Phenotyping approaches for physiological breeding and gene discovery in wheat

Aeluropus littoralis stress-associated protein promotes water deficit resilience in engineered durum wheat

Global climate change-related water deficit negatively affect the growth, development and yield performance of multiple cereal crops, including durum wheat. Therefore, the improvement of water-deficit stress tolerance in durum wheat varieties in arid and semiarid areas has become imperative for food security. Herein, we evaluated the water deficiency resilience potential of two marker-free transgenic durum wheat lines (AlSAP-lines: K9.3 and K21.3) under well-watered and water-deficit stress conditions at both physiological and agronomic levels. These two lines overexpressed the AlSAP gene, isolated from the halophyte grass Aeluropus littoralis, encoding a stress-associated zinc finger protein containing the A20/AN1 domains. Under well-watered conditions, the wild-type (WT) and both AlSAP-lines displayed comparable performance concerning all the evaluated parameters. Ectopic transgene expression exerted no adverse effects on growth and yield performance of the durum wheat plants. Under water-deficit conditions, no significant differences in the plant height, leaf number, spike length, and spikelet number were observed between AlSAP-lines and WT plants. However, compared to WT, the AlSAP-lines exhibited greater dry matter production, greater flag leaf area, improved net photosynthetic rate, stomatal conductance, and water use efficiency. Notably, the AlSAP-lines displayed 25 % higher grain yield (GY) than the WT plants under water-deficit conditions. The RT-qPCR-based selected stress-related gene (TdDREB1, TdLEA, TdAPX1, and TdBlt101-2) expression analyses indicated stress-related genes enhancement in AlSAP-durum wheat plants under both well-watered and water-deficit conditions, potentially related to the water-deficit resilience. Collectively, our findings support that the ectopic AlSAP expression in durum wheat lines enhances water-deficit resilience ability, thereby potentially compensate for the GY loss in arid and semi-arid regions.

Phenotyping of Potato Plants Using Morphological and Physiological Tools

Potato (Solanum tuberosum L.) is one of the main non-grain agricultural crops and one of the main sources of food for humanity. Currently, growing potatoes requires new approaches and methods for cultivation and breeding. Phenotyping is one of the important tools for assessing the characteristics of a potato variety. In this work, 29 potato varieties of different ripeness groups were studied. Linear leaf dimensions, leaf mass area, number of stems, number of tubers per plant, average tuber weight, signs of virus infection, dry weight, pigment content, and number of stomata per unit leaf area were used as phenotyping tools. The strongest positive relationship was found between yield and bush area in the stage of full shoots (R = 0.77, p = 0.001), linear dimensions of a complex leaf (R = 0.44, p = 0.002; R = 0.40, p = 0.003), number of stems (R = 0.36, p = 0.05), and resistance to viruses X (R = 0.42, p = 0.03) and S (R = 0.43, p = 0.02). An inverse relationship was found between growth dynamics and yield (R = -0.29, p = 0.05). Thus, the use of morphological and physiological phenotyping tools in the field is informative for predicting key agricultural characteristics such as yield and/or stress resistance.

The crucial role of lateral root angle in enhancing drought resilience in cotton

Introduction

Plant responses to drought stress are influenced by various factors, including the lateral root angle (LRA), stomatal regulation, canopy temperature, transpiration rate and yield. However, there is a lack of research that quantifies their interactions, especially among different cotton varieties.

Methods

This experiment included two water treatments: well-watered (75 ± 5% soil relative water content) and drought stress (50 ± 5% soil relative water content) starting from the three-leaf growth stage.

Results

The results revealed that different LRA varieties show genetic variation under drought stress. Among them, varieties with smaller root angles show greater drought tolerance. Varieties with smaller LRAs had significantly increased stomatal opening by 15% to 43%, transpiration rate by 61.24% and 62.00%, aboveground biomass by 54% to 64%, and increased seed cotton yield by 76% to 79%, and decreased canopy temperature by 9% to 12% under drought stress compared to the larger LRAs. Varieties with smaller LRAs had less yield loss under drought stress, which may be due to enhanced access to deeper soil water, compensating for heightened stomatal opening and elevated transpiration rates. The increase in transpiration rate promotes heat dissipation from leaves, thereby reducing leaf temperature and protecting leaves from damage.

Discussion

Demonstrating the advantages conferred by the development of a smaller LRA under drought stress conditions holds value in enhancing cotton's resilience and promoting its sustainable adaptation to abiotic stressors.

Genomic regions of durum wheat involved in water productivity

Durum wheat is a staple food in the Mediterranean Basin, mostly cultivated under rainfed conditions. As such, the crop is often exposed to moisture stress. Therefore, the identification of genetic factors controlling the capacity of genotypes to convert moisture into grain yield (i.e., water productivity) is quintessential to stabilize production despite climatic variations. A global panel of 384 accessions was tested across 18 Mediterranean environments (in Morocco, Lebanon, and Jordan) representing a vast range of moisture levels. The accessions were assigned to water responsiveness classes, with genotypes 'Responsive to Low Moisture' reaching an average +1.5 kg ha-1 mm-1 yield advantage. Genome wide association studies revealed that six loci explained most of this variation. A second validation panel tested under moisture stress confirmed that carrying the positive allele at three loci on chromosomes 1B, 2A, and 7B generated an average water productivity gain of +2.2 kg ha-1 mm-1. These three loci were tagged by kompetitive allele specific PCR (KASP) markers, and these were used to screen a third independent validation panel composed of elites tested across moisture stressed sites. The three KASP combined predicted up to 10% of the variation for grain yield at 60% accuracy. These loci are now ready for molecular pyramiding and transfer across cultivars to improve the moisture conversion of durum wheat.

Canopy Structure, Light Intensity, Temperature and Photosynthetic Performance of Winter Wheat under Different Irrigation Conditions

A high-quality canopy architecture is central to obtaining high crop yields. A field experiment was carried out at the Wuqiao Experimental Station from 2015 to 2019 under four irrigation schemes (W0, no irrigation after sowing; W1, 75 mm irrigation at jointing stage; W2, 75 mm irrigation at jointing and anthesis stages, respectively; W3, 75 mm irrigation at tillering, jointing and anthesis stages, respectively) to investigate the canopy structure, canopy apparent photosynthesis (CAP), canopy temperature (CT), yield and water use efficiency (WUE). The results showed that increasing irrigation times improved the leaf area index (LAI), non-leaf area index (NLAI) and light interception (LI) of the spike and total canopy but decreased the canopy temperature (CT) after anthesis. The CAP in the W3 treatment was consistently lower than that in the W1 treatment, suggesting lower effective utilization of light energy under the W3 treatment. Increasing irrigation times improved wheat yield, but the W2 treatment had no significant difference in yield compared to the W3 treatment. In addition, the W1 and W2 treatments had higher WUEs. The CT, organ temperature and LI were closely positively associated with each other, but they were all strongly negatively related to the yield. Overall, the W2 treatment was the best irrigation scheme for constructing a reasonable canopy architecture for winter wheat, obtaining more efficient water use and yield in the North China Plain (NCP). CT and organ temperature can be used as proxy parameters to estimate the canopy structure.

Defining durum wheat ideotypes adapted to Mediterranean environments through remote sensing traits

An acceleration of the genetic advances of durum wheat, as a major crop for the Mediterranean region, is required, but phenotyping still represents a bottleneck for breeding. This study aims to define durum wheat ideotypes under Mediterranean conditions by selecting the most suitable phenotypic remote sensing traits among different ones informing on characteristics related with leaf pigments/photosynthetic status, crop water status, and crop growth/green biomass. A set of 24 post-green revolution durum wheat cultivars were assessed in a wide set of 19 environments, accounted as the specific combinations of a range of latitudes in Spain, under different management conditions (water regimes and planting dates), through 3 consecutive years. Thus, red-green-blue and multispectral derived vegetation indices and canopy temperature were evaluated at anthesis and grain filling. The potential of the assessed remote sensing parameters alone and all combined as grain yield (GY) predictors was evaluated through random forest regression models performed for each environment and phenological stage. Biomass and plot greenness indicators consistently proved to be reliable GY predictors in all of the environments tested for both phenological stages. For the lowest-yielding environment, the contribution of water status measurements was higher during anthesis, whereas, for the highest-yielding environments, better predictions were reported during grain filling. Remote sensing traits measured during the grain filling and informing on pigment content and photosynthetic capacity were highlighted under the environments with warmer conditions, as the late-planting treatments. Overall, canopy greenness indicators were reported as the highest correlated traits for most of the environments and regardless of the phenological moment assessed. The addition of carbon isotope composition of mature kernels was attempted to increase the accuracies, but only a few were slightly benefited, as differences in water status among cultivars were already accounted by the measurement of canopy temperature.

