Genetics of yield, abiotic stress tolerance and biofortification in wheat (Triticum aestivum L.)

A review of the available literature on genetics of yield and its component traits, tolerance to abiotic stresses and biofortification should prove useful for future research in wheat in the genomics era. The work reviewed in this article mainly covers the available information on genetics of some important quantitative traits including yield and its components, tolerance to abiotic stresses (heat, drought, salinity and pre-harvest sprouting = PHS) and biofortification (Fe/Zn and phytate contents with HarvestPlus Program) in wheat. Major emphasis is laid on the recent literature on QTL interval mapping and genome-wide association studies, giving lists of known QTL and marker-trait associations. Candidate genes for different traits and the cloned and characterized genes for yield traits along with the molecular mechanism are also described. For each trait, an account of the present status of marker-assisted selection has also been included. The details of available results have largely been presented in the form of tables; some of these tables are included as supplementary files.

Mapping of QTLs Associated with Yield and Yield Related Traits in Durum Wheat (Triticum durum Desf.) Under Irrigated and Drought Conditions

Global durum wheat consumption (Triticum durum Desf.) is ahead of its production. One reason for this is abiotic stress, e.g., drought. Breeding for resistance to drought is complicated by the lack of fast, reproducible screening techniques and the inability to routinely create defined and repeatable water stress conditions. Here, we report the first analysis of dissection of yield and yield-related traits in durum wheat in Pakistan, seeking to elucidate the genetic components of yield and agronomic traits. Analysis of several traits revealed a total of 221 (160 with logarithm of odds (LOD) > 2 ≤ 3 and 61 with LOD > 3) quantitative trait loci (QTLs) distributed on all fourteen durum wheat chromosomes, of which 109 (78 with LOD > 2 ≤ 3 and 31 with LOD > 3) were observed in 2016-17 (S1) and 112 (82 with LOD > 2 ≤ 3 and 30 with LOD > 3) were observed in 2017-18 (S2). Allelic profiles of yield QTLs on chromosome 2A and 7B indicate that allele A of Xgwm895 and allele B of Xbarc276 can enhance the Yd up to 6.16% in control and 5.27% under drought. Moreover, if combined, a yield gain of up to 11% would be possible.

RGB Vegetation Indices, NDVI, and Biomass as Indicators to Evaluate C3 and C4 Turfgrass under Different Water Conditions

Grasslands have a natural capacity to decrease air pollution and a positive impact on human life. However, their maintenance requires adequate irrigation, which is difficult to apply in many regions where drought and high temperatures are frequent. Therefore, the selection of grass species more tolerant to a lack of irrigation is a fundamental criterion for green space planification. This study compared responses to deficit irrigation of different turfgrass mixtures: a C4 turfgrass mixture, Cynodon dactylon-Brachypodium distachyon (A), a C4 turfgrass mixture, Buchloe dactyloides-Brachypodium distachyon (B), and a standard C3 mixture formed by Lolium perenne-Festuca arundinacea-Poa pratensis (C). Three different irrigation regimes were assayed, full irrigated to 100% (FI-100), deficit irrigated to 75% (DI-75), and deficit irrigated to 50% (DI-50) of container capacity. Biomass, normalized difference vegetation index (NDVI), green area (GA), and greener area (GGA) vegetation indices were measured. Irrigation significantly affected the NDVI, biomass, GA, and GGA. The most severe condition in terms of decreasing biomass and vegetation indices was DI-50. Both mixtures (A) and (B) exhibited higher biomass, NDVI, GA, and GGA than the standard under deficit irrigation. This study highlights the superiority of (A) mixture under deficit irrigation, which showed similar values of biomass and vegetation indices under full irrigated and deficit irrigated (DI-75) container capacities.

Effect of allele combinations at Ppd-1 loci on durum wheat grain filling at contrasting latitudes

Flowering time is the most critical developmental stage in wheat, as it determines environmental conditions during grain filling. Thirty-five spring durum genotypes carrying all known allele variants at Ppd-1 loci were evaluated in fully irrigated field experiments for three years at latitudes of 41°N (Spain), 27°N (northern Mexico) and 19°N (southern Mexico). Relationships between weight of central grains of main spikes (W) and thermal time from flowering to maturity were described by a logistic equation. Differences in flowering time between the allele combination causing the earliest (GS100/Ppd-B1a) and the latest (Ppd-A1b/Ppd-B1a) flowering were 7, 20 and 18 days in Spain, northern Mexico and southern Mexico, respectively. Flowering delay drastically reduced the mean grain filling rate (R) and W at all sites. At autumn-sowing sites, an increase of 1°C in mean temperature during the first half of the grain filling period decreased W by 5.2 mg per grain. At these sites, W was strongly dependent on R. At the spring-sowing site (southern Mexico), W depended on both R and grain filling duration. Our results suggest that incorporating the allele combinations GS100/Ppd-B1a and GS105/Ppd-B1a (alleles conferring photoperiod insensitivity) in newly released varieties can reduce the negative effects of climate change on grain filling at the studied latitudes.

Photosynthetic Metabolism under Stressful Growth Conditions as a Bases for Crop Breeding and Yield Improvement

Increased periods of water shortage and higher temperatures, together with a reduction in nutrient availability, have been proposed as major factors that negatively impact plant development. Photosynthetic CO2 assimilation is the basis of crop production for animal and human food, and for this reason, it has been selected as a primary target for crop phenotyping/breeding studies. Within this context, knowledge of the mechanisms involved in the response and acclimation of photosynthetic CO2 assimilation to multiple changing environmental conditions (including nutrients, water availability, and rising temperature) is a matter of great concern for the understanding of plant behavior under stress conditions, and for the development of new strategies and tools for enhancing plant growth in the future. The current review aims to analyze, from a multi-perspective approach (ranging across breeding, gas exchange, genomics, etc.) the impact of changing environmental conditions on the performance of the photosynthetic apparatus and, consequently, plant growth.

Allelic Variation at the Vernalization Response (Vrn-1) and Photoperiod Sensitivity (Ppd-1) Genes and Their Association With the Development of Durum Wheat Landraces and Modern Cultivars

Wheat adaptability to a wide range of environmental conditions is mostly determined by allelic diversity within genes controlling vernalization requirement (Vrn-1) and photoperiod sensitivity (Ppd-1). We characterized a panel of 151 durum wheat Mediterranean landraces and 20 representative locally adapted modern cultivars for their allelic composition at Vrn-1 and Ppd-1 gene using diagnostic molecular markers and studied their association with the time needed to reach six growth stages under field conditions over 6 years. Compared with the more diverse and representative landrace collection, the set of modern cultivars were characterized by a reduction of 50% in the number of allelic variants at the Vrn-A1 and Vrn-B1 genes, and the high frequency of mutant alleles conferring photoperiod insensitivity at Ppd-A1, which resulted on a shorter cycle length. Vrn-A1 played a greater role than Vrn-B1 in regulating crop development (Vrn-A1 > Vrn-B1). The results suggest that mutations in the Vrn-A1 gene may have been the most important in establishing the spring growth habit of Mediterranean landraces and modern durum cultivars. The allele Vrn-A1d, found in 10 landraces, delayed development. The relative effects of single Vrn-A1 alleles on delaying the development of the landraces were vrn-A1 = Vrn-A1d > Vrn-A1b > Vrn-A1c. Allele vrn-B1 was present in all except two landraces and in all modern cultivars. The null allele at Ppd-A1 (a deletion first observed in the French bread wheat cultivar 'Capelle-Desprez') was found for the first time in durum wheat in the present study that identified it in 30 landraces from 13 Mediterranean countries. Allele Ppd-A1a (GS105) was detected in both germplasm types, while the allele Ppd-A1a (GS100) was found only in modern North American and Spanish cultivars. The relative effect of single Ppd-A1 alleles on extending phenological development was Ppd-A1(DelCD) > Ppd-A1b > Ppd-A1a (GS105) > Ppd-A1a (GS100). Sixteen Vrn-1+Ppd-1 allelic combinations were found in landraces and six in modern cultivars, but only three were common to both panels. Differences in the number of days to reach anthesis were 10 days in landraces and 3 days in modern cultivars. Interactive effects between Vrn-1 and Ppd-1 genes were detected.

The Global Durum Wheat Panel (GDP): An International Platform to Identify and Exchange Beneficial Alleles

Representative, broad and diverse collections are a primary resource to dissect genetic diversity and meet pre-breeding and breeding goals through the identification of beneficial alleles for target traits. From 2,500 tetraploid wheat accessions obtained through an international collaborative effort, a Global Durum wheat Panel (GDP) of 1,011 genotypes was assembled that captured 94-97% of the original diversity. The GDP consists of a wide representation of Triticum turgidum ssp. durum modern germplasm and landraces, along with a selection of emmer and primitive tetraploid wheats to maximize diversity. GDP accessions were genotyped using the wheat iSelect 90K SNP array. Among modern durum accessions, breeding programs from Italy, France and Central Asia provided the highest level of genetic diversity, with only a moderate decrease in genetic diversity observed across nearly 50 years of breeding (1970-2018). Further, the breeding programs from Europe had the largest sets of unique alleles. LD was lower in the landraces (0.4 Mbp) than in modern germplasm (1.8 Mbp) at r ² = 0.5. ADMIXTURE analysis of modern germplasm defined a minimum of 13 distinct genetic clusters (k), which could be traced to the breeding program of origin. Chromosome regions putatively subjected to strong selection pressure were identified from fixation index (F _st ) and diversity reduction index (DRI) metrics in pairwise comparisons among decades of release and breeding programs. Clusters of putative selection sweeps (PSW) were identified as co-localized with major loci controlling phenology (Ppd and Vrn), plant height (Rht) and quality (gliadins and glutenins), underlining the role of the corresponding genes as driving elements in modern breeding. Public seed availability and deep genetic characterization of the GDP make this collection a unique and ideal resource to identify and map useful genetic diversity at loci of interest to any breeding program.

