Nutritional improvement of cereal crops to combat hidden hunger during the COVID-19 pandemic: Progress and prospects

Farmers, in the given geographical region, cultivate only a small set of crop varieties for a long period of time. Modern plant breeding programs also resulted in severe genetic bottleneck. As a consequence, reduction in genetic diversity is widespread among crop plants, and it is considered as a detrimental feature to the future farming process. This is because continuous use of same cultivars usually leads to at least (1) extensive existence of (as well as emergence of new) pest and diseases to the given crop species and (2) loss of landraces and wild species of the given crop plants (which is otherwise referred to as genetic erosion). Due to ever increasing population growth and continuous shrinking of farming lands, farmers are forced to cultivate crop plants under a wide range of latitudes and longitudes. This requires crop plants which can tolerate variations in light, temperature, water and nutrients besides occurrence of peculiar pest and diseases that challenge crop production in these environments. Conventional breeding approaches such as desirable phenotypic selection among the breeding materials have considerably contributed in genetic improvement of crops. However, only a few genetically improved lines are available to meet such challenges. The main limitations that prevent the further progress through conventional breeding methods are lack of adequate genetic/biochemical/molecular knowledge on expression of traits that are beneficial to the crop cultivation and production. Most of the agronomically and economically important traits are quantitative in nature and having complex inheritance. Thanks to the developments in nucleic acid characterisation and manipulation, it is now possible to genetically analyse and manipulate such quantitative traits using quantitative trait loci (QTL) mapping and marker-assisted selection (MAS). Thus, advances in molecular marker technologies have opened the door to new techniques for construction and screening of breeding populations, increase the efficiency of selection and accelerate the rates of genetic gain. By employing genetic and QTL mapping, a marker can either be located within the gene of interest or be linked to a gene determining a trait of interest. Consequently, MAS can be executed as a selection for a trait based on genotype using associated markers rather than the phenotype of the trait. This book is designed to describe the basics of genetic and QTL mapping using molecular markers and practicing MAS in crop plants with step-by-step procedures. In general, MAS scheme in genetic improvement of crop plants for the given trait involves (1) characterisation of germplasm for the trait of interest, (2) selection of extremely diverse parents, (3) development of mapping population, (4) selection of appropriate combinations of molecular markers and genotyping of parents and mapping population, (5) construction of genetic or linkage map, (6) phenotyping of mapping population for the selected trait, (7) QTL analysis by combining the data obtained from step 5 and 6, (8) fine mapping and validation of QTLs and (9) executing MAS for the target trait. Therefore, this first chapter of this book is keen to describe the leading vital step in MAS: characterisation of germplasm.

Previously, association mapping (AM) methodology was used to unravel genetic complications in animal science by measuring the complex traits for candidate and non-candidate genes. Nowadays, this statistical approach is widely used to clarify the complexity in plant breeding program-based genome-wide breeding strategies, marker development, and diversity analysis. This chapter is particularly focused on methodologies with limitations and provides an overview of AM models and software used up to now. Association or linkage disequilibrium mapping has become a very popular method for discovering candidate and non-candidate genes and confirmation of quantitative trait loci (QTL) on various parts of the genome and in marker-assisted selection for breeding. Previously, various QTL investigations were carried out for different plants exclusively by linkage mapping. To help to understand the basics of modern molecular genetic techniques, in this chapter we summarize previous studies done on different crops. AM offers high-resolution power when there is large genotypic diversity and low linkage disequilibrium (LD) for the germplasm being investigated. The benefits of AM, compared with traditional QTL mapping, include a relatively detailed mapping resolution and a far less time-consuming approach since no mapping populations need to be generated. The advancements in genotyping and computational techniques have encouraged the use of AM. AM provides a fascinating approach for genetic investigation of QTLs, due to its resolution and the possibility to study the various genomic areas at the same time without construction of mapping populations. In this chapter we also discuss the advantages and disadvantages of AM, especially in the dicotyledonous crops Fabaceae and Solanaceae, with various genome-size reproductive strategies (clonal vs. sexual), and statistical models. The main objective of this chapter is to highlight the uses of association genetics in major and minor crop species that have trouble being analyzed for dissection of complex traits by identification of the factor responsible for controlling the effect of trait. Graphical Abstract.

