water resources and international security. *Int.*

Hossain, M. (1995). Sustaining food security for fragile environments in Asia: achievements,

Huke, R.E., & Huke, E.H. (1997). Rice area by type of culture: South, Southeast, and East

landrace in background of rice mega-varieties. (Unpublished).

Johnson, G.R. (2004). Marker assisted selection. *Plant Breed. Rev.*, Vol. 24, 293-310

improves resolution to a few candidate genes. *Rice*, Vol. 2, 115-128

international symposium. Ames, IA: Blackwell Publishing.

flowering stage. *Agron. J.*, Vol. 76, 178-183

severities. *Theor. Appl. Genet.,* (Submitted)

breeding. *Rice*, Vol. 3, 131-137

*Security*, Vol. 18(1), 79-112

Asia. IRRI, Los Baños, Philippines

77, 260 p

23

Agriculture Organization of the United Nations. Rome

*Euphytica*, Vol. 134, 335-345

Bernard, M. (1999). Marker-assisted recurrent selection for cumulating additive and interactive QTLs in recombinant inbred lines. *Theor. Appl. Genet.*, Vol. 99, 1143-1148

M. (2009). Rice root genetic architecture: meta-analysis from a QTL database

QTLs controlling constitutive root traits in the rice population IAC 165\_Co39.

future. In: Lamkey, K.R., Lee, M. (eds.). Plant breeding: the Arnel R. Hallauer

QTL and fine mapping of a locus affecting flag leaf width, spikelet number, and

Leung, H., & Kumar, A. (2011). Fine mapping four large-effect QTLs for rice grain yield under drought reveals sub-QTLs conferring response to variable drought

Rice in Drought-prone Environments. Proceedings of an International Workshop held at Ubon Ratchathani, Thailand, 5-8 November 1996. ACIAR Proceedings No.

T.H., & Kumar, A. (2011). A large-effect drought grain yield QTL from Indian

challenges, and implications for rice research. In: Fragile lives in fragile ecosystems. Proceedings of the International Rice Research Conference; 13-17 Feb 1995; Los Baños, Philippines. Manila (Philippines): International Rice Research Institute. p 3-

Sustainable Rice Yield in Water-Short Drought-Prone

*Theor. Appl. Genet.,* Vol. 103, 75-83

consensus. *BMC Genomics*, Vol. 12, 319

potential. *Genome Res.*, Vol. 11, 1441-1452

crops. *Trends Plant Sci.*, Vol. 11, 405-412

approaches. *Biotechnol.* & *Biotechnol*., Vol. 23, 1410-1413

Vol. 16, 289-293

(Unpublished)

Oxford, UK. pp. 228-301

253-315

Vol. 117, 169-266

(*Oryza sativa* L.). *Rice Genet. Newsl.*, Vol. 22, 69-71

Environments: Conventional and Molecular Approaches 167

Shashidhar, H.E., Vinod, M.S., Sudhir, N., Sharma, G.V., & Krishna-Murthy, K. (2005).

Shen, L., Courtois, B., McNally, K.L., Robin, S., & Li, Z. (2001). Evaluation of near-isogenic

Shrivastava, M.N. & Verulkar, S.B. (2009). Progress in crop improvement research. Limited

Swamy, B.P.M, Vikram, P., Dixit, S., Ahmed, H.U., & Kumar, A. (2011a). Meta-analysis of

Swamy, B.P.M., Ahmed, H.U., Henry, A., Dixit, S., Vikram, P., Mauleon, R., Vera Cruz, C.,

Temnykh, S., Declerck, G., Lukashova, A., Lipovich, L., Cartinhour, S., & McCouch, S.

Tsonev, S., Todorovska, E., Avramova, V., Kolev, S., Abu-Mhadi, N., & Christov, N.K.

Tuberosa, R. (2004). Molecular approaches to unravel the genetic basis of water use

Tuberosa, R. & Salvi, S. (2004). QTLs and genes for tolerance to abiotic stress in cereals. *In*:

Tuberosa, R. & Salvi, S. (2006). Genomics-based approaches to improve drought tolerance of

Uga, Y., Okuno, K., & Yano, M. (2011). *Dro1*, a major QTL involved in deep rooting of rice

Venuprasad, R., Dalid, C.O., Del Valle, M., Zhao, D., Espiritu, M., Sta Cruz, M.T., Amante,

Verulkar, S.B., Mandal, N.P., Dwivedi, J.L., Singh, B.N., Sinha, P.K., Mahato, R.N., Dongre,

under upland field conditions. *J. Exp. Bot.* doi:10.1093/jxb/erq429

using bulk-segregant analysis. *Theor. Appl. Genet.*, Vol. 120, 177-190

Markers linked to grain yield using bulked segregant analysis approach in rice

lines of rice introgressed with QTLs for root depth through marker-aided selection.

Proceedings. Edited by Hossain, M., Bennett, J., Mackill, D., Hardy, B. Los Baños, Laguna (Philippines): International Rice Research Institute (IRRI), Vol. 14, 3-12 Sinclair, T.R. (2011). Challenges in breeding for yield increase for drought. *Trends Plant Sci.,*

grain yield QTL identified during agricultural drought in grasses showed

Kouji, S., Ali, M., Ramiah, V., Shoshi, K., Leung H., & Kumar, A. (2011b) Convergence of mapping, physiological, and gene expression analyses reveal multiple QTL that enhance transpiration and yield under drought in rice

(2001). Computational and experimental analysis of microsatellites in rice (*Oryza sativa* L.): frequency, length variation, transposon associations and genetic marker

(2009). Genomics assisted improvement of drought tolerance in maize: QTL

efficiency. *In*: M.A. Bacon (Ed.), Water use efficiency in plant biology. Blackwell,

Gupta, P.K., Varshney, R. (Eds.). Cereal genomics. Kluwer, The Netherlands. pp.