Grain protein content and thousand kernel weight QTLs identified in a durum × wild emmer wheat mapping population tested in five environments

Genetic dissection of GPC and TKW in tetraploid durum × WEW RIL population, based on high-density SNP genetic map, revealed 12 GPC QTLs and 11 TKW QTLs, with favorable alleles for 11 and 5 QTLs, respectively, derived from WEW. Wild emmer wheat (Triticum turgidum ssp. dicoccoides, WEW) was shown to exhibit high grain protein content (GPC) and therefore possess a great potential for improvement of cultivated wheat nutritional value. Genetic dissection of thousand kernel weight (TKW) and grain protein content (GPC) was performed using a high-density genetic map constructed based on a recombinant inbred line (RIL) population derived from a cross between T. durum var. Svevo and WEW acc. Y12-3. Genotyping of 208 F₆ RILs with a 15 K wheat single nucleotide polymorphism (SNP) array yielded 4166 polymorphic SNP markers, of which 1510 were designated as skeleton markers. A total map length of 2169 cM was obtained with an average distance of 1.5 cM between SNPs. A total of 12 GPC QTLs and 11 TKW QTLs were found under five different environments. No significant correlations were found between GPC and TKW across all environments. Four major GPC QTLs with favorable alleles from WEW were found on chromosomes 4BS, 5AS, 6BS and 7BL. The 6BS GPC QTL coincided with the physical position of the NAC transcription factor TtNAM-B1, underlying the cloned QTL, Gpc-B1. Comparisons of the physical intervals of the GPC QTLs described here with the results previously reported in other durum × WEW RIL population led to the discovery of seven novel GPC QTLs. Therefore, our research emphasizes the importance of GPC QTL dissection in diverse WEW accessions as a source of novel alleles for improvement of GPC in cultivated wheat.

Grain protein content and thousand kernel weight QTLs identified in a durum × wild emmer wheat mapping population tested in five environments

Genetic dissection of GPC and TKW in tetraploid durum × WEW RIL population, based on high-density SNP genetic map, revealed 12 GPC QTLs and 11 TKW QTLs, with favorable alleles for 11 and 5 QTLs, respectively, derived from WEW. Wild emmer wheat (Triticum turgidum ssp. dicoccoides, WEW) was shown to exhibit high grain protein content (GPC) and therefore possess a great potential for improvement of cultivated wheat nutritional value. Genetic dissection of thousand kernel weight (TKW) and grain protein content (GPC) was performed using a high-density genetic map constructed based on a recombinant inbred line (RIL) population derived from a cross between T. durum var. Svevo and WEW acc. Y12-3. Genotyping of 208 F₆ RILs with a 15 K wheat single nucleotide polymorphism (SNP) array yielded 4166 polymorphic SNP markers, of which 1510 were designated as skeleton markers. A total map length of 2169 cM was obtained with an average distance of 1.5 cM between SNPs. A total of 12 GPC QTLs and 11 TKW QTLs were found under five different environments. No significant correlations were found between GPC and TKW across all environments. Four major GPC QTLs with favorable alleles from WEW were found on chromosomes 4BS, 5AS, 6BS and 7BL. The 6BS GPC QTL coincided with the physical position of the NAC transcription factor TtNAM-B1, underlying the cloned QTL, Gpc-B1. Comparisons of the physical intervals of the GPC QTLs described here with the results previously reported in other durum × WEW RIL population led to the discovery of seven novel GPC QTLs. Therefore, our research emphasizes the importance of GPC QTL dissection in diverse WEW accessions as a source of novel alleles for improvement of GPC in cultivated wheat.

High Density Mapping of Quantitative Trait Loci Conferring Gluten Strength in Canadian Durum Wheat

Gluten strength is one of the factors that determine the end-use quality of durum wheat and is an important breeding target for this crop. To characterize the quantitative trait loci (QTL) controlling gluten strength in Canadian durum wheat cultivars, a population of 162 doubled haploid (DH) lines segregating for gluten strength and derived from cv. Pelissier × cv. Strongfield was used in this study. The DH lines, parents, and controls were grown in 3 years and two seeding dates in each year and gluten strength of grain samples was measured by sodium dodecyl sulfate (SDS)-sedimentation volume (SV). With a genetic map created by genotyping the DH lines using the Illumina Infinium iSelect Wheat 90K SNP (single nucleotide polymorphism) chip, QTL contributing to gluten strength were detected on chromosome 1A, 1B, 2B, and 3A. Two major and stable QTL detected on chromosome 1A (QGlu.spa-1A) and 1B (QGlu.spa-1B.1) explaining 13.7-18.7% and 25.4-40.1% of the gluten strength variability respectively were consistently detected over 3 years, with the trait increasing alleles derived from Strongfield. Putative candidate genes underlying the major QTL were identified. Two novel minor QTL (QGlu.spa-3A.1 and QGlu.spa-3A.2) with the trait increasing allele derived from Pelissier were mapped on chromosome 3A explaining up to 8.9% of the phenotypic variance; another three minor QTL (QGlu.spa-2B.1, QGlu.spa-2B.2, and QGlu.spa-2B.3) located on chromosome 2B explained up to 8.7% of the phenotypic variance with the trait increasing allele derived from Pelissier. QGlu.spa-2B.1 is a new QTL and has not been reported in the literature. Multi-environment analysis revealed genetic (QTL) × environment interaction due to the difference of effect in magnitude rather than the direction of the QTL. Eleven pairs of digenic epistatic QTL were identified, with an epistatic effect between the two major QTL of QGlu.spa-1A and QGlu.spa-1B.1 detected in four out of six environments. The peak SNPs and SNPs flanking the QTL interval of QGlu.spa-1A and QGlu.spa-1B.1 were converted to Kompetitive Allele Specific PCR (KASP) markers, which can be deployed in marker-assisted breeding to increase the efficiency and accuracy of phenotypic selection for gluten strength in durum wheat. The QTL that were expressed consistently across environments are of great importance to maintain the gluten strength of Canadian durum wheat to current market standards during the genetic improvement.

Investigating the Impact of Biostimulants on the Row Crops Corn and Soybean Using High-Efficiency Phenotyping and Next Generation Sequencing

Row crops represent the most important crops in terms of global cultivated area. Such crops include soybean, corn, wheat, rice, rapeseed, sunflower, and cotton. Row crops agriculture is generally an intensive system of farming used to obtain high yields by employing elevated quantities of organic and mineral fertilizers. Considering this, and the decrease in area of arable land, it becomes crucial to ensure high yield and quality using alternative strategies, such as the use of plant biostimulants. These compounds are increasingly recognized as sustainable solution to optimize nutrient uptake, crop yield, quality, and tolerance to abiotic stresses. In this work, by means of high-throughput plant phenotyping, we evaluated the effectiveness of a set of three new foliar biostimulant prototypes (coded as 52096, 52097, 52113) applied on corn and soybean at application rates 2.5 and 5 mL/L (corresponding to 1 and 2 L/ha respectively). This allowed us to select the most effective prototype (52097, commercial name “YieldOn®”) in increasing digital biovolume (DB) and greener area (GGA) either in soybean (both application rates) or corn (rate 5 mL/L) and decreasing Stress Index (SI) in soybean (both application rates). Molecular mechanism of action of selected prototype 52097 was subsequently characterized through Next Generation Sequencing (NGS). In corn, genes involved in hormone (cytokinin and auxin) metabolism/catabolism, maltose biosynthesis, sugar transport and phloem loading were upregulated after application of prototype 52097. In soybean, genes involved in nitrogen metabolism, metal ion transport (mainly zinc and iron), sulfate reduction, and amino acid biosynthesis were induced. The proposed approach supports the integration of multiple omics to open new perspectives in the discovery, evaluation, and development of innovative and sustainable solutions to meet the increasing needs of row-crops agriculture.