Nitrogen control of transpiration in grapevine

Transpiration per unit of leaf area is the end-product of the root-to-leaf water transport within the plant, and it is regulated by a series of morpho-physiological resistances and hierarchical signals. The rate of water transpired sustains a series of processes such as nutrient absorption and leaf evaporative cooling, with stomata being the end-valves that maintain the optimal water loss under specific degrees of evaporative demand and soil moisture conditions. Previous work provided evidence of a partial modulation of water flux following nitrogen availability linking high nitrate availability with tight stomatal control of transpiration in several species. In this work, we tested the hypothesis that stomatal control of transpiration, among others signals, is partially modulated by soil nitrate ( NO 3 - ) availability in grapevine, with reduced NO 3 - availability (alkaline soil pH, reduced fertilization, and distancing NO 3 - source) associated with decreased water-use efficiency and higher transpiration. We observed a general trend when NO 3 - was limiting with plants increasing either stomatal conductance or root-shoot ratio in four independent experiments with strong associations between leaf water status, stomatal behavior, root aquaporins expression, and xylem sap pH. Carbon and oxygen isotopic signatures confirm the proximal measurements, suggesting the robustness of the signal that persists over weeks and under different gradients of NO 3 - availability and leaf nitrogen content. Nighttime stomatal conductance was unaffected by NO 3 - manipulation treatments, while application of high vapor pressure deficit conditions nullifies the differences between treatments. Genotypic variation for transpiration increase under limited NO 3 - availability was observed between rootstocks indicating that breeding (e.g., for high soil pH tolerance) unintentionally selected for enhanced mass flow nutrient acquisition under restrictive or nutrient-buffered conditions. We provide evidence of a series of specific traits modulated by NO 3 - availability and suggest that NO 3 - fertilization is a potential candidate for optimizing grapevine water-use efficiency and root exploration under the climate-change scenario.

Mechanistic modeling reveals the importance of turgor-driven apoplastic water transport in wheat stem parenchyma during carbohydrate mobilization

During stem elongation, wheat (Triticum aestivum) increases its stem carbohydrate content before anthesis as a reserve for grain filling. Hydraulic functioning during this mobilization process is not well understood, and contradictory results exist on the direct effect of drought on carbohydrate mobilization. In a dedicated experiment, wheat plants were subjected to drought stress during carbohydrate mobilization. Measurements, important to better understand stem physiology, showed some unexpected patterns that could not be explained by our current knowledge on water transport. Traditional water flow and storage models failed to properly describe the drought response in wheat stems during carbohydrate mobilization. To explain the measured patterns, hypotheses were formulated and integrated in a dedicated model for wheat. The new mechanistic model simulates two hypothetical water storage compartments: one where water is quickly exchanged with the xylem and one that contains the carbohydrate storage. Water exchange between these compartments is turgor-driven. The model was able to simulate the measured increase in stored carbohydrate concentrations with a decrease in water content and stem diameter. Calibration of the model showed the importance of turgor-driven apoplastic water flow during carbohydrate mobilization. This resulted in an increase in stem hydraulic capacitance, which became more important under drought stress.

Canopy spectral reflectance indices correlate with yield traits variability in bread wheat genotypes under drought stress

Drought stress is a major issue impacting wheat growth and yield worldwide, and it is getting worse as the world's climate changes. Thus, selection for drought-adaptive traits and drought-tolerant genotypes are essential components in wheat breeding programs. The goal of this study was to explore how spectral reflectance indices (SRIs) and yield traits in wheat genotypes changed in irrigated and water-limited environments. In two wheat-growing seasons, we evaluated 56 preselected wheat genotypes for SRIs, stay green (SG), canopy temperature depression (CTD), biological yield (BY), grain yield (GY), and yield contributing traits under control and drought stress, and the SRIs and yield traits exhibited higher heritability (H²) across the growing years. Diverse SRIs associated with SG, pigment content, hydration status, and aboveground biomass demonstrated a consistent response to drought and a strong association with GY. Under drought stress, GY had stronger phenotypic correlations with SG, CTD, and yield components than in control conditions. Three primary clusters emerged from the hierarchical cluster analysis, with cluster I (15 genotypes) showing minimal changes in SRIs and yield traits, indicating a relatively higher level of drought tolerance than clusters II (26 genotypes) and III (15 genotypes). The genotypes were appropriately assigned to distinct clusters, and linear discriminant analysis (LDA) demonstrated that the clusters differed significantly. It was found that the top five components explained 73% of the variation in traits in the principal component analysis, and that vegetation and water-based indices, as well as yield traits, were the most important factors in explaining genotypic drought tolerance variation. Based on the current study's findings, it can be concluded that proximal canopy reflectance sensing could be used to screen wheat genotypes for drought tolerance in water-starved environments.

Lipidomics-Assisted GWAS (lGWAS) Approach for Improving High-Temperature Stress Tolerance of Crops

High-temperature stress (HT) over crop productivity is an important environmental factor demanding more attention as recent global warming trends are alarming and pose a potential threat to crop production. According to the Sixth IPCC report, future years will have longer warm seasons and frequent heat waves. Thus, the need arises to develop HT-tolerant genotypes that can be used to breed high-yielding crops. Several physiological, biochemical, and molecular alterations are orchestrated in providing HT tolerance to a genotype. One mechanism to counter HT is overcoming high-temperature-induced membrane superfluidity and structural disorganizations. Several HT lipidomic studies on different genotypes have indicated the potential involvement of membrane lipid remodelling in providing HT tolerance. Advances in high-throughput analytical techniques such as tandem mass spectrometry have paved the way for large-scale identification and quantification of the enormously diverse lipid molecules in a single run. Physiological trait-based breeding has been employed so far to identify and select HT tolerant genotypes but has several disadvantages, such as the genotype-phenotype gap affecting the efficiency of identifying the underlying genetic association. Tolerant genotypes maintain a high photosynthetic rate, stable membranes, and membrane-associated mechanisms. In this context, studying the HT-induced membrane lipid remodelling, resultant of several up-/down-regulations of genes and post-translational modifications, will aid in identifying potential lipid biomarkers for HT tolerance/susceptibility. The identified lipid biomarkers (LIPIDOTYPE) can thus be considered an intermediate phenotype, bridging the gap between genotype–phenotype (genotype–LIPIDOTYPE–phenotype). Recent works integrating metabolomics with quantitative genetic studies such as GWAS (mGWAS) have provided close associations between genotype, metabolites, and stress-tolerant phenotypes. This review has been sculpted to provide a potential workflow that combines MS-based lipidomics and the robust GWAS (lipidomics assisted GWAS-lGWAS) to identify membrane lipid remodelling related genes and associations which can be used to develop HS tolerant genotypes with enhanced membrane thermostability (MTS) and heat stable photosynthesis (HP).

Rhizoctonia Resistance Is Negatively Correlated to Early Root Growth Rate in Synthetic Hexaploid Wheat Derivatives

Resistance to the soilborne fungal pathogen Rhizoctonia solani AG-8 is desirable in adapted wheat and barley but remains an elusive trait for prebreeders and breeders. In a previous study, we observed that emergence and root growth was faster in the Rhizoctonia-susceptible 'Scarlet' than in its resistant counterpart, 'Scarlet-Rz1'. The objective of the current study was to quantify early root growth rate and total root length in resistant and susceptible synthetic hexaploid wheat lines, including parental lines and 22 recombinant inbred lines derived crosses between parental lines. In Petri dish assays, the susceptible lines displayed a faster rate of root growth during the first 40 h of root emergence compared with resistant lines. This growth differential was observed in 14-day and 48-h greenhouse assays, in which the total root length of susceptible parental lines was significantly (P < 0.05) greater than that of resistant parental lines. However, the resistant lines sustained less root loss compared with susceptible lines when R. solani AG-8 was present in the soil. Early root growth rate and total root length were not correlated to freezing tolerance in a set of wheat cultivars selected for cold tolerance. The findings indicated that early root growth was negatively correlated to R. solani AG-8 damage in resistant synthetic wheat lines developed for the Pacific Northwest, United States, and suggested that the dynamics of root emergence affect resistance to this soilborne pathogen.

Identification and Validation of a Chromosome 4D Quantitative Trait Locus Hotspot Conferring Heat Tolerance in Common Wheat (Triticum aestivum L.)