Technical advances and development in the market for genomic tools have facilitated access to whole-genome data across species. Building-up on the acquired knowledge of the genome sequences, large-scale genotyping has been optimized for broad use, so genotype information can be routinely used to predict genetic merit. Genomic selection (GS) refers to the use of aggregates of estimated marker effects as predictors which allow improved individual differentiation at young age. Realizable benefits of GS are influenced by several factors and vary in quantity and quality between species. General characteristics and challenges of GS in implementation and routine application are described, followed by an overview over the current status of its use, prospects and challenges in important animal species. Genetic gain for a particular trait can be enhanced by shortening of the generation interval, increased selection accuracy and increased selection intensity, with species- and breed-specific relevance of the determinants. Reliable predictions based on genetic marker effects require assembly of a reference for linking of phenotype and genotype data to allow estimation and regular re-estimation. Experiences from dairy breeding have shown that international collaboration can set the course for fast and successful implementation of innovative selection tools, so genomics may significantly impact the structures of future breeding and breeding programmes. Traits of great and increasing importance, which were difficult to improve in the conventional systems, could be emphasized, if continuous availability of high-quality phenotype data can be assured. Equally elaborate strategies for genotyping and phenotyping will allow tailored approaches to balance efficient animal production, sustainability, animal health and welfare in future.

Most of the economic traits considered in genetic improvement programs are of quantitative nature. They are genetically determined by many genes. To apply major genes or linked markers in gene- or marker-assisted selection program, they must first be identified in the genome. Mapping genomic regions for the economic traits is the first step to identify genes influencing traits of interest. This report gives the most comprehensive information on discovering quantitative traits loci (QTL) and their underlying genes for economic traits in chicken, in particular on chromosome 4 (GGA4), using up-to-date genomic approaches and bioinformatics tools. This work is based on several publications (Goraga et al. 2010, 2012; Nassar and Brockmann 2011, 2013; Nassar et al. 2012, 2013, 2015; Lyu et al. 2016, 2017) and other published QTL results in chicken QTL database (Chicken QTLdb). I had done this work in collaboration with Humboldt-Universitat zu Berlin, Germany, during the year 2010 to 2017. In brief, we mapped several genomic regions on 22 chromosomes affecting 24 traits. The majority of identified loci showed additive effects on several growth and body composition traits. The biggest effect on analysed traits was detected on the distal region of GGA4. The confidence interval of the QTL region on GGA4 harbours hundreds of genes. The final identification of genes and mutations will contribute to our understanding of the complex inheritance pattern of growth regulation, muscle development and fat deposition in chicken. Such information would support breeders in using this information for genetic improvement in breeding programs.

Various programs for genetic improvement in oil yield of the biofuel plant Jatropha curcas L. are currently in progress worldwide. In order to develop strategies for genetic improvement, it is important to estimate the degree of diversity at the genetic level among various genotypes of J. curcas. High-throughput sequencing of complexity-reduced nuclear genomic DNA of J. curcas coupled with computational analysis discovered 2,482 informative single nucleotide polymorphisms (SNPs). Genotyping of selective SNPs among 148 global collections of J. curcas lines and further diversity analysis through NTSYS-pc, DARwin and Structure 2.0 software revealed that a narrow level of genetic diversity existed among the indigenous genotypes as compared to the exotic genotypes of J. curcas. The level of marker informativeness along with distance-based and Bayesian clustering revealed grouping of the accession from Togo (Africa) with various Indian accessions at K = 4 and K = 5 values (where K represents the number of populations). The diverse accessions identified in the study will be of further use in genetic improvement of J. curcas through quantitative trait loci and association mapping.

