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Genomic selection (GS) is a methodology that is revolutionizing plant breeding because it can select candidate genotypes without phenotypic evaluation in the field. However, its practical implementation in hybrid prediction remains challenging since many factors affect its accuracy. The main objective of this study was to research the genomic prediction accuracy of wheat hybrids by adding covariates with the hybrid parental phenotypic information to the model. Four types of different models (MA, MB, MC, and MD) with one covariate (same trait to be predicted) (MA_C, MB_C, MC_C, and MD_C) or several covariates (of the same trait and other correlated traits) (MA_AC, MB_AC, MC_AC, and MD_AC) were studied. We found that the four models with parental information outperformed models without parental information in terms of mean square error by at least 14.1% (MA vs. MA_C), 5.5% (MB vs. MB_C), 51.4% (MC vs. MC_C), and 6.4% (MD vs. MD_C) when parental information of the same trait was used and by at least 13.7% (MA vs. MA_AC), 5.3% (MB vs. MB_AC), 55.1% (MC vs. MC_AC), and 6.0% (MD vs. MD_AC) when parental information of the same trait and other correlated traits were used. Our results also show a large gain in prediction accuracy when covariates were considered using the parental phenotypic information, as opposed to marker information. Finally, our results empirically demonstrate that a significant improvement in prediction accuracy was gained by adding parental phenotypic information as covariates; however, this is expensive since, in many breeding programs, the parental phenotypic information is unavailable.

While sparse testing methods have been proposed by researchers to improve the efficiency of genomic selection (GS) in breeding programs, there are several factors that can hinder this. In this research, we evaluated four methods (M1–M4) for sparse testing allocation of lines to environments under multi-environmental trails for genomic prediction of unobserved lines. The sparse testing methods described in this study are applied in a two-stage analysis to build the genomic training and testing sets in a strategy that allows each location or environment to evaluate only a subset of all genotypes rather than all of them. To ensure a valid implementation, the sparse testing methods presented here require BLUEs (or BLUPs) of the lines to be computed at the first stage using an appropriate experimental design and statistical analyses in each location (or environment). The evaluation of the four cultivar allocation methods to environments of the second stage was done with four data sets (two large and two small) under a multi-trait and uni-trait framework. We found that the multi-trait model produced better genomic prediction (GP) accuracy than the uni-trait model and that methods M3 and M4 were slightly better than methods M1 and M2 for the allocation of lines to environments. Some of the most important findings, however, were that even under a scenario where we used a training-testing relation of 15–85%, the prediction accuracy of the four methods barely decreased. This indicates that genomic sparse testing methods for data sets under these scenarios can save considerable operational and financial resources with only a small loss in precision, which can be shown in our cost-benefit analysis.

Undomesticated wild species, crop wild relatives, and landraces represent sources of variation for wheat improvement to address challenges from climate change and the growing human population. Here, we study 56,342 domesticated hexaploid, 18,946 domesticated tetraploid and 3,903 crop wild relatives in a massive-scale genotyping and diversity analysis. Using DArTseqTM technology, we identify more than 300,000 high-quality SNPs and SilicoDArT markers and align them to three reference maps: the IWGSC RefSeq v1.0 genome assembly, the durum wheat genome assembly (cv. Svevo), and the DArT genetic map. On average, 72% of the markers are uniquely placed on these maps and 50% are linked to genes. The analysis reveals landraces with unexplored diversity and genetic footprints defined by regions under selection. This provides fertile ground to develop wheat varieties of the future by exploring specific gene or chromosome regions and identifying germplasm conserving allelic diversity missing in current breeding programs., Genebanks hold comprehensive collections of wild species, wild relatives, and landraces that are useful for genetic improvement. Here, the authors report the genotype of nearly 80,000 wheat accessions using DArTseq technology to show the less explored genetic diversity.

Durum wheat landraces have huge potential for the identification of genetic factors valuable for improving resistance to biotic stresses. Tunisia is known as a hot spot for Septoria tritici blotch disease (STB), caused by the fungus