M., Kumar, A., & Atlin, G.N. (2009). Identification and characterization of largeeffect quantitative trait loci for grain yield under lowland drought stress in rice

P., Singh, O.N., Bosee, L.K. Swaine, P., Robin, S., Chandrababu, R., Senthil, S., Jain, A., Shashidhar, H.E., Hittalmani, S., Vera Cruzi, C., Paris, T., Ramani, A., Haefelei, S., Serraji, R., Atlin, G., & Kumar, A. (2010). Breeding resilient and productive genotypes adapted to drought-prone rainfed ecosystem of India. *Field Crops Res.*,

*rufipogon* as a source of trait-enhancing alleles for *O. sativa*. *Euphytica*, Vol. 154, 317- 339

McNally, K.L., Childs, K.L., Bohnert, R., Davidson, R.M., Zhao, K., Ulat, V.J., Zeller, G.,

Michelmoore, R.W., Paran, I., & Kesseli, R.V. (1991). Identification of markers linked to

Navabi, A., Mather, D.E, Bernier, J., Spaner, D.M., & Atlin, G.N. (2009). QTL detection with

Nguyen, T.T.T., Klueva, N., Chamareck, V., Aarti, A., Magpantay, G., Millena, A.C.M.,

Ouk, M., Basnayake, J., Tsubo, M., Fukai, S., Fischer, K.S., Cooper, M., & Nesbitt, H. (2006).

Pantuwan, G., Fukai, S., Cooper, M., Rajatasereekul, S., & O'Toole, J.C. (2002). Yield

Pimentel, D., Houser, J., Preiss, E., White, O., Fang, H., Mesnick, L., Barsky, T., Tariche, S.,

Price, A.H., Cairns, J.E., Horton, P., Jones, H.G., & Griffiths, H. (2002a). Linking drought-

Price, A.H., Townend, J., Jones, M.P., Audebert, A., & Courtois, B. (2002b). Mapping QTLs

Ribaut, J.M. & Ragot, M. (2007). Marker-assisted selection to improve drought adaptation in

Salunkhe, A.S., Poornima, R., Silvas, K., Prince, J., Kanagaraj, P., Sheeba, A., Amudha, K.,

Serraj, R., Kumar A., McNally, K.L., Slamet-Loedin, I., Bruskiewich, R., Mauleon, R. Cairns,

varieties of rice. *Proc. Natl. Acad. Sci.* USA, Vol. 106, 12273-12278

*Acad. Sci.* USA, Vol. 88, 9828-9832

*Genomics*, Vol. 272, 35-46

*Crops Res.*, Vol. 73, 181-200

989-1004

*Bot.*, Vol. 58, 351-360

*Biotechnol*.*,* Vol. 49, 90-95

Vol. 103, 41-99

society. *BioScience,* Vol. 47, 97-106

West Africa. *Plant Mol. Biol.,* Vol. 48, 683-695

analyses. *Theor. Appl. Genet.,* Vol. 118, 347-358

rain fed lowland rice. *Field Crops Res.*, Vol. 99, 48-58

339

*rufipogon* as a source of trait-enhancing alleles for *O. sativa*. *Euphytica*, Vol. 154, 317-

Clark, R.M., Hoen, D.R., Bureau, T.E., Stokowski, R., & Ballinger, D.G. (2009). Genome-wide SNP variation reveals relationships among landraces and modern

disease resistance genes by bulked segregant analysis: a rapid method to detect markers in specific genomic regions by using segregating populations. *Proc. Natl.*

bidirectional and unidirectional selective genotyping: marker-based and trait-based

Pathan, M.S., & Nguyen, H.T. (2004). Saturation mapping of QTL regions and identification of putative candidate genes for drought tolerance in rice. *Mol. Gen.*

Use of drought response index for identification of drought tolerant genotypes in

response of rice (*Oryza sativa* L.) genotypes to different types of drought under rainfed lowlands. Part 3. Plant factors contributing to drought resistance. *Field*

Schreck, J., & Alpert, S. (1997). Water resources: agriculture, the environment, and

resistance mechanisms in upland rice using a QTL approach: progress and new opportunities to integrate stomatal and mesophyll responses. *J. Exp. Bot.,* Vol. 53,

associated with drought avoidance in upland rice grown in the Philippines and

maize: the backcross approcah, perspectives, limitations and alternatives. *J. Exp.*

Suji K.K., Senthil, A., & Chandra Babu, R. (2011). Fine mapping QTL for drought resistance traits in rice (*Oryza sativa* L.) using bulk segregant analysis. *Mol.*

J., & Hijmans, R.J. (2009). Improvement of drought resistance in rice. *Adv. Agron.*,

**9**

*Serbia*

**Effects of Salinity on Vegetable**

Irrigation of vegetables during both air and soil-born drought has very positive effect on growth, development and yield. The impact of irrigation on the metabolism of plants is very complex because the increase in soil moisture affects plant physical, chemical and biological properties. Increasing the amount of water in the soil increases its heath capacity. Irrigated (wet) soil is cooler in summer and warmer during the cold weather in comparison with dry soil. Irrigation increases heat conduction in soil and relative humidity of ground layers of the atmosphere. These changes reduce the temperature fluctuations of ground layers of the air and soil during the day and night. Therefore, irrigation suppresses harmful effects of the weak spring and autumn frosts. The water in the soil acts as a solvent and as an environment in which chemical reactions take place. With increasing soil moisture concentration of soil solution is diminishing and the power of water to dissolve different substances is increasing. The CO2 dissolved in the water contributes significantly to this process by lowering the pH value of soil solution. In weak acidic solution mineral elements present in the soil become more soluble, which may alter plant nutrition. However, if there is any excess of water in the soil, than easily soluble salts of potassium, nitrogen and phosphorus from the upper layers of soil can be leached into deeper soil layers, even outside the zone of the root system, which is very undesirable. In general, irrigation increases soil pH, which should be borne in mind because optimum acidity (pH) for cultivation of most vegetables is between 6.0 and 6.5. Irrigation has a positive effect on microbial processes in the soil which in turn affects nutrient availability to plants. Moreover, irrigation stimulates aerobic processes that may be

temporarily slowed down or replaced by anaerobic if the soil is too wet.

In agricultural practice it is not always possible to provide sufficient quantities of irrigation water of good quality. Often more mineralized water and processed waste waters are used (Kalavrouziotis et al., 2010). Therefore, by irrigation the soil can be enriched with useful or harmful salts and various other compounds, depending on water quality. In the irrigation water too high concentration of ions that make it saline is present very often (Table 1).

Salinity of arable land is a problem that is becoming more and more important in many areas where irrigation is a regular agro-technical measure, and in semi-arid and arid regions in the world where atmospheric precipitations are not sufficient to flush the salts from the root zone. When irrigation water is of inadequate quality, the occurrence of chlorosis between leaf veins is commonly observed, leaf tissue necrosis often develops and flowering

**1. Introduction**

**Growth and Nutrients Uptake**

Ivana Maksimovic and Žarko Ilin *University of Novi Sad, Faculty of Agriculture*

### **Effects of Salinity on Vegetable Growth and Nutrients Uptake**

Ivana Maksimovic and Žarko Ilin *University of Novi Sad, Faculty of Agriculture Serbia*

#### **1. Introduction**

168 Irrigation Systems and Practices in Challenging Environments

Vikram, P., Sta Cruz, T., Espiritu, M., Valle, M.D., Singh, A.K., & Kumar, A. (2009). Major

Xiao, J., Li, J., Grandillo, S., Ahn, S.N., Yuan, L., Tanksley, S.D., & McCouch, S.R. (1998).