In plants, most of the phenotypic variations are continuously distributed and could be considered as quantitative traits. The complexity of their genetic control is high because the involved genes are numerous, with usually minor effects and very sensitive to environment. The implicated loci are localised by two basic approaches, linkage mapping and association mapping, based on the use of genetic maps and sophisticated statistical analysis. Linkage mapping leads to the identification of small regions of genome but that could contain still several hundred genes. Identification of gene underlying the quantitative trait loci requires positional cloning or direct tests of promising candidates. Association mapping checks directly the relationship between each polymorphism and phenotypic trait variation in wild populations, but physical linkage and population structure are sources of false positives. Finally, validation that an individual gene is responsible for the quantitative trait needs to be performed by using genetic or functional complementation.Key Concepts:Quantitative traits follow continuous, unbroken quasi‐normal distributions whereas qualitative (mendelian) traits are discreetly distributed.Quantitative traits are controlled by several genes, with small additive, dominant or epistatic effects, and in interaction with the environment.A quantitative trait loci (QTL) is defined as an area of genome associated with an effect on a quantitative trait.The combination of alleles at the many genes involved in a quantitative trait leads to constitute the different phenotypes.QTL mapping relies on statistical linkage analysis among quantitative trait and genetic markers using a population that carries combinations of alleles derived from parental lines.Association mapping looks for association between a genetic marker and phenotype in unrelated individuals by exploiting historical recombination events and genetic diversity.Population structure is the presence of hidden subgroups in wild populations that appear because of relatedness and selection with an unequal distribution of alleles.Physical linkage and population structure are sources of linkage disequilibrium and might influence the genome‐wide association (GWA) mapping by creation of false marker‐trait association.Positional cloning of QTL involves the identification of closely linked recombination events requiring analysis of a large number of segregating progeny with molecular markers covering the critical region.Complete genome sequencing has greatly advanced the use of GWA mapping.

Introduction: Soil salinity poses a severe threat to rice production, resulting in stunted growth, leaf damage, and substantial yield losses. This study focuses on developing an early maturing seedling stage salinity tolerant rice variety by integrating conventional breeding methods with marker assisted breeding (MAB) approaches.Methods: Seedling-stage salinity tolerance Quantitative Trait Locus (QTL) “Saltol” from the salt-tolerant parent FL478 was introduced into the high-yielding but salt-sensitive rice variety ADT 45. This was achieved through a combination of conventional breeding and MAB. The breeding process involved rigorous selection, screening, and physiological parameter assessments.Results: KKL(R) 3 (KR 15066) identified as the top performing Recombinant Inbred Line (RIL), consistently demonstrating maximum mean grain yields under both salinity (3435.6 kg/ha) and normal (6421.8 kg/ha) conditions. In comparison to the early maturing, salt-tolerant national check variety CSR 10, KKL(R) 3 exhibited a substantial yield increase over 50%.Discussion: The notable improvement observed in KKL(R) 3 positions it as a promising variety for release, offering a reliable solution to maximize yields, ensure food security, and promote agricultural sustainability in both saline and non-saline environments. The study highlights the effectiveness of MAB in developing salt-tolerant rice varieties and emphasizes the significance of the Saltol QTL in enhancing seedling stage salinity tolerance. The potential release of KKL(R) 3 has the capacity to revolutionize rice production in salt affected regions, providing farmers with a reliable solution to maximize yields and contribute to food security while ensuring agricultural sustainability.

Crop production is negatively impacted by climate change, which may increase yield losses and reduce the output of crops that are subjected to harsh environmental conditions.Therefore, we need to develop climate-resilient crop varieties to cope with abiotic and biotic stresses. Plant breeding has successfully developed improved crop varieties by applying conventional tools and methodologies where plants are selected based on superior performances (phenotypes). Numerous external environmental factors can affect plant phenotypes, which reduces the accuracy of selection based solely on phenotypic expression. Furthermore, it is time-consuming, and challenging to investigate complex traits like abiotic and biotic stress tolerance/resistance. To mitigate this issue, genomics equips plant breeders with cutting-edge molecular techniques for genome-wide study and makes genotype-phenotype analysis possible. This facilitates the precise and efficient development of climate-resilient crop varieties using genomic approaches, like ‘genomic selection’, ‘marker-assisted selection’ (MAS), ‘marker-assisted backcrossing’ (MABC), ‘quantitative trait loci’ (QTL) mapping and ‘genome editing’. These high-throughput modern techniques help to identify important traits, provide better insight into genetic diversity, and significantly accelerate breeding programs. Moreover, revolutionary technology like ‘CRISPR-Cas9’-mediated genome editing allows precise gene editing, accelerating the breeding process significantly. ‘High-throughput phenotyping’ (HTP), ‘genomic selection’, and MAS help to select specific traits that are responsible for enhanced crop production, stress tolerance, and improved disease resistance. Such molecular tools are invaluable for transferring complex traits affected by various environmental conditions. Ensuring food security and addressing the challenges of climate change, the integration of advanced molecular tools with conventional breeding is essential to produce climate-resilient crops.