Understanding of the genetic mechanism of heat tolerance (HT) can accelerate and improve wheat breeding in dealing with a warming climate. This study identified and validated quantitative trait loci (QTL) responsible for HT in common wheat. The International Triticeae Mapping Initiative (ITMI) population, recombinant inbreed lines (RILs) derived from a cross between Synthetic W7984 and Opata M85, was phenotyped for shoot length, root length, whole plant length under heat stress and corresponding damage indices (DIs) to compare HT performances of individuals. Wide variations among the RILs were shown for all the traits. A total of 13 QTL including 9 major QTL and 4 minor QTL were identified, distributed on 6 wheat chromosomes. The six major QTL with the highest R² were associated with different traits under heat stress. They were all from Opata M85 background and located within a 2.2 cm interval on chromosome 4D, making up a QTL hotspot conferring HT in common wheat. The QTL hotspot was validated by genotyping-phenotyping association analysis using single-nucleotide-polymorphism (SNP) assays. The QTL, especially the 4D QTL hotspot identified and validated in this study, are valuable for the further fine mapping and identification of key genes and exploring genetic mechanism of HT in wheat.

Genetic analysis and marker association of physiological traits under rainfed and heat stress conditions in spring wheat (Triticum aestivum L.)

Identifying gene interactions and markers associated with physiological traits, especially at later stages of grain filling, can help develop effective breeding methodology in wheat crop. Six generations (P1, P2, F1, F2, BC1P1 and BC1P2) of four different spring wheat crosses (drought-responsive x drought susceptible) and F3 generation of a single cross, i.e., MACS6272 x UP2828 were phenotyped and genotyped to decipher gene action and associated markers. Ample variation in canopy temperature depression (CTD - 2.6 - 5.6?C), chlorophyll content by SPAD (39.6 - 51.3), relative water content (RWC - 51.5 - 75.4 %), grain filling period (GFP - 61.1 - 80.1 days), 100 seed weight (3.7 - 5.5 grams), harvest index (HI - 25.8 - 46.2 %), biological yield (BY - 35.5 - 89.8 grams) and grain yield (GY - 13.4 - 36.5 grams) per plant were observed in six generations. GY positively correlated with CTD, SPAD, 100SW, BY and HI (0.08* - 0.85**). BY had the maximum direct (0.82) and indirect effect via other traits on GY. Significant non-additive epistatic interactions (j & l) and duplicate gene action were found for most traits except GFP and 100SW. Seven different SSR markers associated with CTD, SPAD, NDVI, RWC, 100SW, and explained phenotypic variation (PVE) ranging from 10.1% to 18.4%, with marker Xcfd35 explaining highest PVE for RWC. The identified candidate genes (in silico) belonged to transmembrane proteins (Xcfd32, Xcfd50), nucleic acid binding domains (Xbarc124, Xgwm484) and having enzymatic activity (Xcfd35, Xwmc47, Xwmc728) important for abiotic stress tolerance. Complex inheritance deciphered by six generations indicated delaying the selection to later stages of segregation so that useful transgressive segregants can be selected for improving grain yields in wheat.

Challenges for a Massive Implementation of Phenomics in Plant Breeding Programs

Due to climate change and expected food shortage in the coming decades, not only will it be necessary to develop cultivars with greater tolerance to environmental stress, but it is also imperative to reduce breeding cycle time. In addition to yield evaluation, plant breeders resort to many sensory assessments and some others of intermediate complexity. However, to develop cultivars better adapted to current/future constraints, it is necessary to incorporate a new set of traits, such as morphophysiological and physicochemical attributes, information relevant to the successful selection of genotypes or parents. Unfortunately, because of the large number of genotypes to be screened, measurements with conventional equipment are unfeasible, especially under field conditions. High-throughput plant phenotyping (HTPP) facilitates collecting a significant amount of data quickly; however, it is necessary to transform all this information (e.g., plant reflectance) into helpful descriptors to the breeder. To the extent that a holistic characterization of the plant (phenomics) is performed in challenging environments, it will be possible to select the best genotypes (forward phenomics) objectively but also understand why the said individual differs from the rest (reverse phenomics). Unfortunately, several elements had prevented phenomics from developing as desired. Consequently, a new set of prediction/validation methodologies, seasonal ambient information, and the fusion of data matrices (e.g., genotypic and phenotypic information) need to be incorporated into the modeling. In this sense, for the massive implementation of phenomics in plant breeding, it will be essential to count an interdisciplinary team that responds to the urgent need to release material with greater capacity to tolerate environmental stress. Therefore, breeding programs should (i) be more efficient (e.g., early discarding of unsuitable material), (ii) have shorter breeding cycles (fewer crosses to achieve the desired cultivar), and (iii) be more productive, increasing the probability of success at the end of the breeding process (percentage of cultivars released to the number of initial crosses).

Improving Wheat Yield Prediction Using Secondary Traits and High-Density Phenotyping Under Heat-Stressed Environments

A primary selection target for wheat (Triticum aestivum) improvement is grain yield. However, the selection for yield is limited by the extent of field trials, fluctuating environments, and the time needed to obtain multiyear assessments. Secondary traits such as spectral reflectance and canopy temperature (CT), which can be rapidly measured many times throughout the growing season, are frequently correlated with grain yield and could be used for indirect selection in large populations particularly in earlier generations in the breeding cycle prior to replicated yield testing. While proximal sensing data collection is increasingly implemented with high-throughput platforms that provide powerful and affordable information, efficient and effective use of these data is challenging. The objective of this study was to monitor wheat growth and predict grain yield in wheat breeding trials using high-density proximal sensing measurements under extreme terminal heat stress that is common in Bangladesh. Over five growing seasons, we analyzed normalized difference vegetation index (NDVI) and CT measurements collected in elite breeding lines from the International Maize and Wheat Improvement Center at the Regional Agricultural Research Station, Jamalpur, Bangladesh. We explored several variable reduction and regularization techniques followed by using the combined secondary traits to predict grain yield. Across years, grain yield heritability ranged from 0.30 to 0.72, with variable secondary trait heritability (0.0-0.6), while the correlation between grain yield and secondary traits ranged from -0.5 to 0.5. The prediction accuracy was calculated by a cross-fold validation approach as the correlation between observed and predicted grain yield using univariate and multivariate models. We found that the multivariate models resulted in higher prediction accuracies for grain yield than the univariate models. Stepwise regression performed equal to, or better than, other models in predicting grain yield. When incorporating all secondary traits into the models, we obtained high prediction accuracies (0.58-0.68) across the five growing seasons. Our results show that the optimized phenotypic prediction models can leverage secondary traits to deliver accurate predictions of wheat grain yield, allowing breeding programs to make more robust and rapid selections.

High-resolution spectral information enables phenotyping of leaf epicuticular wax in wheat

BACKGROUND

Epicuticular wax (EW) is the first line of defense in plants for protection against biotic and abiotic factors in the environment. In wheat, EW is associated with resilience to heat and drought stress, however, the current limitations on phenotyping EW restrict the integration of this secondary trait into wheat breeding pipelines. In this study we evaluated the use of light reflectance as a proxy for EW load and developed an efficient indirect method for the selection of genotypes with high EW density.

RESULTS

Cuticular waxes affect the light that is reflected, absorbed and transmitted by plants. The narrow spectral regions statistically associated with EW overlap with bands linked to photosynthetic radiation (500 nm), carotenoid absorbance (400 nm) and water content (~ 900 nm) in plants. The narrow spectral indices developed predicted 65% (EWI-13) and 44% (EWI-1) of the variation in this trait utilizing single-leaf reflectance. However, the normalized difference indices EWI-4 and EWI-9 improved the phenotyping efficiency with canopy reflectance across all field experimental trials. Indirect selection for EW with EWI-4 and EWI-9 led to a selection efficiency of 70% compared to phenotyping with the chemical method. The regression model EWM-7 integrated eight narrow wavelengths and accurately predicted 71% of the variation in the EW load (mg·dm-2) with leaf reflectance, but under field conditions, a single-wavelength model consistently estimated EW with an average RMSE of 1.24 mg·dm-2 utilizing ground and aerial canopy reflectance.

CONCLUSIONS

Overall, the indices EWI-1, EWI-13 and the model EWM-7 are reliable tools for indirect selection for EW based on leaf reflectance, and the indices EWI-4, EWI-9 and the model EWM-1 are reliable for selection based on canopy reflectance. However, further research is needed to define how the background effects and geometry of the canopy impact the accuracy of these phenotyping methods.

Breeding for drought and heat tolerance in wheat

Many approaches have been adopted to enhance the heat and drought tolerance of wheat with mixed success. An assessment of the relative merits of different strategies is presented. Wheat is the most widely grown crop globally and plays a key role in human nutrition. However, it is grown in environments that are prone to heat and drought stress, resulting in severely reduced yield in some seasons. Increased climate variability is expected to have a particularly adverse effect of wheat production. Breeding for stable yield across both good and bad seasons while maintaining high yield under optimal conditions is a high priority for most wheat breeding programs and has been a focus of research activities. Multiple strategies have been explored to enhance the heat and drought tolerance of wheat including extensive genetic analysis and modify the expression of genes involved in stress responses, targeting specific physiological traits and direct selection under a range of stress scenarios. These approaches have been combined with improvements in phenotyping, the development of genetic and genomic resources, and extended screening and analysis techniques. The results have greatly expanded our knowledge and understanding of the factors that influence yield under stress, but not all have delivered the hoped-for progress. Here, we provide an overview of the different strategies and an assessment of the most promising approaches.