A Robust Automated Image-Based Phenotyping Method for Rapid Vegetative Screening of Wheat Germplasm for Nitrogen Use Efficiency

Nitrogen use efficiency (NUE) in crops is generally low, with more than 60% of applied nitrogen (N) being lost to the environment, which increases production costs and affects ecosystems and human habitats. To overcome these issues, the breeding of crop varieties with improved NUE is needed, requiring efficient phenotyping methods along with molecular and genetic approaches. To develop an effective phenotypic screening method, experiments on wheat varieties under various N levels were conducted in the automated phenotyping platform at Plant Phenomics Victoria, Horsham. The results from the initial experiment showed that two relative N levels-5 mM and 20 mM, designated as low and optimum N, respectively-were ideal to screen a diverse range of wheat germplasm for NUE on the automated imaging phenotyping platform. In the second experiment, estimated plant parameters such as shoot biomass and top-view area, derived from digital images, showed high correlations with phenotypic traits such as shoot biomass and leaf area seven weeks after sowing, indicating that they could be used as surrogate measures of the latter. Plant growth analysis confirmed that the estimated plant parameters from the vegetative linear growth phase determined by the "broken-stick" model could effectively differentiate the performance of wheat varieties for NUE. Based on this study, vegetative phenotypic screens should focus on selecting wheat varieties under low N conditions, which were highly correlated with biomass and grain yield at harvest. Analysis indicated a relationship between controlled and field conditions for the same varieties, suggesting that greenhouse screens could be used to prioritise a higher value germplasm for subsequent field studies. Overall, our results showed that this phenotypic screening method is highly applicable and can be applied for the identification of N-efficient wheat germplasm at the vegetative growth phase.

Early Prediction of Soybean Traits through Color and Texture Features of Canopy RGB Imagery

Global crop production is facing the challenge of a high projected demand, while the yields of major crops are not increasing at sufficient speeds. Crop breeding is an important way to boost crop productivity, however its improvement rate is partially hindered by the long crop generation cycles. If end-season crop traits such as yield can be predicted through early-season phenotypic measurements, crop selection can potentially be made before a full crop generation cycle finishes. This study explored the possibility of predicting soybean end-season traits through the color and texture features of early-season canopy images. Six thousand three hundred and eighty-three images were captured at V4/V5 growth stage over 6039 soybean plots growing at four locations. One hundred and forty color features and 315 gray-level co-occurrence matrix-based texture features were derived from each image. Another two variables were also introduced to account for location and timing differences between the images. Five regression and five classification techniques were explored. Best results were obtained using all 457 predictor variables, with Cubist as the regression technique and Random Forests as the classification technique. Yield (RMSE = 9.82, R2 = 0.68), Maturity (RMSE = 3.70, R2 = 0.76) and Seed Size (RMSE = 1.63, R2 = 0.53) were identified as potential soybean traits that might be early predictable.

Temporal genetic patterns of root growth in Brassica napus L. revealed by a low-cost, high-efficiency hydroponic system

Application of a low-cost and high-efficiency hydroponic system in a rapeseed population verified two types of genetic factors ("persistent" and "stage-specific") that control root development. The root system is a vital plant component for nutrient and water acquisition and is targeted to enhance plant productivity. Genetic dissection of the root system generally focuses on a single stage, but roots grow continuously during plant development. To reveal the temporal genetic patterns of root development, we measured nine root-related traits in a rapeseed recombinant inbred line population at six continuous stages during vegetative growth, using a modified hydroponic system with low-cost and high-efficiency features that could synchronize plant growth under controlled conditions. Phenotypic correlation and growth dynamic analysis suggested the existence of two types of genetic factors ("persistent" and "stage-specific") that control root development. Dynamic (unconditional and conditional) quantitative trait loci (QTL) mapping detected 28 stage-specific and 23 persistent QTLs related to root growth. Among them, 13 early stage-specific, 19 persistent and 8 later stage-specific QTLs were detected at 7 DAS (days after sowing), 16 DAS and 5 EL (expanding leaf stage), respectively, providing efficient and adaptable stages for QTL identification. The effective prediction of biomass accumulation using root morphological traits (up to 96.6% or 92.64% at a specific stage or the final stage, respectively) verified that root growth allocation with maximum root uptake area facilitated biomass accumulation. Furthermore, marker-assistant selection, which combined the "persistent" and "stage-specific" QTLs, proved their effectiveness for root improvement with an excellent uptake area. Our results highlight the potential of high-throughput and precise phenotyping to assess the dynamic genetics of root growth and provide new insights into ideotype root system-based biomass breeding.

A Genome-Wide Association Study of Highly Heritable Agronomic Traits in Durum Wheat

Uncovering the genetic basis of key agronomic traits, and particularly of drought tolerance, addresses an important priority for durum wheat improvement. Here, a genome-wide association study (GWAS) in 493 durum wheat accessions representing a worldwide collection was employed to address the genetic basis of 17 agronomically important traits and a drought wilting score. Using a linear mixed model with 4 inferred subpopulations and a kinship matrix, we identified 90 marker-trait-associations (MTAs) defined by 78 markers. These markers could be merged into 44 genomic loci by linkage disequilibrium (r 2 > 0.2). Based on sequence alignment of the markers to the reference genome of bread wheat, we identified 14 putative candidate genes involved in enzymes, hormone-response, and transcription factors. The GWAS in durum wheat and a previous quantitative trait locus (QTL) analysis in bread wheat identified a consensus QTL locus.4B.1 conferring drought tolerance, which was further scanned for the presence of potential candidate genes. A haplotype analysis of this region revealed that two minor haplotypes were associated with both drought tolerance and reduced plant stature, thought to be the effect of linkage with the semi-dwarfing gene Rht-B1. Haplotype variants in the key chromosome 4B region were informative regarding evolutionary divergence among durum, emmer and bread wheat. Over all, the data are relevant in the context of durum wheat improvement and the isolation of genes underlying variation in some important quantitative traits.

A large nested association mapping population for breeding and quantitative trait locus mapping in Ethiopian durum wheat

The Ethiopian plateau hosts thousands of durum wheat (Triticum turgidum subsp. durum) farmer varieties (FV) with high adaptability and breeding potential. To harness their unique allelic diversity, we produced a large nested association mapping (NAM) population intercrossing fifty Ethiopian FVs with an international elite durum wheat variety (Asassa). The Ethiopian NAM population (EtNAM) is composed of fifty interconnected bi-parental families, totalling 6280 recombinant inbred lines (RILs) that represent both a powerful quantitative trait loci (QTL) mapping tool, and a large pre-breeding panel. Here, we discuss the molecular and phenotypic diversity of the EtNAM founder lines, then we use an array featuring 13 000 single nucleotide polymorphisms (SNPs) to characterize a subset of 1200 EtNAM RILs from 12 families. Finally, we test the usefulness of the population by mapping phenology traits and plant height using a genome wide association (GWA) approach. EtNAM RILs showed high allelic variation and a genetic makeup combining genetic diversity from Ethiopian FVs with the international durum wheat allele pool. EtNAM SNP data were projected on the fully sequenced AB genome of wild emmer wheat, and were used to estimate pairwise linkage disequilibrium (LD) measures that reported an LD decay distance of 7.4 Mb on average, and balanced founder contributions across EtNAM families. GWA analyses identified 11 genomic loci individually affecting up to 3 days in flowering time and more than 1.6 cm in height. We argue that the EtNAM is a powerful tool to support the production of new durum wheat varieties targeting local and global agriculture.

Drought Stress Tolerance in Wheat and Barley: Advances in Physiology, Breeding and Genetics Research

Climate change is a major threat to most of the agricultural crops grown in tropical and sub-tropical areas globally. Drought stress is one of the consequences of climate change that has a negative impact on crop growth and yield. In the past, many simulation models were proposed to predict climate change and drought occurrences, and it is extremely important to improve essential crops to meet the challenges of drought stress which limits crop productivity and production. Wheat and barley are among the most common and widely used crops due to their economic and social values. Many parts of the world depend on these two crops for food and feed, and both crops are vulnerable to drought stress. Improving drought stress tolerance is a very challenging task for wheat and barley researchers and more research is needed to better understand this stress. The progress made in understanding drought tolerance is due to advances in three main research areas: physiology, breeding, and genetic research. The physiology research focused on the physiological and biochemical metabolic pathways that plants use when exposed to drought stress. New wheat and barley genotypes having a high degree of drought tolerance are produced through breeding by making crosses from promising drought-tolerant genotypes and selecting among their progeny. Also, identifying genes contributing to drought tolerance is very important. Previous studies showed that drought tolerance is a polygenic trait and genetic constitution will help to dissect the gene network(s) controlling drought tolerance. This review explores the recent advances in these three research areas to improve drought tolerance in wheat and barley.

Drought Stress Tolerance in Wheat and Barley: Advances in Physiology, Breeding and Genetics Research

Climate change is a major threat to most of the agricultural crops grown in tropical and sub-tropical areas globally. Drought stress is one of the consequences of climate change that has a negative impact on crop growth and yield. In the past, many simulation models were proposed to predict climate change and drought occurrences, and it is extremely important to improve essential crops to meet the challenges of drought stress which limits crop productivity and production. Wheat and barley are among the most common and widely used crops due to their economic and social values. Many parts of the world depend on these two crops for food and feed, and both crops are vulnerable to drought stress. Improving drought stress tolerance is a very challenging task for wheat and barley researchers and more research is needed to better understand this stress. The progress made in understanding drought tolerance is due to advances in three main research areas: physiology, breeding, and genetic research. The physiology research focused on the physiological and biochemical metabolic pathways that plants use when exposed to drought stress. New wheat and barley genotypes having a high degree of drought tolerance are produced through breeding by making crosses from promising drought-tolerant genotypes and selecting among their progeny. Also, identifying genes contributing to drought tolerance is very important. Previous studies showed that drought tolerance is a polygenic trait and genetic constitution will help to dissect the gene network(s) controlling drought tolerance. This review explores the recent advances in these three research areas to improve drought tolerance in wheat and barley.