New Technologies, Tools and Approaches for Improving Crop Breeding

Agriculture production is directly dependent on climate change and weather. Possible changes in temperature, precipitation and CO2 concentration are expected to significantly impact crop growth and ultimately we lose our crop productivity and indirectly affect the sustainable food availability issue. The overall impact of climate change on worldwide food production is considered to be low to moderate with successful adaptation and adequate irrigation. Climate change has a serious impact on the availability of various resources on the earth especially water, which sustains life on this planet. The global food security situation and outlook remains delicately imbalanced amid surplus food production and the prevalence of hunger, due to the complex interplay of social, economic, and ecological factors that mediate food security outcomes at various human and institutional scales. Weather aberration poses complex challenges in terms of increased variability and risk for food producers and the energy and water sectors. Changes in the biosphere, biodiversity and natural resources are adversely affecting human health and quality of life. Throughout the 21st century, India is projected to experience warming above global level. India will also begin to experience more seasonal variation in temperature with more warming in the winters than summers. Longevity of heat waves across India has extended in recent years with warmer night temperatures and hotter days, and this trend is expected to continue. Strategic research priorities are outlined for a range of sectors that underpin global food security, including: agriculture, ecosystem services from agriculture, climate change, international trade, water management solutions, the water-energy-food security nexus, service delivery to smallholders and women farmers, and better governance models and regional priority setting. There is a need to look beyond agriculture and invest in affordable and suitable farm technologies if the problem of food insecurity is to be addressed in a sustainable manner. Introduction Globally, agriculture is one of the most vulnerable sectors to climate change. This vulnerability is relatively higher in India in view of the large population depending on agriculture and poor coping capabilities of small and marginal farmers. Impacts of climate change pose a serious threat to food security. “Food security exists when all people, at all times, have physical and economic access to sufficient, safe and nutritious food that meets their dietary needs and food preferences for an active and healthy life” (World Food Summit, 1996). This definition gives rise to four dimensions of food security: availability of food, accessibility (economically and physically), utilization (the way it is used and assimilated by the human body) and stability of these three dimensions. According to the United Nations, in 2015, there are still 836 million people in the world living in extreme poverty (less than USD1.25/day) (UN, 2015). And according to the International Fund for Agricultural Development (IFAD), at least 70 percent of the very poor live in rural areas, most of them depending partly (or completely) on agriculture for their livelihoods. It is estimated that 500 million smallholder farms in the developing world are supporting almost 2 billion people, and in Asia and sub-Saharan Africa these small farms produce about 80 percent of the food consumed. Climate change threatens to reverse the progress made so far in the fight against hunger and malnutrition. As highlighted by the assessment report of the Intergovernmental Panel on Climate change (IPCC), climate change augments and intensifies risks to food security for the most vulnerable countries and populations. Few of the major risks induced by climate change, as identified by IPCC have direct consequences for food security (IPCC, 2007). These are mainly to loss of rural livelihoods and income, loss of marine and coastal ecosystems, livelihoods loss of terrestrial and inland water ecosystems and food insecurity (breakdown of food systems). Rural farmers, whose livelihood depends on the use of natural resources, are likely to bear the brunt of adverse impacts. Most of the crop simulation model runs and experiments under elevated temperature and carbon dioxide indicate that by 2030, a 3-7% decline in the yield of principal cereal crops like rice and wheat is likely in India by adoption of current production technologies. Global warming impacts growth, reproduction and yields of food and horticulture crops, increases crop water requirement, causes more soil erosion, increases thermal stress on animals leading to decreased milk yields and change the distribution and breeding season of fisheries. Fast changing climatic conditions, shrinking land, water and other natural resources with rapid growing population around the globe has put many challenges before us (Mukherjee, 2014). Food