Combining Genetic and Multidimensional Analyses to Identify Interpretive Traits Related to Water Shortage Tolerance as an Indirect Selection Tool for Detecting Genotypes of Drought Tolerance in Wheat Breeding

Water shortages have direct adverse effects on wheat productivity and growth worldwide, vertically and horizontally. Productivity may be promoted using water shortage-tolerant wheat genotypes. High-throughput tools have supported plant breeders in increasing the rate of stability of the genetic gain of interpretive traits for wheat productivity through multidimensional technical methods. We used 27 agrophysiological interpretive traits for grain yield (GY) of 25 bread wheat genotypes under water shortage stress conditions for two seasons. Genetic parameters and multidimensional analyses were used to identify genetic and phenotypic variations of the wheat genotypes used, combining these strategies effectively to achieve a balance. Considerable high genotypic variations were observed for 27 traits. Eleven interpretive traits related to GY had combined high heritability (h2 > 60%) and genetic gain (>20%), compared to GY, which showed moderate values both for heritability (57.60%) and genetic gain (16.89%). It was determined that six out of eleven traits (dry leaf weight (DLW), canopy temperature (CT), relative water content (RWC), flag leaf area (FLA), green leaves area (GLA) and leaf area index (LAI)) loaded the highest onto PC1 and PC2 (with scores of >0.27), and five of them had a positive trend with GY, while the CT trait had a negative correlation determined by principal component analysis (PCA). Genetic parameters and multidimensional analyses (PCA, stepwise regression, and path coefficient) showed that CT, RWC, GLA, and LAI were the most important interpretive traits for GY. Selection based on these four interpretive traits might improve genetic gain for GY in environments that are vulnerable to water shortages. The membership index and clustering analysis based on these four traits were significantly correlated, with some deviation, and classified genotypes into five groups. Highly tolerant, tolerant, intermediate, sensitive and highly sensitive clusters represented six, eight, two, three and six genotypes, respectively. The conclusions drawn from the membership index and clustering analysis, signifying that there were clear separations between the water shortage tolerance groups, were confirmed through discriminant analysis. MANOVA indicated that there were considerable variations between the five water shortage tolerance groups. The tolerated genotypes (DHL02, DHL30, DHL26, Misr1, Pavone-76 and DHL08) can be recommended as interesting new genetic sources for water shortage-tolerant wheat breeding programs.

Genetic regulation of the traits contributing to wheat nitrogen use efficiency

High nitrogen application aimed at increasing crop yield is offset by higher production costs and negative environmental consequences. For wheat, only one third of the applied nitrogen is utilized, which indicates there is scope for increasing Nitrogen Use Efficiency (NUE). However, achieving greater NUE is challenged by the complexity of the trait, which comprises processes associated with nitrogen uptake, transport, reduction, assimilation, translocation and remobilization. Thus, knowledge of the genetic regulation of these processes is critical in increasing NUE. Although primary nitrogen uptake and metabolism-related genes have been well studied, the relative influence of each towards NUE is not fully understood. Recent attention has focused on engineering transcription factors and identification of miRNAs acting on expression of specific genes related to NUE. Knowledge obtained from model species needs to be translated into wheat using recently-released whole genome sequences, and by exploring genetic variations of NUE-related traits in wild relatives and ancient germplasm. Recent findings indicate the genetic basis of NUE is complex. Pyramiding various genes will be the most effective approach to achieve a satisfactory level of NUE in the field.

Agro-Physiologic Responses and Stress-Related Gene Expression of Four Doubled Haploid Wheat Lines under Salinity Stress Conditions

Simple Summary

Productivity of wheat can be enhanced using salt-tolerant genotypes. However, the assessment of salt tolerance potential in wheat through agro-physiological traits and stress-related gene expression analysis could potentially minimize the cost of breeding programs and be a powerful way for the selection of the most salt-tolerant genotype. The study evaluated the salt tolerance potential of four doubled haploid lines of wheat and compared them with the check cultivar Sakha-93 using an extensive set of agro-physiologic parameters and salt-stress-related gene expressions. The results indicated that the five genotypes tested displayed reduction in all traits evaluated except the canopy temperature and electrical conductivity, which had the greatest decline occurring in the check cultivar and the least decline in DHL2. The genotypes DHL21 and DHL5 exhibited increased expression rate of salt-stress-related genes under salt stress conditions. The multiple linear regression model and path coefficient analysis showed a coefficient of determination of 0.93. Concluding, the number of spikelets, and/or number of kernels were identified to be unbiased traits for assessing wheat DHLs under salinity conditions, given their contribution and direct impact on the grain yield. Moreover, the two most salt-tolerant genotypes DHL2 and DHL21 can be useful as genetic resources for future breeding programs.

Abstract

Salinity majorly hinders horizontal and vertical expansion in worldwide wheat production. Productivity can be enhanced using salt-tolerant wheat genotypes. However, the assessment of salt tolerance potential in bread wheat doubled haploid lines (DHL) through agro-physiological traits and stress-related gene expression analysis could potentially minimize the cost of breeding programs and be a powerful way for the selection of the most salt-tolerant genotype. We used an extensive set of agro-physiologic parameters and salt-stress-related gene expressions. Multivariate analysis was used to detect phenotypic and genetic variations of wheat genotypes more closely under salinity stress, and we analyzed how these strategies effectively balance each other. Four doubled haploid lines (DHLs) and the check cultivar (Sakha93) were evaluated in two salinity levels (without and 150 mM NaCl) until harvest. The five genotypes showed reduced growth under 150 mM NaCl; however, the check cultivar (Sakha93) died at the beginning of the flowering stage. Salt stress induced reduction traits, except the canopy temperature and initial electrical conductivity, which was found in each of the five genotypes, with the greatest decline occurring in the check cultivar (Sakha-93) and the least decline in DHL2. The genotypes DHL21 and DHL5 exhibited increased expression rate of salt-stress-related genes (TaNHX1, TaHKT1, and TaCAT1) compared with DHL2 and Sakha93 under salt stress conditions. Principle component analysis detection of the first two components explains 70.78% of the overall variation of all traits (28 out of 32 traits). A multiple linear regression model and path coefficient analysis showed a coefficient of determination (R²) of 0.93. The models identified two interpretive variables, number of spikelets, and/or number of kernels, which can be unbiased traits for assessing wheat DHLs under salinity stress conditions, given their contribution and direct impact on the grain yield.

Identification of quantitative trait loci associated with canopy temperature in soybean

A consistent risk for soybean (Glycine max L.) production is the impact of drought on growth and yield. Canopy temperature (CT) is an indirect measure of transpiration rate and stomatal conductance and may be valuable in distinguishing differences among genotypes in response to drought. The objective of this study was to map quantitative trait loci (QTLs) associated with CT using thermal infrared imaging in a population of recombinant inbred lines developed from a cross between KS4895 and Jackson. Heritability of CT was 35% when estimated across environments. QTL analysis identified 11 loci for CT distributed on eight chromosomes that individually explained between 4.6 and 12.3% of the phenotypic variation. The locus on Gm11 was identified in two individual environments and across environments and explained the highest proportion of phenotypic variation (9.3% to 11.5%) in CT. Several of these CT loci coincided with the genomic regions from previous studies associated with canopy wilting, canopy temperature, water use efficiency, and other morpho-physiological traits related with drought tolerance. Candidate genes with biological function related to transpiration, root development, and signal transduction underlie these putative CT loci. These genomic regions may be important resources in soybean breeding programs to improve tolerance to drought.

A Physio-Morphological Trait-Based Approach for Breeding Drought Tolerant Wheat

In the past, there have been drought events in different parts of the world, which have negatively influenced the productivity and production of various crops including wheat (Triticum aestivum L.), one of the world's three important cereal crops. Breeding new high yielding drought-tolerant wheat varieties is a research priority specifically in regions where climate change is predicted to result in more drought conditions. Commonly in breeding for drought tolerance, grain yield is the basis for selection, but it is a complex, late-stage trait, affected by many factors aside from drought. A strategy that evaluates genotypes for physiological responses to drought at earlier growth stages may be more targeted to drought and time efficient. Such an approach may be enabled by recent advances in high-throughput phenotyping platforms (HTPPs). In addition, the success of new genomic and molecular approaches rely on the quality of phenotypic data which is utilized to dissect the genetics of complex traits such as drought tolerance. Therefore, the first objective of this review is to describe the growth-stage based physio-morphological traits that could be targeted by breeders to develop drought-tolerant wheat genotypes. The second objective is to describe recent advances in high throughput phenotyping of drought tolerance related physio-morphological traits primarily under field conditions. We discuss how these strategies can be integrated into a comprehensive breeding program to mitigate the impacts of climate change. The review concludes that there is a need for comprehensive high throughput phenotyping of physio-morphological traits that is growth stage-based to improve the efficiency of breeding drought-tolerant wheat.