Wheat head blast is a dangerous fungal disease in South America and has recently spread to Bangladesh and Zambia, threatening wheat production in those regions. Host resistance as an economical and environment-friendly management strategy has been heavily relied on, and understanding the resistance loci in the wheat genome is very helpful to resistance breeding. In the current study, two recombinant inbred line (RIL) populations, Alondra/Milan (with 296 RILs) and Caninde#2/Milan-S (with 254 RILs and Milan-S being a susceptible variant of Milan), were used for mapping QTL associated with head blast resistance in field experiments. Phenotyping was conducted in Quirusillas and Okinawa, Bolivia, and in Jashore, Bangladesh, during the 2017–18 and 2018–19 cropping cycles. The DArTseq® technology was employed to genotype the lines, along with four STS markers in the 2NS region. A QTL with consistent major effects was mapped on the 2NS/2AS translocation region in both populations, explaining phenotypic variation from 16.7 to 79.4% across experiments. Additional QTL were detected on chromosomes 2DL, 7AL, and 7DS in the Alondra/Milan population, and 2BS, 4AL, 5AS, 5DL, 7AS, and 7AL in the Caninde#2/Milan-S population, all showing phenotypic effects

Background: Durum wheat (Triticum turgidum L. ssp. durum Desf. Husn) is the main staple crop used to make pasta products worldwide. Under the current climate change scenarios, genetic variability within a crop plays a crucial role in the successful release of new varieties with high yields and wide crop adaptation. In this study we evaluated a durum wheat collection consisting of 197 genotypes that mainly comprised a historical set of Argentinian germplasm but also included worldwide accessions. Results: We assessed the genetic diversity, population structure and linkage disequilibrium (LD) patterns in this collection using a 35 K SNP array. The level of polymorphism was considered, taking account of the frequent and rare allelic variants. A total of 1547 polymorphic SNPs was located within annotated genes. Genetic diversity in the germplasm collection increased slightly from 1915 to 2010. However, a reduction in genetic diversity using SNPs with rare allelic variants was observed after 1979. However, larger numbers of rare private alleles were observed in the 2000–2009 period, indicating that a high reservoir of rare alleles is still present among the recent germplasm in a very low frequency. The percentage of pairwise loci in LD in the durum genome was low (13.4%) in our collection. Overall LD and the high (r2 > 0.7) or complete (r2 = 1) LD presented different patterns in the chromosomes. The LD increased over three main breeding periods (1915–1979, 1980–1999 and 2000–2020). Conclusions: Our results suggest that breeding and selection have impacted differently on the A and B genomes, particularly on chromosome 6A and 2A. The collection was structured in five sub-populations and modern Argentinian accessions (cluster Q4) which were clearly differentiated. Our study contributes to the understanding of the complexity of Argentinian durum wheat germplasm and to derive future breeding strategies enhancing the use of genetic diversity in a more efficient and targeted way. Fil: Roncallo, Pablo Federico. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; Argentina. Universidad Nacional del Sur. Departamento de Agronomía; Argentina Fil: Larsen, Adelina Olga. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Sur. Estación Experimental Agropecuaria Barrow; Argentina Fil: Achilli, Ana Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; Argentina. Universidad Nacional del Sur. Departamento de Agronomía; Argentina Fil: Saint Pierre, Carolina. Centro Internacional de Mejoramiento de Maíz y Trigo; México Fil: Gallo, Cristian Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; Argentina. Universidad Nacional del Sur. Departamento de Agronomía; Argentina Fil: Dreisigacker, Susanne. Centro Internacional de Mejoramiento de Maíz y Trigo; México Fil: Echenique, Carmen Viviana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Agronomía; Argentina

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.

This study examines genomic prediction within 8416 Mexican landrace accessions and 2403 Iranian landrace accessions stored in gene banks. The Mexican and Iranian collections were evaluated in separate field trials, including an optimum environment for several traits, and in two separate environments (drought, D and heat, H) for the highly heritable traits, days to heading (DTH), and days to maturity (DTM). Analyses accounting and not accounting for population structure were performed. Genomic prediction models include genotype × environment interaction (G × E). Two alternative prediction strategies were studied: (1) random cross-validation of the data in 20% training (TRN) and 80% testing (TST) (TRN20-TST80) sets, and (2) two types of core sets, “diversity” and “prediction”, including 10% and 20%, respectively, of the total collections. Accounting for population structure decreased prediction accuracy by 15–20% as compared to prediction accuracy obtained when not accounting for population structure. Accounting for population structure gave prediction accuracies for traits evaluated in one environment for TRN20-TST80 that ranged from 0.407 to 0.677 for Mexican landraces, and from 0.166 to 0.662 for Iranian landraces. Prediction accuracy of the 20% diversity core set was similar to accuracies obtained for TRN20-TST80, ranging from 0.412 to 0.654 for Mexican landraces, and from 0.182 to 0.647 for Iranian landraces. The predictive core set gave similar prediction accuracy as the diversity core set for Mexican collections, but slightly lower for Iranian collections. Prediction accuracy when incorporating G × E for DTH and DTM for Mexican landraces for TRN20-TST80 was around 0.60, which is greater than without the G × E term. For Iranian landraces, accuracies were 0.55 for the G × E model with TRN20-TST80. Results show promising prediction accuracies for potential use in germplasm enhancement and rapid introgression of exotic germplasm into elite materials.