is going to be second most challenging issue for mankind in time to come. India will also begin to experience more seasonal variation in temperature with more warming in the winters than summers (Christensen et al., 2007). Climate change is posing a great threat to agriculture and food security in India and it's subcontinent. Water is the most critical agricultural input in India, as 55% of the total cultivated areas do not have irrigation facilities. Currently we are able to secure food supplies under these varying conditions. Under the threat of climate variability, our food grain production system becomes quite comfortable and easily accessible for local people. India's food grain production is estimated to rise 2 per cent in 2020-21 crop years to an all-time high of 303.34 million tonnes on better output of rice, wheat, pulse and coarse cereals amid good monsoon rains last year. In the 2019-20 crop year, the country's food grain output (comprising wheat, rice, pulses and coarse cereals) stood at a record 297.5 million tonnes (MT). Releasing the second advance estimates for 2020-21 crop year, the agriculture ministry said foodgrain production is projected at a record 303.34 MT. As per the data, rice production is pegged at record 120.32 MT as against 118.87 MT in the previous year. Wheat production is estimated to rise to a record 109.24 MT in 2020-21 from 107.86 MT in the previous year, while output of coarse cereals is likely to increase to 49.36 MT from 47.75 MT. Pulses output is seen at 24.42 MT, up from 23.03 MT in 2019-20 crop year. In the non-foodgrain category, the production of oilseeds is estimated at 37.31 MT in 2020-21 as against 33.22 MT in the previous year. Sugarcane production is pegged at 397.66 MT from 370.50 MT in the previous year, while cotton output is expected to be higher at 36.54 million bales (170 kg each) from 36.07. This production figure seem to be sufficient for current population, but we need to improve more and more with vertical farming and advance agronomic and crop improvement tools for future burgeoning population figure under the milieu of climate change issue. Our rural mass and tribal people have very limited resources and they sometime complete depend on forest microhabitat. To order to ensure food and nutritional security for growing population, a new strategy needs to be initiated for growing of crops in changing climatic condition. The country has a large pool of underutilized or underexploited fruit or cereals crops which have enormous potential for contributing to food security, nutrition, health, ecosystem sustainability under the changing climatic conditions, since they require little input, as they have inherent capabilities to withstand biotic and abiotic stress. Apart from the impacts on agronomic conditions of crop productions, climate change also affects the economy, food systems and wellbeing of the consumers (Abbade, 2017). Crop nutritional quality become very challenging, as we noticed that, zinc and iron deficiency is a serious global health problem in humans depending on cereal-diet and is largely prevalent in low-income countries like Sub-Saharan Africa, and South and South-east Asia. We report inefficiency of modern-bred cultivars of rice and wheat to sequester those essential nutrients in grains as the reason for such deficiency and prevalence (Debnath et al., 2021). Keeping in mind the crop yield and nutritional quality become very daunting task to our food security issue and this can overcome with the proper and time bound research in cognizance with the environment. Threat and challenges In recent years, climate change has become a debatable issue worldwide. South Asia will be one of the most adversely affected regions in terms of impacts of climate change on agricultural yield, economic activity and trading policies. Addressing climate change is central for global future food security and poverty alleviation. The approach would need to implement strategies linked with developmental plans to enhance its adaptive capacity in terms of climate resilience and mitigation. Over time, there has been a visible shift in the global climate change initiative towards adaptation. Adaptation can complement mitigation as a cost-effective strategy to reduce climate change risks. The impact of climate change is projected to have different effects across societies and countries. Mitigation and adaptation actions can, if appropriately designed, advance sustainable development and equity both within and across countries and between generations. One approach to balancing the attention on adaptation and mitigation strategies is to compare the costs and benefits of both the strategies. The most imminent change is the increase in the atmospheric temperatures due to increase levels of GHGs (Green House Gases) i.e. carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O) and chlorofluorocarbons (CFCs) etc into the atmosphere. The global mean annual temperatures at the end of the 20th