Xing, Y.Z., Tan, Y.F., Hua, J.P., Sun, X.L., Xu, C.G., & Zhang, Q. (2002). Characterization of

the genetic basis of yield traits in rice. *Theor. Appl. Genet.*, Vol. 105, 248-257 Zeigler, R.S. & Puckridge, D.W. (1995). Improving sustainable productivity in rice based

Zou, G.H., Mei, H.W., Liu, Y., Liu, G.L., Hu, S.P., Yu, X.Q., Li, M.S., Wu, J.H., & Luo, L.J.

among traits and genetic markers. *Theor. Appl. Genet*., Vol. 112, 106-113

relative, *Oryza rufipogon*. *Genetics*, Vol. 150, 899-909

Griff.). *Plant Mol. Biol*., Vol. 62, 247-259

21-39

effect QTLs for grain yield under lowland drought stress. Poster presented at International Rice Genetics Symposium, 16-19 Nov. 2009, Manila, Philippines Wopereis, M.C.S., Kropff, M.J., Maligaya, A.R., & Tuong, T.P. (1996). Drought-stress

responses of two lowland rice cultivars to soil water status. *Field Crops Res.*, Vol. 46,

Identification of trait-improving quantitative trait loci alleles from a wild rice

the main effects, epistatic effects and their environmental interactions of QTLs on

rainfed lowland systems of south and Southeast Asia. Feeding four billion people. The challenge for rice research in the 21st century. *GeoJournal*, Vol. 35, 307-324 Zhang, X., Zhou, S., Fu, Y., Su, Z., Wang, X., & Sun, C. (2006) Identification of a drought

tolerant introgression line derived from Dongxiang common wild rice (*O. rufipogon*

(2005). Grain yield responses to moisture regimes in a rice population: association

Irrigation of vegetables during both air and soil-born drought has very positive effect on growth, development and yield. The impact of irrigation on the metabolism of plants is very complex because the increase in soil moisture affects plant physical, chemical and biological properties. Increasing the amount of water in the soil increases its heath capacity. Irrigated (wet) soil is cooler in summer and warmer during the cold weather in comparison with dry soil. Irrigation increases heat conduction in soil and relative humidity of ground layers of the atmosphere. These changes reduce the temperature fluctuations of ground layers of the air and soil during the day and night. Therefore, irrigation suppresses harmful effects of the weak spring and autumn frosts. The water in the soil acts as a solvent and as an environment in which chemical reactions take place. With increasing soil moisture concentration of soil solution is diminishing and the power of water to dissolve different substances is increasing. The CO2 dissolved in the water contributes significantly to this process by lowering the pH value of soil solution. In weak acidic solution mineral elements present in the soil become more soluble, which may alter plant nutrition. However, if there is any excess of water in the soil, than easily soluble salts of potassium, nitrogen and phosphorus from the upper layers of soil can be leached into deeper soil layers, even outside the zone of the root system, which is very undesirable. In general, irrigation increases soil pH, which should be borne in mind because optimum acidity (pH) for cultivation of most vegetables is between 6.0 and 6.5. Irrigation has a positive effect on microbial processes in the soil which in turn affects nutrient availability to plants. Moreover, irrigation stimulates aerobic processes that may be temporarily slowed down or replaced by anaerobic if the soil is too wet.

In agricultural practice it is not always possible to provide sufficient quantities of irrigation water of good quality. Often more mineralized water and processed waste waters are used (Kalavrouziotis et al., 2010). Therefore, by irrigation the soil can be enriched with useful or harmful salts and various other compounds, depending on water quality. In the irrigation water too high concentration of ions that make it saline is present very often (Table 1).

Salinity of arable land is a problem that is becoming more and more important in many areas where irrigation is a regular agro-technical measure, and in semi-arid and arid regions in the world where atmospheric precipitations are not sufficient to flush the salts from the root zone. When irrigation water is of inadequate quality, the occurrence of chlorosis between leaf veins is commonly observed, leaf tissue necrosis often develops and flowering

Effects of Salinity on Vegetable Growth and Nutrients Uptake 171

Stress caused by lack of water has similarities with the stress caused by excess salt in the soil solution, although there are differences (Munns, 2002). The stress caused by the presence of salts is one of the biggest problems that accompany agricultural production (Francois & Maas, 1994). Vegetables are not immune to the increased concentration of salts and therefore their presence significantly affects their quality and yield. According to FAO (1997) saline soil is the soil whose soil solution electrical conductivity (ECE) is 4 dS m-1 and higher, whereas soils whose ECE exceeds 15 dS m-1 are considered highly saline. Cations that are most commonly associated with saline soils are Na+, Ca2+ and Mg2+, accompanied by anions

, SO42-and HCO3-. However, major ions are considered to be Na+ and Cl- since both are toxic to plants (Dudley, 1992, Hasegawa et al., 2000). Sulfates, which are usually involved in metabolic processes of plants as an integral part of proteins and enzymes, can also disrupt

Stress caused by increased concentrations of salts effect the metabolism of plants and the final outcome of crop production in many ways. Excess salt has an osmotic effect, which means that the presence of salts reduces the amount of water accessible to plants. Some ions may be toxic to some processes in plants. Increased salt concentrations can lead to disturbances in mineral nutrition of plants, the plant hormone imbalances, and to the formation of reactive compounds such as different types of oxygen and other free radicals that damage cell membranes (Marschner, 1995). Plant cells, tissues, organs, individuals and entire ecosystems can have and/or can develop mechanisms by which they protect themselves against adverse effects of elevated salt concentrations (Pitman & Läuchli, 2002).