UAV and Ground Image-Based Phenotyping: A Proof of Concept with Durum Wheat

Climate change is one of the primary culprits behind the restraint in the increase of cereal crop yields. In order to address its effects, effort has been focused on understanding the interaction between genotypic performance and the environment. Recent advances in unmanned aerial vehicles (UAV) have enabled the assembly of imaging sensors into precision aerial phenotyping platforms, so that a large number of plots can be screened effectively and rapidly. However, ground evaluations may still be an alternative in terms of cost and resolution. We compared the performance of red–green–blue (RGB), multispectral, and thermal data of individual plots captured from the ground and taken from a UAV, to assess genotypic differences in yield. Our results showed that crop vigor, together with the quantity and duration of green biomass that contributed to grain filling, were critical phenotypic traits for the selection of germplasm that is better adapted to present and future Mediterranean conditions. In this sense, the use of RGB images is presented as a powerful and low-cost approach for assessing crop performance. For example, broad sense heritability for some RGB indices was clearly higher than that of grain yield in the support irrigation (four times), rainfed (by 50%), and late planting (10%). Moreover, there wasn’t any significant effect from platform proximity (distance between the sensor and crop canopy) on the vegetation indexes, and both ground and aerial measurements performed similarly in assessing yield.

High-Throughput Phenotyping of Fire Blight Disease Symptoms Using Sensing Techniques in Apple

Washington State produces about 70% of total fresh market apples in the United States. One of the primary goals of apple breeding programs is the development of new cultivars resistant to devastating diseases such as fire blight. The overall objective of this study was to investigate high-throughput phenotyping techniques to evaluate fire blight disease symptoms in apple trees. In this regard, normalized stomatal conductance data acquired using a portable photosynthetic system, image data collected using RGB and multispectral cameras, and visible-near infrared spectral reflectance acquired using a hyperspectral sensing system, were independently evaluated to estimate the progression of fire blight infection in young apple trees. Sensors with ranging complexity - from simple RGB to multispectral imaging to hyperspectral system - were evaluated to select the most accurate technique for the assessment of fire blight disease symptoms. The proximal multispectral images and visible-near infrared spectral reflectance data were collected in two field seasons (2016, 2017); while, proximal side-view RGB images and multispectral images using unmanned aerial systems were collected in 2017. The normalized stomatal conductance data was correlated with disease severity rating (r = 0.51, P < 0.05). The features extracted from RGB images (e.g., maximum length of senesced leaves, area of senesced leaves, ratio between senesced and healthy leaf area) and multispectral images (e.g., vegetation indices) also demonstrated potential in evaluation of disease rating (|r| > 0.35, P < 0.05). The average classification accuracy achieved using visible-near infrared spectral reflectance data during the classification of susceptible from symptomless groups ranged between 71 and 93% using partial least square regression and quadratic support vector machine. In addition, fire blight disease ratings were compared with normalized difference spectral indices (NDSIs) that were generated from visible-near infrared reflectance spectra. The selected spectral bands in the range 710-2,340 nm used for computing NDSIs showed consistently higher correlation with disease severity rating than data acquired from RGB and multispectral imaging sensors across multiple seasons. In summary, these specific spectral bands can be used for evaluating fire blight disease severity in apple breeding programs and potentially as early fire blight disease detection tool to assist in production systems.

Identification of traits associated with barley yield performance using contrasting nitrogen fertilizations and genotypes

Much attention has been paid to understanding the traits associated with crop performance and the associated underlying physiological mechanisms, with less effort done towards combining different plant scales, levels of observation, or including hybrids of autogamous species. We aim to identify mechanisms at canopy, leaf and transcript levels contributing to crop performance under contrasting nitrogen supplies in three barley genotypes, two hybrids and one commercial line. High nitrogen fertilization did not affect photosynthetic capacity on a leaf area basis and lowered nitrogen partial factor productivity past a certain point, but increased leaf area and biomass accumulation, parameters that were closely tracked using various different high throughput remote sensing based phenotyping techniques. These aspects, together with a larger catabolism of leaf nitrogen compounds amenable to sink translocation, contributed to higher crop production. Better crop yield and growth in hybrids compared to the line was linked to a nitrogen-saving strategy in source leaves to the detriment of larger sink size, as indicated by the lower leaf nitrogen content and downregulation of nitrogen metabolism and aquaporin genes. While these changes did not reduce photosynthesis capacity on an area basis, they were related with better nitrogen use in the hybrids compared with the line.

High-Throughput Field Imaging and Basic Image Analysis in a Wheat Breeding Programme

Visual assessment of colour-based traits plays a key role within field-crop breeding programmes, though the process is subjective and time-consuming. Digital image analysis has previously been investigated as an objective alternative to visual assessment for a limited number of traits, showing suitability and slight improvement to throughput over visual assessment. However, easily adoptable, field-based high-throughput methods are still lacking. The aim of the current study was to produce a high-throughput digital imaging and analysis pipeline for the assessment of colour-based traits within a wheat breeding programme. This was achieved through the steps of (i) a proof-of-concept study demonstrating basic image analysis methods in a greenhouse, (ii) application of these methods to field trials using hand-held imaging, and (iii) developing a field-based high-throughput imaging infrastructure for data collection. The proof of concept study showed a strong correlation (r = 0.95) between visual and digital assessments of wheat physiological yellowing (PY) in a greenhouse environment, with both scores having similar heritability (H2 = 0.85 and 0.76, respectively). Digital assessment of hand-held field images showed strong correlations to visual scores for PY (r = 0.61 and 0.78), senescence (r = 0.74 and 0.75) and Septoria tritici blotch (STB; r = 0.76), with greater heritability of digital scores, excluding STB. Development of the high-throughput imaging infrastructure allowed for images of field plots to be collected at a rate of 7,400 plots per hour. Images of an advanced breeding trial collected with this system were analysed for canopy cover at two time-points, with digital scores correlating strongly to visual scores (r = 0.88 and 0.86) and having similar or greater heritability. This study details how high-throughput digital phenotyping can be applied to colour-based traits within field trials of a wheat breeding programme. It discusses the logistics of implementing such systems with minimal disruption to the programme, provides a detailed methodology for the basic image analysis methods utilized, and has potential for application to other field-crop breeding or research programmes.

High-Throughput Field Imaging and Basic Image Analysis in a Wheat Breeding Programme

Visual assessment of colour-based traits plays a key role within field-crop breeding programmes, though the process is subjective and time-consuming. Digital image analysis has previously been investigated as an objective alternative to visual assessment for a limited number of traits, showing suitability and slight improvement to throughput over visual assessment. However, easily adoptable, field-based high-throughput methods are still lacking. The aim of the current study was to produce a high-throughput digital imaging and analysis pipeline for the assessment of colour-based traits within a wheat breeding programme. This was achieved through the steps of (i) a proof-of-concept study demonstrating basic image analysis methods in a greenhouse, (ii) application of these methods to field trials using hand-held imaging, and (iii) developing a field-based high-throughput imaging infrastructure for data collection. The proof of concept study showed a strong correlation (r = 0.95) between visual and digital assessments of wheat physiological yellowing (PY) in a greenhouse environment, with both scores having similar heritability (H² = 0.85 and 0.76, respectively). Digital assessment of hand-held field images showed strong correlations to visual scores for PY (r = 0.61 and 0.78), senescence (r = 0.74 and 0.75) and Septoria tritici blotch (STB; r = 0.76), with greater heritability of digital scores, excluding STB. Development of the high-throughput imaging infrastructure allowed for images of field plots to be collected at a rate of 7,400 plots per hour. Images of an advanced breeding trial collected with this system were analysed for canopy cover at two time-points, with digital scores correlating strongly to visual scores (r = 0.88 and 0.86) and having similar or greater heritability. This study details how high-throughput digital phenotyping can be applied to colour-based traits within field trials of a wheat breeding programme. It discusses the logistics of implementing such systems with minimal disruption to the programme, provides a detailed methodology for the basic image analysis methods utilized, and has potential for application to other field-crop breeding or research programmes.

Genomic Regions From an Iranian Landrace Increase Kernel Size in Durum Wheat

Kernel size and shape are important parameters determining the wheat profitability, being main determinants of yield and its technological quality. In this study, a segregating population of 118 recombinant inbred lines, derived from a cross between the Iranian durum landrace accession "Iran_249" and the Iranian durum cultivar "Zardak", was used to investigate durum wheat kernel morphology factors and their relationships with kernel weight, and to map the corresponding QTLs. A high density genetic map, based on wheat 90k iSelect Infinium SNP assay, comprising 6,195 markers, was developed and used to perform the QTL analysis for kernel length and width, traits related to kernel shape and weight, and heading date, using phenotypic data from three environments. Overall, a total of 31 different QTLs and 9 QTL interactions for kernel size, and 21 different QTLs and 5 QTL interactions for kernel shape were identified. The landrace Iran_249 contributed the allele with positive effect for most of the QTLs related to kernel length and kernel weight suggesting that the landrace might have considerable potential toward enhancing the existing gene pool for grain shape and size traits and for further yield improvement in wheat. The correlation among traits and co-localization of corresponding QTLs permitted to define 11 clusters suggesting causal relationships between simplest kernel size trait, like kernel length and width, and more complex secondary trait, like kernel shape and weight related traits. Lastly, the recent release of the T. durum reference genome sequence allowed to define the physical interval of our QTL/clusters and to hypothesize novel candidate genes inspecting the gene content of the genomic regions associated to target traits.

