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Preliminary review of literature
A preliminary review has been compiled to cover on field effects of climate change and agronomical responses to irrigation methods. The literature was reviewed in association mapping studies of durum wheat and for dissection of Global Warming traits. QTL analysis studies for agronomical traits was also reviewed. The literature reviews also covers the current status of research and agriculture status of Mauritania and Senegal. We presented also the material and methods to be used in this study.
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1. On field effects of Climate Change
The climate change can increase variability and change the seasonality of rainfall, reduce soil moisture, change the dynamics of pests, diseases and weeds, increased heat shock/stress, reduced grain quality or nutrient content. The higher temperatures induce also earlier or extended ripening on the plant.
Climate change is projected to have a significant impact on temperature and precipitation profiles in the Mediterranean basin. The incidence and severity of drought will become commonplace and this will reduce the productivity of rain-fed crops such as durum wheat. The major environmental constraints limiting the production of durum wheat in this region are drought and temperature extremes with productivity ranging from 06 t/ha (Nachit and Elouafi, 2004). Changes in total seasonal precipitation and its pattern of variability are both important, and the occurrence of moisture stress during flowering, pollination, and grain-filling is harmful to wheat. Drought at the tillering–booting developmental stages has had a negative impact on durum wheat production (Belaid et al., 2005). Furthermore, crop duration has been shortened by almost one month since 1970 in some areas of southern Morocco. Warmer and drier winters have also exacerbated the effect of some diseases and insects which target wheat and are major biotic constraints on production (A Yahyaoui, personal communication).
2. Agronomical responses to irrigation methods
The relationships between crop yields and water use are complicated. Yield may depend on when water is applied or on the amount. Information on optimal scheduling of limited amounts of water to maximize yields of high quality crops is essential if irrigation water is to be used most efficiently (Al-Kaisi et al., 1997).
The various crop development stages possess different sensitivities to moisture stress (FAO, 1979; English and Nakamura, 1989; Ghahraman and Sepaskhah, 1997). Timing, duration and the degree of water stress all affect yield.
Other studies have reported that the relationship between yield and water consumption, including irrigation, is not linear (Yuan et al., 1992). The results of a study showed that crop yields initially improved with increased water consumption, but that beyond a certain water use level yields decreased over irrigation reduced winter-wheat production. (FAO, 2002).
The simulated results showed that a single irrigation in wet years, two irrigations in normal years and three in dry years produced maximum profits. The timing of the irrigations would be: at jointing to booting for the single irrigation, at jointing and heading to milky filling for the two irrigations; and before over wintering, jointing, and heading to milky filling for the three irrigations. (FAO, 2002).
Water deficits may also affect crop management and production other than the direct effect on plant growth. The efficacy of many herbicides and other pesticides depends on soil moisture. Plants under moisture stress may not respond to foliar applied chemicals, or in some cases, may be damaged by chemical burns. Nutrient utilization and fertilization practices are influenced by the moisture status of the crop plants. Application of pesticides must be scheduled according to irrigation applications or to moisture stress in the crop.(UF/IFAS, 2008)
3. Association Mapping studies of durum wheat
A collection of 134 durum wheat accessions, representative of the major gene pools, was assembled and characterized with 70 SSRs for genetic diversity and level of long-rangelinkage disequilibrium (LD). Results evidenced the presence of a structured diversity and high level of LD (M. Maccaferri et al., 2005).
A collection of 164 elite durum wheat accessions suitable for association mapping has been tested for leaf rust response at the seedling stage and under field conditions. The collection has been profiled with 225 simple sequence repeat (SSR) loci of known map position and a PCR assay targeting Ppd-A1. Associations showing highly consistent experiment-wise significances across leaf rust isolates and field trials were mainly detected for the 7BL distal chromosome region and for two chr. regions located in chrs. 2A and 2B. Additionally,isolate specific associations and/or associations with smaller effects in the field trials were identified in most of the chromosomes(M. Maccaferri et al., 2009).