Response of vegetables to the presence of increased amounts of salts is primarily stunted growth (Romero-Aranda et al., 2001). The ultimate impact of excess salts is of course very dependent on the other environmental factors such as humidity, temperature, light and air pollution (Shannon et al., 1994). The accumulation of salts in the leaves cause premature aging, reduces the supply of plant parts with nutrients and products of carbon assimilation of the fastest-growing plant parts and thus impair the growth of the entire plant. In the more sensitive genotypes salts accumulate more rapidly and because cells are not able to isolate the salt ions in vacuoles to the same extent as more tolerant genotypes, the leaves of more sensitive genotypes usually die faster (Munns, 2002). Neumann (1997) suggests that growth inhibition due to excessive salt concentration in the leaves reduces the volume of new leaf tissue in which excess salts can accumulate and therefore, in combination with the continuous accumulation of salts, it can lead to an increase in salt concentration in the tissue. It is often difficult to determine the relative influence of osmotic effect and the effect of the toxicity of specific ions on vegetable yield. In any case, yield losses due to osmotic stress can be very significant even before symptoms of toxicity on leaves become noticeable. Under the influence of salt stress growth of many species of vegetables is reduced, such as tomato (Romero-Aranda et al., 2001, Maggio et al., 2004), pepper (De Pascale et al., 2003b), celery (De Pascale et al., 2003a) and peas (Maksimovic et al., 2008, Maksimovic et al ., 2010). There are significant differences in salt tolerance between plant species and genotypes and similar goes for the ability to tolerate water deficiency (Munns, 2002; Lukovic et al., 2009). Table 1 shows in parallel the classification of waters with respect to the total concentration of salts and tolerance of selected vegetable species to salts. Salinity causes anatomical changes in

the metabolism of plants. They are usually more toxic than chlorides.

**2. Effect of excess salinity on plant growth**

Cl-

may not happen at all. Very great importance is ascribed to the time during which the plants were exposed to different concentrations of salts. As explained by Munns (2002), effects of salinity on salt-tolerant plants are the same as effects of water deficiency. Within minutes and hours of exposure to salinity salt-specific effects are not visible. If the exposure to salts lasts many days, salt-induced injuries become apparent on older leaves of salt-sensitive plants, in addition to reduced rate of leaf emergence and heavier impact on leaves than on roots, which are symptoms typical for water-stress.  Differences between shortterm/temporary effects of salinization vs. long-term effects (either single irrigation seasons or multiple years) are often overlooked (Maggio et al., 2011).

Table 1. Classification of waters with respect to total salt concentration and salt tolerance of selected vegetables (after Maas 1990, Francois & Maas, 1994 & Hillel, 2000). Asterix (\*) marks the level of tolerance: sensitive (S), moderately sensitive (MS), moderately tolerant (MT), tolerant (T).

may not happen at all. Very great importance is ascribed to the time during which the plants were exposed to different concentrations of salts. As explained by Munns (2002), effects of salinity on salt-tolerant plants are the same as effects of water deficiency. Within minutes and hours of exposure to salinity salt-specific effects are not visible. If the exposure to salts lasts many days, salt-induced injuries become apparent on older leaves of salt-sensitive plants, in addition to reduced rate of leaf emergence and heavier impact on leaves than on roots, which are symptoms typical for water-stress.  Differences between shortterm/temporary effects of salinization vs. long-term effects (either single irrigation seasons

> Common name

brackish 500–1000 0.6–1.5 Bean *Phaseolus vulgaris* L. 1.0 S Carrot *Daucus carota* L. 1.0 S Muskmelon *Cucumis melo* L. 1.0 MS Eggplant *Solanum melongena* L. 1.1 MS Onion *Allium cepa* L. 1.2 S Radish *Raphanus sativus* L. 1.2 MS Lettuce *Lactuca sativa* L. 1.3 MS Pepper *Capsicum annuum L.* 1.5 MS Brackish 1000–2000 1.5–3.0 Garlic *Allium sativum* L. 1.7 MS Potato *Solanum tuberosum* L. 1.7 MS Cabbage *Brassica oleracea* L. 1.8 MS Celery *Apium graveolens* L. 1.8 MS Spinach *Spinacia oleracea* L. 2.0 MS Cucumber *Cucumis sativus* L. 2.5 MS

saline 2000-5000 3.0–8.0 Pea *Pisum sativum* L. 3.4 MS Red beet *Beta vulgaris* L. 4.0 MT Asparagus *Asparagus officinalis* L. 4.1 T

Table 1. Classification of waters with respect to total salt concentration and salt tolerance of selected vegetables (after Maas 1990, Francois & Maas, 1994 & Hillel, 2000). Asterix (\*) marks the level of tolerance: sensitive (S), moderately sensitive (MS), moderately tolerant (MT),

Botanical name

Thresho ld EC (dS m-1)

*esculentum* L. 2.5 MS

Rating\*

or multiple years) are often overlooked (Maggio et al., 2011).

EC (dSm-1)

Tomato *Lycopersicon*

Total dissolved salts (ppm)

Fresh water < 500 < 0.6

Saline 5000-10000 8.0–15.0 Highly saline 10000-35000 15.0–45.0

Water designation

Slightly

Moderately

tolerant (T).

Stress caused by lack of water has similarities with the stress caused by excess salt in the soil solution, although there are differences (Munns, 2002). The stress caused by the presence of salts is one of the biggest problems that accompany agricultural production (Francois & Maas, 1994). Vegetables are not immune to the increased concentration of salts and therefore their presence significantly affects their quality and yield. According to FAO (1997) saline soil is the soil whose soil solution electrical conductivity (ECE) is 4 dS m-1 and higher, whereas soils whose ECE exceeds 15 dS m-1 are considered highly saline. Cations that are most commonly associated with saline soils are Na+, Ca2+ and Mg2+, accompanied by anions Cl- , SO4 2-and HCO3- . However, major ions are considered to be Na+ and Cl since both are toxic to plants (Dudley, 1992, Hasegawa et al., 2000). Sulfates, which are usually involved in metabolic processes of plants as an integral part of proteins and enzymes, can also disrupt the metabolism of plants. They are usually more toxic than chlorides.

Stress caused by increased concentrations of salts effect the metabolism of plants and the final outcome of crop production in many ways. Excess salt has an osmotic effect, which means that the presence of salts reduces the amount of water accessible to plants. Some ions may be toxic to some processes in plants. Increased salt concentrations can lead to disturbances in mineral nutrition of plants, the plant hormone imbalances, and to the formation of reactive compounds such as different types of oxygen and other free radicals that damage cell membranes (Marschner, 1995). Plant cells, tissues, organs, individuals and entire ecosystems can have and/or can develop mechanisms by which they protect themselves against adverse effects of elevated salt concentrations (Pitman & Läuchli, 2002).