Breeder friendly phenotyping

The word phenotyping can nowadays invoke visions of a drone or phenocart moving swiftly across research plots collecting high-resolution data sets on a wide array of traits. This has been made possible by recent advances in sensor technology and data processing. Nonetheless, more comprehensive often destructive phenotyping still has much to offer in breeding as well as research. This review considers the 'breeder friendliness' of phenotyping within three main domains: (i) the 'minimum data set', where being 'handy' or accessible and easy to collect and use is paramount, visual assessment often being preferred; (ii) the high throughput phenotyping (HTP), relatively new for most breeders, and requiring significantly greater investment with technical hurdles for implementation and a steeper learning curve than the minimum data set; (iii) detailed characterization or 'precision' phenotyping, typically customized for a set of traits associated with a target environment and requiring significant time and resources. While having been the subject of debate in the past, extra investment for phenotyping is becoming more accepted to capitalize on recent developments in crop genomics and prediction models, that can be built from the high-throughput and detailed precision phenotypes. This review considers different contexts for phenotyping, including breeding, exploration of genetic resources, parent building and translational research to deliver other new breeding resources, and how the different categories of phenotyping listed above apply to each. Some of the same tools and rules of thumb apply equally well to phenotyping for genetic analysis of complex traits and gene discovery.

Co-Evolution of Sink and Source in the Recent Breeding History of Winter Wheat in Germany

Optimizing the interplay between sinks and sources is of crucial importance for breeding progress in winter wheat. However, the physiological limitations of yield from source (e.g. green canopy duration, GCD) and sink (e.g. grain number) are still unclear. Furthermore, there is little information on how the source traits have been modified during the breeding history of winter wheat. This study analyzed the breeding progress of sink and source components and their relationships to yield components. Field trials were conducted over three years with 220 cultivars representing the German breeding history of the past five decades. In addition, genetic associations of QTL for the traits were assessed with genome-wide association studies. Breeding progress mainly resulted from an increase in grain numbers per spike, a sink component, whose variations were largely explained by the photosynthetic activity around anthesis, a source component. Surprisingly, despite significant breeding progress in GCD and other source components, they showed no direct influence on thousand grain weights, indicating that grain filling was not limited by the source strength. Our results suggest that, 1) the potential longevity of the green canopy is predetermined at the time point that the number of grains is fixed; 2) a co-evolution of source and sink strength during the breeding history contribute to the yield formation of the modern cultivars. For future breeding we suggest to choose parental lines with high grain numbers per spike on the sink side, and high photosynthetic activity around anthesis and canopy duration on the source side, and to place emphasis on these traits throughout selection.

Advancing Bromegrass Breeding Through Imaging Phenotyping and Genomic Selection: A Review

Breeding forage crops for high yields of digestible biomass along with improved resource-use efficiency and wide adaptation is essential to meet future challenges in forage production imposed by growing demand, declining resources, and changing climate. Bromegrasses (Bromus spp.) are economically important forage species in the temperate regions of world, but genetic gain in forage yield of bromegrass is relatively low. In particular, limited breeding efforts have been made in improving abiotic stress tolerance and resource-use efficiency. We conducted a literature review on bromegrass breeding achievements and challenges, global climate change impacts on bromegrass species, and explored the feasibility of applying high-throughput imaging phenotyping techniques and genomic selection for further advances in forage yield and quality selection. Overall genetic gain in forage yield of bromegrass has been low, but genetic improvement in forage yield of smooth bromegrass (Bromus inermis Leyss) is somewhat higher than that of meadow bromegrass (Bromus riparius Rehm). This low genetic gain in bromegrass yield is due to a few factors such as its genetic complexity, lack of long-term breeding effort, and inadequate plant adaptation to changing climate. Studies examining the impacts of global climate change on bromegrass species show that global warming, heat stress, and drought have negative effects on forage yield. A number of useful physiological traits have been identified for genetic improvement to minimize yield loss. Available reports suggest that high-throughput imaging phenotyping techniques, including visual and infrared thermal imaging, imaging hyperspectral spectroscopy, and imaging chlorophyll fluorescence, are capable of capturing images of morphological, physiological, and biochemical traits related to plant growth, yield, and adaptation to abiotic stresses at different scales of organization. The more complex traits such as photosynthetic radiation-use efficiency, water-use efficiency, and nitrogen-use efficiency can be effectively assessed by utilizing combinations of imaging hyperspectral spectroscopy, infrared thermal imaging, and imaging chlorophyll fluorescence techniques in a breeding program. Genomic selection has been applied in the breeding of forage species and the applications show its potential in high ploidy, outcrossing species like bromegrass to improve the accuracy of parental selection and improve genetic gain. Together, these new technologies hold promise for improved genetic gain and wide adaptation in future bromegrass breeding.

Combining Crop Growth Modeling and Statistical Genetic Modeling to Evaluate Phenotyping Strategies

Genomic prediction of complex traits, say yield, benefits from including information on correlated component traits. Statistical criteria to decide which yield components to consider in the prediction model include the heritability of the component traits and their genetic correlation with yield. Not all component traits are easy to measure. Therefore, it may be attractive to include proxies to yield components, where these proxies are measured in (high-throughput) phenotyping platforms during the growing season. Using the Agricultural Production Systems Simulator (APSIM)-wheat cropping systems model, we simulated phenotypes for a wheat diversity panel segregating for a set of physiological parameters regulating phenology, biomass partitioning, and the ability to capture environmental resources. The distribution of the additive quantitative trait locus effects regulating the APSIM physiological parameters approximated the same distribution of quantitative trait locus effects on real phenotypic data for yield and heading date. We use the crop growth model APSIM-wheat to simulate phenotypes in three Australian environments with contrasting water deficit patterns. The APSIM output contained the dynamics of biomass and canopy cover, plus yield at the end of the growing season. Each water deficit pattern triggered different adaptive mechanisms and the impact of component traits differed between drought scenarios. We evaluated multiple phenotyping schedules by adding plot and measurement error to the dynamics of biomass and canopy cover. We used these trait dynamics to fit parametric models and P-splines to extract parameters with a larger heritability than the phenotypes at individual time points. We used those parameters in multi-trait prediction models for final yield. The combined use of crop growth models and multi-trait genomic prediction models provides a procedure to assess the efficiency of phenotyping strategies and compare methods to model trait dynamics. It also allows us to quantify the impact of yield components on yield prediction accuracy even in different environment types. In scenarios with mild or no water stress, yield prediction accuracy benefitted from including biomass and green canopy cover parameters. The advantage of the multi-trait model was smaller for the early-drought scenario, due to the reduced correlation between the secondary and the target trait. Therefore, multi-trait genomic prediction models for yield require scenario-specific correlated traits.

Using environmental clustering to identify specific drought tolerance QTLs in bread wheat (T. aestivum L.)

Environmental clustering helps to identify QTLs associated with grain yield in different water stress scenarios. These QTLs could be useful for breeders to improve grain yields and increase genetic resilience in marginal environments. Drought is one of the main abiotic stresses limiting winter bread wheat growth and productivity around the world. The acquisition of new high-yielding and stress-tolerant varieties is therefore necessary and requires improved understanding of the physiological and genetic bases of drought resistance. A panel of 210 elite European varieties was evaluated in 35 field trials. Grain yield and its components were scored in each trial. A crop model was then run with detailed climatic data and soil water status to assess the dynamics of water stress in each environment. Varieties were registered from 1992 to 2011, allowing us to test timewise genetic progress. Finally, a genome-wide association study (GWAS) was carried out using genotyping data from a 280 K SNP chip. The crop model simulation allowed us to group the environments into four water stress scenarios: an optimal condition with no water stress, a post-anthesis water stress, a moderate-anthesis water stress and a high pre-anthesis water stress. Compared to the optimal water condition, grain yield losses in the stressed conditions were 3.3%, 12.4% and 31.2%, respectively. This environmental clustering improved understanding of the effect of drought on grain yields and explained 20% of the G × E interaction. The greatest genetic progress was obtained in the optimal condition, mostly represented in France. The GWAS identified several QTLs, some of which were specific of the different water stress patterns. Our results make breeding for improved drought resistance to specific environmental scenarios easier and will facilitate genetic progress in future environments, i.e., water stress environments.