The genome location of a resistance gene to the stem rust Sr13 was determined in four tet-raploid wheat (T. turgidum ssp. durum) mapping populations involving the TTKSK resistant varieties Kronos, Kofa, Medora and Sceptre. Results showed that resistance was linked to common molecular markers in all four populations, suggesting that these durum lines carry the same resistance gene. Based on its chromosome location and infection types against different races of stem rust, this gene is postulated to be Sr13. Sr13 was mapped within a1.2–2.8 cM interval (depending on the mapping population) between EST markers CD92604 and BE471213, which corresponds to a 285-kb region in rice chromosome 2, and a 3.1-Mb region in Brachypodium chromosome 3. (K. Simons et al., 2010).
Association studies were effective for identifying markers associated with host plant resistance to rust and powdery mildew,as well as Grain Yield with five sets of historical breeding wheat germplasm (Crossa et al.2007; Terraciano et al.2013).
For the mining of allel that contribute to the tolerance of abiotique stresses, a germplasm collection of 189 elite durum lines was tested across 15 environnements at different regime of water. Association mapping studies with 186 DNA markers identify many of them linked to alleles enhancing adaptation to water stress.(Maccaferi et al, 2011).
4. Association Mapping studies for dissection of Global Warming traits
The creation of suitable mapping populations and the development of molecular markers have enabled linkage studies in wheat and many QTLs have been identified for yield under drought environments (Varshney et al., 2006).
The coupling of new genomic tools, technologies, and resources with genetic approaches is essential to underpin wheat breeding through marker-assisted selection and hence mitigate climate change. Many traits relating to the plant’s response and adaptation to drought are complex and multigenic, and quantitative genetics coupled with genomic technologies have the potential to dissect complex genetic traits and to identify regulatory loci, genes and networks.
Mapping populations have been developed in durum wheat for the study of biotic and abiotic stresses (Blanco et al., 1998; Nachit et al., 2001; Nachit and Elouafi, 2004).
Loci for yield, yield components, heading date, plant height, and physiological and developmental traits under drought have also been established in mapping populations (Maccaferri et al., 2008;DZ Habash et al., unpublished data).
5. QTL analysis studies for agronomical traits
The genetic basis of grain yield (GY), heading date (HD), and plant height (PH) was investigated in a durum wheat population of 249 recombinant inbred lines evaluated in 16 environments. Among the 16 quantitative trait loci (QTL) that affected GY, two major QTL on chromosomes 2BL and 3BS showed significant effects in 8 and 7 environments. QTL specific for PH were identified on chromosomes 1BS, 3AL, and 7AS. Additionally, three major QTL for HD on chromosomes 2AS, 2BL, and 7BS showed limited or no effects on GY. For both PH and GY, notable epistasis between the chromosome 2BL and 3BS QTL was detected across several environments (Maccaferi et al., 2007).
Besides some minor QTLs, one major QTL explaining both reduction of disease severity in the field and increased latency period was found on the long arm of chromosome 7B (Marone et al.,2009).Nine QTL for resistance to stem rust were identified on chromosomes 1AL, 2AS, 3BS, 4BL,5BL, 6AL 7A, 7AL and 7BL (Nachit et al., 2012).
6. Current status of research and agriculture status
- In Senegal
Studies conducted in the 70 and 80 have shown the potential to lead the wheat in particular, in the Senegal River Valley (VFS) but there has been no transfer of results. Analyzing the situation, ISRA has undertaken in recent years, work on wheat and identified promising productive varieties for agro-climatic conditions of the VFS.
According to Dr. Madiama Cissé, a researcher at the ISRA, the Senegal River Valley has huge potential and with the political willing of the state, Senegal will be a major producer of wheat.
A research program was conducted on ten hectares divided between the experimental station Fanaye, located 160 miles from St. Louis, and Ndiole. These ten hectares were used to assess the plant material that comes from Morocco and we found suitable for the cold season and other varieties of Mexico that are being evaluated in order to increase the packet. Today we have over 75 varieties under observation at Fanaye and indicated for intensive cultivation; we will be able to get out a few that are adapted to the Valley. There is also a quarantine which were selected for their temperature tolerance.
Technically, the wheat crop is possible. Water is available in the Valley, as this area has not only water resources, but the agro-climatic conditions are very favorable.