#### **2. Effect of excess salinity on plant growth**

Response of vegetables to the presence of increased amounts of salts is primarily stunted growth (Romero-Aranda et al., 2001). The ultimate impact of excess salts is of course very dependent on the other environmental factors such as humidity, temperature, light and air pollution (Shannon et al., 1994). The accumulation of salts in the leaves cause premature aging, reduces the supply of plant parts with nutrients and products of carbon assimilation of the fastest-growing plant parts and thus impair the growth of the entire plant. In the more sensitive genotypes salts accumulate more rapidly and because cells are not able to isolate the salt ions in vacuoles to the same extent as more tolerant genotypes, the leaves of more sensitive genotypes usually die faster (Munns, 2002). Neumann (1997) suggests that growth inhibition due to excessive salt concentration in the leaves reduces the volume of new leaf tissue in which excess salts can accumulate and therefore, in combination with the continuous accumulation of salts, it can lead to an increase in salt concentration in the tissue. It is often difficult to determine the relative influence of osmotic effect and the effect of the toxicity of specific ions on vegetable yield. In any case, yield losses due to osmotic stress can be very significant even before symptoms of toxicity on leaves become noticeable. Under the influence of salt stress growth of many species of vegetables is reduced, such as tomato (Romero-Aranda et al., 2001, Maggio et al., 2004), pepper (De Pascale et al., 2003b), celery (De Pascale et al., 2003a) and peas (Maksimovic et al., 2008, Maksimovic et al ., 2010). There are significant differences in salt tolerance between plant species and genotypes and similar goes for the ability to tolerate water deficiency (Munns, 2002; Lukovic et al., 2009). Table 1 shows in parallel the classification of waters with respect to the total concentration of salts and tolerance of selected vegetable species to salts. Salinity causes anatomical changes in

Effects of Salinity on Vegetable Growth and Nutrients Uptake 173

to a reduction in the total absorption area for water uptake.  As one of the mechanisms by which plants protect their cells from harmful effect of high concentration of salts is dilution, then increasing of water retention in the tissues of the plant further reduces transpiration. These factors reduce the efficiency of water usage and ultimately result in reduction of vegetable growth and yield. The vegetation period is shortened, water regime of plants is disrupted and the uptake and distribution of essential elements in both semi-controlled and field conditions is altered

At very low soil water potential, the uptake of water and maintenance of turgor pressure in the tissues becomes very difficult. Water potential of leaves of plants well provided with water ranges from -0.2 to about -0.6 MPa, but the leaves of plants in arid regions can have significantly lower values, from -0.2 to 5 MPa even in extreme conditions (Taiz & Zeiger, 2006). Since the uptake of water is spontaneous process, the water potential of root cells must be more negative than potential of soil solution. If, due to increased salt concentration, the difference between water potential of soil solution and of root cells differs very slightly, plants may adapt osmoticaly by accumulation of so-called compatible osmolites in their cells. In that way, water potential of plant cells is kept more negative in relation to the soil solution water potential, thus permitting continuous uptake of water (Guerrier, 2006; Ghoulam et al., 2002). Increasing the concentration of salt in a medium in which is the root leads to a reduction in the osmotic potential of leaves (Sohan et al., 1999, Romero-Aranda et al., 2001). Reduced osmotic potential of leaves is reflected in many processes in plants. Several authors have reported that water and osmotic potential of plants become more negative with increase in soil salinity, while turgor pressure concomitantly increases (Meloni et al., 2001, Romero-Aranda et al., 2001). Ashraf (2001) found that leaf water potential and evapotranspiration significantly decreased with increasing salt concentration in six species of the genus *Brassica*. At 200 mM NaCl *B. campestris* and *B. carinata* held a significantly higher water potential of leaves than other species in their experiment and therefore can be considered more tolerant to stress caused by salts. According to Sohan et al. (1999), the decrease in water potential can be explained by: 1) the influence of high concentrations of salts due to which plants accumulate more NaCl in the leaves than usual, and 2) by the reduced flow of water from root to aboveground organs due to the reduction of water conductivity, causing water stress

After Katerji et al. (1997), a decrease in RWC indicates loss of turgor which occurs due to disturbances in the increase in the area of individual leaves, in other words in leaf expansion. The connection between the impact of salt on gas exchange in leaves and growth is not completely understood. Many experimental results indicate that gas exchange in leaves of plants remains unchanged under the influence of soil water potential, until it reaches a certain threshold value (Ritchie, 1981). Results of Shalhevet (1994) suggest that the expansion of leaves is the most affected by osmotic stress and that there was a linear relationship between transpiration and the synthesis of organic matter in different agroecological conditions. The slope of this function represents the efficiency of water utilization by plants (water use efficiency, WUE). More recently, stomatal traits have been proven to critically affect WUE. In absence of stress, it has been demonstrated that low stomatal density reduces transpirational water fluxes (Zhang et al., 2001) and improves water use

(Maksimovic et al., 2008, Maksimovic et al., 2010).

in the tissues of leaves.

efficiency (Masle et al., 2005).

leaves of many plant species. For example, the epidermis and mesophyll leaves of beans, cotton and *Attriplex* become thick, length of palisade mesophyll cells and diameter of spongy mesophyll cells increase and thickness of palisade and spongy layers and increasing as well (Longstreth & Nobel, 1979). In some other plant species were recorded adverse effects. In spinach leaves the presence of salt reduces the intercellular spaces (Delfine et al., 1998) and stomatal density in tomato (Romero-Aranda et al., 2001), but it increases stomatal density in pea (Maksimović et al., 2010) (Fig. 1).

Fig. 1. Stomatal density and stomatal diffusive resistance in the presence of 0, 0.1, 0.2, 0.6, or 1.2 g NaCl L-1 in the nutrient solution (Maksimovic et al. 2010).

#### **3. Effect of excess salinity on the water regime of plants**

The main cause of reduced plant growth in the presence of salt can be impairment of water regime. Increasing the salt concentration in the soil increases the osmotic pressure of the soil solution and plants can not uptake the water as easily as in the case of relatively non-saline soils. Therefore, as the concentration of salt i.e. soil EC increases, water becomes less accessible to plants, even if the soil contains significant amounts of water and looks wet. Osmotic pressure depends on the number of particles contained in the solution and the temperature. Osmotic pressure (OP) of extracted soil solution can be expressed by the following empirical formula: OP = 0.36 x EC (dS m-1). At a pressure of about 1.44 bar, corresponding to the EC of 4 dS m-1, the plants start to show signs of physiological stress caused by water shortage. Therefore, in saline soils, despite the fact that water can be physically present, it becomes inaccessible to plants and the phenomenon is known as physiological drought (Ayers & Westcot, 1994).