In Sub-Saharan Africa (SSA), both crop production and the hidden hunger index (HHI, a combination of zinc, iron, and vitamin A deficiency), continue to be worse than the rest of the world. Currently, 31 out of 36 countries of SSA show the highest HHI. At the same time, several studies show climate change as a major constraint to agriculture productivity and a significant threat to SSA food security without significant action regarding adaptation. The food security of SSA is dependent on a few major crops, with many of them providing largely only an energy source in the diet. To address this, crop diversification and climate-resilient crops that have adaptation to climate change can be used and one route toward this is promoting the cultivation of African orphan (neglected or underutilized) crops. These crops, particularly legumes, have the potential to improve food and nutrition security in SSA due to their cultural linkage with the regional food habits of the communities, nutritionally rich food, untapped genetic diversity, and adaptation to harsh climate conditions and poor marginal soils. Despite the wide distribution of orphan legumes across the landscape of SSA, these important crop species are characterized by low yield and decreasing utilization due in part to a lack of improved varieties and a lack of adequate research attention. Genomic-assisted breeding (GAB) can contribute to developing improved varieties that yield more, have improved resilience, and high nutritional value. The availability of large and diverse collections of germplasm is an essential resource for crop improvement. In the Genetic Resources Center of the International Institute of Tropical Agriculture, the collections of orphan legumes, particularly the Bambara groundnut, African yambean, and Kersting's groundnut, have been characterized and evaluated for their key traits, and new collections are being undertaken to fill gaps and to widen the genetic diversity available to underpin breeding that can be further utilized with GAB tools to develop faster and cost-effective climate-resilient cultivars with a high nutrition value for SSA farmers. However, a greater investment of resources is required for applying modern breeding to orphan legume crops if their full potential is to be realized.

Genetic dissection of grain weight in bread wheat was undertaken through both genome-wide quantitative trait locus (QTL) interval mapping and association mapping. QTL interval mapping involved preparation of a framework linkage map consisting of 294 loci {194 simple sequence repeats (SSRs), 86 amplified fragment length polymorphisms (AFLPs) and 14 selective amplifications of microsatellite polymorphic loci (SAMPL)} using a bi-parental recombinant inbred line (RIL) mapping population derived from Rye Selection111 × Chinese Spring. Using the genotypic data and phenotypic data on grain weight (GW) of RILs collected over six environments, genome-wide single locus QTL analysis was conducted to identify main effect QTL. This led to identification of as many as ten QTL including four major QTL (three QTL were stable), each contributing >20% phenotypic variation (PV) for GW. The above study was supplemented with association mapping, which allowed identification of 11 new markers in the genomic regions that were not reported earlier to harbour any QTL for GW. It also allowed identification of closely linked markers for six known QTL, and validation of eight QTL reported earlier. The QTL identified through QTL interval mapping and association mapping may prove useful in marker-assisted selection (MAS) for the development of cultivars with high GW in bread wheat.

At least 75% of the world’s grain production comes from the three most important cereal crops: rice (Oryza sativa), wheat (Triticum aestivum), and maize (Zea mays). However, abiotic stressors such as heavy metal toxicity, salinity, low temperatures, and drought are all significant hazards to the growth and development of these grains. Quantitative trait locus (QTL) discovery and mapping have enhanced agricultural production and output by enabling plant breeders to better comprehend abiotic stress tolerance processes in cereals. Molecular markers and stable QTL are important for molecular breeding and candidate gene discovery, which may be utilized in transgenic or molecular introgression. Researchers can now study synteny between rice, maize, and wheat to gain a better understanding of the relationships between the QTL or genes that are important for a particular stress adaptation and phenotypic improvement in these cereals from analyzing reports on QTL and candidate genes. An overview of constitutive QTL, adaptive QTL, and significant stable multi-environment and multi-trait QTL is provided in this article as a solid framework for use and knowledge in genetic enhancement. Several QTL, such as DRO1 and Saltol, and other significant success cases are discussed in this review. We have highlighted techniques and advancements for abiotic stress tolerance breeding programs in cereals, the challenges encountered in introgressing beneficial QTL using traditional breeding techniques such as mutation breeding and marker-assisted selection (MAS), and the in roads made by new breeding methods such as genome-wide association studies (GWASs), the clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 system, and meta-QTL (MQTL) analysis. A combination of these conventional and modern breeding approaches can be used to apply the QTL and candidate gene information in genetic improvement of cereals against abiotic stresses.