Elucidating the genetic basis of biomass accumulation and radiation use efficiency in spring wheat and its role in yield potential

One of the major challenges for plant scientists is increasing wheat (Triticum aestivum) yield potential (YP). A significant bottleneck for increasing YP is achieving increased biomass through optimization of radiation use efficiency (RUE) along the crop cycle. Exotic material such as landraces and synthetic wheat has been incorporated into breeding programmes in an attempt to alleviate this; however, their contribution to YP is still unclear. To understand the genetic basis of biomass accumulation and RUE, we applied genome-wide association study (GWAS) to a panel of 150 elite spring wheat genotypes including many landrace and synthetically derived lines. The panel was evaluated for 31 traits over 2 years under optimal growing conditions and genotyped using the 35K wheat breeders array. Marker-trait association identified 94 SNPs significantly associated with yield, agronomic and phenology-related traits along with RUE and final biomass (BM_PM) at various growth stages that explained 7%-17% of phenotypic variation. Common SNP markers were identified for grain yield, BM_PM and RUE on chromosomes 5A and 7A. Additionally, landrace and synthetic derivative lines showed higher thousand grain weight (TGW), BM_PM and RUE but lower grain number (GM2) and harvest index (HI). Our work demonstrates the use of exotic material as a valuable resource to increase YP. It also provides markers for use in marker-assisted breeding to systematically increase BM_PM, RUE and TGW and avoid the TGW/GM2 and BM_PM/HI trade-off. Thus, achieving greater genetic gains in elite germplasm while also highlighting genomic regions and candidate genes for further study.

Climate Change Impacts and Adaptation Strategies of Agriculture in Mediterranean-Climate Regions (MCRs)

The world’s five Mediterranean-climate regions (MCRs) share unique climatic regimes of mild, wet winters and warm and dry summers. Agriculture in these regions is threatened by increases in the occurrence of drought and high temperature events associated with climate change (CC). In this review we analyze what would be the effects of CC on crops (including orchards and vineyards), how crops and cropping and farming systems could adapt to CC, and what are the social and economic impacts, as well as the strategies used by producers to adapt to CC. In rainfed areas, water deficit occurs mostly during the flowering and grain filling stages (terminal drought stress), which has large detrimental effects on the productivity of crops. Orchards and vineyards, which are mostly cultivated in irrigated areas, will also be vulnerable to water deficit due to a reduction in water available for irrigation and an increase in evapotranspiration. Adaptation of agriculture to CC in MCRs requires integrated strategies that encompass different levels of organization: the crop (including orchards and vineyards), the cropping system (sequence of crops and management techniques used on a particular agricultural field) and the farming system, which includes the farmer.

Yielding to the image: How phenotyping reproductive growth can assist crop improvement and production

Reproductive organs are the main reason we grow and harvest most plant species as crops, yet they receive less attention from phenotyping due to their complexity and inaccessibility for analysis. This review highlights recent progress towards the quantitative high-throughput phenotyping of reproductive development, focusing on three impactful areas that are pivotal for plant breeding and crop production. First, we look at phenotyping phenology, summarizing the indirect and direct approaches that are available. This is essential for analysis of genotype by environment, and to enable effective management interpretation and agronomy and physiological interventions. Second, we look at pollen development and production, in addition to anther characteristics, these are critical points of vulnerability for yield loss when stress occurs before and during flowering, and are of particular interest for hybrid technology development. Third, we elaborate on phenotyping yield components, indirectly or directly during the season, with a numerical or growth related approach and post-harvest processing. Finally, we summarise the opportunities and challenges ahead for phenotyping reproductive growth and their feasibility and impact, with emphasis on plant breeding applications and targeted yield increases.

High-throughput phenotyping for crop improvement in the genomics era

Tremendous progress has been made with continually expanding genomics technologies to unravel and understand crop genomes. However, the impact of genomics data on crop improvement is still far from satisfactory, in large part due to a lack of effective phenotypic data; our capacity to collect useful high quality phenotypic data lags behind the current capacity to generate high-throughput genomics data. Thus, the research bottleneck in plant sciences is shifting from genotyping to phenotyping. This article review the current status of efforts made in the last decade to systematically collect phenotypic data to alleviate this 'phenomics bottlenecks' by recording trait data through sophisticated non-invasive imaging, spectroscopy, image analysis, robotics, high-performance computing facilities and phenomics databases. These modern phenomics platforms and tools aim to record data on traits like plant development, architecture, plant photosynthesis, growth or biomass productivity, on hundreds to thousands of plants in a single day, as a phenomics revolution. It is believed that this revolution will provide plant scientists with the knowledge and tools necessary for unlocking information coded in plant genomes. Efforts have been also made to present the advances made in the last 10 years in phenomics platforms and their use in generating phenotypic data on different traits in several major crops including rice, wheat, barley, and maize. The article also highlights the need for phenomics databases and phenotypic data sharing for crop improvement. The phenomics data generated has been used to identify genes/QTL through QTL mapping, association mapping and genome-wide association studies (GWAS) for genomics-assisted breeding (GAB) for crop improvement.

Quantitative and comparative analysis of whole-plant performance for functional physiological traits phenotyping: New tools to support pre-breeding and plant stress physiology studies

Plants are autotrophic organisms in which there are linear relationships between the rate at which organic biomass is accumulated and many ambient parameters such as water, nutrients, CO₂ and solar radiation. These linear relationships are the result of good feedback regulation between a plants sensing of the environment and the optimization of its performance response. In this review, we suggest that continuous monitoring of the plant physiological profile in response to changing ambient conditions could be a useful new phenotyping tool, allowing the characterization and comparison of different levels of functional phenotypes and productivity. This functional physiological phenotyping (FPP) approach can be integrated into breeding programs, which are facing difficulties in selecting plants that perform well under abiotic stress. Moreover, high-throughput FPP will increase the efficiency of the selection of traits that are closely related to environmental interactions (such as plant water status, water-use efficiency, stomatal conductance, etc.) thanks to its high resolution and dynamic measurements. One of the important advantages of FPP is, its simplicity and effectiveness and compatibility with experimental methods that use load-cell lysimeters and ambient sensors. In the future, this platform could help with phenotyping of complex physiological traits, beneficial for yield gain to enhance functional breeding approaches and guide in crop modeling.

Integrating genomic-enabled prediction and high-throughput phenotyping in breeding for climate-resilient bread wheat

Genomic selection and high-throughput phenotyping (HTP) are promising tools to accelerate breeding gains for high-yielding and climate-resilient wheat varieties. Hence, our objective was to evaluate them for predicting grain yield (GY) in drought-stressed (DS) and late-sown heat-stressed (HS) environments of the International maize and wheat improvement center's elite yield trial nurseries. We observed that the average genomic prediction accuracies using fivefold cross-validations were 0.50 and 0.51 in the DS and HS environments, respectively. However, when a different nursery/year was used to predict another nursery/year, the average genomic prediction accuracies in the DS and HS environments decreased to 0.18 and 0.23, respectively. While genomic predictions clearly outperformed pedigree-based predictions across nurseries, they were similar to pedigree-based predictions within nurseries due to small family sizes. In populations with some full-sibs in the training population, the genomic and pedigree-based prediction accuracies were on average 0.27 and 0.35 higher than the accuracies in populations with only one progeny per cross, indicating the importance of genetic relatedness between the training and validation populations for good predictions. We also evaluated the item-based collaborative filtering approach for multivariate prediction of GY using the green normalized difference vegetation index from HTP. This approach proved to be the best strategy for across-nursery predictions, with average accuracies of 0.56 and 0.62 in the DS and HS environments, respectively. We conclude that GY is a challenging trait for across-year predictions, but GS and HTP can be integrated in increasing the size of populations screened and evaluating unphenotyped large nurseries for stress-resilience within years.

Co-Evolution of Sink and Source in the Recent Breeding History of Winter Wheat in Germany

Optimizing the interplay between sinks and sources is of crucial importance for breeding progress in winter wheat. However, the physiological limitations of yield from source (e.g. green canopy duration, GCD) and sink (e.g. grain number) are still unclear. Furthermore, there is little information on how the source traits have been modified during the breeding history of winter wheat. This study analyzed the breeding progress of sink and source components and their relationships to yield components. Field trials were conducted over three years with 220 cultivars representing the German breeding history of the past five decades. In addition, genetic associations of QTL for the traits were assessed with genome-wide association studies. Breeding progress mainly resulted from an increase in grain numbers per spike, a sink component, whose variations were largely explained by the photosynthetic activity around anthesis, a source component. Surprisingly, despite significant breeding progress in GCD and other source components, they showed no direct influence on thousand grain weights, indicating that grain filling was not limited by the source strength. Our results suggest that, 1) the potential longevity of the green canopy is predetermined at the time point that the number of grains is fixed; 2) a co-evolution of source and sink strength during the breeding history contribute to the yield formation of the modern cultivars. For future breeding we suggest to choose parental lines with high grain numbers per spike on the sink side, and high photosynthetic activity around anthesis and canopy duration on the source side, and to place emphasis on these traits throughout selection.