The first effects of soil salinity, especially when it comes to low and moderate salt concentrations, can be attributed to the increase of osmotic value of the soil solution (Munns & Termaat, 1986). With the increasing salinity of soil solution, uptake of water through the root system becomes more difficult which leads to decreased evapotranspiration and yield. There are several reasons why evapotranspiration decreases with increase in soil salinity. Due to decreased accessibility of water to the root system root growth is reduced wich leads

leaves of many plant species. For example, the epidermis and mesophyll leaves of beans, cotton and *Attriplex* become thick, length of palisade mesophyll cells and diameter of spongy mesophyll cells increase and thickness of palisade and spongy layers and increasing as well (Longstreth & Nobel, 1979). In some other plant species were recorded adverse effects. In spinach leaves the presence of salt reduces the intercellular spaces (Delfine et al., 1998) and stomatal density in tomato (Romero-Aranda et al., 2001), but it increases stomatal

Fig. 1. Stomatal density and stomatal diffusive resistance in the presence of 0, 0.1, 0.2, 0.6, or

The main cause of reduced plant growth in the presence of salt can be impairment of water regime. Increasing the salt concentration in the soil increases the osmotic pressure of the soil solution and plants can not uptake the water as easily as in the case of relatively non-saline soils. Therefore, as the concentration of salt i.e. soil EC increases, water becomes less accessible to plants, even if the soil contains significant amounts of water and looks wet. Osmotic pressure depends on the number of particles contained in the solution and the temperature. Osmotic pressure (OP) of extracted soil solution can be expressed by the following empirical formula: OP = 0.36 x EC (dS m-1). At a pressure of about 1.44 bar, corresponding to the EC of 4 dS m-1, the plants start to show signs of physiological stress caused by water shortage. Therefore, in saline soils, despite the fact that water can be physically present, it becomes inaccessible to plants and the phenomenon is known as

The first effects of soil salinity, especially when it comes to low and moderate salt concentrations, can be attributed to the increase of osmotic value of the soil solution (Munns & Termaat, 1986). With the increasing salinity of soil solution, uptake of water through the root system becomes more difficult which leads to decreased evapotranspiration and yield. There are several reasons why evapotranspiration decreases with increase in soil salinity. Due to decreased accessibility of water to the root system root growth is reduced wich leads

1.2 g NaCl L-1 in the nutrient solution (Maksimovic et al. 2010).

physiological drought (Ayers & Westcot, 1994).

**3. Effect of excess salinity on the water regime of plants**

density in pea (Maksimović et al., 2010) (Fig. 1).

to a reduction in the total absorption area for water uptake.  As one of the mechanisms by which plants protect their cells from harmful effect of high concentration of salts is dilution, then increasing of water retention in the tissues of the plant further reduces transpiration. These factors reduce the efficiency of water usage and ultimately result in reduction of vegetable growth and yield. The vegetation period is shortened, water regime of plants is disrupted and the uptake and distribution of essential elements in both semi-controlled and field conditions is altered (Maksimovic et al., 2008, Maksimovic et al., 2010).

At very low soil water potential, the uptake of water and maintenance of turgor pressure in the tissues becomes very difficult. Water potential of leaves of plants well provided with water ranges from -0.2 to about -0.6 MPa, but the leaves of plants in arid regions can have significantly lower values, from -0.2 to 5 MPa even in extreme conditions (Taiz & Zeiger, 2006). Since the uptake of water is spontaneous process, the water potential of root cells must be more negative than potential of soil solution. If, due to increased salt concentration, the difference between water potential of soil solution and of root cells differs very slightly, plants may adapt osmoticaly by accumulation of so-called compatible osmolites in their cells. In that way, water potential of plant cells is kept more negative in relation to the soil solution water potential, thus permitting continuous uptake of water (Guerrier, 2006; Ghoulam et al., 2002).

Increasing the concentration of salt in a medium in which is the root leads to a reduction in the osmotic potential of leaves (Sohan et al., 1999, Romero-Aranda et al., 2001). Reduced osmotic potential of leaves is reflected in many processes in plants. Several authors have reported that water and osmotic potential of plants become more negative with increase in soil salinity, while turgor pressure concomitantly increases (Meloni et al., 2001, Romero-Aranda et al., 2001). Ashraf (2001) found that leaf water potential and evapotranspiration significantly decreased with increasing salt concentration in six species of the genus *Brassica*. At 200 mM NaCl *B. campestris* and *B. carinata* held a significantly higher water potential of leaves than other species in their experiment and therefore can be considered more tolerant to stress caused by salts. According to Sohan et al. (1999), the decrease in water potential can be explained by: 1) the influence of high concentrations of salts due to which plants accumulate more NaCl in the leaves than usual, and 2) by the reduced flow of water from root to aboveground organs due to the reduction of water conductivity, causing water stress in the tissues of leaves.

After Katerji et al. (1997), a decrease in RWC indicates loss of turgor which occurs due to disturbances in the increase in the area of individual leaves, in other words in leaf expansion. The connection between the impact of salt on gas exchange in leaves and growth is not completely understood. Many experimental results indicate that gas exchange in leaves of plants remains unchanged under the influence of soil water potential, until it reaches a certain threshold value (Ritchie, 1981). Results of Shalhevet (1994) suggest that the expansion of leaves is the most affected by osmotic stress and that there was a linear relationship between transpiration and the synthesis of organic matter in different agroecological conditions. The slope of this function represents the efficiency of water utilization by plants (water use efficiency, WUE). More recently, stomatal traits have been proven to critically affect WUE. In absence of stress, it has been demonstrated that low stomatal density reduces transpirational water fluxes (Zhang et al., 2001) and improves water use efficiency (Masle et al., 2005).