The original article was corrected. Author Muhammad Kundi should instead read: Muhammad Sohail.

To accelerate genetic gains in breeding, physiological trait (PT) characterization of candidate parents can help make more strategic crosses, increasing the probability of accumulating favorable alleles compared to crossing relatively uncharacterized lines. In this study, crosses were designed to complement “source” with “sink” traits, where at least one parent was selected for favorable expression of biomass and/or radiation use efficiency—source—and the other for sink-related traits like harvest-index, kernel weight and grains per spike. Female parents were selected from among genetic resources—including landraces and products of wide-crossing (i.e. synthetic wheat)—that had been evaluated in Mexico at high yield potential or under heat stress, while elite lines were used as males. Progeny of crosses were advanced to the F4 generation within Mexico, and F4-derived F5 and F6 generations were yield tested to populate four international nurseries, targeted to high yield environments (2nd and 3rd WYCYT) for yield potential, and heat stressed environments (2nd and 4th SATYN) for climate resilience, respectively. Each nursery was grown as multi-location yield trials. Genetic gains were achieved in both temperate and hot environments, with most new PT-derived lines expressing superior yield and biomass compared to local checks at almost all international sites. Furthermore, the tendency across all four nurseries indicated either the superiority of the best new PT lines compared with the CIMMYT elite checks, or the superiority of all new PT lines as a group compared with all checks, and in some cases, both. Results support—in a realistic breeding context—the hypothesis that yield and radiation use efficiency can be increased by improving source:sink balance, and validate the feasibility of incorporating exotic germplasm into mainstream breeding efforts to accelerate genetic gains for yield potential and climate resilience.

Scientific Reports 6: Article number: 23092; published online: 15 March 2016; updated: 20 May 2016. Mark Ellis was omitted from the author list in the original version of this Article. In addition, there was a typographical error in the spelling of the author Kai Sonder which was incorrectly given as Kai Sonders.

Climate change and slow yield gains pose a major threat to global wheat production. Underutilized genetic resources including landraces and wild relatives are key elements for developing high-yielding and climate-resilient wheat varieties. Landraces introduced into Mexico from Europe, also known as Creole wheats, are adapted to a wide range of climatic regimes and represent a unique genetic resource. Eight thousand four hundred and sixteen wheat landraces representing all dimensions of Mexico were characterized through genotyping-by-sequencing technology. Results revealed sub-groups adapted to specific environments of Mexico. Broadly, accessions from north and south of Mexico showed considerable genetic differentiation. However, a large percentage of landrace accessions were genetically very close, although belonged to different regions most likely due to the recent (nearly five centuries before) introduction of wheat in Mexico. Some of the groups adapted to extreme environments and accumulated high number of rare alleles. Core reference sets were assembled simultaneously using multiple variables, capturing 89% of the rare alleles present in the complete set. Genetic information about Mexican wheat landraces and core reference set can be effectively utilized in next generation wheat varietal improvement.

Realistic experimental protocols to screen for drought adaptation in controlled conditions are crucial if high throughput phenotyping is to be used for the identification of high performance lines, and is especially important in the evaluation of transgenes where stringent biosecurity measures restrict the frequency of open field trials. Transgenic DREB1A-wheat events were selected under greenhouse conditions by evaluating survival and recovery under severe drought (SURV) as well as for water use efficiency (WUE). Greenhouse experiments confirmed the advantages of transgenic events in recovery after severe water stress. Under field conditions, the group of transgenic lines did not generally outperform the controls in terms of grain yield under water deficit. However, the events selected for WUE were identified as lines that combine an acceptable yield-even higher yield (WUE-11) under well irrigated conditions-and stable performance across the different environments generated by the experimental treatments.

While canopy temperature (CT) shows a strong and reliable association with yield under drought and heat stress and is used in wheat breeding to select for yield, little is known of its genetic control. The objective of this study was to determine the gene action controlling CT in five wheat populations grown in diverse environments (heat, drought, and well-irrigated conditions). CT showed negative phenotypic correlations with grain yield under drought and well-irrigated environments. Additive x additive effects were most prevalent and significant for all crosses and environments. Dominance and dominance x dominance gene actions were also found, though the significance and direction was specific for each environment and genotypic cross. The use of CT as a selection criterion to improve tolerance to drought was supported by its significant association with grain yield and the genotype differences observed between cultivars. Our results indicated that genetic gains for CT in wheat could be achieved through conventional breeding. However, given some dominance and epistatic effects, it would be necessary to delay the selection process until the frequency of heterozygous loci within families is reduced.