Evaluating Maize Genotype Performance under Low Nitrogen Conditions Using RGB UAV Phenotyping Techniques

Maize is the most cultivated cereal in Africa in terms of land area and production, but low soil nitrogen availability often constrains yields. Developing new maize varieties with high and reliable yields using traditional crop breeding techniques in field conditions can be slow and costly. Remote sensing has become an important tool in the modernization of field-based high-throughput plant phenotyping (HTPP), providing faster gains towards the improvement of yield potential and adaptation to abiotic and biotic limiting conditions. We evaluated the performance of a set of remote sensing indices derived from red-green-blue (RGB) images along with field-based multispectral normalized difference vegetation index (NDVI) and leaf chlorophyll content (SPAD values) as phenotypic traits for assessing maize performance under managed low-nitrogen conditions. HTPP measurements were conducted from the ground and from an unmanned aerial vehicle (UAV). For the ground-level RGB indices, the strongest correlations to yield were observed with hue, greener green area (GGA), and a newly developed RGB HTPP index, NDLab (normalized difference Commission Internationale de I´Edairage (CIE)Lab index), while GGA and crop senescence index (CSI) correlated better with grain yield from the UAV. Regarding ground sensors, SPAD exhibited the closest correlation with grain yield, notably increasing in its correlation when measured in the vegetative stage. Additionally, we evaluated how different HTPP indices contributed to the explanation of yield in combination with agronomic data, such as anthesis silking interval (ASI), anthesis date (AD), and plant height (PH). Multivariate regression models, including RGB indices (R2 > 0.60), outperformed other models using only agronomic parameters or field sensors (R2 > 0.50), reinforcing RGB HTPP's potential to improve yield assessments. Finally, we compared the low-N results to the same panel of 64 maize genotypes grown under optimal conditions, noting that only 11% of the total genotypes appeared in the highest yield producing quartile for both trials. Furthermore, we calculated the grain yield loss index (GYLI) for each genotype, which showed a large range of variability, suggesting that low-N performance is not necessarily exclusive of high productivity in optimal conditions.

Genomic tools for durum wheat breeding: de novo assembly of Svevo transcriptome and SNP discovery in elite germplasm

BACKGROUND

The tetraploid durum wheat (Triticum turgidum L. ssp. durum Desf. Husnot) is an important crop which provides the raw material for pasta production and a valuable source of genetic diversity for breeding hexaploid wheat (Triticum aestivum L.). Future breeding efforts to enhance yield potential and climate resilience will increasingly rely on genomics-based approaches to identify and select beneficial alleles. A deeper characterisation of the molecular and functional diversity of the durum wheat transcriptome will be instrumental to more effectively harness its genetic diversity.

RESULTS

We report on the de novo transcriptome assembly of durum wheat cultivar 'Svevo'. The transcriptome of four tissues/organs (shoots and roots at the seedling stage, reproductive organs and developing grains) was assembled de novo, yielding 180,108 contigs, with a N50 length of 1121 bp and mean contig length of 883 bp. Alignment against the transcriptome of nine plant species identified 43% of transcripts with homology to at least one reference transcriptome. The functional annotation was completed by means of a combination of complementary software. The presence of differential expression between the A- and B-homoeolog copies of the durum wheat tetraploid genome was ascertained by phase reconstruction of polymorphic sites based on the T. urartu transcripts and inferring homoeolog-specific sequences. We observed greater expression divergence between A and B homoeologs in grains rather than in leaves and roots. The transcriptomes of 13 durum wheat cultivars spanning the breeding period from 1969 to 2005 were analysed for SNP diversity, leading to 95,358 non-rare, hemi-SNPs shared among two or more cultivars and 33,747 locus-specific (diploid inheritance) SNPs.

CONCLUSIONS

Our study updates and expands the de novo transcriptome reference assembly available for durum wheat. Out of 180,108 assembled transcripts, 13,636 were specific to the Svevo cultivar as compared to the only other reference transcriptome available for durum, thus contributing to the identification of the tetraploid wheat pan-transcriptome. Additionally, the analysis of 13 historically relevant hallmark varieties produced a SNP dataset that could successfully validate the genotyping in tetraploid wheat and provide a valuable resource for genomics-assisted breeding of both tetraploid and hexaploid wheats.

Use of RGB Vegetation Indexes in Assessing Early Effects of Verticillium Wilt of Olive in Asymptomatic Plants in High and Low Fertility Scenarios

Verticillium Wilt of Olive, a disease caused by the hemibiotrophic vascular fungus Verticillium dahliae Kleb. presents one of the most important constraints to olive production in the world, with an especially notable impact in Mediterranean agriculture. This study evaluates the use of RGB vegetation indexes in assessing the effects of this disease during the biotrophic phase of host-pathogen interaction, in which symptoms of wilt are not yet evident. While no differences were detected by measuring stomatal conductance and chlorophyll fluorescence, results obtained from RGB indexes showed significant differences between control and inoculated plants for indexes Saturation, a*, b*, green Area (GA), normalized green-red difference index (NGRDI) and triangular greenness index (TGI), presenting a reduction in plant growth as well as in green and yellow color components as an effect of inoculation. These results were contrasted across two scenarios of mineral fertilization in soil and soil amended with two different olive mill waste composts, presenting a clear interaction between the host-pathogen relationship and plant nutrition and suggesting the effect of V. dahliae infection during the biotrophic phase was not related to plant water status.

Domestication and crop evolution of wheat and barley: Genes, genomics, and future directions

Wheat and barley are two of the founder crops of the agricultural revolution that took place 10,000 years ago in the Fertile Crescent and both crops remain among the world's most important crops. Domestication of these crops from their wild ancestors required the evolution of traits useful to humans, rather than survival in their natural environment. Of these traits, grain retention and threshability, yield improvement, changes to photoperiod sensitivity and nutritional value are most pronounced between wild and domesticated forms. Knowledge about the geographical origins of these crops and the genes responsible for domestication traits largely pre-dates the era of next-generation sequencing, although sequencing will lead to new insights. Molecular markers were initially used to calculate distance (relatedness), genetic diversity and to generate genetic maps which were useful in cloning major domestication genes. Both crops are characterized by large, complex genomes which were long thought to be beyond the scope of whole-genome sequencing. However, advances in sequencing technologies have improved the state of genomic resources for both wheat and barley. The availability of reference genomes for wheat and some of its progenitors, as well as for barley, sets the stage for answering unresolved questions in domestication genomics of wheat and barley.

Genetic dissection of agronomic and quality traits based on association mapping and genomic selection approaches in durum wheat grown in Southern Spain

Climatic conditions affect the growth, development and final crop production. As wheat is of paramount importance as a staple crop in the human diet, there is a growing need to study its abiotic stress adaptation through the performance of key breeding traits. New and complementary approaches, such as genome-wide association studies (GWAS) and genomic selection (GS), are used for the dissection of different agronomic traits. The present study focused on the dissection of agronomic and quality traits of interest (initial agronomic score, yield, gluten index, sedimentation index, specific weight, whole grain protein and yellow colour) assessed in a panel of 179 durum wheat lines (Triticum durum Desf.), grown under rainfed conditions in different Mediterranean environments in Southern Spain (Andalusia). The findings show a total of 37 marker-trait associations (MTAs) which affect phenotype expression for three quality traits (specific weight, gluten and sedimentation indexes). MTAs could be mapped on the A and B durum wheat subgenomes (on chromosomes 1A, 1B, 2A, 2B and 3A) through the recently available bread wheat reference assembly (IWGSC RefSeqv1). Two of the MTAs found for quality traits (gluten index and SDS) corresponded to the known Glu-B1 and Glu-A1 loci, for which candidate genes corresponding to high molecular weight glutenin subunits could be located. The GS prediction ability values obtained from the breeding materials analyzed showed promising results for traits as grain protein content, sedimentation and gluten indexes, which can be used in plant breeding programs.

The General Transcription Repressor TaDr1 Is Co-expressed With TaVrn1 and TaFT1 in Bread Wheat Under Drought

The general transcription repressor, TaDr1 gene, was identified during screening of a wheat SNP database using the Amplifluor-like SNP marker KATU-W62. Together with two genes described earlier, TaDr1A and TaDr1B, they represent a set of three homeologous genes in the wheat genome. Under drought, the total expression profiles of all three genes varied between different bread wheat cultivars. Plants of four high-yielding cultivars exposed to drought showed a 2.0-2.4-fold increase in TaDr1 expression compared to controls. Less strong, but significant 1.3-1.8-fold up-regulation of the TaDr1 transcript levels was observed in four low-yielding cultivars. TaVrn1 and TaFT1, which controls the transition to flowering, revealed similar profiles of expression as TaDr1. Expression levels of all three genes were in good correlation with grain yields of evaluated cultivars growing in the field under water-limited conditions. The results could indicate the involvement of all three genes in the same regulatory pathway, where the general transcription repressor TaDr1 may control expression of TaVrn1 and TaFT1 and, consequently, flowering time. The strength of these genes expression can lead to phenological changes that affect plant productivity and hence explain differences in the adaptation of the examined wheat cultivars to the dry environment of Northern and Central Kazakhstan. The Amplifluor-like SNP marker KATU-W62 used in this work can be applied to the identification of wheat cultivars differing in alleles at the TaDr1 locus and in screening hybrids.