Effects of Salinity on Vegetable Growth and Nutrients Uptake 175

NaCl increase concentrations of Na+ and Cl- and reduce concentrations of Ca2+, K+ and Mg2+ in many plant species (Bayuelo-Jimenez et al., 2003). In the presence of NaCl, the concentration of K+, Ca2+ and P in vegetative parts decreased and in pods and grains increased (Fig. 2A). Ratios between concentrations of essential cations is changed as well (Fig. 2B). It was found that deleterious effects of salinity on tomato biomass production can be ameliorated by an enhanced supply of calcium. Similarly to the effect on the uptake of macroelements, salt stress can exert stimulatory and inhibitory influence on the uptake of

Irrigation waters sometimes contain increased concentration of boron, which can lead to reduced yields of crops (Nable et al., 1997; Kastori et al., 2008). Numerous studies have been done in order to find suitable methods for early assessment of tolerance to excess boron and finding sources of tolerance to high concentrations of this element (Nable et al., 1997, Yau &

It is often considered that the use of fertilizers may aggravate problems that exist due to the presence of excessive amounts of salts in the soil. However, the lack of essential elements in accessible forms is a very common reason for poor productivity on such soils. When the saline soils are for the purpose of remediation washed with large quantities of water, some essential elements may concomitantly be washed away. Therefore, the application of

**5.1 Effect of excess salinity on nitrogen, phosphorus and potassium uptake and**

Under the conditions of salt stress, the uptake of nitrogen is often disrupted and numerous studies have shown that excess salts can reduce the accumulation of nitrogen in plants (Pardossi et al., 1999, Silveira et al., 2001, Wahid et al., 2004). Increase in uptake and

(Savvas & Lenz, 2000). There are authors who have attributed this reduction to the

water uptake (Lea-Cox & Syvertsen, 1993). The rate of nitrate uptake or interactions between NO3- and Cl- is associated with tolerance of examined plant species to salts. Kafkafi et al. (1992) found that tomato and melon varieties tolerant of salts have a higher flow rate of

Nitrogen fertilization on saline soils is often necessary because in such soils there is a lack of accessible nitrogen and also because losses of nitrogen due to leaching typical for nitrate form (Yin et al., 2007, Abdelgadir et al., 2010). In addition, rate of nitrification of ammonia is often significantly reduced due to the large direct toxic effects of Cl- and the total amount of

Level of salinity does not affect necessarily the overall uptake of nitrogen by plants which may continue to accumulate nitrogen in the presence of excess salts despite a reduction in yield of dry matter. With the increase in soil salinity, total removal of nitrogen through the yield often decreases. Reduction in nitrogen fertilizer use efficiency is primarily a result of reduction of plant growth rate rather than the reduction of nitrogen uptake

is accompanied by a reduction in the concentration of NO3- in eggplant

(Bar et al., 1997) and those who explain it by reduced

fertilizers in appropriate doses is necessary to attain higher yields.

and NO3-

salt on the activity of nitrifying bacteria (Stark & Firestone, 1995).

some trace elements (Grattan & Grieve, 1999).

Ryan, 2008; Brdar-Jokanovic et al., 2010).

**metabolism**

rate.

accumulation of Cl-

antagonism between Cl-

NO3- ions than more sensitive varieties.

#### **4. Accumulation of compatible osmolites increases vegetable tolerance to osmotic stress**

One of the ways plants can adapt to conditions of osmotic stress is the accumulation of salt ions, if these salts are isolated in individual cell compartments by which their involvement in metabolism is prevented. The ability to regulate the concentration of salts through compartimentation is an important aspect of tolerance to increased salt concentrations (Romero-Aranda et al., 2001). In the presence of salts plants often accumulate low molecular weight substances which are called compatible osmolites. These substances do not interfere with normal biochemical reactions in cells (Hasegawa et al., 2000, Ashraf & Foolad, 2007). Compatible osmolites are low molecular weight molecules such as proline and glycine betaine (Ghoulam et al., 2002, Ashraf & Foolad, 2007). It is believed that under conditions of stress, proline has a role in osmotic adjustment of cells, enzymes and membrane protection and also as a source of nitrogen for a moment when conditions of stress are over (Ashraf & Foolad, 2007). The role of glycine betaine is also in maintaining pH of the cells, cell detoxification and binding of free radicals. Conditions of salt stress also lead to the accumulation of the other nitrogen compounds such as amino acids, amides, proteins and polyamines, which is often correlated with tolerance to salt (Mansour, 2000). Another group of compatible osmolytes are carbohydrates, both simple sugars (glucose, fructose, sucrose, fruktani), and starch. Their most important roles, beside in osmotic adjustment, is carbon storage and neutralization of free radicals (Parida et al., 2002). A similar role is attributed to the polyols that may accumulate under conditions of salt stress as well (Bohnert et al., 1995).

Ionic status of plants is highly correlated with tolerance to salts so that it can serve as a selection criterion in breeding to help create genotypes more tolerant to excess salt (Ashraf & Khanum, 1997).

#### **5. Effect of excess salinity on mineral nutrition of plants**

Increased salt concentration in the vicinity of the root system can interfere with mineral nutrition of plants and limit vegetable yield due to salinity or osmotic value of the soil solution. Salinity affects nutrient availability to plants in many ways. It modifies binding, retention and transformation of nutrients in the soil and affects the uptake and/or absorption of nutrients by the root system due to antagonism of ions and reduced root growth. It disrupts the metabolism of nutrients in the plant, primarily through water stress, thus reducing the efficiency of utilization of nutrients. In the presence of increasing concentrations of salts some species-specific symptoms may be present, such as necrosis and burns of leaf edges due to the accumulation of Na+ and Cl ions (Wahome, 2001). The high concentration of ions can disrupt the structure and function of cell membranes. Mineral nutrition of plants depends on the activity of membrane transporters which participate in the transfer of ions from the soil into the plant and regulate their distribution within and between cells (Marschner, 1995; Tester & Davenport, 2003, Epstein & Bloom, 2005). Changes in membranes may finally lead to disturbances in chemical composition of cells and can therefore be displayed as symptoms of deficiency of some essential elements, similarly as it happens in the absence of salts (Grattan & Grieve, 1999).

High concentrations of NaCl act antagonistically to the uptake of the other nutrients, such as K+, Ca2+, N, P (Cramer et al., 1991, Grattan & Grieve, 1999). Increased concentrations of

One of the ways plants can adapt to conditions of osmotic stress is the accumulation of salt ions, if these salts are isolated in individual cell compartments by which their involvement in metabolism is prevented. The ability to regulate the concentration of salts through compartimentation is an important aspect of tolerance to increased salt concentrations (Romero-Aranda et al., 2001). In the presence of salts plants often accumulate low molecular weight substances which are called compatible osmolites. These substances do not interfere with normal biochemical reactions in cells (Hasegawa et al., 2000, Ashraf & Foolad, 2007). Compatible osmolites are low molecular weight molecules such as proline and glycine betaine (Ghoulam et al., 2002, Ashraf & Foolad, 2007). It is believed that under conditions of stress, proline has a role in osmotic adjustment of cells, enzymes and membrane protection and also as a source of nitrogen for a moment when conditions of stress are over (Ashraf & Foolad, 2007). The role of glycine betaine is also in maintaining pH of the cells, cell detoxification and binding of free radicals. Conditions of salt stress also lead to the accumulation of the other nitrogen compounds such as amino acids, amides, proteins and polyamines, which is often correlated with tolerance to salt (Mansour, 2000). Another group of compatible osmolytes are carbohydrates, both simple sugars (glucose, fructose, sucrose, fruktani), and starch. Their most important roles, beside in osmotic adjustment, is carbon storage and neutralization of free radicals (Parida et al., 2002). A similar role is attributed to the polyols that may accumulate under conditions of salt stress as well (Bohnert et al., 1995). Ionic status of plants is highly correlated with tolerance to salts so that it can serve as a selection criterion in breeding to help create genotypes more tolerant to excess salt (Ashraf

**4. Accumulation of compatible osmolites increases vegetable tolerance to**

**osmotic stress**

& Khanum, 1997).