Genome-Wide Association Analyses Identify QTL Hotspots for Yield and Component Traits in Durum Wheat Grown under Yield Potential, Drought, and Heat Stress Environments

Understanding the genetic bases of economically important traits is fundamentally important in enhancing genetic gains in durum wheat. In this study, a durum panel of 208 lines (comprised of elite materials and exotics from the International Maize and Wheat Improvement Center gene bank) were subjected to genome wide association study (GWAS) using 6,211 DArTseq single nucleotide polymorphisms (SNPs). The panel was phenotyped under yield potential (YP), drought stress (DT), and heat stress (HT) conditions for 2 years. Mean yield of the panel was reduced by 72% (to 1.64 t/ha) under HT and by 60% (to 2.33 t/ha) under DT, compared to YP (5.79 t/ha). Whereas, the mean yield of the panel under HT was 30% less than under DT. GWAS identified the largest number of significant marker-trait associations on chromosomes 2A and 2B with p-values 10-06 to 10-03 and the markers from the whole study explained 7-25% variation in the traits. Common markers were identified for stress tolerance indices: stress susceptibility index, stress tolerance, and stress tolerance index estimated for the traits under DT (82 cM on 2B) and HT (68 and 83 cM on 3B; 25 cM on 7A). GWAS of irrigated (YP and HT combined), stressed (DT and HT combined), combined analysis of three environments (YP + DT + HT), and its comparison with trait per se and stress indices identified QTL hotspots on chromosomes 2A (54-70 cM) and 2B (75-82 cM). This study enhances our knowledge about the molecular markers associated with grain yield and its components under different stress conditions. It identifies several marker-trait associations for further exploration and validation for marker-assisted breeding.

Biochemical model of C3 photosynthesis applied to wheat at different temperatures

We examined the effects of leaf temperature on the estimation of maximal Rubisco capacity (V_cmax ) from gas exchange measurements of wheat leaves using a C₃ photosynthesis model. Cultivars of spring wheat (Triticum aestivum (L)) and triticale (X Triticosecale Wittmack) were grown in a greenhouse or in the field and measured at a range of temperatures under controlled conditions in a growth cabinet (2 and 21% O₂ ) or in the field using natural diurnal variation in temperature, respectively. Published Rubisco kinetic constants for tobacco did not describe the observed CO₂ response curves well as temperature varied. By assuming values for the Rubisco Michaelis-Menten constants for CO₂ (K_c ) and O₂ (K_o ) at 25 °C derived from tobacco and the activation energies of V_cmax from wheat and respiration in the light, R_d , from tobacco, we derived activation energies for K_c and K_o (93.7 and 33.6 kJ mol^-1 , respectively) that considerably improved the fit of the model to observed data. We confirmed that temperature dependence of dark respiration for wheat was well described by the activation energy for R_d from tobacco. The new parameters improved the estimation of V_cmax under field conditions, where temperatures increased through the day.

Genetic diversity and genomic strategies for improving drought and waterlogging tolerance in soybeans

Drought and its interaction with high temperature are the major abiotic stress factors affecting soybean yield and production stability. Ongoing climate changes are anticipated to intensify drought events, which will further impact crop production and food security. However, excessive water also limits soybean production. The success of soybean breeding programmes for crop improvement is dependent on the extent of genetic variation present in the germplasm base. Screening for natural genetic variation in drought- and flooding tolerance-related traits, including root system architecture, water and nitrogen-fixation efficiency, and yield performance indices, has helped to identify the best resources for genetic studies in soybean. Genomic resources, including whole-genome sequences of diverse germplasms, millions of single-nucleotide polymorphisms, and high-throughput marker genotyping platforms, have expedited gene and marker discovery for translational genomics in soybean. This review highlights the current knowledge of the genetic diversity and quantitative trait loci associated with root system architecture, canopy wilting, nitrogen-fixation ability, and flooding tolerance that contributes to the understanding of drought- and flooding-tolerance mechanisms in soybean. Next-generation mapping approaches and high-throughput phenotyping will facilitate a better understanding of phenotype-genotype associations and help to formulate genomic-assisted breeding strategies, including genomic selection, in soybean for tolerance to drought and flooding stress.

Pentaploid Wheat Hybrids: Applications, Characterisation, and Challenges

Interspecific hybridisation between hexaploid and tetraploid wheat species leads to the development of F1 pentaploid hybrids with unique chromosomal constitutions. Pentaploid hybrids derived from bread wheat (Triticum aestivum L.) and durum wheat (Triticum turgidum spp. durum Desf.) crosses can improve the genetic background of either parent by transferring traits of interest. The genetic variability derived from bread and durum wheat and transferred into pentaploid hybrids has the potential to improve disease resistance, abiotic tolerance, and grain quality, and to enhance agronomic characters. Nonetheless, pentaploid wheat hybrids have not been fully exploited in breeding programs aimed at improving crops. There are several potential barriers for efficient pentaploid wheat production, such as low pollen compatibility, poor seed set, failed seedling establishment, and frequent sterility in F1 hybrids. However, most of the barriers can be overcome by careful selection of the parental genotypes and by employing the higher ploidy level genotype as the maternal parent. In this review, we summarize the current research on pentaploid wheat hybrids and analyze the advantages and pitfalls of current methods used to assess pentaploid-derived lines. Furthermore, we discuss current and potential applications in commercial breeding programs and future directions for research into pentaploid wheat.

Mapping QTLs associated with agronomic and physiological traits under terminal drought and heat stress conditions in wheat (Triticum aestivum L.)

Wheat crops frequently experience a combination of abiotic stresses in the field, but most quantitative trait loci (QTL) studies have focused on the identification of QTLs for traits under single stress field conditions. A recombinant inbred line (RIL) population derived from SeriM82 × Babax was used to map QTLs under well-irrigated, heat, drought, and a combination of heat and drought stress conditions in two years. A total of 477 DNA markers were used to construct linkage groups that covered 1619.6 cM of the genome, with an average distance of 3.39 cM between adjacent markers. Moderate to relatively high heritability estimates (0.60-0.70) were observed for plant height (PHE), grain yield (YLD), and grain per square meter (GM2). The most important QTLs for days to heading (DHE), thousand grain weight (TGW), and YLD were detected on chromosomes 1B, 1D-a, and 7D-b. The prominent QTLs related to canopy temperature were on 3B. Results showed that common QTLs for DHE, YLD, and TGW on 7D-b were validated in heat and drought trials. Three QTLs for chlorophyll content in SPAD unit (on 1A/6B), leaf rolling (ROL) (on 3B/4A), and GM2 (on 1B/7D-b) showed significant epistasis × environment interaction. Six heat- or drought-specific QTLs (linked to 7D-acc/cat-10, 1B-agc/cta-9, 1A-aag/cta-8, 4A-acg/cta-3, 1B-aca/caa-3, and 1B-agc/cta-9 for day to maturity (DMA), SPAD, spikelet compactness (SCOM), TGW, GM2, and GM2, respectively) were stable and validated over two years. The major DHE QTL linked to 7D-acc/cat-10, with no QTL × environment (QE) interaction increased TGW and YLD. This QTL (5.68 ≤ LOD ≤ 10.5) explained up to 19.6% variation in YLD in drought, heat, and combined stress trials. This marker as a candidate could be used for verification in other populations and identifying superior allelic variations in wheat cultivars or its wild progenitors to increase the efficiency of selection of high yielding lines adapted to end-season heat and drought stress conditions.

Physiological breeding

Physiological breeding crosses parents with different complex but complementary traits to achieve cumulative gene action for yield, while selecting progeny using remote sensing, possibly in combination with genomic selection. Physiological approaches have already demonstrated significant genetic gains in Australia and several developing countries of the International Wheat Improvement Network. The techniques involved (see Graphical Abstract) also provide platforms for research and refinement of breeding methodologies. Recent examples of these include screening genetic resources for novel expression of Calvin cycle enzymes, identification of common genetic bases for heat and drought adaptation, and genetic dissection of trade-offs among yield components. Such information, combined with results from physiological crosses designed to test novel trait combinations, lead to more precise breeding strategies, and feed models of genotype-by-environment interaction to help build new plant types and experimental environments for future climates.