Thus, in light of the available results, lines of progress is possible by optimizing production techniques to terms should improve the performance of wheat under the conditions of the Senegal River Valley. These performances are conditioned by:
- Good timing of crop calendar
- Improved fashion and seeding
- The optimization of nitrogen fertilizer, phosphate and potassium
- The weed management
- Control of pest pressure (pests and diseases)
- Optimal water management
- Place the wheat in crop rotations
- In Mauritania
AOAD (Arab Organization for Agricultural deveveloppement) conducts research for the production of wheat in the experimental stage in some areas of the country through the provision of experts to test the degree of adaptation of some varieties of wheat in the Mauritania’s environment.
Salem Merrakchi, the agricultural engineer who oversees the cultivation of wheat, says that good results are expected in the perimeters have met the technical processes. He says to expect a production of over 3,840 tons of wheat on 1,882 acres, but stresses that some regions have proven to be inadequate for this speculation.
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Recall that the experience of growing wheat introduced in Mauritania, there are three years, has allowed the use of 6,000 ha in irrigated area and 10,000 ha in rain-fed area with profitability improving season after season.
Dr. Walid Al Zaki Yamani, a researcher in the wheat industry and expert AOAD in improving the productivity of wheat cultivation, noted that four experienced variety in Mauritania have a record productivity. Furthermore 29 speculation wheat were tested in four seasons to determine which is best suited to the Mauritanian conditions. Following the results, Mauritania is a fertile land suitable for the cultivation of this species, whether in the area irrigated or rain-fed agriculture.
7. Material and methods
- Phenotypic characterization
In this study the germplasm is a core collection of 380 durum wheat accessions (elite, advanced, wild relatives, and landraces) selected from the ICARDA durum breeding program. The material will be accurately phenotyped for their response to abiotic stresses (drought and heat) and WUE (Water Use Efficiency) under a short cycle.
The phenotyping will be conducted along the Senegal River at national experimental stations in Mauritania (Kaedi) and Senegal (Fanaye) were wheat planting will always be performed on lands previously sown with rice to provide indications about wheat-rice crop rotation.
We will use the augmented design to control error with 4 checks completely repeated in each of the19 blocks that will accommodate the genotype in a small plot 2.5mx 6 rows.
We will record the agronomical responses to short cycle and high temperatures and under various water regimes by annotating on-field data (germination, flowering time, plant height, lodging occurrence of disease and pests) and post-harvest data (yield and thousand kernels weight).
Screening for WUE will be conducted in the irrigated trials by providing two water quantities throughout the growing season: ideal amount (500 mm) and sub-ideal (250 mm) and then phenotypic values will be recorded.
- Genotypic characterization
Leaves from this above core collections are collected after growing the 380 lines in the green house. DNA extraction will be effected for the further genotyping.
First an approximately 50 PCR-based markers associated with “drought” traits in wheat will be selected and used in screening the ICARDA core collection to provide a first glimpse at the useful stress tolerance alleles embedded within this collection.
In the second time the germplasm will be deeply genotyped with 25,000 markers SNP (Simple Nucleotide Polymorphism) using the AXIOM (Affimetrix) platform available commercially at INRA (Clermont Ferrand).
- Genetic Studies and statistical analysis
We will use GWAS that use the genotypic data in combination with the phenotypic performances to identify the genomic regions and the specific SNP/alleles associated with the response to abiotic stresses.
From these associations, the genomic estimate of breeding value (GEBV) can be calculated. This GEBV will allow to design targeted crosses and to merge all the useful alleles found by GWAS in single cultivars.
Further, the SNPs found to be associated with the positive traits will be converted into readily available PCR-based assays through the KASPar technology. These assays will be use in further studies using MAS (Marker Assisted Selection) to tag germplasm with useful alleles of interest.
To perform GWAS and GWS (Genome Wide Selection) we need to apply statistical models. In this study we will use a specific software (STRUCTURE, Pritchard et al.2000; TASSEL) in combination with Linear Mixed model witch take on account population structure and genetic relatedness and reduce the rate of false positives.
We will use R statistic witch is a free and easily software where all statistical commands will be ran.
ANOVA table, chi-square, t-test, F-value, P-value and others statistical tools will allow us to identify differences between treatments and all what we need to know in this study.
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