**5. Effect of excess salinity on mineral nutrition of plants**

burns of leaf edges due to the accumulation of Na+ and Cl-

happens in the absence of salts (Grattan & Grieve, 1999).

Increased salt concentration in the vicinity of the root system can interfere with mineral nutrition of plants and limit vegetable yield due to salinity or osmotic value of the soil solution. Salinity affects nutrient availability to plants in many ways. It modifies binding, retention and transformation of nutrients in the soil and affects the uptake and/or absorption of nutrients by the root system due to antagonism of ions and reduced root growth. It disrupts the metabolism of nutrients in the plant, primarily through water stress, thus reducing the efficiency of utilization of nutrients. In the presence of increasing concentrations of salts some species-specific symptoms may be present, such as necrosis and

concentration of ions can disrupt the structure and function of cell membranes. Mineral nutrition of plants depends on the activity of membrane transporters which participate in the transfer of ions from the soil into the plant and regulate their distribution within and between cells (Marschner, 1995; Tester & Davenport, 2003, Epstein & Bloom, 2005). Changes in membranes may finally lead to disturbances in chemical composition of cells and can therefore be displayed as symptoms of deficiency of some essential elements, similarly as it

High concentrations of NaCl act antagonistically to the uptake of the other nutrients, such as K+, Ca2+, N, P (Cramer et al., 1991, Grattan & Grieve, 1999). Increased concentrations of

ions (Wahome, 2001). The high

NaCl increase concentrations of Na+ and Cl- and reduce concentrations of Ca2+, K+ and Mg2+ in many plant species (Bayuelo-Jimenez et al., 2003). In the presence of NaCl, the concentration of K+, Ca2+ and P in vegetative parts decreased and in pods and grains increased (Fig. 2A). Ratios between concentrations of essential cations is changed as well (Fig. 2B). It was found that deleterious effects of salinity on tomato biomass production can be ameliorated by an enhanced supply of calcium. Similarly to the effect on the uptake of macroelements, salt stress can exert stimulatory and inhibitory influence on the uptake of some trace elements (Grattan & Grieve, 1999).

Irrigation waters sometimes contain increased concentration of boron, which can lead to reduced yields of crops (Nable et al., 1997; Kastori et al., 2008). Numerous studies have been done in order to find suitable methods for early assessment of tolerance to excess boron and finding sources of tolerance to high concentrations of this element (Nable et al., 1997, Yau & Ryan, 2008; Brdar-Jokanovic et al., 2010).

It is often considered that the use of fertilizers may aggravate problems that exist due to the presence of excessive amounts of salts in the soil. However, the lack of essential elements in accessible forms is a very common reason for poor productivity on such soils. When the saline soils are for the purpose of remediation washed with large quantities of water, some essential elements may concomitantly be washed away. Therefore, the application of fertilizers in appropriate doses is necessary to attain higher yields.

#### **5.1 Effect of excess salinity on nitrogen, phosphorus and potassium uptake and metabolism**

Under the conditions of salt stress, the uptake of nitrogen is often disrupted and numerous studies have shown that excess salts can reduce the accumulation of nitrogen in plants (Pardossi et al., 1999, Silveira et al., 2001, Wahid et al., 2004). Increase in uptake and accumulation of Cl- is accompanied by a reduction in the concentration of NO3- in eggplant (Savvas & Lenz, 2000). There are authors who have attributed this reduction to the antagonism between Cl and NO3- (Bar et al., 1997) and those who explain it by reduced water uptake (Lea-Cox & Syvertsen, 1993). The rate of nitrate uptake or interactions between NO3- and Cl- is associated with tolerance of examined plant species to salts. Kafkafi et al. (1992) found that tomato and melon varieties tolerant of salts have a higher flow rate of NO3- ions than more sensitive varieties.

Nitrogen fertilization on saline soils is often necessary because in such soils there is a lack of accessible nitrogen and also because losses of nitrogen due to leaching typical for nitrate form (Yin et al., 2007, Abdelgadir et al., 2010). In addition, rate of nitrification of ammonia is often significantly reduced due to the large direct toxic effects of Cl- and the total amount of salt on the activity of nitrifying bacteria (Stark & Firestone, 1995).

Level of salinity does not affect necessarily the overall uptake of nitrogen by plants which may continue to accumulate nitrogen in the presence of excess salts despite a reduction in yield of dry matter. With the increase in soil salinity, total removal of nitrogen through the yield often decreases. Reduction in nitrogen fertilizer use efficiency is primarily a result of reduction of plant growth rate rather than the reduction of nitrogen uptake rate.

Effects of Salinity on Vegetable Growth and Nutrients Uptake 177

that cause water retention and the appearance of anaerobic conditions, plants are often chlorotic, which is symptom characteristic of nitrogen deficiency. Such plants require the application of high doses of fertilizers in order to neutralize the effect of water lodging.

Nitrogen fixing bacteria affect nitrogen nutrition as well. Due to the toxic effects of salts on rhizobium the metabolism of nodulating bacteria can drastically alter (Hua et al., 1982) and number and activity of root nodules may be reduced (Singleton et al., 1982). Graham & Parker (1964) found that the highest EC that can tolerate *Rhizobium* strain compatible with pea is of 4.5 dS m-1. On the basis of tolerance to salt concentration, Elsiddig & Elsheikh (1998) proposed the division of strains of bacteria from the genera *Rhizobium* and *Bradyrhizobium* in four groups: sensitive strains, 0-200 mM; moderately sensitive, 200-500 mM; tolerant, 500-800 mM; and highly tolerant, more than 800 mM. Such a classification should be considered with precaution, as a great influence on the overall tolerance to salts