Net form net blotch (NFNB) caused by Pyrenophora teres f. sp. teres (Ptt) is an emerging barley disease in several countries. It causes severe yield and quality losses due to infection of leaves, kernels, and stems. Owing to the inherent genetic diversity of Ptt, the incorporation of qualitative and quantitative resistance is important to obtain barley cultivars with durable resistance to NFNB. For this purpose, an association mapping panel named HI-AM (high-input association mapping panel) was screened for resistance to NFNB at the seedling stage with two virulent Moroccan Ptt isolates (Ptt40–3 and Ptt45-3) under controlled conditions, and at the adult plant stage at four hot spot locations in Morocco during different cropping seasons (2016–17 and 2017–18).​ Genome-wide association mapping (GWAM) was conducted using 13,182 PAV (presence or absence variations) and 6,311 single-nucleotide polymorphism (SNP) markers for mapping of seedling and adult plant resistance quantitative trait loci (QTLs). GWAM analysis revealed 19 QTLs for the seedling stage and 35 QTLs for the adult plant stage resistance. Of the 54 QTLs detected, 38 QTLs from this study overlapped with previously reported QTLs, while 16 QTLs were novel. Furthermore, two common seedling stage resistance and six common adult plant stage QTLs were detected, while only three QTLs overlapped for both growth stages. Seedling stage QTLs together explained 40% of the genetic variance for seedling resistance to Ptt isolate Ptt40-3, and 69% for isolate Ptt45-3, whereas the genetic variance of the QTLs for adult plant stage resistance ranged from 35% to 85%. This panel was previously used for other GWAM studies, including resistance to spot blotch and stripe rust of barley. By mapping of significant markers for three different diseases on the Morex genome version 3.0, we have identified 13 common QTLs associated with resistance to net blotch and spot blotch, and three QTLs associated with resistance to all three diseases. The identification and introgression of common QTLs conditioning resistance to three pathogens could help in attaining durable disease-resistance in barley in North Africa.

Lepidium campestre (L.) or field cress is a multifaceted oilseed plant, which is not yet domesticated. Moreover, the molecular and genetic mechanisms underlying the domestication traits of field cress remain largely elusive. The overarching goal of this study is to identify quantitative trait loci (QTL) that are fundamental for domestication of field cress. Mapping and dissecting quantitative trait variation may provide important insights into genomic trajectories underlying field cress domestication. We used 7624 single nucleotide polymorphism (SNP) markers for QTL mapping in 428 F2 interspecific hybrid individuals, while field phenotyping was conducted in F2:3 segregating families. We applied multiple QTL mapping algorithms to detect and estimate the QTL effects for seven important domestication traits of field cress. Verification of pod shattering across sites revealed that the non-shattering lines declined drastically whereas the shattering lines increased sharply, possibly due to inbreeding followed by selection events. In total, 1461 of the 7624 SNP loci were mapped to eight linkage groups (LGs), spanning 571.9 cM map length. We identified 27 QTL across all LGs of field cress genome, which captured medium to high heritability, implying that genomics-assisted selection could deliver domesticated lines in field cress breeding. The use of high throughput genotyping can accelerate the process of domestication in novel crop species. This is the first QTL mapping analysis in the field cress genome that may lay a foundational framework for positional or functional QTL cloning, introgression as well as genomics-assisted breeding in field cress domestication.