The production of hard white winter (HWW) wheats (Triticum aestivum L.) with acceptable protein content and quality over different environments requires the correct combination of genotypes and management practices. The objectives of this study were to evaluate moisture deficit and N management on grain protein and quality of seven HWW and two soft white winter (SWW) genotypes, and to identify genotypes and traits that minimize grain quality variability. Plots were irrigated during grain fill to replace from 100 to

The combined problems of climate change, population growth, and increased demands on a declining natural resource base force scientists to push crop performance to its limits. A powerful strategy is to explore genetic resources to identify promising material that can be used directly in breeding, for gene discovery, and to further understand the mechanisms of adaptation. Initially traits must be defined for stress targets using conceptual models, examples being better root systems to access subsoil deep water and the ability to store and remobilize water soluble carbohydrates from storage tissue. New sources of diversity for such traits can be found in collections such as the World Wheat Collection housed at CIMMYT; for example, Mexican landraces provide good sources of both of these traits. Being a polyploid, wheat has a useful secondary gene pool that can be used to re-synthesize hexaploid wheat, while transgenic approaches remove all taxonomic limits to plant improvement. To efficiently explore genetic resources, for crop improvement and to identify genetic and mechanistic bases, requires high throughput phenotyping approaches. For example, an airborne remote sensing platforms is used to determine spectral indices associated with temperature, water content, and pigment composition of leaves via thermal and multispectral imagery. Using the above approaches, best lines are used directly in pre-breeding to combine favorable combinations of traits and their alleles. These approaches have already delivered a new generation of drought adapted lines where cumulative gene action on yield is observed through strategic combination of stress adaptive traits many coming from landraces or products of wide crossing with wheat wild relatives.

Se ha demostrado que Stipa clarazii tiene una mayor tolerancia a la defoliación y capacidad competitiva que S. tenuis y S. ambigua, 3 especies de gramíneas perennes nativas en los pastizales naturales semiáridos del centro de Argentina. Los mecanismos que contribuyen a determinar su mayor tolerancia a la defoliación y capacidad competitiva, sin embargo, todavia no se han investigado. Se examinaron la tolerancia a la defoliación y las tasas de absorción de amonio en plantas defoliadas y no defoliadas de estas especies a 10, 25, y 50 ppm NH4 + usando soluciones de ( NH4)2 SO4 que contenian un enriquecimiento de 15 N del 60%. A mediados de primavera, una mayor producción de rebrote luego de la defoliación en S. clarazii que en S. tenuis y S. ambigua indicó una mayor tolerancia a la defoliación en la primera que en las otras dos especies. Stipa clarazii tuvo tasas de absorción de amonio similares o superiores, pero no menores, que S. tenuis y S. ambigua. Mayores tasas de absorción de amonio parecen ser uno de los mecanismos que contribuyen a determinar la mayor capacidad competitiva y tolerancia a la defoliación en Stipa clarazii que en las otras dos especies. Las plantas defoliadas de las tres especies tuvieron tasas de absorción de amonio similares o mayores que las plantas no defoliadas. Estos resultados sugieren que la restitución de la superficie fotosintetica se puede obtener sin sacrificar la función radical en estas especies, siempre y cuando las reservas de carbon no sean un factor limitante. Las tasas de absorcion de amonio fueron mayores cuando se incremento la concentración de NH4 + en las soluciones marcadas en Stipa clarazii, S. tenuis y S. ambigua. Este resultado demuestra la capacidad. del sistema radical para incrementar la adquisición de nutrientesdurante periodos de alta disponibilidad de recursos. Stipa clarazii, Ball. has been shown to be more tolerant to defoliation and a superior competitor to S. tenuis Philo and S. ambigua Speg. 3 perennial grasses native to semiarid rangelands in central Argentina. Mechanisms contributing to its great defoliation tolerance and competitive ability, however, are largely unexplored. We examined tolerance to defoliation and ammonium uptake rates on defoliated and undefoliated plants of those species at 10, 25, and 50 ppm NH4 + using ( NH4)2 SO4 solutions containing 60 atom %15 N excess. By mid-spring, greater regrowth following defoliation in S. clarazii than in S. tenuis or S. ambigua indicated greater defoliation tolerance in the first than in the other 2 species. Stipa clarazii had similar of higher ammonium uptake rates than S. tenuis and S. ambigua. Higher ammonium uptake rates in S. clarazii thus appear to be one of the mechanisms most likely contributing to its greater competitive ability and defoliation tolerance when compared to the other 2 species. Defoliated plants of all 3 species had similar or greater ammonium uptake rates than undefoliated plants. These results suggest that photosynthetic canopy reestablishment may be achieved without sacrificing root function in these perennial grasses, at least as long as carbon reserves do not become a limiting factor. Ammonium uptake rates increased when NH4 + concentrations increased in the labeled solutions in S. clarazii, S. tenuis and S. ambigua. This result demonstrates the capacity of the root system for increasing nutrient acquisition during periods of high resource availability. Fil: Saint Pierre, Carolina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; Argentina Fil: Busso, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Centro de Recursos Naturales Renovables de la Zona Semiárida. Universidad Nacional del Sur. Centro de Recursos Naturales Renovables de la Zona Semiárida; Argentina Fil: Montenegro, Oscar Alberto. Provincia de Buenos Aires. Ministerio de Asuntos Agrarios. Chacra Experimental de Patagones; Argentina Fil: Rodriguez, Gustavo Dionisio. Provincia de Buenos Aires. Ministerio de Asuntos Agrarios. Chacra Experimental de Patagones; Argentina Fil: Giorgetti, Hugo Dosindo. Provincia de Buenos Aires. Ministerio de Asuntos Agrarios. Chacra Experimental de Patagones; Argentina Fil: Montani, Tomás. Universidad Nacional del Sur. Departamento de Agronomía; Argentina Fil: Bravo, Oscar Abel. Universidad Nacional del Sur. Departamento de Agronomía; Argentina