The Plant-Transpiration Response to Vapor Pressure Deficit (VPD) in Durum Wheat Is Associated With Differential Yield Performance and Specific Expression of Genes Involved in Primary Metabolism and Water Transport

The regulation of plant transpiration was proposed as a key factor affecting transpiration efficiency and agronomical adaptation of wheat to water-limited Mediterranean environments. However, to date no studies have related this trait to crop performance in the field. In this study, the transpiration response to increasing vapor pressure deficit (VPD) of modern Spanish semi-dwarf durum wheat lines was evaluated under controlled conditions at vegetative stage, and the agronomical performance of the same set of lines was assessed at grain filling as well as grain yield at maturity, in Mediterranean environments ranging from water stressed to good agronomical conditions. A group of linear-transpiration response (LTR) lines exhibited better performance in grain yield and biomass compared to segmented-transpiration response (STR) lines, particularly in the wetter environments, whereas the reverse occurred only in the most stressed trial. LTR lines generally exhibited better water status (stomatal conductance) and larger green biomass (vegetation indices) during the reproductive stage than STR lines. In both groups, the responses to growing conditions were associated with the expression levels of dehydration-responsive transcription factors (DREB) leading to different performances of primary metabolism-related enzymes. Thus, the response of LTR lines under fair to good conditions was associated with higher transcription levels of genes involved in nitrogen (GS1 and GOGAT) and carbon (RCBL) metabolism, as well as water transport (TIP1.1). In conclusion, modern durum wheat lines differed in their response to water loss, the linear transpiration seemed to favor uptake and transport of water and nutrients, and photosynthetic metabolism led to higher grain yield except for very harsh drought conditions. The transpiration response to VPD may be a trait to further explore when selecting adaptation to specific water conditions.

QTL and Candidate Gene Identification for Silique Length Based on High-Dense Genetic Map in Brassica napus L

Silique length (SL) is an important yield trait and positively correlates with seeds per silique and seed weight. In the present study, two double haploid (DH) populations, established from crosses Zhongshuang11 × R11 (ZR) and R1 × R2 (RR), containing 280 and 95 DH lines, respectively, were used to map quantitative trait loci (QTL) for SL. A high-dense genetic map from ZR population was constructed comprising 14,658 bins on 19 linkage groups, with map length of 2,198.85 cM and an average marker distance of 0.15 cM. Genetic linkage map from RR population was constructed by using 2,046 mapped markers anchored to 19 chromosomes with 2,217-cM map length and an average marker distance of 1.08 cM. Major QTL qSL_ZR_A09 and qSL_RR_A09b on A09 were identified from ZR and RR populations, respectively. Both QTL could be stably detected in four environments. QTL qSL_RR_A09b and qSL_ZR_A09 were located on 68.5-70.8 cM and 91.33-91.94 cM interval with R² values of 14.99-39.07% and 15.00-20.36% in RR and ZR populations, respectively. Based on the physical positions of single nucleotide polymorphism (SNP) markers flanking qSL_ZR_A09 and gene annotation in Arabidopsis, 26 genes were identified with SNP/Indel variation between parents and two genes (BnaA09g41180D and BnaA09g41380D) were selected as the candidate genes. Expression analysis further revealed BnaA09g41180D, encoding homologs of Arabidopsis fasciclin-like arabinogalactan proteins (FLA3), as the most promising candidate gene for qSL_ZR_A09. The QTL identification and candidate gene analysis will provide new insight into the genomic regions controlling SL in Brassica napus as well as candidate genes underlying the QTL.

Novel Alleles for Combined Drought and Heat Stress Tolerance in Wheat

Drought and heat waves commonly co-occur in many wheat-growing regions causing significant crop losses. The identification of stress associated quantitative trait loci, particularly those for yield, is problematic due to their association with plant phenology and the high genetic × environment interaction. Here we studied a panel of 315 diverse, spring type accessions of bread wheat (Triticum aestivum) in pots in a semi-controlled environment under combined drought and heat stress over 2 years. Importantly, we treated individual plants according to their flowering time. We found 134 out of the 145 identified loci for grain weight that were not associated with either plant phenology or plant height. The majority of loci uncovered here were novel, with favorable alleles widespread in Asian and African landraces providing opportunities for their incorporation into modern varieties through breeding. Using residual heterozygosity in lines from a nested association mapping population, we were able to rapidly develop near-isogenic lines for important target loci. One target locus on chromosome 6A contributed to higher grain weight, harvest index, thousand kernel weight, and grain number under drought and heat stress in field conditions consistent with allelic effects demonstrated in the genome-wide association study.

Multiple Near-Isogenic Lines Targeting a QTL Hotspot of Drought Tolerance Showed Contrasting Performance Under Post-anthesis Water Stress

The complex quantitative nature of drought-related traits is a major constraint to breed tolerant wheat varieties. Pairs of near-isogenic lines (NILs) with a common genetic background but differing in a particular locus could turn quantitative traits into a Mendelian factor facilitating our understanding of genotype and phenotype interactions. In this study, we report our fast track development and evaluation of NILs from C306 × Dharwar Dry targeting a wheat 4BS QTL hotspot in C306, which confers drought tolerance following the heterogeneous inbreed family (HIF) analysis coupled with immature embryo culture-based fast generation technique. Molecular marker screening and phenotyping for grain yield and related traits under post-anthesis water stress (WS) confirmed four isoline pairs, viz., qDSI.4B.1-2, qDSI.4B.1-3, qDSI.4B.1-6, and qDSI.4B.1-8. There were significant contrasts of responses between the NILs with C306 QTL (+NILs) and the NILs without C306 QTL (-NILs). Among the four confirmed NIL pairs, mean grain yield per plant of the +NILs and -NILs showed significant differences ranging from 9.61 to 10.81 and 6.30 to 7.56 g, respectively, under WS condition, whereas a similar grain yield was recorded between the +NILs and -NILs under well-watered condition. Isolines of +NIL and -NIL pairs showed similar chlorophyll content (SPAD), assimilation rate (A), and transpiration rate (Tr) at the beginning of the stress. However, the +NILs showed significantly higher SPAD (12%), A (66%), stomatal conductance (75%), and Tr (97%) than the -NILs at the seventh day of stress. Quantitative RT-PCR analysis targeting the MYB transcription factor gene Triticum aestivum MYB 82 (TaMYB82), within this genomic region which was retrieved from the wheat reference genome TGACv1, also revealed differential expression in +NILs and -NILs under stress. These results confirmed that the NILs can be invaluable resources for fine mapping of this QTL, and also for cloning and functional characterization of the gene(s) responsible for drought tolerance in wheat.

Genetic Variation for Protein Content and Yield-Related Traits in a Durum Population Derived From an Inter-Specific Cross Between Hexaploid and Tetraploid Wheat Cultivars

Wheat grain protein content (GPC) and yield components are complex quantitative traits influenced by a multi-factorial system consisting of both genetic and environmental factors. Although seed storage proteins represent less than 15% of mature kernels, they are crucial in determining end-use properties of wheat, as well as the nutritional value of derived products. Yield and GPC are negatively correlated, and this hampers breeding programs of commercially valuable wheat varieties. The goal of this work was the evaluation of genetic variability for quantity and composition of seed storage proteins, together with yield components [grain yield per spike (GYS) and thousand-kernel weight (TKW)] in a durum wheat population obtained by an inter-specific cross between a common wheat accession and the durum cv. Saragolla. Quantitative trait loci (QTL) analysis was conducted and closely associated markers identified on a genetic map composed of 4,366 SNP markers previously obtained in the same durum population genotyped with the 90K iSelect SNP assay. A total of 22 QTL were detected for traits related to durum wheat quality. Six genomic regions responsible for GPC control were mapped on chromosomes 2B, 3A, 4A, 4B, 5B, and 7B, with major QTL on chromosomes 2B, 4A, and 5B. Nine loci were detected for GYS: two on chromosome 5B and 7A and one on chromosomes 2A, 2B, 4A, 4B, 7B, with the strongest QTL on 2B. Eight QTL were identified for TKW, three of which located on chromosome 3A, two on 1B and one on 4B, 5A, and 5B. Only small overlapping was found among QTL for GYS, TKW, and GPC, and increasing alleles coming from both parents on different chromosomes. Good candidate genes were identified in the QTL confidence intervals for GYS and TKW.

In Vivo Phenotyping for the Early Detection of Drought Stress in Tomato

Drought stress imposes a major constraint over a crop yield and can be expected to grow in importance if the climate change predicted comes about. Improved methods are needed to facilitate crop management via the prompt detection of the onset of stress. Here, we report the use of an in vivo OECT (organic electrochemical transistor) sensor, termed as bioristor, in the context of the drought response of the tomato plant. The device was integrated within the plant's stem, thereby allowing for the continuous monitoring of the plant's physiological status throughout its life cycle. Bioristor was able to detect changes of ion concentration in the sap upon drought, in particular, those dissolved and transported through the transpiration stream, thus efficiently detecting the occurrence of drought stress immediately after the priming of the defence responses. The bioristor's acquired data were coupled with those obtained in a high-throughput phenotyping platform revealing the extreme complementarity of these methods to investigate the mechanisms triggered by the plant during the drought stress event.