Comparative performance of spectral and thermographic properties of plants and physiological traits for phenotyping salinity tolerance of wheat cultivars under simulated field conditions

Successful plant breeding in saline environments requires high-throughput phenotyping techniques to differentiate genotypes for salinity tolerance. This study employed advanced, non-destructive sensing technologies to identify traits contributing to salinity tolerance in wheat (Triticum aestivum L.). Plants were grown in large containers to simulate field conditions for control, salinity stress alone, and combined salinity and drought stress treatments. The comparative performance of spectral reflectance sensing, thermography, digital imaging, and the assessment of physiological traits of two wheat cultivars were tested at booting, anthesis and grain filling. Variation in grain yield between the two cultivars was significant for all treatments (controls, P<0.01; others, P<0.001), whereas there were no significant differences in straw DW regardless of treatment. Among the spectral and thermographic assessments, spectral indices were sufficiently sensitive to detect genotypic differences in salinity tolerance among the wheat cultivars after anthesis for the salinity alone and combined treatments. In contrast, physiological traits such as leaf water status and photosynthetic properties demonstrated no differences between the wheat cultivars for either the salinity alone or the combined treatments. These results suggest that spectral sensing has the potential for high-throughput screening of phenotypic traits associated with salinity tolerance of wheat cultivars.

Metabolic acclimation of source and sink tissues to salinity stress in bermudagrass (Cynodon dactylon)

Salinity is one of the major environmental factors affecting plant growth and survival by modifying source and sink relationships at physiological and metabolic levels. Individual metabolite levels and/or ratios in sink and source tissues may reflect the complex interplay of metabolic activities in sink and source tissues at the whole-plant level. We used a non-targeted gas chromatography-mass spectrometry (GC-MS) approach to study sink and source tissue-specific metabolite levels and ratios from bermudagrass under salinity stress. Shoot growth rate decreased while root growth rate increased which lead to an increased root/shoot growth rate ratio under salt stress. A clear shift in soluble sugars (sucrose, glucose and fructose) and metabolites linked to nitrogen metabolism (glutamate, aspartate and asparagine) in favor of sink roots was observed, when compared with sink and source leaves. The higher shifts in soluble sugars and metabolites linked to nitrogen metabolism in favor of sink roots may contribute to the root sink strength maintenance that facilitated the recovery of the functional equilibrium between shoot and root, allowing the roots to increase competitive ability for below-ground resource capture. This trait could be considered in breeding programs for increasing salt tolerance, which would help maintain root functioning (i.e. water and nutrient absorption, Na⁺ exclusion) and adaptation to stress.

Dissection of drought response of modern and underutilized wheat varieties according to Passioura's yield-water framework

Trait-based breeding is essential to improve wheat yield, particularly when stress adaptation is targeted. A set of modern and underutilized wheat genotypes was examined in a 2-year field experiment with distinct seasonal water supply. Yield formation and drought response strategies were analyzed in relation to components of Passioura's yield-water framework based on phenological, morphological, physiological, and root characteristics. Limited water supply resulted in 60% yield loss and substantially lower water use (37%), water use efficiency (32.6%), and harvest index (14%). Phenology and root length density were key determinants of water use. Late flowering underutilized wheat species with large root system and swift ground coverage showed greatest water use. Leaf chlorophyll concentration and stomata conductance were higher in modern cultivars, supporting their high biomass growth and superior water use efficiency. While, lower chlorophyll concentration and stomata conductance of underutilized wheats indicated a water saving strategy with an intrinsic limitation of potential growth. Harvest index was strongly dependent on phenology and yield components. Optimized flowering time, reduced tillering, and strong grain sink of modern cultivars explained higher harvest index compared to underutilized wheats. Cluster analysis revealed the consistent differentiation of underutilized and modern wheats based on traits underlying Passioura's yield-water framework. We identified physiological and root traits within modern cultivars to be targeted for trait-based crop improvement under water-limited conditions. High capacity of water use in underutilized genetic resources is related to yield-limiting phenological and morphological traits, constraining their potential role for better drought resistance. Still some genetic resources provide adaptive features for stress resistance compatible with high yield as revealed by high harvest index under drought of Khorasan wheat.

Genetic characterization of the wheat association mapping initiative (WAMI) panel for dissection of complex traits in spring wheat

The wheat association mapping initiative is appropriate for gene discovery without the confounding effects of phenology and plant height. The wheat association mapping initiative (WAMI) population is a set of 287 diverse advanced wheat lines with a narrow range of variation for days to heading (DH) and plant height (PH). This study aimed to characterize the WAMI and showed that this diverse panel has a favorable genetic background in which stress adaptive traits and their alleles contributing to final yield can be identified with reduced confounding major gene effects through genome-wide association studies (GWAS). Using single nucleotide polymorphism (SNP) markers, we observed lower gene diversity on the D genome, compared with the other genomes. Population structure was primarily related to the distribution of the 1B.1R rye translocation. The narrow range of variation for DH and PH in the WAMI population still entailed segregation for a few markers associated with the former traits, while Rht genes were associated with grain yield (GY). Genotype by environment (G × E) interaction for GY was primarily explained by Rht-B1, Vrn-A1 and markers on chromosomes 2D and 3A when running GWAS with genotype scores from the G × E biplot. The use of PC scores from the G × E biplot seems a promising tool to determine genes and markers associated with complex interactions across environments. The WAMI panel lends itself to GWAS for complex trait dissection by avoiding the confounding effects of DH and PH which were reduced to a minimum (using Rht-B1 and Vrn-A1 scores as covariables), with significant associations with GY on chromosomes 2D, 3A and 3B.

Multiple QTLs Linked to Agro-Morphological and Physiological Traits Related to Drought Tolerance in Potato

Dissection of the genetic architecture of adaptation and abiotic stress-related traits is highly desirable for developing drought-tolerant potatoes and enhancing the resilience of existing cultivars, particularly as agricultural production in rain-fed areas may be reduced by up to 50 % by 2020. The "DMDD" potato progeny was developed at International Potato Center (CIP) by crossing the sequenced double monoploid line DM and a diploid cultivar of the Solanum tuberosum diploid Andigenum Goniocalyx group. Recently, a high-density integrated genetic map based on single nucleotide polymorphism (SNP), diversity array technology (DArT), simple sequence repeats (SSRs), and amplified fragment length polymorphism (AFLP) markers was also made available for this population. Two trials were conducted, in greenhouse and field, for drought tolerance with two treatments each, well-watered and terminal drought, in which watering was suspended 60 days after planting. The DMDD population was evaluated for agro-morphological and physiological traits before and after initiation of stress, at multiple time points. Two dense parental genetic maps were constructed using published genotypic data, and quantitative trait locus (QTL) analysis identified 45 genomic regions associated with nine traits in well-watered and terminal drought treatments and 26 potentially associated with drought stress. In this study, the strong influence of environmental factors besides water shortage on the expression of traits and QTLs reflects the multigenic control of traits related to drought tolerance. This is the first study to our knowledge in potato identifying QTLs for drought-related traits in field and greenhouse trials, giving new insights into genetic architecture of drought-related traits. Many of the QTLs identified have the potential to be used in potato breeding programs for enhanced drought tolerance.

Genomic tools to assist breeding for drought tolerance

Water deficit or drought stress is a major limitation to crop production globally. Plant breeders have used a wide range of technologies to successfully breed varieties that perform well under the growth conditions for their target environments but they are always seeking new opportunities to enhance rates of genetic gain. Under drought, yield is determined by the integration of variable levels of water deficit across the developmental life of the crop. Genomics technologies were seen as a path to understand the genetic and environmental complexity of drought stress. To be relevant to breeding programs, genomic studies must consider the nature of drought stress in the target environment and use plant material and phenotyping techniques that relate to field conditions.

A genome-wide identification of chromosomal regions determining nitrogen use efficiency components in wheat (Triticum aestivum L.)

This study identified 333 genomic regions associated to 28 traits related to nitrogen use efficiency in European winter wheat using genome-wide association in a 214-varieties panel experimented in eight environments. Improving nitrogen use efficiency is a key factor to sustainably ensure global production increase. However, while high-throughput screening methods remain at a developmental stage, genetic progress may be mainly driven by marker-assisted selection. The objective of this study was to identify chromosomal regions associated with nitrogen use efficiency-related traits in bread wheat (Triticum aestivum L.) using a genome-wide association approach. Two hundred and fourteen European elite varieties were characterised for 28 traits related to nitrogen use efficiency in eight environments in which two different nitrogen fertilisation levels were tested. The genome-wide association study was carried out using 23,603 SNP with a mixed model for taking into account parentage relationships among varieties. We identified 1,010 significantly associated SNP which defined 333 chromosomal regions associated with at least one trait and found colocalisations for 39 % of these chromosomal regions. A method based on linkage disequilibrium to define the associated region was suggested and discussed with reference to false positive rate. Through a network approach, colocalisations were analysed and highlighted the impact of genomic regions controlling nitrogen status at flowering, precocity, and nitrogen utilisation on global agronomic performance. We were able to explain 40 ± 10 % of the total genetic variation. Numerous colocalisations with previously published genomic regions were observed with such candidate genes as Ppd-D1, Rht-D1, NADH-Gogat, and GSe. We highlighted selection pressure on yield and nitrogen utilisation discussing allele frequencies in associated regions.