Stipa clarazii, Ball. has been shown to be more tolerant to defoliation and a superior competitor to S. tenuis Philo and S. ambigua Speg. 3 perennial grasses native to semiarid rangelands in central Argentina. Mechanisms contributing to its great defoliation tolerance and competitive ability, however, are largely unexplored. We examined tolerance to defoliation and ammonium uptake rates on defoliated and undefoliated plants of those species at 10, 25, and 50 ppm NH4+ using (NH4)2SO4 solutions containing 60 atom %15N excess. By mid-spring, greater regrowth following defoliation in S. clarazii than in S. tenuis or S. ambigua indicated greater defoliation tolerance in the first than in the other 2 species. Stipa clarazii had similar of higher ammonium uptake rates than S. tenuis and S. ambigua. Higher ammonium uptake rates in S. clarazii thus appear to be one of the mechanisms most likely contributing to its greater competitive ability and defoliation tolerance when compared to the other 2 species. Defoliated plants of all 3 species had similar or greater ammonium uptake rates than undefoliated plants. These results suggest that photosynthetic canopy reestablishment may be achieved without sacrificing root function in these perennial grasses, at least as long as carbon reserves do not become a limiting factor. Ammonium uptake rates increased when NH4+ concentrations increased in the labeled solutions in S. clarazii, S. tenuis and S. ambigua. This result demonstrates the capacity of the root system for increasing nutrient acquisition during periods of high resource availability.

While genetic resources provide an invaluable gene pool for crop breeding, the majority of accessions in germplasm collections remain uncharacterized and their potential to improve stress adaptation is not quantified. A selection of 25 elite genetic resources for wheat (Triticum aestivum L.) were characterized for agronomic and physiological trait expression in drought- and heat-stessed environments. Under drought, the physiological traits best associated with yield were canopy temperature, associated with water uptake, und carbon isotope discrimination, associated with transpiration efficiency. Under heat stress stomatal conductance, leaf chlorophyll content, and canopy temperature (associated with radiation use efficiency in this environment) were well correlated with yield. Theoretical yield gains based on extrapolating the best trait expression to the highest yielding backgrounds were also estimated. Under drought, the best expression of canopy temperature and carbon isotope discrimination suggested petential yield gains of approximately 10 and 9% above the best yielding cultivars, respectively; under heat stress, canopy temperature and remobilization of stem carbohydrates suggested potential yield gains of approximately 7 and 9%, respectively. Other physiological trait expression was associated with potential yield gains to varying degrees. When considering agronomic traits, the best expression of harvest index suggested yield gains of approximately 14 and 24% in drought and hot environments, respectively, while the combined best expression of both harvest index and final aboveground biomass suggested yield gains of 30 and 34%, respectively. Principal component analysis indicated that mass were not strongly associated with each other, suggesting potential cumulative gene action for yield if traits were combined. When comparing trait expression across drought and hot environments, several physiological traits (e.g., canopy temperature) showed closer association with each other than did performance traits, supporting the idea that such stress-adaptive traits have genetic value across stresses.