Mediterranean Green Roof Simulation in Caldes de Montbui (Barcelona): Thermal and Hydrological Performance Test of Frankenia laevis L., Dymondia margaretae Compton and Iris lutescens Lam

Green roofs provide a number of environmental advantages like increasing urban biodiversity, reducing pollution, easing burdens on drainage systems, and lowering energy costs thanks to thermal insulation. Frankenia laevis, Dymondia margaretae and Iris lutescens were tested in a green roof installation. For all three species, we assessed two minimal irrigation treatments and one rain-fed treatment to resemble Mediterranean climate conditions analyzing the thermal and hydrological performance of all three species and their substrates through an evaluation of green cover, mortality, and biomass. The most influential factors registered for all three species are the relationship between air and water in the substrate and the interaction between green cover and substrate, respectively, for summer and winter seasons. In particular, D. margaretae preserved more water in its substrate than the other species both in summer and winter and after each rainfall event. F. laevis registered the highest level of variation in terms of substrate water content and of rainwater retention. I. lutescens achieved low hydrological performance, a limited amount of green cover, and slow growth. Our results suggest the absolute need of additional irrigation, managed in accordance with specific functional objectives, for all three species analyzed under Mediterranean conditions and different water regime.

Genetic dissection of the mechanism of flowering time based on an environmentally stable and specific QTL in Brassica napus

Flowering time is an important agronomic trait that is highly influenced by the environment. To elucidate the genetic mechanism of flowering time in rapeseed (Brassica napus L.), a genome-wide QTL analysis was performed in a doubled haploid population grown in winter, semi-winter and spring ecological conditions. Fifty-five consensus QTLs were identified after combining phenotype and genomic data, including 12 environment-stable QTLs and 43 environment-specific QTLs. Importantly, six major QTLs for flowering time were identified, of which two were considered environment-specific QTLs in spring ecological condition and four were considered environment-stable QTLs in winter and semi-winter ecological conditions. Through QTL comparison, 18 QTLs were colocalized with QTLs from six other published studies. Combining the candidate genes with their functional annotation, in 49 of 55 consensus QTLs, 151 candidate genes in B. napus corresponding to 95 homologous genes in Arabidopsis thaliana related to flowering were identified, including BnaC03g32910D (CO), BnaA02g12130D (FT) and BnaA03g13630D (FLC). Most of the candidate genes were involved in different flowering regulatory pathways. Based on re-sequencing and differences in sequence annotation between the two parents, we found that regions containing some candidate genes have numerous non-frameshift InDels and many non- synonymous mutations, which might directly lead to gene functional variation. Flowering time was negativly correlated with seed yield and thousand seed weight based on a QTL comparison of flowering time and seed yield traits, which has implications in breeding new early-maturing varieties of B. napus. Moreover, a putative flowering regulatory network was constructed, including the photoperiod, circadian clock, vernalization, autonomous and gibberellin pathways. Multiple copies of genes led to functional difference among the different copies of homologous genes, which also increased the complexity of the flowering regulatory networks. Taken together, the present results not only provide new insights into the genetic regulatory network underlying the control of flowering time but also improve our understanding of flowering time regulatory pathways in rapeseed.

Quantification of Extent, Density, and Status of Aquatic Reed Beds Using Point Clouds Derived from UAV–RGB Imagery

Quantification of reed coverage and vegetation status is fundamental for monitoring and developing lake conservation strategies. The applicability of Unmanned Aerial Vehicles (UAV) three-dimensional data (point clouds) for status evaluation was investigated. This study focused on mapping extent, density, and vegetation status of aquatic reed beds. Point clouds were calculated with Structure from Motion (SfM) algorithms in aerial imagery recorded with Rotary Wing (RW) and Fixed Wing (FW) UAV. Extent was quantified by measuring the surface between frontline and shoreline. Density classification was based on point geometry (height and height variance) in point clouds. Spectral information per point was used for calculating a vegetation index and was used as indicator for vegetation vitality. Status was achieved by combining data on density, vitality, and frontline shape outputs. Field observations in areas of interest (AOI) and optical imagery were used for reference and validation purposes. A root mean square error (RMSE) of 1.58 m to 3.62 m for cross sections from field measurements and classification was achieved for extent map. The overall accuracy (OA) acquired for density classification was 88.6% (Kappa = 0.8). The OA for status classification of 83.3% (Kappa = 0.7) was reached by comparison with field measurements complemented by secondary Red, Green, Blue (RGB) data visual assessments. The research shows that complex transitional zones (water–vegetation–land) can be assessed and support the suitability of the applied method providing new strategies for monitoring aquatic reed bed using low-cost UAV imagery.

Sources for the breeding of soft spring wheat in the conditions of Novosibirsk region

The sources were identified among collection samples characterized by highly pronounced economic and valuable features, which allows new geographically remote source material to be taken to the regional breeding practices. This research aims to assess the agronomic traits (duration of the growing period, lodging resistance and plant height, 1000-grain weight, grain weight and yield) in soft spring wheat varieties of different ecological and geographical origin. Estimation was carried out by a 9-point system of expression of the trait during the study, which allows identifying samples with the greatest expression of the trait in the years of study with respect to the average experience. 5439 samples have been studied over 28 years, with 1106 of them, over two years or more. The study was carried out according to the methods of VIR on plots of 2 m2. It was shown that the samples mainly had no correlation between the yield and the duration of the growing period, while the average dependence (г = 0.6) was revealed between the yield and the height of the plants. Varieties forming the intermediate (4.5-5 points) and above average (6-7) yield in a short growing period (69-85 days) were identified (Lutescens 675, Irkut-skaya 49, Simbirca, Hybrid F3 S-141, Hybrid F4, Hybrid F3 S-289 and Hybrid F4 S-2300 and Pamyati Vavenko-va). A high average score (8.6-9) at 1000 grains weight was shown for 16 varieties with variation from 37 g (N43 and IAO-9) to 56 g (Hofed 1). A high average score (8-9) in the evaluation of grain weight was shown for Pamyati Leont'eva, Ekada 70, Simbirtsit, Don Jose, Yong-Liang 4 and Long-Mai 11, which formed ears with an average weight from 0.96 to 2.30 g. A consistently high score (9) reflecting the yield was in the varieties Condestavel, PF 843025, Prilenskaya 19, Pamyati Leont'eva, Omskaya Krasa.

Haplotype Loci Under Selection in Canadian Durum Wheat Germplasm Over 60 Years of Breeding: Association With Grain Yield, Quality Traits, Protein Loss, and Plant Height

Durum wheat was introduced in the southern prairies of western Canada in the late nineteenth century. Breeding efforts have mainly focused on improving quality traits to meet the pasta industry demands. For this study, 192 durum wheat lines were genotyped using the Illumina 90K Infinium iSelect assay, and resulted in a total of 14,324 polymorphic SNPs. Genetic diversity changed over time, declining during the first 20 years of breeding in Canada, then increased in the late 1980s and early 1990s. We scanned the genome for signatures of selection, using the total variance Fst-based outlier detection method (Lositan), the hierarchical island model (Arlequin) and the Bayesian genome scan method (BayeScan). A total of 407 outliers were identified and clustered into 84 LD-based haplotype loci, spanning all 14 chromosomes of the durum wheat genome. The association analysis detected 54 haplotype loci, of which 39% contained markers with a complete reversal of allelic state. This tendency to fixation of favorable alleles corroborates the success of the Canadian durum wheat breeding programs over time. Twenty-one haplotype loci were associated with multiple traits. In particular, hap_4B_1 explained 20.6, 17.9 and 16.6% of the phenotypic variance of pigment loss, pasta b∗ and dough extensibility, respectively. The locus hap_2B_9 explained 15.9 and 17.8% of the variation of protein content and protein loss, respectively. All these pleiotropic haplotype loci offer breeders the unique opportunity for further improving multiple traits, facilitating marker-assisted selection in durum wheat, and could help in identifying genes as functional annotations of the wheat genome become available.

Omics Approaches for Engineering Wheat Production under Abiotic Stresses

Abiotic stresses greatly influenced wheat productivity executed by environmental factors such as drought, salt, water submergence and heavy metals. The effective management at the molecular level is mandatory for a thorough understanding of plant response to abiotic stress. Understanding the molecular mechanism of stress tolerance is complex and requires information at the omic level. In the areas of genomics, transcriptomics and proteomics enormous progress has been made in the omics field. The rising field of ionomics is also being utilized for examining abiotic stress resilience in wheat. Omic approaches produce a huge amount of data and sufficient developments in computational tools have been accomplished for efficient analysis. However, the integration of omic-scale information to address complex genetics and physiological questions is still a challenge. Though, the incorporation of omic-scale data to address complex genetic qualities and physiological inquiries is as yet a challenge. In this review, we have reported advances in omic tools in the perspective of conventional and present day approaches being utilized to dismember abiotic stress tolerance in wheat. Attention was given to methodologies, for example, quantitative trait loci (QTL), genome-wide association studies (GWAS) and genomic selection (GS). Comparative genomics and candidate genes methodologies are additionally talked about considering the identification of potential genomic loci, genes and biochemical pathways engaged with stress resilience in wheat. This review additionally gives an extensive list of accessible online omic assets for wheat and its effective use. We have additionally addressed the significance of genomics in the integrated approach and perceived high-throughput multi-dimensional phenotyping as a significant restricting component for the enhancement of abiotic stress resistance in wheat.

Measuring the dynamic photosynthome

Background

Photosynthesis underpins plant productivity and yet is notoriously sensitive to small changes in environmental conditions, meaning that quantitation in nature across different time scales is not straightforward. The 'dynamic' changes in photosynthesis (i.e. the kinetics of the various reactions of photosynthesis in response to environmental shifts) are now known to be important in driving crop yield.

Scope

It is known that photosynthesis does not respond in a timely manner, and even a small temporal 'mismatch' between a change in the environment and the appropriate response of photosynthesis toward optimality can result in a fall in productivity. Yet the most commonly measured parameters are still made at steady state or a temporary steady state (including those for crop breeding purposes), meaning that new photosynthetic traits remain undiscovered.

Conclusions

There is a great need to understand photosynthesis dynamics from a mechanistic and biological viewpoint especially when applied to the field of 'phenomics' which typically uses large genetically diverse populations of plants. Despite huge advances in measurement technology in recent years, it is still unclear whether we possess the capability of capturing and describing the physiologically relevant dynamic features of field photosynthesis in sufficient detail. Such traits are highly complex, hence we dub this the 'photosynthome'. This review sets out the state of play and describes some approaches that could be made to address this challenge with reference to the relevant biological processes involved.

Adaptive selection of founder segments and epistatic control of plant height in the MAGIC winter wheat population WM-800

BACKGROUND

Multi-parent advanced generation intercross (MAGIC) populations are a newly established tool to dissect quantitative traits. We developed the high resolution MAGIC wheat population WM-800, consisting of 910 F4:6 lines derived from intercrossing eight recently released European winter wheat cultivars.

RESULTS

Genotyping WM-800 with 7849 SNPs revealed a low mean genetic similarity of 59.7% between MAGIC lines. WM-800 harbours distinct genomic regions exposed to segregation distortion. These are mainly located on chromosomes 2 to 6 of the wheat B genome where founder specific DNA segments were positively or negatively selected. This suggests adaptive selection of individual founder alleles during population development. The application of a genome-wide association study identified 14 quantitative trait loci (QTL) controlling plant height in WM-800, including the known semi-dwarf genes Rht-B1 and Rht-D1 and a potentially novel QTL on chromosome 5A. Additionally, epistatic effects controlled plant height. For example, two loci on chromosomes 2B and 7B gave rise to an additive epistatic effect of 13.7 cm.

CONCLUSION

The present study demonstrates that plant height in the MAGIC-WHEAT population WM-800 is mainly determined by large-effect QTL and di-genic epistatic interactions. As a proof of concept, our study confirms that WM-800 is a valuable tool to dissect the genetic architecture of important agronomic traits.

Plant Phenomics, From Sensors to Knowledge

Major improvements in crop yield are needed to keep pace with population growth and climate change. While plant breeding efforts have greatly benefited from advances in genomics, profiling the crop phenome (i.e., the structure and function of plants) associated with allelic variants and environments remains a major technical bottleneck. Here, we review the conceptual and technical challenges facing plant phenomics. We first discuss how, given plants' high levels of morphological plasticity, crop phenomics presents distinct challenges compared with studies in animals. Next, we present strategies for multi-scale phenomics, and describe how major improvements in imaging, sensor technologies and data analysis are now making high-throughput root, shoot, whole-plant and canopy phenomic studies possible. We then suggest that research in this area is entering a new stage of development, in which phenomic pipelines can help researchers transform large numbers of images and sensor data into knowledge, necessitating novel methods of data handling and modelling. Collectively, these innovations are helping accelerate the selection of the next generation of crops more sustainable and resilient to climate change, and whose benefits promise to scale from physiology to breeding and to deliver real world impact for ongoing global food security efforts.

Effect of Ppd-A1 and Ppd-B1 Allelic Variants on Grain Number and Thousand Kernel Weight of Durum Wheat and Their Impact on Final Grain Yield

The main yield components in durum wheat are grain number per unit area (GN) and thousand kernel weight (TKW), both of which are affected by environmental conditions. The most critical developmental stage for their determination is flowering time, which partly depends on photoperiod sensitivity genes at Ppd-1 loci. Fifteen field experiments, involving 23 spring durum wheat genotypes containing all known allelic variants at the PHOTOPERIOD RESPONSE LOCUS (Ppd-A1 and Ppd-B1) were carried out at three sites at latitudes ranging from 41° to 27° N (Spain, Mexico-north, and Mexico-south, the latter in spring planting). Allele GS100 at Ppd-A1, which causes photoperiod insensitivity and results in early-flowering genotypes, tended to increase TKW and yield, albeit not substantially. Allele Ppd-B1a, also causing photoperiod insensitivity, did not affect flowering time or grain yield. Genotypes carrying the Ppd-B1b allele conferring photoperiod sensitivity had consistently higher GN, which did not translate into higher yield due to under-compensation in TKW. This increased GN was due to a greater number of grains spike-1 as a result of a higher number of spikelets spike-1. Daylength from double ridge to terminal spikelet stage was strongly and positively associated with the number of spikelets spike-1 in Spain. This association was not found in the Mexico sites, thereby indicating that Ppd-B1b had an intrinsic effect on spikelets spike-1 independently of environmental cues. Our results suggest that, in environments where yield is limited by the incapacity to produce a high GN, selecting for Ppd-B1b may be advisable.

The physiological and genetic basis of combined drought and heat tolerance in wheat

Drought and heat stress cause losses in wheat productivity in major growing regions worldwide, and both the occurrence and the severity of these events are likely to increase with global climate change. Water deficits and high temperatures frequently occur simultaneously at sensitive growth stages, reducing wheat yields by reducing grain number or weight. Although genetic variation and underlying quantitative trait loci for either individual stress are known, the combination of the two stresses has rarely been studied. Complex and often antagonistic physiology means that genetic loci underlying tolerance to the combined stress are likely to differ from those for drought or heat stress tolerance alone. Here, we review what is known of the physiological traits and genetic control of drought and heat tolerance in wheat and discuss potential physiological traits to study for combined tolerance. We further place this knowledge in the context of breeding for new, more tolerant varieties and discuss opportunities and constraints. We conclude that a fine control of water relations across the growing cycle will be beneficial for combined tolerance and might be achieved through fine management of spatial and temporal gas exchange.

Simultaneous improvement of grain yield and protein content in durum wheat by different phenotypic indices and genomic selection

Simultaneous improvement of protein content and grain yield by index selection is possible but its efficiency largely depends on the weighting of the single traits. The genetic architecture of these indices is similar to that of the primary traits. Grain yield and protein content are of major importance in durum wheat breeding, but their negative correlation has hampered their simultaneous improvement. To account for this in wheat breeding, the grain protein deviation (GPD) and the protein yield were proposed as targets for selection. The aim of this work was to investigate the potential of different indices to simultaneously improve grain yield and protein content in durum wheat and to evaluate their genetic architecture towards genomics-assisted breeding. To this end, we investigated two different durum wheat panels comprising 159 and 189 genotypes, which were tested in multiple field locations across Europe and genotyped by a genotyping-by-sequencing approach. The phenotypic analyses revealed significant genetic variances for all traits and heritabilities of the phenotypic indices that were in a similar range as those of grain yield and protein content. The GPD showed a high and positive correlation with protein content, whereas protein yield was highly and positively correlated with grain yield. Thus, selecting for a high GPD would mainly increase the protein content whereas a selection based on protein yield would mainly improve grain yield, but a combination of both indices allows to balance this selection. The genome-wide association mapping revealed a complex genetic architecture for all traits with most QTL having small effects and being detected only in one germplasm set, thus limiting the potential of marker-assisted selection for trait improvement. By contrast, genome-wide prediction appeared promising but its performance strongly depends on the relatedness between training and prediction sets.

Land-based crop phenotyping by image analysis: consistent canopy characterization from inconsistent field illumination

BACKGROUND

One of the main challenges associated with image-based field phenotyping is the variability of illumination. During a single day's imaging session, or between different sessions on different days, the sun moves in and out of cloud cover and has varying intensity. How is one to know from consecutive images alone if a plant has become darker over time, or if the weather conditions have simply changed from clear to overcast? This is a significant problem to address as colour is an important phenotypic trait that can be measured automatically from images.

RESULTS

In this work we use an industry standard colour checker to balance the colour in images within and across every day of a field trial conducted over four months in 2016. By ensuring that the colour checker is present in every image we are afforded a 'ground truth' to correct for varying illumination conditions across images. We employ a least squares approach to fit a quadratic model for correcting RGB values of an image in such a way that the observed values of the colour checker tiles align with their true values after the transformation.

CONCLUSIONS

The proposed method is successful in reducing the error between observed and reference colour chart values in all images. Furthermore, the standard deviation of mean canopy colour across multiple days is reduced significantly after colour correction is applied. Finally, we use a number of examples to demonstrate the usefulness of accurate colour measurements in recording phenotypic traits and analysing variation among varieties and treatments.